Objectives: The aim was to evaluate the evolution of transmitted HIV-1 drug resistance (TDR) prevalence in antiretroviral therapy (ART)-naïve patients from 2006 to 2016.
Methods: HIV-1 sequences were retrieved from the Antiviral Response Cohort Analysis (ARCA) database and TDR was defined as detection of at least one mutation from the World Health Organization (WHO) surveillance list.
Results: We included protease/reverse transcriptase sequences from 3573 patients; 455 had also integrase sequences. Overall, 68.1% of the patients were Italian, the median CD4 count was 348 cells/μL [interquartile range (IQR) 169-521 cells/μL], and the median viral load was 4.7 log HIV-1 RNA copies/mL (IQR 4.1-5.3 log copies/mL). TDR was detected in 10.3% of patients: 6% carried mutations to nucleos(t)ide reverse transcriptase inhibitors (NRTIs), 4.4% to nonnucleos(t)ide reverse transcriptase inhibitors (NNRTIs), 2.3% to protease inhibitors (PIs), 0.2% to integrase strand transfer inhibitors (INSTIs) and 2.1% to at least two drug classes. TDR declined from 14.5% in 2006 to 7.3% in 2016 (P = 0.003): TDR to NRTIs from 9.9 to 2.9% (P = 0.003) and TDR to NNRTIs from 5.1 to 3.7% (P = 0.028); PI TDR remained stable. The proportion carrying subtype B virus declined from 76.5 to 50% (P < 0.001). The prevalence of TDR was higher in subtype B vs. non-B (12.6 vs. 4.9%, respectively; P < 0.001) and declined significantly in subtype B (from 17.1 to 8.8%; P = 0.04) but not in non-B subtypes (from 6.1 to 5.8%; P = 0.44). Adjusting for country of origin, predictors of TDR were subtype B [adjusted odds ratio (AOR) for subtype B vs. non-B 2.91; 95% confidence interval (CI) 1.93-4.39; P < 0.001], lower viral load (per log higher: AOR 0.86; 95% CI 0.75-0.99; P = 0.03), site in northern Italy (AOR for southern Italy/island vs. northern Italy, 0.61; 95% CI 0.40-0.91; P = 0.01), and earlier calendar year (per 1 year more recent: AOR 0.95; 95% CI 0.91-0.99; P = 0.02).
Conclusions: The prevalence of HIV-1 TDR has declined during the last 10 years in Italy.
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http://dx.doi.org/10.1111/hiv.12640 | DOI Listing |
J Virol
January 2025
SA MRC Antibody Immunity Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Parktown, Johannesburg, South Africa.
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School of Chemistry, Beihang University, Beijing 100191, China.
Dynamic density functional theory (DDFT) is a fruitful approach for modeling polymer dynamics, benefiting from its multiscale and hybrid nature. However, the Onsager coefficient, the only free parameter in DDFT, is primarily derived empirically, limiting the accuracy and broad application of DDFT. Herein, we propose a machine learning-based, bottom-up workflow to directly extract the Onsager coefficient from molecular simulations, circumventing partly heuristic assumptions in traditional approaches.
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Department of Dravyaguna, Mahatma Gandhi Ayurved College, Hospital and Research Centre, Salod (H), Datta Meghe Institute of Higher Education and Research (Deemed to be University), Wardha, Maharashtra, India.
Teaching and learning are two sides of the same coin. Ayurveda, the ancient system of medicine that originated in India, has a long history of teaching and learning methods. In the early days, Ayurvedic knowledge was primarily transmitted through oral tradition, with teachers passing down their knowledge to students through direct communication.
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Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA.
The emergence of the Omicron lineage represented a major genetic drift in SARS-CoV-2 evolution. This was associated with phenotypic changes including evasion of pre-existing immunity and decreased disease severity. Continuous evolution within the Omicron lineage raised concerns of potential increased transmissibility and/or disease severity.
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