tbuckley/cabot-search huggingface dataset:
MMRNet: Ensemble deep learning models for predicting mismatch repair deficiency in endometrial cancer from histopathological images
Authors: Li-Li Liu, Bing-Zhong Jing, Xuan Liu, Rong-Gang Li, Zhao Wan, Jiang-Yu Zhang, Xiao-Ming Ouyang, Qing-Nuan Kong, Xiao-Ling Kang, Dong-Dong Wang, Hao-Hua Chen, Zi-Han Zhao, Hao-Yu Liang, Ma-Yan Huang, Cheng-You Zheng, Xia Yang, Xue-Yi Zheng, Xin-Ke Zhang, Li-Jun Wei, Chao Cao, Hong-Yi Gao, Rong-Zhen Luo, Mu-Yan Cai
Journal: Cell Reports Medicine (2025)

Combining molecular classification with clinicopathologic methods improves risk assessment and chooses therapies for endometrial cancer (EC). Detecting mismatch repair (MMR) deficiencies in EC is crucial for screening Lynch syndrome and identifying immunotherapy candidates. An affordable and accessible tool is urgently needed to determine MMR status in EC patients. We introduce MMRNet, a deep convolutional neural network designed to predict MMR-deficient EC from whole-slide images stained with hematoxylin and eosin. MMRNet demonstrates strong performance, achieving an average area under the receiver operating characteristic curve (AUROC) of 0.897, with a sensitivity of 0.628 and a specificity of 0.949 in internal cross-validation. External validation using three additional datasets results in AUROCs of 0.790, 0.807, and 0.863. Employing a human-machine fusion approach notably improves diagnostic accuracy. MMRNet presents an effective method for identifying EC cases for confirmatory MMR testing and may assist in selecting candidates for immunotherapy.
Detection of brain cancer using genome-wide cell-free DNA fragmentomes
Authors: Dimitrios Mathios, Noushin Niknafs, Akshaya V. Annapragada, Ernest J. Bobeff, Elaine J. Chiao, Kavya Boyapati, Keerti Boyapati, Sarah Short, Adrianna L. Bartolomucci, Stephen Cristiano, Shashikant Koul, Nicholas A. Vulpescu, Leonardo Ferreira, Jamie E. Medina, Daniel C. Bruhm, Vilmos Adleff, Małgorzata Podstawka, Patrycja Stanisławska, Chul-Kee Park, Judy Huang, Gary L. Gallia, Henry Brem, Debraj Mukherjee, Justin M. Caplan, Jon Weingart, Christopher M. Jackson, Michael Lim, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu
Journal: Cancer Discovery (2025)

Abstract Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer diagnosis. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) or without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.
Reprogramming of radiation-deteriorated TME by liposomal nanomedicine to potentiate radio-immunotherapy
Authors: Yue Liu, Yanxiang Zhang, Xulu Yang, Shanshan Lang, Yansheng Zhu, Jiawei Song, Yi Zhu, Haiyi Xu, Pei Pei, Hong Zhu, Kai Yang, Teng Liu
Journal: Journal of Controlled Release (2025)
An interplay between human genetics and intratumoral microbiota in the progression of colorectal cancer
Authors: Jing Yu, Yuxuan Liang, Qingrong Zhang, Hui Ding, Minghao Xie, Jingjing Zhang, Wenyan Hu, Sihua Xu, Yiyuan Xiao, Sha Xu, Rong Na, Baixing Wu, Jiaming Zhou, Haitao Chen
Journal: Cell Host & Microbe (2025)
IL-10 sensing by lung interstitial macrophages prevents bacterial dysbiosis-driven pulmonary inflammation and maintains immune homeostasis
Authors: Seung Hyeon Kim, Zachary White, Anastasiia Gainullina, Soeun Kang, Jiseon Kim, Joseph R Dominguez, Yeonwoo Choi, Ivan Cabrera, Madison Plaster, Michihiro Takahama, Rafael S Czepielewski, Jinki Yeom, Matthias Gunzer, Nissim Hay, Odile David, Nicolas Chevrier, Teruyuki Sano, Ki-Wook Kim
Journal: Immunity (2025)
scRNA-seq reveals an immune microenvironment and JUN-mediated NK cell exhaustion in relapsed T-ALL
Authors: Yong Liu, Zefan Du, Lindi Li, Junbin Huang, Su Liu, Bo Lu, Yifei Duan, Yucai Cheng, Tianwen Li, Jing Zhang, Jiani Mo, Yalin Yang, Wengqing Wang, Hailin Zou, Tianqi Liang, Meng Jiang, Mo Yang, Yun Chen, Cheng Ouyang, Chun Chen
Journal: Cell Reports Medicine (2025)

