bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alteration of cardiolipin-dependent mitochondrial coupling in muscle protects against obesity
Authors: Prola Alexandre , Blondelle Jordan , Vandestienne Aymeline , Piquereau Jérôme , Denis Raphaël GP , Guyot Stéphane , Chauvin Hadrien , Mourier Arnaud , Letheule Martine , Maurer Marie , Henry Céline , Khadhraoui Nahed , Courtin Guillaume , Blanchard-Gutton Nicolas , Guillaud Laurent , Barthélémy Inès , Gressette Mélanie , Solgadi Audrey , Dumont Florent , Castel Julien , Ternacle Julien , Demarquoy Jean , Malgoyre Alexandra , Koulmann Nathalie , Derumeaux Geneviève , Giraud Marie-France , Blot Stéphane , Joubert Frédéric , Veksler Vladimir , Luquet Serge , Relaix Frédéric , Tiret Laurent , Pilot-Storck Fanny 
Published: July 2019

SummaryThe tubular shape of mitochondrial cristae depends upon a specific composition of the inner mitochondrial membrane, including cardiolipin that allows strong curvature and promotes optimal organization of ATP synthase. Here we identifyHacd1,which encodes an enzyme involved in very long chain fatty acid biosynthesis, as a key regulator of composition, structure and functional properties of mitochondrial membranes in muscle. InHacd1-deficient mice, the reduced cardiolipin content was associated with dilation of cristae and caused defective phosphorylating respiration, characterized by absence of proton leak and oxidative stress.The skeletal muscle-specific mitochondrial coupling defect produced a global elevation in basal energy expenditure with increased carbohydrate and lipid catabolism, despite decreased muscle mass and locomotor capacities. Mice were protected against diet-induced obesity despite reduced muscle activity, providing anin vivoproof of concept that reducing mitochondrial coupling efficiency in skeletal muscle might be an actionable mechanism in metabolic disease conditions.
Biological Plasticity Rescues Target Activity in CRISPR Knockouts
Authors: Smits Arne H. , Ziebell Frederik , Joberty Gerard , Zinn Nico , Mueller William F. , Clauder-Münster Sandra , Eberhard Dirk , Savitski Maria Fälth , Grandi Paola , Jakob Petra , Michon Anne-Marie , Sun Hanice , Tessmer Karen , Bürckstümmer Tilmann , Bantscheff Marcus , Steinmetz Lars M. , Drewes Gerard , Huber Wolfgang 
Published: July 2019

AbstractGene knockouts (KOs) are efficiently engineered through CRISPR-Cas9-induced frameshift mutations. While DNA editing efficiency is readily verified by DNA sequencing, a systematic understanding of the efficiency of protein elimination has been lacking. Here, we devised an experimental strategy combining RNA-seq and triple-stage mass spectrometry (SPS-MS3) to characterize 193 genetically verified deletions targeting 136 distinct genes generated by CRISPR-induced frameshifts in HAP1 cells. We observed residual protein expression for about one third of the quantified targets, at variable levels from low to original, and identified two causal mechanisms, translation reinitiation leading to N-terminally truncated target proteins, or skipping of the edited exon leading to protein isoforms with internal sequence deletions. Detailed analysis of three truncated targets, BRD4, DNMT1 and NGLY1, revealed partial preservation of protein function. Our results imply that systematic characterization of residual protein expression or function in CRISPR-Cas9 generated KO lines is necessary for phenotype interpretation.
Identification of Leishmania donovani inhibitors from pathogen box compounds of Medicine for Malaria Venture
Authors: Tadele Markos , Abay Solomon M. , Makonnen Eyasu , Hailu Asrat 
Published: July 2019

AbstractLeishmaniasis is a collective term used to describe various pathological conditions caused by an obligate intracellular protozoan of the genus Leishmania. It is one of the neglected diseases and has been given low attention in drug discovery researches to narrow the existing gap in safety and efficacy of the currently used drugs to treat leishmaniasis. The challenge is further exacerbated by the emergence of drug resistance by the parasites. Aiming to look for potential anti-leishmanial hits and leads, we screened MMV Pathogen Box against clinically isolated L. donovani strain. Compounds were screened against promastigote, and then against amastigote stages; of which, 35 compounds showed >50% inhibition on promastigotes in the initial screen (1 μM). Out of these compounds, 9 compounds showed >70% inhibition with median inhibitory concentration (IC50) ranges from 12 nM to 491 nM on anti-promastigote assay and 53 to 704 nM on intracellular amastigote assay. Identified compounds demonstrated good safety on THP-1 cell lines and sheep RBCs, and appropriate physico-chemical property suitable for further drug development. Two compounds (MMV690102 and MMV688262) were identified as lead compounds. Among these compounds, anti-tubercular agent MMV688262 (delamanid) showed synergistic effect with amphotericin B, indicating the prospect of this compound for combination therapy. The current study indicates the presence of additional hits which may hold promise as starting points for anti-leishmanial drug discovery and in-depth structure activity relationship studies. Future works also needs to investigate antiamastigotes activity of remaining ‘hits’, which were not covered in the present study.Authors summaryVisceral leishmaniasis is a major public health problem in endemic regions. Different drugs have been used to treat visceral leishmaniasis. However, the available drugs are either toxic, non-compliance to the patient, painful upon administration, low in efficacy, or costly. New chemical entities that overcome the limitations of existing drugs are therefore desperately needed. Screening of 400 pathogen box compounds against of Leishmania donovani clinical isolate resulted in identification of 35 compounds with >50% inhibition against promastigotes at 1 μM. Out of these compounds, 9 showed >70% inhibition with median inhibitory concentration ranges from 12 nM to 491 nM on anti-promastigote assay, and 53 to 704 nM on intracellular amastigote assay. Our work identified new compounds which hold promise for further drug development.
TDP-43 regulates the expression levels of Disc-large in skeletal muscles to promote the assemble of the neuromuscular synapses in Drosophila
Authors: Strah Nina , Romano Giulia , Introna Clelia , Klima Raffaella , Megighian Aram , Nizzardo Monica , Feiguin Fabian 
Published: July 2019

