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Ma X, Räisänen SE, Garcia-Ascolani ME, Bobkov M, He T, Islam MZ, Li Y, Peng R, Reichenbach M, Serviento AM, Soussan E, Sun X, Wang K, Yang S, Zeng Z, Niu M. Effects of 3-nitrooxypropanol (3-NOP, Bovaer®10) and whole cottonseed on milk production and enteric methane emissions from dairy cows under Swiss management conditions. J Dairy Sci 2024:S0022-0302(24)00801-4. [PMID: 38762115 DOI: 10.3168/jds.2023-24460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/29/2024] [Indexed: 05/20/2024]
Abstract
The objective of this study was to determine the potential effect and interaction of 3- nitrooxypropanol (3-NOP; Bovaer®) and whole cottonseed (WCS) on lactational performance, and enteric methane (CH4) emission of dairy cows. A total of 16 multiparous cows, including 8 Holstein Friesian (HF) and 8 Brown Swiss (BS) [224 ± 36 d in milk, 26 ± 3.7 kg milk yield], were used in a split-plot design, where the main plot was the breed of cows. Within each subplot, cows were randomly assigned to a treatment sequence in a replicated 4 × 4 Latin Square design with 2 × 2 factorial arrangements of treatments with 4, 24-d periods. The experimental treatments were: 1) Control (basal TMR), 2) 3-NOP (60 mg/kg TMR DM), 3) WCS (5% TMR DM), and 4) 3-NOP + WCS. The treatment diets were balanced for ether extract, crude protein, and NDF contents (4%, 16%, and 43% of TMR DM, respectively). The basal diets were fed twice daily at 0800 and 1800 h. Dry matter intake (DMI) and milk yield were measured daily, and enteric gas emissions were measured (using the GreenFeed system) during the last 3 d of each 24-d experimental period when animals were housed in tie stalls. There was no difference in DMI on treatment level, whereas the WCS treatment increased ECM yield and milk fat yield. There was no interaction of 3-NOP and WCS for any of the enteric gas emission parameters, but 3-NOP decreased CH4 production (g/d), CH4 yield (g/kg DMI), and CH4 intensity (g/kg ECM) by 13, 14 and 13%, respectively. Further, an unexpected interaction of breed by 3-NOP was observed for different enteric CH4 emission metrics: HF cows had a greater CH4 mitigation effect compared with BS cows for CH4 production (g/d; 18 vs. 8%), CH4 intensity (g/kg MY; 19% vs. 3%) and CH4 intensity (g/kg ECM; 19 vs. 4%). Hydrogen production was increased by 2.85 folds in HF and 1.53 folds in BS cows receiving 3-NOP. Further, there was a 3-NOP ' Time interaction for both breeds. In BS cows, 3-NOP tended to reduce CH4 production by 18% at around 4 h after morning feeding but no effect was observed at other time points. In HF cows, the greatest mitigation effect of 3-NOP (29.6%) was observed immediately after morning feeding and it persisted at around 23% to 26% for 10 h until the second feed provision, and 3 h thereafter, in the evening. In conclusion, supplementing 3-NOP at 60 mg/kg DM to a high fiber diet resulted in 18 to 19% reduction in enteric CH4 emission in Swiss Holstein Friesian cows. The lower response to 3-NOP by BS cows was unexpected and has not been observed in other studies. These results should be interpreted with caution due to low number of cows per breed. Lastly, supplementing WCS at 5% of DM improved ECM and milk fat yield but did not enhance CH4 inhibition effect of 3-NOP of dairy cows.
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Affiliation(s)
- X Ma
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - S E Räisänen
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - M E Garcia-Ascolani
- Nestlé Institute of Agricultural Sciences, Société des Produits Nestlé S. A., Lausanne, Switzerland
| | - M Bobkov
- Nestlé Institute of Agricultural Sciences, Société des Produits Nestlé S. A., Lausanne, Switzerland
| | - T He
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - M Z Islam
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - Y Li
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - R Peng
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - M Reichenbach
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - A M Serviento
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - E Soussan
- Nestlé Institute of Agricultural Sciences, Société des Produits Nestlé S. A., Lausanne, Switzerland
| | - X Sun
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - K Wang
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - S Yang
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - Z Zeng
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - M Niu
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland.
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Xue B, Jian X, Peng L, Wu C, Fahira A, Syed AAS, Xia D, Wang B, Niu M, Jiang Y, Ding Y, Gao C, Zhao X, Zhang Q, Shi Y, Li Z. Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders. Sleep Med 2024; 119:201-209. [PMID: 38703603 DOI: 10.1016/j.sleep.2024.04.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/14/2024] [Accepted: 04/24/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated. METHODS Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways. RESULTS LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships. CONCLUSIONS This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.
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Affiliation(s)
- Baiqiang Xue
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Public Health, Qingdao University, Qingdao, China
| | - Xuemin Jian
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China.
| | - Lixia Peng
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Pharmacy, Qingdao University, Qingdao, 266003, China
| | - Chuanhong Wu
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Basic Medicine, Qingdao University, Qingdao, 266003, China
| | - Aamir Fahira
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Ali Alamdar Shah Syed
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Disong Xia
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Baokun Wang
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Pharmacy, Qingdao University, Qingdao, 266003, China
| | - Mingming Niu
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Public Health, Qingdao University, Qingdao, China
| | - Yajie Jiang
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Public Health, Qingdao University, Qingdao, China
| | - Yonghe Ding
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Public Health, Qingdao University, Qingdao, China
| | - Chengwen Gao
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China
| | - Xiangzhong Zhao
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China
| | - Qian Zhang
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China
| | - Yongyong Shi
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China; School of Basic Medicine, Qingdao University, Qingdao, 266003, China; Shanghai Clinical Research Center for Mental Health, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Shandong Provincial Key Laboratory of Metabolic Disease & the Metabolic Disease Institute of Qingdao University, Qingdao, 266003, China; Institute of Social Cognitive and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, 200030, China; Institute of Neuropsychiatric Science and Systems Biological Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China; Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, 200030, China; Department of Psychiatry, the First Teaching Hospital of Xinjiang Medical University, Urumqi, 830054, China; Changning Mental Health Center, Shanghai, 200042, China.
| | - Zhiqiang Li
- The Affiliated Hospital of Qingdao University, The Biomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao, 266003, China; School of Public Health, Qingdao University, Qingdao, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), the Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, China; School of Pharmacy, Qingdao University, Qingdao, 266003, China; School of Basic Medicine, Qingdao University, Qingdao, 266003, China; Shanghai Clinical Research Center for Mental Health, Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Shandong Provincial Key Laboratory of Metabolic Disease & the Metabolic Disease Institute of Qingdao University, Qingdao, 266003, China; Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, 200030, China.
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Du K, Liu Y, Zhang L, Peng L, Dong W, Jiang Y, Niu M, Sun Y, Wu C, Niu Y, Ding Y. Lapatinib combined with doxorubicin causes dose-dependent cardiotoxicity partially through activating the p38MAPK signaling pathway in zebrafish embryos. Biomed Pharmacother 2024; 175:116637. [PMID: 38653111 DOI: 10.1016/j.biopha.2024.116637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/09/2024] [Accepted: 04/19/2024] [Indexed: 04/25/2024] Open
Abstract
Because of its enhanced antitumor efficacy, lapatinib (LAP) is commonly used clinically in combination with the anthracycline drug doxorubicin (DOX) to treat metastatic breast cancer. While it is well recognized that this combination chemotherapy can lead to an increased risk of cardiotoxicity in adult women, its potential cardiotoxicity in the fetus during pregnancy remains understudied. Here, we aimed to examine the combination of LAP chemotherapy and DOX-induced cardiotoxicity in the fetus using a zebrafish embryonic system and investigate the underlying pathologic mechanisms. First, we examined the dose-dependent cardiotoxicity of combined LAP and DOX exposure in zebrafish embryos, which mostly manifested as pericardial edema, bradycardia, cardiac function decline and reduced survival. Second, we revealed that a significant increase in oxidative stress concurrent with activated MAPK signaling, as indicated by increased protein expression of phosphorylated p38 and Jnk, was a notable pathophysiological event after combined LAP and DOX exposure. Third, we showed that inhibiting MAPK signaling by pharmacological treatment with the p38MAPK inhibitor SB203580 or genetic ablation of the map2k6 gene could significantly alleviate combined LAP and DOX exposure-induced cardiotoxicity. Thus, we provided both pharmacologic and genetic evidence to suggest that inhibiting MAPK signaling could exert cardioprotective effects. These findings have implications for understanding the potential cardiotoxicity induced by LAP and DOX combinational chemotherapy in the fetus during pregnancy, which could be leveraged for the development of new therapeutic strategies.
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Affiliation(s)
- Ke Du
- School of Public Health, Qingdao University, Qingdao 266021, China; The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Yuting Liu
- School of Public Health, Qingdao University, Qingdao 266021, China; The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Lu Zhang
- Department of Clinical Laboratory, Qingdao Women's and Children's Hospital, Qingdao 266034, China
| | - Lixia Peng
- The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Wenjing Dong
- The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Yajie Jiang
- School of Public Health, Qingdao University, Qingdao 266021, China; The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Mingming Niu
- School of Public Health, Qingdao University, Qingdao 266021, China; The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Yuanchao Sun
- The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Chuanhong Wu
- The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Yujuan Niu
- The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China
| | - Yonghe Ding
- School of Public Health, Qingdao University, Qingdao 266021, China; The Biomedical Sciences Institute of the Affiliated Hospital, Qingdao University, Qingdao 266021, China; Department of Biochemistry and Molecular Biology, Division of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
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4
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Jiang X, Niu M, Qin K, Hu Y, Li Y, Che C, Wang C, Mu C, Wang H. Enhancement of Nutrient Composition and Non-Volatile Flavor Substances in Muscle Tissue of Red Drum ( Sciaenops ocellatus) Through Inland Low Salinity Saline-Alkaline Water Culture. J Agric Food Chem 2024; 72:7326-7335. [PMID: 38507568 DOI: 10.1021/acs.jafc.3c08717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
The red drum (Sciaenops ocellatus), a globally significant marine aquaculture species, boasts formidable osmoregulatory capabilities and remarkable adaptability to low salinity, making it an ideal candidate for commercial cultivation in inland low salinity saline-alkaline waters. However, studies on the fundamental nutritional composition and flavor quality of S. ocellatus in these inland low salinity saline-alkaline waters remain unreported. This study delves into the impact of inland low salinity saline-alkaline environments on the basic nutritional components and nonvolatile flavor substances (including free amino acids and free nucleotides) in the muscle tissue of S. ocellatus. The findings reveal that redfish cultivated in these conditions exhibit a significant increase in the crude fat, ash, and protein content in their dorsal muscle tissue, coupled with a decrease in moisture content (p < 0.05), indicating an enhancement in the nutritional value of the dorsal muscle tissue. Furthermore, this cultivation environment significantly elevates the content of free amino acids in the muscle tissue (p < 0.05), particularly those contributing to umami and sweet tastes, while reducing the relative content of bitter amino acids. Although the total content of free nucleotides decreased, the equivalent umami concentration (EUC) in the muscle tissue markedly increased (p < 0.05) due to the synergistic effect of umami amino acids and flavor nucleotides, enhancing the umami taste characteristics. Therefore, inland low salinity saline-alkaline aquaculture not only elevates the nutritional value of S. ocellatus muscle tissue but also improves its umami flavor characteristics. This discovery opens new perspectives for further research into the impact of inland low salinity saline-alkaline environments on the flavor properties of marine animals.
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Affiliation(s)
- Xiaosong Jiang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Mingming Niu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Kangxiang Qin
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Yun Hu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Yuntao Li
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Chenxi Che
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Chunlin Wang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
- Key Laboratory of Aquacultral Biotechnology Ministry of Education, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Changkao Mu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
- Key Laboratory of Aquacultral Biotechnology Ministry of Education, Ningbo University, Ningbo, Zhejiang 315211, China
| | - Huan Wang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang 315211, China
- Key Laboratory of Aquacultral Biotechnology Ministry of Education, Ningbo University, Ningbo, Zhejiang 315211, China
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Islam MZ, Räisänen SE, Schudel A, Wang K, He T, Kunz C, Li Y, Ma X, Serviento AM, Zeng Z, Wahl F, Zenobi R, Giannoukos S, Niu M. Exhalomics as a noninvasive method for assessing rumen fermentation in dairy cows: Can exhaled-breath metabolomics replace rumen sampling? J Dairy Sci 2024; 107:2099-2110. [PMID: 37949405 DOI: 10.3168/jds.2023-24124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 10/20/2023] [Indexed: 11/12/2023]
Abstract
Previously, we used secondary electrospray ionization-mass spectrometry (SESI-MS) to investigate the diurnal patterns and signal intensities of exhaled (EX) volatile fatty acids (VFA) of dairy cows. The current study aimed to validate the potential of an exhalomics approach for evaluating rumen fermentation. The experiment was conducted in a switchback design, with 3 periods of 9 d each, including 7 d for adaptation and 2 d for sampling. Four rumen-cannulated original Swiss Brown (Braunvieh) cows were randomly assigned to 1 of 2 diet sequences (ABA or BAB): (A) low starch (LS; 6.31% starch on a dry matter basis) and (B) high starch (HS; 16.2% starch on a dry matter basis). Feeding was once per day at 0830 h. Exhalome (with the GreenFeed System), and rumen samples were collected 8 times to represent every 3 h of a day, and EX-VFA and ruminal (RM)-VFA were analyzed using SESI-MS and HPLC, respectively. Furthermore, the VFA concentration in the gas phase (HR-VFA) was predicted based on RM-VFA and Henry's Law (HR) constants. No interactions were identified between the types of diets (HS vs. LS) and the measurement methods on daily average VFA profiles (RM vs. EX or HR vs. EX), suggesting a consistent performance among the methods. Additionally, when the 3-h interval VFA data from HS and LS diets were analyzed separately, no interactions were observed between methods and time of day, indicating that the relative daily pattern of VFA molar proportions was similar regardless of the VFA measurement method used. The results revealed that the levels of acetate sharply increased immediately after feeding, trailed by an increase in the acetate:propionate ratio and a steady increase for propionate (2 h after feeding the HS diet, 4 h for LS), and butyrate. This change was more pronounced for the HS diet than the LS diet. However, there was no overall diet effect on the VFA molar proportions, although the measurement methods affected the molar proportions. Furthermore, we observed a strong positive correlation between the levels of RM and EX acetate for both diets (HS: r = 0.84; LS: r = 0.85), RM and EX propionate (r = 0.74), and RM and EX acetate:propionate ratio (r = 0.80). Both EX-VFA and RM-VFA exhibited similar responses to feeding and dietary treatments, suggesting that EX-VFA could serve as a useful proxy for characterizing RM-VFA molar proportions to evaluate rumen fermentation. Similar relationships were observed between RM-VFA and HR-VFA. In conclusion, this study underscores the potential of exhalomics as a reliable approach for assessing rumen fermentation. Moving forward, research should further explore the depth of exhalomics in ruminant studies to provide a comprehensive insight into rumen fermentation metabolites, especially across diverse dietary conditions.
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Affiliation(s)
- M Z Islam
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - S E Räisänen
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - A Schudel
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - K Wang
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - T He
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - C Kunz
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - Y Li
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - X Ma
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - A M Serviento
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - Z Zeng
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland
| | - F Wahl
- Food Microbial Systems Research Division, Agroscope, 3003 Bern, Switzerland
| | - R Zenobi
- Department of Chemistry and Applied Biosciences, Analytical Chemistry, ETH Zürich, 8093 Zürich, Switzerland
| | - S Giannoukos
- Department of Chemistry and Applied Biosciences, Analytical Chemistry, ETH Zürich, 8093 Zürich, Switzerland.
| | - M Niu
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, 8092 Zürich, Switzerland.
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Wang K, Ruiz-González A, Räisänen SE, Ouellet V, Boucher A, Rico DE, Niu M. Dietary supplementation of vitamin D 3 and calcium partially recover the compromised time budget and circadian rhythm of lying behavior in lactating cows under heat stress. J Dairy Sci 2024; 107:1707-1718. [PMID: 37863290 DOI: 10.3168/jds.2023-23589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 09/28/2023] [Indexed: 10/22/2023]
Abstract
Heat stress (HS) impedes cattle behavior and performance and is an animal comfort and welfare issue. The objective of this study was to characterize the time budget and circadian rhythm of lying behavior in dairy cows during HS and to assess the effect of dietary supplementation of vitamin D3 and Ca. Twelve multiparous Holstein cows (42.2 ± 5.6 kg milk/d; 83 ± 27 d in milk) housed in tiestalls were used in a split-plot design with the concentration of dietary vitamin E and Se as main plots (LESe: 11.1 IU/kg and 0.55 mg/kg, and HESe: 223 IU/kg and 1.8 mg/kg, respectively). Within each plot cows were randomly assigned to (1) HS with low concentrations of vitamin D3 and Ca (HS, 1,012 IU/kg and 0.73%, respectively), (2) HS with high concentrations of vitamin D3 and Ca (HS+D3/Ca; 3,764 IU/kg and 0.97%, respectively), or (3) thermoneutral pair-fed (TNPF) with low concentrations of vitamin D3 and Ca (1,012 IU/kg and 0.73%, respectively) in a Latin square design with 14-d periods and 7-d washouts. Lying behavior was measured with HOBO Loggers in 15-min intervals. Overall, cows in HS spent less time lying per day relative to TNPF from d 7 to 14. Daily lying time was positively correlated with milk yield, energy-corrected milk yield, and feed efficiency, and was negatively correlated with rectal temperature, respiratory rate, fecal calprotectin, tumor necrosis factor-α, and C-reactive protein. A treatment by time interaction was observed for lying behavior: the time spent lying was lesser for cows in HS than in TNPF in the early morning (0000-0600 h) and in the night (1800-2400 h). The circadian rhythm of lying behavior was characterized by fitting a cosine function of time into linear mixed model. Daily rhythmicity of lying was detected for cows in TNPF and HS+D3/Ca, whereas only a tendency in HS cows was observed. Cows in TNPF had the highest mesor (the average level of diurnal fluctuations; 34.2 min/h) and amplitude (the distance between the peak and mesor; 17.9 min/h). Both the mesor and amplitude were higher in HS+D3/Ca relative to HS (26.6 vs. 25.2 min/h and 3.91 min/h vs. 2.18 min/h, respectively). The acrophase (time of the peak) of lying time in TNPF, HS, and HS+D3/Ca were 0028, 0152, and 0054 h, respectively. Lastly, a continuous increase in daily lying time in TNPF was observed during the first 4 d of the experimental period in which DMI was gradually restricted, suggesting that intake restrictions may shift feeding behavior and introduce biases in the behavior of animals. In conclusion, lying behavior was compromised in dairy cows under HS, characterizing reduced daily lying time and disrupted circadian rhythms, and the compromised lying behavior can be partially restored by supplementation of vitamin D3 and Ca. Further research may be required for a more suitable model to study behavior of cows under HS.
