Influence of 4 weeks of downhill running on calcium sensitivity of rat single muscle fibers
Bibliographic record
Abstract
Abstract Improved Ca2+ sensitivity has been suggested as a mechanism behind enhancements in muscle mechanical function following eccentric training. However, little is known regarding the effects of eccentric training on single muscle fiber Ca2+ sensitivity. Adult male Sprague–Dawley rats (sacrificial age ~18 weeks; mass = 400.1 ± 34.8 g) were assigned to an eccentric training (n = 5) or sedentary control group (n = 6). Eccentric training consisted of 4 weeks of weighted downhill running 3×/week at a 15° decline and 16 m/min for 35 min per day in 5‐min bouts. After sacrifice, vastus intermedius single muscle fibers were dissected, chemically permeabilized, and stored until testing. Fibers (n = 63) were isolated, and standard Ca2+ sensitivity, force, rate of force redevelopment (ktr), and active instantaneous stiffness tests were performed using [Ca2+] ranging from 7.0 to 4.5. Following all mechanical testing, fiber type was determined using SDS‐PAGE. There was no difference in pCa50 (i.e., [Ca2+] needed to elicit half of maximal force) between groups or between fiber types. However, when comparing normalized force across pCa values, fibers from the control group produced greater forces than fibers from the trained group at lower Ca2+ concentrations (p < 0.05), and this was most evident for Type I fibers (p = 0.002). Type II fibers produced faster (p < 0.001) ktr than Type I fibers, but there were no differences in absolute force, normalized force, or other measures of mechanical function between fibers from the trained and control groups. These findings indicate that eccentric training does not appear to improve single muscle fiber Ca2+ sensitivity.
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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) | 0.001 | 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 | 0.001 |
| 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".