Identification of Human microRNAs Regulating Skeletal Muscle Regeneration In Patients with Sustained Intensive Care Unit Acquired Weakness
Bibliographic record
Abstract
Intensive care unit acquired weakness (ICUAW) is a complication of critical illness characterized by skeletal muscle wasting and impaired contractile function. Dysregulated gene co-expression networks controlling muscle repair/regeneration are present in patients with persistent muscle wasting. MicroRNAs (miRs) regulate gene expression at the post-transcriptional level by affecting the translation/degradation of mRNAs. Thus, we sought to identify miRs regulating the failure of muscle regeneration in patients with sustained ICUAW. We performed an integrated miR/mRNA analysis of quadriceps biopsies from patients with early/sustained ICUAW to identify dysregulated expression of miRs and their gene targets that regulate skeletal muscle myogenesis. We found miRs-490-3p and -744-5p to negatively regulate proliferation and differentiation respectively in human skeletal muscle myoblasts in vitro. We identified genes with significant roles in skeletal muscle repair/regeneration as potential mediators of miR-490-3p’s anti-myogenic activity. In addition, we identified novel miRs-3175 and -4739 as potential regulators of myoblast proliferation/differentiation in vitro.
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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".