Inducible nitric oxide synthase (iNOS) in muscle wasting syndrome, sarcopenia, and cachexia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Muscle atrophy-also known as muscle wasting-is a debilitating syndrome that slowly develops with age (sarcopenia) or rapidly appears at the late stages of deadly diseases such as cancer, AIDS, and sepsis (cachexia). Despite the prevalence and the drastic detrimental effects of these two syndromes, there are currently no widely used, effective treatment options for those suffering from muscle wasting. In an attempt to identify potential therapeutic targets, the molecular mechanisms of sarcopenia and cachexia have begun to be elucidated. Growing evidence suggests that inflammatory cytokines may play an important role in the pathology of both syndromes. As one of the key cytokines involved in both sarcopenic and cachectic muscle wasting, tumor necrosis factor α (TNFα) and its downstream effectors provide an enticing target for pharmacological intervention. However, to date, no drugs targeting the TNFα signaling pathway have been successful as a remedial option for the treatment of muscle wasting. Thus, there is a need to identify new effectors in this important pathway that might prove to be more efficacious targets. Inducible nitric oxide synthase (iNOS) has recently been shown to be an important mediator of TNFα-induced cachectic muscle loss, and studies suggest that it may also play a role in sarcopenia. In addition, investigations into the mechanism of iNOS-mediated muscle loss have begun to reveal potential therapeutic strategies. In this review, we will highlight the potential for targeting the iNOS/NO pathway in the treatment of muscle loss and discuss its functional relevance in sarcopenia and cachexia.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it