Intricate mechanisms trigger scattered crypt IEC apoptosis mediated necrotizing enterocolitis pathogenesis in neonatal mice
Bibliographic record
Abstract
Abstract Necrotizing enterocolitis (NEC) is a life-threatening gastrointestinal inflammatory disorder among premature infants. Intestinal epithelial cell (IEC) apoptosis contributes to NEC pathogenesis. However, how scattered crypt IEC apoptosis leads to NEC with excessive epithelial necrosis in intestinal villi and mucosa inflammation remain unclear. We developed a novel triple-transgenic mouse model, namely, 3xTg-iAPcIEC (inducible apoptosis phenotype in crypt-IEC) using doxycycline (Dox)-inducible tetO-rtTA system and vil-cre technology, for inducing tissue-specific overexpression of Fasl in IECs. We found that scattered crypt IEC apoptosis caused intestinal crypt inflammation and villous necrosis resembling NEC in neonates. This pathological progression initiated a set of NEC-associated intricate cellular and molecular pathophysiological effect including increase in Rip3 and Ifng, infiltration of CD8+ T cells, and dysbiosis with Gram-positive bacteria. Mechanistically, scattered crypt IEC apoptosis-induced IFN-γ and RIP3 activation were noted to mediate both intestinal crypt inflammation and mucosal villous necrosis, whereas CD8+ T cells and dysbiosis with Gram-positive bacteria contribute to mucosal villous necrosis. Notably, we observed that blocking any of these events protects NEC development in 3xTg-iAPcIEC mouse pups, underlining their central roles in the NEC pathogenesis. Our findings may advance knowledge in preventing or treating this devastating disorder in humans.
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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) | 0.000 | 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 | 0.002 |
| 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".