The regulation of muscle mass by endogenous glucocorticoids
Bibliographic record
Abstract
Glucocorticoids are highly conserved fundamental regulators of energy homeostasis. In response to stress in the form of perceived danger or acute inflammation, glucocorticoids are released from the adrenal gland, rapidly mobilizing energy from carbohydrate, fat and protein stores. In the case of inflammation, mobilized protein is critical for the rapid synthesis of acute phase reactants and an efficient immune response to infection. While adaptive in response to infection, chronic mobilization can lead to a profound depletion of energy stores. Skeletal muscle represents the major body store of protein, and can become substantially atrophied under conditions of chronic inflammation. Glucocorticoids elicit the atrophy of muscle by increasing the rate of protein degradation by the ubiquitin-proteasome system and autophagy lysosome system. Protein synthesis is also suppressed at the level of translational initiation, preventing the production of new myofibrillar protein. Glucocorticoids also antagonize the action of anabolic regulators such as insulin further exacerbating the loss of protein and muscle mass. The loss of muscle mass in the context of chronic disease is a key feature of cachexia and contributes substantially to morbidity and mortality. A growing body of evidence demonstrates that glucocorticoid signaling is a common mediator of wasting, irrespective of the underlying initiator or disease state. This review will highlight fundamental mechanisms of glucocorticoid signaling and detail the mechanisms of glucocorticoid-induced muscle atrophy. Additionally, the evidence for glucocorticoids as a driver of muscle wasting in numerous disease states will be discussed. Given the burden of wasting diseases and the nodal nature of glucocorticoid signaling, effective anti-glucocorticoid therapy would be a valuable clinical tool. Therefore, the progress and potential pitfalls in the development of glucocorticoid antagonists for muscle wasting will be discussed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".