Sema4D/CD100 Deficiency Leads to Superior Performance in Mouse Motor Behavior
Bibliographic record
Abstract
BACKGROUND: Sema4D/CD100 is a type of class 4 semaphorin, exhibiting crucial roles in growth cone guidance in developing neurons. Sema4D is widely expressed throughout the central nervous system in embryonic mouse brain, and is selectively localized to oligodendrocytes and myelin in the postnatal brain. However, direct evidence of the actual involvement of Sema4D in the neuronal network development crucial for neurobehavioral performance is still lacking. The present study therefore examined whether Sema4D deficiency leads to abnormal behavioral development. METHODS: Both wild-type and Sema4D-deficient mice were subjected to behavioral analyses including open-field, adhesive tape removal, rotarod tests and a water maze task. RESULTS: Open-field tests revealed increased locomotor activity in Sema4D-deficient mice with less percentage of time spent in the center of the field. In both the adhesive tape removal and rotarod tests, which examine motor coordination and balance, Sema4D-deficient mice showed significantly superior performance, suggesting facilitated motor behavior. Both Sema4D-deficient and wild-type mice successfully learnt the water maze task, locating a hidden escape platform, and also showed precise memory for the platform position in probe tests. However, the swimming speed of Sema4D-deficient mice was significantly faster than that of wild-type mice, providing further evidence of their accelerated motor behavior. CONCLUSION: Our mouse behavioral analyses revealed enhanced motor activity in Sema4D-deficient mice, suggesting the crucial involvement of Sema4D in the neurodevelopmental processes of the central structures mediating motor behavior in mice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".