bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved polygenic prediction by Bayesian multiple regression on summary statistics
Authors: Lloyd-Jones Luke R. , Zeng Jian , Sidorenko Julia , Yengo Loïc , Moser Gerhard , Kemper Kathryn E. , Wang Huanwei , Zheng Zhili , Magi Reedik , Esko Tonu , Metspalu Andres , Wray Naomi R. , Goddard Michael E. , Yang Jian , Visscher Peter M. 
Published: January 2019

ABSTRACTThe capacity to accurately predict an individual’s phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. Recently, Bayesian methods for generating polygenic predictors have been successfully applied in human genomics but require the individual level data, which are often limited in their access due to privacy or logistical concerns, and are computationally very intensive. This has motivated methodological frameworks that utilise publicly available genome-wide association studies (GWAS) summary data, which now for some traits include results from greater than a million individuals. In this study, we extend the established summary statistics methodological framework to include a class of point-normal mixture prior Bayesian regression models, which have been shown to generate optimal genetic predictions and can perform heritability estimation, variant mapping and estimate the distribution of the genetic effects. In a wide range of simulations and cross-validation using 10 real quantitative traits and 1.1 million variants on 350,000 individuals from the UK Biobank (UKB), we establish that our summary based method, SBayesR, performs similarly to methods that use the individual level data and outperforms other state-of-the-art summary statistics methods in terms of prediction accuracy and heritability estimation at a fraction of the computational resources. We generate polygenic predictors for body mass index and height in two independent data sets and show that by exploiting summary statistics on 1.1 million variants from the largest GWAS meta-analysis (n ≈ 700, 000) that the SBayesR prediction R2 improved on average across traits by 6.8% relative to that estimated from an individual-level data BayesR analysis of data from the UKB (n ≈ 450, 000). Compared with commonly used state-of-the-art summary-based methods, SBayesR improved the prediction R2 by 4.1% relative to LDpred and by 28.7% relative to clumping and p-value thresholding. SBayesR gave comparable prediction accuracy to the recent RSS method, which has a similar model, but at a computational time that is two orders of magnitude smaller. The methodology is implemented in a very efficient and user-friendly software tool titled GCTB.
Differential Effector Response of Amnion- and Adipose-Derived Mesenchymal Stem Cells to Inflammation; Implications for Intradiscal Therapy
Authors: Borem Ryan , Madeline Allison , Bowman Mackenzie , Gill Sanjitpal , Tokish John , Mercuri Jeremy 
Published: January 2019

ABSTRACTIntervertebral disc degeneration (IVDD) is a progressive condition marked by inflammation and tissue destruction. The effector functions of mesenchymal stem cells (MSCs) make them an attractive therapy for patients with IVDD. While several sources of MSCs exist, the optimal choice for use in the inflamed IVD remains a significant question. Adipose (AD)- and amnion (AM)-derived MSCs have several advantages compared to other sources, however, no study has directly compared the impact of IVDD inflammation on their effector functions. Human MSCs were cultured in media with or without supplementation of interleukin-1β and tumor necrosis factor-α at concentrations produced by IVDD cells. MSC proliferation and production of pro- and anti-inflammatory cytokines were quantified following 24- and 48-hours of culture. Additionally, the osteogenic and chondrogenic potential of AD- and AM-MSCs was characterized via histology and biochemical analysis following 28 days of culture. In inflammatory culture, AM-MSCs produced significantly more anti-inflammatory IL-10 (p=0.004) and larger chondrogenic pellets (p=0.04) with greater percent area staining positively for glycosaminoglycan (p<0.001) compared to AD-MSCs. Conversely, AD-MSCs proliferated more resulting in higher cell numbers (p=0.048) and produced higher concentrations of pro-inflammatory cytokines PGE2 (p=0.030) and IL-1β (p=0.010) compared to AM-MSCs. Additionally, AD-MSCs produced more mineralized matrix (p<0.001) compared to AM-MSCs. These findings begin to inform researchers and clinicians as to which MSC source may be optimal for different IVD therapies including those that may promote regeneration or fusion. Further study is warranted evaluating these cells in systems which recapitulate the nutrient- and oxygen-deprived environment of the degenerate IVD.
A DNA-based voltmeter for organelles
Authors: Saminathan Anand , Devany John , Pillai Kavya S. , Veetil Aneesh T. , Schwake Michael , Krishnan Yamuna 
Published: January 2019

