Analysis of real-time serotonin (5-HT) availability during experimental colitis in mouse
Bibliographic record
Abstract
Serotonin (5-HT)-containing enterochromaffin (EC) cells of the intestine transduce chemical and mechanical stimuli from the intestinal lumen by releasing 5-HT on to afferent nerve terminals. Dysfunctional mucosal 5-HT signaling has been implicated in heightened visceral sensitivity and altered motility in patients with inflammatory bowel disease and in animal models. Our aim was to characterize the release and uptake of 5-HT in the mouse dextran sulfate sodium (DSS; 5% wt/vol) model of colitis. We made electrochemical recordings and used an ELISA assay to determine mucosal 5-HT release and uptake in untreated mice and mice with DSS-induced colitis. Peak and steady-state 5-HT concentrations were measured before and during blockade of the serotonin reuptake transporter (SERT) with 1 microM fluoxetine. Electrochemical recordings showed that colons from DSS-treated mice had roughly twice the steady-state levels of extracellular 5-HT and compression-evoked 5-HT release compared with untreated mice. Fluoxetine doubled the compression-evoked and steady-state 5-HT levels in control and DSS mice. These data were supported by ELISA assays, which showed enhanced 5-HT release during colitis, by immunohistochemical analyses, which showed increases in EC cell numbers, and by real-time PCR, which identified a decrease in SERT mRNA expression in the mucosa during colitis. These data are the first to demonstrate 5-HT release close to its release site and near its site of action during DSS-colitis. We conclude that DSS-colitis increases 5-HT availability primarily by an increase in the numbers of EC cells and/or of content of 5-HT in these EC cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".