Effect of high-fat diet on mechanosensitive transient receptor potential channel activation in vagal afferent neurons
Bibliographic record
Abstract
Mechanical stimulation of the gastrointestinal tract is an important stimulus of satiety and can be transduced by transient receptor potential (TRP) channels. Several studies have revealed attenuated vagally-mediated satiety responses including mechanosensitivity in diet-induced obesity; however, ion channels underlying this hyposensitivity have not been fully understood. This study aimed to examine the effect of chronic high-fat diet on activation of selected mechanosensitive TRP channels in vagal afferents. C57/BL6 mice were fed on either a high-fat or low-fat diet for 6–8 weeks. An increase in the intracellular calcium to hypotonic solution and activators of TRPV1, TRPV4, and TRPA1 was measured in nodose neurons using Ca2+-imaging techniques. Jejunal afferent nerve firing induced by mechanical stimulation and TRP channel agonists was measured using in vitro extracellular multiunit afferent recording. In high-fat diet–fed mice, we observed reduced calcium influx and jejunal afferent response induced by mechanical stimuli and agonists of TRPV4 and TRPA1, but not TRPV1. Our data show diet-induced obesity disrupts the activation of TRPV4 and TRPA1, at both the cellular level and the level of nerve terminals in the small intestine, which may partly explain reduced mechanosensitivity of vagal afferents and may contribute to decreased gut-brain satiety signaling in obesity.
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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) | 0.001 | 0.000 |
| 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) | 0.002 | 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".