Properties of single FDB fibers following a collagenase digestion for studying contractility, fatigue, and pCa-sarcomere shortening relationship
Bibliographic record
Abstract
The objective of this study was to optimize the approach to obtain viable single flexor digitorum brevis (FDB) fibers following a collagenase digestion. A first aim was to determine the culture medium conditions for the collagenase digestion. The MEM yielded better fibers in terms of morphology and contractility than the DMEM. The addition of FBS to culture media was crucial to prevent fiber supercontraction. The addition of FBS to the physiological solution used during an experiment was also beneficial, especially during fatigue. Optimum FBS concentration in MEM was 10% (vol/vol), and for the physiological solution, it ranged between 0.2 and 1.0%. A second aim was to document the stability of single FDB fibers. If tested the day of the preparation, most fibers (∼80%) had stable contractions for up to 3 h, normal stimulus duration strength to elicit contractions, and normal and stable resting membrane potential during prolonged microelectrode penetration. A third aim was to document their fatigue kinetics. Major differences in fatigue resistance were observed between fibers as expected from the FDB fiber-type composition. All sarcoplasmic [Ca(2+)] and sarcomere length parameters returned to their prefatigue levels after a short recovery. The pCa-sarcomere shortening relationship of unfatigued fibers is very similar to the pCa-force curve reported in other studies. The pCa-sarcomere shortening from fatigue data is complicated by large decreases in sarcomere length between contractions. It is concluded that isolation of single fibers by a collagenase digestion is a viable preparation to study contractility and fatigue kinetics.
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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) | 0.001 | 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".