Ambient CO2, fish behaviour and altered GABAergic neurotransmission: exploring the mechanism of CO2-altered behaviour by taking a hypercapnia dweller down to low CO2 levels
Why this work is in the frame
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Bibliographic record
Abstract
Recent studies suggest that projected rises of aquatic CO2 levels cause acid-base regulatory responses in fishes that lead to altered GABAergic neurotransmission and disrupted behaviour, threatening fitness and population survival. It is thought that changes in Cl(-) and HCO3 (-) gradients across neural membranes interfere with the function of GABA-gated anion channels (GABAA receptors). So far, such alterations have been revealed experimentally by exposing species living in low-CO2 environments, like many oceanic habitats, to high levels of CO2 (hypercapnia). To examine the generality of this phenomenon, we set out to study the opposite situation, hypothesizing that fishes living in typically hypercapnic environments also display behavioural alterations if exposed to low CO2 levels. This would indicate that ion regulation in the fish brain is fine-tuned to the prevailing CO2 conditions. We quantified pH regulatory variables and behavioural responses of Pangasianodon hypophthalmus, a fish native to the hypercapnic Mekong River, acclimated to high-CO2 (3.1 kPa) or low-CO2 (0.04 kPa) water. We found that brain and blood pH was actively regulated and that the low-CO2 fish displayed significantly higher activity levels, which were reduced after treatment with gabazine, a GABAA receptor blocker. This indicates an involvement of the GABAA receptor and altered Cl(-) and HCO3 (-) ion gradients. Indeed, Goldman calculations suggest that low levels of environmental CO2 may cause significant changes in neural ion gradients in P. hypophthalmus. Taken together, the results suggest that brain ion regulation in fishes is fine-tuned to the prevailing ambient CO2 conditions and is prone to disruption if these conditions change.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it