Sexual Dimorphism in Balance and Coordination in p75NTRexonIII Knock-Out Mice
Bibliographic record
Abstract
The p75 neurotrophin receptor (p75NTR) is implicated in various biological functions during development and adulthood. Several animal models have been developed to identify the roles of p75NTR in vivo and in vitro. P75NTRExonIII knock-out mice are widely used to study the neurotrophin receptor and its signaling pathways. Similar to other models of p75NTR knock-out (p75NTRExon IV KO) or conditional knock-out (p75NTRfl/fl) mice, p75NTRExonIII knock-out mice present severe abnormalities in walking, gait, balance and strength. The present study identifies a sexual dimorphism in the p75NTRExonIII knock-out strain regarding balance and coordination. Using Kondziela’s inverted grid test, we observed that p75NTRExonIII knock-out males performed poorly at the task, whereas p75NTRExonIII knock-out females did not exhibit any defects. We also observed that female p75NTRExonIII knock-out mice performed significantly better than male p75NTRExonIII knock-out mice at the beam balance test. There were no differences in strength, skin innervation, or the number of ulcers on the toes between p75NTRExonIII knock-out males and females. The literature regarding the role of p75NTR in behavior is controversial; our results suggest that studies investigating the role of p75NTR in vivo using p75NTR knock-out mice should systematically report data from males and females.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".