Phase 1/2 Open-label Dose-escalation Study of Plasmid DNA Expressing Two Isoforms of Hepatocyte Growth Factor in Patients With Painful Diabetic Peripheral Neuropathy
Bibliographic record
Abstract
This study aimed to evaluate the safety and preliminary efficacy of intramuscular injections of plasmid DNA (VM202) expressing two isoforms of hepatocyte growth factor (HGF) in subjects with painful diabetic peripheral neuropathy (PDPN). Twelve patients in three cohorts (4, 8, and 16 mg) received two sets of VM202 injections separated by two weeks. Safety and tolerability were evaluated and the visual analog scale (VAS), the short form McGill questionnaire (SF-MPQ), and the brief pain inventory for patients with diabetic peripheral neuropathy (BPI-DPN) measured pain level throughout 12 months after treatment. No serious adverse events (AEs) were observed. The mean VAS was reduced from baseline by 47.2% (P = 0.002) at 6 months and by 44.1% (P = 0.005) at 12 months after treatment. The VAS scores for the 4, 8, and 16 mg dose cohorts at 6 months follow-up decreased in a dose-responsive manner, by 21% (P = 0.971), 53% (P = 0.014), and 62% (P = 0.001), respectively. The results with the BPI-DPN and SF-MPQ showed patterns similar to the VAS scores. In conclusion, VM202 treatment appeared to be safe, well tolerated, and sufficient to provide long term symptomatic relief and improvement in the quality of life in patients with PDPN.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".