T cell acute lymphoblastic leukemia (T-ALL) is a heterogeneous disease characterized by a high relapse rate. By single-cell transcriptome analysis, we characterize the bone marrow immune microenvironment in patients with T-ALL, identifying 13 major cell clusters. These patients exhibited abnormally expanded hematopoietic stem cells (HSCs) and granulocyte-monocyte progenitors (GMPs), immunosuppressive traits in CD4+ T, CD8+ T, and natural killer (NK) cells. Subdividing CD4+ T cells reveal two subsets transitioning between T helper (Th)1/Th2, Annexin-A1 (ANXA1)-GATA3-CD4+ T, and ANXA1+GATA3+CD4+ T. Additionally, NK cells demonstrate exhaustion in the tumor microenvironment of patients with relapsed T-ALL, with JUN identified as a critical factor. Additionally, JUN is also highly expressed in T-ALL and is crucial for maintaining its proliferation. The JUN inhibitor exhibited successful lethality toward leukemia cells and ameliorated NK cell exhaustion in relapsed T-ALL cell line, as well as in cell-derived tumor xenograft (CDX), patient-derived tumor xenograft (PDX), and NOTCH1-mutant mouse models. In summary, our findings enhance the understanding of T-ALL relapse mechanisms and support the development of innovative immunotherapies for patients with relapsed T-ALL.
Prenatal and Perinatal Factors of Life’s Essential 8 Cardiovascular Health Trajectories
Authors: Izzuddin M. Aris, Sheryl L. Rifas-Shiman, Sarah D. de Ferranti, Marie-France Hivert, Wei Perng
Journal: JAMA Network Open (2025)

Importance The American Heart Association put forth the Life’s Essential 8 construct to assess cardiovascular health (CVH) based on 8 biological and behavioral factors. Few studies have identified prenatal and perinatal factors of CVH trajectories across childhood and adolescence, life stages where disease precursors and health behaviors are established. Objective To examine associations of prenatal and perinatal factors with child CVH trajectory. Design, setting, and participants Data from the Project Viva prebirth cohort from April 1999 to August 2021 were used. Participant inclusion required 3 or more CVH metrics in early childhood (median [range] age, 3.2 [2.8-6.2] years) or 4 or more in midchildhood (median [range] age, 7.7 [6.6-10.9] years), early adolescence (median [range] age, 13.0 [11.9-16.6] years), or late adolescence (median [range] age, 17.5 [15.4-20.1] years). Data were analyzed from April 1 to September 30, 2024. Exposures Prenatal and perinatal factors. Main outcomes and measures CVH score (0-100 points), calculated as the unweighted average of all available CVH metrics at each life stage. Results Among 1333 children included, 680 (51.0%) were male, 78 (5.9%) Hispanic, 181 (13.6%) non-Hispanic Black, and 959 (71.9%) non-Hispanic White. The estimated mean (SD) age of inflection when CVH started to decline was 10.2 (0.7) years for male children and 10.0 (0.6) years for female children. Prepregnancy overweight or obesity (vs healthy or underweight), smoking during pregnancy (vs never), and formula-feeding (vs breastfeeding) in the first 6 months were each associated with lower CVH from childhood to adolescence, but gestational diabetes (vs normal glucose tolerance) was not associated with CVH. Prepregnancy obesity was associated with later inflection (β = 0.1; 95% CI, 0.0 to 0.2 years) and slower CVH decline after inflection (β = 0.2; 95% CI, 0.1 to 0.4 points per year). Gestational hypertension or preeclampsia (vs normal blood pressure) was associated with faster CVH gain before inflection (β = 0.3; 95% CI, 0.1 to 0.5 points per year), earlier inflection (β = −0.1; 95% CI, −0.2 to 0.0 years), and faster CVH decline after inflection (β = −0.3; 95% CI, −0.5 to −0.1 points per year), while smoking during pregnancy was associated with later inflection (β = 0.2; 95% CI, 0.1 to 0.3 years). Conclusions and Relevance In this cohort study, prepregnancy overweight or obesity, smoking during pregnancy, and formula-feeding in the first 6 months of life were each associated with adverse CVH trajectories early in life. Future work should examine whether interventions that address these factors would be effective in optimizing CVH in children.
Multi-species probiotic supplement enhances vagal nerve function – results of a randomized controlled trial in patients with depression and healthy controls
Authors: Sabrina Mörkl, Martin Narrath, Daria Schlotmann, Marie-Therese Sallmutter, Julia Putz, Julia Lang, Andreas Brandstätter, Rene Pilz, Helmut Karl Lackner, Nandu Goswami, Bianca Steuber, Jasmin Tatzer, Sonja Lackner, Sandra Holasek, Annamaria Painold, Emanuel Jauk, Julian Wenninger, Angela Horvath, Nicolai Spicher, Asmus Barth, Mary I Butler, Jolana Wagner-Skacel
Journal: Gut Microbes (2025)

