microRNA-34a (miRNA-34a) Mediated Down-Regulation of the Post-synaptic Cytoskeletal Element SHANK3 in Sporadic Alzheimer's Disease (AD)
Bibliographic record
Abstract
Integrating a combination of bioinformatics, microRNA microfluidic arrays, ELISA analysis, LED Northern, and transfection-luciferase reporter assay data using human neuronal-glial (HNG) cells in primary culture we have discovered a set of up-regulated microRNAs (miRNAs) linked to a small family of down-regulated messenger RNAs (mRNAs) within the superior temporal lobe neocortex (Brodmann A22) of sporadic Alzheimer's disease (AD) brain. At the level of mRNA abundance, the expression of a significant number of human brain genes found to be down-regulated in sporadic AD neocortex appears to be due to the increased abundance of a several brain-abundant inducible miRNAs. These up-regulated miRNAs-including, prominently, miRNA-34a-have complimentary RNA sequences in the 3' untranslated-region (3'-UTR) of their target-mRNAs that results in the pathological down-regulation in the expression of important brain genes. An up-regulated microRNA-34a, already implicated in age-related inflammatory-neurodegeneration-appears to down-regulate key mRNA targets involved in synaptogenesis and synaptic-structure, distinguishing neuronal deficits associated with AD neuropathology. One significantly down-regulated post-synaptic element in AD is the proline-rich SH3 and multiple-ankyrin-repeat domain SHANK3 protein. Bioinformatics, microRNA array analysis and SHANK3-mRNA-3'UTR luciferase-reporter assay confirmed the importance of miRNA-34a in the regulation of SHANK3 expression in HNG cells. This paper reports on recent studies of a miRNA-34a-up-regulation coupled to SHANK3 mRNA down-regulation in sporadic AD superior-temporal lobe compared to age-matched controls. These findings further support our hypothesis of an altered miRNA-mRNA coupled signaling network in AD, much of which is supported, and here reviewed, by recently reported experimental-findings in the scientific literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".