A phenotypic and molecular characterization of the <i>fmr1‐tm1Cgr</i> Fragile X mouse
Bibliographic record
Abstract
Fragile X Syndrome is the most common form of inherited mental retardation. It is also known for having a substantial behavioral morbidity, including autistic features. In humans, Fragile X Syndrome is almost always caused by inactivation of the X-linked FMR1 gene. A single knockout mouse model, fmr1-tm1Cgr, exists. In this report we further characterize the cognitive and behavioral phenotype of the fmr1-tm1Cgr Fragile X mouse through the use of F1 hybrid mice derived from two inbred strains (FVB/NJ and C57BL/6J). Use of F1 hybrids allows focus on the effects of the fmr1-tm1Cgr allele with reduced influence from recessive alleles present in the parental inbred strains. We find that the cognitive phenotype of fmr1-tm1Cgr mice, including measures of working memory and learning set formation that are known to be seriously impacted in humans with Fragile X Syndrome, are essentially normal. Further testing of inbred strains supports this conclusion. Thus, any fmr1-tm1Cgr cognitive deficit is surprisingly mild or absent. There is, however, clear support presented for a robust audiogenic seizure phenotype in all strains tested, as well as increased entries into the center of an open field. Finally, a molecular examination of the fmr1-tm1Cgr mouse shows that, contrary to common belief, it is not a molecular null. Implications of this finding for interpretation of the phenotype are discussed.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".