Major depression (MD) significantly impacts individual well-being and society. The vagus nerve plays a pivotal role in the gut-brain axis, facilitating bidirectional communication between these systems. Recent meta-analyses suggest potential antidepressant effects of probiotics, although their mechanisms remain unclear. This study aimed to assess the impact of a multi-species probiotic (OMNi-BiOTiC® STRESS Repair) on vagus nerve function in 43 MD patients and 43 healthy controls (HC). Participants received either probiotics or placebo twice daily. Serum and stool samples were collected at baseline, 7 days, 28 days, and 3 months. Vagus nerve (VN) function was evaluated using 24-hour electrocardiography (ECG) for heart rate variability (HRV), alongside stool microbiome analysis via 16S rRNA sequencing. After 3 months, MD patients receiving probiotics demonstrated significantly improved morning VN function compared to HC. MD participants who were in the probiotic group showed a significant increase in Christensellales, particularly Akkermansia muciniphila along with improved sleep parameters (use of sleep medication, sleep latency) as measured by the Pittsburgh Sleep Quality Inventory (PSI). This study highlights potential physiological benefits of probiotics in MD, potentially mediated through VN stimulation. Understanding these mechanisms could lead to novel therapeutic approaches for MD management.
Rhizosphere microbes facilitate the break of chlamydospore dormancy and root colonization of rice false smut fungi
Authors: Xiayan Pan, Yang Yue, Fengjuan Zhao, Tianqiao Song, Boting Xu, Zhi Li, Zhongqiang Qi, Junjie Yu, Huijuan Cao, Mina Yu, Qirong Shen, Jinrong Xu, Wu Xiong, Yongfeng Liu
Journal: Cell Host & Microbe (2025)
A multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder
Authors: Jiawei Wang, Yujing Liu, Hongyu Li, Tuan P Nguyen, John Lee Soto-Vargas, Rashaun Wilson, Weiwei Wang, TuKiet T Lam, Chi Zhang, Chen Lin, David A Lewis, Jill Glausier, Paul E Holtzheimer, Matthew J Friedman, Kenneth R Williams, Marina R Picciotto, Angus C Nairn, John H Krystal, Ronald S Duman, Keith A Young, Hongyu Zhao, Matthew J Girgenti
Journal: Genome Medicine (2025)

Abstract Background Post-traumatic stress disorder (PTSD) is a common and disabling psychiatric disorder. PTSD involves multiple brain regions and is often comorbid with other psychiatric disorders, such as major depressive disorder (MDD). Recent genome-wide association studies (GWASs) have identified many PTSD risk loci and transcriptomics studies of postmortem brain have found differentially expressed genes associated with PTSD cases. In this study, we integrated genome-wide measures across modalities to identify convergent molecular effects in the PTSD brain. Methods We performed tandem mass spectrometry (MS/MS) on a large cohort of donors ( N = 66) in two prefrontal cortical areas, dorsolateral prefrontal cortex (DLPFC), and subgenual prefrontal cortex (sgPFC). We also coupled the proteomics data with transcriptomics and microRNA (miRNA) profiling from RNA-seq and small-RNA sequencing, respectively for the same cohort. Additionally, we utilized published GWAS results of multiple psychiatric disorders for integrative analysis. Results We found differentially expressed proteins and co-expression protein modules disrupted by PTSD. Integrative analysis with transcriptomics and miRNA data from the same cohort pointed to hsa-mir-589 as a regulatory miRNA responsible for dysregulation of neuronal protein networks for PTSD, including the gamma-aminobutyric acid (GABA) vesicular transporter, SLC32A1. In addition, we identified significant enrichment of risk genes for other psychiatric disorders, such as autism spectrum disorder (ASD) and major depressive disorder (MDD) within PTSD protein co-expression modules, suggesting shared molecular pathology. Conclusions We integrated genome-wide measures of mRNA and miRNA expression and proteomics profiling from PTSD, MDD, and control (CON) brains to identify convergent and divergent molecular processes across genomic modalities. We substantially expand the number of differentially expressed genes and proteins in PTSD and identify downregulation of GABAergic processes in the PTSD proteome. This provides a novel framework for future studies integrating proteomic profiling with transcriptomics and non-coding RNAs in the human brain studies.
Escalating vs Fixed Energy Defibrillation in Out-of-Hospital Cardiac Arrest Ventricular Fibrillation
Authors: Hanqi Tang, Ruoxue Wu, Lu Yin, Wenlin Hao, Jing Shi, Huadong Zhu, Shengyong Xu, Jun Xu
Journal: JAMA Network Open (2025)

