Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Influence of pharmacogenetic variability on the pharmacokinetics and toxicity of the aurora kinase inhibitor danusertib

Objectives Danusertib is a serine/threonine kinase inhibitor of multiple kinases, including aurora-A, B, and C. This explorative study aims to identify possible relationships between single nucleotide polymorphisms in genes coding for drug metabolizing enzymes and transporter proteins and clearance of danusertib, to clarify the interpatient variability in exposure. In addition, this study explores the relationship between target receptor polymorphisms and toxicity of danusertib. Methods For associations with clearance, 48 cancer patients treated in a phase I study were analyzed for ABCB1, ABCG2 and FMO3 polymorphisms. Association analyses between neutropenia and drug target receptors, including KDR, RET, FLT3, FLT4, AURKB and AURKA, were performed in 30 patients treated at recommended phase II dose-levels in three danusertib phase I or phase II trials. Results No relationships between danusertib clearance and drug metabolizing enzymes and transporter protein polymorphisms were found. Only, for the one patient with FMO3 18281AA polymorphism, a significantly higher clearance was noticed, compared to patients carrying at least 1 wild type allele. No effect of target receptor genotypes or haplotypes on neutropenia was observed. Conclusions As we did not find any major correlations between pharmacogenetic variability in the studied enzymes and transporters and pharmacokinetics nor toxicity, it is unlikely that danusertib is highly susceptible for pharmacogenetic variation. Therefore, no dosing alterations of danusertib are expected in the future, based on the polymorphisms studied. However, the relationship between FMO3 polymorphisms and clearance of danusertib warrants further research, as we could study only a small group of patients

Experience of, awareness of and help-seeking for potential cancer symptoms in smokers and non-smokers: A cross-sectional study

Background Presenting to primary care with potential cancer symptoms is contingent on one’s ability to recognize potentially serious symptoms. We investigated differences between smokers and non-smokers in symptoms experienced, awareness and consulting of potential respiratory, head and neck cancer symptoms. Methods Smokers and non-smokers aged over 50 from Yorkshire general practice lists were sent a postal questionnaire asking about symptoms, consulting and awareness of cancer symptoms. Data were analysed using STATA14. Results Response rate after one reminder was 30.5% (1205/3954). Smoking status was associated with experience of cough (p<0.001), breathlessness (p = 0.002) and tiredness (p = 0.004) with smokers (25.8% of population) more likely than never-smokers (53.6% of population) to experience all three symptoms (cough OR = 2.56;95%CI[1.75–3.75], breathlessness OR = 2.39;95%CI[1.43–4.00], tiredness OR = 1.57;95%CI[1.12–2.19]). Smoking status was associated with awareness of breathlessness as a potential cancer symptom (p = 0.035) and consulting for cough (p = 0.011) with smokers less likely to consult than never-smokers (OR = 0.37;95% CI[0.17–0.80]). Conclusion Our findings suggest that current smokers are more likely to experience cough, breathlessness and tiredness, but are less likely to consult for cough than never-smokers. To increase cancer awareness and promote consulting among smokers, innovative interventions improving symptom recognition and empowering smokers to seek help are required

A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare

Objective: The aim of this study was to compare the acceptability, validity and concordance of discrete choice experiment (DCE) and best–worst scaling (BWS) stated preference approaches in health. Methods: A systematic search of EMBASE, Medline, AMED, PubMed, CINAHL, Cochrane Library and EconLit databases was undertaken in October to December 2016 without date restriction. Studies were included if they were published in English, presented empirical data related to the administration or findings of traditional format DCE and object-, profile- or multiprofile-case BWS, and were related to health. Study quality was assessed using the PREFS checklist. Results: Fourteen articles describing 12 studies were included, comparing DCE with profile-case BWS (9 studies), DCE and multiprofile-case BWS (1 study), and profile- and multiprofile-case BWS (2 studies). Although limited and inconsistent, the balance of evidence suggests that preferences derived from DCE and profile-case BWS may not be concordant, regardless of the decision context. Preferences estimated from DCE and multiprofile-case BWS may be concordant (single study). Profile- and multiprofile-case BWS appear more statistically efficient than DCE, but no evidence is available to suggest they have a greater response efficiency. Little evidence suggests superior validity for one format over another. Participant acceptability may favour DCE, which had a lower self-reported task difficulty and was preferred over profile-case BWS in a priority setting but not necessarily in other decision contexts. Conclusion: DCE and profile-case BWS may be of equal validity but give different preference estimates regardless of the health context; thus, they may be measuring different constructs. Therefore, choice between methods is likely to be based on normative considerations related to coherence with theoretical frameworks and on pragmatic considerations related to ease of data collection

Adaptation of a transmitted/founder simian-human immunodeficiency virus for enhanced replication in rhesus macaques