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Affiliation(s)
- K Wang
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - A Ruiz-González
- Centre de Recherche en Sciences Animales de Deschambault (CRSAD), Deschambault, QC, G0A 1S0, Canada; Département des Sciences Animales, Université Laval, Québec, QC, G1V 0A6, Canada
| | - S E Räisänen
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland
| | - V Ouellet
- Département des Sciences Animales, Université Laval, Québec, QC, G1V 0A6, Canada
| | - A Boucher
- Département des Sciences Animales, Université Laval, Québec, QC, G1V 0A6, Canada
| | - D E Rico
- Centre de Recherche en Sciences Animales de Deschambault (CRSAD), Deschambault, QC, G0A 1S0, Canada.
| | - M Niu
- Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zürich, Zürich 8092, Switzerland.
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7
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Zhang Z, Cheng J, Hou J, Niu M, Gao Y, Xu J, Zheng Q, Ji K, Zhang M, Hao T, Li N, Han X, Ma X, Kong J, Wang R, Zhao Y, Tian J, Hu X. Discrepancies in breast cancer guideline recommendations despite similar Cochrane systematic review conclusions. J Evid Based Med 2024; 17:17-25. [PMID: 38459781 DOI: 10.1111/jebm.12581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 01/03/2024] [Indexed: 03/10/2024]
Abstract
AIM This study aims to describe the citation patterns of Cochrane systematic reviews (CSR) in guidelines for managing breast cancer. METHODS We searched for systematic reviews on breast cancer in The Cochrane Library from the date of inception to November 15, 2023, and identified guidelines that cited them. We described how systematic reviews were cited by the guidelines in each database and each year. Additionally, we presented the relationships between the conclusions of the systematic reviews and guideline recommendations and compared the consistency of the recommendations on the same topic across different guidelines. RESULTS A total of 64 systematic reviews and 228 guidelines were included in this study. The average number of the 64 systematic reviews cited by the guidelines was 5.91. We found that the guideline recommendations were irrelevant or inconsistent with the conclusions of the systematic reviews in 56 (38.36%) cited entries. We grouped recommendations on the same topic across different guidelines into one group, of which only 5 groups (15.15%) had completely consistent recommendations, and the other 28 groups (84.85%) had inconsistent recommendations. CONCLUSION The average number of citations for CSR on breast cancer in the guidelines was 5.91. There were also situations in which the guideline recommendations were inconsistent with the conclusions of the included systematic reviews, and recommendations on the same topic across different guidelines were inconsistent.
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Affiliation(s)
- Zhigang Zhang
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Jie Cheng
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- Nursing Department, Changzhi People's Hospital, Changzhi, China
| | - Jialu Hou
- Nursing Department, Changzhi People's Hospital, Changzhi, China
| | - Mingming Niu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Ya Gao
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Jianguo Xu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Qingyong Zheng
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Kexin Ji
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Min Zhang
- Nursing Department, Changzhi People's Hospital, Changzhi, China
| | - Tian Hao
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Ning Li
- Nursing Department, Changzhi People's Hospital, Changzhi, China
| | - Xinyi Han
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Xiujuan Ma
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Jiajia Kong
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Rui Wang
- Intensive Care Units, Lanzhou University First Affiliated Hospital, Lanzhou, China
- School of Nursing, Lanzhou University, Lanzhou, China
| | - Ye Zhao
- Departments of Biochemistry and Molecular Biology, Melvin and Bren Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- First Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Xiaofang Hu
- Nursing Department, Changzhi People's Hospital, Changzhi, China
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8
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Wang JT, Li L, Niu M, Zhu QL, Zhao ZW, Kotani K, Yamamoto A, Zhang HJ, Li SX, Xu D, Kang N, Li XG, Zhang KP, Sun J, Wu FZ, Zhang HL, Liu DX, Lyu MH, Ji JS, Kawada N, Xu K, Qi XL. [HVPG minimally invasive era: exploration based on forearm venous approach]. Zhonghua Gan Zang Bing Za Zhi 2024; 32:35-39. [PMID: 38320789 DOI: 10.3760/cma.j.cn501113-20231220-00289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Objective: The transjugular or transfemoral approach is used as a common method for hepatic venous pressure gradient (HVPG) measurement in current practice. This study aims to confirm the safety and effectiveness of measuring HVPG via the forearm venous approach. Methods: Prospective recruitment was conducted for patients with cirrhosis who underwent HVPG measurement via the forearm venous approach at six hospitals in China and Japan from September 2020 to December 2020. Patients' clinical baseline information and HVPG measurement data were collected. The right median cubital vein or basilic vein approach for all enrolled patients was selected. The HVPG standard process was used to measure pressure. Research data were analyzed using SPSS 22.0 statistical software. Quantitative data were used to represent medians (interquartile ranges), while qualitative data were used to represent frequency and rates. The correlation between two sets of data was analyzed using Pearson correlation analysis. Results: A total of 43 cases were enrolled in this study. Of these, 41 (95.3%) successfully underwent HVPG measurement via the forearm venous approach. None of the patients had any serious complications. The median operation time for HVPG detection via forearm vein was 18.0 minutes (12.3~38.8 minutes). This study confirmed that HVPG was positively closely related to Child-Pugh score (r = 0.47, P = 0.002), albumin-bilirubin score (r = 0.37, P = 0.001), Lok index (r = 0.36, P = 0.02), liver stiffness (r = 0.58, P = 0.01), and spleen stiffness (r = 0.77, P = 0.01), while negatively correlated with albumin (r = -0.42, P = 0.006). Conclusion: The results of this multi-centre retrospective study suggest that HVPG measurement via the forearm venous approach is safe and feasible.
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Affiliation(s)
- J T Wang
- Hebei Province Key Laboratory of Hepatocirrhosis and Portal Hypertension, Xingtai People's Hospital Affiliated to Hebei Medical University, Xingtai 054000, China
| | - L Li
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - M Niu
- Interventional Department, the First Affiliated Hospital of China Medical University, Shenyang 110000, China
| | - Q L Zhu
- Department of Gastroenterology, Affiliated Hospital of Southwest Medical University, Lanzhou 646000, China
| | - Z W Zhao
- Interventional Diagnosis and Treatment Center, Lishui Central Hospital,Lishui 323000, China
| | - K Kotani
- Department of Hepatology, Osaka Municipal University Hospital, Osaka City, Japan
| | - A Yamamoto
- Department of Interventional Radiology, Faculty of Medicine, Osaka City University, Osaka City, Japan
| | - H J Zhang
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - S X Li
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - D Xu
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - N Kang
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - X G Li
- Interventional Department, Lanzhou University First Hospital, Lanzhou 730000, China
| | - K P Zhang
- Hebei Province Key Laboratory of Hepatocirrhosis and Portal Hypertension, Xingtai People's Hospital Affiliated to Hebei Medical University, Xingtai 054000, China
| | - J Sun
- Interventional Department, the First Affiliated Hospital of China Medical University, Shenyang 110000, China
| | - F Z Wu
- Interventional Diagnosis and Treatment Center, Lishui Central Hospital,Lishui 323000, China
| | - H L Zhang
- Interventional Diagnosis and Treatment Center, Lishui Central Hospital,Lishui 323000, China
| | - D X Liu
- Hebei Province Key Laboratory of Hepatocirrhosis and Portal Hypertension, Xingtai People's Hospital Affiliated to Hebei Medical University, Xingtai 054000, China
| | - M H Lyu
- Department of Gastroenterology, Affiliated Hospital of Southwest Medical University, Lanzhou 646000, China
| | - J S Ji
- Interventional Diagnosis and Treatment Center, Lishui Central Hospital,Lishui 323000, China
| | - N Kawada
- Department of Hepatology, Osaka Municipal University Hospital, Osaka City, Japan
| | - K Xu
- Interventional Department, the First Affiliated Hospital of China Medical University, Shenyang 110000, China
| | - X L Qi
- Portal Hypertension Centers, Southeast University Affiliated Zhongda Hospital, Nanjing 210009,China
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9
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Liang Q, Jiang Y, Shieh AW, Zhou D, Chen R, Wang F, Xu M, Niu M, Wang X, Pinto D, Wang Y, Cheng L, Vadukapuram R, Zhang C, Grennan K, Giase G, White KP, Peng J, Li B, Liu C, Chen C, Wang SH. The impact of common variants on gene expression in the human brain: from RNA to protein to schizophrenia risk. bioRxiv 2023:2023.06.04.543603. [PMID: 37873195 PMCID: PMC10592607 DOI: 10.1101/2023.06.04.543603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Background The impact of genetic variants on gene expression has been intensely studied at the transcription level, yielding in valuable insights into the association between genes and the risk of complex disorders, such as schizophrenia (SCZ). However, the downstream impact of these variants and the molecular mechanisms connecting transcription variation to disease risk are not well understood. Results We quantitated ribosome occupancy in prefrontal cortex samples of the BrainGVEX cohort. Together with transcriptomics and proteomics data from the same cohort, we performed cis-Quantitative Trait Locus (QTL) mapping and identified 3,253 expression QTLs (eQTLs), 1,344 ribosome occupancy QTLs (rQTLs), and 657 protein QTLs (pQTLs) out of 7,458 genes quantitated in all three omics types from 185 samples. Of the eQTLs identified, only 34% have their effects propagated to the protein level. Further analysis on the effect size of prefrontal cortex eQTLs identified from an independent dataset showed clear post-transcriptional attenuation of eQTL effects. To investigate the biological relevance of the attenuated eQTLs, we identified 70 expression-specific QTLs (esQTLs), 51 ribosome-occupancy-specific QTLs (rsQTLs), and 107 protein-specific QTLs (psQTLs). Five of these omics-specific QTLs showed strong colocalization with SCZ GWAS signals, three of them are esQTLs. The limited number of GWAS colocalization discoveries from omics-specific QTLs and the apparent prevalence of eQTL attenuation prompted us to take a complementary approach to investigate the functional relevance of attenuated eQTLs. Using S-PrediXcan we identified 74 SCZ risk genes, 34% of which were novel, and 67% of these risk genes were replicated in a MR-Egger test. Notably, 52 out of 74 risk genes were identified using eQTL data and 70% of these SCZ-risk-gene-driving eQTLs show little to no evidence of driving corresponding variations at the protein level. Conclusion The effect of eQTLs on gene expression in the prefrontal cortex is commonly attenuated post-transcriptionally. Many of the attenuated eQTLs still correlate with SCZ GWAS signal. Further investigation is needed to elucidate a mechanistic link between attenuated eQTLs and SCZ disease risk.
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Affiliation(s)
- Qiuman Liang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
| | - Yi Jiang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China
| | - Annie W. Shieh
- Center for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310058, China
- Department of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - Rui Chen
- Department of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - Feiran Wang
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
| | - Meng Xu
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
| | - Mingming Niu
- Department of Structural Biology, Department of Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Xusheng Wang
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Dalila Pinto
- Department of Psychiatry, and Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, and Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yue Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA
| | - Lijun Cheng
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Ramu Vadukapuram
- Department of Psychiatry, The University of Texas Rio Grande Valley, Harlingen, TX 78550, USA
| | - Chunling Zhang
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Kay Grennan
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Gina Giase
- The Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | | | - Kevin P White
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore
| | - Junmin Peng
- Department of Structural Biology, Department of Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - Chunyu Liu
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- School of Psychology, Shaanxi Normal University, Xi’an, Shaanxi 710062, China
| | - Chao Chen
- MOE Key Laboratory of Rare Pediatric Diseases & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
- Furong Laboratory, Changsha, Hunan 410000, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410000, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha, Hunan 410000, China
| | - Sidney H. Wang
- Center for Human Genetics, The Brown foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
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Yan M, Chen L, Yang M, Zhang L, Niu M, Wu F, Chen Y, Song Z, Zhang Y, Li J, Tian J. Evidence mapping of clinical practice guidelines recommendations and quality for depression in children and adolescents. Eur Child Adolesc Psychiatry 2023; 32:2091-2108. [PMID: 35262810 DOI: 10.1007/s00787-022-01958-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 02/06/2022] [Indexed: 02/05/2023]
Abstract
This study systematically reviewed the clinical practice guidelines (CPGs) for depression in children and adolescents and assessed the quality and recommendation consistency of those CPGs. Evidence mapping was presented to illustrate the research trends and identify gaps to guide future research. Literature on CPGs for depression was systematically collected from PubMed, Embase, Web of Science, guideline databases, and psychiatric association/ society websites. The basic information, recommendations, methodological quality, and reporting quality of CPGs were extracted, and the supporting evidence strength for the included CPGs was analyzed in Excel. Four appraisers independently assessed the eligible CPGs using AGREE II instrument and the RIGHT checklist. All recommendations from the CPGs were summarized and analyzed, and the evidence mapping bubble charts were plotted in Excel. After excluding 15,184 records, 12 depression CPGs were eventually proved eligible, six of which were of high quality and six medium quality. A total of 39 major recommendations were summarized, 35 of which were supported by high-quality CPGs. Although direct comparisons are challenging due to differences in grading schemes and research quality, most CPGs share many pivotal recommendations that can help guide clinical practice. However, the evidence for some clinical problems is still lacking. Thus, more research is necessary on the screening and treatment of children and adolescents to put forward more evidence-based and high-quality recommendations.
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Affiliation(s)
- Meili Yan
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
| | - Lingmin Chen
- Department of Anesthesiology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University and The Research Units of West China (2018RU012), Chinese Academy of Medical Sciences, Chengdu, Sichuan, China
| | - Min Yang
- Comprehensive Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Li Zhang
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
- The Third Ward of Cardiovascular Clinical Medical Center, Affiliated Hospital of Gansu University of Chinese Medicine, Lanzhou, Gansu, China
| | - Mingming Niu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
| | - Fangfang Wu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
- Shangluo Vocational and Technical College, Shangluo, Shanxi, China
| | - Yamin Chen
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
| | - Ziwei Song
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China
| | - Yonggang Zhang
- Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, China.
| | - Jinhui Tian
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, Gansu, China.
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou, Gansu, China.
- WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, Gansu, China.
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11
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Islam MZ, Giannoukos S, Räisänen SE, Wang K, Ma X, Wahl F, Zenobi R, Niu M. Exhaled volatile fatty acids, ruminal methane emission, and their diurnal patterns in lactating dairy cows. J Dairy Sci 2023; 106:6849-6859. [PMID: 37210352 DOI: 10.3168/jds.2023-23301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/08/2023] [Indexed: 05/22/2023]
Abstract
To date, the commonly used methods to assess rumen fermentation are invasive. Exhaled breath contains hundreds of volatile organic compounds (VOC) that can reflect animal physiological processes. In the present study, for the first time, we aimed to use a noninvasive metabolomics approach based on high-resolution mass spectrometry to identify rumen fermentation parameters in dairy cows. Enteric methane (CH4) production from 7 lactating cows was measured 8 times over 3 consecutive days using the GreenFeed system (C-Lock Technology Inc.). Simultaneously, exhalome samples were collected in Tedlar gas sampling bags and analyzed offline using a secondary electrospray ionization high-resolution mass spectrometry system. In total, 1,298 features were detected, among them targeted exhaled volatile fatty acids (eVFA; i.e., acetate, propionate, butyrate), which were putatively annotated using their exact mass-to-charge ratio. The intensity of eVFA, in particular acetate, increased immediately after feeding and followed a similar pattern to that observed for ruminal CH4 production. The average total eVFA concentration was 35.5 count per second (CPS), and among the individual eVFA, acetate had the greatest concentration, averaging 21.3 CPS, followed by propionate at 11.5 CPS, and butyrate at 2.67 CPS. Further, exhaled acetate was on average the most abundant of the individual eVFA at around 59.3%, followed by 32.5 and 7.9% of the total eVFA for propionate and butyrate, respectively. This corresponds well with the previously reported proportions of these VFA in the rumen. The diurnal patterns of ruminal CH4 emission and individual eVFA were characterized using a linear mixed model with cosine function fit. The model characterized similar diurnal patterns for eVFA and ruminal CH4 and H2 production. Regarding the diurnal patterns of eVFA, the phase (time of peak) of butyrate occurred first, followed by that of acetate and propionate. Importantly, the phase of total eVFA occurred around 1 h before that of ruminal CH4. This corresponds well with existing data on the relationship between rumen VFA production and CH4 formation. Results from the present study revealed a great potential to assess the rumen fermentation of dairy cows using exhaled metabolites as a noninvasive proxy for rumen VFA. Further validation, with comparisons to rumen fluid, and establishment of the proposed method are required.
