Latrunculin B increases force fluctuation-induced relengthening of ACh-contracted, isotonically shortened canine tracheal smooth muscle
Bibliographic record
Abstract
We hypothesized that differences in actin filament length could influence force fluctuation-induced relengthening (FFIR) of contracted airway smooth muscle and tested this hypothesis as follows. One-hundred micromolar ACh-stimulated canine tracheal smooth muscle (TSM) strips set at optimal reference length (Lref) were allowed to shorten against 32% maximal isometric force (Fmax) steady preload, after which force oscillations of +/-16% Fmax were superimposed. Strips relengthened during force oscillations. We measured hysteresivity and calculated FFIR as the difference between muscle length before and after 20-min imposed force oscillations. Strips were relaxed by ACh removal and treated for 1 h with 30 nM latrunculin B (sequesters G-actin and promotes depolymerization) or 500 nM jasplakinolide (stabilizes actin filaments and opposes depolymerization). A second isotonic contraction protocol was then performed; FFIR and hysteresivity were again measured. Latrunculin B increased FFIR by 92.2 +/- 27.6% Lref and hysteresivity by 31.8 +/- 13.5% vs. pretreatment values. In contrast, jasplakinolide had little influence on relengthening by itself; neither FFIR nor hysteresivity was significantly affected. However, when jasplakinolide-treated tissues were then incubated with latrunculin B in the continued presence of jasplakinolide for 1 more h and a third contraction protocol performed, latrunculin B no longer substantially enhanced TSM relengthening. In TSM treated with latrunculin B + jasplakinolide, FFIR increased by only 3.03 +/- 5.2% Lref and hysteresivity by 4.14 +/- 4.9% compared with its first (pre-jasplakinolide or latrunculin B) value. These results suggest that actin filament length, in part, determines the relengthening of contracted airway smooth muscle.
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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".