Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Approach/Avoidance Training on Alcohol Consumption Is Mediated by Change in Alcohol Action Tendency

Training people to respond to alcohol images by making avoidance joystick movements can affect subsequent alcohol consumption, and has shown initial efficacy as a treatment adjunct. However, the mechanisms that underlie the training’s efficacy are unknown. The present study aimed to determine 1) whether the training’s effect is mediated by a change in action tendency or a change in selective attention, and 2) whether the training’s effect is moderated by individual differences in working memory capacity (WMC). Three groups of social drinkers (total N = 74) completed either approach-alcohol training, avoid-alcohol training or a sham-training on the Approach-Avoidance Task (AAT). Participants’ WMC was assessed prior to training, while their alcohol-related action tendency and selective attention were assessed before and after the training on the recently developed Selective-Attention/Action Tendency Task (SA/ATT), before finally completing an alcohol taste-test. There was no significant main effect of approach/avoidance training on alcohol consumption during the taste-test. However, there was a significant indirect effect of training on alcohol consumption mediated by a change in action tendency, but no indirect effect mediated by a change in selective attention. There was inconsistent evidence of WMC moderating training efficacy, with moderation found only for the effect of approach-alcohol training on the AAT but not on the SA/ATT. Thus approach/avoidance training affects alcohol consumption specifically by changing the underlying action tendency. Multiple training sessions may be required in order to observe more substantive changes in drinking behaviour.
Maternal Prepregnancy Body Mass Index and Gestational Weight Gain on Offspring Overweight in Early Infancy

Objective The aim of the present study was to evaluate the association of maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) with anthropometry in the offspring from birth to 12 months old in Tianjin, China. Methods Between 2009 and 2011, health care records of 38,539 pregnant women had been collected, and their children had been measured body weight and length at birth, 3, 6, 9 and 12 months of age. The independent and joint associations of pre-pregnancy BMI and GWG based on the Institute of Medicine (IOM) guidelines with anthropometry in the offspring were examined using General Linear Model and Logistic Regression. Results Prepregnancy BMI and maternal GWG were positively associated with Z-scores for birth weight-for-gestational age, birth length-for-gestational age, and birth weight-for-length. Infants born to mothers with excessive GWG had the greatest changes in Z-scores for weight-for-age from birth to Month 3, and from Month 6 to Month 12, and the greatest changes in Z-scores for length-for-age from birth to months 3 and 12 compared with infants born to mothers with adequate GWG. Excessive GWG was associated with an increased risk of offspring overweight or obesity at 12 months old in all BMI categories except underweight. Conclusions Maternal prepregnancy overweight/obesity and excessive GWG were associated with greater weight gain and length gain of offspring in early infancy. Excessive GWG was associated with increased infancy overweight and obesity risk.
The Connectome Visualization Utility: Software for Visualization of Human Brain Networks

In analysis of the human connectome, the connectivity of the human brain is collected from multiple imaging modalities and analyzed using graph theoretical techniques. The dimensionality of human connectivity data is high, and making sense of the complex networks in connectomics requires sophisticated visualization and analysis software. The current availability of software packages to analyze the human connectome is limited. The Connectome Visualization Utility (CVU) is a new software package designed for the visualization and network analysis of human brain networks. CVU complements existing software packages by offering expanded interactive analysis and advanced visualization features, including the automated visualization of networks in three different complementary styles and features the special visualization of scalar graph theoretical properties and modular structure. By decoupling the process of network creation from network visualization and analysis, we ensure that CVU can visualize networks from any imaging modality. CVU offers a graphical user interface, interactive scripting, and represents data uses transparent neuroimaging and matrix-based file types rather than opaque application-specific file formats.
Immunization with a Mixture of HIV Env DNA and VLP Vaccines Augments Induction of CD8 T Cell Responses

The immune response induced by immunization with HIV Env DNA and virus-like particle (VLP) vaccines was investigated. Immunization with the HIV Env DNA vaccine induced a strong CD8 T cell response but relatively weak antibody response against the HIV Env whereas immunization with VLPs induced higher levels of antibody responses but little CD8 T cell response. Interestingly, immunization with a mixture the HIV Env DNA and VLP vaccines induced enhanced CD8 T cell and antibody responses. Further, it was observed that the mixing of DNA and VLP vaccines during immunization is necessary for augmenting induction of CD8 T cell responses and such augmentation of CD8 T cell responses was also observed by mixing the HIV Env DNA vaccine with control VLPs. These results show that immunization with a mixture of DNA and VLP vaccines combines advantages of both vaccine platforms for eliciting high levels of both antibody and CD8 T cell responses.
Peripheral nerve conduits: technology update

