tbuckley/cabot-search huggingface dataset:
QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy
Authors: Giulio Antonelli, Diogo Libanio, Albert Jeroen De Groof, Fons van der Sommen, Pietro Mascagni, Pieter Sinonquel, Mohamed Abdelrahim, Omer Ahmad, Tyler Berzin, Pradeep Bhandari, Michael Bretthauer, Miguel Coimbra, Evelien Dekker, Alanna Ebigbo, Tom Eelbode, Leonardo Frazzoni, Seth A Gross, Ryu Ishihara, Michal Filip Kaminski, Helmut Messmann, Yuichi Mori, Nicolas Padoy, Sravanthi Parasa, Nastazja Dagny Pilonis, Francesco Renna, Alessandro Repici, Cem Simsek, Marco Spadaccini, Raf Bisschops, Jacques J G H M Bergman, Cesare Hassan, Mario Dinis Ribeiro
Journal: Gut (2024)

Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical practice is hampered by the lack of rigorous standardisation and development methodology ensuring generalisability. The aim of the Quality Assessment of pre-clinical AI studies in Diagnostic Endoscopy (QUAIDE) Explanation and Checklist was to develop recommendations for standardised design and reporting of preclinical AI studies in GI endoscopy.The recommendations were developed based on a formal consensus approach with an international multidisciplinary panel of 32 experts among endoscopists and computer scientists. The Delphi methodology was employed to achieve consensus on statements, with a predetermined threshold of 80% agreement. A maximum three rounds of voting were permitted.Consensus was reached on 18 key recommendations, covering 6 key domains: data acquisition and annotation (6 statements), outcome reporting (3 statements), experimental setup and algorithm architecture (4 statements) and result presentation and interpretation (5 statements). QUAIDE provides recommendations on how to properly design (1. Methods, statements 1-14), present results (2. Results, statements 15-16) and integrate and interpret the obtained results (3. Discussion, statements 17-18).The QUAIDE framework offers practical guidance for authors, readers, editors and reviewers involved in AI preclinical studies in GI endoscopy, aiming at improving design and reporting, thereby promoting research standardisation and accelerating the translation of AI innovations into clinical practice.
Toxin-antitoxin systems reflect community interactions through horizontal gene transfer
Authors: Jonathan H Bethke, Jeffrey Kimbrel, Yongqin Jiao, Dante Ricci
Journal: Molecular Biology and Evolution (2024)

Abstract Bacterial evolution through horizontal gene transfer (HGT) reflects their community interactions. In this way, HGT networks do well at mapping community interactions, but offer little toward controlling them—an important step in the translation of synthetic strains into natural contexts. Toxin–antitoxin (TA) systems serve as ubiquitous and diverse agents of selection; however, their utility is limited by their erratic distribution in hosts. Here we examine the heterogeneous distribution of TAs as a consequence of their mobility. By systematically mapping TA systems across a 10,000 plasmid network, we find HGT communities have unique and predictable TA signatures. We propose these TA signatures arise from plasmid competition and have further potential to signal the degree to which plasmids, hosts, and phage interact. To emphasize these relationships, we construct an HGT network based solely on TA similarity, framing specific selection markers in the broader context of bacterial communities. This work both clarifies the evolution of TA systems and unlocks a common framework for manipulating community interactions through TA compatibility.
DeOri 10.0: An Updated Database of Experimentally Identified Eukaryotic Replication Origins
Authors: Yu-Hao Zeng, Zhen-Ning Yin, Hao Luo, Feng Gao
Journal: Genomics Proteomics & Bioinformatics (2024)

