Embryonic common snapping turtles (<i>Chelydra serpentina</i>) preferentially regulate intracellular tissue pH during acid-base challenges
Bibliographic record
Abstract
The nests of embryonic turtles naturally experience elevated CO2 (hypercarbia), which leads to increased blood PCO2 and a respiratory acidosis, resulting in reduced blood pH [extracellular pH (pHe)]. Some fishes preferentially regulate tissue pH [intracellular pH (pHi)] against changes in pHe; this has been proposed to be associated with exceptional CO2 tolerance and has never been identified in amniotes. As embryonic turtles may be CO2 tolerant based on nesting strategy, we hypothesized that they preferentially regulate pHi, conferring tolerance to severe acute acid-base challenges. This hypothesis was tested by investigating pH regulation in common snapping turtles (Chelydra serpentina) reared in normoxia then exposed to hypercarbia (13 kPa PCO2 ) for 1 h at three developmental ages: 70% and 90% of incubation, and yearlings. Hypercarbia reduced pHe but not pHi, at all developmental ages. At 70% of incubation, pHe was depressed by 0.324 pH units while pHi of brain, white muscle and lung increased; heart, liver and kidney pHi remained unchanged. At 90% of incubation, pHe was depressed by 0.352 pH units but heart pHi increased with no change in pHi of other tissues. Yearlings exhibited a pHe reduction of 0.235 pH units but had no changes in pHi of any tissues. The results indicate common snapping turtles preferentially regulate pHi during development, but the degree of response is reduced throughout development. This is the first time preferential pHi regulation has been identified in an amniote. These findings may provide insight into the evolution of acid-base homeostasis during development of amniotes, and vertebrates in general.
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) | 0.001 | 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".