Genetic variants in the KIF6 region and coronary event reduction from statin therapy

A single nucleotide polymorphism (SNP) in KIF6, a member of the KIF9 family of kinesins, is associated with differential coronary event reduction from statin therapy in four randomized controlled trials; this SNP (rs20455) is also associated with the risk for coronary heart disease (CHD) in multiple prospective studies. We investigated whether other common SNPs in the KIF6 region were associated with event reduction from statin therapy. Of the 170 SNPs in the KIF6 region investigated in the Cholesterol and Recurrent Events trial (CARE), 28 were associated with differential event reduction from statin therapy (Pinteraction < 0.1 in Caucasians, adjusted for age and sex) and were further investigated in the Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis In Myocardial Infarction 22 (PROVE IT-TIMI22) and West of Scotland Coronary Prevention Study (WOSCOPS). These analyses revealed that two SNPs (rs9462535 and rs9471077), in addition to rs20455, were associated with event reduction from statin therapy (Pinteraction < 0.1 in each of the three studies). The relative risk reduction ranged from 37 to 50% (P < 0.01) in carriers of the minor alleles of these SNPs and from −4 to 13% (P > 0.4) in non-carriers. These three SNPs are in high linkage disequilibrium with one another (r2 > 0.84). Functional studies of these variants may help to understand the role of KIF6 in the pathogenesis of CHD and differential response to statin therapy

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

The Water Bugs (Heteroptera: Nepomorpha) of the Guyana Region

NEPOMORPHA OF THE GUYANA REGION The Nepomorpha of the Guyana Region are keyed out and described. In addition distributional, faunistical and comparative notes on the species are given. New species and subspecies: Ochterus aeneifrons surinamensis, O. tenebrosus; Limnocoris fittkaui surinamensis; Ranatra adelomorpha; Neoplea globoidea; Buenoa amnigenopsis; Tenagobia pseudoromani from Suriname and Ranatra ornitheia from Guyana. New synonyms (junior ones between parenthesis): Gelaslocorus flavus flavus Guér. (G. nebulosus nebulosus Guér.); Pelocoris impicticollis Stål (P. horváthi Mont.), P. poeyi (Guér.) not identical with P. femoratus (P.-B.) (P. convexus Nieser), P. procurrens White (P. minutus Mont.); Belostoma bicavum Lauck ( B. parvoculum Lauck); Ranatra doesburgi De Carlo (R. usingeri De C.), R. macrophthalma H.-S. (R. surinamensis De C.), R. mediana Mont. (R. williamsi Kuitert), R. obscura Mont. (R. annulipes White 1879 not Stål), R. sarmentoi De C. (R. ameghinoi De C.); Buenoa amnigenopsis n. sp. ( B. amnigenus Nieser 1968, 1970 not White), B. amnigenus (White) (B. amnigenoidea Nieser 1970), B. nitida Truxal (B. doesburgi Nieser); Heterocorixa surinamensis Nieser ( H. boliviensis Nieser 1970 not Hungerford); Tenagobia incerta Lundbl. ( T. signata and T. serrata in part, Nieser 1970 not White and Deay respectively), T. socialis (White) (T. serrata in part, Nieser 1970 not Deay)

A framework for increasing the availability of life cycle inventory data based on the role of multinational companies

