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Xiao W, Fu Y, Tang L. Primary caruncle and eyelid amyloidosis. J Fr Ophtalmol 2024; 47:104036. [PMID: 38377841 DOI: 10.1016/j.jfo.2023.104036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 09/09/2023] [Indexed: 02/22/2024]
Affiliation(s)
- W Xiao
- Zhongshan Ophthalmic Center, 510060 Guangzhou, China.
| | - Y Fu
- Zhongshan Ophthalmic Center, 510060 Guangzhou, China
| | - L Tang
- Zhongshan Ophthalmic Center, 510060 Guangzhou, China
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2
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Wei P, Lamont B, He T, Xue W, Wang PC, Song W, Zhang R, Keyhani AB, Zhao S, Lu W, Dong F, Gao R, Yu J, Huang Y, Tang L, Lu K, Ma J, Xiong Z, Chen L, Wan N, Wang B, He W, Teng M, Dian Y, Wang Y, Zeng L, Lin C, Dai M, Zhou Z, Xiao W, Yan Z. Vegetation-fire feedbacks increase subtropical wildfire risk in scrubland and reduce it in forests. J Environ Manage 2024; 351:119726. [PMID: 38052142 DOI: 10.1016/j.jenvman.2023.119726] [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] [Received: 08/02/2023] [Revised: 11/20/2023] [Accepted: 11/25/2023] [Indexed: 12/07/2023]
Abstract
Climate dictates wildfire activity around the world. But East and Southeast Asia are an apparent exception as fire-activity variation there is unrelated to climatic variables. In subtropical China, fire activity decreased by 80% between 2003 and 2020 amid increased fire risks globally. Here, we assessed the fire regime, vegetation structure, fuel flammability and their interactions across subtropical Hubei, China. We show that tree basal area (TBA) and fuel flammability explained 60% of fire-frequency variance. Fire frequency and fuel flammability, in turn, explained 90% of TBA variance. These results reveal a novel system of scrubland-forest stabilized by vegetation-fire feedbacks. Frequent fires promote the persistence of derelict scrubland through positive vegetation-fire feedbacks; in forest, vegetation-fire feedbacks are negative and suppress fire. Thus, we attribute the decrease in wildfire activity to reforestation programs that concurrently increase forest coverage and foster negative vegetation-fire feedbacks that suppress wildfire.
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Affiliation(s)
- P Wei
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - B Lamont
- Ecology Section, School of Molecular and Life Sciences, Curtin University, Perth, WA 6845, Australia.
| | - T He
- College of Science Engineering & Education, Murdoch University, Murdoch, WA 6150, Australia.
| | - W Xue
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - P C Wang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - W Song
- College of Agronomy, Northwest Agriculture & Forestry University, Xianyang, 712100, China.
| | - R Zhang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - A B Keyhani
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - S Zhao
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - W Lu
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - F Dong
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - R Gao
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - J Yu
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Y Huang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - L Tang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - K Lu
- Hubei Forestry Survey and Design Institute, East Lake Science and Technology, District, Wuhan, 430074, Hubei, China.
| | - J Ma
- Hubei Forestry Survey and Design Institute, East Lake Science and Technology, District, Wuhan, 430074, Hubei, China.
| | - Z Xiong
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - L Chen
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - N Wan
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - B Wang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - W He
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - M Teng
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Y Dian
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Y Wang
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - L Zeng
- Key Laboratory of Forest Ecology and Environment, Chinese Academy of Forestry, Beijing, 100091, China.
| | - C Lin
- Hubei Forestry Survey and Design Institute, East Lake Science and Technology, District, Wuhan, 430074, Hubei, China.
| | - M Dai
- Hubei Forestry Survey and Design Institute, East Lake Science and Technology, District, Wuhan, 430074, Hubei, China.
| | - Z Zhou
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - W Xiao
- Key Laboratory of Forest Ecology and Environment, Chinese Academy of Forestry, Beijing, 100091, China.
| | - Z Yan
- Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
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Jiao Y, Xu R, Xiao W, Wang Y, Dong SQ. [Femtosecond laser assisted cataract surgery in a complicated cataract patient with reverse implantable collamer len: a case report]. Zhonghua Yan Ke Za Zhi 2023; 59:1038-1041. [PMID: 38061905 DOI: 10.3760/cma.j.cn112142-20230811-00036] [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: 12/18/2023]
Abstract
The patient is a 33-year-old female who, 11 years ago, underwent bilateral posterior chamber phakic intraocular lens (pIOL) implantation due to myopia. She presented with a 2-year history of declining vision in her right eye and sought medical attention. She received femtosecond laser-assisted cataract surgery combined with pIOL extraction. Anterior segment optical coherence tomography and ultrasound biomicroscopy both showed an inverted pIOL in the right eye. Good visual results were achieved, and there were no complications during the six-month follow-up.
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Affiliation(s)
- Y Jiao
- Aier Eye Hospital of Wuhan University, Wuhan 430063, China
| | - R Xu
- Aier Eye Hospital of Wuhan University, Wuhan 430063, China
| | - W Xiao
- Aier Eye Hospital of Wuhan University, Wuhan 430063, China
| | - Y Wang
- Aier Eye Hospital of Wuhan University, Wuhan 430063, China
| | - S Q Dong
- Aier Eye Hospital of Wuhan University, Wuhan 430063, China
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Gregory DJ, Han F, Li P, Gritsenko M, Kyle J, Riley FE, Chavez D, Yotova V, Sindeaux RH, Hawash MBF, Xu F, Hung LY, Hayden DL, Tompkins RG, Lanford RE, Kobzik L, Hellman J, Jacobs JM, Barreiro LB, Xiao W, Warren HS. Multi-Omic blood analysis reveals differences in innate inflammatory sensitivity between species. medRxiv 2023:2023.11.30.23299243. [PMID: 38076828 PMCID: PMC10705660 DOI: 10.1101/2023.11.30.23299243] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Vertebrates differ greatly in responses to pro-inflammatory agonists such as bacterial lipopolysaccharide (LPS), complicating use of animal models to study human sepsis or inflammatory disorders. We compared transcriptomes of resting and LPS-exposed blood from six LPS-sensitive species (rabbit, pig, sheep, cow, chimpanzee, human) and four LPS-resilient species (mice, rats, baboon, rhesus), as well as plasma proteomes and lipidomes. Unexpectedly, at baseline, sensitive species already had enhanced expression of LPS-responsive genes relative to resilient species. After LPS stimulation, maximally different genes in resilient species included genes that detoxify LPS, diminish bacterial growth, discriminate sepsis from SIRS, and play roles in autophagy and apoptosis. The findings reveal the molecular landscape of species differences in inflammation, and may inform better selection of species for pre-clinical models.
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Affiliation(s)
- David J. Gregory
- Department of Pediatrics, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Feifei Han
- Harvard Medical School, Boston, MA, USA
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Peng Li
- Harvard Medical School, Boston, MA, USA
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Marina Gritsenko
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, USA
| | - Jennifer Kyle
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, USA
| | - Frank E. Riley
- Department of Pediatrics, Massachusetts General Hospital, Boston, MA, USA
| | - Deborah Chavez
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio TX, USA
| | - Vania Yotova
- Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
| | | | - Mohamed B. F. Hawash
- Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
- Department of Biochemistry, University of Montréal, Montréal, Québec, Canada
| | - Fengyun Xu
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, USA
| | - Li-Yuan Hung
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Douglas L. Hayden
- Harvard Medical School, Boston, MA, USA
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ron G. Tompkins
- Harvard Medical School, Boston, MA, USA
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Robert E. Lanford
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio TX, USA
| | - Lester Kobzik
- Program in Molecular and Integrative Physiological Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Judith Hellman
- Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan M. Jacobs
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland WA, USA
| | - Luis B. Barreiro
- Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
- Department of Biochemistry, University of Montréal, Montréal, Québec, Canada
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL, USA
- Committee on Immunology, University of Chicago, Chicago, IL, USA
| | - Wenzhong Xiao
- Harvard Medical School, Boston, MA, USA
- Department of Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - H. Shaw Warren
- Department of Pediatrics, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA
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Okamoto R, Xiao W, Fukasawa H, Hirata S, Sankai T, Masuyama H, Otsuki J. Aggregated chromosomes/chromatin transfer: a novel approach for mitochondrial replacement with minimal mitochondrial carryover: the implications of mouse experiments for human aggregated chromosome transfer. Mol Hum Reprod 2023; 29:gaad043. [PMID: 38039159 DOI: 10.1093/molehr/gaad043] [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: 08/30/2023] [Revised: 11/01/2023] [Indexed: 12/03/2023] Open
Abstract
Nuclear transfer techniques, including spindle chromosome complex (SC) transfer and pronuclear transfer, have been employed to mitigate mitochondrial diseases. Nevertheless, the challenge of mitochondrial DNA (mtDNA) carryover remains unresolved. Previously, we introduced a method for aggregated chromosome (AC) transfer in human subjects, offering a potential solution. However, the subsequent rates of embryonic development have remained unexplored owing to legal limitations in Japan, and animal studies have been hindered by a lack of AC formation in other species. Building upon our success in generating ACs within mouse oocytes via utilization of the phosphodiesterase inhibitor 3-isobutyl 1-methylxanthine (IBMX), this study has established a mouse model for AC transfer. Subsequently, a comparative analysis of embryo development rates and mtDNA carryover between AC transfer and SC transfer was conducted. Additionally, the mitochondrial distribution around SC and AC structures was investigated, revealing that in oocytes at the metaphase II stage, the mitochondria exhibited a relatively concentrated arrangement around the spindle apparatus, while the distribution of mitochondria in AC-formed oocytes appeared to be independent of the AC position. The AC transfer approach produced a marked augmentation in rates of fertilization, embryo cleavage, and blastocyst formation, especially as compared to scenarios without AC transfer in IBMX-treated AC-formed oocytes. No significant disparities in fertilization and embryo development rates were observed between AC and SC transfers. However, relative real-time PCR analyses revealed that the mtDNA carryover for AC transfers was one-tenth and therefore significantly lower than that of SC transfers. This study successfully accomplished nuclear transfers with ACs in mouse oocytes, offering an insight into the potential of AC transfers as a solution to heteroplasmy-related challenges. These findings are promising in terms of future investigation with human oocytes, thus advancing AC transfer as an innovative approach in the field of human nuclear transfer methodology.
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Affiliation(s)
- R Okamoto
- Department of Obstetrics and Gynecology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Kita, Okayama, Japan
| | - W Xiao
- Department of Applied Animal Science, Graduate School of Environmental, Life, Natural Science and Technology, Okayama University, Kita, Okayama, Japan
| | - H Fukasawa
- Department of Obstetrics and Gynecology, Faculty of Medicine, University of Yamanashi, Chuo, Yamanashi, Japan
| | - S Hirata
- Department of Obstetrics and Gynecology, Faculty of Medicine, University of Yamanashi, Chuo, Yamanashi, Japan
| | - T Sankai
- Tsukuba Primate Research Center, National Institutes of Biomedical Innovation, Health and Nutrition, Tsukuba, Ibaraki, Japan
| | - H Masuyama
- Department of Obstetrics and Gynecology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Kita, Okayama, Japan
| | - J Otsuki
- Department of Applied Animal Science, Graduate School of Environmental, Life, Natural Science and Technology, Okayama University, Kita, Okayama, Japan
- Assisted Reproductive Technology Center, Okayama University, Kita, Okayama, Japan
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Jing S, Dai Z, Wu Y, Liu X, Ren T, Liu X, Zhang L, Fu J, Chen X, Xiao W, Wang H, Huang Y, Qu Y, Wang W, Gu X, Ma L, Zhang S, Yu Y, Li L, Han Z, Su X, Qiao Y, Wang C. Prevalence and influencing factors of depressive and anxiety symptoms among hospital-based healthcare workers during the surge period of the COVID-19 pandemic in the Chinese mainland: a multicenter cross-sectional study. QJM 2023; 116:911-922. [PMID: 37561096 DOI: 10.1093/qjmed/hcad188] [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] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/06/2023] [Indexed: 08/11/2023] Open
Abstract
BACKGROUND From November 2022 to February 2023, the Chinese mainland experienced a surge in COVID-19 infection and hospitalization, and the hospital-based healthcare workers (HCWs) might suffer serious psychological crisis during this period. This study aims to assess the depressive and anxiety symptoms among HCWs during the surge of COVID-19 pandemic and to provide possible reference on protecting mental health of HCWs in future infectious disease outbreaks. METHODS A multicenter cross-sectional study was carried out among hospital-based HCWs in the Chinese mainland from 5 January to 9 February 2023. The PHQ-9 (nine-item Patient Health Questionnaire) and GAD-7 (seven-item Generalized Anxiety Disorder Questionnaire) were used to measure depressive and anxiety symptoms. Ordinal logistic regression analysis was performed to identify influencing factors. RESULTS A total of 6522 hospital-based HCWs in the Chinse mainland were included in this survey. The prevalence of depressive symptoms among the HCWs was 70.75%, and anxiety symptoms was 47.87%. The HCWs who perceived higher risk of COVID-19 infection and those who had higher work intensity were more likely to experience depressive and anxiety symptoms. Additionally, higher levels of mindfulness, resilience and perceived social support were negatively associated with depressive and anxiety symptoms. CONCLUSION This study revealed that a high proportion of HCWs in the Chinese mainland suffered from mental health disturbances during the surge of the COVID-19 pandemic. Resilience, mindfulness and perceived social support are important protective factors of HCWs' mental health. Tailored interventions, such as mindfulness practice, should be implemented to alleviate psychological symptoms of HCWs during the COVID-19 pandemic or other similar events in the future.
