Age- and speed-dependent modulation of gaits in DSCAM<sup>2J</sup>mutant mice
Bibliographic record
Abstract
Gaits depend on the interplay between distributed spinal neural networks, termed central pattern generators, generating rhythmic and coordinated movements, primary afferents, and descending supraspinal inputs. Recent studies demonstrated that the mouse displays a rich repertoire of gaits. Changes in gaits occur in mutant mice lacking particular neurons or molecular signaling pathways implicated in the normal establishment of these neural networks. Given the role of the Down syndrome cell adherence molecule (DSCAM) to the formation and maintenance of spinal interneuronal circuits and sensorimotor integration, we have investigated its functional contribution to gaits over a wide range of locomotor speeds using freely walking mice. We show in this study that the DSCAM 2J mutation, while not precluding any gait, impairs the age- and speed-dependent modulation of gaits. It impairs the ability of mice to maintain their locomotion at high treadmill speeds. DSCAM 2J mutation induces the dominance of lateral walk over trot and the emergence of aberrant gaits for mice, such as pace and diagonal walk. Gaits were also more labile in DSCAM 2J mutant mice, i.e., less stable, less attractive, and less predictable than in their wild-type littermates. Our results suggest that the DSCAM mutation affects the behavioral repertoire of gaits in an age- and speed-dependent manner. NEW & NOTEWORTHY Gaits evolve throughout development, up to adulthood, and according to the genetic background. Using mutant mice lacking DSCAM (a cell adherence molecule associated with Down syndrome), we show that the DSCAM 2J mutation alters the repertoire of gaits according to the mouse’s age and speed, and prevents fast gaits. Such an incapacity suggests a reorganization of spinal, propriospinal, and supraspinal neuronal circuits underlying locomotor control in DSCAM 2J mutant mice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".