SPRED1 in quadriceps of patients with mild chronic obstructive pulmonary disease (1102.21)
Bibliographic record
Abstract
Limb muscle dysfunction contributes to exercise intolerance in chronic obstructive pulmonary disease (COPD). In turn, quadriceps capillarization is a determinant of muscle function. In our previous study, the number of capillaries and mRNA level of VEGFA were both reduced in mild COPD. MicroRNAs (miRs) regulate biological processes such as angiogenesis. Based on the literature, angiogenesis can be regulated by miR‐126 which blocked the expression of an inhibitor of angiogenesis, SPRED1. In this study, we assessed the expression of miR‐126 in the context of capillarization characterization in muscle tissue obtained from a needle biopsy in 5 patients with mild COPD and 5 healthy age‐matched controls. We hypothesized that miR‐126 will be downregulated and SPRED1 will be enhanced in COPD. Vastus lateralis muscle samples were analyzed for miRs and mRNA content by qPCR and the number of capillaries was obtained by immunochemistry. Levels of miR‐126 were similar between mild COPD and healthy controls. SPRED1 level was enhanced by 2.1 fold (p=0.01) and the number of capillaries tended to be reduced in mild COPD compared to healthy controls. SPRED1 may have a role in limb muscle capillarization in mild COPD. Investigations targeting specifically endothelial cells will better dissect the biochemical process involved in muscle angiogenesis in the context of COPD. Grant Funding Source : CHIR/IRSC
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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) | 0.002 | 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".