Activation of AMP-activated Protein Kinase Regulates Hippocampal Neuronal pH by Recruiting Na+/H+ Exchanger NHE5 to the Cell Surface
Bibliographic record
Abstract
Strict regulation of intra- and extracellular pH is an important determinant of nervous system function as many voltage-, ligand-, and H(+)-gated cationic channels are exquisitely sensitive to transient fluctuations in pH elicited by neural activity and pathophysiologic events such as hypoxia-ischemia and seizures. Multiple Na(+)/H(+) exchangers (NHEs) are implicated in maintenance of neural pH homeostasis. However, aside from the ubiquitous NHE1 isoform, their relative contributions are poorly understood. NHE5 is of particular interest as it is preferentially expressed in brain relative to other tissues. In hippocampal neurons, NHE5 regulates steady-state cytoplasmic pH, but intriguingly the bulk of the transporter is stored in intracellular vesicles. Here, we show that NHE5 is a direct target for phosphorylation by the AMP-activated protein kinase (AMPK), a key sensor and regulator of cellular energy homeostasis in response to metabolic stresses. In NHE5-transfected non-neuronal cells, activation of AMPK by the AMP mimetic AICAR or by antimycin A, which blocks aerobic respiration and causes acidification, increased cell surface accumulation and activity of NHE5, and elevated intracellular pH. These effects were effectively blocked by the AMPK antagonist compound C, the NHE inhibitor HOE694, and mutation of a predicted AMPK recognition motif in the NHE5 C terminus. This regulatory pathway was also functional in primary hippocampal neurons, where AMPK activation of NHE5 protected the cells from sustained antimycin A-induced acidification. These data reveal a unique role for AMPK and NHE5 in regulating the pH homeostasis of hippocampal neurons during metabolic stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".