MicroRNA profiling reveals new aspects of HIV neurodegeneration: caspase‐6 regulates astrocyte survival
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small noncoding RNA molecules, which are known to regulate gene expression in physiological and pathological conditions. miRNA profiling was performed using brain tissue from patients with HIV encephalitis (HIVE), a neuroinflammatory/degenerative disorder caused by HIV infection of the brain. Microarray analysis showed differential expression of multiple miRNAs in HIVE compared to control brains. Target prediction and gene ontology enrichment analysis disclosed targeting of several gene families/biological processes by differentially expressed miRNAs (DEMs), with cell death-related genes, including caspase-6, showing a bias toward down-regulated DEMs. Consistent with the miRNA data, HIVE brains exhibited higher levels of caspase-6 transcripts compared with control patients. Immunohistochemical analysis showed localization of the cleaved form of caspase-6 in astrocytes in HIVE brain sections. Exposure of cultured human primary astrocytes to HIV viral protein R (Vpr) induced p53 up-regulation, loss of mitochondrial membrane potential, and caspase-6 activation followed by cell injury. Transgenic mice, expressing Vpr in microglial cells, demonstrated astrocyte apoptosis in brain, which was associated with caspase-6 activation and neurobehavioral abnormalities. Overall, these data point to previously unrecognized alterations in miRNA profile in the brain during HIV infection, which contribute to cell death through dysregulation of cell death machinery.
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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 | 0.000 | 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".