Mechanisms of sustaining oxygen extraction efficiency in dragonfly nymphs during aquatic hypoxia
Bibliographic record
Abstract
Abstract Despite breathing water using their tidally ventilated rectal gills, dragonfly nymphs show a surprising ability to maintain oxygen (O 2 ) extraction from the water during hypoxia. However, an increase in convective O 2 transfer is insufficient to sustain aerobic demands by itself, which suggests that diffusive mechanisms must also be involved. This study examines the contributions of changing the O 2 partial pressure gradient (PO 2 ) and/or O 2 conductance across the rectal gill in maintaining O 2 extraction efficiency (OEE) of dragonfly nymphs during hypoxia. Data were collected using the same custom-designed respiro-spirometer described in a previous study with the addition of an implanted O 2 sensor to measure hemolymph PO 2 . Results show that the implantation of the O 2 sensor does not affect the respiratory and ventilatory response of nymphs to hypoxia. Hemolymph PO 2 fell from 6.3 ± 1.6 kPa at normoxia to 2.5 ± 0.6 kPa at 16.0 kPa, which resulted in the PO 2 diffusion gradient remaining statistically constant at these two water PO 2 s (17.5 ± 1.7 and 15.4 ± 0.7 kPa during normoxia and 16.0 kPa respectively). Beyond 16.0 kPa, a progressive reduction in hemolymph PO 2 was unable to sustain the diffusion gradient. Mathematical modeling revealed that while the addition of hemolymph PO 2 in tandem with ventilation frequency was able to elevate OEE during 16.0 kPa to that of normoxia, both were still insufficient during severe hypoxia and required an increase in O 2 conductance. Estimating the change in whole-gill conductance showed that nymphs are indeed increasing their conductance as the water becomes hypoxic, demonstrating a reliance on both diffusion gradient and O 2 conductance to enhance diffusive O 2 transfer in conjunction with convective mechanisms to maintain O 2 extraction during hypoxia.
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 | 0.000 | 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) | 0.000 | 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".