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Affiliation(s)
- M Z Islam
- ETH Zürich, Department of Environmental Systems Science, Institute of Agricultural Sciences, 8092 Zürich, Switzerland
| | - S Giannoukos
- ETH Zürich, Department of Chemistry and Applied Biosciences, Analytical Chemistry, 8093 Zürich, Switzerland.
| | - S E Räisänen
- ETH Zürich, Department of Environmental Systems Science, Institute of Agricultural Sciences, 8092 Zürich, Switzerland
| | - K Wang
- ETH Zürich, Department of Environmental Systems Science, Institute of Agricultural Sciences, 8092 Zürich, Switzerland
| | - X Ma
- ETH Zürich, Department of Environmental Systems Science, Institute of Agricultural Sciences, 8092 Zürich, Switzerland
| | - F Wahl
- Food Microbial Systems Research Division, Agroscope, 3003 Bern, Switzerland
| | - R Zenobi
- ETH Zürich, Department of Chemistry and Applied Biosciences, Analytical Chemistry, 8093 Zürich, Switzerland
| | - M Niu
- ETH Zürich, Department of Environmental Systems Science, Institute of Agricultural Sciences, 8092 Zürich, Switzerland.
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12
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Jiang X, Niu M, Qin K, Hu Y, Li Y, Che C, Wang C, Mu C, Wang H. The shared microbiome in mud crab ( Scylla paramamosain) of Sanmen Bay, China: core gut microbiome. Front Microbiol 2023; 14:1243334. [PMID: 37727291 PMCID: PMC10505715 DOI: 10.3389/fmicb.2023.1243334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 08/18/2023] [Indexed: 09/21/2023] Open
Abstract
Introduction The mud crab, Scylla paramamosain, holds great commercial significance as a marine crustacean widely cultivated in the Indo-Pacific region. Understanding the core gut microbiota of aquatic animals is crucial for their overall health and growth, yet the core gut microbiota of mud crab remains poorly characterized. Methods In this study, we gathered gut samples from mud crabs across five locations within Sanmen Bay, China. Through the utilization of high-throughput sequencing, we delved into the composition of the gut microbial community and identified the core gut microbiome of mud crab. Results Our results demonstrate that the gut microbial diversity of mud crab did not exhibit significant variation among the five sampling sites, although there were some differences in community richness. At the phylum level, we identified 35 representative phyla, with Firmicutes, Proteobacteria, Bacteroidota, and Campilobacterota as the dominant phyla. Among the 815 representative genera, we discovered 19 core genera, which accounted for 65.45% of the total sequences. These core genera were distributed across 6 phyla, and among them, Photobacterium exhibited the highest average relative abundance. Discussion Photobacterium has probiotic activity and may play a crucial role in enhancing the immune response of the host and maintaining the diversity of the gut microbiota. Moreover, we observed a positive correlation between the relative abundance of core genera and the stability of the gut microbial community. Furthermore, our findings revealed distinct differences in gut microbial composition and specific taxa between the sexes of mud crab. These differences subsequently influenced the functionality of the gut microbial community. Overall, our investigation sheds light on the core gut microbiota of mud crab, emphasizing the importance of core gut microbial communities in maintaining the health and growth of these commercially significant marine crustaceans.
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Affiliation(s)
- Xiaosong Jiang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Mingming Niu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Kangxiang Qin
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Yun Hu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Yuntao Li
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Chenxi Che
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
| | - Chunlin Wang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
- Key Laboratory of Aquacultral Biotechnology, Ministry of Education, Ningbo University, Ningbo, Zhejiang, China
| | - Changkao Mu
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
- Key Laboratory of Aquacultral Biotechnology, Ministry of Education, Ningbo University, Ningbo, Zhejiang, China
| | - Huan Wang
- School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
- Key Laboratory of Aquacultral Biotechnology, Ministry of Education, Ningbo University, Ningbo, Zhejiang, China
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13
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Zhang MJ, Xu ZK, Zong L, Wang J, Wang B, Qi SM, Wang HN, Niu M, Cui P, Hu WQ. [Research progress in anti-reflux reconstructions and mechanism after proximal gastrectomy]. Zhonghua Wei Chang Wai Ke Za Zhi 2023; 26:499-504. [PMID: 37217358 DOI: 10.3760/cma.j.cn441530-20221227-00547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The electrophysiological activity of the gastrointestinal tract and the mechanical anti-reflux structure of the gastroesophageal junction are the basis of the anti-reflux function of the stomach. Proximal gastrectomy destroys the mechanical structure and normal electrophysiological channels of the anti-reflux. Therefore, the residual gastric function is disordered. Moreover, gastroesophageal reflux is one of the most serious complications. The emergence of various types of anti-reflux surgery through the mechanism of reconstructing mechanical anti-reflux barrier and establishing buffer zone, and the preservation of, the pacing area and vagus nerve of the stomach, the continuity of the jejunal bowel, the original gastroenteric electrophysiological activity of the gastrointestinal tract, and the physiological function of the pyloric sphincter, are all important measures for gastric conservative operations. There are many types of reconstructive approaches after proximal gastrectomy. The design based on the anti-reflux mechanism and the functional reconstruction of mechanical barrier, and the protection of gastrointestinal electrophysiological activities are important considerations for the selected of reconstructive approaches after proximal gastrectomy. In clinical practice, we should consider the principle of individualization and the safety of radical resection of tumor to select a rational reconstructive approaches after proximal gastrectomy.
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Affiliation(s)
- M J Zhang
- Graduate Department of Changzhi Medical College, Changzhi 046000, China
| | - Z K Xu
- Graduate Department of Changzhi Medical College, Changzhi 046000, China
| | - L Zong
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China Department of gastrointestinal Surgery, Changzhi People's Hospital Affiliated to Changzhi Medical College, Changzhi 046000, China
| | - J Wang
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China
| | - B Wang
- Graduate Department of Changzhi Medical College, Changzhi 046000, China
| | - S M Qi
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China
| | - H N Wang
- Graduate Department of Changzhi Medical College, Changzhi 046000, China
| | - M Niu
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China
| | - P Cui
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China Department of gastrointestinal Surgery, Changzhi People's Hospital Affiliated to Changzhi Medical College, Changzhi 046000, China
| | - W Q Hu
- Clinical Medical Research Center for Malignant Tumor (Esophagogastric Junction Cancer) ,Changzhi 046000, China Department of gastrointestinal Surgery, Changzhi People's Hospital Affiliated to Changzhi Medical College, Changzhi 046000, China
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14
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Wang H, Liu C, Xie X, Niu M, Wang Y, Cheng X, Zhang B, Zhang D, Liu M, Sun R, Ma Y, Ma S, Wang H, Zhu G, Lu Y, Huang B, Su P, Chen X, Zhao J, Wang H, Shen L, Fu L, Huang Q, Yang Y, Wang H, Wu C, Ge W, Chen C, Huo Q, Wang Q, Wang Y, Geng L, Xie Y, Xie Y, Liu L, Qi J, Chen H, Wu J, Jiang E, Jiang W, Wang X, Shen Z, Guo T, Zhou J, Zhu P, Cheng T. Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection. Immunity 2023:S1074-7613(23)00224-8. [PMID: 37257450 DOI: 10.1016/j.immuni.2023.05.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/19/2023] [Accepted: 05/11/2023] [Indexed: 06/02/2023]
Abstract
Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.
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Affiliation(s)
- Hong Wang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
| | - Cuicui Liu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Xiaowei Xie
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Mingming Niu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yingrui Wang
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang, China; Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang, China; Center for Infectious Disease Research, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
| | - Xuelian Cheng
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Biao Zhang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Dong Zhang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Mengyao Liu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Rui Sun
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang, China; Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang, China; Center for Infectious Disease Research, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China
| | - Yezi Ma
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Shihui Ma
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Huijun Wang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Guoqing Zhu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yang Lu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Baiming Huang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Pei Su
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Xiaoyuan Chen
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Jingjing Zhao
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Hongtao Wang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Long Shen
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Lixia Fu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Qianqian Huang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Yang Yang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - He Wang
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang, China
| | - Chunlong Wu
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou 310024, China
| | - Weigang Ge
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou 310024, China
| | - Chen Chen
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., Hangzhou 310024, China
| | - Qianyu Huo
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Qingping Wang
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China
| | - Ying Wang
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China
| | - Li Geng
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China
| | - Yan Xie
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China
| | - Yi Xie
- Key Research Laboratory for Infectious Disease Prevention for State Administration of Traditional Chinese Medicine, Tianjin Institute of Respiratory Diseases, Tianjin, China; Tianjin Key Laboratory of Lung Regenerative Medicine, Haihe Hospital, Tianjin University, Tianjin, China
| | - Lijun Liu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Jianwei Qi
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Huaiyong Chen
- Key Research Laboratory for Infectious Disease Prevention for State Administration of Traditional Chinese Medicine, Tianjin Institute of Respiratory Diseases, Tianjin, China; Tianjin Key Laboratory of Lung Regenerative Medicine, Haihe Hospital, Tianjin University, Tianjin, China
| | - Junping Wu
- Department of Tuberculosis, Haihe Hospital, Tianjin University, Tianjin, China; Key Research Laboratory for Infectious Disease Prevention for State Administration of Traditional Chinese Medicine, Tianjin Institute of Respiratory Diseases, Tianjin, China; Tianjin Key Laboratory of Lung Regenerative Medicine, Haihe Hospital, Tianjin University, Tianjin, China
| | - Erlie Jiang
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China
| | - Wentao Jiang
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China
| | - Ximo Wang
- Tianjin Key Laboratory of Lung Regenerative Medicine, Haihe Hospital, Tianjin University, Tianjin, China; Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin, China.
| | - Zhongyang Shen
- Organ Transplant Center, Tianjin First Center Hospital, Tianjin 300192, China; NHC Key Laboratory for Critical Care Medicine, Tianjin First Center Hospital, Tianjin 300192, China; Research Institute of Transplant Medicine, Nankai University, Tianjin 300192, China.
| | - Tiannan Guo
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang, China; Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang, China; Center for Infectious Disease Research, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang, China.
| | - Jiaxi Zhou
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
| | - Ping Zhu
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
| | - Tao Cheng
- Haihe Laboratory of Cell Ecosystem, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China; Tianjin Institutes of Health Science, Tianjin 301600, China.
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15
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Chen PC, Han X, Shaw TI, Fu Y, Sun H, Niu M, Wang Z, Jiao Y, Teubner BJW, Eddins D, Beloate LN, Bai B, Mertz J, Li Y, Cho JH, Wang X, Wu Z, Liu D, Poudel S, Yuan ZF, Mancieri A, Low J, Lee HM, Patton MH, Earls LR, Stewart E, Vogel P, Hui Y, Wan S, Bennett DA, Serrano GE, Beach TG, Dyer MA, Smeyne RJ, Moldoveanu T, Chen T, Wu G, Zakharenko SS, Yu G, Peng J. Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment. Nat Aging 2022; 2:923-940. [PMID: 36636325 PMCID: PMC9833817 DOI: 10.1038/s43587-022-00290-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 09/01/2022] [Indexed: 11/05/2022]
Abstract
Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.
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Affiliation(s)
- Ping-Chung Chen
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xian Han
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Timothy I. Shaw
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL 33612, USA
| | - Yingxue Fu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Huan Sun
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Mingming Niu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Zhen Wang
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Yun Jiao
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Brett J. W. Teubner
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Donnie Eddins
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Lauren N. Beloate
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: Department of Biomedical Engineering and Electrical Engineering, Penn State University, State College, PA 16801, USA
| | - Bing Bai
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: Department of Laboratory Medicine, Center for Precision Medicine, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu 210008, China
| | - Joseph Mertz
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: GlaxoSmithKline, Rockville, MD 20850, USA
| | - Yuxin Li
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xusheng Wang
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Present address: Department of Biology, University of North Dakota, Grand Forks, ND 58202, USA
| | - Zhiping Wu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Danting Liu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Suresh Poudel
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Zuo-Fei Yuan
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Ariana Mancieri
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jonathan Low
- Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hyeong-Min Lee
- Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Mary H. Patton
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Laurie R. Earls
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: Department of Biological Sciences, Loyola University of New Orleans, LA 70118, USA
| | - Elizabeth Stewart
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Peter Vogel
- Veterinary Pathology Core, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Yawei Hui
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Shibiao Wan
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - David A. Bennett
- Department of Neurological Sciences, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | | | - Thomas G. Beach
- Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Michael A. Dyer
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Richard J. Smeyne
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: Department of Neuroscience, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Tudor Moldoveanu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Present address: Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AK 72205, USA
| | - Taosheng Chen
- Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Gang Wu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Stanislav S. Zakharenko
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Gang Yu
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Present address: Department of Neuroscience, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
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16
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Gao Y, Liu M, Yao L, Yang Z, Chen Y, Niu M, Sun Y, Chen J, Hou L, Sun F, Wu S, Zhang Z, Zhang J, Li L, Li J, Zhao Y, Fan J, Ge L, Tian J. Cognitive behavior therapy for insomnia in cancer patients: a systematic review and network meta-analysis. J Evid Based Med 2022; 15:216-229. [PMID: 35996803 DOI: 10.1111/jebm.12485] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 06/27/2022] [Indexed: 01/11/2023]
Abstract
OBJECTIVE The aim of this study was to examine the most effective delivery format of cognitive behavioral therapy for insomnia (CBT-I) on insomnia in cancer patients. METHODS We searched five databases up to February 2021 for randomized clinical trials that compared CBT-I with inactive or active controls for insomnia in cancer patients. Outcomes were insomnia severity, sleep efficiency, sleep onset latency (SOL), wake after sleep onset (WASO), and total sleep time (TST). Pairwise meta-analyses and frequentist network meta-analyses with the random-effects model were applied for data analyses. RESULTS Sixteen unique trials including 1523 participants met inclusion criteria. Compared with inactive control, CBT-I could significantly reduce insomnia severity (mean differences [MD] = -4.98 points, 95% confidence interval [CI]: -5.82 to -4.14), SOL (MD = -12.29 min, 95%CI: -16.48 to -8.09), and WASO (MD = -16.58 min, 95%CI: -22.00 to -11.15), while increasing sleep efficiency (MD = 7.62%, 95%CI: 5.82% to 9.41%) at postintervention. Compared with active control, CBT-I could significantly reduce insomnia severity (MD = -2.75 points, 95%CI: -4.28 to -1.21), SOL (MD = -13.56 min, 95%CI: -18.93 to -8.18), and WASO (MD = -6.99 min, 95%CI: -11.65 to -2.32) at postintervention. These effects diminished in short-term follow-up and almost disappeared in long-term follow-up. Most of the results were rated as "moderate" to "low" certainty of evidence. Network meta-analysis showed that group CBT-I had an increase in sleep efficiency of 10.61%, an increase in TST of 21.98 min, a reduction in SOL of 14.65 min, and a reduction in WASO of 24.30 min, compared with inactive control at postintervention, with effects sustained at short-term follow-up. CONCLUSIONS CBT-I is effective for the management of insomnia in cancer patients postintervention, with diminished effects in short-term follow-up. Group CBT-I is the preferred choice based on postintervention and short-term effects. The low quality of evidence and limited sample size demonstrate the need for robust evidence from high-quality, large-scale trials providing long-term follow-up data.
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Affiliation(s)
- Ya Gao
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ming Liu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Liang Yao
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Zhirong Yang
- Primary Care Unit, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Yamin Chen
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Mingming Niu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Yue Sun
- School of Nursing, Peking University, Beijing, China
| | - Ji Chen
- Mianyang Hospital of Traditional Chinese Medicine, Mianyang, China
| | - Liangying Hou
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Feng Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Shanshan Wu
- National Clinical Research Center of Digestive Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zeqian Zhang
- The University of Hong Kong Shenzhen Hospital, Shenzhen, China
| | - Junhua Zhang
- Evidence-Based Medicine Center, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lun Li
- Department of Breast Cancer, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ye Zhao
- First Clinical Medical College, Lanzhou University, Lanzhou, China
- Departments of Biochemistry and Molecular Biology, Melvin and Bren Simon Comprehensive Cancer Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jingchun Fan
- Epidemiology and Evidence Based-Medicine, School of Public Health, Gansu University of Chinese Medicine, Lanzhou, China
| | - Long Ge
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence-based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
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17
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Bougouin A, Hristov A, Dijkstra J, Aguerre MJ, Ahvenjärvi S, Arndt C, Bannink A, Bayat AR, Benchaar C, Boland T, Brown WE, Crompton LA, Dehareng F, Dufrasne I, Eugène M, Froidmont E, van Gastelen S, Garnsworthy PC, Halmemies-Beauchet-Filleau A, Herremans S, Huhtanen P, Johansen M, Kidane A, Kreuzer M, Kuhla B, Lessire F, Lund P, Minnée EMK, Muñoz C, Niu M, Nozière P, Pacheco D, Prestløkken E, Reynolds CK, Schwarm A, Spek JW, Terranova M, Vanhatalo A, Wattiaux MA, Weisbjerg MR, Yáñez-Ruiz DR, Yu Z, Kebreab E. Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis. J Dairy Sci 2022; 105:7462-7481. [PMID: 35931475 DOI: 10.3168/jds.2021-20885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 04/03/2022] [Indexed: 11/19/2022]
Abstract
Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.
