scholarly journals Accurate Prediction of Antibody Resistance in Clinical HIV-1 Isolates

2018 ◽  
Author(s):  
Reda Rawi ◽  
Raghvendra Mall ◽  
Chen-Hsiang Shen ◽  
Nicole A. Doria-Rose ◽  
S. Katie Farney ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Trials ◽  
Neutralizing Antibodies ◽  
Gradient Boosting ◽  
Clinical Settings ◽  
Gradient Boosting Machine ◽  
Resistant Strains ◽  
Antibody Resistance ◽  
Hiv 1

Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection with several undergoing clinical trials. Due to high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to particular bNAbs. Resistant strains are commonly identified by time-consuming and expensive in vitro neutralization experiments. Here, we developed machine learning-based classifiers that accurately predict resistance of HIV-1 strains to 33 neutralizing antibodies. Notably, our classifiers achieved an overall prediction accuracy of 96% for 212 clinical isolates from patients enrolled in four different clinical trials. Moreover, use of the tree-based machine learning method gradient boosting machine enabled us to identify critical epitope features that distinguish between antibody resistance and sensitivity. The availability of an in silico antibody resistance predictor will facilitate informed decisions of antibody usage in clinical settings.

scholarly journals Accurate Prediction for Antibody Resistance of Clinical HIV-1 Isolates

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Reda Rawi ◽  
Raghvendra Mall ◽  
Chen-Hsiang Shen ◽  
S. Katie Farney ◽  
Andrea Shiakolas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Trials ◽  
Neutralizing Antibodies ◽  
Viral Escape ◽  
Gradient Boosting ◽  
Clinical Settings ◽  
Gradient Boosting Machine ◽  
Antibody Resistance ◽  
Hiv 1

Abstract Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to specific bNAbs. Currently, resistant isolates are commonly identified by time-consuming and expensive in vitro neutralization assays. Here, we report machine learning classifiers that accurately predict resistance of HIV-1 isolates to 33 bNAbs. Notably, our classifiers achieved an overall prediction accuracy of 96% for 212 clinical isolates from patients enrolled in four different clinical trials. Moreover, use of gradient boosting machine – a tree-based machine learning method – enabled us to identify critical features, which had high accordance with epitope residues that distinguished between antibody resistance and sensitivity. The availability of an in silico antibody resistance predictor should facilitate informed decisions of antibody usage and sequence-based monitoring of viral escape in clinical settings.

Focus on the therapeutic efficacy of 3BNC117 against HIV-1: In vitro studies, in vivo studies, clinical trials and challenges

2017 ◽  
Vol 52 ◽  
pp. 44-50 ◽  
Author(s):  
Zhi-Jun Liu ◽  
Jing Bai ◽  
Feng-Li Liu ◽  
Xiang-Yang Zhang ◽  
Jing-Zhang Wang
Keyword(s):  
Clinical Trials ◽  
Therapeutic Efficacy ◽  
In Vitro Studies ◽  
In Vivo Studies ◽  
Hiv 1

scholarly journals Data Analytics for Monitoring the Satisfactory Parameters of Airline Passengers using Machine Learning Algorithms in Python

2020 ◽  
Vol 9 (3) ◽  
pp. 1231-1235
Keyword(s):  
Machine Learning ◽  
Data Analytics ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Complex Information ◽  
Huge Data ◽  
Gradient Boosting Machine ◽  
Airline Passengers ◽  
Effective Representation

An effective representation by machine learning algorithms is to obtain the results especially in Big Data, there are numerous applications can produce outcome, whereas a Random Forest Algorithm (RF) Gradient Boosting Machine (GBM), Decision tree (DT) in Python will able to give the higher accuracy in regard with classifying various parameters of Airliner Passengers satisfactory levels. The complex information of airline passengers has provided huge data for interpretation through different parameters of satisfaction that contains large information in quantity wise. An algorithm has to support in classifying these data’s with accuracies. As a result some of the methods may provide less precision and there is an opportunity of information cancellation and furthermore information missing utilizing conventional techniques. Subsequently RF and GBM used to conquer the unpredictability and exactness about the information provided. The aim of this study is to identify an Algorithm which is suitable for classifying the satisfactory level of airline passengers with data analytics using python by knowing the output. The optimization and Implementation of independent variables by training and testing for accuracy in python platform determined the variation between the each parameters and also recognized RF and GBM as a better algorithm in comparison with other classifying algorithms.

