Respiratory consequences of targeted losses of<i>Hoxa5</i>gene function in mice
Bibliographic record
Abstract
Fetal development of the respiratory tract and diaphragm requires strict coordination between genetically controlled signals and mechanical forces produced by the neural network that generates breathing. Being expressed in the mesenchyme of trachea, lung and diaphragm, and in phrenic motoneurons HOXA5 is a key transcription factor regulating lung development and function. Consequently, most Hoxa5−/− mutants die at birth from respiratory failure. However, the extensive effect of the null mutation makes it difficult to identify the origins of respiratory dysfunction in newborns. To address the physiological impact of Hoxa5 tissue-specific roles, we used conditional gene targeting with the Dermo1Cre and Olig2Cre mouse lines to produce specific Hoxa5 deletions in mesenchyme and motoneurons, respectively. Hoxa5 expression in mesenchyme is critical for trachea development, whereas its expression in phrenic motoneurons is essential for diaphragm formation. Breathing measurements in adult mice with whole body plethysmography demonstrated that at rest, only the motoneuron deletion affects respiration due to higher breathing frequency and decreased tidal volume. But subsequent exposure to a moderate hypoxic challenge (FiO2=0.12; 10 min) revealed that both mutant mice hyperventilate more than controls. Hoxa5flox/flox;Dermo1+/cre mice showed augmented tidal volume while Hoxa5flox/flox;Olig2+/cre mice had the largest increase in breathing frequency. No significant differences were observed between medulla-spinal cord preparations from E18.5 control and Hoxa5flox/flox;Olig2+/Cre mouse embryos that could support a role for Hoxa5 in fetal inspiratory motor command. According to our data, Hoxa5 expression in mesenchyme and phrenic motor neurons controls distinct aspects of respiratory development.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".