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Affiliation(s)
- S Jing
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Z Dai
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Y Wu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - X Liu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - T Ren
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - X Liu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - L Zhang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - J Fu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - X Chen
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - W Xiao
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - H Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Y Huang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Y Qu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - W Wang
- School of Nursing, Jining Medical University, Jining, Shandong, China
| | - X Gu
- Affiliated Tumor Hospital, Xinjiang Medical University, Urumqi, China
| | - L Ma
- Public Health School, Dalian Medical University, Dalian, China
| | - S Zhang
- Henan Cancer Hospital, Affiliate Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Y Yu
- The First Affiliated Hospital of Baotou Medical College, Baotou, Inner Mongolia Autonomous Region, China
| | - L Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangdong, China
| | - Z Han
- China Foreign Affairs University, Beijing, China
| | - X Su
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Y Qiao
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Epidemiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - C Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- National Clinical Research Center for Respiratory Diseases, Beijing, China
- Chinese Academy of Engineering, Beijing, China
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Seo A, Xiao W, Gjyshi O, Court K, Napravnik TC, Venkatesan A, Lynn EJ, Sammouri J, Colbert L, Jhingran A, Joyner MM, Lin LL, Gillison M, Klopp AH. HPV Circulating Cell-Free DNA Kinetics in Cervical Cancer Patients Undergoing Definitive Chemoradiation. Int J Radiat Oncol Biol Phys 2023; 117:S8-S9. [PMID: 37784579 DOI: 10.1016/j.ijrobp.2023.06.218] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) The human papilloma virus (HPV) is a significant cause of cervical cancer and viral DNA can be detected in the blood of patients with cervical cancer (cfHPV-DNA). We hypothesized that detecting HPV cfDNA before, during and after chemoradiation (CRT) could provide insights into disease extent, clinical staging, and treatment response. MATERIALS/METHODS Forty-seven patients with cervical cancer were enrolled on this study between 2017 and 2022, either as part of a standard-of-care (SOC) treatment banking protocol (33 patients) or as part of a clinical trial combining a therapeutic HPV vaccine (PDS0101; Immunocerv, 14 patients). Longitudinal plasma samples were collected from each patient as baseline, during week 1, 3 or 5 of CRT. cfHPV-DNA was quantified using droplet digital PCR targeting the HPV E6/E7 oncogenes of 13 high-risk types based on analysis of cervical tumor genotype (AmpFire). Clinical covariates, including FIGO stage, primary tumor size, and treatment response were studied using appropriate statistical tests. RESULTS All 47 patients had detectable HPV cfDNA during CRT with 38 out of 47 having HPV type 16 detected. The median cfDNA at baseline was 24.5 copies/mL, with a range of 0 to 157,638 copies/mL. Of the 35 patients with at least three measurements, 20 (57%) had peak cfDNA counts at week 3, and 30 out of 35 showed a decline in cfDNA counts at week 5 compared to week 3. The proportion of patients who cleared cfDNA (<16 copies/mL) increased with each week of CRT, reaching 75% at week 5. Baseline cfDNA counts were associated with para-aortic nodal involvement (p<0.0001) but not with FIGO stage or gross tumor volume. A greater proportion of patients treated with therapeutic HPV-directed vaccine had clearance of cfDNA counts as compared to those treated with SOC (at week 3, 38% vs 5%, P = 0.02 and week 5, 79% vs 22%, P = 0.0054) CONCLUSION: HPV cfDNA levels change dynamically throughout definitive CRT and peak during the first 3 weeks for the majority of patients. Treatment with a therapeutic HPV vaccine was associated with a more rapid decline in cfHPV DNA. Further analysis of cfDNA kinetics could provide valuable information on the relationship between cfDNA levels, treatment response, and clinical outcomes.
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Affiliation(s)
- A Seo
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - W Xiao
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - O Gjyshi
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - K Court
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - T Cisneros Napravnik
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - A Venkatesan
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - E J Lynn
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - J Sammouri
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - L Colbert
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - A Jhingran
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - M M Joyner
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - L L Lin
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - M Gillison
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - A H Klopp
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
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8
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Nääs A, Li P, Ahlm C, Aurelius E, Järhult JD, Schliamser S, Studahl M, Xiao W, Bergquist J, Westman G. Temporal pathway analysis of cerebrospinal fluid proteome in herpes simplex encephalitis. Infect Dis (Lond) 2023; 55:694-705. [PMID: 37395107 DOI: 10.1080/23744235.2023.2230281] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 06/20/2023] [Accepted: 06/21/2023] [Indexed: 07/04/2023] Open
Abstract
OBJECTIVES We examined the temporal changes of the CSF proteome in patients with herpes simplex encephalitis (HSE) during the course of the disease, in relation to anti-N-methyl-D-aspartate receptor (NMDAR) serostatus, corticosteroid treatment, brain MRI and neurocognitive performance. METHODS Patients were retrospectively included from a previous prospective trial with a pre-specified CSF sampling protocol. Mass spectrometry data of the CSF proteome were processed using pathway analysis. RESULTS We included 48 patients (110 CSF samples). Samples were grouped based on time of collection relative to hospital admission - T1: ≤ 9 d, T2: 13-28 d, T3: ≥ 68 d. At T1, a strong multi-pathway response was seen including acute phase response, antimicrobial pattern recognition, glycolysis and gluconeogenesis. At T2, most pathways activated at T1 were no longer significantly different from T3. After correction for multiplicity and considering the effect size threshold, 6 proteins were significantly less abundant in anti-NMDAR seropositive patients compared to seronegative: procathepsin H, heparin cofactor 2, complement factor I, protein AMBP, apolipoprotein A1 and polymeric immunoglobulin receptor. No significant differences in individual protein levels were found in relation to corticosteroid treatment, size of brain MRI lesion or neurocognitive performance. CONCLUSIONS We show a temporal change in the CSF proteome in HSE patients during the course of the disease. This study provides insight into quantitative and qualitative aspects of the dynamic pathophysiology and pathway activation patterns in HSE and prompts for future studies on the role of apolipoprotein A1 in HSE, which has previously been associated with NMDAR encephalitis.
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Affiliation(s)
- Anja Nääs
- Department of Medical Sciences, Section of Infectious Diseases, Uppsala University, Uppsala, Sweden
| | - Peng Li
- ME/CFS Collaborative Research Center at Harvard, Massachusetts General Hospital, Boston, USA
| | - Clas Ahlm
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Elisabeth Aurelius
- Unit of Infectious Diseases, Department of Medicine, Karolinska Institutet, Department of Infectious Diseases, Karolinska University Hospital, Solna, Sweden
| | - Josef D Järhult
- Department of Medical Sciences, Zoonosis Science Center, Uppsala University, Uppsala, Sweden
| | - Silvia Schliamser
- Division of Infection Medicine, Department of Clinical Sciences, Lund University, Skane University Hospital, Lund, Sweden
| | - Marie Studahl
- Department of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy at the Gothenburg University, Gothenburg, Sweden
- Region Västra Götaland, Department of Infectious Diseases, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Wenzhong Xiao
- ME/CFS Collaborative Research Center at Harvard, Massachusetts General Hospital, Boston, USA
| | - Jonas Bergquist
- Department of Chemistry, Analytical Chemistry and Neurochemistry, Biomedical Center and The Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Collaborative Research Centre at Uppsala University, Uppsala, Sweden
| | - Gabriel Westman
- Department of Medical Sciences, Section of Infectious Diseases, Uppsala University, Uppsala, Sweden
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9
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Tian X, Huang XX, Zhang ZT, Wei PJ, Wang QX, Chang H, Xiao W, Gao Y. Long-Term Outcome of Rectal Cancer Patients Treated by High-Dose Radiotherapy and Concurrent Chemotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e345. [PMID: 37785200 DOI: 10.1016/j.ijrobp.2023.06.2411] [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: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To explore the therapeutic efficacy and adverse effects of high-dose radiotherapy concurrently with chemotherapy in treating patients with non-metastatic rectal cancer. MATERIALS/METHODS Patients were enrolled if they were diagnosed with stage I-III rectal adenocarcinoma, refused surgery and received high-dose pelvic radiotherapy and concurrent chemotherapy instead. Their clinical data were retrospectively analyzed for calculating local control and survival rates. Treatment related toxicities was evaluated according to the Common Terminology Criteria for Adverse Events (version 5.0). RESULTS Between April 2006 and February 2021, a total of 93 patients in our medical center were eligible for this study, with a median age of 61 (range, 21-84) years. Of those, 86 (92.5%) patients had tumors located within 5 cm of the anal verge. There were 8 (8.6%), 30 (32.3%) and 55 (59.1%) patients diagnosed with stage I, II and III, respectively. All patients received fluorouracil-based chemotherapy (single-agent fluorouracil or FOLFOX regimen). The irradiation techniques included three-dimensional conformal and intensity-modulated radiation therapy. The median total radiation dose for gross tumor volume (GTV) was 80 (range, 60-90) Gy. The 15 (16.1%) patients refusing surgery before treatment received one course of radiation (60-70 Gy/30-35 Fr). And a 2-course radiation (Course 1, 45-50 Gy/25 Fr; Course 2: 24-40 Gy/12-20 Fr) were given to the 78 (83.9%) patients who failed to achieve clinical complete remission (cCR) after neoadjuvant chemoradiotherapy but still refused surgery, with a median interval of 79 (range, 35-195) days. The median follow-up duration was 66 (range, 10-161) months. The 3- and 5-year overall survival (OS) rates for all patients were 90.5% and 72.7%, respectively. The clinical complete remission rate at the end of chemoradiotherapy was 69.9%. Colostomy was performed in the 14 patients whose rectal tumor did not attain cCR or progressed. There was no grade 4/5 severe acute toxicity. No patient suffered from intestinal perforation. Only one patient developed anal stenosis. Because of rectal bleeding, blood transfusion was performed in 7 patients, and one patient underwent an enterostomy. CONCLUSION High-dose radiotherapy concurrent with chemotherapy brought encouraging survival outcomes, satisfactory organ preservation and acceptable short- and long-term side effects. It might be a safe and non-invasive alternative to abdominoperineal resection in rectal cancer patients refusing or unsuitable for surgery, especially for those with a low-position tumor.
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Affiliation(s)
- X Tian
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - X X Huang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Z T Zhang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - P J Wei
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Q X Wang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - H Chang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - W Xiao
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Y Gao
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
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10
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Qi CW, Li Q, Xiao W, Luan ZY. [Autoimmune hemolysis as the initial manifestation in simultaneous pancreatic cancer and diffuse large B-cell lymphoma with hemophagocyticlymphohistocytosis:a case report]. Zhonghua Nei Ke Za Zhi 2023; 62:855-859. [PMID: 37394857 DOI: 10.3760/cma.j.cn112138-20220624-00477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Affiliation(s)
- C W Qi
- Department of Hepatopathy, Taizhou People's Hospital, Taizhou 225300, China
| | - Q Li
- Department of Hematology, Taizhou People's Hospital, Taizhou 225300, China
| | - W Xiao
- Department of Pathology, Taizhou People's Hospital, Taizhou 225300, China
| | - Z Y Luan
- Department of Docimology, Taizhou People's Hospital, Taizhou 225300, China
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11
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Łabaj PP, Dopazo J, Xiao W, Kreil DP. Editorial: Critical assessment of massive data analysis (CAMDA) annual conference 2021. Front Genet 2023; 14:1154398. [PMID: 36873943 PMCID: PMC9978925 DOI: 10.3389/fgene.2023.1154398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 02/06/2023] [Indexed: 02/18/2023] Open
Affiliation(s)
- Paweł P Łabaj
- Małopolska Centre of Biotechnology, Jagiellonian University, Kraków, Lesser Poland, Poland
| | - Joaquin Dopazo
- Computational Medicine Platform, Andalusian Public Foundation Progress and Health-FPS, Sevilla, Spain.,Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, Sevilla, Spain
| | - Wenzhong Xiao
- Genome Technology Center, School of Medicine, Stanford University, Palo Alto, CA, United States.,Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - David P Kreil
- Department of Biotechnology, Boku University Vienna, Vienna, Austria
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12
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Liu Q, Qin G, Xiang T, Xiao W, Zhao Y, Pang Y. Laparoscopic radical resection for rectal cancer in a patient with uncorrected truncus arteriosus type IV: A case report. Rev Esp Anestesiol Reanim (Engl Ed) 2023; 70:56-59. [PMID: 36621567 DOI: 10.1016/j.redare.2021.05.022] [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] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/23/2021] [Indexed: 01/07/2023]
Abstract
Persistent truncus arteriosus is a rare congenital heart malformation which if not corrected, results in the death of about 50% of the patients, while fewer than 20% of the patients survive the first year of life. Here, we report the successful anesthetic management of an adult patient with uncorrected truncus arteriosus who presented for the laparoscopic radical resection of rectal cancer.
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Affiliation(s)
- Q Liu
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
| | - G Qin
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - T Xiang
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - W Xiao
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Y Zhao
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
| | - Y Pang
- Department of Anesthesiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China
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13
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Zhang Z, Wu J, Wang Q, Huang X, Tian X, Chang H, Zeng Z, Xiao W, Li R, Gao Y. Neoadjuvant Chemoradiotherapy Significantly Improved R0 Resection Rate in Unresectable Locally Advanced Colon Cancer: The Initial Analysis from the Randomized Controlled Phase 3 Trial. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1823] [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: 10/31/2022]
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14
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Chen Q, Yang M, Liu X, Zhang J, Mi S, Wang Y, Xiao W, Yu Y. Blood transcriptome analysis and identification of genes associated with supernumerary teats in Chinese Holstein cows. J Dairy Sci 2022; 105:9837-9852. [DOI: 10.3168/jds.2022-22346] [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] [Received: 05/28/2022] [Accepted: 07/20/2022] [Indexed: 11/17/2022]
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15
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Xiao W, Chen L, Xuan T, He X, Yu H, Zhu X, Luo N, Li M, Qi Y, Sun T, Qi C. 1769P KDM6A mutation act as a potential immunotherapy biomarker in urothelial carcinoma. Ann Oncol 2022. [DOI: 10.1016/j.annonc.2022.07.1847] [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: 11/01/2022] Open
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16
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Zhang Y, Blomquist TM, Kusko R, Stetson D, Zhang Z, Yin L, Sebra R, Gong B, Lococo JS, Mittal VK, Novoradovskaya N, Yeo JY, Dominiak N, Hipp J, Raymond A, Qiu F, Arib H, Smith ML, Brock JE, Farkas DH, Craig DJ, Crawford EL, Li D, Morrison T, Tom N, Xiao W, Yang M, Mason CE, Richmond TA, Jones W, Johann DJ, Shi L, Tong W, Willey JC, Xu J. Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples. Genome Biol 2022; 23:141. [PMID: 35768876 PMCID: PMC9241261 DOI: 10.1186/s13059-022-02709-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Background Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified. Results Tissue sections that fail more frequently show low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces are more likely to show FFPE-specific errors, akin to “edge effects” seen in histology, while the inner samples display no quality degradation related to fixation time. Conclusions To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02709-8.
