Bibliographic record
Abstract
Breathing movements are initiated and controlled by a neuronal network within the lower brainstem that is influenced by peripheral and suprapontine inputs. To provide adaptation of breathing to vocalisation, exercise or hypoxia, rhythmogenic neurons of the ventral respiratory group (VRG) within the ventrolateral medulla (VLM) are controlled by numerous neuromodulators. Underlying cellular mechanisms are currently analysed in respiratory active medulla preparations from perinatal rodents. This reveals properties of the perinatal respiratory network pivotal for understanding spontaneous or drug-induced perturbation of breathing in preterm and term infants. Already at birth, ligand-gated anion channels can inhibit VLM-VRG neurons. But impairment of Cl- extrusion by hormones or growth factors may interfere with respiratory functions. During severe hypoxia, resulting in anoxia of the VLM-VRG, perinatal respiratory activity persists for more than twenty minutes, although at a greatly reduced frequency. This frequency depression, associated with a hyperpolarisation of rhythmogenic VLM-VRG neurons, is reversed by K+ channel blockers, thyrotropin-releasing hormone or substance-P, for example. This response may represent an adaptive mechanism for energy conservation during oxygen depletion. Endogenous frequency depression of the normoxic perinatal respiratory rhythm, possibly mediated by endorphins or prostaglandins, may serve to dampen excessive respiratory activity in utero. Opiates and prostaglandins, known to impair breathing in infants during clinical administration, likely act directly to depress rhythmogenic VLM-VRG neurons. Based upon such findings in perinatal rodent models on synaptic inhibition and responses to hypoxia-anoxia or clinically-applicable drugs, novel pharmacological strategies are discussed that aim to stabilise infant breathing by targeting rhythmogenic respiratory neurons.
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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 | 0.000 | 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 | 0.000 |
| 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".