Cell free miRNAs are pharmacodynamic biomarkers for enhanced Dicer activity by Enoxacin in human patients with Amyotrophic lateral sclerosis
Bibliographic record
Abstract
ABSTRACT The activity of the RNase III enzyme DICER is downregulated in both sporadic and genetic forms of Amyotrophic Lateral Sclerosis (ALS). Accordingly, hundreds of microRNAs (miRNAs) are broadly downregulated, leading to derepression of their mRNA targets. Enoxacin is a fluoroquinolone that enhances DICER activity and miRNA biogenesis. Here, we tested for the first time the molecular effect of Enoxacin on miRNA biogenesis in ALS patients and demonstrated that Enoxacin’s engagement with DICER can be pharmacodynamically monitored via miRNA levels in human subjects. In an investigator-initiated, first-in-human study (REALS1), we explored miRNAs as pharmacodynamic biomarkers of DICER activation. Patients with sporadic ALS received oral Enoxacin twice daily for 30 days in a double-blind, randomized clinical trial. The study demonstrated comparable Enoxacin levels in plasma and cerebrospinal fluid (CSF). Furthermore, an increase in cell-free miRNA levels in both plasma and CSF at all time points following Enoxacin treatment (400 mg or 800 mg/day), was measured relative to baseline. Additionally, no serious adverse events were reported. In conclusion, pharmacological enhancement of DICER activity by Enoxacin increases miRNA biogenesis in patients with ALS. These results support further investigation of Enoxacin efficacy in larger clinical trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".