Naphthylisoquinoline alkaloids, validated as hit multistage antiplasmodial natural products

The discovery and development of multistage antimalarial drugs targeting intra-erythrocytic asexual and sexual Plasmodium falciparum parasites is of utmost importance to achieve the ambitious goal of malaria elimination. Here, we report the validation of naphthylisoquinoline (NIQ) alkaloids and their synthetic analogues as multistage active antimalarial drug candidates. A total of 30 compounds were tested, of which 17 exhibited IC50 values <1 μM against drug-sensitive P. falciparum parasites (NF54 strain); 15 of these retained activity against a panel of drug-resistant strains. These compounds showed low in vitro cytotoxicity against HepG2 cells, with selectivity indices of>10. The tested compounds showed activity in vitro against both early- and late-stage P. falciparum gametocytes while blocking male gamete formation (> 70% inhibition of exflagellation at 2 μM). Additionally, five selected compounds were found to have good solubility (≥170 μM in PBS at pH 6.5), while metabolic stability towards human, mouse, and rat microsomes ranged from>90% to >7% after 30 min. Dioncophylline C (2a) emerged as a front runner from the study, displaying activity against both asexual parasites and gametocytes, a lack of cross-resistance to chloroquine, good solubility, and microsomal stability. Overall, this is the first report on the multistage activity of NIQs and their synthetic analogues including gametocytocidal and gametocidal effects induced by this class of compounds.We thank Dr. Raina Seupel, Dr. Jun Li, Dr. Christine Schies, Prof. Dr. Dieudonné Tshitenge, and Dr. Sebastian Bischof for providing substances tested in this study. The UP ISMC acknowledges the SAMRC as Collaborating Centre for Malaria Research. This work was funded by the South African Research Chairs Initiative of the Department of Science and Technology, administered through the South African National Research Foundation to LMB (UID 84627), and supported by the SFB 630 “Agents against Infectious Diseases” funded by the Deutsche Forschungsgesellschaft (DFG) to GB. ACCdS and TJE acknowledge support of the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under grant number R01AI143521. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.https://www.elsevier.com/locate/ijpddram2020BiochemistryChemistryGeneticsMicrobiology and Plant Patholog

Perching but not foraging networks predict the spread of novel foraging skills in starlings

The directed social learning hypothesis suggests that information does not spread evenly through animal groups, but rather individual characteristics and patterns of physical proximity guide the social transmission of information along specific pathways. Network-based diffusion analysis (NBDA) allows researchers to test whether information spreads following a social network. However, the explanatory power of different social networks has rarely been compared, and current models do not easily accommodate random effects (e.g. allowing for individuals within groups to correlate in their asocial solving rates). We tested whether the spread of two novel foraging skills through captive starling groups was affected by individual- and group-level random and fixed effects (i.e. sex, age, body condition, dominance rank and demonstrator status) and perching or foraging networks. We extended NBDA to include random effects and conducted model discrimination in a Bayesian context. We found that social learning increased the rate at which birds acquired the novel foraging task solutions by 6.67 times, and acquiring one of the two novel foraging task solutions facilitated the asocial acquisition of the other. Surprisingly, the spread of task solutions followed the perching rather than the foraging social network. Upon acquiring a task solution, foraging performance was facilitated by the presence of group mates. Our results highlight the importance of considering more than one social network when predicting the spread of information through animal groups. This article is part of a Special Issue entitled: Cognition in the wild

Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees

The authors are grateful to the Royal Zoological Society of Scotland for providing core funding for the Budongo Conservation Field Station. The fieldwork of CH was funded by the Leverhulme Trust, the Lucie Burgers Stichting, and the British Academy. TP was funded by the Canadian Research Chair in Continental Ecosystem Ecology, and received computational support from the Theoretical Ecosystem Ecology group at UQAR. The research leading to these results has received funding from the People Programme (Marie Curie Actions) and from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007–2013) REA grant agreement n°329197 awarded to TG, ERC grant agreement n° 283871 awarded to KZ. WH was funded by a BBSRC grant (BB/I007997/1).Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition-that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, "moss-sponging'' and "leaf-sponge re-use,'' in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most "cultural'' of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.Publisher PDFPeer reviewe

Recent applications and potential of near-term (interannual to decadal) climate predictions

