Miracle-dz/UniFAR-FTUs huggingface dataset:
Suboptimal Provirus Expression Explains Apparent Nonrandom Cell Coinfection with HIV-1

ABSTRACT Despite the ability of primate lentiviruses to prevent infected cells from being reinfected, cell coinfection has occurred in the past and has shaped virus evolution by promoting the biogenesis of heterozygous virions and recombination during reverse transcription. In vitro experiments have shown that cell coinfection with HIV is more frequent than would be expected if coinfection were a random process. A possible explanation for this bias is the heterogeneity of target cells and the preferred infection of a subpopulation. To address this question, we compared the frequency of double-positive cells measured following coincubation with green fluorescent protein (GFP) and DsRed HIV reporter viruses with that of stochastic coinfection calculated as the product of the frequencies of GFP- and DsRed-positive cells upon incubation with either reporter virus. Coinfection was more frequent than would be expected on the grounds of stochastic infection, due to the underestimation of single-infection frequencies, which mathematically decreased the calculated frequency. Indeed, when cells were incubated with either reporter virus, a fraction of the cells were scored as uninfected yet harbored a silent provirus that was reactivated upon coinfection through cross talk between viral elements. When such cross talk was avoided, experimental and calculated coinfection frequencies matched, indicating random coinfection. The proportion of infected cells harboring a silent provirus was estimated from coinfection experiments and was shown to be cell type dependent but independent of the virus entry route.
Defensive Hostility and Coronary Heart Disease: A Preliminary Investigation of Male Veterans

Objective Research and theory link an interpersonal conflict model to cardiovascular disease. Specifically, persons scoring high on cynical hostility and social defensiveness are thought to manifest a defensive need for approval while harboring basic distrust and hostility toward those who could provide such approval. The objective of this study was to assess whether angiographically determined coronary artery disease (CAD) was associated with this combination of high cynical hostility and high social defensiveness. Methods Fifty-nine male patients of a Veterans Administration Medical Center (86% white, mean age = 59.9 years) participated in the study on the day before their angiographic procedure; these men filled out the Cook-Medley Hostility Scale and the Marlowe-Crowne Social Desirability Scale (social defensiveness). They subsequently were categorized as having defensive hostility (DH), high hostility (HH), high social defensiveness (SD), or low psychosocial risk (LRisk; low on both scales). Results The four groups did not differ significantly on risk factor status or health status. As predicted, a preplanned contrast showed that the DH group’s mean number of arteries with at least 50% blockage (mean = 2.5) differed significantly from the combined means of the other groups. The HH and SD groups did not differ from the LRisk group. Conclusions When combined with other reports, the approach-avoidance interpersonal conflict model holds the promise of providing additional information about the psychosocial factors contributing to CAD development among men with high cynical hostility.
Studying Impact of Nutrition on Growth (SING): a prospective cohort for comparing the health outcomes of young children with the dietary quality score

Introduction This study aims to explore the prospective association between the dietary quality (DQ) of preschoolers and their health status in Hong Kong, with the body mass index as the main outcome variable. Methods and analysis This prospective cohort study has recruited 3539 children aged between 2 and 4 years old, with a follow-up period of 4 years. Their diet was reported by their parents by a 3-day food diary, and their body weight and height were measured yearly with standardised instruments. Questionnaires were administered to parents to acquire information of the children’s prenatal development and dietary intake before their age of 2 years and of their baseline lifestyle and family backgrounds. The DQ was measured by the Healthy Eating Index as a continuous scale, while the exposure was defined as having a higher dietary quality score. Data were analysed using SPSS V.24. Linear and logistic regressions were used to examine the association of those predictive factors to the outcomes. Generalised estimating equations will be used to examine the longitudinal changes of the outcomes. A pilot study has been conducted, the preliminary results from which are presented in this cohort profile. Ethics and dissemination This study has been approved by the Joint Chinese University of Hong Kong and New Territory East Cluster Clinical Research Ethics Committee (CREC Ref No: 2013–632). Written informed consent was obtained from all subjects. The results will be published in due course.
Fast Start-up for Spartan-6 FPGAs using Dynamic Partial Reconfiguration

This paper introduces the first available tool flow for Dynamic Partial Reconfiguration on the Spartan-6 family. In addition, the paper proposes a new configuration method called Fast Start-up targeting modern FPGA architectures, where the FPGA is configured in two-steps, instead of using a single (monolithic) full device configuration. In this novel approach, only the timing-critical modules are loaded at power-up using the first high-priority bitstream, while the non-timing critical modules are loaded afterwards. This two-step or prioritized FPGA start-up is used in order to meet the extremely tight startup timing specifications found in many modern applications, like PCI-express or automotive applications. Finally, the developed tool flow and methods for Fast Start-up have been used and tested to implement a CAN-based automotive ECU on a Spartan-6 evaluation board (i.e., SP605). By using this novel approach, it was possible to decrease the initial bitstream size and hence, achieve a configuration time speed-up of up to 4.5×, when compared to a standard configuration solution.
Automatic Text Summarization Approaches to Speed up Topic Model Learning Process

