Changes in Twitch Morphometry of Gastrocnemius Muscle in the SOD1 G93A Mouse Model (P5.098)
Bibliographic record
Abstract
Objective: The objective of this study was to develop a framework to characterize twitch dynamics in mouse ALS muscle. Background: Motor neuron loss in brain and spinal cord in amyotrophic lateral sclerosis (ALS) causes a decrease in muscle strength. The contractile properties of muscle, as measured by isometric twitch force, can help provide insights into the mechanistic changes in muscle that occur in ALS. Methods: In situ isometric twitch experiments were performed on the gastrocnemius of early (13 to 14 weeks, n=9), moderate (15 to 16 weeks, n=11) and advanced (17 to 18 weeks, n=8) mice (B6SJL-Tg(SOD1-G93A)1Gur/J). Maximal twitch force at optimal current and muscle length was measured using a lever system (305C, Aurora Scientific, Aurora, Canada) interfaced to an acquisition system (National Instruments, Texas, USA). A custom program (National Instruments) controlled the lever arm movement and the output of a biphasic pulses current (200 us duration) muscle stimulator (701, Aurora Scientific). Comparisons were performed with 1-way ANOVA (with post-hoc Tukey-Kramer). Results: There was a decline in maximal isometric twitch force and maximum rates of contraction and decline (p<0.001). The half-relaxation time showed a trend toward increase between the mild and moderate groups (p=0.08), which was supported by an increase in the twitch horizontal symmetry (p<0.05); the latter measured as the ratio between twitch contraction and relaxation areas. Conclusions: We found distinctive differences between twitch descriptors in ALS isometric twitches in mild, moderate and severe mice, consistent with the progression of the disease.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".