tbuckley/cabot-search huggingface dataset:
National trends in oncology specialists’ EHR inbox work, 2019–2022
Authors: A Jay Holmgren, Nate C Apathy, Jennie Crews, Tait Shanafelt
Journal: JNCI Journal of the National Cancer Institute (2025)

Electronic health record (EHR) burden is an important driver of the ongoing physician burnout crisis. EHR-based messaging (also known as inbox) in particular, including messages from patients, is associated with burnout and decreased well-being. Little is known regarding EHR messaging burden for oncologists. To address this, we assessed trends in oncologist EHR messaging volume and EHR time from 2019-2022 across oncology sub-specialties. This study used EHR metadata for all US oncology physicians (including medical oncologist/hematologists, radiation oncologists, pediatric oncologists, gynecologic oncologists, and surgical oncologists) providing ambulatory care using an Epic EHR to measure inbox volume and EHR time from July 2019 through April 2022. Descriptive statistics and multi-variable regression were used to evaluate differences over time and across sub-specialties. This sample of 15,653 oncology physicians across 43,228,633 ambulatory visits found that message volume for oncologists increased 19.0% from 2019 to 2022, and patient-initiated messages increased 34.0%. EHR time increased 16.2% from 2019 to 2022, while EHR "work outside of work" time increased 12.1%. Medical oncologist/hematologists had the highest inbox volume, patient-message volume, and EHR time of oncology sub-specialists. Rising levels of EHR work and message volume among oncology physicians are concerning given the role of EHR burden in physician burnout. Oncologists have seen increased EHR time and message volume, especially patient-initiated messages, following the onset of the COVID pandemic. Health system leaders and policymakers should invest in efforts to reduce EHR and inbox burden for all oncologists, with a focus on those with the greatest burden.
Use of the Connor-Davidson Resilience Scale in a Complex Medical Dermatology Clinic: Cross-sectional study evaluating associations between resilience, Health-related Quality of Life and Mental Health
Authors: Caroline J Stone, Eliza Broadbent, Vikram N Sahni, Laurel Gray, Jennie T Clarke, Christopher B Hansen, Jamie L W Rhoads, John J Zone, Christopher M Hull, Yelena P Wu, Jacob Kean, Aaron M Secrest, Zachary H Hopkins
Journal: Journal of the American Academy of Dermatology (2025)
Targeting the PDK/PDH axis modulates neutrophil and smooth muscle cell pathological responses and prevents abdominal aortic aneurysm formation
Authors: S Griepke, A Grentzmann, G L Tripodi, J Hansen, M P Fonseca, M D Nilsson, Y Tallouzi, E Grupe, P S Jensen, H C Beck, G Temprano-Sagrera, M Sabater-Lleal, M Burton, M Dembic, M Thomassen, M J Forteza, M G Terp, J S Lindholt, L M Rasmussen, L B Steffensen, J Stubbe, D F J Ketelhuth
Journal: Cardiovascular Research (2025)

Abdominal aortic aneurysm (AAA) is a life-threatening condition where inflammation plays a key role. Currently, AAA treatment relies exclusively on surgical interventions, and no guideline drug therapy to prevent aneurysm growth or rupture is available. Pharmacological reprogramming of immune cell metabolism, through the modulation of the pyruvate dehydrogenase kinase/pyruvate dehydrogenase (PDK/PDH) axis, has been identified as an attractive strategy to combat inflammation. Here we aimed, for the first time, to investigate the role of the PDK/PDH axis in AAA and its potential as a therapeutic target. Analysis of three separate transcriptome datasets revealed that the expression of PDK isoenzymes is skewed in human AAA. Thus, human AAA homogenates showed increased levels of phosphorylated PDH-Ser293 and lactate compared to controls, confirming a metabolic deviation. In mice subjected to porcine pancreatic elastase (PPE)-induced AAA, treatment with dichloroacetate (DCA), a pan inhibitor of PDK isoenzymes, prevented aortic dilation, reducing the increase in inner aortic diameter by approximately 58% compared to controls. Further analysis showed that DCA treatment upregulated contractile VSMC-related genes and downregulated neutrophil-related genes in the mice. In line with the previous, PDK-inhibition prevented elastin breakdown, preserved aortic alpha-smooth muscle actin and collagen expression, and decreased neutrophil infiltration and neutrophil extracellular traps (NET) release. Thus, treating VSMC with DCA or PDK1-siRNA revealed that the PDK/PDH axis regulates their dedifferentiation, influencing contractile gene expression and proliferation. Moreover, we found that DCA-induced PDK inhibition inhibited neutrophil NET release in vivo and in vitro. We show that the PDK/PDH axis is skewed in human AAA. Through the inhibition of PDK, in vitro and in vivo, we demonstrated that the PDK/PDH axis is a key regulator of vascular- and neutrophil-associated pathological responses with AAA formation. Our study pinpoints immunometabolic reprogramming using PDK inhibitors as an attractive strategy to fight AAA disease.
Identification of Lesion Bioactivity in Hepatic Cystic Echinococcosis Using a Transformer-Based Fusion Model
Authors: Zhanjin Wang, Fuyuan Li, Junjie Cai, Zhangtuo Xue, Kaihao Dua, Yongping Tao, Hanxi Zhang, Ying Zhou, Haining Fan, Zhan Wang
Journal: Journal of Infection (2025)