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Affiliation(s)
- A Bougouin
- Department of Animal Science, University of California, Davis 95616.
| | - A Hristov
- Department of Animal Science, The Pennsylvania State University, University Park 16803
| | - J Dijkstra
- Animal Nutrition Group, Wageningen University and Research, 6700 AH Wageningen, the Netherlands
| | - M J Aguerre
- Department of Animal and Veterinary Sciences, Clemson University, Clemson, SC 29634
| | - S Ahvenjärvi
- Animal Nutrition, Production Systems, Natural Resources Institute Finland (Luke), FI-31600 Jokioinen, Finland
| | - C Arndt
- Mazingira Centre, International Livestock Research Institute (ILRI), 00100 Nairobi, Kenya
| | - A Bannink
- Wageningen Livestock Research, Wageningen University and Research, 6700 AH Wageningen, the Netherlands
| | - A R Bayat
- Animal Nutrition, Production Systems, Natural Resources Institute Finland (Luke), FI-31600 Jokioinen, Finland
| | - C Benchaar
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, Canada J1M 0C8
| | - T Boland
- School of Agriculture and Food Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - W E Brown
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison 53706-1205; Department of Animal Sciences, The Ohio State University, Columbus 43210
| | - L A Crompton
- School of Agriculture, Policy and Development, University of Reading, Reading RG6 6AR, United Kingdom
| | - F Dehareng
- Department of Valorisation of Agricultural Products, Walloon Agricultural Research Centre, 5030 Gembloux, Belgium
| | - I Dufrasne
- Department of Veterinary Management of Animal Resources, Faculty of Veterinary Medicine, Fundamental and Applied Research for Animal and Health (FARAH), University of Liège, 4000 Liège, Belgium
| | - M Eugène
- INRAE - Université Clermont Auvergne - VetAgroSup UMR 1213 Unité Mixte de Recherche sur les Herbivores, Centre de recherche Auvergne-Rhône-Alpes, Theix, 63122 Saint-Genès-Champanelle, France
| | - E Froidmont
- Department of Valorisation of Agricultural Products, Walloon Agricultural Research Centre, 5030 Gembloux, Belgium
| | - S van Gastelen
- Wageningen Livestock Research, Wageningen University and Research, 6700 AH Wageningen, the Netherlands
| | - P C Garnsworthy
- School of Biosciences, University of Nottingham, Loughborough LE12 5RD, United Kingdom
| | - A Halmemies-Beauchet-Filleau
- Faculty of Agriculture and Forestry, Department of Agricultural Sciences, University of Helsinki, 00014 Helsinki, Finland
| | - S Herremans
- Department of Valorisation of Agricultural Products, Walloon Agricultural Research Centre, 5030 Gembloux, Belgium
| | - P Huhtanen
- Department of Agricultural Science for Northern Sweden, Swedish University of Agricultural Sciences, SE-901 83, Umeå, Sweden
| | - M Johansen
- Department of Animal Science, Aarhus University, AU Foulum, Dk-8830 Tjele, Denmark
| | - A Kidane
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1433 Ås, Norway
| | - M Kreuzer
- Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland
| | - B Kuhla
- Institute for Farm Animal Biology (FBN), Institute of Nutritional Physiology "Oskar Kellner," Dummerstorf, Mecklenburg-Vorpommern, Germany
| | - F Lessire
- Department of Veterinary Management of Animal Resources, Faculty of Veterinary Medicine, Fundamental and Applied Research for Animal and Health (FARAH), University of Liège, 4000 Liège, Belgium
| | - P Lund
- Department of Animal Science, Aarhus University, AU Foulum, Dk-8830 Tjele, Denmark
| | - E M K Minnée
- DairyNZ Ltd., Private Bag 3221, Hamilton, New Zealand 3240
| | - C Muñoz
- Instituto de Investigaciones Agropecuarias, INIA Remehue, Ruta 5 S, Osorno, Chile
| | - M Niu
- Department of Animal Science, University of California, Davis 95616; Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland
| | - P Nozière
- INRAE - Université Clermont Auvergne - VetAgroSup UMR 1213 Unité Mixte de Recherche sur les Herbivores, Centre de recherche Auvergne-Rhône-Alpes, Theix, 63122 Saint-Genès-Champanelle, France
| | - D Pacheco
- Ag Research, Palmerston North 4410, New Zealand
| | - E Prestløkken
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1433 Ås, Norway
| | - C K Reynolds
- School of Agriculture, Policy and Development, University of Reading, Reading RG6 6AR, United Kingdom
| | - A Schwarm
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1433 Ås, Norway
| | - J W Spek
- Wageningen Livestock Research, Wageningen University and Research, 6700 AH Wageningen, the Netherlands
| | - M Terranova
- AgroVet-Strickhof, ETH Zurich, 8315 Lindau, Switzerland
| | - A Vanhatalo
- Faculty of Agriculture and Forestry, Department of Agricultural Sciences, University of Helsinki, 00014 Helsinki, Finland
| | - M A Wattiaux
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison 53706-1205
| | - M R Weisbjerg
- Department of Animal Science, Aarhus University, AU Foulum, Dk-8830 Tjele, Denmark
| | - D R Yáñez-Ruiz
- Estación Experimental del Zaidin, CSIC, 1, 18008 Granada, Spain
| | - Z Yu
- Department of Animal Sciences, The Ohio State University, Columbus 43210
| | - E Kebreab
- Department of Animal Science, University of California, Davis 95616
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18
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Zhang W, Liu FQ, Zhang LP, Ding HG, Zhuge YZ, Wang JT, Li L, Wang GC, Wu H, Li H, Cao GH, Lu XF, Kong DR, Sun L, Wu W, Sun JH, Liu JT, Zhu H, Li DL, Guo WH, Xue H, Wang Y, Gengzang CJC, Zhao T, Yuan M, Liu SR, Huan H, Niu M, Li X, Ma J, Zhu QL, Guo WW, Zhang KP, Zhu XL, Huang BR, Li JN, Wang WD, Yi HF, Zhang Q, Gao L, Zhang G, Zhao ZW, Xiong K, Wang ZX, Shan H, Li MS, Zhang XQ, Shi HB, Hu XG, Zhu KS, Zhang ZG, Jiang H, Zhao JB, Huang MS, Shen WY, Zhang L, Xie F, Li ZW, Hou CL, Hu SJ, Lu JW, Cui XD, Lu T, Yang SS, Liu W, Shi JP, Lei YM, Bao JL, Wang T, Ren WX, Zhu XL, Wang Y, Yu L, Yu Q, Xiang HL, Luo WW, Qi XL. [Status of HVPG clinical application in China in 2021]. Zhonghua Gan Zang Bing Za Zhi 2022; 30:637-643. [PMID: 36038326 DOI: 10.3760/cma.j.cn501113-20220302-00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: The investigation and research on the application status of Hepatic Venous Pressure Gradient (HVPG) is very important to understand the real situation and future development of this technology in China. Methods: This study comprehensively investigated the basic situation of HVPG technology in China, including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications and existing problems. Results: According to the survey, there were 70 hospitals in China carrying out HVPG technology in 2021, distributed in 28 provinces (autonomous regions and municipalities directly under the central Government). A total of 4 398 cases of HVPG were performed in all the surveyed hospitals in 2021, of which 2 291 cases (52.1%) were tested by HVPG alone. The average cost of HVPG detection was (5 617.2±2 079.4) yuan. 96.3% of the teams completed HVPG detection with balloon method, and most of the teams used thrombectomy balloon catheter (80.3%). Conclusion: Through this investigation, the status of domestic clinical application of HVPG has been clarified, and it has been confirmed that many domestic medical institutions have mastered this technology, but it still needs to continue to promote and popularize HVPG technology in the future.
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Affiliation(s)
- W Zhang
- Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - F Q Liu
- Department of Interventional Radiology, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
| | - L P Zhang
- Department of Radiology,Third Hospital of Taiyuan, Taiyuan 030012, China
| | - H G Ding
- Liver Disease Digestive Center,Beijing Youan Hospital, Capital Medical University, Beijing 100069, China
| | - Y Z Zhuge
- Digestive Department,Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - J T Wang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - L Li
- Department of Interventional Radiology, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - G C Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China
| | - H Wu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - H Li
- Institute of Hepatology and Department of Infectious Disease, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - G H Cao
- Department of Radiology, Shulan Hospital, Hangzhou 310022, China
| | - X F Lu
- Digestive Department, West China Hospital, Sichuan University, Chengdu 610044, China
| | - D R Kong
- Digestive Department, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - L Sun
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - W Wu
- Department of Gastroenterology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325001, China
| | - J H Sun
- Hepatobiliary and Pancreatic Intervention Center , the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J T Liu
- Digestive Department,Hainan Hospital of Chinese PLA General Hospital, Sanya 572013, China
| | - H Zhu
- The 1 st Department of Interventional Radiology, the Sixth People's Hospital of Shenyang, Shenyang 110006, China
| | - D L Li
- No. 900 Hospital of the Joint Logistic Support Force, Fuzhou 350025, China
| | - W H Guo
- Department of Interventional Radiology, Meng Chao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China
| | - H Xue
- Digestive Department, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Y Wang
- Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - C J C Gengzang
- Department of Interventional Radiology, the Fourth People's Hospital of Qinghai Province, Xining 810007, China
| | - T Zhao
- Department of Radiology,Sir Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China
| | - M Yuan
- Department of Interventional Radiology Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - S R Liu
- Department of Infectious Disease,Qufu People's Hospital, Qufu 273199, China
| | - H Huan
- Digestive Department, Chengdu Office Hospital of Tibet Autonomous Region People's Government, Chengdu 610041, China
| | - M Niu
- Department of Interventional Radiology, the First Affiliated Hospital of China Medical University, Shenyang 110001, China
| | - X Li
- Department of Radiology,Tianjin Second People's Hospital, Tianjin 300192, China
| | - J Ma
- Department of Interventional Vascular Surgerg, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - Q L Zhu
- Digestive Department,the Affiliated Hospital of Southwest Medical University, Luzhou 646099, China
| | - W W Guo
- Department of Interventional Radiology, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - K P Zhang
- Department of Hepatobiliary Surgery, Xingtai People's Hospital, Xingtai 054001, China
| | - X L Zhu
- Department of Surgery, the First Hospital of Lanzhou University, Lanzhou 730013, China
| | - B R Huang
- Department of Interventional Vascular Surgery,Jingzhou First People's Hospital, Jingzhou, China
| | - J N Li
- Liver Diseases Department,Jiamusi Infectious Disease Hospital, Jiamusi 154015, China
| | - W D Wang
- Hepatobiliary, Pancreatic and Spleen Surgery Department,Shunde Hospital, Southern Medical University, Foshan 528427, China
| | - H F Yi
- Digestive Department,Wuhan First Hospital, Wuhan 430030, China
| | - Q Zhang
- Interventional Vascular Surgery Department, Affiliated Zhongda Hospital of Southeast University, Nanjing 210009, China
| | - L Gao
- Oncology and Vascular Interventional Department, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - G Zhang
- Digestive Department, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - Z W Zhao
- Department of Interventional Radiology, Lishui Municipal Central Hospital, Zhejiang University School of Medicine, Lishui 323030, China
| | - K Xiong
- Digestive Department, the Second Affiliated Hospital of Nanchang University, Nanchang 330008, China
| | - Z X Wang
- Inner Mongolia Medical University Affiliated Hospital, Hohhot 010050, China
| | - H Shan
- Interventional Medicine Center, the Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China
| | - M S Li
- Department of Endovascular Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - X Q Zhang
- Digestive Department, the Second Hospital of Hebei Medical University, Shijiazhuang 050004, China
| | - H B Shi
- Department of Interventional Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - X G Hu
- Interventional Radiology Department,Jinhua Municipal Central Hospital, Jinhua 321099, China
| | - K S Zhu
- Interventional Radiology Department, the Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510260, China
| | - Z G Zhang
- Department of Liver Surgery,Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China
| | - H Jiang
- Infectious Disease Department,Second Affiliated Hospital, Military Medical University of the Air Force, Xi'an 710038, China
| | - J B Zhao
- Department of Vascular and Interventional Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - M S Huang
- Interventional Radiology Department, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510000, China
| | - W Y Shen
- Digestive Department,Fuling Hospital Affiliated to Chongqing University, Chongqing 400030, China
| | - L Zhang
- Hepatobiliary Pancreatic Center,Tsinghua Changgung Hospital, Beijing 102200, China
| | - F Xie
- Function Department,Lanzhou Second People's Hospital, Lanzhou 730030, China
| | - Z W Li
- Hepatobiliary Surgery Department,Shenzhen Third People's Hospital, Shenzhen518112, China
| | - C L Hou
- Department of Interventional Radiology, the First Affiliated Hospital of USTC, Hefei 230001, China
| | - S J Hu
- Digestive Department,People's Hospital of Ningxia Hui Autonomous Region, Yinchuan 750002, China
| | - J W Lu
- Department of Interventional Radiology, Qufu People's Hospital, Qufu 273199, China
| | - X D Cui
- Department of Interventional Radiology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530016, China
| | - T Lu
- Department of Gastroenterology, Yangquan Third People's Hospital, Yangquan 045099,China
| | - S S Yang
- Department of Gastroenterology, General Hospital of Ningxia Medical University , Yinchuan 750003, China
| | - W Liu
- Department of Interventional Radiology, Lishui People's Hospital, Zhejiang Province, Lishui 323050, China
| | - J P Shi
- Department of Liver Diseases, Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, China
| | - Y M Lei
- Interventional Radiology Department, People's Hospital of Tibet Autonomous Region, Lhasa 850001, China
| | - J L Bao
- Department of Gastroenterology, Shannan people's Hospital,Shannan 856004, China
| | - T Wang
- Department of Interventional Radiology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai 264099,China
| | - W X Ren
- Interventional Treatment Center, the First Affiliated Hospital of Xinjiang Medical University, Urumqi 830011,China
| | - X L Zhu
- Interventional Radiology Department, the First Affiliated Hospital of Suzhou University, Suzhou 215006, China
| | - Y Wang
- Department of Interventional Vascular Surgery, the Second Affiliated Hospital of Hainan Medical College, Haikou 570216, China
| | - L Yu
- Department of Interventional Radiology, Sanming First Hospital Affiliated to Fujian Medical University,Sanming 365001,China
| | - Q Yu
- Interventional Radiology Department, Fifth Medical Center of PLA General Hospital, Beijing 100039, China
| | - H L Xiang
- Department of Gastroenterology, Tianjin Third Central Hospital, Tianjin 300170, China
| | - W W Luo
- Deparment of Infectious Diseases, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
| | - X L Qi
- Center of Portal Hypertension Department of Radiology, Zhongda Hospital of Southeast University, Nanjing 210009, China
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Zhang Y, Chen Y, Niu M, Li Y, Zhang J, Zhang L, Wu F, Chen Q, Yu H, Tian J. Establishing a core outcome set for neurogenic bladder trials: study protocol for a scoping review and Delphi surveys. Trials 2022; 23:485. [PMID: 35698096 PMCID: PMC9195205 DOI: 10.1186/s13063-022-06419-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 05/20/2022] [Indexed: 11/23/2022] Open
Abstract
Background Neurogenic bladder (NGB) is a chronic and disabling condition with a high prevalence rate, which can cause economic burden on patients and their families and reduce the quality of life of patients. Researchers have carried out a large number of clinical trials on the effectiveness and safety of different interventions for the treatment of NGB. The published clinical trials of NGB generally suffered from inconsistent and irregular reporting of outcome indicators. To facilitate future research studies of NGB, a core outcome set (COS) is required, which helps translate the results into high-quality evidence. Methods and analysis This mixed-method project has four phases instrument: in phase 1, a scoping review of the literature to identify outcomes that have been reported in clinical trials and systematic reviews of clinical trials of interventions for NGB; in phase 2, a qualitative component using interviews to obtain the views of NGB patients, families, and their caregivers; in phase 3, Delphi survey among stakeholders to prioritize the core outcomes; and in phase 4, a face-to-face consensus meeting to discuss and agree on the final NBG COS. Conclusions We will develop a COS that should be reported in future clinical trials of NGB. Trial registration Core Outcome Measures in Effectiveness Trials (COMET) Initiative database registration: http://www.comet-initiative.org/studies/details/1985. Registered on 02 January 2022. INPLASY INPLASY202210007
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Affiliation(s)
- Yan Zhang
- Department of Spinal Cord Injury Rehabilitation, Gansu Province Hospital Rehabilitation Center, 53 Dingxi Road, Chengguan District, Lanzhou, 730000, Gansu, China
| | - Yamin Chen
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China
| | - Mingming Niu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China
| | - Yuanyuan Li
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China
| | - Jiaoyan Zhang
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China
| | - Li Zhang
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China.,The Third Ward of Cardiovascular Clinical Medical Center, Affiliated Hospital of Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Fangfang Wu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China.,School of Nursing, Shangluo Vocational and Technical College, City, Shangluo, 726000, China
| | - Qingyun Chen
- Department of Clinical Laboratory, The Sixth People's Hospital of Chengdu City, Chengdu, 610000, Sichuan, China
| | - Huijin Yu
- Department of Spinal Cord Injury Rehabilitation, Gansu Province Hospital Rehabilitation Center, 53 Dingxi Road, Chengguan District, Lanzhou, 730000, Gansu, China.
