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Sun N, Shao H, Zhang Y, Ci B, Yao H, Bai B, Tan T. Establishing a 3D culture system for early organogenesis of monkey embryos ex vivo and single-cell transcriptome analysis of cultured embryos. STAR Protoc 2024; 5:102835. [PMID: 38224493 PMCID: PMC10826423 DOI: 10.1016/j.xpro.2023.102835] [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: 10/09/2023] [Revised: 11/30/2023] [Accepted: 12/27/2023] [Indexed: 01/17/2024] Open
Abstract
Creating in vitro culture platforms for monkey embryos is crucial for understanding the initial 4 weeks of early primate embryogenesis. Here, we present a protocol to culture cynomolgus monkey embryos in vitro for 25 days post-fertilization and to delineate the key developmental events of gastrulation and early organogenesis. We describe steps for culturing with a 3D system, immunofluorescence analysis, single-cell RNA sequencing, and bioinformatic analysis. For complete details on the use and execution of this protocol, please refer to Gong et al. (2023).1.
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Affiliation(s)
- Nianqin Sun
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
| | - Honglian Shao
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Youyue Zhang
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Baiquan Ci
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Hui Yao
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Bing Bai
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
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Xiang AY, Wang KH, Su W, Tan T, Qu YF, Li XQ, Wang Y, Cai MY, Li QL, Zhang YQ, Hu H, Zhou PH. Endoscopic resection of giant esophageal subepithelial lesions: experience from a large tertiary center. Gastrointest Endosc 2024; 99:358-370.e11. [PMID: 37852331 DOI: 10.1016/j.gie.2023.10.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/28/2023] [Accepted: 10/10/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND AND AIMS Increased reports on endoscopic resection (ER) of esophageal giant subepithelial lesions (g-SELs) have emerged in recent years. The aim of this study was to evaluate the efficacy, technical difficulty, and safety through our single-center experience. METHODS Seventy-five patients with g-SELs undergoing endoscopic resection were included in the training set. Clinicopathologic features, procedure-related characteristics, postprocedural outcomes, and follow-up data were analyzed. A predictive nomogram model for procedural difficulty was proposed based on the multivariable logistic regression analysis. Internal and external validations were conducted to verify the model performance. RESULTS The overall en bloc resection rate was 93.3%. Intraoperative and postoperative adverse events occurred in 7 (9.3%) and 13 (17.3%) patients, respectively. No recurrence or metastasis was observed. Thirty-two (42.7%) patients underwent a difficult procedure. Age (adjusted odds ratio [aOR], .915; P = .004), maximal tumor diameter ≥8 cm (aOR, 9.896; P = .009), irregular shape (aOR, 4.081; P = .053), extraluminal growth pattern (aOR, 5.419; P = .011), and submucosal tunneling endoscopic resection (aOR, .109; P = .042) were found to be statistically or clinically significant factors for predicting endoscopic resection difficulty, based on which a nomogram model was developed. Internal and external validations of the nomogram via receiver-operating characteristic curves and calibration curves achieved favorable results. CONCLUSIONS Endoscopic resection serves as a promising therapeutic option for esophageal g-SELs. A younger patient age, large tumor size, irregular shape, and extraluminal growth may indicate increased endoscopic resection difficulty, whereas a submucosal tunneling endoscopic resection procedure tends to be of lower difficulty. Our nomogram model performs well for predicting endoscopic resection difficulty for esophageal g-SELs.
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Affiliation(s)
- An-Yi Xiang
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ke-Hao Wang
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wei Su
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Tao Tan
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Yi-Fan Qu
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xiao-Qing Li
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yun Wang
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ming-Yan Cai
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Quan-Lin Li
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yi-Qun Zhang
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Hu
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Ping-Hong Zhou
- Endoscopy Center and Endoscopy Research Institute, Shanghai Collaborative Innovation Center of Endoscopy, Zhongshan Hospital, Fudan University, Shanghai, China.
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Jenkins LJ, Luk IY, Chionh F, Tan T, Needham K, Ayton J, Reehorst CM, Vukelic N, Sieber OM, Mouradov D, Gibbs P, Williams DS, Tebbutt NC, Desai J, Hollande F, Dhillon AS, Lee EF, Merino D, Fairlie WD, Mariadason JM. BCL-X L inhibitors enhance the apoptotic efficacy of BRAF inhibitors in BRAF V600E colorectal cancer. Cell Death Dis 2024; 15:183. [PMID: 38429301 PMCID: PMC10907349 DOI: 10.1038/s41419-024-06478-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 01/09/2024] [Accepted: 01/17/2024] [Indexed: 03/03/2024]
Abstract
Metastatic BRAFV600E colorectal cancer (CRC) carries an extremely poor prognosis and is in urgent need of effective new treatments. While the BRAFV600E inhibitor encorafenib in combination with the EGFR inhibitor cetuximab (Enc+Cet) was recently approved for this indication, overall survival is only increased by 3.6 months and objective responses are observed in only 20% of patients. We have found that a limitation of Enc+Cet treatment is the failure to efficiently induce apoptosis in BRAFV600E CRCs, despite inducing expression of the pro-apoptotic protein BIM and repressing expression of the pro-survival protein MCL-1. Here, we show that BRAFV600E CRCs express high basal levels of the pro-survival proteins MCL-1 and BCL-XL, and that combining encorafenib with a BCL-XL inhibitor significantly enhances apoptosis in BRAFV600E CRC cell lines. This effect was partially dependent on the induction of BIM, as BIM deletion markedly attenuated BRAF plus BCL-XL inhibitor-induced apoptosis. As thrombocytopenia is an established on-target toxicity of BCL-XL inhibition, we also examined the effect of combining encorafenib with the BCL-XL -targeting PROTAC DT2216, and the novel BCL-2/BCL-XL inhibitor dendrimer conjugate AZD0466. Combining encorafenib with DT2216 significantly increased apoptosis induction in vitro, while combining encorafenib with AZD0466 was well tolerated in mice and further reduced growth of BRAFV600E CRC xenografts compared to either agent alone. Collectively, these findings demonstrate that combined BRAF and BCL-XL inhibition significantly enhances apoptosis in pre-clinical models of BRAFV600E CRC and is a combination regimen worthy of clinical investigation to improve outcomes for these patients.
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Affiliation(s)
- Laura J Jenkins
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Ian Y Luk
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Fiona Chionh
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Tao Tan
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
| | - Kristen Needham
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Jamieson Ayton
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Camilla M Reehorst
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Natalia Vukelic
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Oliver M Sieber
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Surgery, The University of Melbourne, Melbourne, VIC, Australia
- Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Dmitri Mouradov
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
| | - Peter Gibbs
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - David S Williams
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
- Department of Pathology, Austin Health, Melbourne, VIC, Australia
| | - Niall C Tebbutt
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- Department of Surgery, The University of Melbourne, Melbourne, VIC, Australia
- Department of Medical Oncology, Austin Health, Melbourne, Australia
| | - Jayesh Desai
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Frédéric Hollande
- Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, VIC, Australia
| | - Amardeep S Dhillon
- The institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Geelong, Australia
| | - Erinna F Lee
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
- Department of Biochemistry and Chemistry, School of Agriculture, Biomedicine and Environment, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, VIC, Australia
| | - Delphine Merino
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Immunology Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - W Douglas Fairlie
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
- Department of Biochemistry and Chemistry, School of Agriculture, Biomedicine and Environment, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, VIC, Australia
| | - John M Mariadason
- Olivia Newton-John Cancer Research Institute, Melbourne, VIC, Australia.
- School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia.
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Jiao Y, van der Laak J, Albarqouni S, Li Z, Tan T, Bhalerao A, Cheng S, Ma J, Pocock J, Pluim JPW, Koohbanani NA, Bashir RMS, Raza SEA, Liu S, Graham S, Wetstein S, Khurram SA, Liu X, Rajpoot N, Veta M, Ciompi F. LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. IEEE J Biomed Health Inform 2024; 28:1161-1172. [PMID: 37878422 DOI: 10.1109/jbhi.2023.3327489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in images of colon, breast, and prostate cancer stained with CD3 and CD8 immunohistochemistry. Differently from other challenges setup in medical image analysis, LYSTO participants were solely given a few hours to address this problem. In this paper, we describe the goal and the multi-phase organization of the hackathon; we describe the proposed methods and the on-site results. Additionally, we present post-competition results where we show how the presented methods perform on an independent set of lung cancer slides, which was not part of the initial competition, as well as a comparison on lymphocyte assessment between presented methods and a panel of pathologists. We show that some of the participants were capable to achieve pathologist-level performance at lymphocyte assessment. After the hackathon, LYSTO was left as a lightweight plug-and-play benchmark dataset on grand-challenge website, together with an automatic evaluation platform.
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Xu W, Yang H, Shi Y, Tan T, Liu W, Pan X, Deng Y, Gao F, Su R. ERNet: Edge Regularization Network for Cerebral Vessel Segmentation in Digital Subtraction Angiography Images. IEEE J Biomed Health Inform 2024; 28:1472-1483. [PMID: 38090824 DOI: 10.1109/jbhi.2023.3342195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Abstract
Stroke is a leading cause of disability and fatality in the world, with ischemic stroke being the most common type. Digital Subtraction Angiography images, the gold standard in the operation process, can accurately show the contours and blood flow of cerebral vessels. The segmentation of cerebral vessels in DSA images can effectively help physicians assess the lesions. However, due to the disturbances in imaging parameters and changes in imaging scale, accurate cerebral vessel segmentation in DSA images is still a challenging task. In this paper, we propose a novel Edge Regularization Network (ERNet) to segment cerebral vessels in DSA images. Specifically, ERNet employs the erosion and dilation processes on the original binary vessel annotation to generate pseudo-ground truths of False Negative and False Positive, which serve as constraints to refine the coarse predictions based on their mapping relationship with the original vessels. In addition, we exploit a Hybrid Fusion Module based on convolution and transformers to extract local features and build long-range dependencies. Moreover, to support and advance the open research in the field of ischemic stroke, we introduce FPDSA, the first pixel-level semantic segmentation dataset for cerebral vessels. Extensive experiments on FPDSA illustrate the leading performance of our ERNet.
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van Tiel J, Tan T, Tee J, Marion T, Öner F, Rutges J. Outcome of traumatic thoracolumbar spine fractures in elderly: A systematic review. Brain Spine 2024; 4:102775. [PMID: 38510601 PMCID: PMC10951749 DOI: 10.1016/j.bas.2024.102775] [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] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 02/01/2024] [Accepted: 02/19/2024] [Indexed: 03/22/2024]
Abstract
Introduction Adequate guidelines for treatment of people over 65 years, suffering traumatic thoracolumbar spine fractures without neurologic deficit, are currently lacking. Research question The aim of this study was to systematically review the available literature regarding the outcome of conservative and surgical treatment of thoracolumbar spinal trauma in elderly patients. Material and methods A systematic review according the PRISMA guidelines was performed. Pubmed, Web of Science, EMBASE and the Cochrane Central register were searched until June 2021. Risk of bias of the included studies was evaluated. Clinical and radiological results, as well as complications of conservative or surgical treatment were reviewed. Results Six articles were included (one prospective randomized trial, two prospective and three retrospective cohort studies). In these studies conflicting results were observed with regard to pain, radiological results and complications following both conservative and surgical treatment strategies for thoracolumbar spine fractures in elderly. Discussion and conclusion Treatment of thoracolumbar fractures in elderly should focus on early mobilization to reduce complications and hospital stay. This may improve functional outcome and prevent worsening of frailty in this vulnerable group of patients. To elucidate the optimal treatment for elderly patient with thoracolumbar fractures, future research should focus on patient specific treatment rather than the mere difference between outcome of surgical and conservative treatment.
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Affiliation(s)
- J. van Tiel
- Department of Orthopedic Surgery, University Medical Center Utrecht, Utrecht, the Netherlands
| | - T. Tan
- Department of Neurosurgery, The Alfred Hospital, Melbourne, Victoria, Australia
- National Trauma Research Institute, Melbourne, Victoria, Australia
| | - J. Tee
- Department of Neurosurgery, The Alfred Hospital, Melbourne, Victoria, Australia
- National Trauma Research Institute, Melbourne, Victoria, Australia
| | - T.E. Marion
- Northern Ontario School of Medicine, Thunder Bay, ON, Canada
| | - F.C. Öner
- Department of Orthopedic Surgery, University Medical Center Utrecht, Utrecht, the Netherlands
| | - J.P.H.J. Rutges
- Department of Orthopedic Surgery, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, the Netherlands
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Ran P, Tan T, Li J, Yang H, Li J, Zhang J. Advanced gastrointestinal stromal tumor: reliable classification of imatinib plasma trough concentration via machine learning. BMC Cancer 2024; 24:264. [PMID: 38402382 PMCID: PMC10894477 DOI: 10.1186/s12885-024-11930-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/29/2024] [Indexed: 02/26/2024] Open
Abstract
AIM Patients with advanced gastrointestinal stromal tumors (GISTs) exhibiting an imatinib plasma trough concentration (IM Cmin) under 1100 ng/ml may show a reduced drug response rate, leading to the suggestion of monitoring for IM Cmin. Consequently, the objective of this research was to create a customized IM Cmin classification model for patients with advanced GISTs from China. METHODS Initial data and laboratory indicators from patients with advanced GISTs were gathered, and the above information was segmented into a training set, validation set, and testing set in a 6:2:2 ratio. Key variables associated with IM Cmin were identified to construct the classification model using the least absolute shrinkage and selection operator (LASSO) regression and forward stepwise binary logistic regression. Within the training and validation sets, nine ML classification models were constructed via the resampling method and underwent comparison through the Brier scores, the areas under the receiver-operating characteristic curve (AUROC), the decision curve, and the precision-recall (AUPR) curve to determine the most suitable model for this dataset. Two methods of internal validation were used to assess the most suitable model's classification performance: tenfold cross-validation and random split-sample validation (test set), and the value of the test set AUROC was used to evaluate the model's classification performance. RESULTS Six key variables (gender, daily IM dose, metastatic site, red blood cell count, platelet count, and percentage of neutrophils) were ultimately selected to construct the classification model. In the validation set, it is found by comparison that the Extreme Gradient Boosting (XGBoost) model has the largest AUROC, the lowest Brier score, the largest area under the decision curve, and the largest AUPR value. Furthermore, as evaluated via internal verification, it also performed well in the test set (AUROC = 0.725). CONCLUSION For patients with advanced GISTs who receive IM, initial data and laboratory indicators could be used to accurately estimate whether the IM Cmin is below 1100 ng/ml. The XGBoost model may stand a chance to assist clinicians in directing the administration of IM.