Following efforts from leading centres for climate forecasting, sustained routine operational near-term climate predictions (NTCP) are now produced that bridge the gap between seasonal forecasts and climate change projections offering the prospect of seamless climate services. Though NTCP is a new area of climate science and active research is taking place to increase understanding of the processes and mechanisms required to produce skillful predictions, this significant technical achievement combines advances in initialisation with ensemble prediction of future climate up to a decade ahead. With a growing NTCP database, the predictability of the evolving externally-forced and internally-generated components of the climate system can now be quantified. Decision-makers in key sectors of the economy can now begin to assess the utility of these products for informing climate risk and for planning adaptation and resilience strategies up to a decade into the future. Here, case studies are presented from finance and economics, water management, agriculture and fisheries management demonstrating the emerging utility and potential of operational NTCP to inform strategic planning across a broad range of applications in key sectors of the global economy

Health Care Utilization and Behavior Changes After Workplace Genetic Testing at a Large US Health Care System

PURPOSE: This study explored employee health behavior changes and health care utilization after workplace genetic testing (wGT). Wellness-program-associated wGT seeks to improve employee health, but the related health implications are unknown. METHODS: Employees of a large US health care system offering wGT (cancer, heart disease, and pharmacogenomics [PGx]) were sent electronic surveys. Self-reported data from those who received test results were analyzed. Descriptive statistics characterized responses, whereas logistic regression analyses explored correlates of responses to wGT. RESULTS: 53.9% (n = 418/776) of respondents (88.3% female, mean age = 44 years) reported receiving wGT results. 12.0% (n = 48/399) received results indicating increased risk (IR) of cancer, 9.5% (n = 38/398) had IR of heart disease, and 31.4% (n = 125/398) received informative PGx results. IR results for cancer and/or heart disease (n = 67) were associated with health behavior changes (adjusted odds ratio: 3.23; 95% CI 1.75, 6.13; P \u3c .001) and health care utilization (adjusted odds ratio: 8.60; 95% CI 4.43, 17.5; P \u3c .001). Informative PGx results (n = 125) were associated with medication changes (PGx-informative: 15.2%; PGx-uninformative: 4.8%; P = .002). CONCLUSION: This study explored employee responses to wGT, contributing to the understanding of the ethical and social implications of wGT. Receiving IR results from wGT may promote health behavior changes and health care utilization in employees

Bayesian spatial NBDA for diffusion data with home-base coordinates

Network-based diffusion analysis (NBDA) is a statistical method that allows the researcher to identify and quantify a social influence on the spread of behaviour through a population. Hitherto, NBDA analyses have not directly modelled spatial population structure. Here we present a spatial extension of NBDA, applicable to diffusion data where the spatial locations of individuals in the population, or of their home bases or nest sites, are available. The method is based on the estimation of inter-individual associations (for association matrix construction) from the mean inter-point distances as represented on a spatial point pattern of individuals, nests or home bases. We illustrate the method using a simulated dataset, and show how environmental covariates (such as that obtained from a satellite image, or from direct observations in the study area) can also be included in the analysis. The analysis is conducted in a Bayesian framework, which has the advantage that prior knowledge of the rate at which the individuals acquire a given task can be incorporated into the analysis. This method is especially valuable for studies for which detailed spatially structured data, but no other association data, is available. Technological advances are making the collection of such data in the wild more feasible: for example, bio-logging facilitates the collection of a wide range of variables from animal populations in the wild. We provide an R package, spatialnbda, which is hosted on the Comprehensive R Archive Network (CRAN). This package facilitates the construction of association matrices with the spatial x and y coordinates as the input arguments, and spatial NBDA analyses

Recent applications and potential of near-term (interannual to decadal) climate predictions

Following efforts from leading centres for climate forecasting, sustained routine operational near-term climate predictions (NTCP) are now produced that bridge the gap between seasonal forecasts and climate change projections offering the prospect of seamless climate services. Though NTCP is a new area of climate science and active research is taking place to increase understanding of the processes and mechanisms required to produce skillful predictions, this significant technical achievement combines advances in initialisation with ensemble prediction of future climate up to a decade ahead. With a growing NTCP database, the predictability of the evolving externally-forced and internally-generated components of the climate system can now be quantified. Decision-makers in key sectors of the economy can now begin to assess the utility of these products for informing climate risk and for planning adaptation and resilience strategies up to a decade into the future. Here, case studies are presented from finance and economics, water management, agriculture and fisheries management demonstrating the emerging utility and potential of operational NTCP to inform strategic planning across a broad range of applications in key sectors of the global economy

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