The number of documents available into Internet moves each day up. For this reason, processing this amount of information effectively and expressibly becomes a major concern for companies and scientists. Methods that represent a textual document by a topic representation are widely used in Information Retrieval (IR) to process big data such as Wikipedia articles. One of the main difficulty in using topic model on huge data collection is related to the material resources (CPU time and memory) required for model estimate. To deal with this issue, we propose to build topic spaces from summarized documents. In this paper, we present a study of topic space representation in the context of big data. The topic space representation behavior is analyzed on different languages. Experiments show that topic spaces estimated from text summaries are as relevant as those estimated from the complete documents. The real advantage of such an approach is the processing time gain: we showed that the processing time can be drastically reduced using summarized documents (more than 60\% in general). This study finally points out the differences between thematic representations of documents depending on the targeted languages such as English or latin languages.
Development of a text search engine for medicinal chemistry patents

Division of Medical Information Sciences (SIMED), University Hospitals of Geneva and University of Geneva, Geneva, Switzerland Bibliomics and Text-Mining Group (BiTeM), Information Science Department, University of Applied Sciences, Geneva, Switzerland Novartis Institute for BioMedical Research – Text Mining Services (NIBR-IT/TMS), Novartis Pharma AG, Basel, Switzerland e-mail: emilie.pasche@hcuge.ch (corresponding), julien.gobeill@hesge.ch, fatma.oezdemirzaech@novartis.com, therese.vachon@novartis.com, christian.lovis@hcuge.ch, patrick.ruch@hesge.ch
General Platform for Systematic Quantitative Evaluation of Small-Molecule Permeability in Bacteria

The chemical features that impact small-molecule permeability across bacterial membranes are poorly understood, and the resulting lack of tools to predict permeability presents a major obstacle to the discovery and development of novel antibiotics. Antibacterials are known to have vastly different structural and physicochemical properties compared to nonantiinfective drugs, as illustrated herein by principal component analysis (PCA). To understand how these properties influence bacterial permeability, we have developed a systematic approach to evaluate the penetration of diverse compounds into bacteria with distinct cellular envelopes. Intracellular compound accumulation is quantitated using LC-MS/MS, then PCA and Pearson pairwise correlations are used to identify structural and physicochemical parameters that correlate with accumulation. An initial study using 10 sulfonyladenosines in Escherichia coli, Bacillus subtilis, and Mycobacterium smegmatis has identified nonobvious correlations between chemical structure and permeability that differ among the various bacteria. Effects of cotreatment with efflux pump inhibitors were also investigated. This sets the stage for use of this platform in larger prospective analyses of diverse chemotypes to identify global relationships between chemical structure and bacterial permeability that would enable the development of predictive tools to accelerate antibiotic drug discovery.
Robust Principal Component Analysis

Introduction Over the past decade there has been an explosion in terms of the massive amounts of high-dimensional data in almost all fields of science and engineering. This situation presents a challenge as well as an opportunity to many areas such as web data analysis, search, biomedical imaging, bioinformatics, (social) network analysis, image, video and multimedia processing and many others. In such applications, researches today routinely deal with data that lie in thousands or even billions of dimensions, with a number of samples sometimes of the same order of magnitude. Often, in order to be able to even make sense of data in such high dimensionality and scale, one has to leverage on the fact that such data often have low intrinsic dimensionality. One reasonable (but not the only) approach that is well justified in many practical situations is to assume that the data all lie near some low-dimensional subspace. In mathematical terms, this amounts to saying that if all the data points are stacked as column vectors of a matrix M , the matrix should (approximately) have low rank. Specifically, a common model is to assume that M = L 0 + N 0 (1) where L 0 is of low rank and N 0 is a small perturbation matrix (i.e. the noise). A classical approach to the problem is to seek the best (in an 2-sense) rank-k estimate of L 0 by solving the optimization problem min L M − L 2 : rk(L) ≤ k (2) This approach, known as Principal Component Analysis (PCA) [14, 15], has been studied for almost a century and is used extensively for data analysis and dimensionality reduction in many areas. It is easy to show that this problem can be efficiently solved using the singular value decomposition (SVD) of the data matrix M. It also enjoys a number of optimality properties when the noise N 0 is small and i.i. d. Gaussian. However, PCA in general may fail spectacularly when the assumption on the noise matrix is not satisfied: Even a single grossly corrupted entry in M could render the estimatedˆL arbitrarily far from the true L 0. Unfortunately, these kinds of gross errors are very common in many applications, arising for example from corrupted data, sensor failures or corrupted samples in repetitive measurement tasks in biology applications. We would therefore like a method that is able to extract the principal components …
Researching the geography of mental wellbeing