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Affiliation(s)
- Yifan Zhang
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Thomas M Blomquist
- (Formerly) Department of Pathology, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA.,Lucas County Coroner's Office, 2595 Arlington Ave, Toledo, OH, 43614, USA
| | - Rebecca Kusko
- Immuneering Corporation, 245 Main St, Cambridge, MA, 02142, USA
| | - Daniel Stetson
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Lihui Yin
- (Formerly) Pathology and Laboratory Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Robert Sebra
- Icahn Institute and Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | - Vinay K Mittal
- Thermo Fisher Scientific, 110 Miller Ave, Ann Arbor, MI, 48104, USA
| | | | - Ji-Youn Yeo
- Department of Pathology, University of Toledo, 3000 Arlington Ave, Toledo, OH, 43614, USA
| | - Nicole Dominiak
- Department of Pathology, University of Toledo, 3000 Arlington Ave, Toledo, OH, 43614, USA
| | - Jennifer Hipp
- Department of Pathology, Strata Oncology, Inc., Ann Arbor, MI, 48103, USA
| | - Amelia Raymond
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Hanane Arib
- Icahn Institute and Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Melissa L Smith
- Icahn Institute and Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Jay E Brock
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Daniel H Farkas
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Daniel J Craig
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Erin L Crawford
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tom Morrison
- Accugenomics, Inc., 1410 Commonwealth Drive, Suite 105, Wilmington, NC, 20403, USA
| | - Nikola Tom
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.,EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Wenzhong Xiao
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.,Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
| | - Mary Yang
- Department of Information Science, University of Arkansas at Little Rock, 2801 S. Univ. Ave, Little Rock, AR, 72204, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr, Pleasanton, CA, 94588, USA
| | - Wendell Jones
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd, Morrisville, NC, 27560, USA
| | - Donald J Johann
- Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR, 72205, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China.,Human Phenome Institute, Fudan University, Shanghai, 201203, China.,Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, 200438, China
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, 3000 Arlington Ave, Toledo, OH, 43614, USA.
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
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17
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Joseph P, Pari R, Miller S, Warren A, Stovall MC, Squires J, Chang CJ, Xiao W, Waxman AB, Systrom DM. Neurovascular Dysregulation and Acute Exercise Intolerance in ME/CFS: A Randomized, Placebo-Controlled Trial of Pyridostigmine. Chest 2022; 162:1116-1126. [PMID: 35526605 DOI: 10.1016/j.chest.2022.04.146] [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: 02/27/2022] [Revised: 04/22/2022] [Accepted: 04/22/2022] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by intractable fatigue, postexertional malaise, and orthostatic intolerance, but its pathophysiology is poorly understood. Pharmacologic cholinergic stimulation was used to test the hypothesis that neurovascular dysregulation underlies exercise intolerance in ME/CFS. RESEARCH QUESTION Does neurovascular dysregulation contribute to exercise intolerance in ME/CFS, and can its treatment improve exercise capacity? STUDY DESIGN AND METHODS Forty-five subjects with ME/CFS were enrolled in a single-center, randomized, double-blind, placebo-controlled trial. Subjects were assigned in a 1:1 ratio to receive a 60-mg dose of oral pyridostigmine or placebo after an invasive cardiopulmonary exercise test (iCPET). A second iCPET was performed 50 min later. The primary end point was the difference in peak exercise oxygen uptake (Vo2). Secondary end points included exercise pulmonary and systemic hemodynamics and gas exchange. RESULTS Twenty-three subjects were assigned to receive pyridostigmine and 22 to receive placebo. The peak Vo2 increased after pyridostigmine but decreased after placebo (13.3 ± 13.4 mL/min vs -40.2 ± 21.3 mL/min; P < .05). The treatment effect of pyridostigmine was 53.6 mL/min (95% CI, -105.2 to -2.0). Peak vs rest Vo2 (25.9 ± 15.3 mL/min vs -60.8 ± 25.6 mL/min; P < .01), cardiac output (-0.2 ± 0.6 L/min vs -1.9 ± 0.6 L/min; P < .05), and right atrial pressure (1.0 ± 0.5 mm Hg vs -0.6 ± 0.5 mm Hg; P < .05) were greater in the pyridostigmine group compared with placebo. INTERPRETATION Pyridostigmine improves peak Vo2 in ME/CFS by increasing cardiac output and right ventricular filling pressures. Worsening peak exercise Vo2, cardiac output, and right atrial pressure following placebo may signal the onset of postexertional malaise. We suggest that treatable neurovascular dysregulation underlies acute exercise intolerance in ME/CFS. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov; No.: NCT03674541; URL: www. CLINICALTRIALS gov.
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Affiliation(s)
- Phillip Joseph
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Yale-New Haven Hospital, Yale University, New Haven, CT
| | - Rosa Pari
- Department of Medicine, University of Rochester Medical Center, Rochester, NY
| | - Sarah Miller
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Arabella Warren
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Mary Catherine Stovall
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Johanna Squires
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Chia-Jung Chang
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Wenzhong Xiao
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Aaron B Waxman
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - David M Systrom
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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18
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Li G, Han F, Xiao F, Gu K, Shen Q, Xu W, Li W, Wang Y, Liang B, Huang J, Xiao W, Kong Q. System-level metabolic modeling facilitates unveiling metabolic signature in exceptional longevity. Aging Cell 2022; 21:e13595. [PMID: 35343058 PMCID: PMC9009231 DOI: 10.1111/acel.13595] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 12/23/2021] [Revised: 02/17/2022] [Accepted: 03/10/2022] [Indexed: 12/29/2022] Open
Abstract
Although it is well known that metabolic control plays a crucial role in regulating the health span and life span of various organisms, little is known for the systems metabolic profile of centenarians, the paradigm of human healthy aging and longevity. Meanwhile, how to well characterize the system‐level metabolic states in an organism of interest remains to be a major challenge in systems metabolism research. To address this challenge and better understand the metabolic mechanisms of healthy aging, we developed a method of genome‐wide precision metabolic modeling (GPMM) which is able to quantitatively integrate transcriptome, proteome and kinetome data in predictive modeling of metabolic networks. Benchmarking analysis showed that GPMM successfully characterized metabolic reprogramming in the NCI‐60 cancer cell lines; it dramatically improved the performance of the modeling with an R2 of 0.86 between the predicted and experimental measurements over the performance of existing methods. Using this approach, we examined the metabolic networks of a Chinese centenarian cohort and identified the elevated fatty acid oxidation (FAO) as the most significant metabolic feature in these long‐lived individuals. Evidence from serum metabolomics supports this observation. Given that FAO declines with normal aging and is impaired in many age‐related diseases, our study suggests that the elevated FAO has potential to be a novel signature of healthy aging of humans.
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Affiliation(s)
- Gong‐Hua Li
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- Kunming Key Laboratory of Healthy Aging Study Kunming Yunnan China
| | - Feifei Han
- Harvard Medical School Immune and Metabolic Computational Center Massachusetts General Hospital Boston Massachusetts USA
| | - Fu‐Hui Xiao
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- Kunming Key Laboratory of Healthy Aging Study Kunming Yunnan China
| | - Kang‐Su‐Yun Gu
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- Kunming Key Laboratory of Healthy Aging Study Kunming Yunnan China
| | - Qiu Shen
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
| | - Weihong Xu
- Harvard Medical School Immune and Metabolic Computational Center Massachusetts General Hospital Boston Massachusetts USA
| | - Wen‐Xing Li
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
| | - Yan‐Li Wang
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- School of Life Sciences Center for Life Sciences Yunnan University Kunming Yunnan China
| | - Bin Liang
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- School of Life Sciences Center for Life Sciences Yunnan University Kunming Yunnan China
| | - Jing‐Fei Huang
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
| | - Wenzhong Xiao
- Harvard Medical School Immune and Metabolic Computational Center Massachusetts General Hospital Boston Massachusetts USA
| | - Qing‐Peng Kong
- State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province Kunming Institute of Zoology Chinese Academy of Sciences Kunming Yunnan China
- Kunming Key Laboratory of Healthy Aging Study Kunming Yunnan China
- CAS Center for Excellence in Animal Evolution and Genetics Chinese Academy of Sciences Kunming Yunnan China
- KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases Kunming Yunnan China
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19
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Xiao W, Shi WT, Wang J. [Study of vital inflamed pulp therapy in immature permanent teeth with irreversible pulpitis and apical periodontitis]. Zhonghua Kou Qiang Yi Xue Za Zhi 2022; 57:287-291. [PMID: 35280007 DOI: 10.3760/cma.j.cn112144-20211223-00563] [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: 06/14/2023]
Abstract
To assess the treatment effectiveness of vital inflamed pulp therapy (VIPT) in immature permanent teeth with irreversible pulpitis and apical periodontitis. The faculty members in the Department of Pediatric Dentistry, the Ninth People's Hospital were invited to submit consecutive VIPT cases from June 2015 to June 2016 (follow-up periods>12 months). The cases were retrospectively reviewed, clinical symptoms and radiographic changes in periapical radiolucency were evaluated, meanwhile, the data of radiographic changes such as apical diameter and root length were calculated and analyzed with ANOVA. Totally thirteen submitted patients/cases were included (6 males and 7 females) in the present study,. The average age of patients was (9.9±1.4) years old. The average follow-up time was (26.5±6.8) months (17-37 months). At the 12-month visit, all 13 treated teeth survived, 9 out of 11 teeth with apical periodontitis showed normal radiographic manifestation. At the 3, 6 and 12 months visits, the within-case percentage changes in apical diameter were (8.0±5.1)%, (24.1±9.1)% and (70.3±10.7)%, respectively, while the within-case percentage changes in root length were (11.4±9.8)%, (14.5±9.8)% and (27.4±14.2)%, respectively. There were statistically significant differences in the changes of apical diameter (F=18.80, P<0.001) and root length (F=4.64, P=0.047) from the preoperative time to the postoperative follow-ups. VIPT might improve clinical outcomes, even achieve continued root development. VIPT can be an option in treating immature teeth with irreversible pulpitis and apical periodontitis.
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Affiliation(s)
- W Xiao
- Department of Pediatric Dentistry, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology, Shanghai 200011, China
| | - W T Shi
- Clinical Research Center, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology, Shanghai 200011, China
| | - J Wang
- Department of Pediatric Dentistry, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine & College of Stomatology, Shanghai Jiao Tong University & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Shanghai Key Laboratory of Stomatology, Shanghai 200011, China
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20
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Pan B, Ren L, Onuchic V, Guan M, Kusko R, Bruinsma S, Trigg L, Scherer A, Ning B, Zhang C, Glidewell-Kenney C, Xiao C, Donaldson E, Sedlazeck FJ, Schroth G, Yavas G, Grunenwald H, Chen H, Meinholz H, Meehan J, Wang J, Yang J, Foox J, Shang J, Miclaus K, Dong L, Shi L, Mohiyuddin M, Pirooznia M, Gong P, Golshani R, Wolfinger R, Lababidi S, Sahraeian SME, Sherry S, Han T, Chen T, Shi T, Hou W, Ge W, Zou W, Guo W, Bao W, Xiao W, Fan X, Gondo Y, Yu Y, Zhao Y, Su Z, Liu Z, Tong W, Xiao W, Zook JM, Zheng Y, Hong H. Assessing reproducibility of inherited variants detected with short-read whole genome sequencing. Genome Biol 2022; 23:2. [PMID: 34980216 PMCID: PMC8722114 DOI: 10.1186/s13059-021-02569-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. RESULTS To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. CONCLUSIONS Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.
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Affiliation(s)
- Bohu Pan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Luyao Ren
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | | | | | | | - Len Trigg
- Real Time Genomics, Hamilton, New Zealand
| | - Andreas Scherer
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, the Netherlands
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Chaoyang Zhang
- School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA
| | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Eric Donaldson
- Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Gokhan Yavas
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | | | | | - Joe Meehan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Jing Wang
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Jingcheng Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, 10021, USA
| | - Jun Shang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Lianhua Dong
- Center for Advanced Measurement Science, National Institute of Metrology, Beijing, 100013, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | | | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ping Gong
- Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, 39180, USA
| | | | | | - Samir Lababidi
- Office of Health Informatics, Office of the Commissioner, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | | | - Steve Sherry
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Tao Han
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tao Chen
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- The Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Wanwan Hou
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Weigong Ge
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wen Zou
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjing Guo
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenjun Bao
- SAS Institute Inc., Cary, NC, 27513, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, 94305, USA
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yoichi Gondo
- Department of Molecular Life Sciences, Tokai University School of Medicine, 143 Shimokasuya, Isehara, 259-1193, Japan
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Yongmei Zhao
- CCR-SF Bioinformatics Group, Advanced Biomedical and Computational Sciences, Biomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21701, USA
| | - Zhenqiang Su
- Takeda Pharmaceuticals, Cambridge, MA, 02139, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenming Xiao
- Division of Molecular Genetics and Pathology, Center for Device and Radiological Health, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA.
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 200438, China.
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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21
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Yang Y, Si J, Lv X, Dai D, Liu L, Tang S, Wang Y, Zhang S, Xiao W, Zhang Y. Integrated analysis of whole genome and transcriptome sequencing reveals a frameshift mutation associated with recessive embryonic lethality in Holstein cattle. Anim Genet 2021; 53:137-141. [PMID: 34873723 DOI: 10.1111/age.13160] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 11/20/2021] [Accepted: 11/25/2021] [Indexed: 12/14/2022]
Abstract
Embryo loss is an important factor affecting fertility in dairy production. HH2 was identified as a haplotype on chromosome 1 associated with embryonic lethality in Holstein cattle. In the current study, both short- and long-read WGS was performed on four carriers and four non-carriers of HH2 to screen for variants in concordance with HH2 haplotype status. Sequence variation analysis revealed five putative functional variants of protein-coding genes, including a frameshift mutation (g.107172616delT) in intraflagellar transport protein 80 (IFT80) gene. Transcriptome analysis of whole blood indicated that no gene exhibited significantly differential expression or allele-specific expression between carriers and non-carriers in the candidate region. This evidence points to g.107172616delT as the highest priority causative mutation for HH2. Protein prediction reveals that the frameshift mutation results in a premature stop codon to reduce the peptide chain from 760 to 383 amino acids and greatly alters the structure and function of IFT80 protein. Our results demonstrate that the use of a combination of multiple high-throughput sequencing technologies is an efficient strategy to screen for the candidate causative mutations responsible for Mendelian traits, including genetic disorders.
