Comprehensive gene expression analysis in gallbladder mucosal epithelial cells of dogs with gallbladder mucocele
Bibliographic record
Abstract
BACKGROUND: Gallbladder mucocele (GBM) is a common disease in the canine gallbladder. Although the pathogenesis of GBM remains unclear, we recently reported that the excessive accumulation of mucin in the gallbladder is not a result of overproduction by gallbladder epithelial cells (GBECs). HYPOTHESIS/OBJECTIVES: Changes in the function of GBECs other than the production of mucin are associated with the pathogenesis of GBM. We performed an RNA sequencing (RNA-seq) analysis to comprehensively search for abnormalities in gene expression profiles of GBECs in dogs with GBM. ANIMALS: Fifteen dogs with GBM and 8 dogs euthanized for reasons other than gallbladder disease were included. METHODS: The GBECs were isolated from gallbladder tissues to extract RNA. The RNA-seq analysis was performed using the samples from 3 GBM cases and 3 dogs with normal gallbladders, and the gene expression profiles were compared between the 2 groups. Differences in mRNA expression levels of the extracted differentially expressed genes (DEGs) were validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) using samples of 15 GBM cases and 8 dogs with normal gallbladders. RESULTS: Comparison of gene expression profiles by RNA-seq extracted 367 DEGs, including ANO1, a chloride channel associated with changes in mucin morphology, and HTR4, which regulates the function of chloride channels. The ANO1 and HTR4 genes were confirmed to be downregulated in the GBM group by RT-qPCR. CONCLUSIONS AND CLINICAL IMPORTANCE: Our results suggest that GBM may be associated with decreased function of chloride channels expressed in GBECs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".