Phenotyping of Nod1/2 double deficient mice and characterization of Nod1/2 in systemic inflammation and associated renal disease
Bibliographic record
Abstract
It is indispensable to thoroughly characterize each animal model in order to distinguish between primary and secondary effects of genetic changes. The present study analyzed Nod1 and Nod2 double deficient (Nod1/2 DKO) mice under physiological and inflammatory conditions. Nod1 and Nod2 are members of the Nucleotide-binding domain and Leucine-rich repeat containing Receptor (NLR) family. Several inflammatory disorders, such as Crohn's disease and asthma, are linked to genetic changes in either Nod1 or Nod2. These associations suggest that Nod1 and Nod2 play important roles in regulating the immune system.Three-month-old wildtype (Wt) and Nod1/2 DKO mice were sacrificed, body and organ weight were determined, and blood was drawn. Except for lower liver weight in Nod1/2 DKO mice, no differences were found in body/organ weight between both strains. Leukocyte count and composition was comparable. No significant changes in analyzed plasma biochemical markers were found. Additionally, intestinal and vascular permeability was determined. Nod1/2 DKO mice show increased susceptibility for intestinal permeability while vascular permeability was not affected. Next we induced septic shock and organ damage by administering LPS+PGN intraperitoneally to Wt and Nod1/2 DKO mice and sacrificed animals after 2 and 24 hours. The systemic inflammatory and metabolic response was comparable between both strains. However, renal response was different as indicated by partly preserved kidney function and tubular epithelial cell damage in Nod1/2 DKO at 24 hours. Remarkably, renal inflammatory mediators Tnfα, KC and Il-10 were significantly increased in Nod1/2 DKO compared with Wt mice at 2 hours.Systematic analysis of Nod1/2 DKO mice revealed a possible role of Nod1/2 in the development of renal disease during systemic inflammation.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".