AbstractThe role of membrane potential in most intracellular organelles remains unexplored because of the lack of suitable probes. We describe a DNA-based fluorescent reporter that quantitates membrane potential and can be targeted to specific organelles in live cells. It is equipped with a voltage sensitive fluorophore, a reference fluorophore for ratiometric quantification, and acts as an endocytic tracer. We could thereby measure the membrane potential of different intracellular organelles in living cells, which has not been possible previously. Our understanding of how membrane potential regulates organelle biology is poised to expand through the use of these new sensors.One Sentence SummaryUsing a DNA-based voltmeter we can non-invasively measure the membrane potential of specific organelles in live cells.
The Efficacy of the Antimicrobial Peptide Melittin and the Enzyme DNase I Against E. coli Biofilms
Authors: Phillips Abigail 
Published: January 2019

AbstractBiofilms are aggregations of bacteria that often cause nosocomial infections and are tolerant to antibiotic treatments due to a variety of factors, including the physical barrier of their matrix. One field of treatment that has been explored is the use of antimicrobial peptides, like melittin. Melittin has been demonstrated to have antimicrobial effects on bacteria in both a biofilm and a planktonic state. Its required concentration to affect biofilms, however, is too high to be applicable in clinical settings. One potential way to increase efficacy is to use a compound like DNase I that degrades the matrix and thereby increases the penetration of melittin into the biofilm. I investigated whether DNase I would enhance the efficacy of melittin in relatively low concentrations that could be clinically viable. Melittin and DNase I were applied to E. coli biofilms in 24-well plates, both individually and in combination; biofilm density was measured at two time-points afterwards, using a crystal violet staining assay. The results showed DNase I was the most effective treatment. Surprisingly, none of the melittin treatments were statistically significant. A second experiment investigated variation among 11 bioreplicates and found that there was approximately 5-fold variation in response to treatment with DNase I. Given these promising results, further study on DNase I should be conducted.ImportanceThis work is important as it is crucial to have as many viable treatment options as possible for biofilm infections. Biofilm infections are common and many of our standard antibiotic options are simply not effective against them. According to the NIH, 65% of microbial infections and 80% of chronic infections are associated with biofilms, costing the United States millions of dollars each year (Jamal et al., 2018). Every avenue that could potentially further efforts to increase the efficacy and practicality of treatment options should be explored. Antimicrobial peptides are one of the most promising fields for biofilm treatment, and this study further investigates the potential for treatment that they hold.
Inhibition of MreB and ftsZ proteins to minimize E. coli biofilms formation
Authors: Charles Emile 
Published: January 2019

AbstractIn the United States, more than two million individuals become infected by antibiotic-resistant bacteria, resulting in over 23,000 deaths annually. Bacterial biofilms, one of the major causes of this resistance, form a complex extracellular matrix that physically block antibiotic treatment. Within planktonic bacteria, two proteins, MreB and ftsZ, play a key role in bacterial cell growth and development. MreB regulates this development through maintaining the rod-like shape of gram-negative bacteria, while ftsZ regulates the timing and location of cell division. The present study compared the effects of two protein-inhibitors on biofilm formation of E. coli; the inhibitors, A22 Hydrochloride and PC190723, inhibit MreB (cell shape) and ftsZ (cell division), respectively. Efficacy was measured with a crystal violet staining assay. Four experiments were designed testing 1) the minimum inhibitory concentration of the inhibitors, 2) the synergistic effect of the inhibitors, 3) the microscopic effects of the inhibitors, and 4) the effect of the inhibitors on antibiotic susceptibility. A mid-level dosage of A22 significantly decreased biofilm density while there was no response to PC190732. The effect of A22 was verified microscopically, observing the change from bacilli cells to coccoid ones via the inhibition of MreB. In the second experiment, with conjunct inhibition, no interaction was found. Lastly, A22 was as effective as Amoxicillin in disrupting biofilms. The inhibition of MreB was found to have a key role in biofilm development. A model is proposed for biofilm density based on cell shape as affected by MreB.ImportanceEach year, more than 2 million Americans acquire antibiotic-resistant infection and 23,000 of them die (CDC, 2013). In a study done by Barsoumian et. al (2015), there was a 16% mortality rate pertaining to biofilm-related infections while non-biofilm infection caused a 5% mortality rate. These casualties aren’t limited to the United States. Abroad, antibiotic resistance is a huge issue: 25,000 deaths estimated in the EU; 38,000 deaths in Thailand; and 58,000 deaths in India, among infants alone (CDC, 2012). It is these statistics that inform us that antibiotic resistance must be addressed.
Human and mouse iPSC-derived astrocyte subtypes reveal vulnerability in Vanishing White Matter
Authors: Leferink Prisca S. , Dooves Stephanie , Hillen Anne E.J. , Watanabe Kyoko , Jacobs Gerbren , Gasparotto Lisa , Cornelissen-Steijger Paulien , van der Knaap Marjo S. , Heine Vivi M. 
Published: January 2019

