ArticleBiochemical genetics2026
SLC6A14 as a Key Diagnostic Biomarker for Ulcerative Colitis: An Integrative Bioinformatics and Machine Learning Approach.
Article in Biochemical genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Emerging roles of SLC6A14 in digestive system diseases: from amino acid transport to therapeutic targeting.Molecular biology reports · 2026Review
- Machine learning-based identification of a metabolic cell death gene signature for assessing disease activity and immunological landscape in inflammatory bowel disease.Scientific reports · 2026Article
- Investigating the Therapeutic Mechanisms of Shen-Ling-Bai-Zhu-San in Type 2 Diabetes and Ulcerative Colitis Comorbidity: A Network Pharmacology and Molecular Simulation Approach.Pharmaceuticals (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by intestinal inflammation and autoimmune responses. This study aimed to identify diagnostic biomarkers for UC through bioinformatics analysis and machine learning, and to validate these findings through immunofluorescence staining of clinical samples. Differential expression analysis was conducted on expression profile datasets from 4 UC samples. Key biomarkers were selected using LASSO logistic regression, SVM-RFE, and Random Forest algorithms. The diagnostic performance of these biomarkers was evaluated using receiver operating characteristic (ROC) curves. Functional enrichment analysis assessed the biological functions of these biomarkers. The CIBERSORT algorithm was used to analyze immune cell infiltration. Regulatory networks for diagnostic markers were constructed. Additionally, immunofluorescence staining was performed on clinical samples to validate the expression levels of key biomarkers. Differential analysis identified 199 significantly differentially expressed genes. SLC6A14 was selected as a key diagnostic biomarker, demonstrating excellent diagnostic performance in training and validation sets (AUC values: 0.973, 0.984, and 0.970). Immune cell infiltration analysis revealed significant increases in Neutrophils and activated Mast cells in UC samples, whereas resting Mast cells were relatively downregulated. Furthermore, SLC6A14 showed strong correlations with various immune cells. The ceRNA network identified 22 lncRNAs and 10 miRNAs associated with SLC6A14. Immunofluorescence staining of clinical samples confirmed that SLC6A14 expression is significantly higher in UC patients compared to normal intestinal mucosa, and its expression increases with UC activity. SLC6A14 has been confirmed as a key diagnostic marker for UC, validated both through bioinformatics analysis and immunofluorescence staining of clinical samples. It maintains regulatory relationships with various non-coding RNAs and plays a significant role in the pathogenesis of UC through its interactions with immune cells.
Indexed as
Identifiers
39806040What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.