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Combining transcriptomics, single-cell data, and a combination of 113-combination machine learning framework, as well as experimental verification, identified the key genes related to lactylation modifications in ulcerative colitis
Springer Science and Business Media LLC

Cure8 research brief

Combining transcriptomics, single-cell data, and a combination of 113-combination machine learning framework, as well as experimental verification, identified the key genes related to lactylation modifications in ulcerative colitis

2 min read

Why This Matters

This study uses transcriptomics, single‑cell data, and machine learning to nominate lactylation‑related genes as biomarkers and drug targets in ulcerative colitis, which could guide future biomarker or drug‑repurposing research relevant to UC patients.

Who Should Pay Attention

Researchers, translational scientists, clinicians following UC biomarker research

Study Snapshot

Story typeResearch paper
Evidence typeResearch paper
Source depthJournal abstract

What To Know

This preprint-style research report used bulk transcriptomic data and single-cell RNA-seq plus machine-learning and molecular docking to nominate four lactylation‑related genes (CNN2, HSDL2, LDHB, S100A6) as potential biomarkers and therapeutic targets in ulcerative colitis.

The authors report immune‑cell differences between cases and controls, regulatory network analysis, and in silico drug predictions (valproic acid, isoproterenol, acetaminophen) with molecular docking. The study is presented as an abstract-level research post (Research Square) rather than a peer‑reviewed clinical paper.

Methods combine public gene expression (GSE75214), scRNA‑seq analysis, machine‑learning classifiers (glmBoost+LDA), enrichment and PPI analyses, immune‑infiltration estimates, and molecular docking; results are exploratory and hypothesis‑generating rather than evidence of clinical efficacy.

If you follow UC research, this flags lactylation and the four named genes for further study and potential biomarker development. It does not provide clinical recommendations or validated diagnostic tests.

Keep In Mind

Posted on Research Square (abstract-level); not peer reviewed. Results are exploratory and based largely on computational analyses and public datasets; clinical relevance remains unproven.

Source Details

Review the original publication for the complete reporting, methods, and context.

Read Original Source
Research paper Evidence type derived from source or registry metadata.
PublicationSpringer Science and Business Media LLC
AuthorsWenbin Zeng, Yanhua Mo, Hui Nong +4 more
Study typePosted Content
Indexed viaCrossref
Source typeResearch paper
PublishedOct 19, 2026, 12:00 AM
Content availableJournal abstract

This Cure8 brief is based on source text from the linked article. Cure8 is informational only and is not a substitute for professional medical advice, diagnosis, or treatment.

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