Comparación de tres métodos genotípicos para la detección de resistencia del VIH-1 a los antirretrovirales
Bibliographic record
Abstract
espanolCon la aparicion de nuevos antirretrovirales ha mejorado considerablemente la expectativa de vida de los pacientes infectados por el virus de la inmunodeficiencia humana (VIH), pero mutaciones en la region que codifica la transcriptasa inversa (TI) y la proteasa (P) del VIH-1 pueden producir fallos en el tratamiento, por lo cual los estudios de resistencia pueden ser de utilidad para la seleccion del tratamiento mas eficaz. El objetivo de nuestro trabajo ha sido comparar tres metodos genotipicos de deteccion de resistencias para valorar cual puede resultar mas adecuado en el laboratorio. Se han estudiado un total de 90 pacientes tratados con antirretrovirales, mediante tres metodos diferentes: hibridacion reversa que identifica la presencia de virus salvaje o mutante en 19 codones clave para las regiones de transcriptasa inversa y proteasa, InnoLiPA HIV-1 (Line Probe Assay, Innogenetics, Belgica), y dos de secuenciacion, ViroSeq HIV-1 Genotyping System (Perkin Elmer/Applied Biosystems, California) y TrueGene HIV-1 Genotyping System (Visible Genetics, Canada). Se detectaron 408 mutaciones por InnoLiPA, 572 por TrueGene y 721 por ViroSeq. La hibridacion detecto un numero significativamente superior de mutaciones primarias, asociadas con los grados de resistencia mas altos (p EnglishHighly active antiretroviral therapy has dramatically improved the life expectancy of human immunodeficiency virus (HIV)-infected patients, but mutations in the HIV-1 reverse transcriptase (RT) and protease (P) genes confer drug failure. Evaluation of drug resistance genotyping in HIV-1 has proven to be useful for the selection of drug combinations with maximum antiretroviral activity. The aim of this study was to evaluate the optimal procedure to determine the resistance profile in the laboratory. Plasma from 90 antiretroviral-treated patients was analyzed by reverse hybridization, which identifies the presence of wild-types or mutations at the 19 key codons for protease and RT regions, and was compared with two other methods of direct cDNA sequencing. A total of 408 mutations were detected by InnoLiPA HIV-1, (Line Probe Assay, Innogenetics, Belgium), 572 by TrueGene HIV-1 Genotyping System (Visible Genetics, Canada), and 721 by ViroSeq HIV-1 Genotyping System (Perkin Elmer/Applied Biosystems, California). Hybridization detected a significantly higher number of primary mutations which are associated with a high level of drug resistance (p
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".