Analysis of Novel NEFL mRNA Targeting microRNAs in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by progressive motor neuron degeneration and neurofilament aggregate formation. Spinal motor neurons in ALS also show a selective suppression in the levels of low molecular weight neurofilament (NEFL) mRNA. We have been interested in investigating the role of microRNAs (miRNAs) in NEFL transcript stability. MiRNAs are small, 20-25 nucleotide, non-coding RNAs that act as post-transcriptional gene regulators by targeting the 3' untranslated region (3'UTR) of mRNA resulting in mRNA decay or translational silencing. In this study, we characterized putative novel miRNAs from a small RNA library derived from control and sporadic ALS (sALS) spinal cords. We detected 80 putative novel miRNAs, 24 of which have miRNA response elements (MREs) within the NEFL mRNA 3'UTR. From this group, we determined by real-time PCR that 10 miRNAs were differentially expressed in sALS compared to controls. Functional analysis by reporter gene assay and relative quantitative RT-PCR showed that two novel miRNAs, miR-b1336 and miR-b2403, were downregulated in ALS spinal cord and that both stabilize NEFL mRNA. We confirmed the direct effect of these latter miRNAs using anit-miR-b1336 and anti-miR-b2403. These results demonstrate that the expression of two miRNAs (miRNAs miR-b1336 and miR-b2403) whose effect is to stabilize NEFL mRNA are down regulated in ALS, the net effect of which is predicted to contribute directly to the loss of NEFL steady state mRNA which is pathognomic of spinal motor neurons in ALS.
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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 | 0.000 |
| 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".