Pannexin 3 deletion reduces fat accumulation and inflammation in a sex-specific manner
Bibliographic record
Abstract
Abstract Background Pannexin 3 (PANX3), is a channel-forming glycoprotein that enables nutrient-induced inflammation in vitro , and genetic linkage data suggests it regulates body mass index. Here, we characterized inflammatory and metabolic parameters in global Panx3 knockout (KO) mice in the context of forced treadmill running (FEX) and high fat diet (HFD). Methods C57BL/6N (WT) and KO mice were randomized to either a FEX running protocol or no running (SED) from 24 until 30 weeks of age. Body weight was measured biweekly, and body composition was measured at 24 and 30 weeks of age. Male WT and KO mice were fed a HFD from 12 – 28 weeks of age. Metabolic organs were analyzed for a panel of inflammatory markers and PANX3 expression. Results In females there were no significant differences in body composition between genotypes, which could be due to the lack of PANX3 expression in female white adipose tissue, while male KOs fed a chow diet had lower body weight, and lower fat mass at 24 and 30 weeks of age, which was reduced to the same extent as 6 weeks of FEX in WT mice. Additionally, male KO mice exhibited significantly lower expression of multiple pro-inflammatory genes in white adipose tissue compared to WT mice. While on a HFD body weight differences were insignificant, in KO mice, multiple inflammatory genes were significantly differently expressed in quadriceps muscle and white adipose tissue resulting in a more anti-inflammatory phenotype compared to WT mice. The lower fat mass in male KO mice may be due to significantly fewer adipocytes in their subcutaneous fat compared to WT mice. Mechanistically, adipose stromal cells (ASCs) cultured from KO mice grow significantly slower than WT ASCs. Conclusion PANX3 is expressed in male adult mouse adipose tissue and may regulate adipocyte numbers, influencing fat accumulation and 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 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".