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, No.199, Donggang West Road, Lanzhou City, 730000, Gansu Province, China. .,School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, Gansu, China. .,Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, Gansu, China.
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20
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Yang QY, Lu Y, Xie XL, Lai HH, Tian C, Niu M, Tian JH, Li N, Li J, Ge L. [QUADAS-C-A tool for assessing risk of bias regarding Quality Assessment of Diagnostic Accuracy Studies-Comparative]. Zhonghua Liu Xing Bing Xue Za Zhi 2022; 43:938-944. [PMID: 35725353 DOI: 10.3760/cma.j.cn112338-20211101-00841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
This paper introduced the Quality Assessment of Diagnostic Accuracy Studies-Comparative (QUADAS-C), illustrated the comparison with the QUADAS-2, and using QUADAS-C together with QUADAS-2 to present QUADAS-C results through systematic reviews. Like the domain for QUADAS-2, QUADAS-C retained four domains, including patient selection, index test, reference standard, flow, and timing, and comprised additional questions for each QUADAS-2 part. Unlike the QUADAS-2 tool, the starting question of each domain for QUADAS-C was designed to summarize the risk of biased information captured by QUADAS-2. QUADAS-C only dealt with the risk of bias but did not include the part of concerns regarding applicability. The answers to signaling questions for each domain of QUADAS-C would lead to a 'low''high' or 'unclear' risk of biased judgment for the original study.
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Affiliation(s)
- Q Y Yang
- Evidence Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou 730000, China
| | - Y Lu
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou 730000, China Department of Social Science and Health Management, School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - X L Xie
- The Second School of Clinical Medicine of Lanzhou University, Lanzhou 730000, China
| | - H H Lai
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou 730000, China Department of Social Science and Health Management, School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - C Tian
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou 730000, China Department of Social Science and Health Management, School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - M Niu
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou 730000, China
| | - J H Tian
- Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou 730000, China
| | - N Li
- National Cancer Center/National Cancer Clinical Medical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J Li
- National Cancer Center/National Cancer Clinical Medical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Long Ge
- Evidence-Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou 730000, China Department of Social Science and Health Management, School of Public Health, Lanzhou University, Lanzhou 730000, China Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou 730000, China
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21
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Gao Y, Ge L, Liu M, Niu M, Chen Y, Sun Y, Chen J, Yao L, Wang Q, Li Z, Xu J, Li M, Hou L, Shi J, Yang K, Cai Y, Li L, Zhang J, Tian J. Comparative efficacy and acceptability of cognitive behavioral therapy delivery formats for insomnia in adults: a systematic review and network meta-analysis. Sleep Med Rev 2022; 64:101648. [DOI: 10.1016/j.smrv.2022.101648] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/09/2022] [Accepted: 05/21/2022] [Indexed: 10/18/2022]
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22
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Chen Y, Gao Y, Zhang J, Niu M, Liu X, Zhang Y, Tian J. Quality and clinical applicability of recommendations for incontinence-associated dermatitis: A systematic review of guidelines and consensus statements. J Clin Nurs 2022; 32:2371-2382. [PMID: 35411654 DOI: 10.1111/jocn.16306] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/08/2022] [Accepted: 03/16/2022] [Indexed: 12/20/2022]
Abstract
AIMS AND OBJECTIVES The aim of this study was to assess methodological quality of all currently available guidelines and consensus statements for IAD using the Appraisal of Guidelines, Research and Evaluation (AGREE) II and the AGREE Recommendation Excellence (AGREE-REX) instruments. BACKGROUND Globally, incontinence-associated dermatitis (IAD) is a significant health challenge. IAD is a complex healthcare problem that reduces quality of life of patients, increases healthcare costs and prolongs hospital stays. Several guidelines and consensus statements are available for IAD. However, the quality of these guidelines and consensus statements remains unclear. DESIGN A systematic review of guidelines and consensus statements. METHODS Our study was undertaken using PRISMA guidelines. We searched seven electronic databases. Guidelines and consensus statements had to be published in English, Chinese or German languages. Five independent reviewers assessed the methodological quality of guidelines and consensus statements using the AGREE II and AGREE-REX instruments. Mean with standard deviation (SD) and median with interquartile range (IQR) were calculated for descriptive analyses. We generated bubble plots to describe the assessment results of each domain of each guideline and consensus statement. RESULTS We included ten guidelines and consensus statements. The NICE guidelines, obtained the highest scores, fulfilled 86.11%-98.61% of criteria in AGREE II and 76.67%-91.11% for AGREE-REX. In the domains 'Stakeholder Involvement' (4.39 ± 1.64), 'Rigor of Development' (3.38 ± 1.86), 'Applicability' (3.62 ± 1.64), 'Editorial Independence' (3.91 ± 2.56) and 'Values and Preferences' (2.98 ± 1.41), the remaining guidelines and consensus statements showed deficiencies. CONCLUSIONS Altogether, this study demonstrated that the currently available guidelines and consensus statements for IAD have room for methodological improvement. NICE guidelines on faecal incontinence and urinary incontinence have better quality. Remaining guidelines and consensus statements showed substantial methodological weaknesses, especially the domains of 'Stakeholder Involvement', 'Rigor of Development', 'Applicability', 'Editorial independence' and 'Values and Preferences'. This study was registered on INPLASY. (Registration number: INPLASY202190078). RELEVANCE TO CLINICAL PRACTICE The currently available guidelines and consensus statements on IAD have room for methodological improvement.
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Affiliation(s)
- Yamin Chen
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.,Evidence-Based Medicine Center, Lanzhou University, Lanzhou, China.,WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China
| | - Ya Gao
- Evidence-Based Medicine Center, Lanzhou University, Lanzhou, China.,WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China.,School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.,Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Jiaoyan Zhang
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.,Evidence-Based Medicine Center, Lanzhou University, Lanzhou, China.,WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China
| | - Mingming Niu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.,Evidence-Based Medicine Center, Lanzhou University, Lanzhou, China.,WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China
| | - Xiaofeng Liu
- Department of Nursing, Jingning People's Hospital, Pingliang, China
| | - Yuqin Zhang
- Department of Dermatology, Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, Lanzhou University, Lanzhou, China.,WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China.,School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.,Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
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23
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Sun X, Sun H, Han X, Chen PC, Jiao Y, Wu Z, Zhang X, Wang Z, Niu M, Yu K, Liu D, Dey KK, Mancieri A, Fu Y, Cho JH, Li Y, Poudel S, Branon TC, Ting AY, Peng J. Deep Single-Cell-Type Proteome Profiling of Mouse Brain by Nonsurgical AAV-Mediated Proximity Labeling. Anal Chem 2022; 94:5325-5334. [PMID: 35315655 DOI: 10.1021/acs.analchem.1c05212] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single-cell, or single-cell-type levels. Reliable methods for extracting specific cell-type proteomes are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single-cell-type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAVs) to express TurboID driven by cell-type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins, followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT) labeling. We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single-cell-type proteomic pipeline. To analyze specific brain cell types, we generated recombinant AAVs to coexpress TurboID and mCherry proteins, driven by neuron- or astrocyte-specific promoters and validated the expected cell expression by coimmunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ∼10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analyses indicated that these PL proteomes contain cell-type-specific cellular pathways. Although PL was originally developed for studying protein-protein interactions and subcellular proteomes, we extended it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single-cell-type proteomics.
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Affiliation(s)
- Xiaojun Sun
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Huan Sun
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Xian Han
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, Tennessee 38163, United States
| | - Ping-Chung Chen
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Yun Jiao
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Zhiping Wu
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Xue Zhang
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Zhen Wang
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Mingming Niu
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Kaiwen Yu
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Danting Liu
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Kaushik Kumar Dey
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Ariana Mancieri
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Yingxue Fu
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Suresh Poudel
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
| | - Tess C Branon
- Department of Genetics, Department of Chemistry, Department of Biology, Stanford University, Stanford, California 94305, United States
| | - Alice Y Ting
- Department of Genetics, Department of Chemistry, Department of Biology, Stanford University, Stanford, California 94305, United States
| | - Junmin Peng
- Departments of Structural Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States.,Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, Tennessee 38105, United States
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Li L, Niu M, Erickson A, Luo J, Rowbotham K, Guo K, Huang H, Li Y, Jiang Y, Hur J, Liu C, Peng J, Wang X. SMAP is a pipeline for sample matching in proteogenomics. Nat Commun 2022; 13:744. [PMID: 35136070 PMCID: PMC8825821 DOI: 10.1038/s41467-022-28411-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 01/17/2022] [Indexed: 11/12/2022] Open
Abstract
The integration of genomics and proteomics data (proteogenomics) holds the promise of furthering the in-depth understanding of human disease. However, sample mix-up is a pervasive problem in proteogenomics because of the complexity of sample processing. Here, we present a pipeline for Sample Matching in Proteogenomics (SMAP) to verify sample identity and ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulated data indicates that SMAP is capable of uniquely matching proteomic and genomic samples when ≥20% genotypes of individual samples are available. When SMAP was applied to a large-scale dataset generated by the PsychENCODE BrainGVEX project, 54 samples (19%) were corrected. The correction was further confirmed by ribosome profiling and chromatin sequencing (ATAC-seq) data from the same set of samples. Our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. SMAP is publicly available at https://github.com/UND-Wanglab/SMAP, and a web-based version can be accessed at https://smap.shinyapps.io/smap/. Sample mix-up is a potential problem in large-scale omic studies due to the complexity of sample processing. Here, the authors present a pipeline for sample matching in proteogenomics to verify sample identity and ensure data integrity.
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Affiliation(s)
- Ling Li
- Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Alyssa Erickson
- Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Jie Luo
- State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou, 310021, China
| | - Kincaid Rowbotham
- Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Kai Guo
- Department of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - He Huang
- Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Yuxin Li
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Yi Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Junguk Hur
- Department of Biomedical Sciences, School of medicine and health sciences, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, 13210, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
| | - Xusheng Wang
- Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA.
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25
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Liu P, Yu X, Dai X, Zou W, Yu X, Niu M, Chen Q, Teng W, Kong Y, Guan R, Liu X. Scalp Acupuncture Attenuates Brain Damage After Intracerebral Hemorrhage Through Enhanced Mitophagy and Reduced Apoptosis in Rats. Front Aging Neurosci 2022; 13:718631. [PMID: 34987374 PMCID: PMC8720963 DOI: 10.3389/fnagi.2021.718631] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 11/18/2021] [Indexed: 11/13/2022] Open
Abstract
To study the effect of scalp acupuncture (SA) on the mitophagy signaling pathway in the caudate nucleus of Sprague-Dawley rats following intracerebral hemorrhage (ICH). An ICH model was established by injecting autologous arterial blood into the caudate nucleus in 200 male Sprague-Dawley rats, which were divided into five groups: sham, ICH, 3-methyladenine group (3-MA, 30 mg/kg), SA, and SA+3-MA. Animals were analyzed at 6 and 24 h as well as at 3 and 7 days. Composite neurological scale score was significantly higher in the SA group than in the ICH group. Transmission electron microscopy showed less structural damage and more autophagic vacuoles within brain in the SA group than in the ICH group. SA group showed higher levels of Beclin1, Parkin, PINK1, NIX protein, and a lower level of Caspase-9 in brain tissue. These animals consequently showed less neural cell apoptosis. Compared with the SA group, however, the neural function score and levels of mitophagy protein in the SA+3-MA group were decreased, neural cell apoptosis was increased with more severe structural damage, which suggested that 3-MA may antagonize the protective effect of SA on brain in rats with ICH. SA may mitigate the neurologic impairment after ICH by enhancing mitophagy and reducing apoptosis.
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Affiliation(s)
- Peng Liu
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xinyang Yu
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.,Clinical Key Laboratory of Integrated Traditional Chinese and Western Medicine, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xiaohong Dai
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wei Zou
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China.,Clinical Key Laboratory of Integrated Traditional Chinese and Western Medicine, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xueping Yu
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Mingming Niu
- Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Qiuxin Chen
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wei Teng
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ying Kong
- Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ruiqiao Guan
- Integrated Chinese and Western Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xiaoying Liu
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
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26
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Dey KK, Sun H, Wang Z, Niu M, Wang H, Jiao Y, Sun X, Li Y, Peng J. Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry. Methods Mol Biol 2022; 2420:21-37. [PMID: 34905163 PMCID: PMC8890903 DOI: 10.1007/978-1-0716-1936-0_3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.
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27
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Yang L, Zhi S, Yang G, Qin C, Yan X, Niu M, Zhang W, Liu M, Zhao M, Nie G. Molecular identification of glucose transporter 4: The responsiveness to starvation, glucose, insulin and glucagon on glucose transporter 4 in common carp (Cyprinus carpio L.). J Fish Biol 2021; 99:1843-1856. [PMID: 34418098 DOI: 10.1111/jfb.14885] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 07/27/2021] [Accepted: 08/18/2021] [Indexed: 06/13/2023]
Abstract
Glucose transporter 4 (GLUT4) is comprehensively investigated in mammals, while the comparative research of GLUT4 in common carp is deficient. To investigate the function of GLUT4, carp glut4 was first isolated. The open reading frame of carp glut4 was 1518 bp in length, encoding 505 amino acids. A high-sequence homology was identified in carp and teleost, and the phylogenetic tree displayed that the carp GLUT4 was clustered with the teleost. A high level of glut4 mRNA was analysed in fat, red muscle and white muscle. After fasting treatment, glut4 mRNA expression was increased significantly in muscle. In the oral glucose tolerance test experiment, glut4 mRNA was also significantly elevated in muscle, gut and fat. Furthermore, intraperitoneal injection of insulin resulted in the upregulation of glut4 gene expression significantly in white muscle, gut and fat. On the contrary, the glut4 mRNA level in the white muscle, gut and fat was markedly downregulated after glucagon injection. These results suggest that GLUT4 might play important roles in food intake and could be regulated by nutrient condition, insulin and glucagon in common carp. Our study is the first to report on GLUT4 in common carp. These data provide a basis for further study on fish GLUT4.
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Affiliation(s)
- Liping Yang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Shaoyang Zhi
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Guokun Yang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Chaobin Qin
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Xiao Yan
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Mingming Niu
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Wenlei Zhang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Mingyu Liu
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Mengjuan Zhao
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
| | - Guoxing Nie
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, Xinxiang, China
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Long L, Wei J, Lim SA, Raynor JL, Shi H, Connelly JP, Wang H, Guy C, Xie B, Chapman NM, Fu G, Wang Y, Huang H, Su W, Saravia J, Risch I, Wang YD, Li Y, Niu M, Dhungana Y, Kc A, Zhou P, Vogel P, Yu J, Pruett-Miller SM, Peng J, Chi H. CRISPR screens unveil signal hubs for nutrient licensing of T cell immunity. Nature 2021; 600:308-313. [PMID: 34795452 PMCID: PMC8887674 DOI: 10.1038/s41586-021-04109-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 10/07/2021] [Indexed: 12/26/2022]
Abstract
Nutrients are emerging regulators of adaptive immunity1. Selective nutrients interplay with immunological signals to activate mechanistic target of rapamycin complex 1 (mTORC1), a key driver of cell metabolism2-4, but how these environmental signals are integrated for immune regulation remains unclear. Here we use genome-wide CRISPR screening combined with protein-protein interaction networks to identify regulatory modules that mediate immune receptor- and nutrient-dependent signalling to mTORC1 in mouse regulatory T (Treg) cells. SEC31A is identified to promote mTORC1 activation by interacting with the GATOR2 component SEC13 to protect it from SKP1-dependent proteasomal degradation. Accordingly, loss of SEC31A impairs T cell priming and Treg suppressive function in mice. In addition, the SWI/SNF complex restricts expression of the amino acid sensor CASTOR1, thereby enhancing mTORC1 activation. Moreover, we reveal that the CCDC101-associated SAGA complex is a potent inhibitor of mTORC1, which limits the expression of glucose and amino acid transporters and maintains T cell quiescence in vivo. Specific deletion of Ccdc101 in mouse Treg cells results in uncontrolled inflammation but improved antitumour immunity. Collectively, our results establish epigenetic and post-translational mechanisms that underpin how nutrient transporters, sensors and transducers interplay with immune signals for three-tiered regulation of mTORC1 activity and identify their pivotal roles in licensing T cell immunity and immune tolerance.
