Minocycline Protects Dopaminergic Neurons Against Long-Term Rotenone Toxicity
Bibliographic record
Abstract
BACKGROUND: In Parkinson's disease, most of current therapies only provide symptomatic treatment and so far there is no drug which directly affects the disease process. OBJECTIVES: To investigate the neuroprotective effects of minocycline against long-term rotenone toxicity in primary dopaminergic cell cultures. METHODS: Embryonic mice of 14-days-old were used for preparation of primary dopaminergic cell cultures. On the 6th day in vitro, prepared cultures were treated both with minocycline alone (1, 5, 10 and 20 microM) and concomitantly with rotenone (5 and 20 nM) and minocycline. Cultures were incubated at 37 degrees C for six consecutive days. On Day in vitro culture medium was aspirated and used for measuring lactate dehydrogenase. Cultured cells were fixed in 4% paraformaldhyde and stained immunohistochemically against tyrosine hydroxylase. RESULTS: Treatment of cultures with 5 and 20 nM of rotenone significantly decreased the survival of tyrosine hydroxylase immunoreactive neurons by 27 and 31% and increased the release of lactate dehydrogenase into the culture medium by 31 and 236%, respectively compared to untreated controls. Minocycline (1, 5, 10 microM) significantly protected tyrosine hydroxylase immunoreactive neurons by 17, 15 and 19% and 13, 22 and 23% against 5 and 20 nM of rotenone, respectively compared to rotenone-treated cultures. Minocycline (only at 10 microM) significantly decreased the release of lactate dehydrogenase by 79% and 133% against 5 and 20 nM of rotenone, respectively. CONCLUSION: Minocycline has neuroprotective potential against the progressive loss of tyrosine hydroxylase immunoreactive neurons induced by long-term rotenone toxicity in primary dopaminergic cultures.
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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".