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Affiliation(s)
- Pan Ran
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Tao Tan
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jinjin Li
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Hao Yang
- Department of Internal Medicine, Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Juan Li
- Department of Pharmacy, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
| | - Jun Zhang
- Department of Gastrointestinal Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
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Li J, Xie K, Xu M, Wang Y, Huang Y, Tan T, Xie H. Significance of N6-methyladenosine RNA methylation regulators in diagnosis and subtype classification of primary Sjögren's syndrome. Heliyon 2024; 10:e24860. [PMID: 38318073 PMCID: PMC10839990 DOI: 10.1016/j.heliyon.2024.e24860] [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: 06/14/2023] [Revised: 01/10/2024] [Accepted: 01/16/2024] [Indexed: 02/07/2024] Open
Abstract
The importance of N6-methyladenine (m6A) in mRNA metabolism, physiology, pathology and other life processes is well recognized. However, the exact role of m6A regulators in primary Sjögren's syndrome (PSS) remains unclear. In this study, we used bioinformatics and machine learning random forest approach to screen eight key m6A regulators from the Gene Expression Omnibus GSE7451, GSE40611 and GSE84844 datasets. An accurate nomogram model for predicting PSS risk was established based on these regulators. And using consensus clustering, patients diagnosed with PSS were classified into two different m6A patterns. We found that patients in group B had higher m6A scores compared to those in group A: furthermore, both groups were closely related to immunity and possibly to other diseases. These results emphasise the important role of m6A regulators in the pathogenesis of PSS. Our study of m6A patterns may inform future immunotherapy strategies for PSS.
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Affiliation(s)
- Jiaoyan Li
- Department of Rheumatology and Clinical Immunology, The First Hospital of Changsha, Changsha, 410005, Hunan Province, PR China
| | - Kaihong Xie
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, PR China
| | - Minxian Xu
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, PR China
| | - Ye Wang
- Department of Thoracic Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, PR China
| | - Yinghong Huang
- Department of Rheumatology and Clinical Immunology, The First Hospital of Changsha, Changsha, 410005, Hunan Province, PR China
| | - Tao Tan
- Faulty of Applied Sciences, Macao Polytechnic University, Macao, 999078, PR China
| | - Hui Xie
- Faulty of Applied Sciences, Macao Polytechnic University, Macao, 999078, PR China
- Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, PR China
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Hou Y, Wang Q, Zhou K, Zhang L, Tan T. Integrated machine learning methods with oversampling technique for regional suitability prediction of waste-to-energy incineration projects. Waste Manag 2024; 174:251-262. [PMID: 38070444 DOI: 10.1016/j.wasman.2023.12.006] [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: 09/16/2023] [Revised: 11/12/2023] [Accepted: 12/04/2023] [Indexed: 01/16/2024]
Abstract
China's tiered strategy to enhance county-level waste incineration for energy aligns with the sustainable development goals (SDGs), emphasizing the need for comprehensive assessments of waste-to-energy (WtE) plant suitability. Traditional assessment methodologies face challenges, particularly in suggesting innovative site alternatives, adapting to new data sets, and their dependence on strict assumptions. This study introduced enhancements in three pivotal dimensions. Methodologically, it leverages data-driven machine learning (ML) approaches to capture the complex relationships essential for site selection, reducing dependency on strict assumptions. In terms of predictive performance, the integration of oversampling with stacked ensemble models enhances the diversity and generalizability of ML models. The area under curve (AUC) scores from four ML models, enhanced by the oversampled dataset, demonstrated significant improvements compared to the original dataset. The stacking model excelled, achieving a score of 92%. It also led in overall Precision and Recall, reaching 85.2% and 85.08% respectively. Nevertheless, a noticeable discrepancy existed in Precision and Recall for positive classes. The stacking model topped Precision scores at 83.1%, followed by eXtreme Gradient Boosting (XGBoost) (82.61%). In terms of Recall, XGBoost recorded the lowest at 85.07%, while the other three classifiers all marked 88.06%. From an industry applicability standpoint, the stacking model provides innovative location alternatives and demonstrates adaptability in Hunan province, offering a reusable tool for WtE location. In conclusion, this study not only enhances the methodological aspects of WtE site selection but also provides practical and adaptable solutions, contributing positively to sustainable waste management practices.
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Affiliation(s)
- Yali Hou
- College of Information Engineering, Nanjing Xiaozhuang University, Nanjing 211171, China
| | - Qunwei Wang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
| | - Kai Zhou
- College of Information Engineering, Nanjing Xiaozhuang University, Nanjing 211171, China
| | - Ling Zhang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China; Research Centre for Soft Energy Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
| | - Tao Tan
- College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China.
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Hu S, Fan H, Zhang S, Chen C, You Y, Wang C, Li J, Luo L, Cheng Y, Zhou M, Zhao X, Wen W, Tan T, Xu F, Fu X, Chen J, Zhang X, Wang M, Tang J. Association of LDL-C/HDL-C ratio with coronary heart disease: A meta-analysis. Indian Heart J 2024:S0019-4832(24)00014-2. [PMID: 38342141 DOI: 10.1016/j.ihj.2024.01.014] [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: 08/05/2023] [Revised: 12/07/2023] [Accepted: 01/29/2024] [Indexed: 02/13/2024] Open
Abstract
BACKGROUND Coronary heart disease (CHD) is a common heart disease and a leading cause of death in developed countries and some developing countries such as China. It is recognized as a multifactorial disease, with dyslipidemia being closely associated with the progression of coronary atherosclerosis. Numerous studies have confirmed the relationship between a single indicator of low-density lipoprotein cholesterol (LDL-C) or high-density lipoprotein cholesterol (HDL-C) and CHD. However, the association between LDL-C to HDL-C ratio (LHR) and CHD remains unclear. This study aimed to comprehensively explore the association between LHR and CHD. METHODS This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses. PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were comprehensively searched up to June 15, 2023, to find the studies that indicated the connection between LHR and CHD. A total of 12 published studies were selected. The random-effects model was used to pool the data and mean difference (MD), and the 95% confidence intervals (CI) were taken as the overall outcome. No language restrictions existed in the study selection. The Review Manager 5.4 and Stata 12 were used to analyze the data. RESULTS Twelve high-quality clinical studies involving 5544 participants, including 3009 patients with CHD, were enrolled in the meta-analysis. The findings revealed that the LHR was higher by 0.65 in patients with CHD than in those without CHD (MD, 0.65; 95% CI, 0.50-0.80). CONCLUSION The LHR was found to be positively correlated with CHD, suggesting that it may serve as a potential indicator of CHD.
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Affiliation(s)
- Siqi Hu
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Hua Fan
- School of Clinical Medicine, The First Affiliated Hospital of Henan University of Science and Technology, Henan University of Science and Technology, Luoyang, 471003, Henan, China
| | - Shenghui Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Chen Chen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Yao You
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Chunyi Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Jie Li
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Lin Luo
- Hangzhou Ruolin Hospital Management Co. Ltd, Hangzhou, 310007, China
| | - Yongran Cheng
- School of Public Health, Hangzhou Medical College, Hangzhou, 311300, China
| | - Mengyun Zhou
- Department of Molecular & Cellular Physiology, Shinshu University School of Medicine, 3900803, Japan
| | - Xuezhi Zhao
- Department of Gynecology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, 310006, Zhejiang, China
| | - Wen Wen
- Department of Cardiology, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, 313000, Zhejiang, China
| | - Tao Tan
- Faculty of Applied Science, Macao Polytechnic University, Macao SAR, 999078, China
| | - Fangfang Xu
- Strategy Research and Knowledge Information Center, SAIC Motor Group, 200030, Shanghai, China
| | - Xinyan Fu
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Juan Chen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China
| | - Xingwei Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China.
| | - Mingwei Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China.
| | - Jiake Tang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou, 311321, China.
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11
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Wang Z, Burigotto M, Ghetti S, Vaillant F, Tan T, Capaldo BD, Palmieri M, Hirokawa Y, Tai L, Simpson DS, Chang C, Huang AS, Lieschke E, Diepstraten ST, Kaloni D, Riffkin C, Huang DC, Li Wai Suen CS, Garnham AL, Gibbs P, Visvader JE, Sieber OM, Herold MJ, Fava LL, Kelly GL, Strasser A. Loss-of-Function but Not Gain-of-Function Properties of Mutant TP53 Are Critical for the Proliferation, Survival, and Metastasis of a Broad Range of Cancer Cells. Cancer Discov 2024; 14:362-379. [PMID: 37877779 PMCID: PMC10850947 DOI: 10.1158/2159-8290.cd-23-0402] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 10/03/2023] [Accepted: 10/23/2023] [Indexed: 10/26/2023]
Abstract
Mutations in the tumor suppressor TP53 cause cancer and impart poor chemotherapeutic responses, reportedly through loss-of-function, dominant-negative effects and gain-of-function (GOF) activities. The relative contributions of these attributes is unknown. We found that removal of 12 different TP53 mutants with reported GOFs by CRISPR/Cas9 did not impact proliferation and response to chemotherapeutics of 15 human cancer cell lines and colon cancer-derived organoids in culture. Moreover, removal of mutant TP53/TRP53 did not impair growth or metastasis of human cancers in immune-deficient mice or growth of murine cancers in immune-competent mice. DepMap mining revealed that removal of 158 different TP53 mutants had no impact on the growth of 391 human cancer cell lines. In contrast, CRISPR-mediated restoration of wild-type TP53 extinguished the growth of human cancer cells in vitro. These findings demonstrate that LOF but not GOF effects of mutant TP53/TRP53 are critical to sustain expansion of many tumor types. SIGNIFICANCE This study provides evidence that removal of mutant TP53, thereby deleting its reported GOF activities, does not impact the survival, proliferation, metastasis, or chemotherapy responses of cancer cells. Thus, approaches that abrogate expression of mutant TP53 or target its reported GOF activities are unlikely to exert therapeutic impact in cancer. See related commentary by Lane, p. 211 . This article is featured in Selected Articles from This Issue, p. 201.
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Affiliation(s)
- Zilu Wang
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Matteo Burigotto
- Armenise-Harvard Laboratory of Cell Division, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - Sabrina Ghetti
- Armenise-Harvard Laboratory of Cell Division, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - François Vaillant
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Tao Tan
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Bianca D. Capaldo
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Michelle Palmieri
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Yumiko Hirokawa
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Lin Tai
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
| | - Daniel S. Simpson
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Catherine Chang
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
| | - Allan Shuai Huang
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Elizabeth Lieschke
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Sarah T. Diepstraten
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Deeksha Kaloni
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Chris Riffkin
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
| | - David C.S. Huang
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Connie S.N. Li Wai Suen
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Alexandra L. Garnham
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Peter Gibbs
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Jane E. Visvader
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Oliver M. Sieber
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Marco J. Herold
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Luca L. Fava
- Armenise-Harvard Laboratory of Cell Division, Department of Cellular, Computational and Integrative Biology – CIBIO, University of Trento, Trento, Italy
| | - Gemma L. Kelly
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
| | - Andreas Strasser
- The Walter and Eliza Hall Institute (WEHI), Melbourne, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, Australia
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12
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Yang S, Song D, Wang R, Liu M, Tan T, Wang Y, Xie Q, Wang L. Sodium fluoride-induced autophagy of ameloblast-like cells via the p-ULk1/ATG13/LC3B pathway in vitro. Oral Dis 2024. [PMID: 38321366 DOI: 10.1111/odi.14884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 01/05/2024] [Accepted: 01/18/2024] [Indexed: 02/08/2024]
Abstract
OBJECTIVE To investigate the effects of sodium fluoride on the ameloblast and reveal the mechanism of dental fluorosis. MATERIALS AND METHODS Mouse ameloblast-like cell line (ALC) cells were treated with various concentrations of NaF, and subjected to Incucyte, fluorescence immunoassay, transmission electron microscopy, reverse transcription quantitative polymerase chain reaction (RT-qPCR), western blot for autophagy examination, alkaline phosphatase and alizarin red staining for mineralization after osteogenic induction. RESULTS NaF exerts a dose-dependent inhibitory effect on ALC cell growth. TEM and fluorescence immunoassay showed that 1.5 mM or higher concentrations of NaF could induce a fusion of lysosome and mitochondria, finally increasing the number of autophagosome. RT-qPCR and western blot showed that the upregulation of autophagy related gene 13 (ATG13), downregulation of phosphorylated Unc-51-like kinase 1 (p-ULK1) were found in NaF-induced autophagy of ALC cells. The knockdown of ATG13 could rescue it as well as the expression of p-ULK1 and LC3B. Besides, alizarin red staining showed that fluoride under these concentrations could promote the mineralization of ALC. CONCLUSIONS The data show that fluoride in higher concentration can induce autophagy via the p-ULk1/ATG13/LC3B pathway of ALCs than lower ones promote mineralization in vitro, which provides insight into the function of NaF in the autophagy and mineralization of ameloblast.
