Protective and Anti-Inflammatory Effects of Protegrin-1 on Citrobacter rodentium Intestinal Infection in Mice
Bibliographic record
Abstract
Infectious intestinal colitis, manifesting as intestinal inflammation, diarrhea, and epithelial barrier disruption, affects millions of humans worldwide and, without effective treatment, can result in death. In addition to this, the significant rise in antibiotic-resistant bacteria poses an urgent need for alternative anti-infection therapies for the treatment of intestinal disorders. Antimicrobial peptides (AMPs) are potential therapies that have broad-spectrum antimicrobial activity due to their (1) unique mode of action, (2) broad-spectrum antimicrobial activity, and (3) protective role in GI tract maintenance. Protegrin-1 (PG-1) is an AMP of pig origin that was previously shown to reduce the pathological effects of chemically induced digestive tract inflammation (colitis) and to modulate immune responses and tissue repair. This study aimed to extend these findings by investigating the protective effects of PG-1 on pathogen-induced colitis in an infection study over a 10-day experimental period. The oral administration of PG-1 reduced Citrobacter rodentium intestinal infection in mice as evidenced by reduced histopathologic change in the colon, prevention of body weight loss, milder clinical signs of disease, and more effective clearance of bacterial infection relative to challenged phosphate-buffered saline (PBS)-treated mice. Additionally, PG-1 treatment altered the expression of various inflammatory mediators during infection, which may act to resolve inflammation and re-establish intestinal homeostasis. PG-1 administered in its mature form was more effective relative to the pro-form (ProPG-1). To our knowledge, this is the first study demonstrating the protective effects of PG-1 on infectious colitis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".