Microglial Function during Glucose Deprivation: Inflammatory and Neuropsychiatric Implications
Bibliographic record
Abstract
Inflammation is increasingly recognized as a contributor to the pathophysiology of neuropsychiatric disorders, including depression, anxiety disorders and autism, though the factors leading to contextually inappropriate or sustained inflammation in pathological conditions are yet to be elucidated. Microglia, as the key mediators of inflammation in the CNS, serve as likely candidates in initiating pathological inflammation and as an ideal point of therapeutic intervention. Glucose deprivation, as a component of the pathophysiology of ischemia or occurring transiently in diabetes, may serve to modify microglial function contributing to inflammatory injury. To this end, primary microglia were cultured from postnatal rat brain and subject to glucose deprivation in vitro. Microglia were characterized for their proliferation, phagocytic function and secretion of inflammatory factors, and tested for their capacity to respond to a potent inflammatory stimulus. In the absence of glucose, microglia remained capable of proliferation, phagocytosis and inflammatory activation and showed increased release of inflammatory factors after presentation of an inflammatory stimulus. Glucose-deprived microglia demonstrated increased phagocytic activity and decreased accumulation of lipids in lipid droplets over a 48-h timecourse, suggesting they may use scavenged lipids as a key alternate energy source during metabolic stress. In the present manuscript, we present novel findings that glucose deprivation may sensitize microglial release of inflammatory mediators and prime microglial functions for both survival and inflammatory roles, which may contribute to psychiatric comorbidities of ischemia, diabetes and/or metabolic disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".