Influences of the breathing route on upper airway dynamics properties in normal awake subjects with constant mouth opening
Bibliographic record
Abstract
MB (mouth breathing) promotes the occurrence of sleep-disordered breathing even in non-apnoeic subjects. Considering that MO (mouth opening) contributes to an increase in UA (upper airway) collapsibility independently of MB, the aim of the present study was to assess the influence of breathing route on UA dynamics in the presence of MO. Bilateral anterior magnetic phrenic nerve stimulation was performed 2 s after expiratory onset in 12 healthy male subjects during wakefulness (age, 50+/-5 years; body mass index, 27.8+/-2.4 kg/m(2)) during MB through a mouthpiece and during exclusive NB (nasal breathing) with the same mouthpiece in place. Twitch-induced V(I) (instantaneous flow), P(ph) and P(es) (pharyngeal and oesophageal pressures respectively) were recorded and the corresponding resistances were measured. A polynomial regression model, V(I)=k(1)P(d)+k(2)P(d)(2), was used to characterize flow-pressure relationship and to determine the P(d) value at which UA collapses. There was no difference in UA dynamic properties between NB and MB when UA collapse occurred above the pharyngeal catheter. For twitches where UA collapse occurred lower in the UA, pharyngeal resistance decreased from NB to MB (2.0+/-0.3 and 1.5+/-0.2 cmH(2)Oxl(-1)xs respectively; P=0.02; values are means+/-S.D.), whereas closing pressure increased (-25.7+/-10.1 and -18.0+/-3.0 cmH(2)O respectively; P=0.04). We conclude that (i) in the presence of MO the dynamic properties of the proximal UA free of phasic activity do not differ between NB and MB, and (ii) MB decreases the upstream resistance and increases collapsibility of the distal UA.
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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 | 0.001 |
| 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".