Effects of stretch on work and efficiency of frog (<i>Rana pipiens</i>)muscle
Bibliographic record
Abstract
Applying a small stretch to active muscle immediately before shortening results in an increase in force and work done during subsequent shortening. The basis of the increase is not fully understood, having important implications for work and efficiency, and how they are influenced through stretch. We used the anterior tibialis muscle of leopard frogs (Rana pipiens complex) to measure the oxygen consumed and work done during shortening contractions that were immediately preceded by either a brief stretch (5% muscle length over 25 ms) or an isometric contraction (25 ms duration). Work done by the muscle while shortening following stretch was about 28% greater than work done following an isometric contraction (P<0.001). However the net work done during the entire contraction (i.e. accounting for the work required to stretch the muscle) was reduced by 13% if stretch preceded the shortening phase (P=0.003). The energy (oxygen) used during a stretch-shorten cycle was the same as for an isometric-shorten contraction (P=0.34). Likewise, the efficiency of net work (net work/energy used) was only marginally different between shortening contractions preceded by stretch or an isometric phase (P=0.07). Thus, under conditions that were intended to mimic what might occur during animal movement, a stretch that immediately preceded shortening enhanced work during shortening but did not impart a net mechanical or energetic benefit to the contraction. These observations could indicate that stretch simply extends compliant elements that recoil subsequently with some loss of mechanical energy in the process and/or that stretch results in an increase in the number of, and hence work done by, cross bridges during muscle shortening accompanied by a proportionate increase in energy consumed.
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 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".