Peripheral nerve injury is a worldwide clinical problem which could lead to loss of neuronal communication along sensory and motor nerves between the central nervous system (CNS) and the peripheral organs and impairs the quality of life of a patient. The primary requirement for the treatment of complete lesions is a tension-free, end-to-end repair. When end-to-end repair is not possible, peripheral nerve grafts or nerve conduits are used. The limited availability of autografts, and drawbacks of the allografts and xenografts like immunological reactions, forced the researchers to investigate and develop alternative approaches, mainly nerve conduits. In this review, recent information on the various types of conduit materials (made of biological and synthetic polymers) and designs (tubular, fibrous, and matrix type) are being presented.
Efficient Moment-Based Inference of Admixture Parameters and Sources of Gene Flow

The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here, we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically from the data and include estimates of statistical uncertainty. MixMapper also uses a new method to express branch lengths in easily interpretable drift units. We apply MixMapper to recently published data for Human Genome Diversity Cell Line Panel individuals genotyped on a SNP array designed especially for use in population genetics studies, obtaining confident results for 30 populations, 20 of them admixed. Notably, we confirm a signal of ancient admixture in European populations—including previously undetected admixture in Sardinians and Basques—involving a proportion of 20–40% ancient northern Eurasian ancestry.
Recasting the theory of mosquito-borne pathogen transmission dynamics and control

Mosquito-borne diseases pose some of the greatest challenges in public health, especially in tropical and sub-tropical regions of the world. Efforts to control these diseases have been underpinned by a theoretical framework developed for malaria by Ross and Macdonald, including models, metrics for measuring transmission, and theory of control that identifies key vulnerabilities in the transmission cycle. That framework, especially Macdonald's formula for R0 and its entomological derivative, vectorial capacity, are now used to study dynamics and design interventions for many mosquito-borne diseases. A systematic review of 388 models published between 1970 and 2010 found that the vast majority adopted the Ross–Macdonald assumption of homogeneous transmission in a well-mixed population. Studies comparing models and data question these assumptions and point to the capacity to model heterogeneous, focal transmission as the most important but relatively unexplored component in current theory. Fine-scale heterogeneity causes transmission dynamics to be nonlinear, and poses problems for modeling, epidemiology and measurement. Novel mathematical approaches show how heterogeneity arises from the biology and the landscape on which the processes of mosquito biting and pathogen transmission unfold. Emerging theory focuses attention on the ecological and social context for mosquito blood feeding, the movement of both hosts and mosquitoes, and the relevant spatial scales for measuring transmission and for modeling dynamics and control.
UvA-DARE ( Digital Academic Repository ) HIV reservoirs and immune surveillance evasion cause the failure of structured treatment interruptions : a computational study

Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models. Citation: Mancini E, Castiglione F, Bernaschi M, de Luca A, Sloot PMA (2012) HIV Reservoirs and Immune Surveillance Evasion Cause the Failure of Structured Treatment Interruptions: A Computational Study. PLoS ONE 7(4): e36108. doi:10.1371/journal.pone. 0036108 Editor: Vladimir Brusic, Dana-Farber Cancer Institute, United States of America Received December 15, 2011; Accepted March 30, 2012; Published April 27, 2012 Copyright: 2012 Mancini et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Partial support from the European Union under the EC contract FP6-2004-IST-4, No. 028069 (ImmunoGrid) http://igrid-ext.cryst. bbk.ac. uk/immunogrid/ site/. No additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: E.Mancini@uva.nl
Impacts of Fluid Dynamics Simulation in Study of Nasal Airflow Physiology and Pathophysiology in Realistic Human Three-Dimensional Nose Models

