Computational Analysis of Cholangiocarcinoma Phosphoproteomes Identifies Patient-Specific Drug Targets

Cholangiocarcinoma is a form of hepatobiliary cancer with an abysmal prognosis. Despite advances in our understanding of cholangiocarcinoma pathophysiology and its genomic landscape, targeted therapies have not yet made a significant impact on its clinical management. The low response rates of targeted therapies in cholangiocarcinoma suggest that patient heterogeneity contributes to poor clinical outcome. Here we used mass spectrometry–based phosphoproteomics and computational methods to identify patient-specific drug targets in patient tumors and cholangiocarcinoma-derived cell lines. We analyzed 13 primary tumors of patients with cholangiocarcinoma with matched nonmalignant tissue and 7 different cholangiocarcinoma cell lines, leading to the identification and quantification of more than 13,000 phosphorylation sites. The phosphoproteomes of cholangiocarcinoma cell lines and patient tumors were significantly correlated. MEK1, KIT, ERK1/2, and several cyclin-dependent kinases were among the protein kinases most frequently showing increased activity in cholangiocarcinoma relative to nonmalignant tissue. Application of the Drug Ranking Using Machine Learning (DRUML) algorithm selected inhibitors of histone deacetylase (HDAC; belinostat and CAY10603) and PI3K pathway members as high-ranking therapies to use in primary cholangiocarcinoma. The accuracy of the computational drug rankings based on predicted responses was confirmed in cell-line models of cholangiocarcinoma. Together, this study uncovers frequently activated biochemical pathways in cholangiocarcinoma and provides a proof of concept for the application of computational methodology to rank drugs based on efficacy in individual patients. SIGNIFICANCE: Phosphoproteomic and computational analyses identify patient-specific drug targets in cholangiocarcinoma, supporting the potential of a machine learning method to predict personalized therapies

Characterizing the Initial Phase of Epidemic Growth on some Empirical Networks

A key parameter in models for the spread of infectious diseases is the basic reproduction number $R_0$, which is the expected number of secondary cases a typical infected primary case infects during its infectious period in a large mostly susceptible population. In order for this quantity to be meaningful, the initial expected growth of the number of infectious individuals in the large-population limit should be exponential. We investigate to what extent this assumption is valid by performing repeated simulations of epidemics on selected empirical networks, viewing each epidemic as a random process in discrete time. The initial phase of each epidemic is analyzed by fitting the number of infected people at each time step to a generalised growth model, allowing for estimating the shape of the growth. For reference, similar investigations are done on some elementary graphs such as integer lattices in different dimensions and configuration model graphs, for which the early epidemic behaviour is known. We find that for the empirical networks tested in this paper, exponential growth characterizes the early stages of the epidemic, except when the network is restricted by a strong low-dimensional spacial constraint, such as is the case for the two-dimensional square lattice. However, on finite integer lattices of sufficiently high dimension, the early development of epidemics shows exponential growth.Comment: To be included in the conference proceedings for SPAS 2017 (International Conference on Stochastic Processes and Algebraic Structures), October 4-6, 201

Western Australian public opinions of a minimum pricing policy for alcohol: study protocol

Background: Excessive alcohol consumption has significant adverse economic, social, and health outcomes. Recent estimates suggest that the annual economic costs of alcohol in Australia are up to AUD $36 billion. Policies influencing price have been demonstrated to be very effective in reducing alcohol consumption and alcohol-related harms. Interest in minimum pricing has gained traction in recent years. However, there has been little research investigating the level of support for the public interest case of minimum pricing in Australia. Objective: This article describes protocol for a study exploring Western Australian (WA) public knowledge, understanding, and reaction to a proposed minimum price policy per standard drink. Methods: The study will employ a qualitative methodological design. Participants will be recruited from a wide variety of backgrounds, including ethnic minorities, blue and white collar workers, unemployed, students, and elderly/retired populations to participate in focus groups. Focus group participants will be asked about their knowledge of, and initial reactions to, the proposed policy and encouraged to discuss how such a proposal may affect their own alcohol use and alcohol consumption at the population level. Participants will also be asked to discuss potential avenues for increasing acceptability of the policy. The focus groups will adopt a semi-structured, open-ended approach guided by a question schedule. The schedule will be based on feedback from pilot samples, previous research, and a steering group comprising experts in alcohol policy and pricing. Results: The study is expected to take approximately 14 months to complete. Conclusions: The findings will be of considerable interest and relevance to government officials, policy makers, researchers, advocacy groups, alcohol retail and licensed establishments and organizations, city and town planners, police, and other stakeholder organizations

