Neuroprotective properties of 17β‐estradiol, progesterone, and raloxifene in MPTP <i>C57Bl/6 mice</i>
Bibliographic record
Abstract
Previous work from our laboratory showed prevention of 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine (MPTP) induced dopamine depletion in striatum of C57Bl/6 mice by 17beta-estradiol, progesterone, and raloxifene, whereas 17alpha-estradiol had no effect. The present study investigated the mechanism by which these compounds exert their neuroprotective activity. The hormonal effect on the dopamine transporter (DAT) was examined to probe the integrity of dopamine neurons and glutamate receptors in order to find a possible excitotoxic mechanism. Drugs were injected daily for 5 days before MPTP (four injections, 15 mg/kg ip at 2-h intervals) and drug treatment continued for 5 more days. MPTP induced a decrease of striatal DAT-specific binding (50% of control) and DAT mRNA in the substantia nigra (20% of control), suggesting that loss of neuronal nerve terminals was more extensive than cell bodies. This MPTP-induced decrease of striatal [(125)I]RTI-121 specific binding was prevented by 17beta-estradiol (2 microg/day), progesterone (2 microg/day), or raloxifene (5 mg/kg/day) but not by 17alpha-estradiol (2 microg/day) or raloxifene (1 mg/kg/day). No treatment completely reversed the decreased levels of DAT mRNA in the substantia nigra. Striatal [(125)I]RTI-121 specific binding was positively correlated with dopamine concentrations in intact, saline, or hormone-treated MPTP mice. Striatal NMDA-sensitive [(3)H]glutamate or [(3)H]AMPA specific binding remained unchanged in intact, saline, or hormone-treated MPTP mice, suggesting the unlikely implication of changes of glutamate receptors in an excitotoxic mechanism. These results show a stereospecific neuroprotection by 17beta-estradiol of MPTP neurotoxicity, which is also observed with progesterone or raloxifene treatment. The present paradigm modeled early DA nerve cell damage and was responsive to hormones.
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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 | 0.001 | 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".