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http://dx.doi.org/10.1016/j.jad.2025.120278 | DOI Listing |
J Affect Disord
September 2025
Department of Intensive Care Unit, Tiantai People's Hospital of Zhejiang Province (Tiantai Branch of Zhejiang Provincial People's Hospital), Hangzhou Medical College, Tiantai, Taizhou, Zhejiang, China. Electronic address:
Mol Pharmacol
August 2025
Division of Preclinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland. Electronic address:
Although multiparameter cellular morphological profiling methods and three-dimensional (3D) biological model systems can potentially provide complex insights for pharmaceutical discovery campaigns, there have been relatively few reports combining these experimental approaches. In this study, we used the U87 glioblastoma cell line grown in a 3D spheroid format to validate a multiparameter cellular morphological profiling screening method. The steps of this approach include 3D spheroid treatment, cell staining, fully automated digital image acquisition, image segmentation, numerical feature extraction, and multiple machine learning approaches for cellular profiling.
View Article and Find Full Text PDFDeep learning models applied to digital histology can predict gene expression signatures (GES) and offer a low-cost, rapidly available alternative to molecular testing at the time of diagnosis. We optimized transformer-based models to infer GES results and applied this approach to pre-treatment H&E-stained biopsies from 1,940 breast cancer patients treated with neoadjuvant chemotherapy in clinical trial and real-world cohorts. The most predictive histology-derived GES for pathologic complete response (pCR) in the I-SPY2 trial was validated in four external cohorts: CALGB 40601, CALGB 40603, a trial of durvalumab plus CT, and standard-of-care CT-treated patients from the University of Chicago.
View Article and Find Full Text PDFBlood Cancer Discov
September 2025
Memorial Sloan Kettering Cancer Center, New York, NY, United States.
Genomic antigen loss is a recurring mechanism of resistance to chimeric antigen receptor T-cell (CAR-T) and T-cell engagers (TCE) in relapsed/refractory multiple myeloma (RRMM). Yet, it remains unclear whether these events are acquired under treatment or merely selected from pre-existing, undetectable clones. By leveraging chemotherapy mutational signatures as temporal barcodes within whole genome sequencing data, we could time genomic antigen escape in 4 out of 11 RRMM patients.
View Article and Find Full Text PDFJ Oral Microbiol
August 2025
Department of Periodontology, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Background: Behçet's Disease (BD), a complex autoinflammatory disorder, is increasingly linked to microbial dysbiosis, yet the specific microbial signatures and their functional consequences remain incompletely characterized. Elucidating these alterations is crucial for understanding BD pathogenesis.
Objective: To identify distinct microbial community structures and functional potentials in supragingival plaque microbiomes of BD patients versus healthy controls (HC) using high-resolution shotgun metagenomic sequencing.