THE SALIVARY TRIPEPTIDE ANALOGUE feG MAY AMELIORATE CAERULEIN-INDUCED ACUTE PANCREATITIS VIA DOWNREGULATION OF ICAM-1 EXPRESSION
Bibliographic record
Abstract
We have evidence that feG treatment ameliorates caerulein-induced acute pancreatitis (AP). One possible mechanism by which feG may achieve this is by modulating the expression of ICAM-1. ICAM-1 expression is upregulated in AP and is believed to be required for neutrophil infiltration into the pancreas. Aim: To determine whether administration of feG will alter AP-induced ICAM-1 expression. Methods: 8 groups of Swiss male mice were used (n = 4/group). AP was induced by 12 hourly i.p. injections of caerulein (50μg/kg). A single dose feG (100ug/kg) was administered at AP induction (prophylactic) or 2h post induction (therapeutic). Control groups (n = 4) received feG, a control peptide (100ug/kg) at 0 or 2h, saline injections or where untreated. Pancreata were harvested 13h post-AP induction, snap frozen in liquid nitrogen and subsequently RNA was extracted using a modification of the Trizol® method. The expression of ICAM-1 mRNA was quantified using real-time RT-PCR. 18S was used as a housekeeping gene for normalization of ICAM-1 expression. The Mann-Whitney test was used for statistical analysis. Results: ICAM-1 mRNA in the AP alone group was increased by 75% compared to the saline control group. Treatment of AP with prophylactic feG decreased the expression of ICAM-1 mRNA by 32% when compared to the AP alone group (P < 0.05). Therapeutic feG treatment did not alter the AP-induced increase in ICAM-1 mRNA expression. These data suggest that feG treatment at AP-induction, but not at 2 h, will decrease the expression of pancreatic ICAM-1 mRNA. Conclusion: feG treatment may ameliorate AP, at least in part, by reducing the AP-induced upregulation of pancreatic ICAM-1 mRNA. Salivary tripeptide analogues may offer a new therapeutic approach to AP treatment. (feG was kindly provided by Salpep Biotechnology Inc.).
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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".