Treatment with integrase inhibitor suggests a new interpretation of HIV RNA decay curves that reveals a subset of cells with slow integration.

The kinetics of HIV-1 decay under treatment depends on the class of antiretrovirals used. Mathematical models are useful to interpret the different profiles, providing quantitative information about the kinetics of virus replication and the cell populations contributing to viral decay. We modeled proviral integration in short- and long-lived infected cells to compare viral kinetics under treatment with and without the integrase inhibitor raltegravir (RAL). We fitted the model to data obtained from participants treated with RAL-containing regimes or with a four-drug regimen of protease and reverse transcriptase inhibitors. Our model explains the existence and quantifies the three phases of HIV-1 RNA decay in RAL-based regimens vs. the two phases observed in therapies without RAL. Our findings indicate that HIV-1 infection is mostly sustained by short-lived infected cells with fast integration and a short viral production period, and by long-lived infected cells with slow integration but an equally short viral production period. We propose that these cells represent activated and resting infected CD4+ T-cells, respectively, and estimate that infection of resting cells represent ~4% of productive reverse transcription events in chronic infection. RAL reveals the kinetics of proviral integration, showing that in short-lived cells the pre-integration population has a half-life of ~7 hours, whereas in long-lived cells this half-life is ~6 weeks. We also show that the efficacy of RAL can be estimated by the difference in viral load at the start of the second phase in protocols with and without RAL. Overall, we provide a mechanistic model of viral infection that parsimoniously explains the kinetics of viral load decline under multiple classes of antiretrovirals.

Spatial modeling of HIV cryptic viremia and 2-LTR formation during raltegravir intensification.

Combination Antiretroviral Therapy (cART) can suppress plasma HIV below the limit of detection in normal assays. Recently reported results suggest that viral replication may continue in some patients, despite undetectable levels in the blood. It has been suggested that the appearance of the circularized episomal HIV DNA artifact 2-LTR following treatment intensification with the integrase inhibitor raltegravir is a marker of ongoing viral replication. Other work has suggested that lymphoid organs may be a site of reduced antiviral penetration and increased viral production. In this study we model the hypothesis that this ongoing replication occurs in lymphoid follicle sanctuary sites and investigate the patterns of 2-LTR formation expected after raltegravir application. Experimental data is used to estimate the reaction and diffusion parameters in the model, and Monte-Carlo simulations are used to explore model behavior subject to variation in these rates. The results suggest that conditions for the formation of an observed transient peak in 2-LTR formation following raltegravir intensification include a sanctuary site diameter larger than 0.2mm, a viral basic reproductive ratio within the site larger than 1, and a total volume of active sanctuary sites above 20mL. Significant levels of uncontrolled replication can occur in the sanctuary sites without measurable changes in the plasma viral load. By contrast, subcritical replication (where the basic reproductive ratio of the virus is less than 1 in all sites) always results in monotonic increases of measured 2-LTR following raltegravir intensification, occurring at levels below the limit of detection.

Increased inflammation in sanctuary sites may explain viral blips in HIV infection.

Combined antiretroviral therapy (cART) suppress HIV-1 viral replication, such that viral load in plasma remains below the limit of detection in standard assays. However, intermittent episodes of transient viremia (blips) occur in a set of HIV-patients. Given that follicular hyperplasia occurs during lymphoid inflammation as a normal response to infection, it is hypothesised that when the diameter of the lymph node follicle (LNF) increases and crosses a critical size, a viral blip occurs due to cryptic viremia. To study this hypothesis, a theoretical analysis of a mathematical model is performed to find the conditions for virus suppression in all compartments and different scenarios of LNF size changes are simulated. According to the analysis, blips with duration of around 30 days arise when the diameter rise rate is between 0.02 and 0.03 days(-1). Moreover, the final diameter of the site is directly related to the steady states of the virus load after the occurrence of a blip. When the value of R0 is around 2.1, to have a steady-state below the limit of detection after the viral blip, the maximum final diameters should be greater than 0.7 mm so that there is a relative loss of connection between compartments.

Modelling HIV-1 2-LTR dynamics following raltegravir intensification.

