Dueling effects of nocturnal hypoxia in experimental asthma: implications for future therapies
Bibliographic record
Abstract
Introduction. Exposure to hypoxia has been used in murine models of asthma to study potential therapeutic applications. Herein, a new strategy consisting of nocturnal hypoxia was investigated. We hypothesized that nocturnal hypoxia affects the manifestation of experimental asthma in mice. Methods. Male BALB/c mice were divided into four groups: exposed to either normoxia or normobaric hypoxia (12h/day from 6 pm to 6 am at 13% O2) and with or without experimental asthma induced by daily exposure to intranasal house-dust mite for 10 days. One day later, anesthetized mice were connected to the flexiVent to measure: 1- lung volumes, such as total lung capacity (TLC) and vital capacity (VC); and 2- baseline respiratory mechanics, such as respiratory system elastance (Ers) and tissue elastance (H). Alternatively, mice were challenged with nebulized methacholine at increasing concentrations from 0 to 100 mg/mL to assess changes in respiratory mechanics. Results. At baseline, a two-way ANOVA shows that nocturnal hypoxia decreased Ers and H (p<0.001 & p<0.0001, respectively) and increased TLC and VC (p<0.001 & p=0.0002, respectively) compared to normoxia. A three-way ANOVA shows that nocturnal hypoxia affects the methacholine response (p<0.0001), which was mainly driven by the exacerbating effect of nocturnal hypoxia on the methacholine response in groups with experimental asthma. Conclusions. Nocturnal hypoxia reduces lung elastance and enhances lung volumes such as TLC and VC. It also exacerbates the methacholine response in mice with experimental asthma. These findings suggest dueling effects of nocturnal hypoxia, potentially offering some benefits but also worsening hyperreactivity in asthma.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".