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Affiliation(s)
- S Yang
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - D Song
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - R Wang
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - M Liu
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - T Tan
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - Y Wang
- Central Laboratory, Peking University School and Hospital of Stomatology, Beijing, China
| | - Q Xie
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
| | - L Wang
- Department of Prosthodontics, School and Hospital of Stomatology, Peking University, Beijing, China
- National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, Beijing, China
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13
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Han L, Tan T, Zhang T, Huang Y, Wang X, Gao Y, Teuwen J, Mann R. Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI. Med Image Anal 2024; 92:103044. [PMID: 38043455 DOI: 10.1016/j.media.2023.103044] [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: 03/08/2023] [Revised: 10/14/2023] [Accepted: 11/24/2023] [Indexed: 12/05/2023]
Abstract
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences. However, redundant information exists across sequences, which interferes with mining efficient representations by learning-based models. To handle various clinical scenarios, we propose a sequence-to-sequence generation framework (Seq2Seq) for imaging-differentiation representation learning. In this study, not only do we propose arbitrary 3D/4D sequence generation within one model to generate any specified target sequence, but also we are able to rank the importance of each sequence based on a new metric estimating the difficulty of a sequence being generated. Furthermore, we also exploit the generation inability of the model to extract regions that contain unique information for each sequence. We conduct extensive experiments using three datasets including a toy dataset of 20,000 simulated subjects, a brain MRI dataset of 1251 subjects, and a breast MRI dataset of 2101 subjects, to demonstrate that (1) top-ranking sequences can be used to replace complete sequences with non-inferior performance; (2) combining MRI with our imaging-differentiation map leads to better performance in clinical tasks such as glioblastoma MGMT promoter methylation status prediction and breast cancer pathological complete response status prediction. Our code is available at https://github.com/fiy2W/mri_seq2seq.
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Affiliation(s)
- Luyi Han
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands; Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Tao Tan
- Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands; Faculty of Applied Sciences, Macao Polytechnic University, 999078, Macao Special Administrative Region of China.
| | - Tianyu Zhang
- Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, P. Debyelaan 25, 6202 AZ, Maastricht, The Netherlands
| | - Yunzhi Huang
- Institute for AI in Medicine, School of Automation, Nanjing University of Information Science and Technology, Nanjing, China
| | - Xin Wang
- Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, P. Debyelaan 25, 6202 AZ, Maastricht, The Netherlands
| | - Yuan Gao
- Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands; GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, P. Debyelaan 25, 6202 AZ, Maastricht, The Netherlands
| | - Jonas Teuwen
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Ritse Mann
- Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands; Department of Radiology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
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14
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Duan Y, Zhang H, Tan T, Ye W, Yin K, Yu Y, Kang M, Yang J, Liao R. The immune response of hepatocellular carcinoma after locoregional and systemic therapies: The available combination option for immunotherapy. Biosci Trends 2024; 17:427-444. [PMID: 37981319 DOI: 10.5582/bst.2023.01275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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] [Indexed: 11/21/2023]
Abstract
Hepatocellular carcinoma (HCC) is associated with a highly heterogeneous immune environment that produces an immune response to various locoregional treatments (LRTs), which in turn affects the effectiveness of immunotherapy. Although LRTs still dominate HCC therapies, 50-60% of patients will ultimately be treated with systemic therapies and might receive those treatments for the rest of their life. TACE, SIRT, and thermal ablation can dramatically increase the immunosuppressive state of HCC, a condition that can be addressed by combination with immunotherapy to restore the activity of lymphocytes and the secretion of cellular immune factors. Immune treatment with locoregional and systemic treatments has dramatically changed the management of HCC. In this review, we examine the research on the changes in the immune microenvironment after locoregional or systemic treatment. We also summarize the regulation of various immune cells and immune factors in the tumor microenvironment and discuss the different infiltration degrees of immune cells and factors on the prognosis of HCC to better compare the efficacy between different treatment methods from the perspective of the tumor microenvironment. This information can be used to help develop treatment options for the upcoming new era of HCC treatment in the future.
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Affiliation(s)
- Yuxin Duan
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hua Zhang
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tao Tan
- Chongqing Health Statistics Information Center, Chongqing, China
| | - Wentao Ye
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Kunli Yin
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yanxi Yu
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Meiqing Kang
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jian Yang
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Rui Liao
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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15
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Xu M, Chen H, Tan T, Xie K, Xie H, Li Q. Exploring the causal association between rheumatoid arthritis and the risk of cervical cancer: a two-sample Mendelian randomization study. Arthritis Res Ther 2024; 26:35. [PMID: 38263277 PMCID: PMC10804645 DOI: 10.1186/s13075-023-03240-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVE Whether rheumatoid arthritis patients have an increased risk of cervical cancer remains controversial, and further research is needed on this clinical question. This study aims to investigate the association between rheumatoid arthritis and the susceptibility to cervical cancer by employing Mendelian randomization methodology, utilizing the extensive dataset from human genome-wide association data analysis. METHODS The publicly accessible MR base database was utilized to obtain the complete genome, relevant research findings, and summarized data pertaining to rheumatoid arthritis and cervical cancer. Genetic tool variables, specifically single-nucleotide polymorphisms closely linked to rheumatoid arthritis, were chosen for analysis. Four methods, namely inverse variance weighted analysis, weighted median analysis, weighted mode, and MR-Egger regression, were employed. Statistical analysis was conducted to explore the potential association between rheumatoid arthritis and susceptibility to cervical cancer. RESULTS The results of the inverse variance weighted analysis (OR = 1.096, 95% CI: 1.018-1.180, P = 0.015) indicate a significant causal relationship between rheumatoid arthritis and an increased risk of cervical cancer. Furthermore, the absence of horizontal pleiotropic effects (MR-Egger intercept = 0.00025, P = 0.574) and heterogeneity (QEgger = 2.239, I2Egger = 0.225, PEgger = 0.268, QIVW = 2.734, I2IVW = 0.220, PIVW = 0.999) suggests that the observed association is not influenced by confounding factors. Sensitivity analysis and other statistical methods also support the conclusion that genetic pleiotropy does not introduce bias to the findings. CONCLUSION There is a causal relationship between rheumatoid arthritis and the occurrence of cervical cancer. People with rheumatoid arthritis is one of the high-risk groups for early screening of cervical cancer. The IL-18 may play a significant role in elevating the risk of cervical cancer among rheumatoid arthritis patients.
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Affiliation(s)
- Minxian Xu
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China
- Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, People's Republic of China
| | - Huan Chen
- Department of Gynecology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China
| | - Tao Tan
- Faulty of Applied Sciences, Macao Polytechnic University, Macao, 999078, People's Republic of China
| | - Kaihong Xie
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China
| | - Hui Xie
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China.
- Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, People's Republic of China.
| | - Qing Li
- Department of Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China.
- Department of Radiation Oncology, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, Hunan Province, People's Republic of China.
- School of Medical Imaging, Laboratory Science and Rehabilitation, Xiangnan University, 423000, Chenzhou, Hunan Province, People's Republic of China.
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16
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Hou R, Guo Q, Wu Q, Zhao Z, Hu X, Yan Y, He W, Lyu P, Su R, Tan T, Wang X, Li Y, He D, Xu L. Quantification of Hypsarrhythmia in Infantile Spasmatic EEG: A Large Cohort Study. IEEE Trans Neural Syst Rehabil Eng 2024; 32:350-357. [PMID: 38194391 DOI: 10.1109/tnsre.2024.3351670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Infantile spasms (IS) is a neurological disorder causing mental and/or developmental retardation in many infants. Hypsarrhythmia is a typical symptom in the electroencephalography (EEG) signals with IS. Long-term EEG/video monitoring is most frequently employed in clinical practice for IS diagnosis, from which manual screening of hypsarrhythmia is time consuming and lack of sufficient reliability. This study aims to identify potential biomarkers for automatic IS diagnosis by quantitative analysis of the EEG signals. A large cohort of 101 IS patients and 155 healthy controls (HC) were involved. Typical hypsarrhythmia and non-hypsarrhythmia EEG signals were annotated, and normal EEG were randomly picked from the HC. Root mean square (RMS), teager energy (TE), mean frequency, sample entropy (SamEn), multi-channel SamEn, multi-scale SamEn, and nonlinear correlation coefficient were computed in each sub-band of the three EEG signals, and then compared using either a one-way ANOVA or a Kruskal-Wallis test (based on their distribution) and the receiver operating characteristic (ROC) curves. The effects of infant age on these features were also investigated. For most of the employed features, significant ( ) differences were observed between hypsarrhythmia EEG and non-hypsarrhythmia EEG or HC, which seem to increase with increased infant age. RMS and TE produce the best classification in the delta and theta bands, while entropy features yields the best performance in the gamma band. Our study suggests RMS and TE (delta and theta bands) and entropy features (gamma band) to be promising biomarkers for automatic detection of hypsarrhythmia in long-term EEG monitoring. The findings of our study indicate the feasibility of automated IS diagnosis using artificial intelligence.
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17
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Zhao K, Zhou X, Chen M, Gou L, Mei D, Gao C, Zhao S, Luo S, Wang X, Tan T, Zhang Y. Neuroprotective Effects of CXCR2 Antagonist SB332235 on Traumatic Brain Injury Through Suppressing NLRP3 Inflammasome. Neurochem Res 2024; 49:184-198. [PMID: 37702890 PMCID: PMC10776743 DOI: 10.1007/s11064-023-04021-8] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/19/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023]
Abstract
The inflammatory process mediated by nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain comprising 3 (NLRP3) inflammasome plays a predominant role in the neurological dysfunction following traumatic brain injury (TBI). SB332235, a highly selective antagonist of chemokine receptor 2 (CXCR2), has been demonstrated to exhibit anti-inflammatory properties and improve neurological outcomes in the central nervous system. We aimed to determine the neuroprotective effects of SB332235 in the acute phase after TBI in mice and to elucidate its underlying mechanisms. Male C57BL/6J animals were exposed to a controlled cortical impact, then received 4 doses of SB332235, with the first dose administered at 30 min after TBI, followed by additional doses at 6, 24, and 30 h. Neurological defects were assessed by the modified neurological severity score, while the motor function was evaluated using the beam balance and open field tests. Cognitive performance was evaluated using the novel object recognition test. Brain tissues were collected for pathological, Western blot, and immunohistochemical analyses. The results showed that SB332235 significantly ameliorated TBI-induced deficits, including motor and cognitive impairments. SB332235 administration suppressed expression of both CXCL1 and CXCR2 in TBI. Moreover, SB332235 substantially mitigated the augmented expression levels and activation of the NLRP3 inflammasome within the peri-contusional cortex induced by TBI. This was accompanied by the blocking of subsequent production of pro-inflammatory cytokines. Additionally, SB332235 hindered microglial activity induced by TBI. These findings confirmed the neuroprotective effects of SB332235 against TBI, and the involved mechanisms were in part due to the suppression of NLRP3 inflammasome activity. This study suggests that SB332235 may act as an anti-inflammatory agent to improve functional outcomes in brain injury when applied clinically.
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Affiliation(s)
- Ke Zhao
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China
| | - Xinkui Zhou
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China
| | - Mengyuan Chen
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China
| | - Lingshan Gou
- Center for Genetic Medicine, Xuzhou Maternity and Child Health Care Hospital Affiliated to Xuzhou Medical University, Xuzhou, China
| | - Daoqi Mei
- Department of Neurology, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Chao Gao
- Department of Rehabilitation, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Shuai Zhao
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China
| | - Shuying Luo
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China
| | - Xiaona Wang
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China.
| | - Tao Tan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - Yaodong Zhang
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Children's Neurodevelopment Engineering Research Center, Zhengzhou, China.
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Yang H, Tan T, Tegzes P, Dong X, Tamada R, Ferenczi L, Avinash G. Light mixed-supervised segmentation for 3D medical image data. Med Phys 2024; 51:167-178. [PMID: 37909833 DOI: 10.1002/mp.16816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 10/03/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND Accurate 3D semantic segmentation models are essential for many clinical applications. To train a model for 3D segmentation, voxel-level annotation is necessary, which is expensive to obtain due to laborious work and privacy protection. To accurately annotate 3D medical data, such as MRI, a common practice is to annotate the volumetric data in a slice-by-slice contouring way along principal axes. PURPOSE In order to reduce the annotation effort in slices, weakly supervised learning with a bounding box (Bbox) was proposed to leverage the discriminating information via a tightness prior assumption. Nevertheless, this method requests accurate and tight Bboxes, which will significantly drop the performance when tightness is not held, that is when a relaxed Bbox is applied. Therefore, there is a need to train a stable model based on relaxed Bbox annotation. METHODS This paper presents a mixed-supervised training strategy to reduce the annotation effort for 3D segmentation tasks. In the proposed approach, a fully annotated contour is only required for a single slice of the volume. In contrast, the rest of the slices with targets are annotated with relaxed Bboxes. This mixed-supervised method adopts fully supervised learning, relaxed Bbox prior, and contrastive learning during the training, which ensures the network exploits the discriminative information of the training volumes properly. The proposed method was evaluated on two public 3D medical imaging datasets (MRI prostate dataset and Vestibular Schwannoma [VS] dataset). RESULTS The proposed method obtained a high segmentation Dice score of 85.3% on an MRI prostate dataset and 83.3% on a VS dataset with relaxed Bbox annotation, which are close to a fully supervised model. Moreover, with the same relaxed Bbox annotations, the proposed method outperforms the state-of-the-art methods. More importantly, the model performance is stable when the accuracy of Bbox annotation varies. CONCLUSIONS The presented study proposes a method based on a mixed-supervised learning method in 3D medical imaging. The benefit will be stable segmentation of the target in 3D images with low accurate annotation requirement, which leads to easier model training on large-scale datasets.