Abstract DNA replication is a complex and crucial biological process in eukaryotes. To facilitate the study of eukaryotic replication events, we present a database of eukaryotic DNA replication origins (DeOri), which collects scattered data and integrates extensive sequencing data on eukaryotic DNA replication origins. With continuous updates of DeOri, the number of datasets in the new release increased from 10 to 151 and the number of sequences increased from 16,145 to 9,742,396. Besides nucleotide sequences and bed files, corresponding annotation files, such as coding sequences (CDS), mRNA, and other biological elements within replication origins, are also provided. The experimental techniques used for each dataset, as well as other statistical data, are also presented on web page. Differences in experimental methods, cell lines, and sequencing technologies have resulted in distinct replication origins, making it challenging to differentiate between cell-specific and non-specific replication. We combined multiple replication origins at the species level, scored them, and screened them. The screened regions were considered as species-conservative origins. They are integrated and presented as reference replication origins (rORIs), including Homo sapiens, Gallus gallus, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans. Additionally, we analyzed the distribution of relevant genomic elements associated with replication origins at the genome level, such as CpG island (CGI), transcription start site (TSS), and G-quadruplex (G4). These analysis results allow users to select the desired data based on it. DeOri is available at http://tubic.tju.edu.cn/deori/.
MitoSort: Robust Demultiplexing of Pooled Single-cell Genomics Data Using Endogenous Mitochondrial Variants
Authors: Zhongjie Tang, Weixing Zhang, Peiyu Shi, Sijun Li, Xinhui Li, Yueming Li, Yicong Xu, Yaqing Shu, Zheng Hu, Jin Xu
Journal: Genomics Proteomics & Bioinformatics (2024)

Abstract Multiplexing across donors has emerged as a popular strategy to increase throughput, reduce costs, overcome technical batch effects, and improve doublet detection in single-cell genomic studies. To eliminate additional experimental steps, endogenous nuclear genome variants are used for demultiplexing pooled single-cell RNA sequencing (scRNA-seq) data by several computational tools. However, these tools have limitations when applied to single-cell sequencing methods that do not cover nuclear genomic regions well, such as single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq). Here, we demonstrate that mitochondrial germline variants are an alternative, robust, and computationally efficient endogenous barcode for sample demultiplexing. We propose MitoSort, a tool that uses mitochondrial germline variants to assign cells to their donor of origin and identify cross-genotype doublets in single-cell genomics datasets. We evaluate its performance by using in silico pooled mitochondrial scATAC-seq (mtscATAC-seq) libraries and experimentally multiplexed data with cell hashtags. MitoSort achieves high accuracy and efficiency in genotype clustering and doublet detection for mtscATAC-seq data, addressing the limitations of current computational techniques tailored for scRNA-seq data. Moreover, MitoSort exhibits versatility and can be applied to various single-cell sequencing approaches beyond mtscATAC-seq, provided the mitochondrial variants are reliably detected. Furthermore, we demonstrate the application of MitoSort in a case study where B cells from eight donors were pooled and assayed by single-cell multi-omics sequencing. Altogether, our results demonstrate the accuracy and efficiency of MitoSort, which enables reliable sample demultiplexing in various single-cell genomic applications. MitoSort is available at https://github.com/tangzhj/MitoSort.
LAPTM5
Authors: Michael S. Balzer
Journal: Journal of the American Society of Nephrology (2024)

Department of Nephrology and Medical Intensive Care, Charité – Universitätsmedizin Berlin, Berlin, Germany; and Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Clinician Scientist Program, Berlin, Germany Correspondence: Dr. Michael S. Balzer, email: [email protected] See related article, "Lysosomal-Associated Protein Transmembrane 5, Tubular Senescence, and Progression of CKD," on pages XXX–XXX.
Bioinformatic Resources for Exploring Human-virus Protein-protein Interactions Based on Binding Modes
Authors: Huimin Chen, Jiaxin Liu, Gege Tang, Gefei Hao, Guangfu Yang
Journal: Genomics Proteomics & Bioinformatics (2024)

