Reevaluation of the Role of ERK3 in Perinatal Survival and Post-Natal Growth Using New Genetically-Engineered Mouse Models
Bibliographic record
Abstract
Abstract The physiological functions of the atypical MAP kinase ERK3 remain poorly characterized. Previous analysis of mice with a targeted insertion of the lacZ reporter in the Mapk6 locus ( Mapk6 lacZ ) showed that inactivation of ERK3 in Mapk6 lacZ mice leads to perinatal lethality associated with intrauterine growth restriction, defective lung maturation, and neuromuscular anomalies. To further explore the role of ERK3 in physiology and disease, we generated novel mouse models expressing a catalytically-inactive ( Mapk6 KD ) or conditional ( Mapk6 Δ ) allele of ERK3. Surprisingly, we found that mice devoid of ERK3 kinase activity or expression survive the perinatal period without any observable lung or neuromuscular phenotype. ERK3 mutant mice reached adulthood, were fertile and showed no apparent health problem. However, analysis of growth curves revealed that ERK3 kinase activity is ncessary for optimal post-natal growth. To gain insight into the genetic basis underlying the discrepancy in phenotypes of different Mapk6 mutant mouse models, we analyzed the regulation of genes flanking the Mapk6 locus by quantitative PCR. We found that expression of several Mapk6 neighboring genes is deregulated in Mapk6 lacZ mice, but not in Mapk6 KD or Mapk6 Δ mutant mice. Our genetic analysis suggests that off-target effects of the targeting construct on local gene expression are likely to be responsible for the perinatal lethality phenotype of Mapk6 lacZ mutant 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".