bluuebunny/crossref_metadata_2025_split huggingface dataset:
Eliminating redundancy among protein sequences using submodular optimization
Authors: Libbrecht Maxwell W. , Bilmes Jeffrey A. , Noble William Stafford 
Published: May 2016

AbstactMotivationSubmodular optimization, a discrete analogue to continuous convex optimization, has been used with great success in many fields but is not yet widely used in biology. We apply submodular optimization to the problem of removing redundancy in protein sequence data sets. This is a common step in many bioinformatics and structural biology workflows, including creation of non-redundant training sets for sequence and structural models as well as selection of “operational taxonomic units” from metagenomics data.ResultsWe demonstrate that the submodular optimization approach results in representative protein sequence subsets with greater structural diversity than sets chosen by existing methods. In particular, we compare to a widely used, heuristic algorithm implemented in software tools such as CD-HIT, as well to as a variety of standard clustering methods, using as a gold standard the SCOPe library of protein domain structures. In this setting, submodular optimization consistently yields protein sequence subsets that include more SCOPe domain families than sets of the same size selected by competing approaches. We also show how the optimization framework allows us to design a mixture objective function that performs well for both large and small representative sets. The framework we describe is theoretically optimal under some assumptions, and it is flexible and intuitive because it applies generic methods to optimize one of a variety of objective functions. This application serves as a model for how submodular optimization can be applied to other discrete problems in biology.AvailabilitySource code is available athttps://github.com/mlibbrecht/submodular_sequence_repset.Contactwilliam-noble@uw.edu
Chloroquine inhibits Zika Virus infection in different cellular models
Authors: Delvecchio Rodrigo , Higa Luiza M , Pezzuto Paula , Valadão Ana Luiza , Garcez Patrícia P , Monteiro Fábio L , Loiola Erick C. , Rehen Stevens , Campanati Loraine , de Aguiar Renato Santana , Tanuri Amilcar 
Published: May 2016

SummaryZika virus (ZIKV) infectionin uteromight lead to microcephaly and other congenital defects. In adults, cases of Guillain-Barré syndrome and meningoencephalitis associated with ZIKV infection have been reported, and no specific therapy is available so far. There is urgency for the discovery of antiviral agents capable of inhibiting viral replication and its deleterious effects. Chloroquine is widely administered as an antimalarial drug, anti-inflammatory agent, and it also shows antiviral activity against several viruses. Here we show that chloroquine exhibits antiviral activity against ZIKV in VERO, human brain microvascular endothelial, and neural stem cells. We demonstratedin vitrothat chloroquine reduces the number of ZIKV-infected cells, virus production and cell death promoted by ZIKV infection without cytotoxic effects. Our results suggest that chloroquine is a promising candidate for ZIKV clinical trials, since it is already approved for clinical use and can be safely administered to pregnant woman.
Systematic exploration of unsupervised methods for mapping behavior
Authors: Todd Jeremy G. , Kain Jamey S. , de Bivort Benjamin L. 
Published: May 2016

AbstractTo fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a data set consisting of the x-and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when the probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.AbbreviationsGMM: Gaussian mixture model; PCA: principal components analysis; SW: sparse watershed; t-SNE: t-distributed stochastic neighbor embedding
Sub-atomic resolution X-ray diffraction of the SH3 domain from the post-synaptic density protein Shank3
Authors: Ponna Srinivas Kumar , Myllykoski Matti , Boeckers Tobias M. , Kursula Petri 
Published: May 2016

AbstractThe post-synaptic density multidomain scaffolding proteins of the Shank family are structurally poorly characterised. The Shank family consists of three members, and domain-specific interactions of Shank are involved in forming a network of proteins at the post-synaptic region for intracellular signalling and cellular scaffolding. While X-ray crystallography has provided some information on individual Shank domains, the structural basis of Shank interactions is still largely unknown. In this study, the production and crystallisation of the previously uncharacterised Shank3 SH3 domain is presented. The highly twinned crystals diffracted synchrotron X-rays to a resolution higher than 0.9 Å, and these crystals will eventually have the potential to provide an ultrahigh-resolution view into the Shank family SH3 domains and their interactions.
Multi-ethnic polygenic risk scores improve risk prediction in diverse populations
Authors: Márquez-Luna Carla , Loh Po-Ru ,   South Asian Type 2 Diabetes (SAT2D) Consortium,   The SIGMA Type 2 Diabetes Consortium, Price Alkes L. 
Published: May 2016