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Affiliation(s)
- Lingyun Long
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jun Wei
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Seon Ah Lim
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jana L Raynor
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Hao Shi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jon P Connelly
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Hong Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Cliff Guy
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Boer Xie
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Nicole M Chapman
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Guotong Fu
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yanyan Wang
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Hongling Huang
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Wei Su
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jordy Saravia
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Isabel Risch
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yong-Dong Wang
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Mingming Niu
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yogesh Dhungana
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Anil Kc
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Peipei Zhou
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Peter Vogel
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jiyang Yu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Shondra M Pruett-Miller
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Junmin Peng
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, USA
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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Niu M, Gao Y, Yang M, Zhang Y, Geng J, Song Z, Chen Y, Li Y, Li J, Tian J. The quality and clinical applicability of recommendations in anxiety disorders guidelines: A systematic review of seventeen guidelines from seven countries. J Affect Disord 2021; 295:1301-1309. [PMID: 34706444 DOI: 10.1016/j.jad.2021.08.103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 07/31/2021] [Accepted: 08/28/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Anxiety disorders are the most common mental disorders, for which some countries and organizations have developed guidelines. It is necessary to understand the quality of these guidelines. METHODS The relevant guidelines were searched systematically by five reviewers using Appraisal of Guidelines for Research and Evaluation (AGREE) II and AGREE Recommendation Excellence (AGREE-REX) instruments. The scores in each domain were descriptively analyzed, and guidelines from different countries were compared. RESULTS Seventeen guidelines were included. The scores in the domains "rigor of development" and "applicability" were the lowest and ranged from 16% to 77% and 25% to 71%, respectively. The scores in the domains "implementability" and "values and preferences" were similar and ranged from 30% to 67% and 25% to 77%. In terms of the comparison among countries, the Canadian guidelines achieved the highest scores in many domains but only scored 43% in the domain of "values and preferences". The Indian guidelines scored less than 50% in many domains but achieved a high score of 83% in the domain "scope and purpose". LIMITATIONS Language restrictions may cause selection bias. Besides, insufficient reports may lead to deviation of assessment results. CONCLUSIONS There was no obvious advantage in guidelines from different countries. There was still a lot of room for improvement in some domains, especially "applicability", "implementability", "rigor of development" and "values and preferences".
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Affiliation(s)
- Mingming Niu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ya Gao
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Min Yang
- Comprehensive Department of Medical Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yonggang Zhang
- Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu, China
| | - Jie Geng
- Department of General Surgery, Second Hospital of Lanzhou University, Lanzhou, China
| | - Ziwei Song
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yamin Chen
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yanchen Li
- The Second Clinical Medical College, Lanzhou University, Lanzhou, China
| | - Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Jinhui Tian
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China; WHO Collaborating Center for Guideline Implementation and Knowledge Translation, Lanzhou, China.
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30
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Roberts JA, Varma VR, An Y, Varma S, Candia J, Fantoni G, Tiwari V, Anerillas C, Williamson A, Saito A, Loeffler T, Schilcher I, Moaddel R, Khadeer M, Lovett J, Tanaka T, Pletnikova O, Troncoso JC, Bennett DA, Albert MS, Yu K, Niu M, Haroutunian V, Zhang B, Peng J, Croteau DL, Resnick SM, Gorospe M, Bohr VA, Ferrucci L, Thambisetty M. A brain proteomic signature of incipient Alzheimer's disease in young APOE ε4 carriers identifies novel drug targets. Sci Adv 2021; 7:eabi8178. [PMID: 34757788 PMCID: PMC8580310 DOI: 10.1126/sciadv.abi8178] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Aptamer-based proteomics revealed differentially abundant proteins in Alzheimer’s disease (AD) brains in the Baltimore Longitudinal Study of Aging and Religious Orders Study (mean age, 89 ± 9 years). A subset of these proteins was also differentially abundant in the brains of young APOE ε4 carriers relative to noncarriers (mean age, 39 ± 6 years). Several of these proteins represent targets of approved and experimental drugs for other indications and were validated using orthogonal methods in independent human brain tissue samples as well as in transgenic AD models. Using cell culture–based phenotypic assays, we showed that drugs targeting the cytokine transducer STAT3 and the Src family tyrosine kinases, YES1 and FYN, rescued molecular phenotypes relevant to AD pathogenesis. Our findings may accelerate the development of effective interventions targeting the earliest molecular triggers of AD.
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Affiliation(s)
- Jackson A Roberts
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032
| | - Vijay R Varma
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Yang An
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | | | - Julián Candia
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Giovanna Fantoni
- Clinical Research Core, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Vinod Tiwari
- Section on DNA Repair, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Carlos Anerillas
- Laboratory of Genetics and Genomics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Andrew Williamson
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Atsushi Saito
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Tina Loeffler
- QPS Austria GmbH, Parkring 12, 8074 Grambach, Austria
| | | | - Ruin Moaddel
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Mohammed Khadeer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Jacqueline Lovett
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Toshiko Tanaka
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Olga Pletnikova
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA
| | - Juan C Troncoso
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Kaiwen Yu
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Vahram Haroutunian
- Departments of Psychiatry and Neuroscience, The Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences and Department of Pharmacological Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Deborah L Croteau
- Section on DNA Repair, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Susan M Resnick
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Myriam Gorospe
- Laboratory of Genetics and Genomics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Vilhelm A Bohr
- Section on DNA Repair, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Madhav Thambisetty
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
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Xu B, Wang H, Wright S, Hyle J, Zhang Y, Shao Y, Niu M, Fan Y, Rosikiewicz W, Djekidel MN, Peng J, Lu R, Li C. Acute depletion of CTCF rewires genome-wide chromatin accessibility. Genome Biol 2021; 22:244. [PMID: 34429148 PMCID: PMC8386078 DOI: 10.1186/s13059-021-02466-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 08/12/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The transcription factor CTCF appears indispensable in defining topologically associated domain boundaries and maintaining chromatin loop structures within these domains, supported by numerous functional studies. However, acute depletion of CTCF globally reduces chromatin interactions but does not significantly alter transcription. RESULTS Here, we systematically integrate multi-omics data including ATAC-seq, RNA-seq, WGBS, Hi-C, Cut&Run, and CRISPR-Cas9 survival dropout screens, and time-solved deep proteomic and phosphoproteomic analyses in cells carrying auxin-induced degron at endogenous CTCF locus. Acute CTCF protein degradation markedly rewires genome-wide chromatin accessibility. Increased accessible chromatin regions are frequently located adjacent to CTCF-binding sites at promoter regions and insulator sites associated with enhanced transcription of nearby genes. In addition, we use CTCF-associated multi-omics data to establish a combinatorial data analysis pipeline to discover CTCF co-regulatory partners. We successfully identify 40 candidates, including multiple established partners. Interestingly, many CTCF co-regulators that have alterations of their respective downstream gene expression do not show changes of their own expression levels across the multi-omics measurements upon acute CTCF loss, highlighting the strength of our system to discover hidden co-regulatory partners associated with CTCF-mediated transcription. CONCLUSIONS This study highlights that CTCF loss rewires genome-wide chromatin accessibility, which plays a critical role in transcriptional regulation.
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Affiliation(s)
- Beisi Xu
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA.
| | - Hong Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Shaela Wright
- Tumor Cell Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Judith Hyle
- Tumor Cell Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Yang Zhang
- Tumor Cell Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Ying Shao
- Computational Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Yiping Fan
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Wojciech Rosikiewicz
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Mohamed Nadhir Djekidel
- Center for Applied Bioinformatics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Junmin Peng
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Rui Lu
- Division of Hematology/Oncology, University of Alabama at Birmingham, 1824 6th Ave S WTI 510G, Birmingham, AL, 35294, USA
- O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, 1824 6th Ave S WTI 510G, Birmingham, AL, 35294, USA
| | - Chunliang Li
- Tumor Cell Biology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA.
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32
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Shaw TI, Wagner J, Wickman E, Tian L, Li D, Poudel S, Stewart E, Li Y, Wang H, Niu M, Paul R, Reilly C, Zhou X, Dyer M, Baker S, Peng J, Yu J, Velasquez P, DeRenzo C, Krenciute G, Zhang J, Gottschalk S. Abstract 1543: Mining cancer-specific isoforms as CAR T-cell therapy targets for pediatric solid and brain tumors. Cancer Res 2021. [DOI: 10.1158/1538-7445.am2021-1543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Immunotherapy with T-cells expressing chimeric antigen receptors (CARs) holds the promise to improve outcomes for children with solid and brain tumors. However, at present, there is a limited array of targetable antigens. We posit here that targets generated by alternative splicing events (ASEs) in cancer cells present an untapped class of CAR targets since many of these are tumor-specific and overexpressed in malignant cells. Thus, we developed Cancer-Specific Isoform Miner (CSI-Miner), a pipeline to perform a comprehensive ASE analysis of pediatric cancers to discover CSIs as CAR T-cell therapy targets. We analyzed 1,938 solid and brain tumor samples collected from PCGP, TARGET, and St. Jude's real-time clinical sequencing data sets. In addition, 7,527 GTEx RNAseq samples across 31 human tissues were harmonized to prioritize exon candidates with minimal expression in normal tissue. Through CSI-Miner, we identified 40,748 highly expressed exons from the tumor's surfaceome and secretome, of which 185 were unannotated novel exons. Taking advantage of available mass-spectrometry proteome data from the Clinical Proteomic Tumor Analysis Consortium and St. Jude's proteomics facility, we validated the presence of peptides encoded by these novel exons for rhabdomyosarcoma, medulloblastoma, high-grade glioma, low-grade glioma, and ependymoma. Moreover, non-malignant mass-spectrometry data from muscle and brain samples were incorporated as negative controls. Several secretome targets were identified that adhered to the surface of cancer cells, including EDB, an oncofetal splice variant of fibronectin. EDB was expressed in a broad range of pediatric solid and brain tumors, including Ewing sarcoma and high-grade glioma. We generated T-cells expressing a 2nd generation EDB-CAR (EDB-CAR T-cells) by standard retroviral transduction. EDB-CAR T-cells recognized and killed EDB+ cancer cells in vitro and had potent antitumor activity in xenograft models, resulting in improved overall survival compared to control mice. Importantly, EDB-CAR T-cells did not induce ‘on target/off cancer' toxicities in mice, which is encouraging since EDB is identical in mice and humans. c-MET was also identified as a candidate surfaceome CAR target for rhabdomyosarcoma and melanoma. In summary, we developed CSI-Miner, an integrative analysis pipeline to discover CSIs as CAR T-cell therapy targets, comprised of 248 surfaceome and 51 secretome candidates, for pediatric solid and brain tumors. At present we have validated these CSIs by mass-spectrometry and successfully generated CAR T-cells for one of the candidates. Collectively, CSIs present an untapped class of immunotherapy targets that hold the promise to improve current CAR T-cell therapy approaches for a wide range of pediatric solid and brain tumors. A web portal has been developed supporting access and visualization of this data set to the research community.
Citation Format: Timothy I. Shaw, Jessica Wagner, Elizabeth Wickman, Liqing Tian, Dong Li, Suresh Poudel, Elizabeth Stewart, Yuxin Li, Hong Wang, Mingming Niu, Robin Paul, Colleen Reilly, Xin Zhou, Michael Dyer, Suzanne Baker, Junmin Peng, Jiyang Yu, Paulina Velasquez, Chris DeRenzo, Giedre Krenciute, Jinghui Zhang, Stephen Gottschalk. Mining cancer-specific isoforms as CAR T-cell therapy targets for pediatric solid and brain tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1543.
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Affiliation(s)
| | | | | | - Liqing Tian
- St Jude Children's Research Hospital, Memphis, TN
| | - Dong Li
- St Jude Children's Research Hospital, Memphis, TN
| | | | | | - Yuxin Li
- St Jude Children's Research Hospital, Memphis, TN
| | - Hong Wang
- St Jude Children's Research Hospital, Memphis, TN
| | - Mingming Niu
- St Jude Children's Research Hospital, Memphis, TN
| | - Robin Paul
- St Jude Children's Research Hospital, Memphis, TN
| | | | - Xin Zhou
- St Jude Children's Research Hospital, Memphis, TN
| | - Michael Dyer
- St Jude Children's Research Hospital, Memphis, TN
| | | | - Junmin Peng
- St Jude Children's Research Hospital, Memphis, TN
| | - Jiyang Yu
- St Jude Children's Research Hospital, Memphis, TN
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Gao Y, Liu M, Shi S, Niu M, Li J, Zhang J, Song F, Tian J. Prespecification of subgroup analyses and examination of treatment-subgroup interactions in cancer individual participant data meta-analyses are suboptimal. J Clin Epidemiol 2021; 138:156-167. [PMID: 34186194 DOI: 10.1016/j.jclinepi.2021.06.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 06/18/2021] [Accepted: 06/22/2021] [Indexed: 12/16/2022]
Abstract
OBJECTIVES This study aimed to explore the prespecification and conduct of subgroup analyses in cancer individual participant data meta-analyses (IPDMAs). STUDY DESIGN AND SETTING We searched PubMed, Embase.com, Cochrane Library, and Web of Science to identify IPDMAs of randomized controlled trials evaluating intervention effects for cancer. We evaluated how often cancer IPDMAs prespecify subgroup analyses and statistical approaches for examining treatment-subgroup interactions and handling continuous subgroup variables. RESULTS We included 89 IPDMAs, of which 41 (46.1%) reported a statistically significant treatment-subgroup interaction (P < 0.05) in at least one subgroup analysis. 47 (52.8%) IPDMAs prespecified methods for conducting subgroup analyses and the remaining 42 (47.2%) did not prespecify subgroup analyses. Of the 47 IPDMAs prespecified subgroup analyses, 19 performed the planned subgroup analyses, 21 added subgroup analyses, 7 reduced subgroup analyses. Eighty IPDMAs examined treatment-subgroup interactions, but 72 IPDMAs did not provide enough information to determine whether an appropriate approach that avoided aggregation bias was used. 85 IPDMAs that used continuous variables in subgroup analyses categorized continuous variables and only 1 IPDMA examined non-linear relationships. CONCLUSION Many cancer IPDMAs did not prespecify subgroup analyses, nor did they fully perform planned subgroup analyses. Lack of details for the test of treatment-subgroup interactions and examination of non-linear interactions was suboptimal.
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Affiliation(s)
- Ya Gao
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ming Liu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Shuzhen Shi
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Mingming Niu
- Evidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China
| | - Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking UnionMedical College, Beijing, China
| | - Junhua Zhang
- Evidence-Based Medicine Center, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Fujian Song
- Public Health and Health Services Research, Norwich Medical School, University of East Anglia, Norwich, UK.
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China; Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China.
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Yu K, Niu M, Wang H, Li Y, Wu Z, Zhang B, Haroutunian V, Peng J. Global Profiling of Lysine Accessibility to Evaluate Protein Structure Changes in Alzheimer's Disease. J Am Soc Mass Spectrom 2021; 32:936-945. [PMID: 33683887 PMCID: PMC8255072 DOI: 10.1021/jasms.0c00450] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The linear sequence of amino acids in a protein folds into a 3D structure to execute protein activity and function, but it is still challenging to profile the 3D structure at the proteome scale. Here, we present a method of native protein tandem mass tag (TMT) profiling of Lys accessibility and its application to investigate structural alterations in human brain specimens of Alzheimer's disease (AD). In this method, proteins are extracted under a native condition, labeled by TMT reagents, followed by trypsin digestion and peptide analysis using two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC-MS/MS). The method quantifies Lys labeling efficiency to evaluate its accessibility on the protein surface, which may be affected by protein conformations, protein modifications, and/or other molecular interactions. We systematically optimized the amount of TMT reagents, reaction time, and temperature and then analyzed protein samples under multiple conditions, including different labeling time (5 and 30 min), heat treatment, AD and normal human cases. The experiment profiled 15370 TMT-labeled peptides in 4475 proteins. As expected, the heat treatment led to extensive changes in protein conformations, with 17% of the detected proteome displaying differential labeling. Compared to the normal controls, AD brain showed different Lys accessibility of tau and RNA splicing complexes, which are the hallmarks of AD pathology, as well as proteins involved in transcription, mitochondrial, and synaptic functions. To eliminate the possibility that the observed differential Lys labeling was caused by protein level change, the whole proteome was quantified with standard TMT-LC/LC-MS/MS for normalization. Thus, this native protein TMT method enables the proteome-wide measurement of Lys accessibility, representing a straightforward strategy to explore protein structure in any biological system.
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Affiliation(s)
- Kaiwen Yu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Hong Wang
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multi-scale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Vahram Haroutunian
- Departments of Psychiatry and Neuroscience, The Alzheimer’s Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education and Clinical Center (MIRECC), James J Peters VA Medical Center, Bronx, NY 10468, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
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McEwen M, Kafri D, Chen Z, Atalaya J, Satzinger KJ, Quintana C, Klimov PV, Sank D, Gidney C, Fowler AG, Arute F, Arya K, Buckley B, Burkett B, Bushnell N, Chiaro B, Collins R, Demura S, Dunsworth A, Erickson C, Foxen B, Giustina M, Huang T, Hong S, Jeffrey E, Kim S, Kechedzhi K, Kostritsa F, Laptev P, Megrant A, Mi X, Mutus J, Naaman O, Neeley M, Neill C, Niu M, Paler A, Redd N, Roushan P, White TC, Yao J, Yeh P, Zalcman A, Chen Y, Smelyanskiy VN, Martinis JM, Neven H, Kelly J, Korotkov AN, Petukhov AG, Barends R. Removing leakage-induced correlated errors in superconducting quantum error correction. Nat Commun 2021; 12:1761. [PMID: 33741936 PMCID: PMC7979694 DOI: 10.1038/s41467-021-21982-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 02/23/2021] [Indexed: 11/30/2022] Open
Abstract
Quantum computing can become scalable through error correction, but logical error rates only decrease with system size when physical errors are sufficiently uncorrelated. During computation, unused high energy levels of the qubits can become excited, creating leakage states that are long-lived and mobile. Particularly for superconducting transmon qubits, this leakage opens a path to errors that are correlated in space and time. Here, we report a reset protocol that returns a qubit to the ground state from all relevant higher level states. We test its performance with the bit-flip stabilizer code, a simplified version of the surface code for quantum error correction. We investigate the accumulation and dynamics of leakage during error correction. Using this protocol, we find lower rates of logical errors and an improved scaling and stability of error suppression with increasing qubit number. This demonstration provides a key step on the path towards scalable quantum computing.
