Role of HRas and NRas in murine lung development and neonatal survival
Bibliographic record
Abstract
[ES]Las GTPasas Ras controlan rutas de señalización implicadas en proliferación, migración, muerte \ny supervivencia celular, Actúan como interruptores moleculares, alternando entre una \nconformación inactiva (unido a GDP) y activa (unido a GTP), estando este proceso altamente \nregulado por proteínas activadoras de la actividad GTPasa intrínseca de Ras (GAPs, reguladores \nnegativos), y factores de intercambio de nucleótidos de guanosina (GEFs, reguladores positivos). \nDe entre las más de 150 GTPasas conocidas, la subfamilia de GTPasas Ras canonicas está \nconstituida por HRas, NRas, y por las dos variantes Kras4A y Kras4B. A pesar de la gran \nhomología, no son funcionalmente redundantes. Solo la pérdida individual de Kras4B, o la \neliminación combinada de HRas y NRas junto con una haploinsuficiencia de Kras produce \nletalidad embrionaria. Sin embargo, hemos observado que la eliminación conjunta de HRas y \nNRas provocaba un aumento significativo de la letalidad perinatal, asociada con insuficiencia \nrespiratoria. En esta Tesis Doctoral se ha llevado a cabo un análisis detallado de los modelos \nmurinos knockouts (KO) para HRas y/o NRas con el fin de evaluar la especificidad o redundancia \nfuncional de las dos GTPasas canónicas durante el desarrollo embrionario del pulmón
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".