Developmental Coordination Disorder: What Can We Learn From Recombinant Inbred Mice Using Motor Learning Tasks and Quantitative Trait Locus Analysis
Bibliographic record
Abstract
Abstract Developmental Coordination Disorder (DCD) is a motor skills disorder that affects 5-6% of all school-aged children. There is an indication that DCD has an underlying genetic component due to its high heritability. Therefore, we we have explored the use of a recombinant inbred family of mice known as the BXD panel to understand the genetic basis of complex traits (i.e., motor learning) through identification of Quantitative Trait Loci (QTLs). The overall aim of this study was to utilize the QTL approach to evaluate the genome-to-phenome correlation in BXD strains of mice in order to to better understanding the human presentation of DCD. Results in this current study indicate there is a spectrum of motor learning in the pre-selected BXD strains of mice with a spectrum between high and low learning capabilities. Five lines – BXD15, BXD27, BXD28, BXD75, and BXD86 – exhibited the most DCD-like phenotype, when compared to other BXD lines of interest. The results indicate that BXD15 and BXD75 struggled primarily with gross motor skills, BXD28 primarily had difficulties with fine motor skills, and BXD27 and BXD28 lines struggled with both fine and gross motor skills. The functional roles of significant QTL genes were assessed in relation to DCD-like behavior. Only Rab3a (Ras-related protein Rab-3A) emerged as a best candidate gene for the horizontal ladder rung task. This gene is found to be associated with brain and skeletal muscle development. This is the first study to specifically examine the genetic linkage of DCD using BXD lines of 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".