Towards an early diagnosis of HIV infection: an electrochemical approach for detection ofHIV-1 reverse transcriptase enzyme
Bibliographic record
Abstract
Oriented for the rapid diagnosis of HIV infection, highly sensitive and facile electrochemical assays for HIV-1 reverse transcriptase (HIV1-RT) are presented in this article. A non-labeled and a labeled assay format were based on the formation of self-assembled monolayers (SAMs) of either lipoic acid active ester or a newly synthesized ferrocene (Fc)-labeled cystamine derivative on electrode surfaces, respectively. A short RT-specific peptide, VEAIIRILQQLLFIH, was covalently attached to the surface of the formed SAMs. Electrochemical impedance spectroscopy (EIS) allowed a sensitive interrogation of RT in the non-labeled assay format. Furthermore, square wave voltammetry (SWV) offered a two-dimensional measurement of RT based on the anodic shift and reduction of current density of the Fc redox signal upon binding of RT to its specific peptide. These techniques allowed a linear quantification of the target RT in the range of 75 to 750 pg mL(-1), with a limit of detection of 50 pg mL(-1). Furthermore, the developed biosensors showed a good specificity and allowed a proper discrimination between RT and other HIV enzymes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".