Differentiating whether hepatic cystic echinococcosis (HCE) lesions exhibit biological activity is essential for developing effective treatment plans. This study evaluates the performance of a Transformer-based fusion model in predicting HCE lesion activity. This study analyzed CT images and clinical variables from 700 HCE patients across three hospitals from 2018 to 2023. Univariate and multivariate logistic regression analyses were conducted for the selection of clinical variables to construct a clinical model. Radiomic features were extracted from CT images using Pyradiomics to develop a radiomics model. Additionally, a 2D deep learning model and a 3D deep learning model were trained using the CT images. The fusion model was constructed using feature-level fusion, decision-level fusion, and a Transformer network architecture, allowing for the analysis of the discriminative ability and correlation among radiomic features, 2D deep learning features, and 3D deep learning features, while comparing the classification performance of the three multimodal fusion models. In comparison to radiomic and 2D deep learning features, the 3D deep learning features exhibited superior discriminative ability in identifying the biological activity of HCE lesions. The Transformer-based fusion model demonstrated the highest performance in both the test set and the external validation set, achieving AUC values of 0.997 (0.992-1.000) and 0.944 (0.911-0.977), respectively, thereby outperforming both the feature-level and decision-level fusion models, and enabling precise differentiation of HCE lesion biological activity. The Transformer multimodal fusion model integrates clinical features, radiomic features, and both 2D and 3D deep learning features, facilitating accurate differentiation of the biological activity of HCE lesions and exhibiting significant potential for clinical application.
Evidence for intermittent coupling of intramyocardial small, engineered heart tissues acutely implanted into rabbit myocardium
Authors: E Huethorst, M J Bishop, F L Burton, C Denning, N Gadegaard, R C Myles, G L Smith
Journal: Cardiovascular Research (2025)

Electrical integration of human iPSC-derived cardiomyocyte (hiPSC-CM)-based tissue with the host myocardium is a requirement of successful regeneration therapy. This study was designed to identify electrical coupling in the acute phase (1-2h) post-grafting using an ex vivo model. Small, engineered heart tissues (mini-EHTs) consisting of ∼50,000 hiPSC-CMs on a hydrogel (spontaneous rate 0.34±0.05 Hz), were loaded with Cal520-AM. EHTs were implanted sub-epicardially into a Langendorff-perfused rabbit heart after blebbistatin treatment. For up to 100 mins, a continuous pseudo-ECG was recorded during sinus rhythm (rate 2.0-3.5 Hz). At 25 min intervals, EHT calcium transients (CaTs) were recorded for 10-20 s (No Contraction group). To study the influence of mechanical activity, blebbistatin was washed off after implantation (Contraction Recovery group).Periodic entrainment of EHTs with the myocardium was detected less often (p=0.011) in the No Contraction group (1/9 hearts) than in the Contraction Recovery group (5/6 hearts). The average coupling delay (QRS-CaT) and the difference in consecutive delays (Δdelay) were 89±50 ms and 10±3 ms respectively (n=12 traces; N=6 hearts). Coupling ratios (QRS:CaT) varied from 2:1 to 4:1. These coupling parameters were not significantly different in the two experimental groups. Modelling of hiPSC-CM tissue separated by a 25 μm saline gap from the myocardium demonstrated field-effect coupling with similarly variable activation delays. Importantly, coupling failed with a gap of 100 μm. In conclusion, EHT entrainment is possible immediately after grafting and has features compatible with field-effect coupling. Sensitivity to the gap dimensions may explain why entrainment is more common in actively contracting myocardium.
Tirzepatide alleviates doxorubicin-induced cardiotoxicity via inhibiting HRD1-mediated Nrf2 ubiquitination
Authors: Dan Yang, Yang-Hao Chen, Yan-Kun Chen, Ya-Lin Zeng, Zhi-Yu Ling
Journal: Cardiovascular Research (2025)