Ultrasensitive force and displacement detection using trapped ions

The ability to detect extremely small forces is vital for a variety of disciplines including precision spin-resonance imaging, microscopy, and tests of fundamental physical phenomena. Current force-detection sensitivity limits have surpassed 1 $aN/\sqrt{Hz}$ (atto $=10^{-18}$) through coupling of micro or nanofabricated mechanical resonators to a variety of physical systems including single-electron transistors, superconducting microwave cavities, and individual spins. These experiments have allowed for probing studies of a variety of phenomena, but sensitivity requirements are ever-increasing as new regimes of physical interactions are considered. Here we show that trapped atomic ions are exquisitely sensitive force detectors, with a measured sensitivity more than three orders of magnitude better than existing reports. We demonstrate detection of forces as small as 174 $yN$ (yocto $=10^{-24}$), with a sensitivity 390$\pm150$ $yN/\sqrt{Hz}$ using crystals of $n=60$ $^{9}$Be$^{+}$ ions in a Penning trap. Our technique is based on the excitation of normal motional modes in an ion trap by externally applied electric fields, detection via and phase-coherent Doppler velocimetry, which allows for the discrimination of ion motion with amplitudes on the scale of nanometers. These experimental results and extracted force-detection sensitivities in the single-ion limit validate proposals suggesting that trapped atomic ions are capable of detecting of forces with sensitivity approaching 1 $yN/\sqrt{Hz}$. We anticipate that this demonstration will be strongly motivational for the development of a new class of deployable trapped-ion-based sensors, and will permit scientists to access new regimes in materials science.Comment: Expanded introduction and analysis. Methods section added. Subject to press embarg

The effects of land use disturbance varies with trophic position in littoral cichlid fish communities from Lake Tanganyika

Impacts of anthropogenic disturbance are especially severe in freshwater ecosystems. In particular, land use disturbance can lead to increased levels of pollution, including elevated nutrient and sediment loads whose negative impacts range from the community to the individual level. However, few studies have investigated if these impacts are uniform across species represented by multiple trophic levels. To address this knowledge gap, we focused on Lake Tanganyika cichlid fishes, which comprise hundreds of species representing a wide range of feeding strategies. Cichlids are at their most diverse within the near‐shore environment; however, land use disturbance of this environment has led to decreasing diversity, particularly in herbivores. We therefore tested if there is a uniform effect of pollution across species and trophic groups within the hyper‐diverse rocky shore cichlid fish community. We selected three sites with differing levels of human impact along the Tanzanian coastline and 10 cichlid species, comprising varying taxonomic and trophic groups, common to these sites. Nitrogen and carbon stable isotope values for 528 samples were generated and analysed using generalised linear mixed models. We also estimated stomach contents including sediment proportions. Our study highlights that multiple sources of pollution are having differing effects across species within a diverse fish community. We found that nitrogen stable isotope values were significantly higher at the most disturbed (urbanised) site for benthic feeding species, whereas there was no difference in these isotopes between sites for the water column feeding trophic group. Stomach contents revealed that the elevated δ15N values were unlikely to have been caused by differences in diet between sites. However, at the most disturbed site, higher proportions of sediment were present in most herbivores, irrespective of foraging behaviour. It is likely that anthropogenic nitrogen loading is the cause of higher nitrogen stable isotope values since there was no evidence of species shifting trophic levels between sites. Results support our previous study showing herbivore species to be most affected by human disturbance and make the link to pollution much more explicit. As lower diversity of consumers can negatively affect ecosystem processes such as stability, alleviating environmental impact through sewage treatment and afforestation programmes should continue to be a global priority for the conservation of aquatic ecosystems, as well as human health

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation

Pathological and ecological host consequences of infection by an introduced fish parasite

The infection consequences of the introduced cestode fish parasite Bothriocephalus acheilognathi were studied in a cohort of wild, young-of-the-year common carp Cyprinus carpio that lacked co-evolution with the parasite. Within the cohort, parasite prevalence was 42% and parasite burdens were up to 12% body weight. Pathological changes within the intestinal tract of parasitized carp included distension of the gut wall, epithelial compression and degeneration, pressure necrosis and varied inflammatory changes. These were most pronounced in regions containing the largest proportion of mature proglottids. Although the body lengths of parasitized and non-parasitized fish were not significantly different, parasitized fish were of lower body condition and reduced weight compared to non-parasitized conspecifics. Stable isotope analysis (δ15N and δ13C) revealed trophic impacts associated with infection, particularly for δ15N where values for parasitized fish were significantly reduced as their parasite burden increased. In a controlled aquarium environment where the fish were fed ad libitum on an identical food source, there was no significant difference in values of δ15N and δ13C between parasitized and non-parasitized fish. The growth consequences remained, however, with parasitized fish growing significantly slower than non-parasitized fish, with their feeding rate (items s−1) also significantly lower. Thus, infection by an introduced parasite had multiple pathological, ecological and trophic impacts on a host with no experience of the parasite

