Spontaneously developing chronic colitis in IL-10/iNOS double-deficient mice
Bibliographic record
Abstract
Mice deficient in both inducible nitric oxide synthase (iNOS) and interleukin (IL)-10 (iNOS(-/-)/IL-10(-/-)) were created to examine the role of iNOS in spontaneously developing intestinal inflammation. IL-10(-/-)/iNOS(-/-) mice were compared with IL-10(-/-) (iNOS(+/+)) littermates over 6 mo. RT-PCR, Western blot analysis, and immunohistochemistry were performed to measure iNOS message and protein levels. Plasma nitrate/nitrite (NO(x)) levels were assessed by HPLC. Damage scores (macroscopic and microscopic) and granulocyte infiltration were assessed. At 3-4 wk, IL-10(-/-) and IL-10(-/-)/iNOS(-/-) mice had no signs of colonic inflammation or granulocyte infiltration. Plasma NO(x) levels were not different from controls. By 3-4 mo, IL-10(-/-) mice had increased damage scores and granulocyte infiltration concurrent with increased mRNA and protein synthesis (restricted to the epithelium) for iNOS in intestinal tissues but not other tissues. Plasma NO(x) levels increased fivefold. Interestingly, in the absence of iNOS induction or increased plasma NO(x), iNOS(-/-)/IL-10(-/-) mice had damage and granulocyte infiltration equivalent to those observed in IL-10(-/-) littermates. These data suggest that iNOS does not impact on the development or severity of spontaneous chronic inflammation in IL-10-deficient mice.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".