Different disciplines have different methods of investigating the same phenomenon and truly multi-disciplinary research can bring added benefits to most areas of study. Geography is the study of any phenomenon at or near the earth’s surface, and as such it necessitates a multidisciplinary approach. This editorial highlights the role that can be played by professional geographers in mental health research, advocating more multi-disciplinary research and the broadening of research methods taught to all disciplines. Analytical methods used in geography have undergone many changes. One of the most notable and significant changes took place in the 1960s when geographical research went through what is now commonly referred to as the quantitative revolution. It was a major paradigm shift for the discipline seeing it largely move away from descriptive narrative to statistical analysis of space, place and society. Since that time geographical research methodology has continued to evolve, and so have the techniques used by geographers. Advances in micro-computing have facilitated the development of new quantitative techniques and more recently they have brought digital mapping and Geographic Information Systems (GIS) to the desk-top. Gatrell (2002) noted in his introductory book, Geographies of Health, that a good deal of spatial analytical work has been paralleled by the development of geographic information systems. GIS is a computer-based information system that enables capture, modelling, storage, retrieval, sharing, manipulation, analysis and presentation of geographically referenced data (Worboys & Duckham, 2004). Typically, GIS data have two elements. The first is the location of each instance of a phenomenon, and this is usually in the form of a map grid reference or a pair of latitude and longitude coordinates. The second element is associated with the attributes of each instance of the phenomenon. For example, a GIS of disease would have the spatial location of each incident together with information about the disease (disease name, age, gender, date, outcome, etc. of the sufferer). Openshaw et al. (1987) and colleagues analysed data on the incidence of cancer using information held in the regional cancer registry in northern England. The spatial references were produced from the postcode of each patient, which then allowed them to analyse for spatial clustering in cases. In GIS, data are stored in thematic layers with
Tissue integration versus bacterial colonization on dental implant materials

Biomaterialen worden in de huidige geneeskunde vaak als implantaat gebruikt om de functie en vorm van het menselijk lichaam te herstellen. Echter, de aanwezigheid van een biomateriaal vergroot de kans op infectie drastisch. Om infectie gerelateerd falen van implantaten te voorkomen hebben we verschillende materialen en oppervlakte modificaties toegepast die weefsel integratie verbeteren en biofilm formatie tegen gaan op tandheelkundige implantaten. In het begin van dit proefschrift hebben we onderbouwd waarom tandheelkundige implantaten, die zich in een bacterie rijk milieu bevinden, zo vaak succesvol zijn, terwijl andere implantaten in een bijna steriele omgeving falen. De voornaamste reden is het snelle herstel van orale weefsels en de tolerantie van het orale immuun systeem. Om de orale omgeving na te bootsen werden twee modellen ontwikkeld, het peri-operatieve model, gebruikmakend van supra-gingivale bacteriele stammen versus humane gingivale fibroblasten, en een laat post-operatief model met periodontale pathogenen versus osteoblasten. De resultaten wijzen op verschillende materialen voor het stimuleren van de formatie van een afdichting van zacht weefsel gevormd door fibroblasten vergeleken met het behouden van integratie in het bot; de nek van het implantaat zou bij voorkeur van glad titanium gemaakt moeten worden, terwijl voor integratie in het bot een titanium-zirkonium legering en andere zirkonium varianten de voorkeur hebben. De gebruikte co-cultuur (bacterien en cellen) studies in dit proefschrift zijn in lijn met klinische bevindingen en bieden relevantere informatie dan traditionele in vitro mono-cultuur studies die alleen de bacteriele of alleen weefsel respons op biomateriaal bekijken.
A Model of Biological Motion Perception from Configural Form Cues

Biological motion perception is the compelling ability of the visual system to perceive complex human movements effortlessly and within a fraction of a second. Recent neuroimaging and neurophysiological studies have revealed that the visual perception of biological motion activates a widespread network of brain areas. The superior temporal sulcus has a crucial role within this network. The roles of other areas are less clear. We present a computational model based on neurally plausible assumptions to elucidate the contributions of motion and form signals to biological motion perception and the computations in the underlying brain network. The model simulates receptive fields for images of the static human body, as found by neuroimaging studies, and temporally integrates their responses by leaky integrator neurons. The model reveals a high correlation to data obtained by neurophysiological, neuroimaging, and psychophysical studies.
Phonemic auditory and somatosensory goals in speech production