scholarly journals Evaluation of HIV-1 latency reversal and antibody-dependent viral clearance by quantification of singly spliced HIV-1 vpu/env mRNA

2021 ◽  
Author(s):  
Hongbo Gao ◽  
Ayşe N. Ozantürk ◽  
Qiankun Wang ◽  
Gray H. Harlan ◽  
Aaron J. Schmitz ◽  
...  
Keyword(s):  
T Cells ◽  
Neutralizing Antibodies ◽  
Ex Vivo ◽  
Viral Envelope ◽  
Latent Reservoir ◽  
Broadly Neutralizing Antibodies ◽  
Major Barrier ◽  
Hiv 1 ◽  
Reversing Agents

The latent reservoir of HIV-1 is a major barrier for viral eradication. Potent HIV-1 broadly neutralizing antibodies (bNabs) have been used to prevent and treat HIV-1 infections in animal models and clinical trials. Combination of bNabs and latency-reversing agents (LRAs) is considered a promising approach for HIV-1 eradication. PCR-based assays that can rapidly and specifically measure singly spliced HIV-1 vpu/env mRNA are needed to evaluate the induction of the viral envelope production at the transcription level and bNab-mediated reservoir clearance. Here we reported a PCR-based method to accurately quantify the production of intracellular HIV-1 vpu/env mRNA. With the vpu/env assay, we determined the LRA combinations that could effectively induce vpu/env mRNA production in CD4+ T cells from ART-treated individuals. None of the tested LRAs were effective alone. A comparison between the quantitative viral outgrowth assay (Q-VOA) and the vpu/env assay showed that vpu/env mRNA production was closely associated with the reactivation of replication-competent HIV-1, suggesting that vpu/env mRNA was mainly produced by intact viruses. Finally, antibody-mediated in vitro killing in HIV-1-infected humanized mice demonstrated that the vpu/env assay could be used to measure the reduction of infected cells in tissues and was more accurate than the commonly used gag-based PCR assay which measured unspliced viral genomic RNA. In conclusion, the vpu/env assay allows convenient and accurate assessment of HIV-1 latency reversal and bNab-mediated therapeutic strategies. Importance HIV-1 persists in individuals on antiretroviral therapy (ART) due to the long-lived cellular reservoirs that contain dormant viruses. Recent discoveries of HIV-1-specific broadly neutralizing antibodies (bNabs) targeting HIV-1 Env protein rekindled the interest in antibody-mediated elimination of latent HIV-1. Latency-reversing agents (LRAs) together with HIV-1 bNabs is a possible strategy to clear residual viral reservoirs, which makes the evaluation of HIV-1 Env expression upon LRA treatment critical. We developed a PCR-based assay to quantify the production of intracellular HIV-1 vpu/env mRNA. Using patient CD4+ T cells, we found that induction of HIV-1 vpu/env mRNA required a combination of different LRAs. Using in vitro, ex vivo and humanized mouse models, we showed that the vpu/env assay could be used to measure antibody efficacy in clearing HIV-1 infection. These results suggest that the vpu/env assay can accurately evaluate HIV-1 reactivation and bNab-based therapeutic interventions.

