Evaluation of optimal biopsy location for assessment of histological activity, transcriptomic and immunohistochemical analyses in patients with active Crohn’s disease
Bibliographic record
Abstract
BACKGROUND: The appropriate location for biopsy procurement relative to an ulcer in active Crohn's disease is unknown. AIM: To explore the relationship between biopsy location, histological disease activity, proinflammatory gene expression and the presence of inflammatory cells. METHODS: Fifty-one patients with Crohn's disease and ulcers >0.5 cm diameter in the colon and/or ileum were prospectively enrolled at three centres. Biopsies were obtained from 0 mm, 7 to 8 mm and 21 to 24 mm from the edge of the largest ulcer. Histological activity was blindly assessed with the Global Histological Disease Activity Score, the Robarts Histopathology and Nancy Histological indices. Messenger ribonucleic acid (mRNA) levels for interleukins-6, -8 and -23 (p19 and p40 subunits), CD31 and S100A9 were measured using quantitative polymerase chain reaction. The number of CD3+, CD68+ and myeloperoxidase-positive cells was quantified by immunohistochemistry. Data were analysed using mixed models with location and segment as fixed effects and patients as random effect to account for correlation among segments within a patient. RESULTS: Histological disease activity scores (P < 0.0001), proinflammatory gene expression levels (P < 0.005) and numbers of myeloperoxidase-positive cells (P < 0.0001) were highest in biopsies from the ulcer edge in the colon and ileum, with decreasing gradients observed with distance from the edge (P < 0.05). No differences between colonic and ileal samples were detected for the parameters measured at any location. CONCLUSIONS: Biopsies from the ulcer edge in patients with Crohn's disease yielded the greatest histological disease activity and mRNA levels and had similar readouts in the colon and ileum. Research is needed to confirm this conclusion for other measures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".