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Affiliation(s)
| | - Tao Tan
- GE Healthcare, Eindhoven, The Netherlands
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Yao L, Li X, Wu Z, Wang J, Luo C, Chen B, Luo R, Zhang L, Zhang C, Tan X, Lu Z, Zhu C, Huang Y, Tan T, Liu Z, Li Y, Li S, Yu H. Effect of artificial intelligence on novice-performed colonoscopy: a multicenter randomized controlled tandem study. Gastrointest Endosc 2024; 99:91-99.e9. [PMID: 37536635 DOI: 10.1016/j.gie.2023.07.044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/21/2023] [Accepted: 07/22/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND AIMS The efficacy and safety of colonoscopy performed by artificial intelligence (AI)-assisted novices remain unknown. The aim of this study was to compare the lesion detection capability of novices, AI-assisted novices, and experts. METHODS This multicenter, randomized, noninferiority tandem study was conducted across 3 hospitals in China from May 1, 2022, to November 11, 2022. Eligible patients were randomized into 1 of 3 groups: the CN group (control novice group, withdrawal performed by a novice independently), the AN group (AI-assisted novice group, withdrawal performed by a novice with AI assistance), or the CE group (control expert group, withdrawal performed by an expert independently). Participants underwent a repeat colonoscopy conducted by an AI-assisted expert to evaluate the lesion miss rate and ensure lesion detection. The primary outcome was the adenoma miss rate (AMR). RESULTS A total of 685 eligible patients were analyzed: 229 in the CN group, 227 in the AN group, and 229 in the CE group. Both AMR and polyp miss rate were lower in the AN group than in the CN group (18.82% vs 43.69% [P < .001] and 21.23% vs 35.38% [P < .001], respectively). The noninferiority margin was met between the AN and CE groups of both AMR and polyp miss rate (18.82% vs 26.97% [P = .202] and 21.23% vs 24.10% [P < .249]). CONCLUSIONS AI-assisted colonoscopy lowered the AMR of novices, making them noninferior to experts. The withdrawal technique of new endoscopists can be enhanced by AI-assisted colonoscopy. (Clinical trial registration number: NCT05323279.).
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Affiliation(s)
- Liwen Yao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xun Li
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhifeng Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jing Wang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chaijie Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Boru Chen
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Renquan Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihui Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chenxia Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xia Tan
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zihua Lu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ci Zhu
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Yuan Huang
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Tao Tan
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Zhifeng Liu
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Ying Li
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Shuyu Li
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China.
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Wei Y, Zhang E, Yu L, Ci B, Sakurai M, Guo L, Zhang X, Lin S, Takii S, Liu L, Liu J, Schmitz DA, Su T, Zhang J, Shen Q, Ding Y, Zhan L, Sun HX, Zheng C, Xu L, Okamura D, Ji W, Tan T, Wu J. Dissecting embryonic and extraembryonic lineage crosstalk with stem cell co-culture. Cell 2023; 186:5859-5875.e24. [PMID: 38052213 PMCID: PMC10916932 DOI: 10.1016/j.cell.2023.11.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 09/01/2023] [Accepted: 11/02/2023] [Indexed: 12/07/2023]
Abstract
Embryogenesis necessitates harmonious coordination between embryonic and extraembryonic tissues. Although stem cells of both embryonic and extraembryonic origins have been generated, they are grown in different culture conditions. In this study, utilizing a unified culture condition that activates the FGF, TGF-β, and WNT pathways, we have successfully derived embryonic stem cells (FTW-ESCs), extraembryonic endoderm stem cells (FTW-XENs), and trophoblast stem cells (FTW-TSCs) from the three foundational tissues of mouse and cynomolgus monkey (Macaca fascicularis) blastocysts. This approach facilitates the co-culture of embryonic and extraembryonic stem cells, revealing a growth inhibition effect exerted by extraembryonic endoderm cells on pluripotent cells, partially through extracellular matrix signaling. Additionally, our cross-species analysis identified both shared and unique transcription factors and pathways regulating FTW-XENs. The embryonic and extraembryonic stem cell co-culture strategy offers promising avenues for developing more faithful embryo models and devising more developmentally pertinent differentiation protocols.
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Affiliation(s)
- Yulei Wei
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
| | - E Zhang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Leqian Yu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Baiquan Ci
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Masahiro Sakurai
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Lei Guo
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Xin Zhang
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Sirui Lin
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Shino Takii
- Department of Advanced Bioscience, Graduate School of Agriculture, Kindai University, Nakamachi, Nara 631-8505, Japan
| | - Lizhong Liu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jian Liu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Daniel A Schmitz
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Ting Su
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Junmei Zhang
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China; State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiaoyan Shen
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China
| | - Yi Ding
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Linfeng Zhan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | | | - Canbin Zheng
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Lin Xu
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Daiji Okamura
- Department of Advanced Bioscience, Graduate School of Agriculture, Kindai University, Nakamachi, Nara 631-8505, Japan
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
| | - Jun Wu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
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Tan T, Mouradov D, Lee M, Gard G, Hirokawa Y, Li S, Lin C, Li F, Luo H, Wu K, Palmieri M, Leong E, Clarke J, Sakthianandeswaren A, Brasier H, Tie J, Tebbutt NC, Jalali A, Wong R, Burgess AW, Gibbs P, Sieber OM. Unified framework for patient-derived, tumor-organoid-based predictive testing of standard-of-care therapies in metastatic colorectal cancer. Cell Rep Med 2023; 4:101335. [PMID: 38118423 PMCID: PMC10783557 DOI: 10.1016/j.xcrm.2023.101335] [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: 05/17/2023] [Revised: 09/11/2023] [Accepted: 11/18/2023] [Indexed: 12/22/2023]
Abstract
Predictive drug testing of patient-derived tumor organoids (PDTOs) holds promise for personalizing treatment of metastatic colorectal cancer (mCRC), but prospective data are limited to chemotherapy regimens with conflicting results. We describe a unified framework for PDTO-based predictive testing across standard-of-care chemotherapy and biologic and targeted therapy options. In an Australian community cohort, PDTO predictions based on treatment-naive patients (n = 56) and response rates from first-line mCRC clinical trials achieve 83% accuracy for forecasting responses in patients receiving palliative treatments (18 patients, 29 treatments). Similar assay accuracy is achieved in a prospective study of third-line or later mCRC treatment, AGITG FORECAST-1 (n = 30 patients). "Resistant" predictions are associated with inferior progression-free survival; misclassification rates are similar by regimen. Liver metastases are the optimal site for sampling, with testing achievable within 7 weeks for 68.8% cases. Our findings indicate that PDTO drug panel testing can provide predictive information for multifarious standard-of-care therapies for mCRC.
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Affiliation(s)
- Tao Tan
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Dmitri Mouradov
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Margaret Lee
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia; Department of Medical Oncology, Eastern Health, Box Hill, VIC 3128, Australia; Eastern Health Clinical School, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Box Hill, VIC 3128, Australia
| | - Grace Gard
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia
| | - Yumiko Hirokawa
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Shan Li
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Cong Lin
- HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, BGI Research, Hangzhou 310000, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China
| | - Fuqiang Li
- HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, BGI Research, Hangzhou 310000, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China
| | - Huijuan Luo
- HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, BGI Research, Hangzhou 310000, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China
| | - Kui Wu
- HIM-BGI Omics Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, BGI Research, Hangzhou 310000, China; Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI Research, Shenzhen 518083, China
| | - Michelle Palmieri
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Evelyn Leong
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Jordan Clarke
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Anuratha Sakthianandeswaren
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Helen Brasier
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia
| | - Jeanne Tie
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia
| | - Niall C Tebbutt
- Department of Medical Oncology, Olivia Newton-John Cancer Wellness & Research Centre, Austin Health, Heidelberg, VIC 3084, Australia
| | - Azim Jalali
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia; Department of Cancer Services, Latrobe Regional Hospital, Traralogon, VIC 3844, Australia; Department of Medical Oncology, The Northern Hospital, Epping, VIC 3076, Australia
| | - Rachel Wong
- Department of Medical Oncology, Eastern Health, Box Hill, VIC 3128, Australia; Eastern Health Clinical School, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Box Hill, VIC 3128, Australia
| | - Antony W Burgess
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Surgery, The University of Melbourne, Parkville, VIC 3050, Australia
| | - Peter Gibbs
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Medical Oncology, Western Health, Footscray, VIC 3011, Australia
| | - Oliver M Sieber
- Personalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC 3052, Australia; Department of Medical Biology, The University of Melbourne, Parkville, VIC 3052, Australia; Department of Surgery, The University of Melbourne, Parkville, VIC 3050, Australia; Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.
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Wang J, Li Y, Chen B, Cheng D, Liao F, Tan T, Xu Q, Liu Z, Huang Y, Zhu C, Cao W, Yao L, Wu Z, Wu L, Zhang C, Xiao B, Xu M, Liu J, Li S, Yu H. A real-time deep learning-based system for colorectal polyp size estimation by white-light endoscopy: development and multicenter prospective validation. Endoscopy 2023. [PMID: 37827513 DOI: 10.1055/a-2189-7036] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
BACKGROUND The choice of polypectomy device and surveillance intervals for colorectal polyps are primarily decided by polyp size. We developed a deep learning-based system (ENDOANGEL-CPS) to estimate colorectal polyp size in real time. METHODS ENDOANGEL-CPS calculates polyp size by estimating the distance from the endoscope lens to the polyp using the parameters of the lens. The depth estimator network was developed on 7297 images from five virtually produced colon videos and tested on 730 images from seven virtual colon videos. The performance of the system was first evaluated in nine videos of a simulated colon with polyps attached, then tested in 157 real-world prospective videos from three hospitals, with the outcomes compared with that of nine endoscopists over 69 videos. Inappropriate surveillance recommendations caused by incorrect estimation of polyp size were also analyzed. RESULTS The relative error of depth estimation was 11.3% (SD 6.0%) in successive virtual colon images. The concordance correlation coefficients (CCCs) between system estimation and ground truth were 0.89 and 0.93 in images of a simulated colon and multicenter videos of 157 polyps. The mean CCC of ENDOANGEL-CPS surpassed all endoscopists (0.89 vs. 0.41 [SD 0.29]; P<0.001). The relative accuracy of ENDOANGEL-CPS was significantly higher than that of endoscopists (89.9% vs. 54.7%; P<0.001). Regarding inappropriate surveillance recommendations, the system's error rate is also lower than that of endoscopists (1.5% vs. 16.6%; P<0.001). CONCLUSIONS ENDOANGEL-CPS could potentially improve the accuracy of colorectal polyp size measurements and size-based surveillance intervals.
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Affiliation(s)
- Jing Wang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ying Li
- Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China
| | - Boru Chen
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Du Cheng
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Fei Liao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Tao Tan
- Department of Endoscopy, Third People's Hospital of Hubei Province, Wuhan, China
| | - Qinghong Xu
- Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China
| | - Zhifeng Liu
- Department of Endoscopy, Third People's Hospital of Hubei Province, Wuhan, China
| | - Yuan Huang
- Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China
| | - Ci Zhu
- Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China
| | - Wenbing Cao
- Department of Endoscopy, Eighth Hospital of Wuhan, Wuhan, China
| | - Liwen Yao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhifeng Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lianlian Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chenxia Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Bing Xiao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ming Xu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jun Liu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shuyu Li
- Department of Endoscopy, Third People's Hospital of Hubei Province, Wuhan, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Digestive System, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial Intelligence Endoscopy Interventional Treatment of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China
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23
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Li Y, Liu J, Zhang Y, Mao M, Wang H, Ma Y, Chen Z, Zhang Y, Liao C, Chang X, Gao Q, Guo J, Ye Y, Ai F, Liu X, Zhao X, Tian W, Yang H, Ji W, Tan T, Zhu L. A comprehensive evaluation of spontaneous pelvic organ prolapse in rhesus macaques as an ideal model for the study of human pelvic organ prolapse. Sci Bull (Beijing) 2023; 68:2434-2447. [PMID: 37714805 DOI: 10.1016/j.scib.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/02/2023] [Accepted: 09/01/2023] [Indexed: 09/17/2023]
Abstract
Pelvic organ prolapse (POP) seriously affects a woman's quality of life, and the treatment complications are severe. Although new surgical treatments are being developed, the host tissue responses and safety need to be evaluated in preclinical trials. However, there is a lack of suitable animal models, as most quadrupeds exhibit different structural and pathological changes. In this study, 72 elderly rhesus macaques (Macaca mulatta) were physically examined, and the incidence of spontaneous POP was similar to that in humans. The vaginal wall from five control monkeys and four monkeys with POP were selected for further analysis. Verhoeff-van Gieson staining showed that elastin content decreased significantly in monkeys with POP compared with control samples. Immunohistological staining revealed that the smooth muscle bundles in monkey POP appeared disorganized, and the number of large muscle bundles decreased significantly. The collagen I/III ratio in monkey POP also significantly decreased, as revealed by Sirius Red staining. These histological and biochemical changes in monkeys with POP were similar to those in humans with POP. Moreover, we generated a single-cell transcriptomic atlas of the prolapsed monkey vagina. Cross-species analysis between humans and monkeys revealed a comparable cellular composition. Notably, a differential gene expression analysis determined that dysregulation of the extracellular matrix and an immune disorder were the conserved molecular mechanisms. The interplay between fibroblasts and macrophages contributed to human and monkey POP. Overall, this study represents a comprehensive evaluation of spontaneous POP in rhesus macaques and demonstrates that monkeys are a suitable animal model for POP research.