Importance There is limited evidence on whether higher-energy defibrillation is preferred in patients experiencing out-of-hospital cardiac arrest (OHCA) with shockable rhythms. Objective To investigate the optimal energy regimen for initial and subsequent defibrillation delivered by biphasic waveform automated external defibrillators (AEDs) in OHCA ventricular fibrillation (VF). Design, Setting, and Participants This cohort study was conducted in 48 cities across China, from 2017 to 2023, among 342 patients with OHCA who experienced at least 1 shock. Exposures Escalating higher-energy (200-300-360 J) defibrillation or fixed low-energy (200-200-200 J) defibrillation according to the AED program available for use. Main Outcome and Measures Sustained and transient termination of VF and establishment of an organized rhythm after defibrillations were the main clinical outcomes. Results A total of 342 patients with OHCA were included (mean [SD] age, 57.2 [20.6] years; 273 male [79.8%]) with 782 VF defibrillations; 218 patients (63.8%) with a total of 480 instances (61.4%) of VF rhythm received AED with escalating higher-energy regimens. Most VF episodes were effectively terminated transiently at the first shock (200 J in both groups) (94% in the escalating higher-energy group vs 93% in the fixed lower-energy group; P = .64), but only half remained terminated until the next rhythm analysis (49% vs 47%; P = .68). Comparatively, VF that received escalating higher-energy regimens were more likely to establish sustained organized rhythm (34% vs 25%; P = .008; absolute difference, 9% [95% CI, 2% to 16%]). In refractory VF rhythms, the percentage of cases where sustained organized rhythms were established was significantly greater in escalating higher-energy regimens after second shocks and above (24% vs 13%; P = .008; absolute difference, 11% [95% CI, 3% to 19%]) and third shocks and above (35% vs 18%; P = .003; absolute difference 17% [95% CI, 5% to 27%]). Conclusions and Relevance In this retrospective cohort study of patients experiencing OHCA-VF, both the escalating higher-energy (200-300-360 J) regimen and the fixed low-energy (200-200-200 J) regimen were effective for transient VF termination at first shock, whereas the escalating higher-energy regimens were more likely to maintain termination and restore an organized rhythm. Higher-energy regimens were associated with better outcomes after all shocks, especially in patients with refractory VF.
The Lung Cancer Autochthonous Model Gene Expression Database Enables Cross-Study Comparisons of the Transcriptomic Landscapes Across Mouse Models
Authors: Ling Cai, Fangjiang Wu, Qinbo Zhou, Ying Gao, Bo Yao, Ralph J. DeBerardinis, George K. Acquaah-Mensah, Vassilis Aidinis, Jennifer E. Beane, Shyam Biswal, Ting Chen, Carla P. Concepcion-Crisol, Barbara M. Grüner, Deshui Jia, Robert A. Jones, Jonathan M. Kurie, Min Gyu Lee, Per Lindahl, Yonathan Lissanu, Corina Lorz, David MacPherson, Rosanna Martinelli, Pawel K. Mazur, Sarah A. Mazzilli, Shinji Mii, Herwig P. Moll, Roger A. Moorehead, Edward E. Morrisey, Sheng Rong Ng, Matthew G. Oser, Arun R. Pandiri, Charles A. Powell, Giorgio Ramadori, Mirentxu Santos, Eric L. Snyder, Rocio Sotillo, Kang-Yi Su, Tetsuro Taki, Kekoa Taparra, Phuoc T. Tran, Yifeng Xia, J. Edward van Veen, Monte M. Winslow, Guanghua Xiao, Charles M. Rudin, Trudy G. Oliver, Yang Xie, John D. Minna
Journal: Cancer Research (2025)

