Editorial: Hypoxia and Cardiorespiratory Control
Bibliographic record
Abstract
To maintain adequate oxygen levels in the body, which is essential for a healthy life, the respiratory and cardiovascular systems play vitally important roles. When the oxygen content is insufficient, i.e., when hypoxia is loaded, respiratory and cardiovascular systems respond to restore, compensate, or adapt to hypoxia, e.g., by increasing ventilation and blood flow to maintain oxygen transport to vital organs. Traditionally, it has been thought that hypoxia is detected solely by carotid and aortic bodies, i.e., by peripheral chemoreceptors, and information from the peripheral chemoreceptors is transmitted to respiratory and cardiovascular centers in the brainstem whose respiratory and cardiovascular neural outputs are regulated. However, recent progress in neurophysiology has clarified that there are hypoxia-sensors not only in the periphery but also in the central nervous system. Hypoxia also affects the vascular system causing atherosclerosis and pulmonary hypertension and impairs blood glucose regulation that also facilitates atherosclerosis. The effects of hypoxia on vital organs and tissues vary depending on the modality of hypoxia exposure, i.e., acute, chronically sustained, or intermittent hypoxia. Although these issues have been vigorously investigated, the underlying mechanisms are yet to be unraveled. Likewise, long-range consequences for organ and tissue functions affected by hypoxia have not been fully elucidated. In the article collection of this Research Topic, a series of studies report the latest and most notable pathophysiological findings that are categorized into four areas: respiratory control, glucose metabolism, pulmonary hypertension, and sympathetic nervous system activation. The articles attempt to clarify many of the unsolved issues summarized below. \n \n(Introduction)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".