Transmitted/founder (TF) simian-human immunodeficiency viruses (SHIVs) express HIV-1 envelopes modified at position 375 to efficiently infect rhesus macaques while preserving authentic HIV-1 Env biology. SHIV.C.CH505 is an extensively characterized virus encoding the TF HIV-1 Env CH505 mutated at position 375 shown to recapitulate key features of HIV-1 immunobiology, including CCR5-tropism, a tier 2 neutralization profile, reproducible early viral kinetics, and authentic immune responses. SHIV.C.CH505 is used frequently in nonhuman primate studies of HIV, but viral loads after months of infection are variable and typically lower than those in people living with HIV. We hypothesized that additional mutations besides Δ375 might further enhance virus fitness without compromising essential components of CH505 Env biology. From sequence analysis of SHIV.C.CH505-infected macaques across multiple experiments, we identified a signature of envelope mutations associated with higher viremia. We then used short-term in vivo mutational selection and competition to identify a minimally adapted SHIV.C.CH505 with just five amino acid changes that substantially improve virus replication fitness in macaques. Next, we validated the performance of the adapted SHIV in vitro and in vivo and identified the mechanistic contributions of selected mutations. In vitro, the adapted SHIV shows improved virus entry, enhanced replication on primary rhesus cells, and preserved neutralization profiles. In vivo, the minimally adapted virus rapidly outcompetes the parental SHIV with an estimated growth advantage of 0.14 days-1 and persists through suppressive antiretroviral therapy to rebound at treatment interruption. Here, we report the successful generation of a well-characterized, minimally adapted virus, termed SHIV.C.CH505.v2, with enhanced replication fitness and preserved native Env properties that can serve as a new reagent for NHP studies of HIV-1 transmission, pathogenesis, and cure

Sodium Chloride Inhibits the Growth and Infective Capacity of the Amphibian Chytrid Fungus and Increases Host Survival Rates

The amphibian chytrid fungus Batrachochytrium dendrobatidis is a recently emerged pathogen that causes the infectious disease chytridiomycosis and has been implicated as a contributing factor in the global amphibian decline. Since its discovery, research has been focused on developing various methods of mitigating the impact of chytridiomycosis on amphibian hosts but little attention has been given to the role of antifungal agents that could be added to the host's environment. Sodium chloride is a known antifungal agent used routinely in the aquaculture industry and this study investigates its potential for use as a disease management tool in amphibian conservation. The effect of 0–5 ppt NaCl on the growth, motility and survival of the chytrid fungus when grown in culture media and its effect on the growth, infection load and survivorship of infected Peron's tree frogs (Litoria peronii) in captivity, was investigated. The results reveal that these concentrations do not negatively affect the survival of the host or the pathogen. However, concentrations greater than 3 ppt significantly reduced the growth and motility of the chytrid fungus compared to 0 ppt. Concentrations of 1–4 ppt NaCl were also associated with significantly lower host infection loads while infected hosts exposed to 3 and 4 ppt NaCl were found to have significantly higher survival rates. These results support the potential for NaCl to be used as an environmentally distributed antifungal agent for the prevention of chytridiomycosis in susceptible amphibian hosts. However, further research is required to identify any negative effects of salt exposure on both target and non-target organisms prior to implementation

Systematic Analysis of Pleiotropy in C. elegans Early Embryogenesis

Pleiotropy refers to the phenomenon in which a single gene controls several distinct, and seemingly unrelated, phenotypic effects. We use C. elegans early embryogenesis as a model to conduct systematic studies of pleiotropy. We analyze high-throughput RNA interference (RNAi) data from C. elegans and identify “phenotypic signatures”, which are sets of cellular defects indicative of certain biological functions. By matching phenotypic profiles to our identified signatures, we assign genes with complex phenotypic profiles to multiple functional classes. Overall, we observe that pleiotropy occurs extensively among genes involved in early embryogenesis, and a small proportion of these genes are highly pleiotropic. We hypothesize that genes involved in early embryogenesis are organized into partially overlapping functional modules, and that pleiotropic genes represent “connectors” between these modules. In support of this hypothesis, we find that highly pleiotropic genes tend to reside in central positions in protein-protein interaction networks, suggesting that pleiotropic genes act as connecting points between different protein complexes or pathways

Systematic Analysis of Pleiotropy in C. elegans Early Embryogenesis

Pleiotropy refers to the phenomenon in which a single gene controls several distinct, and seemingly unrelated, phenotypic effects. We use C. elegans early embryogenesis as a model to conduct systematic studies of pleiotropy. We analyze high-throughput RNA interference (RNAi) data from C. elegans and identify “phenotypic signatures”, which are sets of cellular defects indicative of certain biological functions. By matching phenotypic profiles to our identified signatures, we assign genes with complex phenotypic profiles to multiple functional classes. Overall, we observe that pleiotropy occurs extensively among genes involved in early embryogenesis, and a small proportion of these genes are highly pleiotropic. We hypothesize that genes involved in early embryogenesis are organized into partially overlapping functional modules, and that pleiotropic genes represent “connectors” between these modules. In support of this hypothesis, we find that highly pleiotropic genes tend to reside in central positions in protein-protein interaction networks, suggesting that pleiotropic genes act as connecting points between different protein complexes or pathways

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p