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Affiliation(s)
- Yaqian Li
- Medical Science Research Center, the State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Jian Liu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Ye Zhang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Meng Mao
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Hong Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Yidi Ma
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; Department of Obstetrics and Gynecology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China
| | - Zhigang Chen
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Youyue Zhang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Chengmin Liao
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Xiaoqing Chang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Qianqian Gao
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jianbin Guo
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Yang Ye
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Fangfang Ai
- Department of Obstetrics and Gynecology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xudong Liu
- Medical Science Research Center, the State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China
| | - Xiaoyue Zhao
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Weijie Tian
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China; Department of Gynecology, Guizhou Provincial People's Hospital, Medical College of Guizhou University, Guiyang 550002, China
| | - Hua Yang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.
| | - Lan Zhu
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, the State Key Laboratory for Complex, Severe, and Rare Diseases, the State Key Laboratory of Common Mechanism Research for Major Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
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Wang J, Tan T, Pang R, Li D, Li C, Zhang S, Jiang L, Zhang H. A novel broadband Ba 3Ca 4(BO 3) 3(SiO 4)Cl:Mn 4+ near-infrared phosphor with a special pseudo-octahedral Mn 4+ coordination structure. Dalton Trans 2023; 52:15078-15090. [PMID: 37812416 DOI: 10.1039/d3dt02602g] [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: 10/10/2023]
Abstract
A pseudo-octahedral coordination structure of Mn4+ has been innovatively designed, which has realized the maximum red shift and the widest full width at half-maximum (FWHM) of Mn4+ emission so far, not only extending the emission wavelength of Mn4+ to the near-infrared (NIR) region, but also effectively broadening its bandwidth. In the Ba3Ca4(BO3)3(SiO4)Cl:Mn4+ (BCBSC:Mn4+) phosphor, the [Mn/Ca1O9] polyhedron contains one [Mn/Ca1O6] octahedron, which constitutes the pseudo-octahedral coordination structure of Mn4+. The BCBSC:Mn4+ phosphor can be excited at 362 nm and 470 nm and exhibits a broadband NIR emission centered at ∼756 nm with a super-wide range from 650 nm to 1100 nm. The FWHM can reach ∼90 nm. In addition, the internal quantum efficiency (IQE) of the BCBSC:0.01Mn4+ phosphor is 69.7%. The unique luminescence characteristics of BCBSC:Mn4+ phosphors are explored using experimental data and first principles calculation. The significant redshift, the abnormal broadband emission, and the high luminous efficiency are closely related to the special highly distorted [Mn/Ca1O6] pseudo-octahedral coordination environment. The results contribute to comprehending the mechanism of the broadband NIR emission of Mn4+ activated phosphors and broaden the research ideas of developing high-performance Mn4+ doped phosphors for NIR phosphor-converted light-emission diode applications.
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Affiliation(s)
- Jiutian Wang
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Tao Tan
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Ran Pang
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Da Li
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Chengyu Li
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Su Zhang
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Lihong Jiang
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Hongjie Zhang
- State key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
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Zheng D, Wang R, Duan Y, Pang PCI, Tan T. Focus-RCNet: a lightweight recyclable waste classification algorithm based on focus and knowledge distillation. Vis Comput Ind Biomed Art 2023; 6:19. [PMID: 37819427 PMCID: PMC10567611 DOI: 10.1186/s42492-023-00146-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023] Open
Abstract
Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of domestic waste generated has increased dramatically, and there is an urgent need for further treatment. The rapid development of artificial intelligence has provided an effective solution for automated waste classification. However, the high computational power and complexity of algorithms make convolutional neural networks unsuitable for real-time embedded applications. In this paper, we propose a lightweight network architecture called Focus-RCNet, designed with reference to the sandglass structure of MobileNetV2, which uses deeply separable convolution to extract features from images. The Focus module is introduced to the field of recyclable waste image classification to reduce the dimensionality of features while retaining relevant information. To make the model focus more on waste image features while keeping the number of parameters small, we introduce the SimAM attention mechanism. In addition, knowledge distillation was used to further compress the number of parameters in the model. By training and testing on the TrashNet dataset, the Focus-RCNet model not only achieved an accuracy of 92[Formula: see text] but also showed high deployment mobility.
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Affiliation(s)
- Dashun Zheng
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, China
| | - Rongsheng Wang
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, China
| | - Yaofei Duan
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, China
| | - Patrick Cheong-Iao Pang
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, China.
| | - Tao Tan
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, 999078, China
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26
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Yao H, Sun N, Shao H, Wang T, Tan T. Ex utero embryogenesis of non-human primate embryos and beyond. Curr Opin Genet Dev 2023; 82:102093. [PMID: 37573834 DOI: 10.1016/j.gde.2023.102093] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/19/2023] [Accepted: 07/14/2023] [Indexed: 08/15/2023]
Abstract
Understanding cellular and molecular processes underlying the human early post-implantation development represents one of the most fundamental questions in development and stem cell biology. As embryos implant into the uterus a week after fertilization, human development beyond the blastocyst stage is extremely difficult to study due to the inaccessibility of embryos and ethical concerns. The advents in the human embryo in vitro culture system provide an easily accessible, tractable, and perturbable platform to dissect key developmental events of human early embryonic development. However, these studies stopped around gastrulation to technical and ethical limitations, and our understanding of human gastrulation and early organogenesis remains poor. As closely related species to humans, non-human primates (NHPs) are suitable surrogate species to interrogate mechanisms underpinning human embryonic development. Here, we review the most recent advances in embryo in vitro culture systems of NHP and discuss their potential optimization strategies and applications.
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Affiliation(s)
- Hui Yao
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Nianqin Sun
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Honglian Shao
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Tianxiang Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
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27
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Yu L, Logsdon D, Pinzon-Arteaga CA, Duan J, Ezashi T, Wei Y, Ribeiro Orsi AE, Oura S, Liu L, Wang L, Liu K, Ding X, Zhan L, Zhang J, Nahar A, Stobbe C, Katz-Jaffe M, Schoolcraft WB, Tan T, Hon GC, Yuan Y, Wu J. Large-scale production of human blastoids amenable to modeling blastocyst development and maternal-fetal cross talk. Cell Stem Cell 2023; 30:1246-1261.e9. [PMID: 37683605 DOI: 10.1016/j.stem.2023.08.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 03/07/2023] [Accepted: 08/03/2023] [Indexed: 09/10/2023]
Abstract
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. One limitation of our first protocol for human blastoid generation was relatively low efficiency. We now report an optimized protocol for the efficient generation of large quantities of high-fidelity human blastoids from naive pluripotent stem cells. This enabled proteomics analysis that identified phosphosite-specific signatures potentially involved in the derivation and/or maintenance of the signaling states in human blastoids. Additionally, we uncovered endometrial stromal effects in promoting trophoblast cell survival, proliferation, and syncytialization during co-culture with blastoids and blastocysts. Side-by-side single-cell RNA sequencing revealed similarities and differences in transcriptome profiles between pre-implantation blastoids and blastocysts, as well as post-implantation cultures, and uncovered a population resembling early migratory trophoblasts during co-culture with endometrial stromal cells. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, and tractable model for human blastocysts.
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Affiliation(s)
- Leqian Yu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Deirdre Logsdon
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA
| | - Carlos A Pinzon-Arteaga
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jialei Duan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Toshihiko Ezashi
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA
| | - Yulei Wei
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China, Agricultural University, Beijing, 100193, China
| | - Ana Elisa Ribeiro Orsi
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo 05508-090, São Paulo, Brazil
| | - Seiya Oura
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Lizhong Liu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Lei Wang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Kun Liu
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA; Paul M. Rady Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
| | - Xiaoyun Ding
- Paul M. Rady Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
| | - Linfeng Zhan
- State Key Laboratory of Primate Biomedical Research Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, Yunnan, China; Yunan Key Laboratory of Primate Biomedical Research, Kunming 650500, Yunnan, China
| | - Junfei Zhang
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China, Agricultural University, Beijing, 100193, China
| | - Asrafun Nahar
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA
| | - Caitlen Stobbe
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA
| | - Mandy Katz-Jaffe
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA
| | | | - Tao Tan
- State Key Laboratory of Primate Biomedical Research Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, Yunnan, China; Yunan Key Laboratory of Primate Biomedical Research, Kunming 650500, Yunnan, China
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Ye Yuan
- Colorado Center for Reproductive Medicine, Lone Tree, CO 80124, USA.
| | - Jun Wu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
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28
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Chen Y, Wang T, Tang H, Zhao L, Zhang X, Tan T, Gao Q, Du M, Tong T. CoTrFuse: a novel framework by fusing CNN and transformer for medical image segmentation. Phys Med Biol 2023; 68:175027. [PMID: 37605997 DOI: 10.1088/1361-6560/acede8] [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: 06/03/2023] [Accepted: 08/07/2023] [Indexed: 08/23/2023]
Abstract
Medical image segmentation is a crucial and intricate process in medical image processing and analysis. With the advancements in artificial intelligence, deep learning techniques have been widely used in recent years for medical image segmentation. One such technique is the U-Net framework based on the U-shaped convolutional neural networks (CNN) and its variants. However, these methods have limitations in simultaneously capturing both the global and the remote semantic information due to the restricted receptive domain caused by the convolution operation's intrinsic features. Transformers are attention-based models with excellent global modeling capabilities, but their ability to acquire local information is limited. To address this, we propose a network that combines the strengths of both CNN and Transformer, called CoTrFuse. The proposed CoTrFuse network uses EfficientNet and Swin Transformer as dual encoders. The Swin Transformer and CNN Fusion module are combined to fuse the features of both branches before the skip connection structure. We evaluated the proposed network on two datasets: the ISIC-2017 challenge dataset and the COVID-QU-Ex dataset. Our experimental results demonstrate that the proposed CoTrFuse outperforms several state-of-the-art segmentation methods, indicating its superiority in medical image segmentation. The codes are available athttps://github.com/BinYCn/CoTrFuse.
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Affiliation(s)
- Yuanbin Chen
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Tao Wang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Hui Tang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Longxuan Zhao
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Xinlin Zhang
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Tao Tan
- Faculty of Applied Science, Macao Polytechnic University, Macao 999078, People's Republic of China
| | - Qinquan Gao
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Min Du
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
| | - Tong Tong
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, People's Republic of China
- Fujian Key Lab of Medical Instrumentation & Pharmaceutical Technology, Fuzhou University, Fuzhou 350116, People's Republic of China
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Wang X, Mei D, Gou L, Zhao S, Gao C, Guo J, Luo S, Guo B, Yang Z, Wang Q, Tan T, Zhang Y. Functional Evaluation of a Novel GRIN2B Missense Variant Associated with Epilepsy and Intellectual Disability. Neuroscience 2023; 526:107-120. [PMID: 37385334 DOI: 10.1016/j.neuroscience.2023.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 06/17/2023] [Accepted: 06/21/2023] [Indexed: 07/01/2023]
Abstract
Epilepsy, a neurological condition, is widely prevalent among individuals with intellectual disability (ID). It is well established that N-methyl-D-aspartate (NMDA) receptors play an important role in both epilepsy and ID. Autosomal dominant mutations in the GRIN2B gene, which encodes the GluN2B subunit of the NMDA receptor, have been reported to be associated with epilepsy and ID. However, the underlying mechanism of this association is not well-understood. In this study, we identified a novel GRIN2B mutation (c.3272A > C, p.K1091T) in a patient with epilepsy and ID. The proband was a one year and ten months old girl. GRIN2B variant was inherited from her mother. We further investigated the functional consequences of this mutation. Our findings revealed that the p.K1091T mutation created a Casein kinase 2 phosphorylation site. Using recombinant NMDA receptors containing the GluN2B-K1091T along with GluN1 in HEK 293T cells, we observed significant defects in its interactions with postsynaptic density 95. It is accompanied by reduced delivery of the receptors to the cell membrane and a decrease in glutamate affinity. Moreover, primary neurons expressing GluN2B-K1091T also exhibited impaired surface expression of NMDA receptors, a reduction in dendritic spine number and excitatory synaptic transmission. In summary, our study reports a novel GRIN2B mutation and provides functional characteristics of this mutation in vitro, thereby contributing to the understanding of GRIN2B variants in epilepsy and ID.
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Affiliation(s)
- Xiaona Wang
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Provincial Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Engineering Research Center of Childhood Neurodevelopment, Zhengzhou 450018, Henan, China.
| | - Daoqi Mei
- Department of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou 450018, Henan, China
| | - Lingshan Gou
- Center for Genetic Medicine, Xuzhou Maternity and Child Health Care Hospital Affiliated to Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
| | - Shuai Zhao
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Provincial Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Engineering Research Center of Childhood Neurodevelopment, Zhengzhou 450018, Henan, China
| | - Chao Gao
- Department of Rehabilitation, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou 450018, Henan, China
| | - Jisheng Guo
- School of Basic Medical Sciences, Yantai Campus of Binzhou Medical University, Yantai 264003, Shandong, China
| | - Shuying Luo
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Provincial Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Engineering Research Center of Childhood Neurodevelopment, Zhengzhou 450018, Henan, China
| | - Bin Guo
- School of Traditional Chinese Medicine, Ningxia Medical University, Ningxia 750004, China
| | - Zhigang Yang
- Department of Neurology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Zhengzhou 450018, Henan, China
| | - Qi Wang
- Department of Histology and Embryology, School of Basic Medicine, Guizhou Medical University, Guiyang 550025, Guizhou, China.
| | - Tao Tan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.
| | - Yaodong Zhang
- Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital, Zhengzhou Children's Hospital, Henan Provincial Key Laboratory of Children's Genetics and Metabolic Diseases, Henan Engineering Research Center of Childhood Neurodevelopment, Zhengzhou 450018, Henan, China.
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Zhang T, Tan T, Wang X, Gao Y, Han L, Balkenende L, D'Angelo A, Bao L, Horlings HM, Teuwen J, Beets-Tan RGH, Mann RM. RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease. Cell Rep Med 2023; 4:101131. [PMID: 37490915 PMCID: PMC10439251 DOI: 10.1016/j.xcrm.2023.101131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/26/2023] [Accepted: 06/30/2023] [Indexed: 07/27/2023]
Abstract
Digital health data used in diagnostics, patient care, and oncology research continue to accumulate exponentially. Most medical information, and particularly radiology results, are stored in free-text format, and the potential of these data remains untapped. In this study, a radiological repomics-driven model incorporating medical token cognition (RadioLOGIC) is proposed to extract repomics (report omics) features from unstructured electronic health records and to assess human health and predict pathological outcome via transfer learning. The average accuracy and F1-weighted score for the extraction of repomics features using RadioLOGIC are 0.934 and 0.934, respectively, and 0.906 and 0.903 for the prediction of breast imaging-reporting and data system scores. The areas under the receiver operating characteristic curve for the prediction of pathological outcome without and with transfer learning are 0.912 and 0.945, respectively. RadioLOGIC outperforms cohort models in the capability to extract features and also reveals promise for checking clinical diagnoses directly from electronic health records.
