Heme oxygenase‐1 modulates microRNA expression in cultured astroglia: Implications for chronic brain disorders
Bibliographic record
Abstract
BACKGROUND: Over-expression of the heme-degrading enzyme, heme oxygenase-1 (HO-1) promotes iron deposition, mitochondrial damage, and autophagy in astrocytes and enhances the vulnerability of nearby neuronal constituents to oxidative injury. These neuropathological features and aberrant brain microRNA (miRNA) expression patterns have been implicated in the etiopathogeneses of various neurodevelopmental and aging-related neurodegenerative disorders. OBJECTIVE: To correlate glial HO-1 overexpression with altered miRNA patterns, which have been linked to the aforementioned "core" neuropathological features. METHODS: miRNA microchip assays were performed on HMOX1- and sham-transfected primary rat astroglia and affected miRNAs were further validated by qPCR. The roles of the heme degradation products, carbon monoxide (CO), iron (Fe) and bilirubin on miRNA expression were assessed and salient mRNA targets of the impacted miRNAs were ascertained. RESULTS: In HMOX1-transfected astrocytes, rno-miR-140*, rno-miR-17, and rno-miR-16 were significantly up-regulated, and rno-miR-297, rno-miR-206, rno-miR-187, rno-miR-181a, rno-miR-138 and rno-miR-29c were down-regulated, compared to sham-transfected controls. CO and Fe were implicated in the HMOX1 effects, whereas bilirubin was inert or counteracted the HMOX1-related changes. mRNA levels of Ngfr, Vglut1, Mapk3, Tnf-α, and Sirt1, known targets of the down-regulated miRNAs and abnormal in various human brain disorders, were significantly increased in the HMOX-1-transfected astrocytes. CONCLUSIONS: In chronic CNS disorders, altered expression of salient miRNAs and their mRNA targets may contribute to the neural damage accruing from the over-expression of glial HO-1.
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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".