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Affiliation(s)
- M McEwen
- Department of Physics, University of California, Santa Barbara, CA, USA
- Google, Santa Barbara, CA, USA
| | | | - Z Chen
- Google, Santa Barbara, CA, USA
| | | | | | | | | | - D Sank
- Google, Santa Barbara, CA, USA
| | | | | | - F Arute
- Google, Santa Barbara, CA, USA
| | - K Arya
- Google, Santa Barbara, CA, USA
| | | | | | | | | | | | | | | | | | - B Foxen
- Google, Santa Barbara, CA, USA
| | | | - T Huang
- Google, Santa Barbara, CA, USA
| | - S Hong
- Google, Santa Barbara, CA, USA
| | | | - S Kim
- Google, Santa Barbara, CA, USA
| | | | | | | | | | - X Mi
- Google, Santa Barbara, CA, USA
| | - J Mutus
- Google, Santa Barbara, CA, USA
| | | | | | - C Neill
- Google, Santa Barbara, CA, USA
| | | | - A Paler
- Johannes Kepler University, Linz, Austria
- University of Texas at Dallas, Richardson, TX, USA
| | - N Redd
- Google, Santa Barbara, CA, USA
| | | | | | - J Yao
- Google, Santa Barbara, CA, USA
| | - P Yeh
- Google, Santa Barbara, CA, USA
| | | | - Yu Chen
- Google, Santa Barbara, CA, USA
| | | | - John M Martinis
- Department of Physics, University of California, Santa Barbara, CA, USA
| | - H Neven
- Google, Santa Barbara, CA, USA
| | - J Kelly
- Google, Santa Barbara, CA, USA
| | - A N Korotkov
- Google, Santa Barbara, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
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Shi J, Zhao L, Gao Y, Niu M, Yan M, Chen Y, Song Z, Ma X, Wang P, Tian J. Associating the risk of three urinary cancers with obesity and overweight: an overview with evidence mapping of systematic reviews. Syst Rev 2021; 10:58. [PMID: 33597037 PMCID: PMC7888186 DOI: 10.1186/s13643-021-01606-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 01/31/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The relationship between cancer with overweight and obesity has been extensively reported. However, the association between urinary cancers with these risk factors remains unclear, with existing reports showing conflicting findings. The current review, therefore, sought to clarify the latter association by assessing the methodological and reporting quality of existing systematic reviews on the subject. METHODS We first screened PubMed, EMBASE, and Cochrane Library databases for relevant literature and subjected the resulting articles to meta-analysis. We adopted the AMSTAR-2 and PRISMA checklists for assessing methodological and reporting quality, respectively, then performed meta-analyses to determine the relationship between incidence and mortality of three types of urinary cancers with obesity and overweight. Indirect comparisons were also done across subgroups. RESULTS All systematic reviews (SRs) were of critically low methodological quality. Seventeen SRs had minimal reporting flaws, and 11 SRs had minor reporting flaws. We found an association between obesity with an incidence of kidney (RR = 1.68, 95% CI 1.47-1.92), bladder (RR = 1.1, 95% CI 1.07-1.13), and prostate (RR = 1.02, 95% CI 0.91, 1.13) cancers. Similarly, overweight was associated with the incidence of the three types of cancer, recording RR values of 1.37 (95% CI 1.26-1.48), 1.07 (95% CI 1.03-1.1), and 1 (95% CI 0.93, 1.07) for kidney, bladder, and prostate cancers, respectively. With regard to the dose analysis, the RR of BMI (per 5 kg/m2 increase) was associated with kidney (RR = 1.24, 95% CI 1.2-1.28), bladder (RR = 1.03, 95% CI 1.02-1.05), and prostate (RR = 1.02, 95% CI 1.01, 1.03) cancers. CONCLUSIONS This comprehensive quantitative analysis provides an affirmation that overweight and obesity are strong risk factors for kidney cancer, owing to a strong association between them. Conversely, a weak association between overweight and obesity with bladder and prostate cancers confirms their status as mild risk factors for the 2 types of cancer. But due to the low quality of included SRs, the results need to be interpreted with caution. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42019119459.
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Affiliation(s)
- Jiyuan Shi
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
- Evidence-Based Medicine Centre, School of Basic Medical Sciences, Lanzhou University, Lanzhou City, 730000, China
- School of Nursing and Health, Zhengzhou University, Zhengzhou city, 450001, China
| | - Liang Zhao
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
| | - Ya Gao
- Evidence-Based Medicine Centre, School of Basic Medical Sciences, Lanzhou University, Lanzhou City, 730000, China
| | - Mingming Niu
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
| | - Meili Yan
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
| | - Yamin Chen
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
| | - Ziwei Song
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China
| | - Xueni Ma
- The Second Clinical Medical College of Lanzhou University, Lanzhou University, Lanzhou City, 730000, China
| | - Peng Wang
- School of Nursing and Health, Zhengzhou University, Zhengzhou city, 450001, China.
| | - Jinhui Tian
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou City, 730000, China.
- Evidence-Based Medicine Centre, School of Basic Medical Sciences, Lanzhou University, Lanzhou City, 730000, China.
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Yang L, Zhi S, Yang G, Qin C, Zhao W, Niu M, Zhang W, Tang W, Yan X, Zhang Y, Meng X, Lu R, Nie G. Molecular identification of FNDC5 and effect of irisin on the glucose metabolism in common carp (Cyprinus carpio L.). Gen Comp Endocrinol 2021; 301:113647. [PMID: 33166532 DOI: 10.1016/j.ygcen.2020.113647] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 09/01/2020] [Accepted: 10/06/2020] [Indexed: 12/25/2022]
Abstract
Irisin, encoded by fibronectin type III domain-containing protein 5 (FNDC5) gene, plays a role in energy expenditure and insulin sensitivity in mice. In fish, the function of irisin related to glucose metabolism is less reported. It may increase glucose utilization in fish. The aim of the present study was to characterize the regulatory role of irisin in glucose metabolism in common carp (Cyprinus carpio L.). In this study, FNDC5a and FNDC5b were isolated from common carp. The cDNA of FNDC5a and FNDC5b were 722 bp and 714 bp, encoding 221 and 207 amino acids, respectively. FNDC5a was abundantly expressed in the brain and gonad. FNDC5b was mainly expressed in brain. Different expression pattern of FNDC5a and FNDC5b under fasting/refeeding and OGTT experiment were identified. The recombinant common carp irisinA and irisinB were prepared by prokaryotic expression system. Glucose concentration was decreased in treatment with irisinA or irisinB in the in vitro and in vivo experiments. The mRNA expression levels of gluconeogenesis-related genes were significantly down-regulated, while the mRNA expression of glycolysis-related genes were significantly up-regulated after treatment with recombinant irisinA or irisinB in liver in vivo and in primary hepatocytes in vitro. Our research shows that irisin inhibits hepatic gluconeogenesis and promotes hepatic glycolysis. Taken together, this study for the first time revealed the two subtypes of FNDC5 and explored the function and mechanisms of irisinA and irisinB in fish glucose homeostasis.
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Affiliation(s)
- Liping Yang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Shaoyang Zhi
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Guokun Yang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Chaobin Qin
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Wenli Zhao
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Mingming Niu
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Wenlei Zhang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Wenyu Tang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Xiao Yan
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Yuru Zhang
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Xiaolin Meng
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Ronghua Lu
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Guoxing Nie
- College of Fisheries, Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China.
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Tian S, Niu M, Xie L, Song Q, Liu A. Diffusion-tensor imaging for differentiating uterine sarcoma from degenerative uterine fibroids. Clin Radiol 2020; 76:313.e27-313.e32. [PMID: 33358441 DOI: 10.1016/j.crad.2020.11.115] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 11/20/2020] [Indexed: 01/07/2023]
Abstract
AIM To explore the applicability of diffusion-tensor imaging (DTI) sequence quantitative parameters in differentiating uterine sarcoma (USr) from degenerative uterine fibroids (DUF). MATERIALS AND METHODS Fourteen cases of USr and 30 cases of DUF were analysed retrospectively. The diffusion-weighted imaging (DWI) and DTI images were analysed by two observers using Functool software on a ADW4.6 workstation. The images were post-processed to generate an apparent diffusion coefficient (ADC) map of DWI, ADC map of DTI (ADCT map), and fractional anisotropy (FA) map. Three regions of interest (ROI) were selected from the ADC, ADCT, and FA maps to obtain the ADC, ADCT, and FA values. The receiver operating characteristic (ROC) curves of all parameters were used to analyse and compare the diagnostic value of USr and DUF. RESULTS The ADC value, ADCT value, and FA value of USr (1.190 ± 0.262 × 10-3mm2/s, 1.165 ± 0.270 × 10-9mm2/s, 0.168 ± 0.063) were significantly lower compared to the values for DUF (1.525 ± 0.314 × 10-3mm2/s, 1.650 ± 0.332 × 10-9mm2/s, 0.254 ± 0.111; all p<0.001). The diagnostic threshold values for USr were: ADC ≤1.290 × 10-3mm2/s, ADCT ≤1.322 × 10-9mm2/s and FA ≤0.192. The corresponding sensitivities and specificities were 78.6%/90%, 96.7%/92.9%, and 86.7%/85.7%, respectively. The areas under the curve (AUC) were 0.875, 0.974, and 0.831, respectively. CONCLUSIONS DTI quantitative parameters can be used to differentiate USr from DUF. The ADCT value had the highest diagnostic efficacy.
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Affiliation(s)
- S Tian
- The First Affiliated Hospital of Dalian Medical University, Department of Radiology, Dalian, China
| | - M Niu
- The First Affiliated Hospital of Xiamen University, Department of Radiology, Xiamen, China
| | - L Xie
- GE Healthcare, MR Research, Beijing, China
| | - Q Song
- The First Affiliated Hospital of Dalian Medical University, Department of Radiology, Dalian, China
| | - A Liu
- The First Affiliated Hospital of Dalian Medical University, Department of Radiology, Dalian, China.
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Foxen B, Neill C, Dunsworth A, Roushan P, Chiaro B, Megrant A, Kelly J, Chen Z, Satzinger K, Barends R, Arute F, Arya K, Babbush R, Bacon D, Bardin JC, Boixo S, Buell D, Burkett B, Chen Y, Collins R, Farhi E, Fowler A, Gidney C, Giustina M, Graff R, Harrigan M, Huang T, Isakov SV, Jeffrey E, Jiang Z, Kafri D, Kechedzhi K, Klimov P, Korotkov A, Kostritsa F, Landhuis D, Lucero E, McClean J, McEwen M, Mi X, Mohseni M, Mutus JY, Naaman O, Neeley M, Niu M, Petukhov A, Quintana C, Rubin N, Sank D, Smelyanskiy V, Vainsencher A, White TC, Yao Z, Yeh P, Zalcman A, Neven H, Martinis JM. Demonstrating a Continuous Set of Two-Qubit Gates for Near-Term Quantum Algorithms. Phys Rev Lett 2020; 125:120504. [PMID: 33016760 DOI: 10.1103/physrevlett.125.120504] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 06/27/2020] [Accepted: 07/22/2020] [Indexed: 06/11/2023]
Abstract
Quantum algorithms offer a dramatic speedup for computational problems in material science and chemistry. However, any near-term realizations of these algorithms will need to be optimized to fit within the finite resources offered by existing noisy hardware. Here, taking advantage of the adjustable coupling of gmon qubits, we demonstrate a continuous two-qubit gate set that can provide a threefold reduction in circuit depth as compared to a standard decomposition. We implement two gate families: an imaginary swap-like (iSWAP-like) gate to attain an arbitrary swap angle, θ, and a controlled-phase gate that generates an arbitrary conditional phase, ϕ. Using one of each of these gates, we can perform an arbitrary two-qubit gate within the excitation-preserving subspace allowing for a complete implementation of the so-called Fermionic simulation (fSim) gate set. We benchmark the fidelity of the iSWAP-like and controlled-phase gate families as well as 525 other fSim gates spread evenly across the entire fSim(θ,ϕ) parameter space, achieving a purity-limited average two-qubit Pauli error of 3.8×10^{-3} per fSim gate.
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Affiliation(s)
- B Foxen
- Department of Physics, University of California, Santa Barbara, California 93106, USA
- Google Research, Santa Barbara, California 93117, USA
| | - C Neill
- Google Research, Santa Barbara, California 93117, USA
| | - A Dunsworth
- Google Research, Santa Barbara, California 93117, USA
| | - P Roushan
- Google Research, Santa Barbara, California 93117, USA
| | - B Chiaro
- Department of Physics, University of California, Santa Barbara, California 93106, USA
| | - A Megrant
- Google Research, Santa Barbara, California 93117, USA
| | - J Kelly
- Google Research, Santa Barbara, California 93117, USA
| | - Zijun Chen
- Google Research, Santa Barbara, California 93117, USA
| | - K Satzinger
- Google Research, Santa Barbara, California 93117, USA
| | - R Barends
- Google Research, Santa Barbara, California 93117, USA
| | - F Arute
- Google Research, Santa Barbara, California 93117, USA
| | - K Arya
- Google Research, Santa Barbara, California 93117, USA
| | - R Babbush
- Google Research, Santa Barbara, California 93117, USA
| | - D Bacon
- Google Research, Santa Barbara, California 93117, USA
| | - J C Bardin
- Google Research, Santa Barbara, California 93117, USA
- Department of Electrical and Computer Engineering, University of Massachusetts-Amherst, Amherst, Massachusetts 01003, USA
| | - S Boixo
- Google Research, Santa Barbara, California 93117, USA
| | - D Buell
- Google Research, Santa Barbara, California 93117, USA
| | - B Burkett
- Google Research, Santa Barbara, California 93117, USA
| | - Yu Chen
- Google Research, Santa Barbara, California 93117, USA
| | - R Collins
- Google Research, Santa Barbara, California 93117, USA
| | - E Farhi
- Google Research, Santa Barbara, California 93117, USA
| | - A Fowler
- Google Research, Santa Barbara, California 93117, USA
| | - C Gidney
- Google Research, Santa Barbara, California 93117, USA
| | - M Giustina
- Google Research, Santa Barbara, California 93117, USA
| | - R Graff
- Google Research, Santa Barbara, California 93117, USA
| | - M Harrigan
- Google Research, Santa Barbara, California 93117, USA
| | - T Huang
- Google Research, Santa Barbara, California 93117, USA
| | - S V Isakov
- Google Research, Santa Barbara, California 93117, USA
| | - E Jeffrey
- Google Research, Santa Barbara, California 93117, USA
| | - Z Jiang
- Google Research, Santa Barbara, California 93117, USA
| | - D Kafri
- Google Research, Santa Barbara, California 93117, USA
| | - K Kechedzhi
- Google Research, Santa Barbara, California 93117, USA
| | - P Klimov
- Google Research, Santa Barbara, California 93117, USA
| | - A Korotkov
- Google Research, Santa Barbara, California 93117, USA
| | - F Kostritsa
- Google Research, Santa Barbara, California 93117, USA
| | - D Landhuis
- Google Research, Santa Barbara, California 93117, USA
| | - E Lucero
- Google Research, Santa Barbara, California 93117, USA
| | - J McClean
- Google Research, Santa Barbara, California 93117, USA
| | - M McEwen
- Department of Physics, University of California, Santa Barbara, California 93106, USA
| | - X Mi
- Google Research, Santa Barbara, California 93117, USA
| | - M Mohseni
- Google Research, Santa Barbara, California 93117, USA
| | - J Y Mutus
- Google Research, Santa Barbara, California 93117, USA
| | - O Naaman
- Google Research, Santa Barbara, California 93117, USA
| | - M Neeley
- Google Research, Santa Barbara, California 93117, USA
| | - M Niu
- Google Research, Santa Barbara, California 93117, USA
| | - A Petukhov
- Google Research, Santa Barbara, California 93117, USA
| | - C Quintana
- Google Research, Santa Barbara, California 93117, USA
| | - N Rubin
- Google Research, Santa Barbara, California 93117, USA
| | - D Sank
- Google Research, Santa Barbara, California 93117, USA
| | - V Smelyanskiy
- Google Research, Santa Barbara, California 93117, USA
| | - A Vainsencher
- Google Research, Santa Barbara, California 93117, USA
| | - T C White
- Google Research, Santa Barbara, California 93117, USA
| | - Z Yao
- Google Research, Santa Barbara, California 93117, USA
| | - P Yeh
- Google Research, Santa Barbara, California 93117, USA
| | - A Zalcman
- Google Research, Santa Barbara, California 93117, USA
| | - H Neven
- Google Research, Santa Barbara, California 93117, USA
| | - J M Martinis
- Department of Physics, University of California, Santa Barbara, California 93106, USA
- Google Research, Santa Barbara, California 93117, USA
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Niu M, Ming H, Cheng LJ, Yi BF, Xia TT, Li M, Nie GX. Brevibacillus migulae sp. nov., isolated from a Yellow River sediment sample. Int J Syst Evol Microbiol 2020; 70:5693-5700. [PMID: 32931405 DOI: 10.1099/ijsem.0.004462] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Strain CFH S0501T, a novel Gram-stain-positive, aerobic, rod-shaped, endospore-forming and motile micro-organism with peritrichous flagella, was isolated from a sediment sample collected from the Yellow River in Henan Province, PR China. Optimum growth was observed at 28 °C, pH 7.0 and without NaCl. Phylogenetic analysis based on the 16S rRNA gene sequences indicated that the strain belonged to the genus Brevibacillus and was closely related to Brevibacillus centrosporus DSM 8445T and Brevibacillus ginsengisoli Gsoil 3088T (with 96.8 and 96.7 % sequence similarity, respectively). The predominant menaquinone was MK-7. Major cellular fatty acids were anteiso-C15 : 0 and iso-C15 : 0. Polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylmonomethylethanolamine, phosphatidylethanolamine, two unidentified phospholipids and an unidentified polar lipid. The cell-wall peptidoglycan was found to contain meso-diaminopimelic acid. The genome size was 5.26 Mbp with a G+C content of 49.7 mol%. The average nucleotide identity (ANI) and in silico DNA-DNAhybridization (DDH) values between CFH S0501T and the other species of the genus Brevibacillus were found to be low (ANIm <86.11 %, ANIb <70.30 % and DDH <25.00 %). Based on physiological properties, chemotaxonomic characteristics and low ANI and DDH results, strain CFH S0501T is considered to represent a novel species, for which the name Brevibacillus migulae sp. nov. is proposed. The type strain is CFH S0501T (=DSM 29940T=BCRC 80809T).
