One Universal Common Endpoint in Mouse Models of Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
There is no consensus among research laboratories around the world on the criteria that define endpoint in studies involving rodent models of amyotrophic lateral sclerosis (ALS). Data from 4 nutrition intervention studies using 162 G93A mice, a model of ALS, were analyzed to determine if differences exist between the following endpoint criteria: CS 4 (functional paralysis of both hindlimbs), CS 4+ (CS 4 in addition to the earliest age of body weight loss, body condition deterioration or righting reflex), and CS 5 (CS 4 plus righting reflex >20 s). The age (d; mean ± SD) at which mice reached endpoint was recorded as the unit of measurement. Mice reached CS 4 at 123.9±10.3 d, CS 4+ at 126.6±9.8 d and CS 5 at 127.6±9.8 d, all significantly different from each other (P<0.001). There was a significant positive correlation between CS 4 and CS 5 (r = 0.95, P<0.001), CS 4 and CS 4+ (r = 0.96, P<0.001), and CS 4+ and CS 5 (r = 0.98, P<0.001), with the Bland-Altman plot showing an acceptable bias between all endpoints. Logrank tests showed that mice reached CS 4 24% and 34% faster than CS 4+ (P = 0.046) and CS 5 (P = 0.006), respectively. Adopting CS 4 as endpoint would spare a mouse an average of 4 days (P<0.001) from further neuromuscular disability and poor quality of life compared to CS 5. Alternatively, CS 5 provides information regarding proprioception and severe motor neuron death, both could be important parameters in establishing the efficacy of specific treatments. Converging ethics and discovery, would adopting CS 4 as endpoint compromise the acquisition of insight about the effects of interventions in animal models of ALS?
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".