P3‐062: ABNORMAL REGULATION OF ENDOGENOUS TAU METABOLISM IN MICRORNA‐132 KNOCKOUT MICE
Bibliographic record
Abstract
Changes in the regulation of tau metabolism such as expression, splicing and phosphorylation are involved in the development of tauopathies, a group of neurodegenerative disorders that includes Alzheimer's disease (AD). Recently, we have shown that microRNAs, in particular microRNA-132 (miR-132), participate in the regulation of tau expression and splicing in neuronal cells in culture. Interestingly, miR-132 is amongst the most strongly down-regulated miRNAs in AD and other tauopathies. Our current aim now is to translate these observations by investigating the role of miR-132 function in the regulation of tau metabolism in vivo in mice. We used miR-132 knockout (KO) and littermate control mice as biological models. Mice were sacrificed at various ages in order to study endogenous tau metabolism. Western blot analysis of tau protein was performed using a panel of phospho and exon-specific epitopes. PCR was used to validate changes in tau splicing. Real-time quantitative RT-PCR was used to quantify total tau mRNA levels. We demonstrate that endogenous tau splicing, expression, and phosphorylation are affected by the absence of miR-132 in vivo. Interestingly, these effects on tau regulation seem age dependent. Finally, we demonstrate that tau is a direct target for miR-132. Our results validate previous findings in cell cultures and support the hypothesis that miR-132 levels are critical in the regulation of neuronal tau metabolism. Further experiments are underway to understand the relationship between miR-132 loss, abnormal tau regulation, and neurodegeneration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".