Terrestrial-focused protected areas are effective for conservation of freshwater fish diversity in Lake Tanganyika

Freshwater protected areas are rarely designed specifically for this purpose and consequently their conservation benefit cannot be guaranteed. Using Lake Tanganyika as a test case we investigated the benefits of terrestrial-focussed protected areas on the alpha and beta taxonomic and functional diversity of the diverse endemic rocky-shore cichlid fishes. Lake Tanganyika has limited protected shorelines and continued human population growth in its catchment, which has potential for negative impacts on habitat quality and key biological processes. We conducted 554 underwater surveys across a gradient of human disturbance including two protected areas, along 180 km of Tanzanian coastline, sampling 70 cichlid species representing a diverse range of life-histories and trophic groups. Alpha diversity was up to 50% lower outside of protected areas, and herbivores appeared most affected. Turnover dominated within-locality variation in beta diversity, but the nestedness component was positively related to human disturbance indicating an increase in generalist species outside of protected areas. Within protected areas the decline in zeta diversity (the expected number of shared species across multiple surveys) was best described by power law functions, which occur when local abundance is predicted by regional abundance; but declined exponentially in unprotected waters indicating a dominance of stochastic assembly. Despite not being designed for the purpose, the protected areas are clearly benefitting cichlid taxonomic and functional diversity within Lake Tanganyika, probably through local reduction in sediment deposition and/or pollution, but as cichlids can be poor dispersers protected area coverage should be expanded to benefit isolated communities

Centre selection for clinical trials and the generalisability of results: a mixed methods study.

BACKGROUND: The rationale for centre selection in randomised controlled trials (RCTs) is often unclear but may have important implications for the generalisability of trial results. The aims of this study were to evaluate the factors which currently influence centre selection in RCTs and consider how generalisability considerations inform current and optimal practice. METHODS AND FINDINGS: Mixed methods approach consisting of a systematic review and meta-summary of centre selection criteria reported in RCT protocols funded by the UK National Institute of Health Research (NIHR) initiated between January 2005-January 2012; and an online survey on the topic of current and optimal centre selection, distributed to professionals in the 48 UK Clinical Trials Units and 10 NIHR Research Design Services. The survey design was informed by the systematic review and by two focus groups conducted with trialists at the Birmingham Centre for Clinical Trials. 129 trial protocols were included in the systematic review, with a total target sample size in excess of 317,000 participants. The meta-summary identified 53 unique centre selection criteria. 78 protocols (60%) provided at least one criterion for centre selection, but only 31 (24%) protocols explicitly acknowledged generalisability. This is consistent with the survey findings (n = 70), where less than a third of participants reported generalisability as a key driver of centre selection in current practice. This contrasts with trialists' views on optimal practice, where generalisability in terms of clinical practice, population characteristics and economic results were prime considerations for 60% (n = 42), 57% (n = 40) and 46% (n = 32) of respondents, respectively. CONCLUSIONS: Centres are rarely enrolled in RCTs with an explicit view to external validity, although trialists acknowledge that incorporating generalisability in centre selection should ideally be more prominent. There is a need to operationalize 'generalisability' and incorporate it at the design stage of RCTs so that results are readily transferable to 'real world' practice

Oxygen uptake and denitrification in soil aggregates

A mathematical model of oxygen uptake by bacteria in agricultural soils is presented with the goal of predicting anaerobic regions in which denitrification occurs. In an environment with a plentiful supply of oxygen, microorganisms consume oxygen through normal respiration. When the local oxygen concentration falls below a threshold level, denitrification may take place leading to the release of nitrous oxide, a potent agent for global warming. A two-dimensional model is presented in which one or more circular soil aggregates are located at a distance below the ground-level at which the prevailing oxygen concentration is prescribed. The level of denitrification is estimated by computing the area of any anaerobic cores which may develop in the interior of the aggregates. The oxygen distribution throughout the model soil is calculated first for an aggregated soil for which the ratio of the oxygen diffusivities between an aggregate and its surround is small via an asymptotic analysis. Second, the case of a non-aggregated soil featuring one or more microbial hotspots, for which the diffusion ratio is arbitrary, is examined numerically using the boundary-element method. Calculations with multiple aggregates demonstrate a sheltering effect whereby some aggregates receive less oxygen than their neighbours. In the case of an infinite regular triangular network representing an aggregated soil, it is shown that there is an optimal inter-aggregate spacing which minimises the total anaerobic core area