Astrocyte-specific Ca<sup>2+</sup> activity: Mechanisms of action, experimental tools, and roles in ethanol-induced dysfunction
Bibliographic record
Abstract
Astrocytes are a subtype of non-neuronal glial cells that reside in the central nervous system. Astrocytes have extensive peripheral astrocytic processes that ensheathe synapses to form the tripartite synapse. Through a multitude of pathways, astrocytes can influence synaptic development and structural maturation, respond to neuronal signals, and modulate synaptic transmission. Over the last decade, strong evidence has emerged demonstrating that astrocytes can influence behavioral outcomes in various animal models of cognition. However, the full extent of how astrocytes influence brain function is still being revealed. Astrocyte calcium (Ca 2+ ) signaling has emerged as an important driver of astrocyte-neuronal communication allowing intricate crosstalk through mechanisms that are still not fully understood. Here, we will review the field's current understanding of astrocyte Ca 2+ signaling and discuss the sophisticated state-of-the-art tools and approaches used to continue unraveling astrocytes' interesting role in brain function. Using the field of pre-clinical ethanol (EtOH) studies in the context of alcohol use disorder, we focus on how these novel approaches have helped to reveal an important role for astrocyte Ca 2+ function in regulating EtOH consumption and how astrocyte Ca 2+ dysfunction contributes to the cognitive deficits that emerge after EtOH exposure in a rodent model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".