Abstract Historically, there have been many outbreaks of viral diseases that have continued to claim millions of lives. Research on human-virus protein-protein interactions (PPIs) is vital to understanding the principles of human-virus relationships, providing an essential foundation for developing virus control strategies to combat diseases. The rapidly accumulating data on human-virus PPIs offer unprecedented opportunities for bioinformatics research around human-virus PPIs. However, available detailed analyses and summaries to help use these resources systematically and efficiently are lacking. Here, we comprehensively review the bioinformatic tools used in human-virus PPIs research, discuss and compare the function, performance, and limitations of these web resources. This study aims to provide researchers with a bioinformatic toolbox that will hopefully better facilitate the exploration of human-virus PPIs based on binding modes.
EMC3 regulates trafficking and pulmonary toxicity of the SFTPCI73T mutation associated with interstitial lung disease
Authors: Xiaofang Tang, Wei Wei, Yuqing Sun, Timothy E. Weaver, Ernesto S. Nakayasu, Geremy Clair, John M. Snowball, Cheng-Lun Na, Karen S. Apsley, Emily P. Martin, Darrell N. Kotton, Konstantinos-Dionysios Alysandratos, Jiuzhou Huo, Jeffery D. Molkentin, William A. Gower, Xinhua Lin, Jeffrey A. Whitsett
Journal: Journal of Clinical Investigation (2024)

The most common mutation in surfactant protein C gene (SFTPC), SFTPCI73T, causes interstitial lung disease with few therapeutic options. We previously demonstrated that EMC3, an important component of the multiprotein endoplasmic reticulum membrane complex (EMC), is required for surfactant homeostasis in alveolar type 2 epithelial (AT2) cells at birth. In the present study, we investigated the role of EMC3 in the control of SFTPCI73T metabolism and its associated alveolar dysfunction. Using a knock-in mouse model phenocopying the I73T mutation, we demonstrated that conditional deletion of Emc3 in AT2 cells rescued alveolar remodeling/simplification defects in neonatal and adult mice. Proteomic analysis revealed that Emc3 depletion reversed the disruption of vesicle trafficking pathways and rescued the mitochondrial dysfunction associated with I73T mutation. Affinity purification-mass spectrometry analysis identified potential EMC3 interacting proteins in lung AT2 cells, including Valosin Containing Protein (VCP) and its interactors. Treatment of SftpcI73T knock-in mice and SFTPCI73T expressing iAT2 cells derived from SFTPCI73T patient-specific iPSCs with the specific VCP inhibitor CB5083 restored alveolar structure and SFTPCI73T trafficking respectively. Taken together, the present work identifies the EMC complex and VCP in the metabolism of the disease-associated SFTPCI73T mutant, providing novel therapeutical targets for SFTPCI73T-associated interstitial lung disease.
The Nr4a family regulates intrahepatic Treg proliferation and liver fibrosis in MASLD models
Authors: Daisuke Aki, Taeko Hayakawa, Tanakorn Srirat, Shigeyuki Shichino, Minako Ito, Shin-Ichiroh Saitoh, Setsuko Mise-Omata, Akihiko Yoshimura
Journal: Journal of Clinical Investigation (2024)

