HIV-associated sensory polyneuropathy and neuronal injury are associated with miRNA–455-3p induction
Bibliographic record
Abstract
Symptomatic distal sensory polyneuropathy (sDSP) is common and debilitating in people with HIV/AIDS, leading to neuropathic pain, although the condition's cause is unknown. To investigate biomarkers and associated pathogenic mechanisms for sDSP, we examined plasma miRNA profiles in HIV/AIDS patients with sDSP or without sDSP in 2 independent cohorts together with assessing related pathogenic effects. Several miRNAs were found to be increased in the Discovery Cohort (sDSP, n = 29; non-DSP, n = 40) by array analyses and were increased in patients with sDSP compared with patients without sDSP. miR-455-3p displayed a 12-fold median increase in the sDSP group, which was confirmed by machine learning analyses and verified by reverse transcription PCR. In the Validation Cohort (sDSP n = 16, non-DSP n = 20, healthy controls n = 15), significant upregulation of miR-455-3p was also observed in the sDSP group. Bioinformatics revealed that miR-455-3p targeted multiple host genes implicated in peripheral nerve maintenance, including nerve growth factor (NGF) and related genes. Transfection of cultured human dorsal root ganglia with miR-455-3p showed a concentration-dependent reduction in neuronal β-III tubulin expression. Human neurons transfected with miR-455-3p demonstrated reduced neurite outgrowth and NGF expression that was reversed by anti-miR-455-3p antagomir cotreatment. miR-455-3p represents a potential biomarker for HIV-associated sDSP and might also exert pathogenic effects leading to sDSP.
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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 | 0.001 | 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".