During the past decades, numerous computational fluid dynamics (CFD) studies, constructed from CT or MRI images, have simulated human nasal models. As compared to rhinomanometry and acoustic rhinometry, which provide quantitative information only of nasal airflow, resistance, and cross sectional areas, CFD enables additional measurements of airflow passing through the nasal cavity that help visualize the physiologic impact of alterations in intranasal structures. Therefore, it becomes possible to quantitatively measure, and visually appreciate, the airflow pattern (laminar or turbulent), velocity, pressure, wall shear stress, particle deposition, and temperature changes at different flow rates, in different parts of the nasal cavity. The effects of both existing anatomical factors, as well as post-operative changes, can be assessed. With recent improvements in CFD technology and computing power, there is a promising future for CFD to become a useful tool in planning, predicting, and evaluating outcomes of nasal surgery. This review discusses the possibilities and potential impacts, as well as technical limitations, of using CFD simulation to better understand nasal airflow physiology.
The nature of activatory and tolerogenic dendritic cell-derived signal II

Dendritic cells (DCs) are central in maintaining the intricate balance between immunity and tolerance by orchestrating adaptive immune responses. Being the most potent antigen presenting cells, DCs are capable of educating naïve T cells into a wide variety of effector cells ranging from immunogenic CD4+ T helper cells and cytotoxic CD8+ T cells to tolerogenic regulatory T cells. This education is based on three fundamental signals. Signal I, which is mediated by antigen/major histocompatibility complexes binding to antigen-specific T cell receptors, guarantees antigen specificity. The co-stimulatory signal II, mediated by B7 family molecules, is crucial for the expansion of the antigen-specific T cells. The final step is T cell polarization by signal III, which is conveyed by DC-derived cytokines and determines the effector functions of the emerging T cell. Although co-stimulation is widely recognized to result from the engagement of T cell-derived CD28 with DC-expressed B7 molecules (CD80/CD86), other co-stimulatory pathways have been identified. These pathways can be divided into two groups based on their impact on primed T cells. Whereas pathways delivering activatory signals to T cells are termed co-stimulatory pathways, pathways delivering tolerogenic signals to T cells are termed co-inhibitory pathways. In this review, we discuss how the nature of DC-derived signal II determines the quality of ensuing T cell responses and eventually promoting either immunity or tolerance. A thorough understanding of this process is instrumental in determining the underlying mechanism of disorders demonstrating distorted immunity/tolerance balance, and would help innovating new therapeutic approaches for such disorders.
Psychopathy-related traits and the use of reward and social information: a computational approach

Psychopathy is often linked to disturbed reinforcement-guided adaptation of behavior in both clinical and non-clinical populations. Recent work suggests that these disturbances might be due to a deficit in actively using information to guide changes in behavior. However, how much information is actually used to guide behavior is difficult to observe directly. Therefore, we used a computational model to estimate the use of information during learning. Thirty-six female subjects were recruited based on their total scores on the Psychopathic Personality Inventory (PPI), a self-report psychopathy list, and performed a task involving simultaneous learning of reward-based and social information. A Bayesian reinforcement-learning model was used to parameterize the use of each source of information during learning. Subsequently, we used the subscales of the PPI to assess psychopathy-related traits, and the traits that were strongly related to the model's parameters were isolated through a formal variable selection procedure. Finally, we assessed how these covaried with model parameters. We succeeded in isolating key personality traits believed to be relevant for psychopathy that can be related to model-based descriptions of subject behavior. Use of reward-history information was negatively related to levels of trait anxiety and fearlessness, whereas use of social advice decreased as the perceived ability to manipulate others and lack of anxiety increased. These results corroborate previous findings suggesting that sub-optimal use of different types of information might be implicated in psychopathy. They also further highlight the importance of considering the potential of computational modeling to understand the role of latent variables, such as the weight people give to various sources of information during goal-directed behavior, when conducting research on psychopathy-related traits and in the field of forensic psychiatry.
Rapid and quantitative detection of C-reactive protein using quantum dots and immunochromatographic test strips