AbstractMethods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multi-ethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size and Latino training data in small sample size. We attained a >70% relative improvement in prediction accuracy (fromR2=0.027 toR2=0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. Application of our approach to predict T2D in a South Asian UK Biobank cohort attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.Author SummaryThe use of genetic information to predict disease risk is of great interest because of its potential clinical application. Prediction is performed via the construction of polygenic risk scores, which separate individuals into different risk categories. Polygenic risk scores can also be applied to improve our understanding of the genetic architecture of complex diseases. The ideal training data set would be a large cohort from the same population as the target sample, but this is generally unavailable for non-European populations. Thus, we propose a summary statistics based polygenic risk score that leverages both a large European training sample and a training sample from the same population as the target population. This approach produces a substantial relative improvement in prediction accuracy compared to methods that use a single training population when applied to predict type 2 diabetes in a Latino cohort, consistent with simulation results. We observed similar relative improvements in applications to predict type 2 diabetes in a South Asian cohort and height in an African cohort.
Design leaps: business model adaptation in emerging economies
Authors: Sharma Sunil , Dixit Mukund R. , Karna Amit 
Published: May 2016

PurposeFirms take design leaps when they imitate an established business model developed either by another firm or in another market to create business opportunities. While recent research has suggested the use of contextual intelligence for imitation, the exact process of adaptation of a business model is not fully understood. The purpose of this paper is to outline the process through which an emerging market firm adapts a developed market business model for creating business opportunities in the local market.Design/methodology/approachThis paper investigates the journey of Air Deccan, the pioneer low-cost airline in India, from its founding until its successful adaptation of a (Western) business model and eventual failure. The authors use a qualitative case-based approach to study business model adaptation.FindingsThe authors find that adaptation involves the incorporation of following design features: novelty to overcome problem of institutional voids, elasticity to exploit unexpected increase in demand and efficiency to serve large volumes. Based on the evidence, the authors suggest the introduction of global efficiency measures as the boundary conditions of business model adaptation in emerging markets.Research limitations/implicationsThe paper contributes to the literature on business models by suggesting elasticity as a unique design feature relevant for emerging markets. This paper provides granular understanding of business model toxicity.Practical implicationsEntrepreneurs and managers – looking to enter emerging markets through opportunity creation – should focus on providing contextually novel design features in the adapted business model. The authors also caution practitioners against the perils of toxicity arising out of combining contextual novelty with efficiency.Originality/valueRecent literature suggests that multinationals need contextual intelligence to successfully monetize their investment in emerging economies. This paper provides rich description of the challenges faced by entrepreneurs in emerging markets, local innovations used to overcome them and boundary conditions.
Investment and collaboration: the Indian model for “best” HRM practices
Authors: Rao Pramila 
Published: May 2016

Purpose
The purpose of this paper is to examine human resource management (HRM) practices of the top 25 companies identified as “best” in India in 2011. This paper provides insights into HRM practices of a leading country in Asia that is playing a very important role in the global economy.

Design/methodology/approach
This conceptual paper will use for its research analysis the business reports of the Outlook Business Magazine and AON Hewitt. AON Hewitt is a global human resource consulting company and is an established authority in identifying “best” companies in India since 2004. A qualitative content analysis was done of the business report to identify predominant themes.

Findings
The analysis identified how the “best” 25 Indian companies offer progressive HRM practices that required careful investment and collaboration. This research showcases seven specific HRM themes that include elaborate staffing, investment in learning, work–life balance, egalitarian practices, developmental performance culture, generous benefits and engagement initiatives.

Practical implications
This paper provides preliminary guidelines for global practitioners who may be interested in doing business in India. It also provides a model of “best” HRM practices adopted by 25 companies that could help other organizations identify successful HRM practices in India. Among the 25 companies, 16 are Indian companies and 9 are subsidiaries of multinationals.