Doxorubicin (DOX), an effective and commonly used chemotherapeutic agent, often triggers dosage-dependent and potentially lethal cardiotoxicity, which heavily limits its clinical application in cancer survivors. However, no actual pharmacological therapeutics for this adverse effect are available. Tirzepatide (TZP), a novel GIP/GLP-1 receptor agonist, exhibits efficacy in controlling glycemia and has very recently been approved for the treatment of type 2 diabetes. Several clinical trials provided evidence that TZP treatment contributed to a substantial reduction in HbA1c levels, body weight, and cardiovascular risk factors through the involvement of biochemical and molecular mechanisms that needed to be deeply explored. Here, we aimed to investigate the role of TZP in DOX-induced cardiotoxicity and to clarify the underlying mechanisms. Male C57BL/6 mice were exposed to subcutaneous injections of TZP or an equal volume of vehicle once a day for 14 consecutive days. To generate DOX-induced cardiotoxicity, the mice received a single intraperitoneal injection of DOX (15 mg/kg). In vitro studies were performed on the H9c2 cell line in exposure to DOX alone or combined with TZP incubation. Echocardiographic measurement, histological assessment, and molecular analysis were obtained to determine the impact of TZP treatment on cardiotoxicity induced by DOX insult. To explore the underlying mechanisms, we performed RNA-sequencing of murine heart tissue to screen for the potential targets. Moreover, Ad-Hrd1 and siNrf2 were utilized to further confirm the involvement of HRD1 and Nrf2 in this process. Mice with TZP administration were protected from myocardial injury, cardiac dysfunction, and fatality in response to DOX. A significant reduction in both oxidative stress and cardiomyocyte apoptosis induced by DOX injection was also observed in the presence of TZP. Consistently, results obtained from in vitro studies revealed that DOX challenge impaired cell viability and led to elevated oxidative damage and cellular apoptosis, which were significantly alleviated in TZP-treated H9c2 cells. Mechanistically, we provided direct evidence that the cardioprotective effect of TZP was mediated by the transcription factor Nrf2 in an HRD1-dependent manner. Upon DOX treatment, TZP incubation could prevent ER stress-induced HRD1 upregulation in cardiomyocytes and subsequently decrease the ubiquitylation and degradation of Nrf2, thus enhancing its protein expression level, nuclear translocation, and transcription activity, ultimately contributing to the decreased oxidative stress and cardiomyocyte apoptosis. Our study suggested that TZP attenuated oxidative stress and cardiomyocyte apoptosis by modulating HRD1-mediated Nrf2 expression and activity, thereby protecting against the cardiotoxic effects exerted by DOX. These results supported that TZP might be a promising therapeutic option for reducing chemotherapy-related cardiotoxicity.
Safety of combined long-acting injectable cabotegravir and long-acting injectable rilpivirine in virologically suppressed adolescents with HIV (IMPAACT 2017/MOCHA): a phase 1/2, multicentre, open-label, non-comparative, dose-finding study
Authors: Carolyn Bolton Moore, Kristin Baltrusaitis, Brookie M Best, John H Moye, Ellen Townley, Avy Violari, Barbara Heckman, Sarah Buisson, Rodica M Van Solingen-Ristea, Edmund V Capparelli, Mark A Marzinke, Elizabeth D Lowenthal, Shawn Ward, Chelsea Krotje, Ryan Milligan, Allison L Agwu, Jenny Huang, S Y Amy Cheung, Cynthia McCoig, Dwight E Yin, Gilly Roberts, Herta Crauwels, Veerle Van Eygen, Sara Zabih, Gaerolwe Masheto, Pradthana Ounchanum, Linda Aurpibul, Violet Korutaro, Aditya H Gaur
Journal: The Lancet HIV (2025)
LigExtract: Large-scale Automated Identification of Ligands from Protein Structures in the Protein Data Bank
Authors: Natália Aniceto, Nuno Martinho, Ismael Rufino, Rita C Guedes
Journal: Genomics Proteomics & Bioinformatics (2025)