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Affiliation(s)
- Tianyu Zhang
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; GROW School for Oncology and Development Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Tao Tan
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands; Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China.
| | - Xin Wang
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; GROW School for Oncology and Development Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Yuan Gao
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; GROW School for Oncology and Development Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Luyi Han
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Luuk Balkenende
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Anna D'Angelo
- Dipartimento di diagnostica per immagini, Radioterapia, Oncologia ed ematologia, Fondazione Universitaria A. Gemelli, IRCCS Roma, Roma, Italy
| | - Lingyun Bao
- Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hugo M Horlings
- Division of Pathology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Jonas Teuwen
- Department of Radiation Oncology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; GROW School for Oncology and Development Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, the Netherlands
| | - Ritse M Mann
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX Amsterdam, the Netherlands; Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
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Feng S, Shang J, Tan T, Wen Q, Meng Q. Nondestructive quality assessment and maturity classification of loquats based on hyperspectral imaging. Sci Rep 2023; 13:13189. [PMID: 37580378 PMCID: PMC10425455 DOI: 10.1038/s41598-023-40553-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 08/12/2023] [Indexed: 08/16/2023] Open
Abstract
The traditional method for assessing the quality and maturity of loquats has disadvantages such as destructive sampling and being time-consuming. In this study, hyperspectral imaging technology was used to nondestructively predict and visualise the colour, firmness, and soluble solids content (SSC) of loquats and discriminate maturity. On comparison of the performance of different feature variables selection methods and the calibration models, the results indicated that the multiple linear regression (MLR) models combined with the competitive adaptive reweighting algorithm (CARS) yielded the best prediction performance for loquat quality. Particularly, CARS-MLR models with optimal prediction performance were obtained for the colour (R2P = 0.96, RMSEP = 0.45, RPD = 5.38), firmness (R2P = 0.87, RMSEP = 0.23, RPD = 2.81), and SSC (R2P = 0.84, RMSEP = 0.51, RPD = 2.54). Subsequently, distribution maps of the colour, firmness, and SSC of loquats were obtained based on the optimal CARS-MLR models combined with pseudo-colour technology. Finally, on comparison of different classification models for loquat maturity, the partial least square discrimination analysis model demonstrated the best performance, with classification accuracies of 98.19% and 97.99% for calibration and prediction sets, respectively. This study demonstrated that the hyperspectral imaging technique is promising for loquat quality assessment and maturity classification.
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Affiliation(s)
- Shunan Feng
- Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China
| | - Jing Shang
- Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China.
- Research Center of Nondestructive Testing for Agricultural Products of Guizhou Province, Guiyang, 550005, China.
| | - Tao Tan
- Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China
| | - Qingchun Wen
- Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China
| | - Qinglong Meng
- Food and Pharmaceutical Engineering Institute, Guiyang University, Guiyang, 550005, China
- Research Center of Nondestructive Testing for Agricultural Products of Guizhou Province, Guiyang, 550005, China
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Lin P, Yang J, Wu S, Ye T, Zhuang W, Wang W, Tan T. Current trends of high-risk gene Cul3 in neurodevelopmental disorders. Front Psychiatry 2023; 14:1215110. [PMID: 37575562 PMCID: PMC10416632 DOI: 10.3389/fpsyt.2023.1215110] [Citation(s) in RCA: 1] [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] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023] Open
Abstract
Cul3 encodes Cullin-3, a core component of the ubiquitin E3 ligase that is involved in protein ubiquitination. Recent studies have identified Cul3 as a high-confidence risk gene in neurodevelopmental disorders (NDDs), especially autism spectrum disorder (ASD). Different strategies have been used to generate animal models with Cul3 deficiency in the central nervous system, including whole-brain knockout (KO), cell-type specific conditional KO (cKO), and brain region-specific knockdown. In this review, we revisited the basic properties of CUL3 and its function under physiological and pathological conditions. Recent clinical studies including case reports and large cohort sequencing studies related to CUl3 in NDDs have been summarized. Moreover, we characterized the behavioral, electrophysiological, and molecular changes in newly developed Cul3 deficiency models. This would guide further studies related to Cul3 in CNS and provide potential therapeutic targets for Cul3-deficiency-induced NDDs, including ASD.
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Affiliation(s)
- Ping Lin
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Jie Yang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Shumin Wu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tong Ye
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Wenting Zhuang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Wei Wang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Tao Tan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, Zhejiang, China
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Hu J, Feng Y, Zhong H, Liu W, Tian X, Wang Y, Tan T, Hu Z, Liu Y. Impact of climate change on the geographical distribution and niche dynamics of Gastrodia elata. PeerJ 2023; 11:e15741. [PMID: 37520262 PMCID: PMC10373646 DOI: 10.7717/peerj.15741] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 06/20/2023] [Indexed: 08/01/2023] Open
Abstract
Background Gastrodia elata is widely used in China as a valuable herbal medicine. Owing to its high medicinal and nutrient value, wild resources of G. elata have been overexploited and its native areas have been severely damaged. Understanding the impacts of climate change on the distribution of this endangered species is important for the conservation and sustainable use of G. elata. Methods We used the optimized maximum entropy model to simulate the potential distribution of G. elata under contemporary and future time periods (1970-2000, 2050s, 2070s, and 2090s) and different climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Under these conditions, we investigated the key environmental factors influencing the distribution of G. elata as well as the spatial and temporal characteristics of its niche dynamics. Results With high Maxent model accuracy (AUCmean = 0.947 ± 0.012, and the Kappa value is 0.817), our analysis revealed that annual precipitation, altitude, and mean temperature of driest quarter are the most important environmental factors influencing the distribution of G. elata. Under current bioclimatic conditions, the potentially suitable area for G. elata in China is 71.98 × 104 km2, while the highly suitable region for G. elata growth is 7.28 × 104 km2. Our models for three future periods under four climate change scenarios indicate that G. elata can maintain stable distributions in southern Shaanxi, southwestern Hubei, and around the Sichuan basin, as these areas are highly suitable for its growth. However, the center of the highly suitable areas of G. elata shift depending on different climatic scenarios. The values of niche overlap for G. elata show a decreasing trend over the forecasted periods, of which the niche overlap under the SSP3-7.0 scenario shows the greatest decrease. Discussions Under the condition of global climate change in the future, our study provides basic reference data for the conservation and sustainable utilization of the valuable and endangered medicinal plant G. elata. It is important to carefully choose the protection area of G. elata wild resources according the suitable area conditions modeled. Moreover, these findings will be valuable for providing insights into the breeding and artificial cultivation of this plant, including the selection of suitable areas for planting.
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Affiliation(s)
- Juan Hu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Ying Feng
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Haotian Zhong
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Wei Liu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Xufang Tian
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Yehong Wang
- Wufeng Tujia Autonomous County Agricultural Science and Technology Demonstration Center, Yichang, China
| | - Tao Tan
- Wufeng Tujia Autonomous County Herbal Medicine Development Center, Yichang, China
| | - Zhigang Hu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Yifei Liu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
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Li H, Li Z, Li X, Cai C, Zhao SL, Merritt RE, Zhou X, Tan T, Bergdall V, Ma J. MG53 Mitigates Nitrogen Mustard-Induced Skin Injury. Cells 2023; 12:1915. [PMID: 37508578 PMCID: PMC10378386 DOI: 10.3390/cells12141915] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/07/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Sulfur mustard (SM) and nitrogen mustard (NM) are vesicant agents that cause skin injury and blistering through complicated cellular events, involving DNA damage, free radical formation, and lipid peroxidation. The development of therapeutic approaches targeting the multi-cellular process of tissue injury repair can potentially provide effective countermeasures to combat vesicant-induced dermal lesions. MG53 is a vital component of cell membrane repair. Previous studies have demonstrated that topical application of recombinant human MG53 (rhMG53) protein has the potential to promote wound healing. In this study, we further investigate the role of MG53 in NM-induced skin injury. Compared with wild-type mice, mg53-/- mice are more susceptible to NM-induced dermal injuries, whereas mice with sustained elevation of MG53 in circulation are resistant to dermal exposure of NM. Exposure of keratinocytes and human follicle stem cells to NM causes elevation of oxidative stress and intracellular aggregation of MG53, thus compromising MG53's intrinsic cell membrane repair function. Topical rhMG53 application mitigates NM-induced dermal injury in mice. Histologic examination reveals the therapeutic benefits of rhMG53 are associated with the preservation of epidermal integrity and hair follicle structure in mice with dermal NM exposure. Overall, these findings identify MG53 as a potential therapeutic agent to mitigate vesicant-induced skin injuries.
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Affiliation(s)
- Haichang Li
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH 43210, USA
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Zhongguang Li
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Xiuchun Li
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Chuanxi Cai
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Serena Li Zhao
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Robert E Merritt
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Xinyu Zhou
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
| | - Tao Tan
- TRIM-Edicine, Inc., 1275 Kinnear Road, Columbus, OH 43212, USA
| | - Valerie Bergdall
- Department of Veterinary Preventive Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Jianjie Ma
- Department of Surgery, The Ohio State University, Columbus, OH 43210, USA
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Zou Q, Su C, Du W, Ouyang Y, Wang H, Zhang B, Luo S, Tan T, Chen Y, Zhong X, Zhang H. The Mediation and Moderation Effect Association among Physical Activity, Body-Fat Percentage, Blood Pressure, and Serum Lipids among Chinese Adults: Findings from the China Health and Nutrition Surveys in 2015. Nutrients 2023; 15:3113. [PMID: 37513531 PMCID: PMC10383535 DOI: 10.3390/nu15143113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Physical activity (PA) is of benefit and particularly important for cardiovascular disease risk factors as being sedentary becomes a lifestyle habit. Research into Chinese complex association among physical activity, body-fat percentage (BF%), blood pressure, and serum lipids is limited. The present study is based on an observational study among adults (>18 years old) residing in fifteen provinces in China. Data of 10,148 adult participants in the 2015 China Health and Nutrition Survey (CHNS) were analyzed. The simple mediation effect models with covariates were utilized to assess the association among PA and blood pressure or serum lipids, and BF% was played as a mediator. The serial multiple-mediator models with covariates were constructed to the further analysis of the relationship between PA and blood pressure, and BF% was the mediator 1 and blood lipids were the mediator 2. Based on the above hypothesis, the moderated mediation models with covariates were used to analyze the association among PA, BF%, and blood pressure; in addition, BF% was used as the mediator and blood lipids played as the moderator. In the simple mediation models, the model with a dependent variable was high-density lipoprotein cholesterol (HDL-C) or low-density lipoprotein cholesterol (LDL-C); BF% was played as the partly mediation effect and the proportion of contribution was 0.23 and 0.25, respectively. In the serial multiple-mediator models, blood lipids, as the second mediator, played the mediation effect; however, the effect was smaller than the BF%. In the moderated mediation model, blood lipids had the moderation effect as the moderator variable. HDL-C played a moderating role in the latter pathway of the "PA→BF%→SBP/DBP" mediation model, and LDL-C/TC played a moderating role in the direct effect of the "PA→BF%→DBP". In conclusion, BF% played a mediating role in the relationship between PA and blood pressure. HDL-C, LDL-C, and TC were more likely to act as moderating variables in the mediation model "PA→BF%→SBP/DBP". PA could directly and indirectly benefit to control the CVD risk factors simultaneously.
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Affiliation(s)
- Qinpei Zou
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
- School of Public Health, Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China
- Department of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China
| | - Chang Su
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Wenwen Du
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Yifei Ouyang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Huijun Wang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Bing Zhang
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Shuquan Luo
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Tao Tan
- Chongqing Health Statistics Information Center, Chongqing 401120, China
| | - Yaokai Chen
- Department of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China
| | - Xiaoni Zhong
- School of Public Health, Research Center for Medicine and Social Development, Chongqing Medical University, Chongqing 400016, China
| | - Huadong Zhang
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
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Wang R, Duan Y, Hu M, Liu X, Li Y, Gao Q, Tong T, Tan T. LightR-YOLOv5: A compact rotating detector for SARS-CoV-2 antigen-detection rapid diagnostic test results. Displays 2023; 78:102403. [PMID: 36937555 PMCID: PMC10011043 DOI: 10.1016/j.displa.2023.102403] [Citation(s) in RCA: 1] [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] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/07/2023] [Accepted: 02/19/2023] [Indexed: 05/20/2023]
Abstract
Nucleic acid testing is currently the golden reference for coronaviruses (SARS-CoV-2) detection, while the SARS-CoV-2 antigen-detection rapid diagnostic tests (RDT) is an important adjunct. RDT can be widely used in the community or regional screening management as self-test tools and may need to be verified by healthcare authorities. However, manual verification of RDT results is a time-consuming task, and existing object detection algorithms usually suffer from high model complexity and computational effort, making them difficult to deploy. We propose LightR-YOLOv5, a compact rotating SARS-CoV-2 antigen-detection RDT results detector. Firstly, we employ an extremely light-weight L-ShuffleNetV2 network as a feature extraction network with a slight reduction in recognition accuracy. Secondly, we combine semantic and texture features in different layers by judiciously combining and employing GSConv, depth-wise convolution, and other modules, and further employ the NAM attention to locate the RDT result detection region. Furthermore, we propose a new data augmentation approach, Single-Copy-Paste, for increasing data samples for the specific task of RDT result detection while achieving a small improvement in model accuracy. Compared with some mainstream rotating object detection networks, the model size of our LightR-YOLOv5 is only 2.03MB, and it is 12.6%, 6.4%, and 7.3% higher in mAP@.5:.95 metrics compared to RetianNet, FCOS, and R3Det, respectively.
