ATP and glutamate released via astroglial connexin 43 hemichannels mediate neuronal death through activation of pannexin 1 hemichannels
Bibliographic record
Abstract
Inflammation contributes to neurodegeneration in post-ischemic brain, diabetes, and Alzheimer's disease. Participants in this inflammatory response include activation of microglia and astrocytes. We studied the role of microglia treated with amyloid-β peptide (Aβ) on hemichannel activity of astrocytes subjected to hypoxia in high glucose. Reoxygenation after 3 h hypoxia in high glucose induced transient astroglial permeabilization via Cx43 hemichannels and reduction in intercellular communication via Cx43 cell-cell channels. Both responses were greater and longer lasting in astrocytes previously exposed for 24 h to conditioned medium from Aβ-treated microglia (CM-Aβ). The effects of CM-Aβ were mimicked by TNF-α and IL-1β and were abrogated by neutralizing TNF-α with soluble receptor and IL-1β with a receptor antagonist. Astrocytes under basal conditions protected neurons against hypoxia, but exposure to CM-Aβ made them toxic to neurons subjected to a sub-lethal hypoxia/reoxygenation episode, revealing the additive nature of the insults. Astrocytes exposed to CM-Aβ induced permeabilization of cortical neurons through activation of neuronal pannexin 1 (Panx1) hemichannels by ATP and glutamate released through astroglial Cx43 hemichannels. In agreement, inhibition of NMDA or P2X receptors only partially reduced the activation of neuronal Panx1 hemichannels and neuronal mortality, but simultaneous inhibition of both receptors completely prevented the neurotoxic response. Therefore, we suggest that responses to ATP and glutamate converge in activation of neuronal Panx1 hemichannels. Thus, we propose that blocking hemichannels expressed by astrocytes and/or neurons in the inflamed nervous system could represent a novel and alternative strategy to reduce neuronal loss in various pathological states including Alzheimer's disease, diabetes and ischemia.
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) | 0.001 | 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".