The HIV-1 Nucleocapsid Regulates Its Own Condensation by Phase-Separated Activity-Enhancing Sequestration of the Viral Protease during Maturation

A growing number of studies indicate that mRNAs and long ncRNAs can affect protein populations by assembling dynamic ribonucleoprotein (RNP) granules. These phase-separated molecular ‘sponges’, stabilized by quinary (transient and weak) interactions, control proteins involved in numerous biological functions. Retroviruses such as HIV-1 form by self-assembly when their genomic RNA (gRNA) traps Gag and GagPol polyprotein precursors. Infectivity requires extracellular budding of the particle followed by maturation, an ordered processing of ∼2400 Gag and ∼120 GagPol by the viral protease (PR). This leads to a condensed gRNA-NCp7 nucleocapsid and a CAp24-self-assembled capsid surrounding the RNP. The choreography by which all of these components dynamically interact during virus maturation is one of the missing milestones to fully depict the HIV life cycle. Here, we describe how HIV-1 has evolved a dynamic RNP granule with successive weak–strong–moderate quinary NC-gRNA networks during the sequential processing of the GagNC domain. We also reveal two palindromic RNA-binding triads on NC, KxxFxxQ and QxxFxxK, that provide quinary NC-gRNA interactions. Consequently, the nucleocapsid complex appears properly aggregated for capsid reassembly and reverse transcription, mandatory processes for viral infectivity. We show that PR is sequestered within this RNP and drives its maturation/condensation within minutes, this process being most effective at the end of budding. We anticipate such findings will stimulate further investigations of quinary interactions and emergent mechanisms in crowded environments throughout the wide and growing array of RNP granules.

The Influence of Social Crowding on Consumer Creativity

The importance of consumer creativity is currently widely recognized, yet the examination of the influence of environmental elements on consumer creativity is still limited. Our research investigates the influence of social crowding on consumer creativity performance. While past research mainly focuses on extreme crowding conditions, our research examines the impact of a moderate level of social crowding, which is more commonly experienced in reality. From two lab experiments, our research shows that compared to consumers in crowded environments, consumers in uncrowded environments perform better on creativity tasks (e.g., designing promotion slogans and identifying solutions to problems). Furthermore, the effect of social crowding is mediated by approach motives. Consumers in an uncrowded (vs. crowded) environment are more likely to trigger approach-based motivation, which enhances their creativity performance. These findings extend our knowledge of social crowding and creativity and can help consumers and companies improve creativity performance in appropriate environments.

Sociale inclusie en ASS in het voortgezet onderwijs: wat is er nodig?

Since the introduction of the Appropriate Education Act, attempts have been made to include pupils with special needs in mainstream secondary education, including pupils with autism. Statistics show that this was only partially successful. This may be partly explained by the fact that the main focus of the involved professionals (school principals, teachers) to date seems to have been mainly on the educational needs of these pupils and less on students’ sense of belonging, i.e. going to school with the feeling to be part of something, a group or community. The central question in this qualitative research is to what extent young people with autism within mainstream education experience this sense of belonging and what is needed for this. This has been investigated by means of literature research and focus groups with (former) students with autism. The first preliminary results show that students with autism indicate that they have little contact with their fellow students, which is complicated by a too busy environment (too many students, too few seats, too many stimuli). All this leads to overstimulation, fatigue, and can cause so much stress that it takes very little to completely skip school that day. In short, the most important recommendation is to create more calm and less crowded environments in schools. We conclude that social inclusion of pupils with autism in mainstream schools is essential for the success of the Appropriate Education Act but it does not come naturally: it requires active policies from schools. The project described in this article is part of a larger project in which we try to develop concrete recommendations for this purpose.

Impact of crowded environments on binding between protein and single-stranded DNA

The concept of Molecular Crowding depicts the high density of diverse molecules present in the cellular interior. Here, we determine the impact of low molecular weight and larger molecules on binding capacity of single-stranded DNA (ssDNA) to the cold shock protein B (CspB). Whereas structural features of ssDNA-bound CspB are fully conserved in crowded environments as probed by high-resolution NMR spectroscopy, intrinsic fluorescence quenching experiments reveal subtle changes in equilibrium affinity. Kinetic stopped-flow data showed that DNA-to-protein association is significantly retarded independent of choice of the molecule that is added to the solution, but dissociation depends in a nontrivial way on its size and chemical characteristics. Thus, for this DNA–protein interaction, excluded volume effect does not play the dominant role but instead observed effects are dictated by the chemical properties of the crowder. We propose that surrounding molecules are capable of specific modification of the protein’s hydration shell via soft interactions that, in turn, tune protein–ligand binding dynamics and affinity.

Design a Mobile Application for Children’s Tracking in Crowded Environments

Child Tracking System is a mobile application where the parent can monitor their children location in crowded environments. In addition to children, there is also the elderly people, and the disabled people, so the guidance or the person responsible of them can use this application to track their location. The parent or guidance side will have the application in which they can track, and on the other side, the child or the old person or the disabled person will have device that includes the GPS chip. The main goal of this research is to design an application with system that will help parents to keep track of their children, eventually reducing the cases in which the children or the other mentioned categories of people could be lost. The current used solution to this problem is that the children first have a wearable hand wrist in which they print their parent phone number, so when the child is lost there is a center in which the child is being taken and dealt with care till they contact the parent to come and pick the child up. The problem with the current way that it takes time, and there is a risk that child get totally lost or kidnapped before even reaching to any help, so the new way is better to even prevent them to go far away or to be lost for hours, thus the recovery here will be fast unlike the regular used way nowadays. That goal will be achieved throw systematically objectives starting from studying the existed systems, to planning and analysing, going to designing and implementing, and lastly, testing our own system.

Neural network-based anomalous diffusion parameter estimation approaches for Gaussian processes

Anomalous diffusion behavior can be observed in many single-particle (contained in crowded environments) tracking experimental data. Numerous models can be used to describe such data. In this paper, we focus on two common processes: fractional Brownian motion (fBm) and scaled Brownian motion (sBm). We proposed novel methods for sBm anomalous diffusion parameter estimation based on the autocovariance function (ACVF). Such a function, for centered Gaussian processes, allows its unique identification. The first estimation method is based solely on theoretical calculations, and the other one additionally utilizes neural networks (NN) to achieve a more robust and well-performing estimator. Both fBm and sBm methods were compared between the theoretical estimators and the ones utilizing artificial NN. For the NN-based approaches, we used such architectures as multilayer perceptron (MLP) and long short-term memory (LSTM). Furthermore, the analysis of the additive noise influence on the estimators’ quality was conducted for NN models with and without the regularization method.