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Affiliation(s)
- Rongsheng Wang
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, 999078, Macao Special Administrative Region of China
| | - Yaofei Duan
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, 999078, Macao Special Administrative Region of China
| | - Menghan Hu
- Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200240, China
| | - Xiaohong Liu
- John Hopcroft Center, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yukun Li
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, 999078, Macao Special Administrative Region of China
| | - Qinquan Gao
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China
| | - Tong Tong
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China
| | - Tao Tan
- Faculty of Applied Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, 999078, Macao Special Administrative Region of China
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You Y, Fan H, Zhang S, Hu S, Tang J, Chen C, Wen W, Wang C, Cheng Y, Zhou M, Feng Z, Tan T, Qi G, Zhao W, Zhang X, Wang M, Dai L. Reduced plasma cholesterol in Plasmodium falciparum infection: A meta-analysis. J Infect 2023; 87:e19-e21. [PMID: 37172785 DOI: 10.1016/j.jinf.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 04/25/2023] [Accepted: 05/06/2023] [Indexed: 05/15/2023]
Affiliation(s)
- Yao You
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Hua Fan
- School of Clinical Medicine, The First Affiliated Hospital of Henan University of Science and Technology, Henan University of Science and Technology, Luoyang 471003, Henan, China
| | - Shenghui Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Siqi Hu
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Jiake Tang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Chen Chen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Wen Wen
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Chunyi Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Yongran Cheng
- School of Public Health, Hangzhou Medical College, Hangzhou 311300, China
| | - Mengyun Zhou
- Department of Molecular & Cellular Physiology, Shinshu University School of Medicine, 3900803, Japan
| | - Zhanhui Feng
- Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Tao Tan
- Faculty of Applied Science, Macao Polytechnic University, 999078, Macao Special Administrative Region of China
| | - Guanming Qi
- Division of Pulmonary, Critical Care and Sleep, Tufts Medical Center, Boston, MA 02111, USA
| | - Wenbin Zhao
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China
| | - Xingwei Zhang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China.
| | - Mingwei Wang
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China.
| | - Lili Dai
- Department of Cardiology, Affiliated Hospital of Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, China; Hangzhou Lin'an Fourth People's Hospital, Hangzhou 311321, China.
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Wang X, Su R, Xie W, Wang W, Xu Y, Mann R, Han J, Tan T. 2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small data. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104858] [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: 03/22/2023]
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Ding Y, Yao L, Tan T, Li Q, Shi H, Tian Y, Franssen AJPM, de Loos ER, Al Zaidi M, Cardillo G, Kidane B, Grapatsas K, Wu Q, Zhang C. Risk assessment for postoperative venous thromboembolism using the modified Caprini risk assessment model in lung cancer. J Thorac Dis 2023; 15:3386-3396. [PMID: 37426170 PMCID: PMC10323546 DOI: 10.21037/jtd-23-776] [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: 05/12/2023] [Accepted: 06/12/2023] [Indexed: 07/11/2023]
Abstract
Background Postoperative venous thromboembolism (VTE) is a well-documented cause of morbidity and mortality in lung cancer patients. However, risk identification remains limited. In this study, we sought to analyze the risk factors for VTE and verify the predictive value of the modified Caprini risk assessment model (RAM). Methods This prospective single-center study included patients with resectable lung cancer who underwent resection between October 2019 and March 2021. The incidence of VTE was estimated. Logistic regression was used to analyze the risk factors for VTE. Receiver operating characteristic (ROC) curve analysis was performed to test the ability of the modified Caprini RAM to predict VTE. Results The VTE incidence was 10.5%. Several variables, including age, D-dimer, hemoglobin (Hb), bleeding, and patient confinement to bed were significantly associated with VTE after surgery. The difference between the VTE and non-VTE groups in the high-risk levels was statistically significant (P<0.001), while the low and moderate risk levels showed no significant difference. The combined use of the modified Caprini score and the Hb and D-dimer levels showed an area under the curve (AUC) was 0.822 [95% confidence interval (CI): 0.760-0.855. P<0.001]. Conclusions The risk-stratification approach of the modified Caprini RAM is not particularly valid after lung resection in our population. The use of the modified Caprini RAM combined with Hb and D-dimer levels shows a good diagnostic performance for VTE prediction in patients with lung cancer undergoing resection.
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Affiliation(s)
- Yao Ding
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Thoracic Surgery, The People’s Hospital of Kaizhou District, Chongqing, China
| | - Lijun Yao
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tao Tan
- Chongqing Health Statistics Information Center, Chongqing, China
| | - Qiang Li
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Haoming Shi
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuan Tian
- Department of Medical Affairs, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Aimée J. P. M. Franssen
- Department of Surgery, Division of General Thoracic Surgery, Zuyderland Medical Center, Heerlen, The Netherlands
| | - Erik R. de Loos
- Department of Surgery, Division of General Thoracic Surgery, Zuyderland Medical Center, Heerlen, The Netherlands
| | - Muteb Al Zaidi
- Thoracic and Upper GI Surgeon, Thoracic Surgery Unit, King Abdullah Medical City, Makkah, Saudi Arabia
| | - Giuseppe Cardillo
- Unit of Thoracic Surgery, San Camillo Forlanini Hospital, Rome, Italy
- Unicamillus – Saint Camillus University of Health Sciences, Rome, Italy
| | - Biniam Kidane
- Section of Thoracic Surgery, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Konstantinos Grapatsas
- Department of Thoracic Surgery, Ruhrlandklinik, University of Duisburg-Essen, Essen, Germany
| | - Qingchen Wu
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Cheng Zhang
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Tan T, Zheng Y, Li Y, Zeng Y. [Pharmacogenetic testing improves treatment responses in patients with PLA2R-related membranous nephropathy]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:1047-1050. [PMID: 37439180 DOI: 10.12122/j.issn.1673-4254.2023.06.23] [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: 07/14/2023]
Abstract
OBJECTIVE To evaluate the value of pharmacogenetic testing for improving the efficacy and safety of treatment with cyclosporine, tacrolimus, and cyclophosphamide (CTX) for PLA2R-related membranous nephropathy and for determing individualized and precise treatment plans for the patients. METHODS A total of 63 patients with PLA2R-related membranous nephropathy hospitalized in the Department of Nephrology at our hospital from January, 2019 to October, 2021 were enrolled in this study. Thirty-three of the patients underwent pharmacogenetic testing before taking the immunosuppressive drugs selected based on the results of genetic screening for sensitive targets, and the other 30 patients were empirically given immunosuppressive drugs according to the guidelines (control group). The clinical efficacy and adverse effects of the immunosuppressive drugs were analyzed for all the patients. The two groups of patients were compared for demographic and biochemical parameters including 24-h urine protein, serum albumin, renal function, and serum anti-phospholipase A2 receptor antibody both before and at 3 months after the beginning of the treatment. RESULTS Among the 33 patients undergoing pharmacogenetic testing, 51.5% showed a GG genotype for cyclosporine, and 61.6% had an AG genotype for tacrolimus; for CTX, 51.5% of the patients showed a homozygous deletion and 63.6% had an AA genotype. After treatment for 3 months, serum anti-phospholipase A2 receptor antibody, 24-h urine protein, and serum albumin levels were significantly improved in pharmacogenetic testing group as compared with the control group (P < 0.05). CONCLUSION Individualized and precise administration of immunosuppressive drugs based on pharmacogenetic testing better controls proteinuria and serum antiphospholipase A2 receptor antibodies and increases serum albumin level in patients with PLA2R-related membranous nephropathy.
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Affiliation(s)
- T Tan
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518000, China
| | - Y Zheng
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518000, China
| | - Y Li
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518000, China
| | - Y Zeng
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen 518000, China
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Tan T, Pang R, Wang S, Wu H, Wang J, Zhang S, Li C, Zhang H. A broadband near-infrared Cr 3+-doped phosphor applied to near-infrared light-emitting diodes: enhanced luminescence and thermal stability by annealing. Dalton Trans 2023. [PMID: 37266926 DOI: 10.1039/d3dt01113e] [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: 06/03/2023]
Abstract
Cr3+-activated phosphors with high quantum efficiency show excellent promise in the field of near-infrared (NIR) phosphor converted light-emitting diodes (pc-LEDs). Here, we design an annealing program for Cr3+-doped phosphors containing variable valence elements that cannot be prepared in a reducing atmosphere to enhance their luminescence efficiency and thermal stability. A novel phosphor, Li2Mg3SnO6:Cr3+, developed by this annealing design, containing variable valence element Sn, exhibits higher quantum efficiency and better thermal stability than the one prepared by the conventional solid-state reaction. The Li2Mg3SnO6:0.03Cr3+ sample exhibits broadband NIR emission with a full width at half-maximum (FWHM) of 201 nm. After annealing, the internal quantum efficiency (IQE) and external quantum efficiency (EQE) of the Li2Mg3SnO6:0.03Cr3+ sample are enhanced from 48.5% to 84.7% and from 22.7% to 32.6%, respectively, and the thermal quenching temperature at which the luminescence intensity of the phosphor reduces to half of its initial value is promoted from ∼400 K to ∼425 K. The luminescence intensity of the optimized Li2Mg3SnO6:0.03Cr3+ sample at 425 K (∼152 °C) remains 49.2% of its initial intensity at 300 K. A NIR pc-LED is fabricated by combining the optimized Li2Mg3SnO6:0.03Cr3+ sample with a blue LED (455 nm blue chip), and the NIR radiant fluxes of 3.676 mW (at 10 mA) and 29.21 mW (at 100 mA), as well as a maximum NIR photoelectric efficiency of 14.2%, are obtained. The results show that this novel phosphor has great application potential in NIR pc-LEDs, and the annealing design exhibits huge potential for improving the optical properties of Cr3+-activated phosphors.
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Affiliation(s)
- Tao Tan
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
- University of Science and Technology of China Hefei 230026, China
| | - Ran Pang
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
| | - Shangwei Wang
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
| | - Haiyan Wu
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
| | - Jiutian Wang
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
- University of Science and Technology of China Hefei 230026, China
| | - Su Zhang
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
- University of Science and Technology of China Hefei 230026, China
| | - Chengyu Li
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
- University of Science and Technology of China Hefei 230026, China
| | - Hongjie Zhang
- State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022, China.
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Wang S, Pang R, Tan T, Wu H, Wang Q, Li C, Zhang S, Tan T, You H, Zhang H. Achieving High Quantum Efficiency Broadband NIR Mg 4 Ta 2 O 9 :Cr 3+ Phosphor Through Lithium-Ion Compensation. Adv Mater 2023; 35:e2300124. [PMID: 36867871 DOI: 10.1002/adma.202300124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/20/2023] [Indexed: 06/02/2023]
Abstract
Ultra-efficient broadband near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) are urgently needed to improve the detection sensitivity and spatial resolution of current smart NIR spectroscopy-based techniques. Nonetheless, the performance of NIR pc-LED has severely limited owing to the external quantum efficiency (EQE) bottleneck of NIR light-emitting materials. Herein, a blue LED excitable Cr3+ -doped tetramagnesium ditantalate (Mg4 Ta2 O9 , MT) phosphor is advantageously modified through lithium ion as a key efficient broadband NIR emitter to achieve high optical output power of the NIR light source. The emission spectrum encompasses the 700-1300 nm electromagnetic spectrum of first biological window (λmax = 842 nm) with a full-width at half-maximum (FWHM) of ≈2280 cm-1 (≈167 nm), and achieves a record EQE of 61.25% detected at 450 nm excitation through Li-ion compensation. A prototype NIR pc-LED is fabricated with MT:Cr3+ , Li+ to evaluate its potential practical application, which reveals an NIR output power of 53.22 mW at a driving current of 100 mA, and a photoelectric conversion efficiency of 25.09% at 10 mA. This work provides an ultra-efficient broadband NIR luminescent material, which shows great promise in practical applications and presents a novel option for the next-generation high-power compact NIR light sources.
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Affiliation(s)
- Shangwei Wang
- School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, Jiangxi, 330031, P. R. China
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi, 341000, P. R. China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Ran Pang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Tao Tan
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Haiyan Wu
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Qi Wang
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi, 341000, P. R. China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Chengyu Li
- School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, Jiangxi, 330031, P. R. China
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi, 341000, P. R. China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Su Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Taixing Tan
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi, 341000, P. R. China
| | - Hongpeng You
- School of Chemistry and Chemical Engineering, Nanchang University, Nanchang, Jiangxi, 330031, P. R. China
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi, 341000, P. R. China
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
| | - Hongjie Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, P. R. China
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Gong Y, Bai B, Sun N, Ci B, Shao H, Zhang T, Yao H, Zhang Y, Niu Y, Liu L, Zhao H, Wu H, Zhang L, Wang T, Li S, Wei Y, Yu Y, Ribeiro Orsi AE, Liu B, Ji W, Wu J, Chen Y, Tan T. Ex utero monkey embryogenesis from blastocyst to early organogenesis. Cell 2023; 186:2092-2110.e23. [PMID: 37172563 DOI: 10.1016/j.cell.2023.04.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [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: 08/02/2022] [Revised: 01/18/2023] [Accepted: 04/12/2023] [Indexed: 05/15/2023]
Abstract
The third and fourth weeks of gestation in primates are marked by several developmental milestones, including gastrulation and the formation of organ primordia. However, our understanding of this period is limited due to restricted access to in vivo embryos. To address this gap, we developed an embedded 3D culture system that allows for the extended ex utero culture of cynomolgus monkey embryos for up to 25 days post-fertilization. Morphological, histological, and single-cell RNA-sequencing analyses demonstrate that ex utero cultured monkey embryos largely recapitulated key events of in vivo development. With this platform, we were able to delineate lineage trajectories and genetic programs involved in neural induction, lateral plate mesoderm differentiation, yolk sac hematopoiesis, primitive gut, and primordial germ-cell-like cell development in monkeys. Our embedded 3D culture system provides a robust and reproducible platform for growing monkey embryos from blastocysts to early organogenesis and studying primate embryogenesis ex utero.