Nonalcoholic steatohepatitis (NASH) is a chronic progressive liver disease and highly prevalent worldwide. NASH is characterized by hepatic steatosis, inflammation, fibrosis and liver damage, which eventually results in liver dysfunction due to cirrhosis or hepatocellular carcinoma. However, the cellular and molecular mechanisms underlying NASH progression remain largely unknown. Here, we found an increase of Nr4a family of orphan nuclear receptors expression in intrahepatic T cells from mice with diet-induced NASH. Loss of Nr4a1 and Nr4a2 in T cell (dKO) ameliorated liver cell death and fibrosis, thereby mitigating liver dysfunction in NASH mice. dKO resulted in reduction of infiltrated macrophages and Th1/Th17 cells, whereas massive accumulation of T regulatory (Treg) cells in the liver of NASH mice. Combined single-cell RNA transcriptomic and TCR sequencing analysis revealed that intrahepatic dKO Tregs exhibited enhanced TIGIT and IL10 expression and were clonally expanded during NASH progression. Mechanistically, we found that dKO Tregs expressed high levels of Batf which promotes Treg cell proliferation and function upon TCR stimulation. Collectively, our findings not only provide an insight into the impact of intrahepatic Treg cells on NASH pathogenesis, but also suggest a therapeutic potential of targeting of Nr4a family to treat the disease.
Targeting exosomal double-stranded RNA-TLR3 signaling pathway attenuates morphine tolerance and hyperalgesia
Authors: Bing Wang, Dong-Sheng Le, Li Liu, Xue-Xue Zhang, Fan Yang, Guo-Rong Lai, Chao Zhang, Mai-Lin Zhao, Yun-Peng Shen, Ping-Sheng Liao, Tong Liu, Ying-Ping Liang
Journal: Cell Reports Medicine (2024)
Lighting up arginine metabolism reveals its functional diversity in physiology and pathology
Authors: Rui Li, Yan Li, Kun Jiang, Lijuan Zhang, Ting Li, Aihua Zhao, Zhuo Zhang, Yale Xia, Kun Ge, Yaqiong Chen, Chengnuo Wang, Weitao Tang, Shuning Liu, Xiaoxi Lin, Yuqin Song, Jie Mei, Chun Xiao, Aoxue Wang, Yejun Zou, Xie Li, Xianjun Chen, Zhenyu Ju, Wei Jia, Joseph Loscalzo, Yu Sun, Wei Fang, Yi Yang, Yuzheng Zhao
Journal: Cell Metabolism (2024)
Deep learning model with pathological knowledge for detection of colorectal neuroendocrine tumor
Authors: Ke Zheng, Jinling Duan, Ruixuan Wang, Haohua Chen, Haiyang He, Xueyi Zheng, Zihan Zhao, Bingzhong Jing, Yuqian Zhang, Shasha Liu, Dan Xie, Yuan Lin, Yan Sun, Ning Zhang, Muyan Cai
Journal: Cell Reports Medicine (2024)
Modeling lung adenocarcinoma metastases using patient-derived organoids
Authors: Yuan Liu, Manendra Lankadasari, Joel Rosiene, Kofi E Johnson, Juan Zhou, Samhita Bapat, Lai-Fong L Chow-Tsang, Huasong Tian, Brooke Mastrogiacomo, Di He, James G Connolly, Harry B Lengel, Raul Caso, Elizabeth G Dunne, Cameron N Fick, Gaetano Rocco, Smita Sihag, James M Isbell, Mathew J Bott, Bob T Li, Piro Lito, Cameron W Brennan, Mark H Bilsky, Natasha Rekhtman, Prasad S Adusumilli, Marty W Mayo, Marcin Imielinski, David R Jones
Journal: Cell Reports Medicine (2024)
Adipocyte lipin 1 expression associates with human metabolic health and regulates systemic metabolism in mice
Authors: Andrew LaPoint, Jason M. Singer, Daniel Ferguson, Trevor M. Shew, M. Katie Renkemeyer, Hector H. Palacios, Rachael L. Field, Sireeesha Yerrathota, Roshan Kumari, Mahalakshmi Shankaran, Gordon I. Smith, Jun Yoshino, Mai He, Gary J. Patti, Marc K. Hellerstein, Samuel Klein, E. Matthew Morris, Jonathan R. Brestoff, Brian N. Finck, Andrew Lutkewitte
Journal: Journal of Clinical Investigation (2024)

