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Shapira, E.

Publications and source records attributed to Shapira, E..

2 recordsLinked to original sources

RNA-sequencing of butyrate-treated human lymphoblastoid cell lines shows dysregulated genes of multiple disease-related pathways

Abstract Butyrate, a 4-carbon fatty acid produced from insoluble starch by the gut microbiome, plays key roles in mitochondrial respiration, activation of cell-surface G-protein-coupled receptors, and protein acetylation by inhibiting histone deacetylases (HDACs). Butyrate (as sodium salt) added to drinking water was shown to improve pathological symptoms in numerous model mouse disorders, including models for cancer metastasis, neuroinflammation, autism spectrum disorders, dementia, insulin resistance, and colorectal cancer. Over 5000 PubMed-listed studies feature butyrate in their title, yet its genome-wide transcriptomic effects have not been reported in human cell lines from multiple healthy donors. Here, we report the genome-wide transcriptomic effects of 1 mM sodium butyrate on human lymphoblastoid cell lines (LCLs) generated from blood samples of eight unrelated healthy donors. Paired bioinformatics analysis comparing the butyrate-treated LCLs to the same untreated cell line identified thousands of differentially expressed gene (DEG) transcripts with padj<0.05, of which over half were upregulated by butyrate. Pathway analysis showed that butyrate exposure of LCLs upregulated extracellular matrix, cell adhesion, junction organization, Wnt signaling, axonogenesis, and neurodevelopment pathways. Downregulated pathways included cell cycle, G2/M checkpoint, E2F/MYC targets, DNA replication and repair, mitotic spindle integrity, mTOR signaling, oxidative phosphorylation, unfolded-protein response, and translation/ribosome-related pathways. Our RNA-seq study, utilizing LCLs from healthy donors and paired bioinformatic analysis, opens venues for assessing butyrate effects on cellular pathways and potential therapeutics for cancer, metabolic, immune, and CNS-related disorders.

genomics↗

Dementia Language Models: a generalizable and controllable representation of cognitive impairment

We introduce Dementia Language Models (DLMs)--a generalizable and controllable representation of cognitive impairment through language--alongside an evaluation framework for establishing their validity and clinical grounding. DLMs created by large language models fine-tuned on a small clinical corpus successfully generated patient-like narratives across unseen tasks, received predicted MMSE scores in the impaired range, and produced narratives that neurologists identified with accuracy comparable to real transcripts. The models' internal representations themselves, as well as their non-linguistic decision-making, supported cognitive-state detection in unseen cohorts. The effect was controllable: moving from Healthy toward Dementia in weight space progressively worsened language and predicted MMSE scores while increasing dementia probability. DLMs could support clinician training, hypothesis generation, and scalable experimentation, reserving patient involvement for where it is truly needed.

neuroscience↗