All-Trans Retinoic Acid Modulates TLR4/NF-<i>κ</i>B Signaling Pathway Targeting TNF-<i>α</i>and Nitric Oxide Synthase 2 Expression in Colonic Mucosa during Ulcerative Colitis and Colitis Associated Cancer
Bibliographic record
Abstract
Colitis associated cancer (CAC) is the colorectal cancer (CRC) subtype that is associated with bowel disease such as ulcerative colitis (UC). The data on role of NF- κ B signaling in development and progression of CAC were derived from preclinical studies, whereas data from human are rare. The aim of this work was to study the contribution of NF- κ B pathway during UC and CAC, as well as the immunomodulatory effect of all-trans retinoic acid (AtRA). We analyzed the expression of NOS2, TNF- α , TLR4, and NF- κ B, in colonic mucosa. We also studied NO/TNF- α modulation by LPS in colonic mucosa pretreated with AtRA. A marked increase in TLR4, NF- κ B, TNF- α , and NOS2 expression was reported in colonic mucosa. The relationship between LPS/TLR4 and TNF- α /NO production, as well as the role of NF- κ B signaling, was confirmed by ex vivo experiments and the role of LPS/TLR4 in NOS2/TNF- α induction through NF- κ B pathway was suggested. AtRA downregulates NOS2 and TNF- α expression. Collectively, our study indicates that AtRA modulates in situ LPS/TLR4/NF- κ B signaling pathway targeting NOS2 and TNF- α expression. Therefore, we suggest that AtRA has a potential value in new strategies to improve the current therapy, as well as in the clinical prevention of CAC development and progression.
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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 | 0.000 | 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 | 0.001 |
| 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".