Caspase-12 inhibits obesity and insulin resistance (P4057)
Bibliographic record
Abstract
Abstract Our lab has previously identified CASPASE-12 as an inhibitor of the inflammasome, a multiprotein complex composed of a NLR, CASPASE-1, and potentially other adaptor proteins. The inflammasome has recently been identified as having a crucial role in the development of obesity and type 2 diabetes and we hypothesized that Caspase-12 may also play a role. Mice lacking Caspase-12 develop spontaneous obesity and insulin resistance. On a high fat diet (HFD), the mice develop a more severe phenotype, having increased liver triglycerides and metabolic defects including reduced respiration and activity. The adipose tissue of the Caspase-12-/- mice had increased macrophage infiltration and increased Caspase-1 processing and activation. Analysis of insulin signalling indicated that the Caspase-12-/- mice had increased insulin resistance in adipose, liver, and muscle tissue. The majority of the human population has a truncated and inactive CASPASE-12, however a proportion of people of African descent have a T125C SNP that restores the protein. To determine if Caspase-12 also had a protective effect in humans, we sequenced patients of the Dallas Heart Study for the T125C SNP. Preliminary analysis revealed a possible protective effect of a full length CASPASE-12 with respect to plasma triglycerides, however the effect was restricted to African American individuals without diabetes. No associations with body-mass index, diabetes prevalence, of fasting glucose levels were observed.
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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) | 0.000 | 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) | 0.004 | 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".