Physiological Evidence That Pyramidal Neurons Lack Functional Water Channels
Bibliographic record
Abstract
The physiological conditions that swell mammalian neurons are clinically important but contentious. Distinguishing the neuronal component of brain swelling requires viewing intact neuronal cell bodies, dendrites, and axons and measuring their changing volume in real time. Cultured or dissociated neuronal somata swell within minutes under acutely overhydrated conditions and shrink when strongly dehydrated. But paradoxically, most central nervous system (CNS) neurons do not express aquaporins, the membrane channels that conduct osmotically driven water. Using 2-photon laser scanning microscopy (2PLSM), we monitored neuronal volume under osmotic stress in real time. Specifically, the volume of pyramidal neurons in cerebral cortex and axon terminals comprising cerebellar mossy fibers was measured deep within live brain slices. The expected swelling or shrinking of the gray matter was confirmed by recording altered light transmittance and by indirectly measuring extracellular resistance over a wide osmotic range of -80 to +80 milliOsmoles (mOsm). Neurons expressing green fluorescent protein were then imaged with 2PLSM between -40 and +80 mOsm over 20 min. Surprisingly, pyramidal somata, dendrites, and spines steadfastly maintained their volume, as did the cerebellar axon terminals. This precluded a need for the neurons to acutely regulate volume, preserved their intrinsic electrophysiological stability, and confirmed that these CNS nerve cells lack functional aquaporins. Thus, whereas water easily permeates the aquaporin-rich endothelia and glia driving osmotic brain swelling, neurons tenatiously maintain their volume. However, these same neurons then swell dramatically upon oxygen/glucose deprivation or [K+]0 elevation, so prolonged depolarization (as during stroke or seizure) apparently swells neurons by opening nonaquaporin channels to water.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".