Dysfunctional adipose tissue is believed to promote the development of hepatic steatosis and systemic insulin resistance, but many of the mechanisms involved are still unclear. Lipin 1 catalyzes the conversion of phosphatidic acid to diacylglycerol (DAG), the penultimate step of triglyceride synthesis, which is essential for lipid storage. Herein we found that adipose tissue LPIN1 expression is decreased in people with obesity compared to lean subjects, and low LPIN1 expression correlated with multi-tissue insulin resistance and increased rates of hepatic de novo lipogenesis. Comprehensive metabolic and multi-omic phenotyping demonstrated that adipocyte-specific Lpin1-/- mice had a metabolically-unhealthy phenotype, including liver and skeletal muscle insulin resistance, hepatic steatosis, increased hepatic de novo lipogenesis, and transcriptomic signatures of metabolically associated steatohepatitis that was exacerbated by high-fat diets. We conclude that adipocyte lipin 1-mediated lipid storage is vital for preserving adipose tissue and systemic metabolic health, and its loss predisposes mice to metabolically associated steatohepatitis.
A phase 2 trial of gemcitabine plus toripalimab for cisplatin-ineligible patients with recurrent or metastatic nasopharyngeal carcinoma
Authors: Xiong Zou, Xi Ding, Zheng-Kai Feng, Yan-Feng Ouyang, Hui-Feng Li, Kai Wen, Zhi-Qiang Wang, You-Ping Liu, Yong-Long Liu, Wei-Jing Zhang, Qi Yang, Si-Yuan Chen, Yu-Long Xie, Ruo-Qi Xie, Chao Lin, Chen-Mei Gu, Pei-Yu Huang, Rui Sun, Yi-Jun Hua, Rui You, Ming-Yuan Chen
Journal: Cell Reports Medicine (2024)
Application of Community Detection Methods to Identify Emergency General Surgery–Specific Regional Networks
Authors: Jiuying Han, Neng Wan, Joshua J. Horns, Marta L. McCrum
Journal: JAMA Network Open (2024)

Importance There is growing interest in developing coordinated regional systems for nontraumatic surgical emergencies; however, our understanding of existing emergency general surgery (EGS) care communities is limited. Objective To apply network analysis methods to delineate EGS care regions and compare the performance of this method with the Dartmouth Health Referral Regions (HRRs). Design, Setting, and Participants This cross-sectional study was conducted using the 2019 California and New York state emergency department and inpatient databases. Eligible participants included all adult patients with a nonelective admission for common EGS conditions. Interhospital transfers (IHTs) were identified by transfer indicators or temporally adjacent hospitalizations at 2 different facilities. Data analysis was conducted from January to May 2024. Exposure Admission for primary EGS diagnosis. Main Outcomes and Measures Regional EGS networks (RENs) were delineated by modularity optimization (MO), a community detection method, and compared with the plurality-based Dartmouth HRRs. Geographic boundaries were compared through visualization of patient flows and associated health care regions. Spatial accuracy of the 2 methods was compared using 6 common network analysis measures: localization index (LI), market share index (MSI), net patient flow, connectivity, compactness, and modularity. Results A total of 1 244 868 participants (median [IQR] age, 55 [37-70 years]; 776 725 male [62.40%]) were admitted with a primary EGS diagnosis. In New York, there were 405 493 EGS encounters with 3212 IHTs (0.79%), and 9 RENs were detected using MO compared with 10 Dartmouth HRRs. In California, there were 839 375 encounters with 10 037 IHTs (1.20%), and 14 RENs were detected compared with 24 HRRs. The greatest discrepancy between REN and HRR boundaries was in rural regions where one REN often encompassed multiple HRRs. The MO method was significantly better than HRRs in identifying care networks that accurately captured patients living within the geographic region as indicated by the LI and MSI for New York (mean [SD] LI, 0.86 [1.00] for REN vs 0.74 [1.00] for HRR; mean [SD] MSI, 0.16 [0.13] for REN vs 0.32 [0.21] for HRR) and California (mean [SD] LI, 0.83 [1.00] for REN vs 0.74 [1.00] for HRR; mean [SD] MSI, 0.19 [0.14] for REN vs 0.39 [0.43] for HRR). Nearly 27% of New York hospitals (37 of 139 hospitals [26.62%]) and 15% of California hospitals (48 of 336 hospitals [14.29%]) were reclassified into a different community with the MO method. Conclusions and Relevance Development of optimal health delivery systems for EGS patients will require knowledge of care patterns specific to this population. The findings of this cross-sectional study suggest that network science methods, such as MO, offer opportunities to identify empirical EGS care regions that outperform HRRs and can be applied in the development of coordinated regional systems of care.
Toward the Rigorous Evaluation of Early Warning Scores
Authors: Amol A. Verma
Journal: JAMA Network Open (2024)

