African African American and Native American nurses in Appalachia 1900-1965
Bibliographic record
Abstract
Increased serial sarcomere number (SSN) has been observed in rats following downhill running training due to the emphasis on active lengthening contractions; however, little is known about the influence on dynamic contractile function. Therefore, we employed 4 weeks of weighted downhill running training in rats, then assessed soleus SSN and work loop performance. We hypothesised trained rats would produce greater net work output during work loops due to a greater SSN. Thirty-one Sprague-Dawley rats were assigned to a training or sedentary control group. Weight was added during downhill running via a custom-made vest, progressing from 5-15% body mass. Following sacrifice, the soleus was dissected, and a force-length relationship was constructed. Work loops (cyclic muscle length changes) were then performed about optimal muscle length (LO) at 1.5-3-Hz cycle frequencies and 1-7-mm length changes. Muscles were then fixed in formalin at LO. Fascicle lengths and sarcomere lengths were measured to calculate SSN. Intramuscular collagen content and crosslinking were quantified via a hydroxyproline content and pepsin-solubility assay. Trained rats had longer fascicle lengths (+13%), greater SSN (+8%), and a less steep passive force-length curve than controls (P<0.05). There were no differences in collagen parameters (P>0.05). Net work output was greater (+78-209%) in trained than control rats for the 1.5-Hz work loops at 1 and 3-mm length changes (P<0.05), however, net work output was more related to maximum specific force (R2=0.17-0.48, P<0.05) than SSN (R2=0.03-0.07, P=0.17-0.86). Therefore, contrary to our hypothesis, training-induced sarcomerogenesis likely contributed little to the improvements in work loop performance. This article has an associated First Person interview with the first author of the paper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".