Interferon-γ-Induced Neurotoxicity of Human Astrocytes
Bibliographic record
Abstract
Activated astrocytes, which can also be referred to as reactive astrocytes or astrogliosis, have been identified in affected regions of common neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and multiple sclerosis. Activated astrocytes may be beneficial, promoting neuronal survival due to their production of growth factors and neurotrophins. Activated astrocytes can also be detrimental to neighboring neurons in neuroinflammatory processes. Astrocytes exposed to certain inflammatory stimulants in vitro have been shown to release potentially neurotoxic molecules, including inflammatory cytokines, glutamate, nitric oxide and reactive oxygen species. It has recently been shown that adult human astrocytes stimulated with interferon-γ, a common inflammatory cytokine evidently present in neuropathological brains, exert potent neurotoxicity in vitro. This interferon- γ-induced astrocytic neurotoxicity is mediated by the activation of the Janus kinase-signal transducer and activator of transcription (STAT) 3 pathway in the astrocytes, and involves intracellular phosphorylation of STAT3 at tyrosine-705 residue. Therefore, control of STAT3 activation in human astrocytes may be a promising new therapeutic strategy for a broad spectrum of neurodegenerative and neuroinflammatory disorders where activated astrocytes may contribute to the pathology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".