Changes in miR-134-3p expression and zDHHC3-AMPARs axis in association with aluminum neurotoxicity
Bibliographic record
Abstract
Abstract Aluminum (Al) is a neurotoxic substance associated with cognitive dysfunction and neurodegenerative diseases, such as Alzheimer’s disease, but the mechanisms for aluminum neurotoxicity remain to be identified. In this work, we try to investigate a novel potential biomarker of cognitive dysfunction following aluminum exposure and the mechanism involved. Recently, miR-134-3p was reported as a novel regulator of cognitive function. To address this, we investigate the expression level of miR-134-3p in plasma from 280 aluminum factory workers and analyzed the correlation between miRNA-134-3p, blood Al concentration, and Montreal Cognitive Assessment Scale (MoCA scale) score. The results implied that occupational aluminum exposure elevated miR-134-3p expression in the plasma of workers accompanied by cognitive impairment. Our experiment studies using both animal models and PC12 cells validated the up-regulation of miR-134-3p caused by aluminum. In addition, we identified that palmitoylation enzyme zDHHC3 was the target of miR-134-3p, and the decreasing AMPAR receptors (AMPARs) trafficking was related to the learning and memory impairment induced by aluminum. More importantly, using transfection and interference approaches in PC12 cells, inhibition of miR-134-3p resulted in a recovery of zDHHC3-AMPARs axis to a certain extent in response to aluminum. In summary, miR-134-3p was found to be involved in aluminum neurotoxicity by targeting zDHHC3-AMPARs axis and could serve as a potential biomarker or helpful target.
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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) | 0.001 | 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".