From Cancer to Diarrhea: The Moving Target of Public Concern about Environmental Health Risks

Public concern about the environment can be unpredictable because it is influenced by numerous factors. Environmental health issues often emerge as important because the public is worried about their health especially when it comes to cancer. Public fear of cancer from environmental exposures is reinforced by many of the US regulations that set pollutant limits based on reducing the risk of cancers rather than other health outcomes. While fear of cancer will never dissipate, recent foodborne outbreaks are contributing to raising public awareness of the health effects from microbes. This paper adds to the dialogue about the challenges of enhancing public understanding of environmental health issues. Internal factors, such as worry, that contribute to public outrage are sometimes more important than external factors such as the media. In addition, relying on the media to inform the public about imminent public health risks may be an ineffective approach to enhancing understanding. In the end, scientists and risk communicators are forced to compete with politicians who are often very effective at manipulating public understanding of risk

A pilot randomized controlled trial of a stepped care intervention package for depression in primary care in Nigeria

Background Depression is common in primary care and is often unrecognized and untreated. Studies are needed to demonstrate the feasibility of implementing evidence-based depression care provided by primary health care workers (PHCWs) in sub-Saharan Africa. We carried out a pilot two-parallel arm cluster randomized controlled trial of a package of care for depression in primary care. Methods Six primary health care centers (PHCC) in two Local Government Areas of Oyo State, South West Nigeria were randomized into 3 intervention and 3 control clinics. Three PHCWs were selected for training from each of the participating clinics. The PHCWs from the intervention clinics were trained to deliver a manualized multicomponent stepped care intervention package for depression consisting of psychoeducation, activity scheduling, problem solving treatment and medication for severe depression. Providers from the control clinics delivered care as usual, enhanced by a refresher training on depression diagnosis and management. Outcome measures Patient’s Health Questionnaire (PHQ-9), WHO quality of Life instrument (WHOQOL-Bref) and the WHO disability assessment schedule (WHODAS) were administered in the participants’ home at baseline, 3 and 6 months. Results About 98% of the consecutive attendees to the clinics agreed to have the screening interview. Of those screened, 284 (22.7%) were positive (PHQ-9 score ≥ 8) and 234 gave consent for inclusion in the study: 165 from intervention and 69 from control clinics. The rates of eligible and consenting participants were similar in the control and intervention arms. In all 85.9% (92.8% in intervention and 83% in control) of the participants were successfully administered outcome assessments at 6 months. The PHCWs had little difficulty in delivering the intervention package. At 6 months follow up, depression symptoms had improved in 73.0% from the intervention arm compared to 51.6% control. Compared to the mean scores at baseline, there was improvement in the mean scores on all outcome measures in both arms at six months. Conclusion The results provide support for the feasibility of conducting a fully-powered randomized study in this setting and suggest that the instruments used may have the potential to detect differences between the arms

Do regional brain volumes and major depressive disorder share genetic architecture?:A study of Generation Scotland (<i>n</i>=19,762), UK Biobank (<i>n</i>=24,048) and the English Longitudinal Study of Ageing (<i>n</i>=5,766)

Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium's genome-wide association study of regional brain volume, we sought to test whether there is shared genetic architecture between seven subcortical brain volumes and intracranial volume (ICV) and MDD. We explored this using linkage disequilibrium score regression, polygenic risk scoring (PRS) techniques, Mendelian randomisation (MR) analysis and BUHMBOX. Utilising summary statistics from ENIGMA and Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of the other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. Using PRS analysis, no regional volumetric PRS demonstrated a significant association with MDD or recurrent MDD. MR analysis in hippocampal volume and MDD identified no causal association, however, BUHMBOX analysis identified genetic subgrouping in GS:SFHS MDD cases only (P=0.00281). In this study, we provide some evidence that hippocampal volume and MDD may share genetic architecture in a subgroup of individuals, albeit the genetic correlation did not survive multiple testing correction and genetic subgroup heterogeneity was not replicated. In contrast, we found no evidence to support a shared genetic architecture between MDD and other regional subcortical volumes or ICV

Publication Bias in Antipsychotic Trials: An Analysis of Efficacy Comparing the Published Literature to the US Food and Drug Administration Database

A comparison of data held by the U.S. Food and Drug Administration (FDA) against data from journal reports of clinical trials enables estimation of the extent of publication bias for antipsychotics

Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques

<p>Abstract</p> <p>Background</p> <p>Protein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.</p> <p>Results</p> <p>We applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K_d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least- squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P²= 0.67-0.73; for new kinases it ranged P²_kin= 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P²= 0.47, P²_kin= 0.42 and AUC = 0.83.</p> <p>Conclusions</p> <p>Our results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.</p

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally

The implications of three major new trials for the effect of water, sanitation and hygiene on childhood diarrhea and stunting: a consensus statement

BACKGROUND: Three large new trials of unprecedented scale and cost, which included novel factorial designs, have found no effect of basic water, sanitation and hygiene (WASH) interventions on childhood stunting, and only mixed effects on childhood diarrhea. Arriving at the inception of the United Nations' Sustainable Development Goals, and the bold new target of safely managed water, sanitation and hygiene for all by 2030, these results warrant the attention of researchers, policy-makers and practitioners. MAIN BODY: Here we report the conclusions of an expert meeting convened by the World Health Organization and the Bill and Melinda Gates Foundation to discuss these findings, and present five key consensus messages as a basis for wider discussion and debate in the WASH and nutrition sectors. We judge these trials to have high internal validity, constituting good evidence that these specific interventions had no effect on childhood linear growth, and mixed effects on childhood diarrhea. These results suggest that, in settings such as these, more comprehensive or ambitious WASH interventions may be needed to achieve a major impact on child health. CONCLUSION: These results are important because such basic interventions are often deployed in low-income rural settings with the expectation of improving child health, although this is rarely the sole justification. Our view is that these three new trials do not show that WASH in general cannot influence child linear growth, but they do demonstrate that these specific interventions had no influence in settings where stunting remains an important public health challenge. We support a call for transformative WASH, in so much as it encapsulates the guiding principle that - in any context - a comprehensive package of WASH interventions is needed that is tailored to address the local exposure landscape and enteric disease burden