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Affiliation(s)
- Y Yang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - J Si
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - X Lv
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - D Dai
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - L Liu
- Beijing Dairy Cattle Center, Beijing, 100192, China
| | - S Tang
- Beijing Animal Husbandry Station, Beijing, 100107, China
| | - Y Wang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - S Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - W Xiao
- Beijing Animal Husbandry Station, Beijing, 100107, China
| | - Y Zhang
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
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22
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Rosser JI, Tayyar R, Giardina R, Kolonoski P, Kenski D, Shen P, Steinmetz LM, Hung LY, Xiao W, Bains K, Morrison T, Madison A, Chang SI, Tompkins L, Pinsky BA, Holubar M. Case-control study evaluating risk factors for SARS-CoV-2 outbreak amongst healthcare personnel at a tertiary care center. Am J Infect Control 2021; 49:1457-1463. [PMID: 34536502 PMCID: PMC8440319 DOI: 10.1016/j.ajic.2021.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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: 06/22/2021] [Revised: 09/02/2021] [Accepted: 09/08/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Despite several outbreaks of SARS-CoV-2 amongst healthcare personnel (HCP) exposed to COVID-19 patients globally, risk factors for transmission remain poorly understood. METHODS We conducted an outbreak investigation and case-control study to evaluate SARS-CoV-2 transmission risk in an outbreak among HCP at an academic medical center in California that was confirmed by whole genome sequencing. RESULTS A total of 7/9 cases and 93/182 controls completed a voluntary survey about risk factors. Compared to controls, cases reported significantly more patient contact time. Cases were also significantly more likely to have performed airway procedures on the index patient, particularly placing the patient on high flow nasal cannula, continuous positive airway pressure (CPAP), or bilevel positive airway pressure (BiPAP) (OR = 11.6; 95% CI = 1.7 -132.1). DISCUSSION This study highlights the risk of nosocomial infection of SARS-CoV-2 from patients who become infectious midway into their hospitalization. Our findings also reinforce the importance of patient contact time and aerosol-generating procedures as key risk factors for HCP infection with SARS-CoV-2. CONCLUSIONS Re-testing patients for SARS-CoV-2 after admission in suspicious cases and using N95 masks for all aerosol-generating procedures regardless of initial patient SARS-CoV-2 test results can help reduce the risk of SARS-COV-2 transmission to HCP.
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Affiliation(s)
- Joelle I Rosser
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA.
| | - Ralph Tayyar
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA
| | | | | | | | - Peidong Shen
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA
| | - Lars M Steinmetz
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA
| | - Li-Yuan Hung
- Immune-Metabolism Computational Center, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA
| | - Wenzhong Xiao
- Immune-Metabolism Computational Center, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA
| | | | | | | | | | - Lucy Tompkins
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA; Stanford Health Care, Stanford, CA
| | - Benjamin A Pinsky
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA
| | - Marisa Holubar
- Division of Infectious Diseases & Geographic Medicine, Stanford University School of Medicine, Stanford, CA; Stanford Health Care, Stanford, CA
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23
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Wu Y, Xiao W, Tong W, Borlak J, Chen M. A systematic comparison of hepatobiliary adverse drug reactions in FDA and EMA drug labeling reveals discrepancies. Drug Discov Today 2021; 27:337-346. [PMID: 34607018 DOI: 10.1016/j.drudis.2021.09.009] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/20/2021] [Accepted: 09/20/2021] [Indexed: 01/23/2023]
Abstract
Drug labeling informs physicians and patients on the safe and effective use of medication. However, recent studies suggested discrepancies in labeling of the same drug between different regulatory agencies. Here, we evaluated the hepatic safety information in labeling for 549 medications approved by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Limited discrepancies were found regarding risk for hepatic adverse drug reactions (ADRs) (8.7% in hepatic ADR warnings and 21.3% in contraindication for liver disease), while caution should be exercised over drugs with inconsistencies in contraindications for liver disease and evidence for hepatotoxicity (4.9%). Most discrepancies were attributable to less-severe hepatic events and low-frequency hepatic ADR reports and had limited implication on clinical outcomes.
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Affiliation(s)
- Yue Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Wenzhong Xiao
- Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Boston, MA, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Jürgen Borlak
- Center of Pharmacology and Toxicology, Hannover Medical School, 30625 Hannover, Germany.
| | - Minjun Chen
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA.
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24
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Wen H, Luo H, Yang M, Augustino SMA, Wang D, Mi S, Guo Y, Zhang Y, Xiao W, Wang Y, Yu Y. Genetic parameters and weighted single-step genome-wide association study for supernumerary teats in Holstein cattle. J Dairy Sci 2021; 104:11867-11877. [PMID: 34482976 DOI: 10.3168/jds.2020-19943] [Citation(s) in RCA: 3] [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] [Received: 11/23/2020] [Accepted: 06/29/2021] [Indexed: 01/22/2023]
Abstract
Supernumerary teats (SNT) are a common epidermal abnormality of udders in mammals. The SNT negatively affect machine milking ability, udder health, and animal welfare and sometimes act as reservoirs for undesirable bacteria, resulting in economic losses on calves and lactating cows due to the cost of SNT removal surgery, early culling, and low milk yield. This study aimed to analyze the incidence and genetic parameter of SNT and detect SNT-related genes in Chinese Holstein cattle. In this study, the incidence of SNT was recorded in 4,670 Chinese Holstein cattle (born between 2008 and 2017) from 2 farms, including 734 genotyped cows with 114,485 SNPs. The SNT had a total frequency of 9.8% and estimated heritability of 0.22 (SE = 0.07), which were obtained using a threshold model in the studied Chinese Holstein population. Furthermore, we calculated approximate genetic correlations between SNT and the following indicator traits: 12 milk production, 28 body conformation, 5 fertility and reproduction, 5 health, and 9 longevity. Generally, the estimated correlations, such as 305-d milk yield for third parity (-0.55; SE = 0.02) and age at first calving in heifer (0.19; SE = 0.03), were low to moderate. A single-step GWAS was implemented, and 10 genes associated with SNT located in BTA4 were identified. The region (112.70-112.90 Mb) on BTA4 showed the highest genetic variance for SNT. The quantitative trait loci on BTA4 was mapped into the RARRES2 gene, which was previously shown to affect adipogenesis and hormone secretion. The WIF1 gene, which was located in BTA5, was also considered as a candidate gene for SNT. Overall, these findings provide useful information for breeders who are interested in reducing SNT.
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Affiliation(s)
- H Wen
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - H Luo
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - M Yang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - S M A Augustino
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - D Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - S Mi
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - Y Guo
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, SLU 75007, Uppsala, Sweden
| | - Y Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China
| | - W Xiao
- Beijing Animal Husbandry Station, No. 15A Anwaibeiyuan Road, 100029, Beijing, China
| | - Y Wang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
| | - Y Yu
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, 100193, Beijing, China.
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25
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Deveson IW, Gong B, Lai K, LoCoco JS, Richmond TA, Schageman J, Zhang Z, Novoradovskaya N, Willey JC, Jones W, Kusko R, Chen G, Madala BS, Blackburn J, Stevanovski I, Bhandari A, Close D, Conroy J, Hubank M, Marella N, Mieczkowski PA, Qiu F, Sebra R, Stetson D, Sun L, Szankasi P, Tan H, Tang LY, Arib H, Best H, Burgher B, Bushel PR, Casey F, Cawley S, Chang CJ, Choi J, Dinis J, Duncan D, Eterovic AK, Feng L, Ghosal A, Giorda K, Glenn S, Happe S, Haseley N, Horvath K, Hung LY, Jarosz M, Kushwaha G, Li D, Li QZ, Li Z, Liu LC, Liu Z, Ma C, Mason CE, Megherbi DB, Morrison T, Pabón-Peña C, Pirooznia M, Proszek PZ, Raymond A, Rindler P, Ringler R, Scherer A, Shaknovich R, Shi T, Smith M, Song P, Strahl M, Thodima VJ, Tom N, Verma S, Wang J, Wu L, Xiao W, Xu C, Yang M, Zhang G, Zhang S, Zhang Y, Shi L, Tong W, Johann DJ, Mercer TR, Xu J. Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology. Nat Biotechnol 2021; 39:1115-1128. [PMID: 33846644 PMCID: PMC8434938 DOI: 10.1038/s41587-021-00857-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 02/15/2021] [Indexed: 02/08/2023]
Abstract
Circulating tumor DNA (ctDNA) sequencing is being rapidly adopted in precision oncology, but the accuracy, sensitivity and reproducibility of ctDNA assays is poorly understood. Here we report the findings of a multi-site, cross-platform evaluation of the analytical performance of five industry-leading ctDNA assays. We evaluated each stage of the ctDNA sequencing workflow with simulations, synthetic DNA spike-in experiments and proficiency testing on standardized, cell-line-derived reference samples. Above 0.5% variant allele frequency, ctDNA mutations were detected with high sensitivity, precision and reproducibility by all five assays, whereas, below this limit, detection became unreliable and varied widely between assays, especially when input material was limited. Missed mutations (false negatives) were more common than erroneous candidates (false positives), indicating that the reliable sampling of rare ctDNA fragments is the key challenge for ctDNA assays. This comprehensive evaluation of the analytical performance of ctDNA assays serves to inform best practice guidelines and provides a resource for precision oncology.
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Affiliation(s)
- Ira W Deveson
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Kevin Lai
- Bioinformatics, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | | | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | | | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, China
| | | | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, Toledo, OH, USA
| | | | | | - Guangchun Chen
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bindu Swapna Madala
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - James Blackburn
- Cancer Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St. Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Igor Stevanovski
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Devin Close
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | | | - Michael Hubank
- NIHR Biomedical Research Centre, Royal Marsden Hospital, Sutton, Surrey, UK
| | | | | | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, China
| | - Robert Sebra
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Lihyun Sun
- Elim Biopharmaceuticals, Inc., Hayward, CA, USA
| | - Philippe Szankasi
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | - Haowen Tan
- Primbio Genes Biotechnology, East Lake High-tech Development Zone, Wuhan, Hubei, China
| | - Lin-Ya Tang
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Hanane Arib
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hunter Best
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
- Departments of Pathology and Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | | | - Pierre R Bushel
- National Institute of Environmental Health Sciences, Research Triangle Park, Morrisville, NC, USA
| | - Fergal Casey
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | - Simon Cawley
- Clinical Sequencing Division, Thermo Fisher Scientific, South San Francisco, CA, USA
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
| | - Jonathan Choi
- Roche Sequencing Solutions, Inc., Pleasanton, CA, USA
| | - Jorge Dinis
- Roche Sequencing Solutions, Inc., Pleasanton, CA, USA
| | | | - Agda Karina Eterovic
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Liang Feng
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | | | - Kristina Giorda
- Marketing, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | | | | | | | | | - Li-Yuan Hung
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mirna Jarosz
- NGS Products and Services, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | - Garima Kushwaha
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., Pleasanton, CA, USA
| | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Quan-Zhen Li
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Zhiguang Li
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Liang-Chun Liu
- Clinical Diagnostic Division, Thermo Fisher Scientific, Fremont, CA, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Charles Ma
- Cancer Genetics, Inc., Rutherford, NJ, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Dalila B Megherbi
- CMINDS Research Center, Department of Electrical and Computer Engineering, College of Engineering, University of Massachusetts Lowell, Lowell, MA, USA
| | | | | | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Paula Z Proszek
- NIHR Biomedical Research Centre, Royal Marsden Hospital, Sutton, Surrey, UK
| | | | - Paul Rindler
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, Salt Lake City, UT, USA
| | | | - Andreas Scherer
- Institute for Molecular Medicine Finland (FIMM), Nordic EMBL Partnership for Molecular Medicine, HiLIFE Unit, Biomedicum Helsinki 2U (D302b), University of Helsinki, Helsinki, Finland
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, The Netherlands
| | | | - Tieliu Shi
- Center for Bioinformatics and Computational Biology and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, China
| | - Melissa Smith
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ping Song
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, Houston, TX, USA
| | - Maya Strahl
- Icahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Nikola Tom
- EATRIS ERIC- European Infrastructure for Translational Medicine, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | | | - Jiashi Wang
- Research and Development, Integrated DNA Technologies, Inc., Coralville, IA, USA
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chang Xu
- Research and Development, QIAGEN Sciences, Inc., Frederick, MD, USA
| | - Mary Yang
- Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR, USA
| | | | - Sa Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, China
| | - Yilin Zhang
- Elim Biopharmaceuticals, Inc., Hayward, CA, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, China
- Human Phenome Institute, Fudan University, Shanghai, China
- Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, China
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Donald J Johann
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
| | - Timothy R Mercer
- St. Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia.
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, Queensland, QLD, Australia.
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA.
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Du F, Xu J, Li X, Li Z, Li X, Zuo X, Bi L, Zhao D, Zhang M, Wu H, He D, Wu Z, Li Z, Li Y, Xu J, Tao Y, Zhao J, Chen J, Zhang H, Li J, Jiang L, Xiao Z, Chen Z, Yin G, Gong L, Wang G, Dong L, Xiao W, Bao C. POS0664 A MULTICENTER RANDOMIZED STUDY IN RHEUMATOID ARTHRITIS TO COMPARE IGURATIMOD, METHOTREXATE, OR COMBINATION: 52 WEEK EFFICACY AND SAFETY RESULTS OF THE SMILE TRIAL. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.1486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Iguratimod (IGU) has demonstrated efficacy and safety for active rheumatoid arthritis (RA) patients in double-blind clinical trials in China and Japan as a new disease-modifying anti-rheumatic drug (DMARD). There are no studies evaluating the radiographic progression of structural joint damage of IGU for the treatment of RA using the mTSS as the primary endpoint.Objectives:Our study was to evaluate the efficacy and safety of IGU monotherapy and IGU combined methotrexate (MTX) compared with MTX monotherapy, including the inhibitory effects of joint destruction.Methods:This randomized, double-blind, parallel-controlled, multicenter study in patients with active RA who have not previously used MTX and biological DMARDs (bDMARDs) (ClinicalTrials.gov Identifier NCT01548001) was carried out in China. Patients were randomized 1:1:1 to receive IGU 25 mg twice a day (bid), MTX 10mg once a week(qw) for the first 4 weeks and 15 mg once a week(qw) for week 5 to 52, or IGU combined MTX (IGU+MTX) for 52 weeks. The primary endpoints were to assess and compare American College of Rheumatology 20% (ACR20) response and the change of modified total Sharp scoring (mTSS) score over 52 weeks (Intention-to-treat, ITT analysis). The non-inferiority test was used to analyze the difference of ACR20 response at 52 weeks between the IGU monotherapy and the MTX monotherapy arms, and the non-inferiority limit value was 10%. The difference test was used for the comparison between the IGU+MTX and MTX monotherapy arms. Two-way ANOVA was used to analyze the difference of the changes of mTSS score of each arm compared with baseline value (0 week).Results:A total of 895 patients were randomized to IGU 25mg bid (n =297), MTX 10-15mg qw(n=293), and IGU+MTX (n=305). Baseline characteristics were comparable between the arms (Table 1).Table 1.Demographic and Other Baseline Characteristics (SAS)IGUMTXIGU+MTXNumber of Subjects297293305Age, mean (SD) years46.87(10.67)47.63(10.70)48.37(10.69)Female/male, %77.44/22.5679.18/20.8278.03/21.97Duration of RA, mean(SD) years11.67±7.1611.60±7.9811.67±7.27CRP, mean(SD) mg/L222.32±35.4720.67±26.6119.74±31.38Tender joint count, mean (SD)14.59±9.1614.83±9.3014.93±9.88Swollen joint count, mean (SD)9.81±6.639.73±7.209.51±6.22DAS28-CRP, mean (SD)5.084±0.9945.102±0.9795.103±0.956HAQ score, mean (SD)15.82±11.2515.24±10.9316.06±10.92SAS: Safety Analysis Set; CRP: C-reactive protein;DAS28: disease activity score; HAQ: Health Assessment QuestionnaireThe study met its primary endpoints. More concretely, IGU monotherapy and IGU+MTX were found to be superior to MTX at week 52 with a higher ACR20 response of 77.44%(230/297, P=0.0019) and 77.05%(235/305, P=0.0028) versus 65.87%(193/293) (fig 1). As shown in fig 1, the structural remission (ΔmTSS≤0.5) was statistically significant for IGU monotherapy (57.4%, P=0.0308) but not for IGU+MTX arm (55%) versus MTX monotherapy (47.8%).Overall incidence of the adverse events (AEs) leading to study discontinuation were reported in 13.8% (41/297) in IGU monotherapy arm, 11.26% (33/293) in MTX monotherapy arm and 11.51% (35/305) patients in IGU+MTX arm. The incidence of adverse drug reactions (ADR) leading to study discontinuation were 11.45% (34/297), 8.53% (25/293) and 9.21% (28/305), respectively. There was no one death and no significant difference in all the safety indicators among the three arms.Conclusion:Iguratimod alone or in combination with MTX demonstrated superior efficacy with acceptable safety compared to MTX for patients with active RA who have not previously used MTX bDMARDs.Disclosure of Interests:None declared
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27
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Gong B, Li D, Kusko R, Novoradovskaya N, Zhang Y, Wang S, Pabón-Peña C, Zhang Z, Lai K, Cai W, LoCoco JS, Lader E, Richmond TA, Mittal VK, Liu LC, Johann DJ, Willey JC, Bushel PR, Yu Y, Xu C, Chen G, Burgess D, Cawley S, Giorda K, Haseley N, Qiu F, Wilkins K, Arib H, Attwooll C, Babson K, Bao L, Bao W, Lucas AB, Best H, Bhandari A, Bisgin H, Blackburn J, Blomquist TM, Boardman L, Burgher B, Butler DJ, Chang CJ, Chaubey A, Chen T, Chierici M, Chin CR, Close D, Conroy J, Cooley Coleman J, Craig DJ, Crawford E, Del Pozo A, Deveson IW, Duncan D, Eterovic AK, Fan X, Foox J, Furlanello C, Ghosal A, Glenn S, Guan M, Haag C, Hang X, Happe S, Hennigan B, Hipp J, Hong H, Horvath K, Hu J, Hung LY, Jarosz M, Kerkhof J, Kipp B, Kreil DP, Łabaj P, Lapunzina P, Li P, Li QZ, Li W, Li Z, Liang Y, Liu S, Liu Z, Ma C, Marella N, Martín-Arenas R, Megherbi DB, Meng Q, Mieczkowski PA, Morrison T, Muzny D, Ning B, Parsons BL, Paweletz CP, Pirooznia M, Qu W, Raymond A, Rindler P, Ringler R, Sadikovic B, Scherer A, Schulze E, Sebra R, Shaknovich R, Shi Q, Shi T, Silla-Castro JC, Smith M, López MS, Song P, Stetson D, Strahl M, Stuart A, Supplee J, Szankasi P, Tan H, Tang LY, Tao Y, Thakkar S, Thierry-Mieg D, Thierry-Mieg J, Thodima VJ, Thomas D, Tichý B, Tom N, Garcia EV, Verma S, Walker K, Wang C, Wang J, Wang Y, Wen Z, Wirta V, Wu L, Xiao C, Xiao W, Xu S, Yang M, Ying J, Yip SH, Zhang G, Zhang S, Zhao M, Zheng Y, Zhou X, Mason CE, Mercer T, Tong W, Shi L, Jones W, Xu J. Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions. Genome Biol 2021; 22:109. [PMID: 33863344 PMCID: PMC8051090 DOI: 10.1186/s13059-021-02315-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [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: 07/28/2020] [Accepted: 03/18/2021] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing. RESULTS All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden. CONCLUSION This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.
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Affiliation(s)
- Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Rebecca Kusko
- Immuneering Corporation, One Broadway, 14th Floor, Cambridge, MA, 02142, USA
| | | | - Yifan Zhang
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
- Department of Information Science, University of Arkansas at Little Rock, 2801 S. Univ. Ave, Little Rock, AR, 72204, USA
| | - Shangzi Wang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Carlos Pabón-Peña
- Agilent Technologies, 5301 Stevens Creek Blvd, Santa Clara, CA, 95051, USA
| | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Kevin Lai
- Bioinformatics, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Wanshi Cai
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | | | - Eric Lader
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr, Pleasanton, CA, 94588, USA
| | - Vinay K Mittal
- Thermo Fisher Scientific, 110 Miller Ave, Ann Arbor, MI, 48104, USA
| | - Liang-Chun Liu
- Clinical Diagnostic Division, Thermo Fisher Scientific, 46500 Kato Rd, Fremont, CA, 94538, USA
| | - Donald J Johann
- Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR, 72205, USA
| | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, 3000 Arlington Ave, Toledo, OH, 43614, USA
| | - Pierre R Bushel
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Chang Xu
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Guangchun Chen
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd, Dallas, TX, 75390, USA
| | - Daniel Burgess
- Research and Development, Roche Sequencing Solutions Inc., 500 South Rosa Rd, Madison, WI, 53719, USA
| | - Simon Cawley
- Clinical Sequencing Division, Thermo Fisher Scientific, 180 Oyster Point Blvd, South San Francisco, CA, 94080, USA
| | - Kristina Giorda
- Marketing, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Nathan Haseley
- Illumina Inc., 5200 Illumina Way, San Diego, CA, 92122, USA
| | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Katherine Wilkins
- Agilent Technologies, 5301 Stevens Creek Blvd, Santa Clara, CA, 95051, USA
| | - Hanane Arib
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | | | - Kevin Babson
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Longlong Bao
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Wenjun Bao
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | | | - Hunter Best
- Departments of Pathology and Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, 84108, USA
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | - Halil Bisgin
- Department of Computer Science, Engineering and Physics, University of Michigan-Flint, Flint, MI, 48502, USA
| | - James Blackburn
- Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia
| | - Thomas M Blomquist
- Department of Pathology, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
- Lucas County Coroner's Office, 2595 Arlington Ave., Toledo, OH, 43614, USA
| | - Lisa Boardman
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Blake Burgher
- OmniSeq, Inc. 700 Ellicott St, Buffalo, NY, 14203, USA
| | - Daniel J Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
| | - Alka Chaubey
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Tao Chen
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | - Christopher R Chin
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Devin Close
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | | | - Daniel J Craig
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Erin Crawford
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Angela Del Pozo
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Ira W Deveson
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Daniel Duncan
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Agda Karina Eterovic
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | | | | | - Sean Glenn
- OmniSeq, Inc. 700 Ellicott St, Buffalo, NY, 14203, USA
| | - Meijian Guan
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | - Christine Haag
- Molecular Laboratory, Prof. F. Raue, Im Weiher 12, Heidelberg, Germany
| | - Xinyi Hang
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | - Scott Happe
- Agilent Technologies, 1834 State Hwy 71 West, Cedar Creek, TX, 78612, USA
| | - Brittany Hennigan
- Greenwood Genetic Center, 106 Gregor Mendel Circle, Greenwood, SC, 29646, USA
| | - Jennifer Hipp
- Department of Pathology, Strata Oncology, Inc., Ann Arbor, MI, 48103, USA
| | - Huixiao Hong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Kyle Horvath
- ResearchDx, Inc., 5 Mason, Irvine, CA, 92618, USA
| | - Jianhong Hu
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Li-Yuan Hung
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Mirna Jarosz
- NGS Products and Services, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Jennifer Kerkhof
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
| | - Benjamin Kipp
- Division of Anatomic Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - David Philip Kreil
- Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria
| | - Paweł Łabaj
- Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Department of Biotechnology, Boku University, Vienna, Austria
| | - Pablo Lapunzina
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, IdiPaz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- ITHACA, European Reference Network on Rare Congenital Malformations and Rare Intellectual Disability, European Commission, Lille, France
| | - Peng Li
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Quan-Zhen Li
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd, Dallas, TX, 75390, USA
| | - Weihua Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Zhiguang Li
- Center of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, 116044, Liaoning, China
| | - Yu Liang
- Geneis, 5 Guangshun North St., Chaoyang District, Beijing, 100102, China
| | - Shaoqing Liu
- GeneSmile Ltd Co., Jiangsu Cancer Hospital, 42 Baiziting St., Xuanwu District, Nanjing, 210009, Jiangsu, China
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Charles Ma
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Narasimha Marella
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Rubén Martín-Arenas
- Genycell Biotech España, Calle Garrido Atienza, 18320 Santa Fe, Granada, Spain
| | - Dalila B Megherbi
- CMINDS Research Center, Department of Electrical and Computer Engineering, College of Engineering, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Qingchang Meng
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Piotr A Mieczkowski
- Department of Genetics, University of North Carolina, 250 Bell Tower Drive, Chapel Hill, NC, 27599, USA
| | - Tom Morrison
- Accugenomics, Inc., 1410 Commonwealth Drive, Suite 105, Wilmington, NC, 20403, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Barbara L Parsons
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Cloud P Paweletz
- Translational Research Laboratory, Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, 360 Longwood Ave, Boston, MA, 02215, USA
| | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Wubin Qu
- iGeneTech, 8 Shengmingyuan Rd., Zhongguancun Life Science Park, Changping District, Beijing, 100080, China
| | - Amelia Raymond
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Paul Rindler
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | | | - Bekim Sadikovic
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
- Department of Pathology and Laboratory Medicine, Western University, London, Ontario, N6A3K7, Canada
| | - Andreas Scherer
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Institute for Molecular Medicine Finland (FIMM), Nordic EMBL Partnership for Molecular Medicine, HiLIFE Unit, Biomedicum Helsinki 2U (D302b), P.O. Box 20, (Tukholmankatu 8), FI-00014 University of Helsinki, Helsinki, Finland
| | - Egbert Schulze
- Laboratory for Molecular Genetics, Endocrine Practice, Im Weiher 12, 69121, Heidelberg, Germany
| | - Robert Sebra
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Rita Shaknovich
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - Qiang Shi
- Division of Systems Biology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, 500 Dongchuan Rd, Shanghai, 200241, China
| | | | - Melissa Smith
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Mario Solís López
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Ping Song
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Daniel Stetson
- Astrazeneca Pharmaceuticals, 35 Gatehouse Dr, Waltham, MA, 02451, USA
| | - Maya Strahl
- Icahn Institute and Dept. of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY, 10029, USA
| | - Alan Stuart
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, 800 Commissioners Rd E, London, Ontario, N6A5W9, Canada
| | - Julianna Supplee
- Translational Research Laboratory, Belfer Center for Applied Cancer Science, Dana-Farber Cancer Institute, 360 Longwood Ave, Boston, MA, 02215, USA
| | - Philippe Szankasi
- R&D Genomics MPS, Institute for Clinical and Experimental Pathology ARUP Laboratories, 500 Chipeta Way, Salt Lake City, UT, 84108, USA
| | - Haowen Tan
- Primbio Genes Biotechnology, Building C6-501, Biolake, No.666 Gaoxin Ave., East Lake High-tech Development Zone, Wuhan, 430074, Hubei, China
| | - Lin-Ya Tang
- Institute for Personalized Cancer Therapy, MD Anderson Cancer Center, 6565 MD Anderson Blvd, Houston, TX, 77030, USA
| | - Yonghui Tao
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Shraddha Thakkar
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | - Venkat J Thodima
- Cancer Genetics Inc, 201 Route 17 N, Meadows Office Building, Rutherford, NJ, 07070, USA
| | - David Thomas
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Boris Tichý
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Nikola Tom
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Elena Vallespin Garcia
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Suman Verma
- ResearchDx, Inc., 5 Mason, Irvine, CA, 92618, USA
| | - Kimbley Walker
- Human Genome Sequencing Center, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Charles Wang
- Center for Genomics, School of Medicine, Loma Linda University, Loma Linda, CA, 92350, USA
- Division of Microbiology & Molecular Genetics, Department of Basic Sciences, School of Medicine, Loma Linda University, Loma Linda, CA, 92350, USA
| | - Junwen Wang
- Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Department of Health Sciences, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Yexun Wang
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Zhining Wen
- College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China
| | - Valtteri Wirta
- Science for Life Laboratory, Karolinska Institutet, Tomtebodavägen 23B, 171 65, Solna, Sweden
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD, 20894, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Shibei Xu
- Department of Biostatistics, Columbia Mailman School of Public Health, 722 West 168th St., New York, NY, 10032, USA
| | - Mary Yang
- Department of Information Science, University of Arkansas at Little Rock, 2801 S. Univ. Ave, Little Rock, AR, 72204, USA
| | - Jianming Ying
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Shun H Yip
- Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ, 85259, USA
- Center for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR, China
| | - Guangliang Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, 510300, Guangdong, China
| | - Sa Zhang
- Clinical Laboratory, Burning Rock Biotech, Guangzhou, 510300, Guangdong, China
| | - Meiru Zhao
- Geneplus, PKUCare Industrial Park, Changping District, Beijing, 102206, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Xiaoyan Zhou
- Department of Pathology, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200032, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Institute of Pathology, Fudan University, Shanghai, 200032, China
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Timothy Mercer
- Australian Institute of Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
- Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
- Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, 200438, China.
| | - Wendell Jones
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd, Morrisville, NC, 27560, USA.
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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Jones W, Gong B, Novoradovskaya N, Li D, Kusko R, Richmond TA, Johann DJ, Bisgin H, Sahraeian SME, Bushel PR, Pirooznia M, Wilkins K, Chierici M, Bao W, Basehore LS, Lucas AB, Burgess D, Butler DJ, Cawley S, Chang CJ, Chen G, Chen T, Chen YC, Craig DJ, Del Pozo A, Foox J, Francescatto M, Fu Y, Furlanello C, Giorda K, Grist KP, Guan M, Hao Y, Happe S, Hariani G, Haseley N, Jasper J, Jurman G, Kreil DP, Łabaj P, Lai K, Li J, Li QZ, Li Y, Li Z, Liu Z, López MS, Miclaus K, Miller R, Mittal VK, Mohiyuddin M, Pabón-Peña C, Parsons BL, Qiu F, Scherer A, Shi T, Stiegelmeyer S, Suo C, Tom N, Wang D, Wen Z, Wu L, Xiao W, Xu C, Yu Y, Zhang J, Zhang Y, Zhang Z, Zheng Y, Mason CE, Willey JC, Tong W, Shi L, Xu J. A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency. Genome Biol 2021; 22:111. [PMID: 33863366 PMCID: PMC8051128 DOI: 10.1186/s13059-021-02316-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 03/18/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Oncopanel genomic testing, which identifies important somatic variants, is increasingly common in medical practice and especially in clinical trials. Currently, there is a paucity of reliable genomic reference samples having a suitably large number of pre-identified variants for properly assessing oncopanel assay analytical quality and performance. The FDA-led Sequencing and Quality Control Phase 2 (SEQC2) consortium analyze ten diverse cancer cell lines individually and their pool, termed Sample A, to develop a reference sample with suitably large numbers of coding positions with known (variant) positives and negatives for properly evaluating oncopanel analytical performance. RESULTS In reference Sample A, we identify more than 40,000 variants down to 1% allele frequency with more than 25,000 variants having less than 20% allele frequency with 1653 variants in COSMIC-related genes. This is 5-100× more than existing commercially available samples. We also identify an unprecedented number of negative positions in coding regions, allowing statistical rigor in assessing limit-of-detection, sensitivity, and precision. Over 300 loci are randomly selected and independently verified via droplet digital PCR with 100% concordance. Agilent normal reference Sample B can be admixed with Sample A to create new samples with a similar number of known variants at much lower allele frequency than what exists in Sample A natively, including known variants having allele frequency of 0.02%, a range suitable for assessing liquid biopsy panels. CONCLUSION These new reference samples and their admixtures provide superior capability for performing oncopanel quality control, analytical accuracy, and validation for small to large oncopanels and liquid biopsy assays.
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Affiliation(s)
- Wendell Jones
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd., Morrisville, NC, 27560, USA.
| | - Binsheng Gong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | | | - Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Rebecca Kusko
- Immuneering Corporation, One Broadway, 14th Floor, Cambridge, MA, 02142, USA
| | - Todd A Richmond
- Market & Application Development Bioinformatics, Roche Sequencing Solutions Inc., 4300 Hacienda Dr., Pleasanton, CA, 94588, USA
| | - Donald J Johann
- Winthrop P Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, 4301 W Markham St., Little Rock, AR, 72205, USA
| | - Halil Bisgin
- Department of Computer Science, Engineering and Physics, University of Michigan-Flint, Flint, MI, 48502, USA
| | - Sayed Mohammad Ebrahim Sahraeian
- Bioinformatics Research & Early Development, Roche Sequencing Solutions Inc., 1301 Shoreway Rd., Suite 7 #300, Belmont, CA, 94002, USA
| | - Pierre R Bushel
- National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC, 27709, USA
| | - Mehdi Pirooznia
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Katherine Wilkins
- Agilent Technologies, 5301 Stevens Creek Blvd., Santa Clara, CA, 95051, USA
| | | | - Wenjun Bao
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | - Lee Scott Basehore
- Agilent Technologies, 11011 N Torrey Pines Rd., La Jolla, CA, 92037, USA
| | | | - Daniel Burgess
- (formerly) Research and Development, Roche Sequencing Solutions Inc., 500 South Rosa Rd., Madison, WI, 53719, USA
| | - Daniel J Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - Simon Cawley
- (formerly) Clinical Sequencing Division, Thermo Fisher Scientific, 180 Oyster Point Blvd., South San Francisco, CA, 94080, USA
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
| | - Guangchun Chen
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd., Dallas, TX, 75390, USA
| | - Tao Chen
- University of Texas Southwestern Medical Center, 2330 Inwood Rd., Dallas, TX, 75390, USA
| | - Yun-Ching Chen
- Bioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Daniel J Craig
- Department of Medicine, College of Medicine and Life Sciences, The University of Toledo, Toledo, OH, 43614, USA
| | - Angela Del Pozo
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | | | - Yutao Fu
- Thermo Fisher Scientific, 110 Miller Ave., Ann Arbor, MI, 48104, USA
| | | | - Kristina Giorda
- Marketing, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Kira P Grist
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd., Morrisville, NC, 27560, USA
| | - Meijian Guan
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | - Yingyi Hao
- College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China
| | - Scott Happe
- Agilent Technologies, 1834 State Hwy 71 West, Cedar Creek, TX, 78612, USA
| | - Gunjan Hariani
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd., Morrisville, NC, 27560, USA
| | - Nathan Haseley
- Illumina Inc., 5200 Illumina Way, San Diego, CA, 92122, USA
| | - Jeff Jasper
- Q2 Solutions - EA Genomics, 5927 S Miami Blvd., Morrisville, NC, 27560, USA
| | | | - David Philip Kreil
- Bioinformatics Research, Institute of Molecular Biotechnology, Boku University Vienna, Vienna, Austria
| | - Paweł Łabaj
- Małopolska Centre of Biotechnology, Jagiellonian University, Krakow, Poland
- Department of Biotechnology, Boku University, Vienna, Austria
| | - Kevin Lai
- Bioinformatics, Integrated DNA Technologies, Inc., 1710 Commercial Park, Coralville, IA, 52241, USA
| | - Jianying Li
- Kelly Government Solutions, Inc., Research Triangle Park, NC, 27709, USA
| | - Quan-Zhen Li
- Department of Immunology, Genomics and Microarray Core Facility, University of Texas Southwestern Medical Center, 5323 Harry Hine Blvd., Dallas, TX, 75390, USA
| | - Yulong Li
- Center of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, Liaoning, China
| | - Zhiguang Li
- Center of Genome and Personalized Medicine, Institute of Cancer Stem Cell, Dalian Medical University, Dalian, Liaoning, China
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Mario Solís López
- Institute of Medical and Molecular Genetics (INGEMM), Hospital Universitario La Paz, CIBERER Instituto de Salud Carlos III, 28046, Madrid, Spain
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
| | - Kelci Miclaus
- JMP Life Sciences, SAS Institute Inc., Cary, NC, 27519, USA
| | - Raymond Miller
- Agilent Technologies, 5301 Stevens Creek Blvd., Santa Clara, CA, 95051, USA
| | - Vinay K Mittal
- Thermo Fisher Scientific, 110 Miller Ave., Ann Arbor, MI, 48104, USA
| | - Marghoob Mohiyuddin
- Bioinformatics Research & Early Development, Roche Sequencing Solutions Inc., 1301 Shoreway Rd., Suite 7 #300, Belmont, CA, 94002, USA
| | - Carlos Pabón-Peña
- Agilent Technologies, 5301 Stevens Creek Blvd., Santa Clara, CA, 95051, USA
| | - Barbara L Parsons
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Fujun Qiu
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Andreas Scherer
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
- Institute for Molecular Medicine Finland (FIMM), Nordic EMBL Partnership for Molecular Medicine, HiLIFE Unit, Biomedicum Helsinki 2U (D302b), FI-00014 University of Helsinki, P.O. Box 20 (Tukholmankatu 8), Helsinki, Finland
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, 500 Dongchuan Rd, Shanghai, 200241, China
| | - Suzy Stiegelmeyer
- University of North Carolina Health, 101 Manning Drive, Chapel Hill, NC, 27514, USA
| | - Chen Suo
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Nikola Tom
- EATRIS ERIC- European Infrastructure for Translational Medicine, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
- Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic
| | - Dong Wang
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Zhining Wen
- College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China
| | - Leihong Wu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Chang Xu
- Research and Development, QIAGEN Sciences Inc., Frederick, MD, 21703, USA
| | - Ying Yu
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Jiyang Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Yifan Zhang
- University of Arkansas at Little Rock, Little Rock, AR, 72204, USA
| | - Zhihong Zhang
- Research and Development, Burning Rock Biotech, Shanghai, 201114, China
| | - Yuanting Zheng
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY, 10065, USA
| | - James C Willey
- Departments of Medicine, Pathology, and Cancer Biology, College of Medicine and Life Sciences, University of Toledo Health Sciences Campus, 3000 Arlington Ave, Toledo, OH, 43614, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai, 200438, China
- Human Phenome Institute, Fudan University, Shanghai, 201203, China
- Fudan-Gospel Joint Research Center for Precision Medicine, Fudan University, Shanghai, 200438, China
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA.
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Li YW, Wang HJ, Cui W, Zhou P, Xiao W, Hu BT, Li F, Zhao SX, Wen Y. [Treatment of lumbar degenerative diseases with recapping laminoplasty and nerve root canal's decompression preserving the continuity of supraspinous ligament]. Zhonghua Yi Xue Za Zhi 2021; 101:641-646. [PMID: 33685046 DOI: 10.3760/cma.j.cn112137-20200601-01732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the clinical effect of lumbar discectomy and nerve root canal's enlargement preserving the continuity of supraspinous ligament in the treatment of lumbar degenerative disease. Methods: The data of patients with lumbar degenerative disease who underwent operation from 2016 to 2018 were analyzed retrospectively, and the patients were divided into two groups according to the different operation. The treatment group (17 cases) was treated with recapping laminoplasty, lumbar discectomy and nerve root canal's enlargement, and the control group (28 cases) was treated with total laminectomy, nerve root canal's enlargement, lumbar discectomy, interbody fusion and internal fixation (PLIF). All patients were followed up for 12 to 27 months (mean 17.8 months). Japanese Orthopaedic Association Scores(JOA) and visual analogue scale(VAS) of pain were used to evaluate the clinical effect before and after the operation, lumbar dynamical X-ray and Cobb angle were collecting for imaging evaluation, and the adjacent segment degeneration at the last follow-up was recorded. Results: There was no significant difference in preoperative JOA score, VAS score and Lumbar Cobb angle between the two groups (all P>0.05). The operation time in the treatment group was shorter than that in the control group, and the blood loss during operation in the treatment group was lower than that in the control group, the bed rest time of the treatment group after operation was shorter than that in the control group ((79±14) vs (118±17) min, (151±38) vs (324±70) ml and (3.4±0.7) vs (4.3±1.0) d,respectively; t=-8.508, -10.724, -3.244, all P<0.01). In addition, compared with the control group, the volume of postoperative drainage in the treatment group also decreased significantly (t=-5.637, P<0.01). There was no significant difference in JOA score between the two groups 1 year after the operation (P>0.05), but there was significant difference in VAS score between the two groups, the treatment group was better than the control group (P<0.05). Compared with the control group, the lumbar Cobb angle in the treatment group increased significantly one year after the operation (55.3°±3.2° vs 38.4°±6.2°, t=10.391, P<0.05). During the follow-up, no loosening or fracture of the implants was found in all patients. Conclusion: Treatment of lumbar degenerative diseases with recapping laminoplasty and nerve root canal's decompression preserving the continuity of supraspinous ligament by ultrasound osteotome has the same clinical effect as PLIF. It has the advantages of shortening operation time, less bleeding, better maintenance of lumbar lordosis after operation and reduction of adjacent segment degeneration.
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Affiliation(s)
- Y W Li
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - H J Wang
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - W Cui
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - P Zhou
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - W Xiao
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - B T Hu
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - F Li
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - S X Zhao
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
| | - Y Wen
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
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Zhang JH, Gu YJ, Yu L, Zhao LJ, Xiao W, Xu JF, Xu RM. [The feasibility of digital guidance drill template assisted expansive open-door laminoplasty]. Zhonghua Yi Xue Za Zhi 2021; 101:636-640. [PMID: 33685045 DOI: 10.3760/cma.j.cn112137-20200612-01829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore The feasibility of digital guidance drill templates assisted expansive open-door laminoplasty. Methods: Ten specimens of normal adult cervical spine (C3-7) were selected, including six males and four females. The specimens aged 42-67 years, with an average age of (43.6±4.2) years. After CT scanning, the date was imported into Mimics software in DICOM format. 3D models were reconstructed and the position and depth of troughs on the open side and hinge side were selected for expansive open-door laminoplasty. Drill templates were designed and exported in STL, manufactured by 3D printing finally. Then drill templates were attached to the posterior part of cervical lamina and spinous process. Under guidance of templates, troughs of both sides were conducted by using a high-speed drill. Then the lamina is elevated and instrumentations were implanted. Postoperative CT scanning was conducted to record the fracture of trough on the hinge side. 3D reconstruction was performed again to compare the position and depth between theory and actual trough on both sides by paired t test. Results: A total of 50 drill templates were designed and manufactured. There was no occurrence of hinge fracture after operation. In C3-7, the distance range between the theory position of troughs on the open side and the midline was 11.8-14.4 mm, while in actual it was 11.4-14.0 mm. The distance range between the theory position of troughs on the hinge side and the midline was 11.6-14.3 mm; in actual, it was 10.9-14.0 mm. The theory depth range of trough on the hinge side was 3.0-3.8 mm, while the actual depth was 3.1-3.8 mm. According to the statistical analysis, the difference in the position of trough on the open side, the position of trough on the hinge side and the depth of trough on the hinge side between theory and actual were not statistically significant (all P>0.05). Conclusion: Digital guided template assisted open-door laminoplasty is a feasible technique, which can improve the accuracy and safety of the position and depth of the trough, and has clinical application value.
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Affiliation(s)
- J H Zhang
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
| | - Y J Gu
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
| | - L Yu
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
| | - L J Zhao
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
| | - W Xiao
- Ningbo University School of Medicine, Ningbo 315211, China
| | - J F Xu
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
| | - R M Xu
- Department of Spinal Surgery, Ningbo NO.6 Hospital, Ningbo 315040, China
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Zhao LJ, Zhang JH, Gu YJ, Yu L, Wang LN, Xiao W, Xu RM. [Study on the best entry region and trajectory of anterior transpedicular root screws]. Zhonghua Yi Xue Za Zhi 2020; 100:3235-3239. [PMID: 33167110 DOI: 10.3760/cma.j.cn112137-20200309-00672] [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] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To evaluate the best entry region and trajectory of anterior transpedicular root screws (ATPRS). Methods: From January 2018 to May 2019, 50 cervical CT date integral of healthy people were selected from Ningbo No. 6 Hospital and were confirmed no obvious defect. Of these, 24 cases were males and 26 were females, aged 20-49 (32±5) years. The CT data was imported into Mimics by DICOM format, then 3D reconstruction was performed. In the coronal plane, the area from the centreline of the anterior of C(3-7) to the left Z-line(marked a line through the intersection of the anterior of the luschak joint and upper endplates, parallel to the centralline of the anterior of the vertebral body) was divided into nine areas. Then virtual screw with diameter of 3.5 mm was inserted. Record the length of screw of each area (L), the angle between screw and the posterior of the vertebral body in horizontal plane(α), the angle between screw and the anterior of the vertebral body in sagittal plane (β), individually. The data between groups were compared by independent sample t test. Results: The best regions were zone 9 of C(3), C(4); zone 8, 9 of C(5); zone 2-3, 5-9 of C(6); zone 1-9 of C(7) in men. And these were zone 9 of C(3); zone 3, 6, 8 and 9 of C(4), C(5); zone 2-3, 5-9 of C(6); zone 1-9 of C(7) in women. The distribution of best region was almost the same in men and women, zone 9 of each segment was the best region, and the screw length was the longest. It increased gradually from C(3) to C(7). C(3) had the least region, C(4) and C(5) had less, while C(6) and C(7) had the most. The horizontal angle of C(3-7) in men and women were 44.0°-47.2°, 40.2°-45.3° in zone 1, 4 and 7, respectively; 35.1°-41.4°, 34.6°-38.7° in zone 2, 5 and 8, respectively; 30.0°-37.2°, 30.2°-34.5° in zone 3, 6 and 9, respectively; and it demonstrated a gradually decreased trend. The sagittal angle of C(3-7) in men and women was 85.3°-97.4°, 80.5°-88.9° in zone 1-3, respectively; 101.2°-113.7°, 101.0°-109.3° in zone 4-6, respectively; 116.6°-128.8°, 119.9°-125.3° in zone 7-9, respectively; and it demonstrated a gradually increased trend. There was no significant difference in the horizontal and sagittal angle between men and women (both P>0.05). Conclusions: Anterior transpedicular root screw is a feasible internal fixation technique. It has wide region and the Z-line can be used as a reference for screw placement.
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Affiliation(s)
- L J Zhao
- Department of Spinal Surgery, Ningbo No. 6 Hospital, Ningbo 315040, China
| | - J H Zhang
- Department of Spinal Surgery, Ningbo No. 6 Hospital, Ningbo 315040, China
| | - Y J Gu
- Department of Spinal Surgery, Ningbo No. 6 Hospital, Ningbo 315040, China
| | - L Yu
- Department of Spinal Surgery, Ningbo No. 6 Hospital, Ningbo 315040, China
| | - L N Wang
- Ningbo University School of Medicine, Ningbo 315211, China
| | - W Xiao
- Ningbo University School of Medicine, Ningbo 315211, China
| | - R M Xu
- Department of Spinal Surgery, Ningbo No. 6 Hospital, Ningbo 315040, China
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Wang Q, Zhang S, Zhou C, Zeng Z, Ding P, Cheng G, Li L, Xiao W, Gao Y. Efficacy and Safety of High Dose Radiotherapy for the Treatment of Locally Advanced Rectal Cancer. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1939] [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: 11/16/2022]
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33
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Wang Q, Zhang R, Xiao W, Zhang S, Wei M, Li Y, Chang H, Xie W, Li L, Ding P, Wu X, Lu Z, Cheng G, Zeng Z, Pan Z, Wang W, Wan X, Gao Y, Xu R. Watch-and-wait Strategy against Surgical Resection for Rectal Cancer Patients with Complete Clinical Response after Neoadjuvant Chemoradiotherapy. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1821] [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: 10/23/2022]
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34
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Xiao W, Li M, Guo Z, Zhang R, Xi S, Zhang X, Li Y, Wu D, Ren Y, Pang X, Wan X, Li K, Zhou C, Zhai X, Wang Q, Zeng Z, Zhang H, Yang X, Wu Y, Li M, Gao Y. A Genotype Signature for Predicting Pathologic Complete Response in Locally Advanced Rectal Cancer. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2241] [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: 11/16/2022]
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35
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Ji X, Li P, Fuscoe JC, Chen G, Xiao W, Shi L, Ning B, Liu Z, Hong H, Wu J, Liu J, Guo L, Kreil DP, Łabaj PP, Zhong L, Bao W, Huang Y, He J, Zhao Y, Tong W, Shi T. A comprehensive rat transcriptome built from large scale RNA-seq-based annotation. Nucleic Acids Res 2020; 48:8320-8331. [PMID: 32749457 PMCID: PMC7470976 DOI: 10.1093/nar/gkaa638] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [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: 11/24/2019] [Revised: 07/14/2020] [Accepted: 07/21/2020] [Indexed: 01/01/2023] Open
Abstract
The rat is an important model organism in biomedical research for studying human disease mechanisms and treatments, but its annotated transcriptome is far from complete. We constructed a Rat Transcriptome Re-annotation named RTR using RNA-seq data from 320 samples in 11 different organs generated by the SEQC consortium. Totally, there are 52 807 genes and 114 152 transcripts in RTR. Transcribed regions and exons in RTR account for ∼42% and ∼6.5% of the genome, respectively. Of all 73 074 newly annotated transcripts in RTR, 34 213 were annotated as high confident coding transcripts and 24 728 as high confident long noncoding transcripts. Different tissues rather than different stages have a significant influence on the expression patterns of transcripts. We also found that 11 715 genes and 15 852 transcripts were expressed in all 11 tissues and that 849 house-keeping genes expressed different isoforms among tissues. This comprehensive transcriptome is freely available at http://www.unimd.org/rtr/. Our new rat transcriptome provides essential reference for genetics and gene expression studies in rat disease and toxicity models.
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Affiliation(s)
- Xiangjun Ji
- Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China.,School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Peng Li
- Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China.,Massachusetts General Hospital, Harvard Medical School, 51 Blossom St, Boston, MA 02114, USA
| | - James C Fuscoe
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Geng Chen
- Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China
| | - Wenzhong Xiao
- Massachusetts General Hospital, Harvard Medical School, 51 Blossom St, Boston, MA 02114, USA
| | - Leming Shi
- Center for Pharmacogenomics, School of Pharmacy, Fudan University, Shanghai, 200438, China
| | - Baitang Ning
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Zhichao Liu
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Huixiao Hong
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China
| | - Jinghua Liu
- School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China
| | - Lei Guo
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - David P Kreil
- Department of Biotechnology, Boku University Vienna, 1190 Muthgasse 18, Austria
| | - Paweł P Łabaj
- Department of Biotechnology, Boku University Vienna, 1190 Muthgasse 18, Austria.,Małopolska Centre of Biotechnology, Jagiellonian University, ul. Gronostajowa 7A, 30-387 Kraków, Poland
| | - Liping Zhong
- Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning 530021, China
| | - Wenjun Bao
- SAS Institute Inc., Cary, NC, 27513, USA
| | - Yong Huang
- Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning 530021, China
| | - Jian He
- Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning 530021, China
| | - Yongxiang Zhao
- Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning 530021, China
| | - Weida Tong
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, 100083, China
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Li GH, Dai S, Han F, Li W, Huang J, Xiao W. Correction to: FastMM: an efficient toolbox for personalized constraint-based metabolic modeling. BMC Bioinformatics 2020; 21:409. [PMID: 32938389 PMCID: PMC7493383 DOI: 10.1186/s12859-020-03723-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Gong-Hua Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Shaoxing Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Feifei Han
- Immue and Metabolic Computational Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Wenxing Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Jingfei Huang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China. .,Collaborative Innovation Center for Natural Products and Biological Drugs of Yunnan, Kunming, 650223, Yunnan, China.
| | - Wenzhong Xiao
- Immue and Metabolic Computational Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA. .,Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA.
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Yuan C, Han J, Chang H, Xiao W. Arabidopsis CK2 family gene CKB3 involved in abscisic acid signaling. BRAZ J BIOL 2020; 81:318-325. [PMID: 32491060 DOI: 10.1590/1519-6984.225345] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 12/14/2019] [Indexed: 11/22/2022] Open
Abstract
CKB3 is a regulatory (beta) subunit of CK2. In this study Arabidopsis thaliana homozygous T-DNA mutant ckb3 was studied to understand the role of CKB3 in abscisic acid (ABA) signaling. The results shown: CKB3 was expressed in all organs and the highest expression in the seeds, followed by the root. During seed germination and root growth the ckb3 mutant showed reduced sensitivity to ABA. The ckb3 mutant had more stomatal opening and increased proline accumulation and leaf water loss. The expression levels of number of genes in the ABA regulatory network had changed. This study demonstrates that CKB3 is an ABA signaling-related gene and may play a positive role in ABA signaling.
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Affiliation(s)
- C Yuan
- College of Life Science, Luoyang Normal University, Luoyang, PR China
| | - J Han
- College of Life Science, Luoyang Normal University, Luoyang, PR China
| | - H Chang
- College of Life Science and Engineering, Handan University, Handan, PR China
| | - W Xiao
- State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Biology, Hunan University, Changsha, PR China
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38
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Li R, Liu A, Wu T, Xiao W, Tang LI, Chen L. Digital scanned laser light-sheet fluorescence lifetime microscopy with wide-field time-gated imaging. J Microsc 2020; 279:69-76. [PMID: 32307699 DOI: 10.1111/jmi.12898] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 01/23/2020] [Revised: 03/21/2020] [Accepted: 04/14/2020] [Indexed: 01/01/2023]
Abstract
We develop a multidimensional fluorescence imaging technique by implementing a wide-field time-gated fluorescence lifetime imaging into digital scanned laser light-sheet microscopy (FLIM-DSLM) to measure 3D fluorescence lifetime distribution in mesoscopic specimens with high resolution. This is achieved by acquiring a series of time-gated images at different relative time delays with respect of excitation pulses at different depths. The lifetime is determined for each voxel by iteratively fitting to single exponential decay. The performance of the developed system is evaluated with the measurements of a lifetime reference Rhodamine 6G solution and a subresolution fluorescent bead phantom. We also demonstrate the application performances of this system to ex vivo and in vivo imaging of Tg(kdrl:EGFP) transgenic zebrafish embryos, illustrating the lifetime differences between the GFP signal and the autofluorescence signal. The results show that FLIM-DSLM can be used for sample size up to a few millimetres and can be utilised as a powerful and robust method for biomedical research, for example as a readout of protein-protein interactions via Förster resonance energy transfer.
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Affiliation(s)
- R Li
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
| | - A Liu
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
| | - T Wu
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
| | - W Xiao
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
| | - L I Tang
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
| | - Lingling Chen
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China.,College of Optoelectronics Engineering, Shenzhen University, Shenzhen, China
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Lu S, Chang CJ, Guan Y, Szafer-Glusman E, Punnoose E, Do A, Suttmann B, Gagnon R, Rodriguez A, Landers M, Spoerke J, Lackner MR, Xiao W, Wang Y. Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level. J Mol Diagn 2020; 22:770-781. [PMID: 32247862 PMCID: PMC8351127 DOI: 10.1016/j.jmoldx.2020.02.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [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: 09/06/2019] [Revised: 12/20/2019] [Accepted: 02/28/2020] [Indexed: 01/22/2023] Open
Abstract
Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification–based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non–small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non–small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.
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Affiliation(s)
- Shan Lu
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California; Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, California
| | - Chia-Jung Chang
- Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, California
| | - Yinghui Guan
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Edith Szafer-Glusman
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Elizabeth Punnoose
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - An Do
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Becky Suttmann
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Ross Gagnon
- Division of Expression Analysis Genomics, Q2 Solutions, Morrisville, North Carolina
| | - Angel Rodriguez
- Department of Translational Research, Epic Sciences Inc., San Diego, California
| | - Mark Landers
- Department of Translational Research, Epic Sciences Inc., San Diego, California
| | - Jill Spoerke
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Mark R Lackner
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California
| | - Wenzhong Xiao
- Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, California.
| | - Yulei Wang
- Department of Oncology Biomarker Development, Genentech Inc., South San Francisco, California.
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40
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Li YW, Wang HJ, Cui W, Xiao W, Hu BT, Li F. [Clinical safety and efficiency of ultrasonic bone curette used in anterior cervical discectomy and fusion surgery]. Zhonghua Yi Xue Za Zhi 2020; 100:669-673. [PMID: 32187909 DOI: 10.3760/cma.j.issn.0376-2491.2020.09.005] [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] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To investigate the safety and efficiency of ultrasonic bone curette used in anterior cervical discectomy and fusion surgery. Methods: As a retrospective study, we collected and analyzed the clinical data of 47 patients receiving anterior cervical discectomy and fusion surgery in Luohe Central Hospital from January 2014 to January 2017, there were 26 males and 21 females with a mean age of (52±9) years. According to the different surgical tools used in the process of decompression by resecting osteophytes or bone like an inverted Chinese character "" located at the posterior margin of the vertebral body, the patients were divided into two groups: ultrasonic bone curette group (group A) and traditional tools group (group B). The operating time, volume of intraoperative blood losing, complications, Japanese Orthopedic Association (JOA) score before and after the operation and improvement rate were recorded in the two groups. The t test was used to compare the data between the two groups. Results: In group A, the operating time was (47±7) min, blood loss was (49±4) ml, 1 case experienced urinary tract infection and there was no cerebrospinal fluid leakage or spinal cord injury. In group B, the operating time was (54±12) min and the blood loss was (117±16) ml, cerebrospinal fluid leakage occurred in 2 patients and the incision healed one-stage by local compression, hoarseness happened in 1 case and it disappeared after 2 weeks, 2 patients had swallowing discomfort and recovered in one month, no spinal cord injury occurred in this group. The operating time and blood loss in group A were lower than those in group B (t=2.691, 20.704, both P<0.05). And the incidence of complications in group A were lower than that in group B (χ(2)=4.157, P=0.041). The JOA score of group A at 3 days after surgery was improved for 39.0% when compared with that before the surgery, and it was improved for 71.6% at one year after the surgery. The JOA score in group B at 3 days after surgery was elevated for 38.7% from that before the surgery, and it increased for 69.4% at one year after the surgery. There was no significant different in JOA score before the surgery, 3 days and one year after the surgery between the two groups (t=0.611, 1.076, 0.061, all P>0.05). Conclusion: In the process of decompression by resecting osteophytes or bone located at the posterior margin of the vertebral body in the anterior cervical discectomy and fusion surgery, ultrasonic bone curette is safe and effective, and it can effectively shorten the operating time, decrease the blood loss and cut down the incidence of complications.
