Sex dimorphism in the aged metabolic phenotype of smoothelin-like 1 (SMTNL1) deficient mice
Bibliographic record
Abstract
ABSTRACT Smoothelin-like 1 (SMTNL1) is expressed in smooth and skeletal muscle tissues as well as a variety of steroid hormone-sensitive tissues. SMTNL1 can play a sex-dependent regulatory role in skeletal muscle metabolism in mice. Previous studies have documented appreciable changes in muscle morphology and metabolic function of young male mice with genetic deletion of Smtnl1 . SMTNL1 can also impact the energy metabolism and insulin sensitivity of female mice during pregnancy. Therefore, we investigated the metabolic outcome of global SMTNL1 knockout (KO) in male and female mice with advancing age using a comprehensive lab animal monitoring system (CLAMS). With ageing, body weight gain was markedly higher with a concomitant increase in whole body adiposity as well as specific white adipose depots in the absence of SMTNL1. Moreover, this genotypic difference in whole body adiposity was greater in the female cohort. The deletion of SMTNL1 was also associated with delayed satiety in mice fed a high fat diet, which was more pronounced in the female mice. A significant genotypic difference was also revealed for the metabolic energy balance in 12 month old animals of both sexes. The KO animals were metabolically less efficient and displayed a preference for carbohydrate catabolism. However, reduced glucose tolerance was observed only in the female group with the deletion of SMTNL1. Taken together, the current findings establish a novel role for SMTNL1 in modulating adiposity and energy metabolism with ageing in a sex dimorphic way.
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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) | 0.004 | 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".