Neurotensin receptor 1 overexpression in inflammatory bowel diseases and colitis-associated neoplasia
Bibliographic record
Abstract
AIM: To explore the association of neurotensin receptor 1 (NTSR1) with inflammatory bowel diseases (IBD) and colitis-associated neoplasia. METHODS: NTSR1 was detected by immunohistochemistry in clinical samples of colonic mucosa with IBD colitis, colitis-associated raised low-grade dysplasia (LGD) including dysplasia-associated lesions or masses (DALMs, n = 18) and adenoma-like dysplastic polyps (ALDPs, n = 4), colitis-associated high-grade dysplasia (HGD, n = 11) and colitis-associated colorectal carcinoma (CACRC, n = 13), sporadic colorectal adenomatous polyp (SAP, n = 17), and sporadic colorectal carcinoma (SCRC, n = 12). The immunoreactivity of NTSR1 was semiquantitated (as negative, 1+, 2+, and 3+) and compared among different conditions. RESULTS: NTSR1 was not detected in normal mucosa but was expressed similarly in both active and inactive colitis. LGD showed a significantly stronger expression as compared with non-dysplastic colitic mucosa, with significantly more cases showing > 2+ intensity (68.75% in LGD vs 32.26% in nondysplastic mucosa, P = 0.001). However, no significant difference existed between DALMs and ALDPs. CACRC and HGD showed a further stronger expression, with significantly more cases showing 3+ intensity than that in LGD (61.54% vs 12.50% for CACRC vs LGD, P = 0.022; 58.33% vs 12.50% for CACRC/HGD vs LGD, P = 0.015). No significant difference existed between colitis-associated and non-colitic sporadic neoplasia. CONCLUSION: NTSR1 in colonic epithelial cells is overexpressed in IBD, in a stepwise fashion with sequential progress from inflammation to dysplasia and carcinoma.
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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) | 0.001 | 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".