Non-clinical outcomes of antiretroviral therapy for HIV/AIDS in developing countries: a systematic literature review

The impacts of antiretroviral therapy on quality of life, mental health, labor productivity, and economic wellbeing for people living with HIV/AIDS in developing countries are only beginning to be measured. We conducted a systematic literature review to analyze the effect of antiretroviral therapy (ART) on these non-clinical indicators in developing countries and assess the state of research on these topics. Both qualitative and quantitative studies were included, as were peer-reviewed articles, gray literature, and conference abstracts and presentations. Findings are reported from 12 full-length articles, 7 abstracts, and 1 presentation (representing 16 studies). Compared to HIV-positive patients not yet on treatment, patients on ART reported significant improvements in physical, emotional and mental health and daily function. Work performance improved and absenteeism decreased, with the most dramatic changes occurring in the first three months of treatment and then leveling off. Little research has been done on the impact of ART on household wellbeing, with modest changes in child and family wellbeing within households where adults are receiving ART reported so far. Studies from developing countries have not yet assessed non-clinical outcomes of therapy beyond the first year; therefore, longitudinal outcomes are still unknown. As ART roll out extends throughout high HIV prevalence, low-resource countries and is sustained over years and decades, both positive and adverse non-clinical outcomes need to be empirically measured and qualitatively explored in order to support patient adherence and maximize treatment benefits.

Scalable Peer-to-Peer Indexing with Constant State

We present a distributed indexing scheme for peer to peer networks. Past work on distributed indexing traded off fast search times with non-constant degree topologies or network-unfriendly behavior such as flooding. In contrast, the scheme we present optimizes all three of these performance measures. That is, we provide logarithmic round searches while maintaining connections to a fixed number of peers and avoiding network flooding. In comparison to the well known scheme Chord, we provide competitive constant factors. Finally, we observe that arbitrary linear speedups are possible and discuss both a general brute force approach and specific economical optimizations.

Dopaminergic and Non-Dopaminergic Value Systems in Conditioning and Outcome-Specific Revaluation

Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal Values Triggers Option Revaluations) neural model. MOTIVATOR describes cognitiveemotional interactions between higher-order sensory cortices and an evaluative neuraxis composed of the hypothalamus, amygdala, and orbitofrontal cortex. Given a conditioned stimulus (CS), the model amygdala and lateral hypothalamus interact to calculate the expected current value of the subjective outcome that the CS predicts, constrained by the current state of deprivation or satiation. The amygdala relays the expected value information to orbitofrontal cells that receive inputs from anterior inferotemporal cells, and medial orbitofrontal cells that receive inputs from rhinal cortex. The activations of these orbitofrontal cells code the subjective values of objects. These values guide behavioral choices. The model basal ganglia detect errors in CS-specific predictions of the value and timing of rewards. Excitatory inputs from the pedunculopontine nucleus interact with timed inhibitory inputs from model striosomes in the ventral striatum to regulate dopamine burst and dip responses from cells in the substantia nigra pars compacta and ventral tegmental area. Learning in cortical and striatal regions is strongly modulated by dopamine. The model is used to address tasks that examine food-specific satiety, Pavlovian conditioning, reinforcer devaluation, and simultaneous visual discrimination. Model simulations successfully reproduce discharge dynamics of known cell types, including signals that predict saccadic reaction times and CS-dependent changes in systolic blood pressure.