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Inhibitors against the NS3-4A protease of hepatitis C virus (HCV) have proven to be useful drugs in the treatment of HCV infection. Although variants have been identified with mutations that confer resistance to these inhibitors, the mutations do not restore replicative fitness and no secondary mutations that rescue fitness have been found. To gain insight into the molecular mechanisms underlying the lack of fitness compensation, we screened known resistance mutations in infectious HCV cell culture with different genomic backgrounds. We observed that the Q41R mutation of NS3-4A efficiently rescues the replicative fitness in cell culture for virus variants containing mutations at NS3-Asp168. To understand how the Q41R mutation rescues activity, we performed protease activity assays complemented by molecular dynamics simulations, which showed that protease-peptide interactions far outside the targeted peptide cleavage sites mediate substrate recognition by NS3-4A and support protease cleavage kinetics. These interactions shed new light on the mechanisms by which NS3-4A cleaves its substrates, viral polyproteins and a prime cellular antiviral adaptor protein, the mitochondrial antiviral signaling protein MAVS. Peptide binding is mediated by an extended hydrogen-bond network in NS3-4A that was effectively optimized for protease-MAVS binding in Asp168 variants with rescued replicative fitness from NS3-Q41R. In the protease harboring NS3-Q41R, the N-terminal cleavage products of MAVS retained high affinity to the active site, rendering the protease susceptible for potential product inhibition. Our findings reveal delicately balanced protease-peptide interactions in viral replication and immune escape that likely restrict the protease adaptive capability and narrow the virus evolutionary space.
Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
People with Parkinson’s disease (PD) experience a gradual loss of functional abilities that affects all facets of their daily life. There is a lack of longitudinal studies on coping styles in relation to the disease progression among people with PD. The aim of this study was to explore how coping styles in PD evolve over a 3-year period. Data from the longitudinal project “Home and Health in People Ageing with PD” was utilized (N = 158), including baseline and 3-year follow-up assessments. Coping was captured by ratings of 13 different coping styles. A factor analysis was conducted to analyse patterns of coping styles. Stability and change were analysed for each of the 13 styles with respect to the course of the disease. The factor analysis revealed four coping patterns: pessimistic, optimistic, persistent and support-seeking. The stability of each coping style over time ranged from 75.3% to 90.5%. Those who experienced a worsening of the disease were most inclined to change their coping style (p = 0.006). The results suggest that even when facing severe challenges due to PD in daily life, coping styles remain relatively stable over time. However, a worsening in PD severity appeared to trigger a certain re-evaluation of coping styles.
Operating in a reverberating regime enables rapid tuning of network states to task requirements
(2018)
Neural circuits are able to perform computations under very diverse conditions and requirements. The required computations impose clear constraints on their fine-tuning: a rapid and maximally informative response to stimuli in general requires decorrelated baseline neural activity. Such network dynamics is known as asynchronous-irregular. In contrast, spatio-temporal integration of information requires maintenance and transfer of stimulus information over extended time periods. This can be realized at criticality, a phase transition where correlations, sensitivity and integration time diverge. Being able to flexibly switch, or even combine the above properties in a task-dependent manner would present a clear functional advantage. We propose that cortex operates in a "reverberating regime" because it is particularly favorable for ready adaptation of computational properties to context and task. This reverberating regime enables cortical networks to interpolate between the asynchronous-irregular and the critical state by small changes in effective synaptic strength or excitation-inhibition ratio. These changes directly adapt computational properties, including sensitivity, amplification, integration time and correlation length within the local network. We review recent converging evidence that cortex in vivo operates in the reverberating regime, and that various cortical areas have adapted their integration times to processing requirements. In addition, we propose that neuromodulation enables a fine-tuning of the network, so that local circuits can either decorrelate or integrate, and quench or maintain their input depending on task. We argue that this task-dependent tuning, which we call "dynamic adaptive computation," presents a central organization principle of cortical networks and discuss first experimental evidence.
Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain “decide” what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function).