Brain <scp>H<sup>+</sup>/CO<sub>2</sub></scp> sensing and control by glial cells
Bibliographic record
Abstract
Abstract Maintenance of constant brain pH is critically important to support the activity of individual neurons, effective communication within the neuronal circuits, and, thus, efficient processing of information by the brain. This review article focuses on how glial cells detect and respond to changes in brain tissue pH and concentration of CO 2 , and then trigger systemic and local adaptive mechanisms that ensure a stable milieu for the operation of brain circuits. We give a detailed account of the cellular and molecular mechanisms underlying sensitivity of glial cells to H + and CO 2 and discuss the role of glial chemosensitivity and signaling in operation of three key mechanisms that work in concert to keep the brain pH constant. We discuss evidence suggesting that astrocytes and marginal glial cells of the brainstem are critically important for central respiratory CO 2 chemoreception—a fundamental physiological mechanism that regulates breathing in accord with changes in blood and brain pH and partial pressure of CO 2 in order to maintain systemic pH homeostasis. We review evidence suggesting that astrocytes are also responsible for the maintenance of local brain tissue extracellular pH in conditions of variable acid loads associated with changes in the neuronal activity and metabolism, and discuss potential role of these glial cells in mediating the effects of CO 2 on cerebral vasculature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".