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Affiliation(s)
- Mingming Niu
- College of Fisheries, Henan Normal University, Xinxiang, 453007, PR China
| | - Hong Ming
- Synthetic Biology Engineering Lab of Henan Province, College of Life Sciences and Technology, Xinxiang Medical University, Xinxiang 453003, PR China
| | - Li-Jiao Cheng
- College of Fisheries, Henan Normal University, Xinxiang, 453007, PR China
| | - Bing-Fang Yi
- College of Fisheries, Henan Normal University, Xinxiang, 453007, PR China
| | - Ting-Ting Xia
- Synthetic Biology Engineering Lab of Henan Province, College of Life Sciences and Technology, Xinxiang Medical University, Xinxiang 453003, PR China
| | - Meng Li
- Synthetic Biology Engineering Lab of Henan Province, College of Life Sciences and Technology, Xinxiang Medical University, Xinxiang 453003, PR China
| | - Guo-Xing Nie
- College of Fisheries, Henan Normal University, Xinxiang, 453007, PR China
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Jiang RM, Li J, Wang ZQ, Shen JF, Niu M. [Primary hypertrophic osteoarthropathy with renal hypokalemia: a case report]. Zhonghua Nei Ke Za Zhi 2020; 59:720-723. [PMID: 32838506 DOI: 10.3760/cma.j.cn112138-20190918-00637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Affiliation(s)
- R M Jiang
- Department of Endocrinology, Fuyang People's Hospital of Anhui Province, Fuyang, Anhui 236003, China
| | - J Li
- Department of Endocrinology, Fuyang People's Hospital of Anhui Province, Fuyang, Anhui 236003, China
| | - Z Q Wang
- Department of Endocrinology, Fuyang People's Hospital of Anhui Province, Fuyang, Anhui 236003, China
| | - J F Shen
- Department of Endocrinology, Fuyang People's Hospital of Anhui Province, Fuyang, Anhui 236003, China
| | - M Niu
- Department of Endocrinology, Fuyang People's Hospital of Anhui Province, Fuyang, Anhui 236003, China
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Wang Z, Kavdia K, Dey KK, Pagala VR, Kodali K, Liu D, Lee DG, Sun H, Chepyala SR, Cho JH, Niu M, High AA, Peng J. High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry. J Vis Exp 2020:10.3791/61684. [PMID: 32894271 PMCID: PMC7752892 DOI: 10.3791/61684] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an expanded 16-plex TMT method has been introduced, which further increases the throughput of proteomic studies. In this manuscript, we present an optimized protocol for 16-plex TMT-based deep-proteome profiling, including protein sample preparation, enzymatic digestion, TMT labeling reaction, two-dimensional reverse-phase liquid chromatography (LC/LC) fractionation, tandem mass spectrometry (MS/MS), and computational data processing. The crucial quality control steps and improvements in the process specific for the 16-plex TMT analysis are highlighted. This multiplexed process offers a powerful tool for profiling a variety of complex samples such as cells, tissues, and clinical specimens. More than 10,000 proteins and posttranslational modifications such as phosphorylation, methylation, acetylation, and ubiquitination in highly complex biological samples from up to 16 different samples can be quantified in a single experiment, providing a potent tool for basic and clinical research.
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Affiliation(s)
- Zhen Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Kanisha Kavdia
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital
| | - Kaushik Kumar Dey
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | | | - Kiran Kodali
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital
| | - Danting Liu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Dong Geun Lee
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Huan Sun
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Surendhar Reddy Chepyala
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital
| | - Anthony A High
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital;
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital; Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital;
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Wang H, Dey KK, Chen PC, Li Y, Niu M, Cho JH, Wang X, Bai B, Jiao Y, Chepyala SR, Haroutunian V, Zhang B, Beach TG, Peng J. Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer's disease. Mol Neurodegener 2020; 15:43. [PMID: 32711556 PMCID: PMC7382148 DOI: 10.1186/s13024-020-00384-6] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 05/18/2020] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Based on amyloid cascade and tau hypotheses, protein biomarkers of different Aβ and tau species in cerebrospinal fluid (CSF) and blood/plasma/serum have been examined to correlate with brain pathology. Recently, unbiased proteomic profiling of these human samples has been initiated to identify a large number of novel AD biomarker candidates, but it is challenging to define reliable candidates for subsequent large-scale validation. METHODS We present a comprehensive strategy to identify biomarker candidates of high confidence by integrating multiple proteomes in AD, including cortex, CSF and serum. The proteomes were analyzed by the multiplexed tandem-mass-tag (TMT) method, extensive liquid chromatography (LC) fractionation and high-resolution tandem mass spectrometry (MS/MS) for ultra-deep coverage. A systems biology approach was used to prioritize the most promising AD signature proteins from all proteomic datasets. Finally, candidate biomarkers identified by the MS discovery were validated by the enzyme-linked immunosorbent (ELISA) and TOMAHAQ targeted MS assays. RESULTS We quantified 13,833, 5941, and 4826 proteins from human cortex, CSF and serum, respectively. Compared to other studies, we analyzed a total of 10 proteomic datasets, covering 17,541 proteins (13,216 genes) in 365 AD, mild cognitive impairment (MCI) and control cases. Our ultra-deep CSF profiling of 20 cases uncovered the majority of previously reported AD biomarker candidates, most of which, however, displayed no statistical significance except SMOC1 and TGFB2. Interestingly, the AD CSF showed evident decrease of a large number of mitochondria proteins that were only detectable in our ultra-deep analysis. Further integration of 4 cortex and 4 CSF cohort proteomes highlighted 6 CSF biomarkers (SMOC1, C1QTNF5, OLFML3, SLIT2, SPON1, and GPNMB) that were consistently identified in at least 2 independent datasets. We also profiled CSF in the 5xFAD mouse model to validate amyloidosis-induced changes, and found consistent mitochondrial decreases (SOD2, PRDX3, ALDH6A1, ETFB, HADHA, and CYB5R3) in both human and mouse samples. In addition, comparison of cortex and serum led to an AD-correlated protein panel of CTHRC1, GFAP and OLFM3. In summary, 37 proteins emerged as potential AD signatures across cortex, CSF and serum, and strikingly, 59% of these were mitochondria proteins, emphasizing mitochondrial dysfunction in AD. Selected biomarker candidates were further validated by ELISA and TOMAHAQ assays. Finally, we prioritized the most promising AD signature proteins including SMOC1, TAU, GFAP, SUCLG2, PRDX3, and NTN1 by integrating all proteomic datasets. CONCLUSIONS Our results demonstrate that novel AD biomarker candidates are identified and confirmed by proteomic studies of brain tissue and biofluids, providing a rich resource for large-scale biomarker validation for the AD community.
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Affiliation(s)
- Hong Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
| | - Kaushik Kumar Dey
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ping-Chung Chen
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Present address: Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA
| | - Bing Bai
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Present address: Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, 210008, Jiangsu, China
| | - Yun Jiao
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Surendhar Reddy Chepyala
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Vahram Haroutunian
- Departments of Psychiatry and Neuroscience, The Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences and Department of Pharmacological Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, AZ, 85351, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
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Bai B, Wang X, Li Y, Chen PC, Yu K, Dey KK, Yarbro JM, Han X, Lutz BM, Rao S, Jiao Y, Sifford JM, Han J, Wang M, Tan H, Shaw TI, Cho JH, Zhou S, Wang H, Niu M, Mancieri A, Messler KA, Sun X, Wu Z, Pagala V, High AA, Bi W, Zhang H, Chi H, Haroutunian V, Zhang B, Beach TG, Yu G, Peng J. Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression. Neuron 2020; 106:700. [PMID: 32437656 DOI: 10.1016/j.neuron.2020.04.031] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Niu M, Li Y, Li G, Zhou L, Luo N, Yao M, Kang W, Liu J. A longitudinal study on α-synuclein in plasma neuronal exosomes as a biomarker for Parkinson's disease development and progression. Eur J Neurol 2020; 27:967-974. [PMID: 32150777 DOI: 10.1111/ene.14208] [Citation(s) in RCA: 94] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Accepted: 03/05/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE The identification of reliable diagnostic and prognostic biomarkers for Parkinson's disease (PD) is urgently needed. Here, we explored the potential use of α-synuclein (α-syn) in plasma neuronal exosomes as a biomarker for early PD diagnosis and disease progression. METHODS This study included both cross-sectional and longitudinal designs. The subjects included 36 patients with early-stage PD, 17 patients with advanced PD, 20 patients with idiopathic rapid eye movement sleep behavior disorder and 21 healthy controls (HCs). α-syn levels were measured by electrochemiluminescence immunoassay. A subgroup of patients with early-stage PD (n = 18) participated in a follow-up examination with repeated blood collection and clinical assessments after an average of 22 months. RESULTS The α-syn levels in plasma neuronal exosomes were significantly higher in patients with early-stage PD compared with HCs (P = 0.007). Differences in α-syn levels between patients with idiopathic rapid eye movement sleep behavior disorder and HCs did not reach statistical significance (P = 0.08). In addition, Spearman correlation analysis revealed that neuronal exosomal α-syn concentrations were correlated with Movement Disorders Society Unified Parkinson's Disease Rating Scale III/(I + II + III) scores, Non-Motor Symptom Questionnaire scores and Sniffin' Sticks 16-item test scores of patients with PD (P < 0.05). After a mean follow-up of 22 months in patients with early-stage PD, a Cox regression analysis adjusted for age and gender showed that longitudinally increased α-syn rather than baseline α-syn levels were associated with higher risk for motor symptom progression in PD (P = 0.039). CONCLUSIONS Our results suggested that α-syn in plasma neuronal exosomes may serve as a biomarker to aid early diagnosis of PD and also as a prognostic marker for PD progression.
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Affiliation(s)
- M Niu
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Y Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - G Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - L Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - N Luo
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - M Yao
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - W Kang
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.,Ruijin Hospital North affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - J Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
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Bai B, Wang X, Li Y, Chen PC, Yu K, Dey KK, Yarbro JM, Han X, Lutz BM, Rao S, Jiao Y, Sifford JM, Han J, Wang M, Tan H, Shaw TI, Cho JH, Zhou S, Wang H, Niu M, Mancieri A, Messler KA, Sun X, Wu Z, Pagala V, High AA, Bi W, Zhang H, Chi H, Haroutunian V, Zhang B, Beach TG, Yu G, Peng J. Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression. Neuron 2020; 105:975-991.e7. [PMID: 31926610 PMCID: PMC7318843 DOI: 10.1016/j.neuron.2019.12.015] [Citation(s) in RCA: 239] [Impact Index Per Article: 59.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 11/11/2019] [Accepted: 12/10/2019] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.
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Affiliation(s)
- Bing Bai
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
| | - Yuxin Li
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Ping-Chung Chen
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Kaiwen Yu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Kaushik Kumar Dey
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jay M Yarbro
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Xian Han
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Brianna M Lutz
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Shuquan Rao
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Yun Jiao
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jeffrey M Sifford
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jonghee Han
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Minghui Wang
- Departments of Psychiatry and Neuroscience, The Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Haiyan Tan
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Timothy I Shaw
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Suiping Zhou
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hong Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Mingming Niu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Ariana Mancieri
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Kaitlynn A Messler
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xiaojun Sun
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Vishwajeeth Pagala
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Anthony A High
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Wenjian Bi
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hui Zhang
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Vahram Haroutunian
- Departments of Psychiatry and Neuroscience, The Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences and Department of Pharmacological Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Gang Yu
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA; Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.
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Zhao W, Qin C, Yang G, Yan X, Meng X, Yang L, Lu R, Deng D, Niu M, Nie G. Expression of glut2 in response to glucose load, insulin and glucagon in grass carp (Ctenophcuyngodon idellus). Comp Biochem Physiol B Biochem Mol Biol 2019; 239:110351. [PMID: 31518684 DOI: 10.1016/j.cbpb.2019.110351] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Revised: 09/03/2019] [Accepted: 09/06/2019] [Indexed: 12/20/2022]
Abstract
Generally, fish are thought to have a limited ability to utilize carbohydrate. Postprandial blood glucose is cleared sluggishly in fish, resulting in prolonged hyperglycemia. Facilitative glucose transporters (GLUTs) play an important role in glucose utilization. In the present study, the expression levels of glut2 in different tissues were detected in grass carp. Furthermore, the effects of oral glucose administration on glut2 mRNA expression in the liver, intestine and kidney were investigated, and we also evaluated the response of glut2 mRNA to insulin and glucagon in the primary hepatocytes of grass carp. The expression level of glut2 mRNA was highest in the liver, followed by the intestine and kidney, but lower in other tissues. The result of glucose tolerance test (GTT) showed that serum glucose reached the highest level at 3 h after GTT and recovered to the basic level at 6 h. The glut2 mRNA in the intestine was up-regulated at 1 h after GTT. However, the glut2 mRNA expression in the liver of grass carp was unchanged after GTT for 1, 3, 6 h, and even decreased at 12 h after GTT. In addition, the expression of glut2 mRNA in the primary hepatocytes was enhanced by insulin and glucagon at 3 h post treatment. These results suggested that glut2 expression in the liver of grass carp was sensitive to insulin and glucagon, but not blood glucose. The up-regulation of glut2 by these hormones might be involved in the bi-directional transportation of glucose in the liver.
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Affiliation(s)
- Wenli Zhao
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Chaobin Qin
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China.
| | - Guokun Yang
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Xiao Yan
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Xiaolin Meng
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Liping Yang
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Ronghua Lu
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Dapeng Deng
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Mingming Niu
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China
| | - Guoxing Nie
- Engineering Technology Research Center of Henan Province for Aquatic Animal Cultivation, College of Fisheries, Henan Normal University, No. 46 Jianshe Road, Xinxiang 453007, PR China.
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Sun X, Xiong Y, Su P, Zhu P, Niu M, Zhou D. A Non-coding RNA Sequence Alignment Algorithm Based on Improved Covariance Model. Int J Bioautomation 2019. [DOI: 10.7546/ijba.2019.23.3.000720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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49
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Wang H, Diaz AK, Shaw TI, Li Y, Niu M, Cho JH, Paugh BS, Zhang Y, Sifford J, Bai B, Wu Z, Tan H, Zhou S, Hover LD, Tillman HS, Shirinifard A, Thiagarajan S, Sablauer A, Pagala V, High AA, Wang X, Li C, Baker SJ, Peng J. Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes. Nat Commun 2019; 10:3718. [PMID: 31420543 PMCID: PMC6697699 DOI: 10.1038/s41467-019-11661-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Accepted: 07/19/2019] [Indexed: 12/11/2022] Open
Abstract
High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1, analyzing 13,860 proteins and 30,431 phosphosites by mass spectrometry. Systems biology approaches identify numerous master regulators, including 41 kinases and 23 transcription factors. Pathway activity computation and mouse survival indicate the NTRK1 mutation induces a higher activation of AKT downstream targets including MYC and JUN, drives a positive feedback loop to up-regulate multiple other RTKs, and confers higher oncogenic potency than the PDGFRA mutation. A mini-gRNA library CRISPR-Cas9 validation screening shows 56% of tested master regulators are important for the viability of NTRK-driven HGG cells, including TFs (Myc and Jun) and metabolic kinases (AMPKa1 and AMPKa2), confirming the validity of the multiomics integrative approaches, and providing novel tumor vulnerabilities.
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Affiliation(s)
- Hong Wang
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - Alexander K Diaz
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Timothy I Shaw
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Yuxin Li
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Mingming Niu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ji-Hoon Cho
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Barbara S Paugh
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Yang Zhang
- Department of Tumor Cell Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jeffrey Sifford
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Bing Bai
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, 210008, China
| | - Zhiping Wu
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Haiyan Tan
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Suiping Zhou
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Laura D Hover
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Heather S Tillman
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Abbas Shirinifard
- Department of Information Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Suresh Thiagarajan
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Andras Sablauer
- Department of Information Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Vishwajeeth Pagala
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Anthony A High
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Chunliang Li
- Department of Tumor Cell Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Suzanne J Baker
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
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Xiong Y, Sun X, Zhu P, Niu M, Su P. Lysing Agents for Characteristic Polluting Microorganisms in Jet Fuels. Int J Bioautomation 2019. [DOI: 10.7546/ijba.2019.23.2.000679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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