Dana P. Edelson, MD, MS; Matthew M. Churpek, MD, MPH, PhD; Kyle A. Carey, MPH; Zhenqui Lin, PhD; Chenxi Huang, PhD; Jonathan M. Siner, MD; Jennifer Johnson, MSN, APRN; Harlan M. Krumholz, MD, SM; Deborah J. Rhodes, MD
Hospital Strain During the COVID-19 Pandemic and Outcomes in Older Racial and Ethnic Minority Adults
Authors: Laurent G. Glance, Karen E. Joynt Maddox, Patricia W. Stone, E. Yoko Furuya, Jingjing Shang, Mark J. Sorbero, Ashley Chastain, Stewart J. Lustik, Andrew W. Dick
Journal: JAMA Network Open (2024)

Importance Marginalized populations have been disproportionately affected by the COVID-19 pandemic. Critically ill patients belonging to racial and ethnic minority populations treated in hospitals operating under crisis or near-crisis conditions may have experienced worse outcomes than White individuals. Objective To examine whether hospital strain was associated with worse outcomes for older patients hospitalized with sepsis and whether these increases in poor outcomes were greater for members of racial and ethnic minority groups compared with White individuals. Design, Setting, and Participants In this cross-sectional study, multivariable regression analysis was conducted to assess differential changes in all-cause 30-day mortality and major morbidity among older racial and ethnic minoritized individuals hospitalized with sepsis compared with White individuals and changes in hospital strain using Medicare claims data. Data were obtained on patients hospitalized between January 1, 2016, and December 31, 2021, and analyzed between December 16, 2023, and July 11, 2024. Exposure Time-varying weekly hospital percentage of inpatients with COVID-19. Main Outcomes and Measures Composite of all-cause 30-day mortality and major morbidity. Results Among the 5 899 869 hospitalizations for sepsis (51.5% women; mean [SD] age, 78.2 [8.8] years), there were 177 864 (3.0%) Asian, 664 648 (11.3%) Black, 522 964 (8.9%) Hispanic, and 4 534 393 (76.9%) White individuals. During weeks when the hospital COVID-19 burden was greater than 40%, the risk of death or major morbidity increased nearly 2-fold (adjusted odds ratio [AOR], 1.90; 95% CI, 1.80-2.00; P &amp;amp;lt; .001) for White individuals compared with before the pandemic. Asian, Black, and Hispanic individuals experienced 44% (AOR, 1.44; 95% CI, 1.28-1.61; P &amp;amp;lt; .001), 21% (AOR, 1.21; 95% CI, 1.11-1.33; P &amp;amp;lt; .001), and 45% (AOR, 1.45; 95% CI, 1.32-1.59; P &amp;amp;lt; .001) higher risk of death or morbidity, respectively, compared with White individuals when the hospital weekly COVID-19 burden was greater than 40%. Conclusion and Relevance In this cross-sectional study, older adults hospitalized with sepsis were more likely to die or experience major morbidity as the hospital COVID-19 burden increased. These increases in adverse outcomes were greater in magnitude among members of minority populations than for White individuals.
Early-Life Factors and Early-Onset Endometrial Cancer Risk in the UK Biobank
Authors: Noah C. Peeri, Kelli O’Connell, Elizabeth D. Kantor, V. Wendy Setiawan, Xingyi Guo, Loren Lipworth, Mengmeng Du
Journal: JAMA Network Open (2024)

This case-control study investigates UK Biobank data for 8 early-life factors and early-onset endometrial cancer risk among UK residents.