Abstract Lung cancer, the leading cause of cancer mortality, exhibits diverse histologic subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. In this study, we established the Lung Cancer Autochthonous Model Gene Expression Database (LCAMGDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMM), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCAMGDB aligned 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in the GEMMs. To accompany this resource, a web application was developed that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCAMGDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance. Significance: The Lung Cancer Autochthonous Model Gene Expression Database (LCAMGDB) provides a comprehensive and accessible resource for the research community to investigate lung cancer biology in mouse models.
Cancer-Associated Cachexia: Bridging Clinical Findings with Mechanistic Insights in Human Studies
Authors: Kexin Koh, Rachel Scott, Elizabeth M. Cespedes Feliciano, Tobias Janowitz, Marcus D. Goncalves, Eileen P. White, Barry J.A. Laird, Kerstin Haase, Mariam Jamal-Hanjani
Journal: Cancer Discovery (2025)

Abstract Cancer-associated cachexia (CAC) is a chronic wasting disease typically associated with advanced cancer, resulting in progressive and debilitating loss of function and poor tolerance to anticancer therapy. Preclinical animal models have identified various potential mechanisms and mediators, which have had limited translational success in clinical trials. This review focuses on human studies and discusses the clinical phenotyping of CAC using imaging-derived body composition, quality-of-life and functional measures, existing evidence for mediators, current therapeutic options, and future directions to advance the field. Identifying mechanisms driving CAC and targeting them are expected to improve the quality of life, treatment efficacy, and survival. Significance: CAC represents a significant clinical unmet need. Despite its high prevalence and associated mortality and morbidity, there are currently no globally approved effective therapies. This review provides a comprehensive overview of human studies aimed at defining CAC clinically and identifying mediators underlying it that are revealing effective health interventions. Furthermore, we highlight ongoing international efforts to advance our understanding of CAC.
Guidelines on the selection of patients with lung cancer for surgery
Authors: None British Thoracic Society
Journal: Thorax (2001)

Age 1. Perioperative morbidity increases with advancing age.Elderly patients undergoing lung resection are more likely to require intensive perioperative support.Preoperatively, a careful assessment of co-morbidity needs to be made.[B] 2. Surgery for clinically stage I and II disease can be as eVective in patients over 70 years as in younger patients.Such patients should be considered for surgical treatment regardless of age.[B] 3. Age over 80 alone is not a contraindication to lobectomy or wedge resection for clinically stage I disease.[B] 4. Pneumonectomy is associated with a higher mortality risk in the elderly.Age should be a factor in deciding suitability for pneumonectomy.[B] 90 BTS/SCTS www.thoraxjnl.com
A Phase <scp>II</scp> Trial of Geriatric Assessment‐Guided Selection of Treatment Intensity in Older Adults With <scp>AML</scp>
Authors: Vijaya R. Bhatt, Christopher S. Wichman, Thuy T. Koll, Alfred L. Fisher, Tanya M. Wildes, Michael Haddadin, Ann M. Berger, James O. Armitage, Sarah A. Holstein, Lori J. Maness, Krishna Gundabolu
Journal: American Journal of Hematology (2025)

ABSTRACT How to select the appropriate intensity of chemotherapy in older adults with acute myeloid leukemia (AML) remains an unanswered question. In a phase II trial of older adults ≥ 60 years with AML ( n = 73), we used geriatric assessment (measures of comorbidity burden, physical and cognitive function) to determine fitness for intensive chemotherapy. We integrated the geriatric assessment and genetic test results to personalize the selection of chemotherapy intensity with a goal to reduce early mortality (NCT03226418). Broad eligibility criteria allowed enrolling patients representative of those treated in real‐world practices: 45% of patients were ≥ 70 years, 57% had ≥ 2 comorbidities, 27% had a history of solid malignancies, and 74% had impairments in ≥ 2 geriatric assessment domains used to assign treatment intensity. Thirty‐two percent of patients resided in rural areas, and 45% were comanaged with community oncologists. The median time from enrollment to therapy initiation was 1 day (range 0–13). Eight patients (11%) received intensive chemotherapy; others received low‐intensity chemotherapy. Mortality at 30 days from diagnosis was 6.8% (95% confidence interval, CI 3.0%–15.1%) and at 90 days was 21.9% (95% CI 14.0%–32.7%). One‐year survival was 45.9% (95% CI 35.6%–59.3%). Our study demonstrates that pre‐treatment geriatric assessment in older adults with AML is feasible, can identify several functional impairments, and guide the selection of treatment intensity. A randomized trial is necessary to confirm the survival benefit of this approach over the traditional approach of treatment selection. Trial Registration: NCT03226418