The Protein Data Bank is an ever-growing database of 3D macromolecular structures that has become a crucial resource for the drug discovery process. Exploring complexed proteins and accessing the ligands in these proteins is paramount to help researchers understand biological processes and design new compounds of pharmaceutical interest. However, currently available tools to perform large-scale ligand identification do not address many of the more complex ways in which ligands are stored and represented in PDB structures. Therefore, a new tool called LigExtract was specifically developed for the large-scale processing of PDB structures and the identification of their ligands. This is a fully open-source tool available to the scientific community, designed to provide end-to-end processing whereby the user simply provides a list of UniProt IDs and LigExtract returns a list of ligands, their individual PDB files, a PDB file of the protein chains engaged with the ligand and a series of log files that inform the user of the decisions made during the ligand extraction process as well as potential flagging of additional scenarios that might have to be considered during any follow-up use of the processed files (e.g., ligands covalently bound to the protein). LigExtract is available, open-source, on GitHub (https://github.com/comp-medchem/LigExtract).
First-line treatment patterns and overall survival in patients diagnosed with metastatic Merkel cell carcinoma in England from 2013 to 2020: results of a nationwide observational cohort study
Authors: Seyed Hamidreza Mahmoudpour, Craig Knott, Jenny Nobes, Mairead Kearney, Emmanuelle Boutmy, Patrice Verpillat, Zoe C Venables
Journal: British Journal of Dermatology (2025)

This retrospective study examined real-world treatment patterns and outcomes in patients diagnosed with metastatic Merkel cell carcinoma (MCC) in England from 2013 to 2020. Among 667 patients identified, only 30% received systemic anticancer treatment, of whom 39% received first-line avelumab. Longer median overall survival (OS) was observed in patients treated with first-line avelumab vs other first-line treatments, including patients with stage III MCC (37.8 vs 13.0 months) or stage IV MCC (19.9 vs 7.2 months).
Preclinical <i>in vitro</i> and <i>in vivo</i> evidence for CD74-targeting as effective treatment strategy for cutaneous T cell lymphomas
Authors: Mariantonia Costanza, Catello Giordano, Ann-Christin von Brünneck, Jing Zhao, Ahmad Makky, Katharina Vinh, Ivonne Aidee Montes-Mojarro, Florian Reisinger, Stephan Forchhammer, Agnieszka Witalisz-Siepracka, Sophie Edtmayer, Dagmar Stoiber, Gang Yin, David Horst, Anja Fischer, Reiner Siebert, Jan P Nicolay, Menghong Yin, Martin Janz, Falko Fend, Jürgen C Becker, Christian M Schürch, Lukas Kenner, Chalid Assaf, Olaf Merkel, Stephan Mathas
Journal: British Journal of Dermatology (2025)

Prognosis and quality of life of advanced cutaneous T cell lymphoma (CTCL) patients, in particular those with Sézary syndrome (SS) and advanced-stage mycosis fungoides (MF), are poor. Monoclonal antibodies or antibody-drug conjugates (ADCs) have been implemented into CTCL therapy algorithms, but the spectrum of antibody-targetable cell-surface antigens on T cell non-Hodgkin lymphomas (T-NHL) is limited. To evaluate expression of the MHC-II chaperone CD74 across common subtypes of CTCL by various methods, and to explore the efficacy of CD74-targeting of CTCL cells by anti-CD74 antibody-drug conjugate (ADC) in vitro and in vivo. We comprehensively investigate expression of CD74 in well-defined CTCL cell lines by PCR analyses, immunoblotting and flow cytometry. More than 140 primary CTCL samples of all common entities are analyzed by immunohistochemistry, flow cytometry, immunofluorescence and 'co-detection by indexing' (CODEX) multiplexed tissue imaging as well as single-cell RNAseq analyses. DNA methylation of CTCL cell lines is interrogated by generation of genome-wide methylation profiling. The effect of a maytansinoid-conjugated humanized ADC against CD74 is investigated on CTCL cell lines in vitro, alone or in combination with gemcitabine, and in vivo after xenotransplantation of CTCL cell lines in NOD-scid Il2rgnull (NSG) mice. We demonstrate by different experimental approaches in CTCL cell lines and a broad collection of primary CTCL samples that CD74 is widely and robustly expressed in CTCL cells. Additionally, CD74 expression in SS and MF is confirmed by analyses of single cell (sc)RNA-seq data, and correlates in CTCL cell lines with CD74 gene DNA hypomethylation. CD74 is rapidly internalized in CTCL cells, and CD74 targeting by the ADC STRO-001 efficiently kills CTCL-derived cell lines. Finally, CD74 targeting synergizes with conventional chemotherapy in vitro, and eradicates murine xenotransplants of CTCL cell lines in vivo. CD74 is expressed across common CTCL subtypes, and CD74-targeting efficiently kills CTCL cells in vitro and in vivo. Our data thus identify CD74-targeting as highly promising treatment strategy for CTCL.
PIVKA-II as a Biomarker in Pseudoxanthoma Elasticum-like Disorder with Multiple Coagulation Factor Deficiency: Implications for Vitamin K Therapy
Authors: Suzuka Miyamoto, Satoru Shinkuma, Koji Yada, Kengo Hamada, Kohei Ogawa, Keiji Nogami, Hideo Asada
Journal: British Journal of Dermatology (2025)