In this target paper, Hickok proposes a hierarchical state feedback control (HSFC) model of speech production in an attempt to integrate a range of theoretical and empirical works coming from psycholinguistic, motor control, neuropsychology and cognitive neuroscience. While we find much to like about the HSFC model, we will focus in this commentary on one important piece of disagreement, namely, its conceptual view on the nature and control of phoneme in speech production.
Simulation of aerosol optical properties over Europe with a 3-D size-resolved aerosol model: comparisons with AERONET data

This paper aims at presenting a model-to-data comparison of the Aerosol Optical Thickness (AOT) and of a few sparse data for Single Scattering Albedo (SSA) over Europe for one year. The main contribution of this paper is the sensitivity study to a large number of parameters, includ- ing physical and numerical parameters of the aerosol model itself. The optical parameters are computed from a size- resolved aerosol model embedded in the POLYPHEMUS sys- tem. The methodology is first described, showing that several hypothesis can be made for micro-physical aerosol proper- ties. The simulation is made over one year (2001); statistics and monthly time series for the simulation and AERONET data are used to evaluate the ability of the model to reproduce AOT and vertically averaged SSA fields and their variabil- ity. The relation with the uncertainties of measurements is discussed. Then a sensitivity study with respect to the mix- ing state of the particle, the way to take into account wa- ter uptake, numerical parameters and physical parameteriza- tions of the model is carried out. The results indicate that the mixing state of particles has an influence on optical param- eters, as well as the computation of the wet diameter. But some physical and numerical parameters associated with the aerosol model itself have even more influence under certain conditions, through the uncertainties on the aerosol chemical composition, and their size distribution.
Consequences of Overnight Work Travel for Personal Social Relations: Problems, Promises, and Further Repercussions

Abstract The article uses survey data from Sweden to examine social consequences of the mobile society. Key questions tackled include the implications of overnight work travel for the travellers’ ability to cultivate locally based and long‐distance friendships and the potential of travel to provide a source of new acquaintances. Data analysis indicates that widening social networks and increasing opportunities to achieve co‐presence with long‐distance friends, as brought by mobility, represent significant consequences of overnight work travel from an individual’s standpoint. This experience was salient even among those respondents who travelled no more than occasionally, while only the most frequent travellers perceived their travel as something impeding with their chances of sustaining local social ties. While the benefits deriving from travel thus seem incontestable, it may therefore not be possible either to entirely discard the prevalent notion of mobile lifestyles as a factor undermining social cohesion and promoting isolation and loneliness.
Genetic heterogeneity of diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common form of lymphoma in adults. The disease exhibits a striking heterogeneity in gene expression profiles and clinical outcomes, but its genetic causes remain to be fully defined. Through whole genome and exome sequencing, we characterized the genetic diversity of DLBCL. In all, we sequenced 73 DLBCL primary tumors (34 with matched normal DNA). Separately, we sequenced the exomes of 21 DLBCL cell lines. We identified 322 DLBCL cancer genes that were recurrently mutated in primary DLBCLs. We identified recurrent mutations implicating a number of known and not previously identified genes and pathways in DLBCL including those related to chromatin modification (ARID1A and MEF2B), NF-κB (CARD11 and TNFAIP3), PI3 kinase (PIK3CD, PIK3R1, and MTOR), B-cell lineage (IRF8, POU2F2, and GNA13), and WNT signaling (WIF1). We also experimentally validated a mutation in PIK3CD, a gene not previously implicated in lymphomas. The patterns of mutation demonstrated a classic long tail distribution with substantial variation of mutated genes from patient to patient and also between published studies. Thus, our study reveals the tremendous genetic heterogeneity that underlies lymphomas and highlights the need for personalized medicine approaches to treating these patients.
Linear programming of voltage-controlled memristors with an anti-serial memristor circuit

The memristance variation of a single memristor with voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is addressed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance by virtue of complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method.
Radio in Botswana: A Critical Examination of its Growth and Dominance Across Botswana's Mass Media Landscape

To a certain extent, the position of radio in Botswana since the colonial period has benefited significantly from recent developments in the media. The potency of radio as a mobile medium; its usefulness for public dialogue and entertainment; and its effectiveness as a less sophisticated technology that is easily accessible and adaptable in remote communities, have ensured that radio remains the most preferred and dominant medium of mass communication in Botswana. The recent introduction of the Internet and digital communication technologies also meant that in Botswana, radio is appropriately situated in the World Wide Web and mobile phones.