{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T12:47:46Z","timestamp":1785847666571,"version":"3.56.0"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T00:00:00Z","timestamp":1785369600000},"content-version":"vor","delay-in-days":29,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The accurate deconvolution of bulk transcriptomes typically confounds stable physical cell identities with dynamic physiological states, limiting our understanding of complex microenvironmental processes such as ovarian aging. To overcome this, we present DeepMCD, an end-to-end multi-task deep learning framework designed to simultaneously deconvolve cell-type proportions and programmed cell death (PCD) compositional fractions from standard bulk RNA-seq data. By mapping high-dimensional expression profiles into a shared, tokenized latent space, DeepMCD employs a Transformer-based cross-task attention mechanism to explicitly leverage cellular morphological context for calibrating PCD predictions. Concurrently, an adaptive uncertainty-weighting loss ensures balanced optimization, effectively mitigating negative transfer. Extensive benchmarking demonstrates that DeepMCD significantly outperforms state-of-the-art single-task algorithms. Through rigorous ablation and interpretability analyses, we computationally substantiate the biological premise that functional death states are heavily reliant on specific cell-type contexts. Applying DeepMCD to real-world mouse ovarian aging cohorts, we reconstructed a cell-type-specific PCD landscape, bypassing the need for costly single-cell sequencing. Specifically, we identified an age-associated increase in inflammatory and lytic death modalities, together with a strong association between macrophage enrichment and pyroptosis during ovarian aging. Crucially, the DeepMCD-derived PCD fractions exhibit profound divergent correlations with core ovarian fibrosis-related genes. These computationally extracted signatures may serve as cost-effective candidate digital biomarkers for evaluating ovarian fibrosis and reproductive senescence. Ultimately, DeepMCD provides a highly interpretable, robust, and scalable computational tool for bulk RNA-seq data decoding.<\/jats:p>","DOI":"10.1093\/bib\/bbag399","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T11:21:53Z","timestamp":1783336913000},"source":"Crossref","is-referenced-by-count":0,"title":["Cell type\u2013specific dissection of cell death programs during ovarian aging"],"prefix":"10.1093","volume":"27","author":[{"given":"Ruizhe","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Gynecology, The First Affiliated Hospital of China Medical University , No. 155 Nanjing North Street, Heping District, Shenyang 110001, Liaoning Province ,","place":["P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Cardiology, The First Affiliated Hospital of China Medical University , No. 155 Nanjing North Street, Heping District, Shenyang 110001, Liaoning Province ,","place":["P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4070-7345","authenticated-orcid":false,"given":"Sheng","family":"Li","sequence":"additional","affiliation":[{"name":"Zhongnan Hospital of Wuhan University , No. 169 Donghu Road, Wuchang District, Wuhan 430060, Hubei Province ,","place":["P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Operating Room, The First Affiliated Hospital of China Medical University , No. 155 Nanjing North Street, Heping District, Shenyang 110001, Liaoning Province ,","place":["P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Gynecology, The First Affiliated Hospital of China Medical University , No. 155 Nanjing North Street, Heping District, Shenyang 110001, Liaoning Province ,","place":["P.R. China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,7,30]]},"reference":[{"key":"2026080408270293500_ref1","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1210\/er.2009-0006","article-title":"Ovarian aging: mechanisms and clinical consequences","volume":"30","author":"Broekmans","year":"2009","journal-title":"Endocr Rev"},{"key":"2026080408270293500_ref2","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1016\/j.cell.2020.01.009","article-title":"Single-cell transcriptomic atlas of primate ovarian aging","volume":"180","author":"Wang","year":"2020","journal-title":"Cell"},{"key":"2026080408270293500_ref3","doi-asserted-by":"publisher","first-page":"1213","DOI":"10.1097\/GME.0000000000001424","article-title":"The menopause transition and Women\u2019s health at midlife: a progress report from the study of Women\u2019s health across the nation (SWAN)","volume":"26","author":"El 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