INSL5 is a novel marker for human enteroendocrine cells of the large intestine and neuroendocrine tumours
Bibliographic record
Abstract
We report for the first time the distribution of human INSL5 and its cognate leucine rich G-protein coupled receptor RXFP4 in the large intestine and in neuroendocrine/carcinoid tissues. Immunoreactive INSL5 was uniquely expressed by enteroendocrine cells (EECs) located within the colonic mucosa, whereas colonocytes were immunopositive for RXFP4. INSL5+ and RXFP4+ cells were also detected in human neuroendocrine/carcinoid tissues. We employed a recently described Insl5 knockout mouse model and 2 mouse models of induced colitis to address the relevance of Insl5 in EEC development and in acute inflammation of the colon. We identified INSL5 as a specific marker for synaptophysin+ EECs in the mucosa of the normal human and mouse colon. Insl5 was not essential for the development of mouse synaptophysin+ EECs. The mouse models of chemically induced colitis (dextran sulfate sodium and dinitrobenzene-sulfonic acid) failed to show changes in the numbers of Insl5+ EECs at inflammatory sites during the acute phase of colitis. In conclusion, we showed that INSL5 is a novel marker of colorectal EECs and provide first evidence for the presence of a potentially autocrine/paracrine INSL5-RXFP4 signaling system in the normal human and mouse colon and in rare human neuroendocrine tumours.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".