AbstractAstrocytes gained attention as important players in neurological disease, including a number of leukodystrophies. Several studies explored the generation of induced pluripotent stem cell-derived astrocytes for drug screening and regenerative studies. Developing robust models of patient induced pluripotent stem cells is challenged by high variability due to diverse genetic backgrounds and long-term culture procedures. While human models are of special interest, mouse-based models have the advantage that for them these issues are less pronounced. Here we present astrocyte differentiation protocols for both human and mouse induced pluripotent stem cells to specifically induce grey and white matter astrocytes. Both subtypes expressed astrocyte-associated markers, had typical astrocyte morphologies, and gave a reactive response to stress. Importantly, the grey and white matter-like astrocytes differed in size, complexity of processes, and expression profile, conform primary grey and white matter astrocytes. The newly presented mouse and human stem cell-based models for the leukodystrophy Vanishing White Matter replicated earlier findings, such as increased proliferation, decreased OPC maturation and modulation by hyaluronidase. We studied intrinsic astrocyte subtype vulnerability in Vanishing White Matter in both human and mouse cells. Oligodendrocyte maturation was specifically inhibited in cultures with Vanishing White Matter white matter-like astrocytes. By performing RNA sequencing, we found more differentially regulated genes in the white than in the grey matter-like astrocytes. Human and mouse astrocytes showed the same affected pathways, although human white matter-like astrocytes presented human-specific disease mechanisms involved in Vanishing White Matter. Using both human and mouse induced pluripotent stem cells, our study presents protocols to generate white and grey matter-like astrocytes, and shows astrocyte subtype-specific defects in Vanishing White Matter. While mouse induced pluripotent stem cell-based cultures may be less suitable to mimic human astrocyte subtype- or patient-specific changes, they might more robustly represent disease mutation-related cellular phenotypes as the cells are derived from inbred mice and the protocols are faster. The presented models give new tools to generate astrocyte subtypes forin vitrodisease modeling andin vivoregenerative applications.
To what extent gene connectivity within co-expression network matters for phenotype prediction?
Authors: Chateigner Aurélien , Lesage-Descauses Marie-Claude , Rogier Odile , Jorge Véronique , Leplé Jean-Charles , Brunaud Véronique , Roux Christine Paysant-Le , Soubigou-Taconnat Ludivine , Martin-Magniette Marie-Laure , Sanchez Leopoldo , Segura Vincent 
Published: January 2019

AbstractRecent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. We sequenced RNA in a Populus nigra collection and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes deemed important for trait prediction, they did not systematically predict better than peripherals or even random genes. Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.
Understanding the variation in wood densities of trees and its implications for carbon assessments
Authors: Teegalapalli Karthik , Pandey Chandan Kumar , Osuri Anand M , Ratnam Jayashree , Sankaran Mahesh 
Published: January 2019

AbstractWood density is a key functional trait used to estimate aboveground biomass (AGB) and carbon stocks. A common practice in forest AGB and carbon estimation is to substitute genus averages (across species with known wood densities) in cases where wood densities of particular species are unknown. However, the extent to which genus-level averages are reflective of species wood densities across tree genera is uncertain, and understanding this is critical for estimating the accuracy of carbon stock estimates. Using primary field data from India and secondary data from a published global dataset, we quantified the extent to which wood density varied among individuals within species (intraspecific variation) at the regional scale and among species within genera (interspecific variation) at regional to global scales. We used a published global database with wood density data for 7743 species belonging to 1741 genera. Linear models were used to compare the species values with the genera averages and the individual values with the species averages, respectively. To estimate the error associated with using genus-level averages for carbon stocks estimation, we compared genus values averaged at the global, old world and continental scales with species values from actually measured data. We also ran a simulation using vegetation data from a published database to calculate the estimation errors in a 1 hectare plot level when genera-averaged wood densities are used. Intraspecific variation was significantly lower than interspecific variation. Continental level genera averages led to estimates closer to the species values for the 10 genera for which most data on species was available. This was also evident from a comparison of genera averages at these three spatial scales with species values from our data. Species within certain ‘hypervarying’ genera showed relatively high levels of variation, irrespective of the spatial scale of the dataset used. The error in estimation of AGB when genera-averaged values were used for species wood densities was 0.35, 0.71 and 2.43% when 0, 10 and 25% of the girth of the trees in the simulated plot were from hypervariable genera. Our findings indicate that species values provide the most accurate estimates for individuals. Genus average wood density values at the continental scale provided more reliable estimates than those at larger spatial scales. The aboveground biomass estimation error when species wood densities were approximated to the genera-average values was 1.4 to 3.7 tonnes per ha when 10% and 25%, respectively, of the girth of trees was from species from hypervariable genera. Our findings indicate that regional or continental scale genera averages provide more reliable estimates than global data and we propose a method to identify hypervariable genera, for which species values rather than genera averages can provide better estimates of carbon stocks.
Do patients really perceive better quality of service in private hospitals than public hospitals in India?
Authors: Swain Swapnarag 
Published: January 2019

Purpose
The purpose of this paper is to compare perceived service quality of public/government and private medical college hospitals.

