Glial<i>HMOX1</i>expression promotes central and peripheral α‐synuclein dysregulation and pathogenicity in parkinsonian mice
Bibliographic record
Abstract
α-Synuclein is a key player in the pathogenesis of Parkinson disease (PD). Expression of human heme oxygenase-1 (HO-1) in astrocytes of GFAP.HMOX1 transgenic (TG) mice between 8.5 and 19 months of age results in a parkinsonian phenotype characterized by neural oxidative stress, nigrostriatal hypodopaminergia associated with locomotor incoordination, and overproduction of α-synuclein. We identified two microRNAs (miR-), miR-153 and miR-223, that negatively regulate α-synuclein in the basal ganglia of male and female GFAP.HMOX1 mice. Serum concentrations of both miRNAs progressively declined in the wild-type (WT) and GFAP.HMOX1 mice between 11 and 19 months of age. Moreover, at each time point surveyed, circulating levels of miR-153 were significantly lower in the TG animals compared to WT controls, while α-synuclein protein concentrations were elevated in erythrocytes of the GFAP.HMOX1 mice at 19 months of age relative to WT values. Primary WT neurons co-cultured with GFAP.HMOX1 astrocytes exhibited enhanced protein oxidation, mitophagy and apoptosis, aberrant expression of genes regulating the dopaminergic phenotype, and an imbalance in gene expression profiles governing mitochondrial fission and fusion. Many, but not all, of these neuronal abnormalities were abrogated by small interfering RNA (siRNA) knockdown of α-synuclein, implicating α-synuclein as a potent, albeit partial, mediator of HO-1's neurodystrophic effects in these parkinsonian mice. Overexpression of HO-1 in stressed astroglia has previously been documented in the substantia nigra of idiopathic PD and may promote α-synuclein production and toxicity by downmodulating miR-153 and/or miR-223 both within the CNS and in peripheral tissues.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".