Background Rapid immunochromatographic tests can detect disease markers in 10–15 minutes, which facilitates clinical diagnosis and treatment programs. However, most immunochromatographic tests employ gold nanoparticles as reporters, and these have only moderate sensitivity and act as qualitative methods for analyzing high biomarker concentrations. Methods In this study, we introduce quantum dots (QDs) as fluorescent probes and immunochromatographic strips to develop quantitative fluorescence point-of-care tests (QF-POCT) to analyze C-reactive protein (CRP) levels. Goat anti-rabbit IgG and rabbit IgG were used as control antibodies, and mouse monoclonal CRP antibody pairs were used for disease marker detection. One monoclonal CRP antibody was conjugated with QDs and served as a signal antibody, and the other monoclonal CRP antibody was dispensed onto the nitrocellulose membrane and served as a capturing antibody. In the presence of CRP, the fluorescence intensity of the monoclonal antibody-CRP-monoclonal antibody sandwich complex captured on the nitrocellulose membrane was determined using the fluorescence strip reader. Results QF-POCT assays could quantitatively analyze the concentration of CRP in 15 minutes had a detection limit of 0.25 mg/L, and had a wide detection linearity range (0.5–300 mg/L). The intra-assay and interassay coefficients of variation were 8.95% and 9.86% at 0.5 mg/L, 6.47% and 8.66% at 10 mg/L, and 6.81% and 9.10% at 60 mg/L, respectively. In a comparison between clinical samples, the results of this QD-based assay of CRP levels were significantly correlated with those of an Immulite 2000 assay (R=0.993, P<0.001). Conclusion Our results demonstrated that the QD-based immunochromatographic test is a rapid, sensitive, accurate, and quantitative method for the detection of disease biomarkers.
Postmitotic neurons develop a p21-dependent senescence-like phenotype driven by a DNA damage response

In senescent cells, a DNA damage response drives not only irreversible loss of replicative capacity but also production and secretion of reactive oxygen species (ROS) and bioactive peptides including pro‐inflammatory cytokines. This makes senescent cells a potential cause of tissue functional decline in aging. To our knowledge, we show here for the first time evidence suggesting that DNA damage induces a senescence‐like state in mature postmitotic neurons in vivo. About 40–80% of Purkinje neurons and 20–40% of cortical, hippocampal and peripheral neurons in the myenteric plexus from old C57Bl/6 mice showed severe DNA damage, activated p38MAPkinase, high ROS production and oxidative damage, interleukin IL‐6 production, heterochromatinization and senescence‐associated β‐galactosidase activity. Frequencies of these senescence‐like neurons increased with age. Short‐term caloric restriction tended to decrease frequencies of positive cells. The phenotype was aggravated in brains of late‐generation TERC−/− mice with dysfunctional telomeres. It was fully rescued by loss of p21(CDKN1A) function in late‐generation TERC−/−CDKN1A−/− mice, indicating p21 as the necessary signal transducer between DNA damage response and senescence‐like phenotype in neurons, as in senescing fibroblasts and other proliferation‐competent cells. We conclude that a senescence‐like phenotype is possibly not restricted to proliferation‐competent cells. Rather, dysfunctional telomeres and/or accumulated DNA damage can induce a DNA damage response leading to a phenotype in postmitotic neurons that resembles cell senescence in multiple features. Senescence‐like neurons might be a source of oxidative and inflammatory stress and a contributor to brain aging.
Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes

Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.
Sulfide as a soil phytotoxin—a review

In wetland soils and underwater sediments of marine, brackish and freshwater systems, the strong phytotoxin sulfide may accumulate as a result of microbial reduction of sulfate during anaerobiosis, its level depending on prevailing edaphic conditions. In this review, we compare an extensive body of literature on phytotoxic effects of this reduced sulfur compound in different ecosystem types, and review the effects of sulfide at multiple ecosystem levels: the ecophysiological functioning of individual plants, plant-microbe associations, and community effects including competition and facilitation interactions. Recent publications on multi-species interactions in the rhizosphere show even more complex mechanisms explaining sulfide resistance. It is concluded that sulfide is a potent phytotoxin, profoundly affecting plant fitness and ecosystem functioning in the full range of wetland types including coastal systems, and at several levels. Traditional toxicity testing including hydroponic approaches generally neglect rhizospheric effects, which makes it difficult to extrapolate results to real ecosystem processes. To explain the differential effects of sulfide at the different organizational levels, profound knowledge about the biogeochemical, plant physiological and ecological rhizosphere processes is vital. This information is even more important, as anthropogenic inputs of sulfur into freshwater ecosystems and organic loads into freshwater and marine systems are still much higher than natural levels, and are steeply increasing in Asia. In addition, higher temperatures as a result of global climate change may lead to higher sulfide production rates in shallow waters.