Design/methodology/approach
This study adopts a descriptive, cross-sectional and research design. The research sample includes 340 in patients from six medical college hospitals located in the state of Odisha, India. Primary data are collected through a structured closed ended questionnaire containing 66 items on 1–7 point Likert scale. Statistical tools like factor analysis and ANOVA are performed with the help of SPSS-17 software to analyze the collected data.

Findings
This study identifies 13 dimensions of perceived hospital service quality. The comparative study indicates better performance of public/government hospitals across the technical dimensions of perceived service quality, whereas private hospitals report better performance across majority of the functional dimensions.

Originality/value
In the Indian healthcare system, public hospitals provide low-cost healthcare targeted toward low to middle socio-economic population whereas, large corporate private hospitals provide high-cost healthcare targeted toward high-income group. So the comparison between them produces an obvious result indicating better service quality in private hospitals. Present study minimizes this gap by comparing the service quality of public and private medical college hospitals. Medical colleges ensure access to health services for a larger group of people. Thus, similarity in the segment of population receiving medical services in public and private medical colleges is higher, making the comparison of perceived service quality fairer.
Benchmarking the performance of dairy products in Chinese dairy industry
Authors: Wibowo Santoso , Yang Rongbin , Ramsaran Roshnee 
Published: January 2019

PurposeThe purpose of this paper is to present a review of the main factors that are important to consumers of dairy products and develop a new product performance index for evaluating and benchmarking the performance of dairy products. This helps dairy product companies understand their dairy products’ overall performance level, relative to other dairy products in the market.Design/methodology/approachA new product performance index is developed for evaluating and benchmarking the performance of dairy products with respect to multiple criteria. Seven important criteria are identified for evaluating and benchmarking the performance of dairy products. To deal with the subjective assessments of qualitative performance measures, linguistic terms approximated by fuzzy numbers are used. Based on the concept of the degree of dominance, a fuzzy multicriteria group decision-making approach is developed to obtain a product performance index for each dairy product.FindingsThe proposed multicriteria group decision-making approach is found to be useful and effective in evaluating and benchmarking the performance of dairy products. The approach is capable of adequately considering the presence of multiple decision makers, the multi-dimensional nature of the performance evaluation problem, and modeling the subjectiveness and imprecision of the performance evaluation process.Research limitations/implicationsThe outcome of the multicriteria group decision-making approach is dependent on the subjective inputs provided by the decision makers.Practical implicationsThis product performance index will provide useful insights for companies understand their strengths and weaknesses in terms of their products’ performance criteria, and identify relevant areas for continuous improvement. This product performance index is also applicable for dealing with the general multicriteria decision-making problems.Social implicationsThe proposed multicriteria group decision-making approach can be used as a decision-making tool for providing various decision makers in dairy product companies and general consumers with useful information regarding the performance of different dairy products.Originality/valueThis paper highlights the important factors for evaluating and benchmarking dairy products and develops a new product performance index for evaluating and benchmarking the performance of dairy products in China.
Quality assessment of city bus service based on subjective and objective service quality dimensions
Authors: Deb Saikat , Ahmed Mokaddes Ali 
Published: January 2019

Purpose
The purpose of this paper is to estimate and compare the service quality of the city bus service measured by two different approaches which are subjective service quality dimensions and objective service quality dimensions.

Design/methodology/approach
The objective service quality dimensions have been estimated based on the benchmarking technique provided by the Ministry of Urban Development, India. For the analysis of subjective service quality dimensions, a questionnaire survey has been conducted to measure the users’ satisfaction and dissatisfaction about the service. The questionnaire consists of users’ socioeconomic characteristics and 23 questions related to city bus service quality dimensions. Questionnaire data have been analyzed by factor analysis, regression analysis and path analysis to find out the indicators representing subjective service quality dimensions. Finally, the overall service quality of the bus service has been determined based on both the measures.

Findings
The study indicates that the overall service quality of the bus service is different for subjective and objective analyses. While the objective measures show that the service quality is very good, the subjective measures indicate that the service is not doing well.

Research limitations/implications
The analysis of the subjective dimensions is complicated. Analysis of the subjective dimensions needed more expertise and resources than the objective analysis.

Originality/value
In this study, the estimated service quality of the bus service is more reliable than the other methods as it comprises of both operators’ perspective and passengers’ expectations from the service.