Inflammatory cytokine TNF-α inhibits Na<sup>+</sup>–glutamine cotransport in intestinal epithelial cells
Bibliographic record
Abstract
Glutamine (Gln), a preferred fuel source for enterocytes, is critical for intestinal epithelial cell integrity and barrier function. Chronic enteritis inhibits apical Na(+)-Gln cotransport. It is not known whether inflammatory cytokines that are secreted during inflammation inhibit Na(+)-Gln cotransport. Thus, this study aimed to examine whether TNF-α would affect apical Na(+)-Gln cotransport in intestinal epithelial cells. In this study, the presence of Na(+)-Gln cotransport was established by measuring Gln uptake in 10 days postconfluent IEC-6 cells grown on transwell plates. Cation, amino acid specificity, and siRNA transfection studies established that Na(+)-Gln cotransport is mediated via B(0)AT1. Immunoblotting and immunofluorescence studies established the apical membrane localization of B(0)AT1 in IEC-6 cells. Tumour necrosis factor α (TNF-α) inhibited Na(+)-Gln cotransport in a concentration- and time-dependent manner with an inhibitory concentration of 1.53 nmol·L(-1). Quantitative real-time PCR and Western blot analyses indicated that TNF-α did not alter B(0)AT1-specific transcripts or protein expression level. Kinetic studies revealed that TNF-α inhibited Na(+)-Gln cotransport by reducing the affinity of the cotransporters for Gln, and this effect was antagonized by genistein. Thus, we conclude that the TNF-α inhibition of Na(+)-Gln cotransport occurs at the post-translational level, and that the IEC-6 cell line is an excellent system to study the role of cytokines in Na(+)-Gln cotransport.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".