Male‐specific colon motility dysfunction in the <i>TashT</i> mouse line
Bibliographic record
Abstract
BACKGROUND: In Hirschsprung disease (HSCR), the absence of myenteric neural ganglia in the distal bowel prevents motility and thereby causes functional intestinal obstruction. Although surgical resection of the aganglionic segment allows HSCR children to survive this condition, a number of patients still suffer from impaired motility despite having myenteric ganglia in their postoperative distal bowel. Such phenomenon is also observed in patients suffering from other enteric neuropathies and, in both cases, colonic dysmotility is believed to result from abnormalities of myenteric ganglia and/or associated interstitial cells of Cajal (ICC). To better understand this, we used a recently described HSCR mouse model called TashT. METHODS: Intestinal motility parameters were assessed and correlated with extent of aganglionosis and with neuronal density in ganglionated regions. The neural composition of the myenteric plexus and the status of ICC networks was also evaluated using immunofluorescence. KEY RESULTS: TashT(Tg/Tg) mice display a strong male bias in the severity of both colonic aganglionosis and hypoganglionosis, which are associated with male-specific reduced colonic motility. TashT(Tg/Tg) male mice also exhibit a specific increase in nNos(+) neurons that is restricted to the most distal ganglionated regions. In contrast, Calretinin(+) myenteric neurons, Sox10(+) myenteric glial cells, and cKit(+) ICC are not affected in TashT(Tg/Tg) mice. CONCLUSIONS AND INFERENCES: Male-specific impairment of colonic motility in TashT(Tg/Tg) mice is associated with both severe hypoganglionosis and myenteric neuronal imbalance. Considering these parameters in the clinic might be important for the management of postoperative HSCR patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".