A154 PROPERDIN DEFICIENCY DOES NOT IMPACT THE MOUSE RESPONSE TO DSS-INDUCED COLITIS DESPITE DIFFERENCES IN COLONIC MICROBIOME
Bibliographic record
Abstract
The role of complement in colitis is only beginning to be understood. We reported that properdin deficient mice (PKO) have increased susceptibility to infectious colitis and to piroxicam-provoked colitis when combined with IL-10 deficiency. Here we examined the PKO strain’s response to chemical colitis, including their colon microbiome. The aim was to determine whether properdin deficiency impacted the intestinal microbiome and response to DSS. Second generation offspring from PKO X C57BL/6 wildtype (WT) matings were used. Dextran sulfate sodium (DSS) was added to their water for 5 days, then groups of mice were killed either 1 (acute) or up to 5 days (recovery) later. The animals’ weights were recorded and stool collected and frozen. At necropsy their colons were extracted, measured, a scraping collected, and the remainder prepared for histology or cultured overnight for secreted mediators. DNA was isolated from stool and mucosal scrapes and the 16S rRNA gene was amplified and sequenced for microbiome analysis. All mice lost weight and became inflamed with no significant difference between strains in any measure of pathology or anaphylatoxin levels. This was despite a significant difference in the colon microbiome of healthy mice of the two strains, and the colitis resulting in significant changes in the microbiome of both strains. Interestingly, a greater change was detected in mucosal scrapes but not feces of WT compared to PKO mice. We conclude that properdin does not play a role in chemical-induced colitis despite the mice hosting a different microbiome. Moreover, our results underscore how models of colitis may have different mechanisms including the relationship between complement and the microbiome. Nova Scotia Health Research Foundation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".