Gender‐based differential infiltration of CRP from the blood into skeletal muscle
Bibliographic record
Abstract
We conducted 3 studies to profile C‐reactive protein (CRP), a marker of systemic inflammation, in serum and muscle (vastus lateralis) and its response to endurance exercise in men and women. In study 1, we found serum CRP to be 2.9 fold higher in sedentary lean women (mean ± SD; 1096 ± 1241 ng/mL) vs. men (382 ± 366 ng/mL) (P = 0.006), in contrast to muscle CRP which was 40% higher in men (0.83 ± 0.21 ng/mg protein) vs. women (0.61 ± 0.13 ng/mg protein) (P < 0.001). Sedentary obese women had 3.8 fold higher serum CRP (4147 ± 3452 ng/mL; P = 0.022) and 50% higher muscle CRP (0.88 ± 0.49 ng/mg protein; P = 0.031) vs. sedentary lean women (serum, 1096 ± 1241 mg/mL; muscle, 0.58 ± 0.14 ng/mg protein) in the follicular phase. Serum CRP corrected for protein concentration (6.9 ± 6.2 ng/mg protein) was 9.8 fold higher than muscle CRP (0.7 ± 0.2 ng/mg protein; P < 0.001): men had 7 fold higher (P < 0.001), whereas women had 26 fold higher (P = 0.002), CRP in serum vs muscle. However, serum and muscle CRP values did not correlate. In study 2, plasma CRP decreased by 53% in 8 men eight days following one bout of cycling for 90 min at 65% VO 2 max (344 ± 208ng/mL vs. 164 ± 50 ng/mL, P = 0.07). In study 3, plasma and muscle CRP concentrations were measured prior to and following 12 weeks of progressive endurance exercise training in lean and obese women. There were not significant differences in CRP. We conclude that ‐1‐ lean sedentary men have lower serum, but higher muscle, CRP vs. lean women and ‐2‐ obese women have higher serum and muscle CRP vs. lean women. The discrepancy in fold difference between serum and muscle CRP in men vs. women suggests gender‐based differential infiltration of CRP from the blood into the skeletal muscle. (Supported by CIHR and NSERC Canada)
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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 | 0.001 |
| 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".