Balancing the dilution and oddity effects: Decisions depend on body size

Background Grouping behaviour, common across the animal kingdom, is known to reduce an individual's risk of predation; particularly through dilution of individual risk and predator confusion (predator inability to single out an individual for attack). Theory predicts greater risk of predation to individuals more conspicuous to predators by difference in appearance from the group (the ‘oddity’ effect). Thus, animals should choose group mates close in appearance to themselves (eg. similar size), whilst also choosing a large group. Methodology and Principal Findings We used the Trinidadian guppy (Poecilia reticulata), a well known model species of group-living freshwater fish, in a series of binary choice trials investigating the outcome of conflict between preferences for large and phenotypically matched groups along a predation risk gradient. We found body-size dependent differences in the resultant social decisions. Large fish preferred shoaling with size-matched individuals, while small fish demonstrated no preference. There was a trend towards reduced preferences for the matched shoal under increased predation risk. Small fish were more active than large fish, moving between shoals more frequently. Activity levels increased as predation risk decreased. We found no effect of unmatched shoal size on preferences or activity. Conclusions and Significance Our results suggest that predation risk and individual body size act together to influence shoaling decisions. Oddity was more important for large than small fish, reducing in importance at higher predation risks. Dilution was potentially of limited importance at these shoal sizes. Activity levels may relate to how much sampling of each shoal was needed by the test fish during decision making. Predation pressure may select for better decision makers to survive to larger size, or that older, larger fish have learned to make shoaling decisions more efficiently, and this, combined with their size relative to shoal-mates, and attractiveness as prey items influences shoaling decisions

Prognostic value of electrocardiographic detection of unrecognized myocardial infarction in persons with stable coronary artery disease: data from the Heart and Soul Study

Unrecognized myocardial infarction (MI) carries a poor prognosis in the general population, but its prognostic value is less clear in high-risk patients. We sought to determine whether Q waves on electrocardiogram (ECG), suggestive of unrecognized MI, predict cardiovascular events in patients with stable coronary artery disease (CAD), but without a prior history of MI. We studied 462 patients enrolled in the Heart and Soul Study with stable CAD but without a prior history of MI. All patients had baseline ECGs. The baseline prevalence of unrecognized myocardial infarction was 36%. After a mean of 6.3 years of follow-up, there were a total of 141 cardiovascular events. The presence of Q waves in any ECG lead territory predicted cardiovascular events before (unadjusted HR 1.41, 95% CI 1.01-1.97) and after adjustment for demographics, medical history, diastolic function, and ejection fraction (HR 1.55, 95% CI 1.06-2.26). This association was partly attenuated after adjustment for the presence of inducible ischemia at baseline (HR 1.43, 95% CI 0.96-2.12). When specific territories were analyzed separately, Q waves in anterior leads were predictive of cardiovascular events in both unadjusted and adjusted models (adjusted HR 1.85, 95% CI 1.14-3.00), and this association was partly attenuated after adjustment for inducible ischemia. In conclusion, in patients with CAD but no history of prior MI, the presence of any Q waves or anterior Q waves alone is independently predictive of adverse cardiovascular events

Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening

Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutaminemediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington’s Disease (HD) model.National Institutes of Health (U.S.) (Grant

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Novel miRNA-based drug CD5-2 reduces liver tumor growth in diethylnitrosamine-treated mice by normalizing tumor vasculature and altering immune infiltrate

IntroductionLiver cancers exhibit abnormal (leaky) vasculature, hypoxia and an immunosuppressive microenvironment. Normalization of tumor vasculature is an emerging approach to treat many cancers. Blockmir CD5-2 is a novel oligonucleotide-based inhibitor of the miR-27a interaction with VE-Cadherin, the endothelial-specific cadherin. The combination of a vasoactive medication with inhibition of immune checkpoints such as programmed cell death protein 1 (PD1) has been shown to be effective in treating liver cancer in humans. We aimed to study the effect of CD5-2 combined with checkpoint inhibition (using an antibody against PD1) on liver tumor growth, vasculature and immune infiltrate in the diethylnitrosamine (DEN)-induced liver tumor mouse model.MethodsWe first analyzed human miR-27a and VE-Cadherin expression data from The Cancer Genome Atlas for hepatocellular carcinoma. CD5-2 and/or anti-PD1 antibody were given to the DEN-treated mice from age 7-months until harvest at age 9-months. Tumor and non-tumor liver tissues were analyzed using histology, immunohistochemistry, immunofluorescence and scanning electron microscopy.ResultsHuman data showed high miR-27a and low VE-Cadherin were both significantly associated with poorer prognosis. Mice treated with CD5-2 plus anti-PD1 antibody had significantly smaller liver tumors (50% reduction) compared to mice treated with either agent alone, controls, or untreated mice. There was no difference in tumor number. Histologically, tumors in CD5-2-treated mice had less leaky vessels with higher VE-Cadherin expression and less tumor hypoxia compared to non-CD5-2-treated mice. Only tumors in the combination CD5-2 plus anti-PD1 antibody group exhibited a more favorable immune infiltrate (significantly higher CD3+ and CD8+ T cells and lower Ly6G+ neutrophils) compared to tumors from other groups.DiscussionCD5-2 normalized tumor vasculature and reduced hypoxia in DEN-induced liver tumors. CD5-2 plus anti-PD1 antibody reduced liver tumor size possibly by altering the immune infiltrate to a more immunosupportive one

A systematic review of frameworks for the interrelationships of mental health evidence and policy in low- and middle-income countries

Background: The interrelationships between research evidence and policy-making are complex. Different theoretical frameworks exist to explain general evidence–policy interactions. One largely unexplored element of these interrelationships is how evidence interrelates with, and influences, policy/political agenda-setting. This review aims to identify the elements and processes of theories, frameworks and models on interrelationships of research evidence and health policy-making, with a focus on actionability and agenda-setting in the context of mental health in low- and middle-income countries (LMICs). Methods: A systematic review of theories was conducted based on the BeHeMOTh search method, using a tested and refined search strategy. Nine electronic databases and other relevant sources were searched for peer-reviewed and grey literature. Two reviewers screened the abstracts, reviewed full-text articles, extracted data and performed quality assessments. Analysis was based on a thematic analysis. The included papers had to present an actionable theoretical framework/model on evidence and policy interrelationships, such as knowledge translation or evidence-based policy, specifically target the agenda-setting process, focus on mental health, be from LMICs and published in English. Results: From 236 publications included in the full text analysis, no studies fully complied with our inclusion criteria. Widening the focus by leaving out ‘agenda-setting’, we included ten studies, four of which had unique conceptual frameworks focusing on mental health and LMICs but not agenda-setting. The four analysed frameworks confirmed research gaps from LMICs and mental health, and a lack of focus on agenda-setting. Frameworks and models from other health and policy areas provide interesting conceptual approaches and lessons with regards to agenda-setting. Conclusion: Our systematic review identified frameworks on evidence and policy interrelations that differ in their elements and processes. No framework fulfilled all inclusion criteria. Four actionable frameworks are applicable to mental health and LMICs, but none specifically target agenda-setting. We have identified agenda-setting as a research theory gap in the context of mental health knowledge translation in LMICs. Frameworks from other health/policy areas could offer lessons on agenda-setting and new approaches for creating policy impact for mental health and to tackle the translational gap in LMICs

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty