Reply to: Hypoxia treatment of Parkinson’s disease may disrupt the circadian system
Bibliographic record
Abstract
Background Introduction In recent years, increasing attention has been given to hypoxia-based treatment for persons with neurodegenerative and mitochondrial disease, as reflected by the significant rise in publications from basic [1], preclinical [2] and clinical [3, 4] research groups. Hypoxia treatment is based on the idea of hypoxic conditioning and adaptations induced by hypoxia. Recently, we published a protocol paper to assess the safety, feasibility, and acute symptomatic effects of single sessions of continuous and intermittent hypoxia (for 45 min, at FiO2 0.133 and 0.163) in persons with Parkinson’s disease (PD) [3]. In Coste & Touitou’s recent correspondence [5] to our protocol [6], they highlighted the potential for circadian rhythm disturbances induced by hypoxia in PD. This interesting insight is based on their two different studies, in which a phase shift in circadian rhythm (as measured by cortisol and melatonin) was observed after eight-hours-long ‘chronic’ exposure to hypoxia [7, 8]. Coste & Touitou [6] carefully considered that hypoxia-based interventions could therefore induce changes in circadian rhythm, and this may in turn affect the outcome of these interventions. Here, we discuss important differences between chronic hypoxia, which resembles hypoxia as a disease model for sleep apnea, and hypoxic conditioning.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.026 | 0.022 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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".