Adiponectin is Expressed in Skeletal Muscle and Influences Muscle Phenotype and Function
Bibliographic record
Abstract
Adiponectin (Ad) plays a vital role in various diseases and generally mediates anti‐diabetic and anti‐inflammatory effects. It was originally thought that Ad expression was limited to adipocytes, however, recent evidence has demonstrated its expression in other cells/tissues such as cardiac muscle. We present evidence that Ad is expressed in L6 myotubes and mouse soleus, as assessed by RT‐PCR and Western blot analysis. Furthermore, Ad was detected within the muscle fibers of wild‐type (WT) mouse tibialis anterior sections via IHC. Subsequently, we employed the Ad‐null (KO) mouse to determine the effect of Ad on muscle phenotype and function. Body mass increased significantly in KO mice (+5.5 ± 2.9% relative to WT) with no change in muscle mass. Epidydymal fat mass appeared to increase in KO mice (+35.1 ± 22.8%) vs. WT mice but was not statistically significant ( p =0.16). Intramuscular triglyceride content was significantly greater in KO mice (+75.1 ± 25.1%) than WT. Muscle fiber type composition did not change, though there was a trend for an increase in muscle fiber area in KO mice (type IIA +13.6 ± 3.2%, IIB +25.5 ± 5.7%, IID +12.3 ± 12.7%) vs. WT. Using in situ electrical muscle stimulation, peak tetanic force was lower in KO mice (−47.5 ± 6.0) than WT with no change in muscle fatigue rates. Future studies will assess if muscle‐derived and circulating Ad elicit differential effects on skeletal muscle phenotype and function.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".