Originality/value
This paper outlines HRM “best” practices of organizations in an emerging Asian economy that has not been addressed before. This paper hopes to bridge this paucity in the extant literature by showcasing the “best” HRM practices from 25 “best” companies in India. It also provides an Indian model of “best” HRM practices that can be tested by other scholars for future studies.
Wage Growth for the Health Care Workforce: Projecting the Affordable Care Act Impact
Authors: Parente Stephen T. , Feldman Roger , Spetz Joanne , Dowd Bryan , Baggett Emily Egan 
Published: May 2016

ObjectiveTo predict changes in wage growth for health care workers based on projections of insurance enrollment from the Affordable Care Act (ACA).Data SourcesEnrollment data came from three large employers and a sampling of premiums from ehealthinsurance.com. Information on state Medicaid eligibility rules and costs were from the Kaiser Family Foundation. National predictions were based on the MEPS and Medicare Current Beneficiary surveys. Bureau of Labor Statistics data were used to estimate employment.Study DesignWe projected health insurance enrollment by plan type using a health plan choice model. Using claims data, we measured the services demanded for each plan choice and year. Projections of labor demand were based on current output/input ratios. Changes in wages resulting from changes in labor demand from 2014 to 2021 were based on labor supply and demand elasticities.Principal FindingsExpenditures required to retain and grow the health care workforce will increase substantially. Wages will increase most for professions with the greatest training requirements (physicians and registered nurses). The largest impact will be felt in 2015.ConclusionsProjected wage increases for health care workers may drive substantial growth in insurance premiums and reduce the affordability of health insurance.
Geographic Variation in Quality of Care for Commercially Insured Patients
Authors: McKellar Michael Richard , Landrum Mary Beth , Gibson Teresa B. , Landon Bruce E. , Fendrick A. Mark , Chernew Michael E. 
Published: May 2016

BackgroundExtensive evidence documents geographic variation in spending, but limited research assesses geographic variation in quality, particularly among commercially insured enrollees.ObjectiveTo measure geographic variation in quality measures, correlation among measures, and correlation between measures and spending for commercially insured enrollees.Data SourceAdministrative claims from the 2007–2009 Truven MarketScan database.MethodsWe calculated variation in, and correlations among, 10 quality measures across 306 Hospital Referral Regions (HRRs), adjusting for beneficiary traits and sample size differences. Further, we created a quality index and correlated it with spending.ResultsThe coefficient of variation of HRR‐level performance ranged from 0.04 to 0.38. Correlations among quality measures generally ranged from 0.2 to 0.5. Quality was modestly positively related to spending.ConclusionQuality varied across HRRs and there was only a modest geographic “quality footprint.”
Spinal fentanyl vs. sufentanil for post‐operative analgesia after C‐section: a double‐blinded randomised trial
Authors: Wilwerth M. , Majcher J.‐L. , Van der Linden P. 
Published: May 2016

BackgroundFentanyl and sufentanil are the most commonly administered intrathecal lipophilic opioids worldwide, although their relative efficacy when given by this route is not well characterised.The primary endpoint of this prospective, randomised, double‐blind study was to compare effective analgesia duration of intrathecal administered fentanyl 25 μg and sufentanil 2.5 or 5 μg, Second endpoints were to compare post‐operative morphine consumption and incidence of side effects between these opioids dosages.MethodsAfter IRB approval, 180 full‐term parturients undergoing elective Caesarean section were randomly allocated into three groups, according to the opioid added to 10 mg intrathecal hyperbaric bupivacaine: fentanyl 25 μg, sufentanil 2.5 μg or sufentanil 5 μg. Total effective analgesia was defined as time from spinal injection (T0) to first IV morphine requirement (T1) administered with a patient controlled intravenous pump. Statistical data analysis included non‐parametric tests and chi‐squared. A P value < 0.05 was considered statistically significant. Data are presented as median [interquartile ranges 25–75].ResultsDuration of analgesia was significantly longer with sufentanil 2.5 μg (214 min [189–251]) and 5 μg (236 min [190–372]) compared to fentanyl 25 μg (187 min [151–230]) (P < 0.01). Morphine consumption at T1 + 4 h was lower in the sufentanil groups (6 mg [3–9] and 6 mg [2–10]) than in the fentanyl group (9 mg [5–13]) (P < 0.01). Incidence of adverse effects was not different between groups.ConclusionIn the conditions of our study, sufentanil 5 μg was the opioid of choice, associated with the best quality of anaesthesia without increased incidence of side effects.
Food for Thought: A Randomised Controlled Trial of Emotional Freedom Techniques and Cognitive Behavioural Therapy in the Treatment of Food Cravings
Authors: Stapleton Peta , Bannatyne Amy Jean , Urzi Keri‐Charle , Porter Brett , Sheldon Terri 
Published: May 2016