Purpose The aim of the paper is to assesses the role and effectiveness of a proposed novel strategy for Life Cycle Inventory (LCI) data collection in the food sector and associated supply chains. The study represents one of the first of its type and provides answers to some of the key questions regarding the data collection process developed, managed and implemented by a multinational food company across the supply chain. Methods An integrated LCI data collection process for confectionery products was developed and implemented by Nestlé, a multinational food company. Some of the key features includes: (1) management and implementation by a multinational food company, (2) types of roles to manage, provide and facilitate data exchange, (3) procedures to identify key products, suppliers and customers, (4) LCI questionnaire and cover letter, and (5) data quality management based on the pedigree matrix. Overall, the combined features in an integrated framework provides a new way of thinking about the collection of LCI data from the perspective of a multinational food company. Results The integrated LCI collection framework spanned across five months and resulted in 87 new LCI datasets for confectionery products from raw material, primary resource use, emission and waste release data collected from suppliers across 19 countries. The data collected was found to be of medium-to-high quality compared with secondary data. However, for retailers and waste service companies only partially completed questionnaires were returned. Some of the key challenges encountered during the collection and creation of data included: lack of experience, identifying key actors, communication and technical language, commercial compromise, confidentiality protection, and complexity of multi-tiered supplier systems. A range of recommendations are proposed to reconcile these challenges which include: standardisation of environmental data from suppliers, concise and targeted LCI questionnaires, and visualising complexity through drawings. Conclusions The integrated LCI data collection process and strategy has demonstrated the potential role of a multinational company to quickly engage and act as a strong enabler to unlock latent data for various aspects of the confectionery supply chain. Overall, it is recommended that the research findings serve as the foundations to transition towards a standardised procedure which can practically guide other multinational companies to considerably increase the availability of LCI data

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease.Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone.Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p<0.0001; reference model: 2.56, 1.85-3.53, p<0.0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0.768). Meta-analysis across all methods confirmed previously identified predictive clinical variables and revealed aspartate aminotransferase as an important, albeit previously under-reported, prognostic biomarker.Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer

Characteristics associated with inappropriate hospital use in elderly patients admitted to a general internal medicine service

Our objective was to identify patient characteristics associated with inappropriate hospital days in a cohort of elderly medical inpatients. This prospective cohort study included a total of 196 patients aged 75 years and older, who were consecutively admitted over eight months to the internal medicine service of a regional, non-academic public hospital located in a rural area of Western Switzerland. Patients with severe cognitive impairment, terminal disease, or previously living in a nursing home were excluded. Data on demographics, medical, physical, social and mental status were collected at admission. A blinded hospitalization review was performed concurrently using a modified version of the Appropriateness Evaluation Protocol (AEP). Subjects' mean age was 82.4 years; 63.3% were women. Median length of stay was 8 days. Overall, 68 patients (34.7%) had at least one inappropriate day during their stay, including 18 patients (9.2%) whose hospital admission and entire stay were considered inappropriate. Most inappropriate days were due to discharge delays (87.10%), primarily to nursing homes (59.30%). Univariate analysis showed that subjects with inappropriate days were more likely to be living alone (69.1 vs 48.4%, p=0.006), and receiving formal in-home help (48.5 vs 32.8%, p=0.031). In addition, they were more impaired in basic and instrumental activities of daily living (BADLs, and IADLs, p&lt;0.001 and p=0.015, respectively), and more frequently had a depressed mood [29.4 vs 10.9%, p=0.001 with a score &gt; 6 at the Geriatric Depression Scale (GDS), short form]. Using multivariate analysis, independent associations remained for patients living alone (OR 2.6, 95%CI 1.2-5.8, p=0.016), those with a depressed mood (OR 2.8, 95%CI 1.1-7.3, p=0.032), with BADL dependencies (OR 1.5, 95%CI 1.2-1.8, p=0.001), and IADL dependencies (OR 1.3, 95%CI 1.0-1.6, p=0.032). Cardiovascular (OR 0.2, 95%CI 0.1-0.7, p=0.008) and pulmonary admission diagnoses (OR 0.1, 95%CI 0.0-0.7, p=0.022) were inversely associated with inappropriate hospital days. In conclusion, patients living alone, functionally impaired and showing depressive symptoms were at increased risk for inappropriate hospital days. These characteristics might permit better targeting for early discharge planning in these at-risk subjects, and contribute to avoiding premature discharge of other vulnerable elderly patients. Whether these interventions for at-risk patients will also result in prevention of hospitalization hazards, such as deconditioning and related functional decline, will require further study