MicroRNA: Implications for Alzheimer Disease and other Human CNS Disorders
Bibliographic record
Abstract
Understanding complex diseases such as sporadic Alzheimer disease (AD) has been a major challenge. Unlike the familial forms of AD, the genetic and environmental risks factors identified for sporadic AD are extensive. MicroRNAs are one of the major noncoding RNAs that function as negative regulators to silence or suppress gene expression via translational inhibition or message degradation. Their discovery has evoked great excitement in biomedical research for their promise as potential disease biomarkers and therapeutic targets. Key microRNAs have been identified as essential for a variety of cellular events including cell lineage determination, proliferation, apoptosis, DNA repair, and cytoskeletal organization; most, if not all, acting to fine-tune gene expression at the post-transcriptional level in a host of cellular signaling networks. Dysfunctional microRNA-mediated regulation has been implicated in the pathogenesis of many disease states. Here, the current understanding of the role of miRNAs in the central nervous system is reviewed with emphasis on their impact on the etiopathogenesis of sporadic AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".