Explore the vast range of titles available.

The inadequacy of HIV viraemia and resistance monitoring in Africa leads to uncontrolled circulation of HIV strains with drug resistance mutations (DRM), compromising antiretroviral therapy (ART) effectiveness. This study describes the DRM prevalence and its therapeutic impact in HIV-infected pediatric patients from Kinshasa (Democratic Republic of Congo, DRC). From 2016-2018, dried blood were collected from 71 HIV-infected children and adolescents under ART in two hospitals in Kinshasa for HIV-1 DRM pol analysis, predicted ARV-susceptibility by Stanford and phylogenetic characterization. HIV-1 sequences were recovered from 55 children/adolescents with 14 years of median-age. All had received nucleoside and non-nucleoside reverse transcriptase inhibitors (NRTI, NNRTI), 9.1% protease inhibitors (PI) and only one integrase inhibitor (INI). Despite the use of ART, 89.1% showed virological failure and 67.3% carried viruses with major-DRM to one (12.7%), two (47.3%), or three (5.5%) ARV-families. Most children/adolescents harbored DRM to NNRTI (73.5%) or NRTI (61.2%). Major-DRM to PI was present in 8.3% and minor-DRM to INI in 15%. Dual-class-NRTI+NNRTI resistance appeared in 53.1% of patients. Viruses presented high/intermediate resistance to nevirapine (72.9% patients), efavirenz (70.9%), emtricitabine/lamivudine (47.9%), rilpivirine (41.7%), etravirine (39.6%), doravidine (33.3%), zidovudine (22.9%), among others. Most participants were susceptible to INI and PI. Great diversity of variants was found, with a high rate (40%) of unique recombinants. The high DRM prevalence observed among HIV-infected children and adolescents in Kinshasa could compromise the 95-95-95-UNAIDS targets in the DRC. It also reinforces the need for routine resistance monitoring for optimal rescue therapy election in this vulnerable population to control the spread of resistant HIV in the country.

Motivation: Genetic sequence analysis has become essential in many medicine, biology, and epidemiology fields. However, the currently available tools can pose a challenge for users without advanced computational skills. Results: We present EpiMolBio, a free-to-use software designed with an intuitive, user- friendly interface that enables a broad spectrum of users to explore genetic variability. Its diverse toolkit encompasses sequence processing, conservation and variability analysis, consensus sequence generation, and genome mutation or amino acid changes identification, including specialized tools for HIV and SARS-CoV-2 analysis. Availability: Freely available on the web at https://www.epimolbio.com and https://github.com/EpiMolBio/EpiMolBio.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://epimolbio.com/* https://github.com/EpiMolBio/EpiMolBio/tree/main