Low Glycolysis Is Neuroprotective during Anoxic Spreading Depolarization (SD) and Reoxygenation in Locusts
Bibliographic record
Abstract
Abstract Migratory locusts enter a reversible hypometabolic coma to survive environmental anoxia, wherein the cessation of CNS activity is driven by spreading depolarization (SD). While glycolysis is recognized as a crucial anaerobic energy source contributing to animal anoxia tolerance, its influence on the anoxic SD trajectory and recovery outcomes remains poorly understood. We investigated the effects of varying glycolytic capacity on adult female locust anoxic SD parameters, using glucose or the glycolytic inhibitors 2-deoxy-d-glucose (2DG) or monosodium iodoacetate (MIA). Surprisingly, 2DG treatment shared similarities with glucose yet had opposite effects compared with MIA. Specifically, although SD onset was not affected, both glucose and 2DG expedited the recovery of CNS electrical activity during reoxygenation, whereas MIA delayed it. Additionally, glucose and MIA, but not 2DG, increased tissue damage and neural cell death following anoxia-reoxygenation. Notably, glucose-induced injuries were associated with heightened CO2output during the early phase of reoxygenation. Conversely, 2DG resulted in a bimodal response, initially dampening CO2output and gradually increasing it throughout the recovery period. Given the discrepancies between effects of 2DG and MIA, the current results require cautious interpretations. Nonetheless, our findings present evidence that glycolysis is not a critical metabolic component in either anoxic SD onset or recovery and that heightened glycolysis during reoxygenation may exacerbate CNS injuries. Furthermore, we suggest that locust anoxic recovery is not solely dependent on energy availability, and the regulation of metabolic flux during early reoxygenation may constitute a strategy to mitigate damage.
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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 | 0.000 |
| 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 | 0.001 |
| 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".