Neuronal Swelling: A Non-osmotic Consequence of Spreading Depolarization
Bibliographic record
Abstract
Abstract An acute reduction in plasma osmolality causes rapid uptake of water by astrocytes but not by neurons, whereas both cell types swell as a consequence of lost blood flow (ischemia). Either hypoosmolality or ischemia can displace the brain downwards, potentially causing death. However, these disorders are fundamentally different at the cellular level. Astrocytes osmotically swell or shrink because they express functional water channels (aquaporins), whereas neurons lack functional aquaporins and thus maintain their volume. Yet both neurons and astrocytes immediately swell when blood flow to the brain is compromised (cytotoxic edema) as following stroke onset, sudden cardiac arrest, or traumatic brain injury. In each situation, neuronal swelling is the direct result of spreading depolarization (SD) generated when the ATP-dependent sodium/potassium ATPase (the Na + /K + pump) is compromised. The simple, and incorrect, textbook explanation for neuronal swelling is that increased Na + influx passively draws Cl − into the cell, with water following by osmosis via some unknown conduit. We first review the strong evidence that mammalian neurons resist volume change during acute osmotic stress. We then contrast this with their dramatic swelling during ischemia. Counter-intuitively, recent research argues that ischemic swelling of neurons is non-osmotic, involving ion/water cotransporters as well as at least one known amino acid water pump. While incompletely understood, these mechanisms argue against the dogma that neuronal swelling involves water uptake driven by an osmotic gradient with aquaporins as the conduit. Promoting clinical recovery from neuronal cytotoxic edema evoked by spreading depolarizations requires a far better understanding of molecular water pumps and ion/water cotransporters that act to rebalance water shifts during brain ischemia.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".