Tropisetron attenuates amyloid‐beta‐induced inflammatory and apoptotic responses in rats
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Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder featured by deposition of beta-amyloid (Aβ) plaques in the hippocampus and associated cortices and progressive cognitive decline. Tropisetron, a selective 5-HT3 receptor antagonist, is conventionally used to counteract chemotherapy-induced emesis. Recent investigations describe antiphlogistic properties for tropisetron. It has been shown that tropisetron protects against rat embolic stroke. We investigated protective properties of tropisetron in a beta-amyloid (Aβ) rat model of AD and possible involvement of 5-HT3 receptors. MATERIAL AND METHODS: Aβ (1-42) was injected into the hippocampus of male rats. Animals were treated intracerebroventricularly with tropisetron, mCPBG (selective 5-HT3 receptor agonist) or mCPBG plus tropisetron on days 1, 3, 5 and 7. Seven days following Aβ administration, inflammatory markers (TNF-α, COX-2, iNOS and NF-κB), apoptotic markers (caspase 3 cytochrome c release) and calcineurin phosphatase activity were assessed in hippocampus. RESULTS: Seven days following Aβ inoculation, control animals displayed dramatic increase in TNF-α, COX-2, iNOS, NF-κB, active caspase 3, cytochrome c release and calcineurin phosphatase activity in the hippocampus. Tropisetron significantly diminished the elevated levels of these markers and reversed the cognitive deficit. Interestingly, tropisetron was also found to be a potent inhibitor of calcineurin phosphatase activity. The selective 5-HT3 receptor agonist mCPBG, when co-administered with tropisetron, completely reversed the procognitive and anti-apoptotic properties of tropisetron while it could only partially counteract the anti-inflammatory effects. mCPBG alone significantly aggravated Aβ-induced injury. CONCLUSION: Our findings indicate that tropisetron protects against Aβ-induced neurotoxicity in vivo through both 5-HT3 receptor-dependent and independent pathways.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| 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) | 0.000 | 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 it