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Affiliation(s)
- Y W Li
- Department of Orthopedics, Luohe Central Hospital, Luohe 462000, China
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Li GH, Dai S, Han F, Li W, Huang J, Xiao W. FastMM: an efficient toolbox for personalized constraint-based metabolic modeling. BMC Bioinformatics 2020; 21:67. [PMID: 32085724 PMCID: PMC7035665 DOI: 10.1186/s12859-020-3410-4] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 02/12/2020] [Indexed: 11/24/2022] Open
Abstract
Background Constraint-based metabolic modeling has been applied to understand metabolism related disease mechanisms, to predict potential new drug targets and anti-metabolites, and to identify biomarkers of complex diseases. Although the state-of-art modeling toolbox, COBRA 3.0, is powerful, it requires substantial computing time conducting flux balance analysis, knockout analysis, and Markov Chain Monte Carlo (MCMC) sampling, which may limit its application in large scale genome-wide analysis. Results Here, we rewrote the underlying code of COBRA 3.0 using C/C++, and developed a toolbox, termed FastMM, to effectively conduct constraint-based metabolic modeling. The results showed that FastMM is 2~400 times faster than COBRA 3.0 in performing flux balance analysis and knockout analysis and returns consistent outputs. When applied to MCMC sampling, FastMM is 8 times faster than COBRA 3.0. FastMM is also faster than some efficient metabolic modeling applications, such as Cobrapy and Fast-SL. In addition, we developed a Matlab/Octave interface for fast metabolic modeling. This interface was fully compatible with COBRA 3.0, enabling users to easily perform complex applications for metabolic modeling. For example, users who do not have deep constraint-based metabolic model knowledge can just type one command in Matlab/Octave to perform personalized metabolic modeling. Users can also use the advance and multiple threading parameters for complex metabolic modeling. Thus, we provided an efficient and user-friendly solution to perform large scale genome-wide metabolic modeling. For example, FastMM can be applied to the modeling of individual cancer metabolic profiles of hundreds to thousands of samples in the Cancer Genome Atlas (TCGA). Conclusion FastMM is an efficient and user-friendly toolbox for large-scale personalized constraint-based metabolic modeling. It can serve as a complementary and invaluable improvement to the existing functionalities in COBRA 3.0. FastMM is under GPL license and can be freely available at GitHub site: https://github.com/GonghuaLi/FastMM.
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Affiliation(s)
- Gong-Hua Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Shaoxing Dai
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Feifei Han
- Immue and Metabolic Computational Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Wenxing Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Jingfei Huang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China. .,Collaborative Innovation Center for Natural Products and Biological Drugs of Yunnan, Kunming, 650223, Yunnan, China.
| | - Wenzhong Xiao
- Immue and Metabolic Computational Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA. .,Stanford Genome Technology Center, Stanford University, Palo Alto, CA, 94304, USA.
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42
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Li ZS, Ma S, Shan HW, Wang T, Xiao W. Responses of hemocyanin and energy metabolism to acute nitrite stress in juveniles of the shrimp Litopenaeus vannamei. Ecotoxicol Environ Saf 2019; 186:109753. [PMID: 31604159 DOI: 10.1016/j.ecoenv.2019.109753] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [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: 03/01/2019] [Revised: 05/21/2019] [Accepted: 10/01/2019] [Indexed: 06/10/2023]
Abstract
Nitrite is a common toxic substance in culture systems of Litopenaeus vannamei, and the stress may disturb hemocyanin synthesis and energy metabolism and result in shrimp death. In the present study, nitrite at concentrations of 0 (control), 3.3 (46.2 NO2-N mg/L), 6.6 (92.4) and 9.9 mM (138.6) was used to evaluate the responses of hemocyanin level and energy metabolism in L. vannamei (5.80 ± 0.44 cm, 1.88 ± 0.38 g) for 96 h. The mortality rate at 96 h increased with nitrite concentration (50% at 9.9 mM, 40% at 6.6 mM, 30% at 3.3 mM, and 10% at 0 mM). In general, HIF-1α and hemocyanin mRNA expression in the nitrite stress groups was upregulated from 6 to 12 h and downregulated from 24 to 96 h. In the hemolymph, nitrite levels were significantly elevated in a dose-dependent manner, and exposure to nitrite stress significantly decreased the oxyhemocyanin content from 24 to 96 h. The glucose and lactate levels in the hemolymph in the nitrite stress groups were higher than those in the control group from 12 to 96 h. Compared with the control group, the shrimp in the nitrite stress groups exhibited decreased glycogen concentrations in the hepatopancreas. The triglyceride (TG) levels in the nitrite stress groups were all higher than those in the control group from 48 to 96 h. The hexokinase (HK) activity in the hepatopancreas and muscle increased in the nitrite stress groups from 48 to 96 h. In general, nitrite stress enhanced the activities of pyruvate kinase (PK), phosphofructokinase (PFK) and lactate dehydrogenase (LDH) in muscle from 24 to 96 h. In addition, nitrite stress decreased the activities of succinate dehydrogenase (SDH) and fatty acid synthase (FAS) from 24 to 96 h in the hepatopancreas and muscle. This study indicates that exposure to nitrite stress can enhance the accumulation of nitrite in the hemolymph and then reduce oxygenation and hemocyanin synthesis, leading to tissue hypoxia and thereby resulting in accelerated anaerobic metabolism and the inhibition of aerobic metabolism. The effects of nitrite stress on hemocyanin synthesis and energy metabolism may be one of the reasons for the mortality of L. vannamei in culture systems.
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Affiliation(s)
- Z S Li
- The Key Laboratory of Mariculture (Ocean University of China), Ministry of Education, Qingdao, 266003, China.
| | - S Ma
- The Key Laboratory of Mariculture (Ocean University of China), Ministry of Education, Qingdao, 266003, China
| | - H W Shan
- The Key Laboratory of Mariculture (Ocean University of China), Ministry of Education, Qingdao, 266003, China.
| | - T Wang
- The Key Laboratory of Mariculture (Ocean University of China), Ministry of Education, Qingdao, 266003, China
| | - W Xiao
- The Key Laboratory of Mariculture (Ocean University of China), Ministry of Education, Qingdao, 266003, China
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43
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Zhang S, Luo J, Xie J, Wang Z, Xiao W, Zhao L. Cooperated biotransformation of ginsenoside extracts into ginsenoside 20(
S
)‐Rg3 by three thermostable glycosidases. J Appl Microbiol 2019; 128:721-734. [DOI: 10.1111/jam.14513] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 10/29/2019] [Accepted: 11/08/2019] [Indexed: 12/14/2022]
Affiliation(s)
- S. Zhang
- Co‐Innovation Center for Sustainable Forestry in Southern China Nanjing Forestry University Nanjing China
- College of Chemical Engineering Nanjing Forestry University Nanjing China
| | - J. Luo
- Co‐Innovation Center for Sustainable Forestry in Southern China Nanjing Forestry University Nanjing China
- College of Chemical Engineering Nanjing Forestry University Nanjing China
| | - J. Xie
- Co‐Innovation Center for Sustainable Forestry in Southern China Nanjing Forestry University Nanjing China
- College of Chemical Engineering Nanjing Forestry University Nanjing China
| | - Z. Wang
- Jiangsu Kanion Pharmaceutical Co. Ltd Lianyungang China
| | - W. Xiao
- Jiangsu Kanion Pharmaceutical Co. Ltd Lianyungang China
| | - L. Zhao
- Co‐Innovation Center for Sustainable Forestry in Southern China Nanjing Forestry University Nanjing China
- College of Chemical Engineering Nanjing Forestry University Nanjing China
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Abstract
1. Prolactin hormone (governed by the PRL gene) is secreted by the anterior pituitary of animals, which combines with its receptor (prolactin receptor, PRLR) to act on target cells. Both PRL and PRLR are mainly associated with reproductive performance. The genetic mechanism of nesting in poultry is not yet clear, and so the aim of the current study was to determine expression patterns of PRL and PRLR at different times across the breeding stages of black Muscovy ducks.2. In this study, the CDS regions of PRL and PRLR were determined by RACE sequencing. The expression levels of PRL and PRLR in the pituitary, ovary and uterus from the black Muscovy duck were compared and analysed during the pre-laying, laying and nesting periods.3. The results showed that PRL and PRLR are highly homologous in a variety of poultry species. The expression of the PRL gene in the pituitary was the highest, which was significantly higher than seen in the ovary and uterus. This trend ran through the entire prenatal period, i.e. the laying period and the nesting period. The expression level of the PRLR gene in the pituitary and ovary was generally low, and expression in the uterus was the highest. There was no significant difference in expression of the PRLR gene between pituitary and ovary during different periods, but the expression level of the PRLR gene in the uterus reached its highest level during the nesting stage, which was significantly higher than seen in the early laying period.
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Affiliation(s)
- X Li
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China.,National Gene Bank of Waterfowl Resources, Taizhou, Jiangsu, China
| | - W Ji
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China
| | - G Sun
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China.,National Gene Bank of Waterfowl Resources, Taizhou, Jiangsu, China
| | - W Xiao
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China.,National Gene Bank of Waterfowl Resources, Taizhou, Jiangsu, China
| | - Y Bian
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China.,National Gene Bank of Waterfowl Resources, Taizhou, Jiangsu, China
| | - H Qing
- Jiangsu Agri-Animal Husbandry Vocational College, Taizhou, Jiangsu, China.,National Gene Bank of Waterfowl Resources, Taizhou, Jiangsu, China
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45
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Xiao W. [Effects of inhaled bronchodilator therapy on left ventricular diastolic function in chronic obstructive pulmonary disease patients]. Zhonghua Jie He He Hu Xi Za Zhi 2019; 42:810-812. [PMID: 31694088 DOI: 10.3760/cma.j.issn.1001-0939.2019.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
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46
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Bai CX, Tang Y, Xin JB, Li YL, Li ZK, Kang J, Huang JA, Xiao W, Wen ZG, Fu XH, He B, Liu CT, Chen P. [The efficacy and safety of tiotropium/olodaterol fixed-dose combination in Chinese patients with chronic obstructive pulmonary disease: a pooled subgroup analysis of TONADO 1+2]. Zhonghua Jie He He Hu Xi Za Zhi 2019; 42:838-844. [PMID: 31694094 DOI: 10.3760/cma.j.issn.1001-0939.2019.11.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Objective: To compare the efficacy and safety profiles of tiotropium/olodaterol with the mono-components in Chinese and total study population from TONADO trial. Methods: In the replicate, double-blind, parallel-group, active-controlled, randomized, 52-week, Phase Ⅲ TONADO studies (TONADO 1+2), patients received tiotropium/olodaterol, tiotropium, or olodaterol via the Respimat(®) Inhaler (Boehringer Ingelheim, Germany). Primary end points were forced expiratory volume in 1 second (FEV(1)) area under the curve from 0 to 3 hours (AUC(0-3h)) response and trough FEV(1) response, and St George's respiratory questionnaire (SGRQ) total score at 24 weeks. Adverse events were also collected. This subgroup analysis only focused on the efficacy and safety of the drug at the approved dose in China. Results: 548 Chinese patients were randomized, aged 41 to 82 years [mean age, (63±8) years] and most were male (526, 96%), 111 received tiotropium/olodaterol 5/5 μg, and 127 received tiotropium 5 μg and 95 received olodaterol 5 μg. The baseline characteristics of these groups were similar. After 24 weeks, treatment with tiotropium/olodaterol 5/5 μg, tiotropium 5 μg and olodaterol 5 μg resulted in an adjusted mean FEV(1) AUC(0-3h) response of 0.240, 0.157 and 0.079 L, and trough FEV(1) response of 0.117, 0.068 and-0.001 L, respectively. Tiotropium/olodaterol 5/5 μg significantly improved SGRQ scores in Chinese patients compared with olodaterol 5 μg (32.729 and 37.202, respectively). Generally, the safety profile of tiotropium/olodaterol was comparable with mono-components in 52 weeks. Conclusion: Compared with tiotropium or olodaterol, tiotropium/olodaterol in Chinese patients provided significant improvement in lung function and quality of life, and the safety profiles were similar.
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Affiliation(s)
- C X Bai
- Department of Respiratory and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Y Tang
- Guangzhou Institute of Respiratory Diseases, the First Affiliated Hospital, Guangzhou Medical College, Guangzhou 510120, China
| | - J B Xin
- Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Y L Li
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China
| | - Z K Li
- Department of Respiratory and Critical Care Medicine, Shenzhen Hospital of Southern Medical University, Shenzhen 518110, China
| | - J Kang
- Department of Respiratory and Critical Care Medicine, the First Hospital of China Medical University, Shenyang 110001, China
| | - J A Huang
- Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Soochow University, Suzhou 215031, China
| | - W Xiao
- Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan 250002, China
| | - Z G Wen
- Department of Respiratory and Critical Care Medicine, Fourth Medical Center of PLA General Hospital, Beijing 100037, China
| | - X H Fu
- Department of Respiratory Diseases, the Affiliated Hospital of Inner Mongolia Medical University, Inner Mongolia 010050, China
| | - B He
- Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Beijing 100083, China
| | - C T Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - P Chen
- Department of Respiratory and Critical Care Medicine, the Second Xiangya Hospital of Central South University, Changsha 410007, China
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Miao J, Di M, Cao Y, Wang L, Xiao W, Zhu M, Chen B, Huang S, Han F, Deng X, Xiang Y, Chua M, Guo X, Zhao C. Long-term results of phase II trial of reduced modified clinical target volume in low-risk nasopharyngeal carcinoma treated with intensity modulated radiotherapy. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz428.004] [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: 11/13/2022] Open
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48
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Miao Q, Sui R, Wang J, Wang Q, Jiang W, Song L, Yu J, Cao L, Yu J, Feng L, Huang J, Xiao W, Xiao B, Ma C. Ginkgolide K induces myelin regeneration by immunoregulation. J Neurol Sci 2019. [DOI: 10.1016/j.jns.2019.10.782] [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: 11/28/2022]
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49
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Miao J, Di M, Cao Y, Wang L, Xiao W, Zhu M, Chen B, Huang S, Han F, Deng X, Xiang Y, Chua M, Guo X, Zhao C. Long-term results of phase II trial of reduced modified clinical target volume in low-risk nasopharyngeal carcinoma treated with intensity modulated radiotherapy. Ann Oncol 2019. [DOI: 10.1093/annonc/mdz252.033] [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: 11/14/2022] Open
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50
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Shaheen MA, Xiao W, Aziz M, Karim A, Saleem M, Mustaqeem M, Mehmood T, Tahir MN, Sultan A, Simair A, Lu C. Synthesis and Antibacterial Evaluation of Cu(II), Co(II), and Mn(II) Complexes with Schiff Bases Derived from 5-Aminosalicylic Acid and o-Vanillin. RUSS J GEN CHEM+ 2019. [DOI: 10.1134/s1070363219080231] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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