This manuscript presents a detailed case study of familial instances of Pseudoxanthoma Elasticum (PXE)-like syndrome, focusing on the elevation of vitamin K absence or antagonist-II (PIVKA-II) as a potential biomarker. Our findings suggest that PIVKA-II may serve as a sensitive marker for the pathophysiology of PXE-like syndrome, and we propose that vitamin K supplementation could be beneficial in managing this disorder.
Evaluative Methodology for HRD Testing: Development of Standard Tools for Consistency Assessment
Authors: Zheng Jia, Yaqing Liu, Shoufang Qu, Wenbin Li, Lin Gao, Lin Dong, Yun Xing, Yadi Cheng, Huan Fang, Yuting Yi, Yuxing Chu, Chao Zhang, Yanming Xie, Chunli Wang, Zhe Li, Zhihong Zhang, Zhipeng Xu, Yang Wang, Wenxin Zhang, Xiaoping Gu, Shuang Yang, Jinghua Li, Liangshen Wei, Yuanting Zheng, Guohui Ding, Leming Shi, Xin Yi, Jianming Ying, Jie Huang
Journal: Genomics Proteomics & Bioinformatics (2025)

Homologous recombination deficiency (HRD) has emerged as a critical prognostic and predictive biomarker in oncology. However, current testing methods, especially those reliant on targeted panels, are plagued by inconsistent results from the same samples. This highlights the urgent need for standardized benchmarks to evaluate HRD assay performance. In phases IIa and IIb of the Chinese HRD Harmonization Project, we developed ten pairs of well-characterized DNA reference materials derived from lung, breast, and melanoma cancer cell lines and their matched normal cell lines, each paired with seven cancer-to-normal mass ratios. Reference datasets for allele-specific copy number variations (ASCNVs) and HRD scores were established and validated based on three sequencing methods and nine analytical pipelines. The Genomic Instability Scores (GIS) of the reference materials ranged from 11 to 96, enabling validation across various thresholds. The ASCNV reference datasets covered a genomic span of 2340 to 2749 Mb, equivalent to 81.2% to 95.4% of the autosomes in the 37d5 reference genome. These benchmarks were subsequently utilized to assess the accuracy and reproducibility of four HRD panel assays, revealing significant variability in both ASCNV detection and HRD scores. The concordance between panel-detected GIS and reference GIS ranged from 0.81 to 0.94, and only two assays exhibited high overall agreement with Myriad MyChoice CDx for HRD classification. This study also identified specific challenges in ASCNV detection in HRD-related regions and the profound impact of high ploidy on consistency. The established HRD reference materials and datasets provide a robust toolkit for objective evaluation of HRD testing.
Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis
Authors: Junwei Liu, Xiaoping Cen, Chenxin Yi, Feng-ao Wang, Junxiang Ding, Jinyu Cheng, Qinhua Wu, Baowen Gai, Yiwen Zhou, Ruikun He, Feng Gao, Yixue Li
Journal: Genomics Proteomics & Bioinformatics (2025)

The rapid development of biological and medical examination methods has vastly expanded personal biomedical information, including molecular, cellular, image, and electronic health record datasets. Integrating this wealth of information enables precise disease diagnosis, biomarker identification, and treatment design in clinical settings. Artificial intelligence (AI) techniques, particularly deep learning models, have been extensively employed in biomedical applications, demonstrating increased precision, efficiency, and generalization. The success of the large language and vision models further significantly extends their biomedical applications. However, challenges remain in learning these multimodal biomedical datasets, such as data privacy, fusion, and model interpretation. In this review, we provided a comprehensive overview of various biomedical data modalities, multi-modal representation learning methods, and the applications of AI in biomedical data integrative analysis. Additionally, we discussed the challenges in applying these deep learning methods and how to better integrate them into biomedical scenarios. We then proposed future directions for adapting deep learning methods with model pre-training and knowledge integration to advance biomedical research and benefit their clinical applications.
Hyalohyphomycosis caused by Antifungal-resistance <i>Scopulariopsis brevicaulis</i> in a patient with <i>CARD9</i> deficiency
Authors: Yanyang Guo, Tianshuo Zhao, Chunying Xiao, Dong Yan, Luming Hai, Yubo Ma, Meng Fu
Journal: British Journal of Dermatology (2025)

We report the first case of hyalohyphomycosis caused by S. brevicaulis in a patient with CARD9 mutations, and we establish a novel link between CARD9 deficiency and Scopulariopsis susceptibility.