A potential role for mTORC1/2 in β2 adrenergic regulation of skeletal muscle glucose oxidation in models of intrauterine growth restriction.
Bibliographic record
Abstract
The epidemic of intrauterine growth restriction (IUGR) continues to be a leading cause of perinatal morbidity and mortality throughout the world. This condition has been linked to the development of metabolic health problems such as obesity, hypertension, glucose intolerance, and type 2 diabetes at all ages. Previous studies have demonstrated that IUGR fetal adaptations impair proper glucose homeostasis in part via changes in insulin responsiveness in key tissues including skeletal muscle and liver, and that these deficits persists into adulthood. Many components of insulin signaling pathways associated with glucose metabolic regulation have been evaluated in IUGR tissues for adaptive changes. Among these are mammalian target of rapamycin complexes 1 and 2 (mTORC1/2) and their associated pathways, which function in mitochondrial control and maintenance. However, recent findings demonstrate that β2 adrenoceptors (β2AR) appear to activate an insulin-independent pathway or pathways that modify glucose metabolism via mTORC1/2 complexes. These findings represent a novel potential target for interventions that could improve the treatment and prevention of IUGR-induced metabolic disorders. This review will focus on mechanistic components of β2AR-mTORC1/2 signaling as well as their role in regulating glucose oxidative metabolism within skeletal muscle.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".