Development of a Diabetes Melitus Detection and Prediction Model Using Light Gradient Boosting Machine and K-Nearest Neighbour

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
B. A Omodunbi
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Hybrid Model ◽  
Learning Model ◽  
Experimental Result ◽  
Gradient Boosting ◽  
Light Gradient ◽  
Machine Learning Model ◽  
Gradient Boosting Machine ◽  
Receiver Operating

Diabetes mellitus is a health disorder that occurs when the blood sugar level becomes extremely high due to body resistance in producing the required amount of insulin. The aliment happens to be among the major causes of death in Nigeria and the world at large. This study was carried out to detect diabetes mellitus by developing a hybrid model that comprises of two machine learning model namely Light Gradient Boosting Machine (LGBM) and K-Nearest Neighbor (KNN). This research is aimed at developing a machine learning model for detecting the occurrence of diabetes in patients. The performance metrics employed in evaluating the finding for this study are Receiver Operating Characteristics (ROC) Curve, Five-fold Cross-validation, precision, and accuracy score. The proposed system had an accuracy of 91% and the area under the Receiver Operating Characteristic Curve was 93%. The experimental result shows that the prediction accuracy of the hybrid model is better than traditional machine learning

HTLV-II down-regulates HIV-1 replication in IL-2–stimulated primary PBMC of coinfected individuals through expression of MIP-1α

Blood ◽  
2000 ◽  
Vol 95 (9) ◽  
pp. 2760-2769 ◽  
Author(s):  
Claudio Casoli ◽  
Elisa Vicenzi ◽  
Andrea Cimarelli ◽  
Giacomo Magnani ◽  
Paolo Ciancianaini ◽  
...  
Keyword(s):  
T Cells ◽  
Neutralizing Antibodies ◽  
Ex Vivo ◽  
Interleukin 2 ◽  
Peripheral Blood Mononuclear ◽  
Human T Cell ◽  
Cc Chemokines ◽  
Kinetics Of ◽  
Hiv 1

The influence of human T-cell leukemia/lymphoma virus type II (HTLV-II) in individuals also infected with HIV-1 is poorly understood. To evaluate the reciprocal influence of HTLV-II and HIV-1 infection, primary peripheral blood mononuclear cell (PBMC) cultures from coinfected individuals were established in the presence of interleukin 2 (IL-2). In these cultures, the kinetics of HTLV-II replication always preceded those of HIV-1. Noteworthy, the kinetics of HIV-1 production were inversely correlated to the HTLV-II proviral load in vivo and its replication ex vivo. These observations suggested a potential interaction between the 2 retroviruses. In this regard, the levels of IL-2, IL-6, and tumor necrosis factor- (TNF-) were measured in the same coinfected PBMC cultures. Endogenous IL-2 was not produced, whereas IL-6 and TNF- were secreted at levels compatible with their known ability to up-regulate HIV-1 expression. The HIV-suppressive CC-chemokines RANTES, macrophage inflammatory protein-1 (MIP-1), and MIP-1β were also determined in IL-2–stimulated PBMC cultures. Of interest, their kinetics and concentrations were inversely related to those of HIV-1 replication. Experiments were performed in which CD8+ T cells or PBMCs from HTLV-II monoinfected individuals were cocultivated with CD4+ T cells from HIV-1 monoinfected individuals separated by a semipermeable membrane in the presence or absence of antichemokine neutralizing antibodies. The results indicate that HTLV-II can interfere with the replicative potential of HIV-1 by up-regulating viral suppressive CC-chemokines and, in particular, MIP-1. This study is the first report indicating that HTLV-II can influence HIV replication, at least in vitro, via up-regulation of HIV-suppressive chemokines.

scholarly journals Autologous IgG antibodies block outgrowth of a substantial but variable fraction of viruses in the latent reservoir for HIV-1

2020 ◽  
Vol 117 (50) ◽  
pp. 32066-32077
Author(s):  
Lynn N. Bertagnolli ◽  
Joseph Varriale ◽  
Sarah Sweet ◽  
Jacqueline Brockhurst ◽  
Francesco R. Simonetti ◽  
...  
Keyword(s):  
T Cell Activation ◽  
Neutralizing Antibodies ◽  
Cell Activation ◽  
Viral Evolution ◽  
Treatment Interruption ◽  
Latent Reservoir ◽  
Env Protein ◽  
Autologous Antibodies ◽  
Hiv 1