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Affiliation(s)
- Yandong Gong
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China; State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Senior Department of Hematology, Fifth Medical Center, Medical Innovation Research Department, Chinese PLA General Hospital, Beijing 100071, China
| | - Bing Bai
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Nianqin Sun
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Baiquan Ci
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Honglian Shao
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Ting Zhang
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Hui Yao
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Youyue Zhang
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Yuyu Niu
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Lizhong Liu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Hu Zhao
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Hao Wu
- School of Information Science and Engineering, Yunnan University, Kunming, Yunnan 650504, China
| | - Lei Zhang
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Tianxiang Wang
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Shangang Li
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Yulei Wei
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yang Yu
- Reproductive Medical Center and Clinical Stem Cell Research Center, Peking University Third Hospital, Beijing 100191, China
| | - Ana Elisa Ribeiro Orsi
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, SP 05508-090, Brazil
| | - Bing Liu
- State Key Laboratory of Experimental Hematology, Haihe Laboratory of Cell Ecosystem, Senior Department of Hematology, Fifth Medical Center, Medical Innovation Research Department, Chinese PLA General Hospital, Beijing 100071, China.
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
| | - Jun Wu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
| | - Yongchang Chen
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
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Zhang J, Sha D, Ma Y, Zhang D, Tan T, Xu X, Yi Q, Zhao Y. Joint conditional generative adversarial networks for eyelash artifact removal in ultra-wide-field fundus images. Front Cell Dev Biol 2023; 11:1181305. [PMID: 37215081 PMCID: PMC10196374 DOI: 10.3389/fcell.2023.1181305] [Citation(s) in RCA: 1] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 04/24/2023] [Indexed: 05/24/2023] Open
Abstract
Background: Ultra-Wide-Field (UWF) fundus imaging is an essential diagnostic tool for identifying ophthalmologic diseases, as it captures detailed retinal structures within a wider field of view (FOV). However, the presence of eyelashes along the edge of the eyelids can cast shadows and obscure the view of fundus imaging, which hinders reliable interpretation and subsequent screening of fundus diseases. Despite its limitations, there are currently no effective methods or datasets available for removing eyelash artifacts from UWF fundus images. This research aims to develop an effective approach for eyelash artifact removal and thus improve the visual quality of UWF fundus images for accurate analysis and diagnosis. Methods: To address this issue, we first constructed two UWF fundus datasets: the paired synthetic eyelashes (PSE) dataset and the unpaired real eyelashes (uPRE) dataset. Then we proposed a deep learning architecture called Joint Conditional Generative Adversarial Networks (JcGAN) to remove eyelash artifacts from UWF fundus images. JcGAN employs a shared generator with two discriminators for joint learning of both real and synthetic eyelash artifacts. Furthermore, we designed a background refinement module that refines background information and is trained with the generator in an end-to-end manner. Results: Experimental results on both PSE and uPRE datasets demonstrate the superiority of the proposed JcGAN over several state-of-the-art deep learning approaches. Compared with the best existing method, JcGAN improves PSNR and SSIM by 4.82% and 0.23%, respectively. In addition, we also verified that eyelash artifact removal via JcGAN could significantly improve vessel segmentation performance in UWF fundus images. Assessment via vessel segmentation illustrates that the sensitivity, Dice coefficient and area under curve (AUC) of ResU-Net have respectively increased by 3.64%, 1.54%, and 1.43% after eyelash artifact removal using JcGAN. Conclusion: The proposed JcGAN effectively removes eyelash artifacts in UWF images, resulting in improved visibility of retinal vessels. Our method can facilitate better processing and analysis of retinal vessels and has the potential to improve diagnostic outcomes.
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Affiliation(s)
- Jiong Zhang
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- The Affiliated Ningbo Eye Hospital of Wenzhou Medical University, Ningbo, China
| | - Dengfeng Sha
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China
| | - Yuhui Ma
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
| | - Dan Zhang
- School of Cyber Science and Engineering, Ningbo University of Technology, Ningbo, China
| | - Tao Tan
- Faulty of Applied Sciences, Macao Polytechnic University, Macao, Macao SAR, China
| | - Xiayu Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, China
- Zhejiang Research Institute of Xi’an Jiaotong University, Hangzhou, China
| | - Quanyong Yi
- The Affiliated Ningbo Eye Hospital of Wenzhou Medical University, Ningbo, China
| | - Yitian Zhao
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- The Affiliated Ningbo Eye Hospital of Wenzhou Medical University, Ningbo, China
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Wang W, Tan T, Wang S, Tan T, Zhang S, Li C, Zhang H. Multiple site occupancy induced yellow-orange emission in an Eu 2+-doped KSr 6Sc(SiO 4) 4 phosphor towards optical temperature sensors. Dalton Trans 2023; 52:6331-6342. [PMID: 37082961 DOI: 10.1039/d3dt00163f] [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: 04/22/2023]
Abstract
Phosphors have attracted significant interest as potential optical temperature sensors in recent years. In our work, a new blue-light stimulated KSr6Sc(SiO4)4:Eu2+ phosphor with decorative kröhnkite-like octahedral tetrahedral chains was successfully synthesized. Multiple site occupancy occurred in KSr6Sc(SiO4)4:Eu2+ and induced a yellow-orange emission band with a peak at 571 nm and an FWHM of 91 nm. Gaussian fitting and time-resolved photoluminescence mapping were combined to analyze the occupation of Eu2+ in five Sr2+ sites. In the meantime, the site occupation preference, energy transfer process, and thermal quenching mechanism of Eu2+ emission centers have been comprehensively examined. Under 450 nm excitation, the optimal sample possesses an acceptable quantum efficiency (EQE = 17.3%) and a high sensitivity between luminescence properties and temperature variation ranging from 200 to 475 K. The optimal sample's relative sensor sensitivity achieves a maximum value of 3.53% K-1 at 475 K. The phosphor KSr6Sc(SiO4)4:0.07Eu2+ presents the potentiality as an optical thermometer.
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Affiliation(s)
- Wenjing Wang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou 341000, P. R. China
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China
| | - Tao Tan
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Shangwei Wang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou 341000, P. R. China
| | - Taixing Tan
- Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou 341000, P. R. China
| | - Su Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Chengyu Li
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
| | - Hongjie Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China.
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Chockalingam Jnr R, Tang K, Chew K, Abdul Aziz Z, Loh J, Chao V, Tan T, Kerk K, Teo L, Sim D, Sivathasan C. A Retrospective Analysis of Concomitant Alfieri Stitch Mitral Valve Repair in Patients Undergoing Left Ventricular Assist Device Implantation. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1283] [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: 04/05/2023] Open
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47
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Tan J, Kerk K, Tay J, Neo C, Tan T, Sivathasan C. Microtrauma - A Common Cause for Driveline Infection. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1570] [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: 04/05/2023] Open
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48
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Zhang T, Tan T, Han L, Appelman L, Veltman J, Wessels R, Duvivier KM, Loo C, Gao Y, Wang X, Horlings HM, Beets-Tan RGH, Mann RM. Predicting breast cancer types on and beyond molecular level in a multi-modal fashion. NPJ Breast Cancer 2023; 9:16. [PMID: 36949047 PMCID: PMC10033710 DOI: 10.1038/s41523-023-00517-2] [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] [Received: 05/27/2022] [Accepted: 02/21/2023] [Indexed: 03/24/2023] Open
Abstract
Accurately determining the molecular subtypes of breast cancer is important for the prognosis of breast cancer patients and can guide treatment selection. In this study, we develop a deep learning-based model for predicting the molecular subtypes of breast cancer directly from the diagnostic mammography and ultrasound images. Multi-modal deep learning with intra- and inter-modality attention modules (MDL-IIA) is proposed to extract important relations between mammography and ultrasound for this task. MDL-IIA leads to the best diagnostic performance compared to other cohort models in predicting 4-category molecular subtypes with Matthews correlation coefficient (MCC) of 0.837 (95% confidence interval [CI]: 0.803, 0.870). The MDL-IIA model can also discriminate between Luminal and Non-Luminal disease with an area under the receiver operating characteristic curve of 0.929 (95% CI: 0.903, 0.951). These results significantly outperform clinicians' predictions based on radiographic imaging. Beyond molecular-level test, based on gene-level ground truth, our method can bypass the inherent uncertainty from immunohistochemistry test. This work thus provides a noninvasive method to predict the molecular subtypes of breast cancer, potentially guiding treatment selection for breast cancer patients and providing decision support for clinicians.
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Affiliation(s)
- Tianyu Zhang
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- GROW School for Oncology and Development Biology, Maastricht University, P. O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Tao Tan
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
- Faculty of Applied Sciences, Macao Polytechnic University, 999078, Macao SAR, China.
| | - Luyi Han
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Linda Appelman
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Jeroen Veltman
- Department of Radiology, Hospital Group Twente (ZGT), Almelo, The Netherlands
- Multi-Modality Medical Imaging Group, TechMed Centre, University of Twente, Enschede, The Netherlands
| | - Ronni Wessels
- Department of Radiology, Haga Teaching Hospital, The Hague, The Netherlands
| | - Katya M Duvivier
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Claudette Loo
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Yuan Gao
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- GROW School for Oncology and Development Biology, Maastricht University, P. O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Xin Wang
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- GROW School for Oncology and Development Biology, Maastricht University, P. O. Box 616, 6200 MD, Maastricht, The Netherlands
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
| | - Hugo M Horlings
- Division of Pathology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Regina G H Beets-Tan
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- GROW School for Oncology and Development Biology, Maastricht University, P. O. Box 616, 6200 MD, Maastricht, The Netherlands
| | - Ritse M Mann
- Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Diagnostic Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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Abstract
CTNNB1 is the gene that encodes β-catenin which acts as a key player in the Wnt signaling pathway and regulates cellular homeostasis. Most CTNNB1-related studies have been mainly focused on its role in cancer. Recently, CTNNB1 has also been found involved in neurodevelopmental disorders (NDDs), such as intellectual disability, autism, and schizophrenia. Mutations of CTNNB1 lead to the dysfunction of the Wnt signaling pathway that regulates gene transcription and further disturbs synaptic plasticity, neuronal apoptosis, and neurogenesis. In this review, we discuss a wide range of aspects of CTNNB1 and its physiological and pathological functions in the brain. We also provide an overview of the most recent research regarding CTNNB1 expression and its function in NDDs. We propose that CTNNB1 would be one of the top high-risk genes for NDDs. It could also be a potential therapeutic target for the treatment of NDDs.
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Affiliation(s)
- Wenting Zhuang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, China
| | - Tong Ye
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, China
| | - Wei Wang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, China
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Weihong Song
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, China
- *Correspondence: Weihong Song,
| | - Tao Tan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Key Laboratory of Alzheimer's Disease of Zhejiang Province, Institute of Aging, Wenzhou Medical University, Wenzhou, China
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
- Tao Tan,
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50
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Wei Y, Zhang E, Yu L, Ci B, Guo L, Sakurai M, Takii S, Liu J, Schmitz DA, Ding Y, Zhan L, Zheng C, Sun HX, Xu L, Okamura D, Ji W, Tan T, Wu J. Dissecting embryonic and extra-embryonic lineage crosstalk with stem cell co-culture. bioRxiv 2023:2023.03.07.531525. [PMID: 36945498 PMCID: PMC10028955 DOI: 10.1101/2023.03.07.531525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
Faithful embryogenesis requires precise coordination between embryonic and extraembryonic tissues. Although stem cells from embryonic and extraembryonic origins have been generated for several mammalian species(Bogliotti et al., 2018; Choi et al., 2019; Cui et al., 2019; Evans and Kaufman, 1981; Kunath et al., 2005; Li et al., 2008; Martin, 1981; Okae et al., 2018; Tanaka et al., 1998; Thomson et al., 1998; Vandevoort et al., 2007; Vilarino et al., 2020; Yu et al., 2021b; Zhong et al., 2018), they are grown in different culture conditions with diverse media composition, which makes it difficult to study cross-lineage communication. Here, by using the same culture condition that activates FGF, TGF-β and WNT signaling pathways, we derived stable embryonic stem cells (ESCs), extraembryonic endoderm stem cells (XENs) and trophoblast stem cells (TSCs) from all three founding tissues of mouse and cynomolgus monkey blastocysts. This allowed us to establish embryonic and extraembryonic stem cell co-cultures to dissect lineage crosstalk during early mammalian development. Co-cultures of ESCs and XENs uncovered a conserved and previously unrecognized growth inhibition of pluripotent cells by extraembryonic endoderm cells, which is in part mediated through extracellular matrix signaling. Our study unveils a more universal state of stem cell self-renewal stabilized by activation, as opposed to inhibition, of developmental signaling pathways. The embryonic and extraembryonic stem cell co-culture strategy developed here will open new avenues for creating more faithful embryo models and developing more developmentally relevant differentiation protocols.
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Affiliation(s)
- Yulei Wei
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - E Zhang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Leqian Yu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- The State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Baiquan Ci
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Lei Guo
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390
| | - Masahiro Sakurai
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Shino Takii
- Department of Advanced Bioscience, Graduate School of Agriculture, Kindai University, Nakamachi, Nara 631-8505, Japan
| | - Jian Liu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Daniel A. Schmitz
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yi Ding
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Linfeng Zhan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Canbin Zheng
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | | | - Lin Xu
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, Peter O’Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390
| | - Daiji Okamura
- Department of Advanced Bioscience, Graduate School of Agriculture, Kindai University, Nakamachi, Nara 631-8505, Japan
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Tao Tan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Jun Wu
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
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