Addressing the internal determinants of dysfunctional eating behaviours (e.g. food cravings) in the prevention and treatment of obesity has been increasingly recognised. This study compared Emotional Freedom Techniques (EFT) to Cognitive Behavioural Therapy (CBT) for food cravings in adults who were overweight or obese (N = 83) in an 8‐week intervention. Outcome data were collected at baseline, post‐intervention, and at 6‐ and 12‐months follow‐up. Overall, EFT and CBT demonstrated comparable efficacy in reducing food cravings, one's responsiveness to food in the environment (power of food), and dietary restraint, with Cohen's effect size values suggesting moderate to high practical significance for both interventions. Results also revealed that both EFT and CBT are capable of producing treatment effects that are clinically meaningful, with reductions in food cravings, the power of food, and dietary restraint normalising to the scores of a non‐clinical community sample. While reductions in BMI were not observed, the current study supports the suggestion that psychological interventions are beneficial for food cravings and both CBT and EFT could serve as vital adjunct tools in a multidisciplinary approach to managing obesity.
Risk factors for traumatic dental injuries in the primary dentition: concepts, interpretation, and evidence
Authors: Feldens Carlos Alberto , Borges Tássia Silvana , Vargas‐Ferreira Fabiana , Kramer Paulo Floriani 
Published: May 2016

AbstractThe purpose of this comprehensive review is to explore the main concepts related to quantification and interpretation of risk factors and investigate characteristics associated with traumatic dental injuries (TDI) in the primary dentition. Initially, the main concepts related to causality and risk factors were summarized, including how to measure, express, and compare risk as well as interpret statistical significance. Based on a structured search through PubMed, original research articles regarding TDI and associated factors in the primary dentition were then reviewed by two examiners. Studies with a sample size of at least 300 children aged between 0 and 6 years were summarized according to journal, country, study design, and type of statistical analysis. Variables associated with TDI in primary teeth were identified from studies with multivariable analysis. Measures of effect size and P values were presented. Thirty‐two studies were retrieved: most were cross‐sectional in design and only 17 (53.1%) performed multivariable analysis. Most investigations did not find an association between gender and socioeconomic variables with TDI. Increased overjet was the only factor consistently identified as an associated factor. Behavioral characteristics have been recently investigated and suggested as potential risk factors for TDI in the primary dentition. In conclusion, increased overjet is undoubtedly associated with TDI in the primary dentition. As behavioral factors may be targeted by preventive strategies, their role on TDI occurrence should be clarified in future cohort studies. Clinicians should understand the terms and measures described in studies on risk factors to properly apply knowledge and benefit patients.
Climate‐driven changes to ocean circulation and their inferred impacts on marine dispersal patterns
Authors: Wilson Laura J. , Fulton Christopher J. , Hogg Andrew McC , Joyce Karen E. , Radford Ben T. M. , Fraser Ceridwen I. 
Published: May 2016

AbstractAimThe dispersal and distribution patterns of many marine organisms are driven by oceanographic conditions, which are influenced by global climate. Climate‐driven oceanographic changes are thus likely to result in biogeographical changes. We assess how recent and predicted oceanographic changes affect the dispersal capacities and distributions of ecologically important (especially habitat‐forming) marine organisms.LocationWe include studies from tropical, temperate and sub‐polar regions to draw globally relevant conclusions.MethodsWe review biogeographical, biological and oceanographic studies to critically evaluate emerging trends in biogeographical responses to climate‐driven oceanographic changes, and predict how future changes will affect marine ecosystems.ResultsMany oceanic dispersal pathways are being altered by climate change. These changes will affect marine ecosystems by differentially affecting the replenishment potential and connectivity of key habitat‐forming species. In particular, the length of propagule pre‐competency periods, propagule behaviour and the geographical distance between areas of suitable habitat will be critical in determining how oceanographic changes affect the pattern and success of dispersal events, including the likelihood of species experiencing poleward range shifts in response to a warming climate.Main conclusionsFuture climate‐driven oceanographic changes are likely to strengthen or weaken different oceanic dispersal pathways, which will either increase or decrease the potential for dispersal and connectivity in various marine taxa according to the interaction between the local oceanographic, geographical and taxon‐specific biological factors. A key focus for future work should be the development of fine‐scale near‐shore ocean circulation models that can be used to assess the dispersal response of key marine taxa under various marine climate change scenarios.