In untreated HIV-1 infection, rapid viral evolution allows escape from immune responses. Viral replication can be blocked by antiretroviral therapy. However, HIV-1 persists in a latent reservoir in resting CD4+ T cells, and rebound viremia occurs following treatment interruption. The reservoir, which is maintained in part by clonal expansion, can be measured using quantitative viral outgrowth assays (QVOAs) in which latency is reversed with T cell activation to allow viral outgrowth. Recent studies have shown that viruses detected in QVOAs prior to treatment interruption often differ from rebound viruses. We hypothesized that autologous neutralizing antibodies directed at the HIV-1 envelope (Env) protein might block outgrowth of some reservoir viruses. We modified the QVOA to reflect pressure from low concentrations of autologous antibodies and showed that outgrowth of a substantial but variable fraction of reservoir viruses is blocked by autologous contemporaneous immunoglobulin G (IgG). A reduction in outgrowth of >80% was seen in 6 of 15 individuals. This effect was due to direct neutralization. We established a phylogenetic relationship between rebound viruses and viruses growing out in vitro in the presence of autologous antibodies. Some large infected cell clones detected by QVOA carried neutralization-sensitive viruses, providing a cogent explanation for differences between rebound virus and viruses detected in standard QVOAs. Measurement of the frequency of reservoir viruses capable of outgrowth in the presence of autologous IgG might allow more accurate prediction of time to viral rebound. Ultimately, therapeutic immunization targeting the subset of variants resistant to autologous IgG might contribute to a functional cure.

scholarly journals A Novel MVA-Based HIV Vaccine Candidate (MVA-gp145-GPN) Co-Expressing Clade C Membrane-Bound Trimeric gp145 Env and Gag-Induced Virus-Like Particles (VLPs) Triggered Broad and Multifunctional HIV-1-Specific T Cell and Antibody Responses

Viruses ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 160 ◽  
Author(s):  
Beatriz Perdiguero ◽  
Cristina Sánchez-Corzo ◽  
Carlos Sorzano ◽  
Lidia Saiz ◽  
Pilar Mediavilla ◽  
...  
Keyword(s):  
Neutralizing Antibodies ◽  
Vaccine Candidate ◽  
Hiv Vaccine ◽  
Replication Capacity ◽  
Virus Like Particles ◽  
Modified Vaccinia Virus Ankara ◽  
Clade C ◽  
Membrane Bound ◽  
Hiv 1

The development of an effective Human Immunodeficiency Virus (HIV) vaccine that is able to stimulate both the humoral and cellular HIV-1-specific immune responses remains a major priority challenge. In this study, we described the generation and preclinical evaluation of single and double modified vaccinia virus Ankara (MVA)-based candidates expressing the HIV-1 clade C membrane-bound gp145(ZM96) trimeric protein and/or the Gag(ZM96)-Pol-Nef(CN54) (GPN) polyprotein that was processed to form Gag-induced virus-like particles (VLPs). In vitro characterization of MVA recombinants revealed the stable integration of HIV-1 genes without affecting its replication capacity. In cells that were infected with Env-expressing viruses, the gp145 protein was inserted into the plasma membrane exposing critical epitopes that were recognized by broadly neutralizing antibodies (bNAbs), whereas Gag-induced VLPs were released from cells that were infected with GPN-expressing viruses. VLP particles as well as purified MVA virions contain Env and Gag visualized by immunoelectron microscopy and western-blot of fractions that were obtained after detergent treatments of purified virus particles. In BALB/c mice, homologous MVA-gp145-GPN prime/boost regimen induced broad and polyfunctional Env- and Gag-specific CD4 T cells and antigen-specific T follicular helper (Tfh) and Germinal Center (GC) B cells, which correlated with robust HIV-1-specific humoral responses. Overall, these results support the consideration of MVA-gp145-GPN vector as a potential vaccine candidate against HIV-1.

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