An “Escape Clock” for Estimating the Turnover of SIV DNA in Resting CD4+ T Cells

Persistence of HIV DNA presents a major barrier to the complete control of HIV infection under current therapies. Most studies suggest that cells with latently integrated HIV decay very slowly under therapy. However, it is much more difficult to study the turnover and persistence of HIV DNA during active infection. We have developed an “escape clock” approach for measuring the turnover of HIV DNA in resting CD4+ T cells. This approach studies the replacement of wild-type (WT) SIV DNA present in early infection by CTL escape mutant (EM) strains during later infection. Using a strain-specific real time PCR assay, we quantified the relative amounts of WT and EM strains in plasma SIV RNA and cellular SIV DNA. Thus we can track the formation and turnover of SIV DNA in sorted resting CD4+ T cells. We studied serial plasma and PBMC samples from 20 SIV-infected Mane-A*10 positive pigtail macaques that have a signature Gag CTL escape mutation. In animals with low viral load, WT virus laid down early in infection is extremely stable, and the decay of this WT species is very slow, consistent with findings in subjects on anti-retroviral medications. However, during active, high level infection, most SIV DNA in resting cells was turning over rapidly, suggesting a large pool of short-lived DNA produced by recent infection events. Our results suggest that, in order to reduce the formation of a stable population of SIV DNA, it will be important either to intervene very early or intervene during active replication

A causal account of the brain network computations underlying strategic social behavior

During competitive interactions, humans have to estimate the impact of their own actions on their opponent's strategy. Here we provide evidence that neural computations in the right temporoparietal junction (rTPJ) and interconnected structures are causally involved in this process. By combining inhibitory continuous theta-burst transcranial magnetic stimulation with model-based functional MRI, we show that disrupting neural excitability in the rTPJ reduces behavioral and neural indices of mentalizing-related computations, as well as functional connectivity of the rTPJ with ventral and dorsal parts of the medial prefrontal cortex. These results provide a causal demonstration that neural computations instantiated in the rTPJ are neurobiological prerequisites for the ability to integrate opponent beliefs into strategic choice, through system-level interaction within the valuation and mentalizing networks

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning

Metabolic changes in concussed American football players during the acute and chronic post-injury phases

<p>Abstract</p> <p>Background</p> <p>Despite negative neuroimaging findings many athletes display neurophysiological alterations and post-concussion symptoms that may be attributable to neurometabolic alterations.</p> <p>Methods</p> <p>The present study investigated the effects of sports concussion on brain metabolism using ¹H-MR Spectroscopy by comparing a group of 10 non-concussed athletes with a group of 10 concussed athletes of the same age (mean: 22.5 years) and education (mean: 16 years) within both the acute and chronic post-injury phases. All athletes were scanned 1-6 days post-concussion and again 6-months later in a 3T Siemens MRI.</p> <p>Results</p> <p>Concussed athletes demonstrated neurometabolic impairment in prefrontal and motor (M1) cortices in the acute phase where NAA:Cr levels remained depressed relative to controls. There was some recovery observed in the chronic phase where Glu:Cr levels returned to those of control athletes; however, there was a pathological increase of m-I:Cr levels in M1 that was only present in the chronic phase.</p> <p>Conclusions</p> <p>These results confirm cortical neurometabolic changes in the acute post-concussion phase as well as recovery and continued metabolic abnormalities in the chronic phase. The results indicate that complex pathophysiological processes differ depending on the post-injury phase and the neurometabolite in question.</p

A Novel Approach for Mining Polymorphic Microsatellite Markers In Silico

An important emerging application of high-throughput 454 sequencing is the isolation of molecular markers such as microsatellites from genomic DNA. However, few studies have developed microsatellites from cDNA despite the added potential for targeting candidate genes. Moreover, to develop microsatellites usually requires the evaluation of numerous primer pairs for polymorphism in the focal species. This can be time-consuming and wasteful, particularly for taxa with low genetic diversity where the majority of primers often yield monomorphic polymerase chain reaction (PCR) products. Transcriptome assemblies provide a convenient solution, functional annotation of transcripts allowing markers to be targeted towards candidate genes, while high sequence coverage in principle permits the assessment of variability in silico. Consequently, we evaluated fifty primer pairs designed to amplify microsatellites, primarily residing within transcripts related to immunity and growth, identified from an Antarctic fur seal (Arctocephalus gazella) transcriptome assembly. In silico visualization was used to classify each microsatellite as being either polymorphic or monomorphic and to quantify the number of distinct length variants, each taken to represent a different allele. The majority of loci (n = 36, 76.0%) yielded interpretable PCR products, 23 of which were polymorphic in a sample of 24 fur seal individuals. Loci that appeared variable in silico were significantly more likely to yield polymorphic PCR products, even after controlling for microsatellite length measured in silico. We also found a significant positive relationship between inferred and observed allele number. This study not only demonstrates the feasibility of generating modest panels of microsatellites targeted towards specific classes of gene, but also suggests that in silico microsatellite variability may provide a useful proxy for PCR product polymorphism

Searches for the Z gamma decay mode of the Higgs boson and for new high-mass resonances in pp collisions at root s=13 TeV with the ATLAS detector

This article presents searches for the Zγ decay of the Higgs boson and for narrow high-mass resonances decaying to Zγ, exploiting Z boson decays to pairs of electrons or muons. The data analysis uses 36.1 fb−1 of pp collisions at s√=13s=13 recorded by the ATLAS detector at the CERN Large Hadron Collider. The data are found to be consistent with the expected Standard Model background. The observed (expected — assuming Standard Model pp → H → Zγ production and decay) upper limit on the production cross section times the branching ratio for pp → H → Zγ is 6.6. (5.2) times the Standard Model prediction at the 95% confidence level for a Higgs boson mass of 125.09 GeV. In addition, upper limits are set on the production cross section times the branching ratio as a function of the mass of a narrow resonance between 250 GeV and 2.4 TeV, assuming spin-0 resonances produced via gluon-gluon fusion, and spin-2 resonances produced via gluon-gluon or quark-antiquark initial states. For high-mass spin-0 resonances, the observed (expected) limits vary between 88 fb (61 fb) and 2.8 fb (2.7 fb) for the mass range from 250 GeV to 2.4 TeV at the 95% confidence level