A model of reservoir activation and viral replication is introduced accounting for the production of 2-LTR HIV-1 DNA circles following antiviral intensification with the HIV integrase inhibitor raltegravir, considering contributions of de novo infection events and exogenous sources of infected cells, including quiescent infected cell activation. The model shows that a monotonic increase in measured 2-LTR concentration post intensification is consistent with limited de novo infection primarily maintained by sources of infected cells unaffected by raltegravir, such as quiescent cell activation, while a transient increase in measured 2-LTR concentration is consistent with significant levels of efficient (R0 > 1) de novo infection. The model is validated against patient data from the INTEGRAL study and is shown to have a statistically significant fit relative to the null hypothesis of random measurement variation about a mean. We obtain estimates and confidence intervals for the model parameters, including 2-LTR half-life. Seven of the 13 patients with detectable 2-LTR concentrations from the INTEGRAL study have measured 2-LTR dynamics consistent with significant levels of efficient replication of the virus prior to treatment intensification.

Measurement error robustness of a closed-loop minimal sampling method for HIV therapy switching.

We test the robustness of a closed-loop treatment scheduling method to realistic HIV viral load measurement error. The purpose of the algorithm is to allow the accurate detection of an induced viral load minimum with a reduced number of samples. Therapy must be switched at or near the viral-load minimum to achieve optimal therapeutic benefit; therapeutic benefit decreases logarithmically with increased viral load at the switching time. The performance of the algorithm is characterized using a number of metrics. These include the number of samples saved vs. fixed-rate sampling, the risk-reduction achieved vs. the risk-reduction possible with frequent sampling, and the difference between the switching time vs. the theoretical optimal switching time. The algorithm is applied to simulated patient data generated from a family of data-driven patient models and corrupted by experimentally confirmed levels of log-normal noise.

Aprendizaje de clases de equivalencia de redes bayesianas basado en búsqueda competitiva de hormigas artificiales / Learning of bayesian networks equivalence classes based on competitive search of artificial ants

Este artículo propone un algoritmo de aprendizaje de clases de equivalencia de redes bayesianas basado en un algoritmo de búsqueda Greedy y modelos de búsqueda inspirados en hormigas competitivas. Específicamente para el algoritmo propuesto, se obtuvo una mejor aproximación entre la red predicha y la red bayesiana teórica de ejemplo ASIA, con respecto a algoritmos anteriores, para conjuntos de datos con 20 y 500 muestras. En promedio el algoritmo desarrollado obtuvo una aproximación con respecto a la distancia estructural de hamming de 10.7% y 5.3% menor comparada con la obtenida por los algoritmos Greedy y de colonia de hormigas (ACO-E) respectivamente para 20 muestras, y de hasta el 6.8% menor con respecto al algoritmo ACO-E para 500 muestras. Además, para 500 muestras el número de llamadas a la función de puntaje realizadas por el algoritmo propuesto fue menor que las realizadas por el algoritmo ACO-E en el 90% de las combinaciones, concluyendo que hubo una reducción de la complejidad computacional. Finalmente se presentan los resultados de la aplicación del algoritmo propuesto a un microarreglo obtenido por muestras de pacientes con Leucemia Mieloide Aguda (LMA) con 6 nuevas interacciones con dependencias estadísticas como potenciales interacciones biológicas con alta probabilidad.

This article proposes an algorithm for learning equivalence classes of Bayesian networks based on a Greed search algorithm and search patterns inspired by competitive ants. Specifically, for the proposed algorithm, we obtained a better approximation between the predicted network and the theoretical network ASIA with respect to previous algorithms for data sets with 20 and 500 samples. On average, the algorithm developed an approximation with respect to Structural Hamming Distance of 10.7% and 5.3% lower than Greedy algorithms and ACO-E respectively to 20 samples, and up to 6.8% lower tan ACO-E algorithm for 500 samples. Furthermore, for 500 samples the number of calls to the scoring function performed by the algorithm proposed was smaller than in the ACO-E algorithm in 90% of the combinations, concluding that there was a reduction in the computational complexity. Finally, we present the results of applying the proposed algorithm to a microarray samples obtained from patients with acute myeloid leukemia (AML) with 6 new interactions with statistical dependencies as potential biological interactions with high probability.