Light microscopic and heterogeneity analysis of astrocytes in the common marmoset brain
Bibliographic record
Abstract
Astrocytes are abundant cells of the central nervous system (CNS) and are involved in processes including synapse formation/function, ion homeostasis, neurotransmitter uptake, and neurovascular coupling. Recent evidence indicates that astrocytes show diverse molecular, structural, and physiological properties within the CNS. This heterogeneity is reflected in differences in astrocyte structure, gene expression, functional properties, and responsiveness to injury/pathological conditions. Deeper investigation of astrocytic heterogeneity is needed to understand how astrocytes are configured to enable diverse roles in the CNS. While much has been learned about astrocytic heterogeneity in rodents, much less is known about astrocytic heterogeneity in the primate brain where astrocytes have greater size and complexity. The common marmoset (Callithrix jacchus) is a promising non-human primate model because of similarities between marmosets and humans with respect to genetics, brain anatomy, and cognition/behavior. Here, we investigated the molecular and structural heterogeneity of marmoset astrocytes using an array of astrocytic markers, multi-label confocal microscopy, and quantitative analysis. We used male and female marmosets and found that marmoset astrocytes show differences in expression of astrocytic markers in cortex, hippocampus, and cerebellum. These differences were accompanied by intra-regional variation in expression of markers for glutamate/GABA transporters, and potassium and water channels. Differences in astrocyte structure were also found, along with complex interactions with blood vessels, microglia, and neurons. This study contributes to our knowledge of the cellular and molecular features of marmoset astrocytes and is useful for understanding the complex properties of astrocytes in the primate CNS.
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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 | 0.001 | 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".