AbstractBackgroundAlterations in the intracellular distribution of TDP-43 were observed in the skeletal muscles of patients suffering from ALS. However, it is not clear whether these modifications play an active role in the disease or represent a physiological adaptation to muscles homeostasis.ResultTo answer these questions, we modulated the activity of this protein in Drosophila muscles and observed that TDP-43 was required in these tissues to promote the formation and growth of the neuromuscular synapses. Moreover, we identified that TDP-43 regulates the expression levels of Disc-large (Dlg) and demonstrated that the modulation of Dlg activity, in skeletal muscles or motoneurons, was sufficient to recover the TDP-43-null locomotive and synaptic defects in flies. Additionally, we found that similar mechanisms are conserved in human cell lines and present in tissues derived from ALS patients.ConclusionsOur results uncover the physiological role of TDP-43 in skeletal muscles as well as the mechanisms behind the autonomous and non-autonomous behavior of this protein in the organization of the neuromuscular synapses.
The impact paths of social capital and the effects of microfinance
Authors: Xiong Fang , You Jia Lu 
Published: July 2019

Purpose
The purpose of this paper is to investigate the impact paths of the social capital and the effects of microfinance in rural China, and address effective methods to enhance the effects of microfinance for rural China.

Design/methodology/approach
Using a structural equation model with survey data from 350 rural households in China, this paper analyzes empirically whether greater level of social sanctions and social relations caused more tangible effects of microfinance, and whether tangible effects of microfinance are associated with social capital formation of households.

Findings
The results indicate that social capital promotes the effects of microfinance and the process of providing microfinance service is also the process of building social capital. Moreover, social sanctions diminish the effects of microfinance while social relations boost them and enhance the effects of microfinance that can encourage social capital formation. Results also show that a reverse causal relationship exists between social sanctions and social relations.

Research limitations/implications
The empirical results imply that actively utilizing and creating social capital is vital to improve the effects of microfinance, and microfinance institutions (MFIs) should concentrate more on harmonious social relations and deliberately build social capital.

Practical implications
These findings imply that actively utilizing and creating social capital is vital to improve the effects of microfinance, and the MFIs should concentrate more on harmonious social relations and deliberately build social capital to enhance the effects of microfinance while prudently use social sanctions.

Social implications
Enhancing the effects of microfinance, while prudently using social sanctions, increases households income.

Originality/value
This paper originates to investigate the links between the social capital and the effects of microfinance in a mutual way, and the results urge more attentions on the harmonious social relations which have been ignored to enhance the effects of microfinance.
SOM approach for clustering customers using credit card transactions
Authors: Yanık Seda , Elmorsy Abdelrahman 
Published: July 2019

Purpose
The purpose of this paper is to generate customer clusters using self-organizing map (SOM) approach, a machine learning technique with a big data set of credit card consumptions. The authors aim to use the consumption patterns of the customers in a period of three months deducted from the credit card transactions, specifically the consumption categories (e.g. food, entertainment, etc.).

Design/methodology/approach
The authors use a big data set of almost 40,000 credit card transactions to cluster customers. To deal with the size of the data set and the eliminated the required parametric assumptions the authors use a machine learning technique, SOMs. The variables used are grouped into three as demographical variables, categorical consumption variables and summary consumption variables. The variables are first converted to factors using principal component analysis. Then, the number of clusters is specified by k-means clustering trials. Then, clustering with SOM is conducted by only including the demographical variables and all variables. Then, a comparison is made and the significance of the variables is examined by analysis of variance.

Findings
The appropriate number of clusters is found to be 8 using k-means clusters. Then, the differences in categorical consumption levels are investigated between the clusters. However, they have been found to be insignificant, whereas the summary consumption variables are found to be significant between the clusters, as well as the demographical variables.

Originality/value
The originality of the study is to incorporate the credit card consumption variables of customers to cluster the bank customers. The authors use a big data set and dealt with it with a machine learning technique to deduct the consumption patterns to generate the clusters. Credit card transactions generate a vast amount of data to deduce valuable information. It is mainly used to detect fraud in the literature. To the best of the authors’ knowledge, consumption patterns obtained from credit card transaction are first used for clustering the customers in this study.
Making the student voice count: using qualitative student feedback to enhance the student experience
Authors: Shah Mahsood , Pabel Anja 
Published: July 2019

Purpose
The purpose of this paper is to outline how qualitative data can be used to gain insights into the experience of different cohorts of students including online and on-campus students.

Design/methodology/approach
Qualitative data from student surveys are used to analyse three years of data. The text analytics software Leximancer was used to analyse the qualitative student comments.

Findings
Comparing comments of on-campus and online students, the findings indicate that the students had different perceptions in regards to what they rated as best aspects of their course and what needed improvement.

Originality/value
The study is based on three years of qualitative comments collected in student surveys. The study is unique, given that previous studies have looked at qualitative comments in general rather than comparing the experience of online and on-campus students.
Exploring service quality and its customer consequences in the sports spectating sector
Authors: Koronios Konstantinos , Kriemadis Athanasios , Papadopoulos Andreas 
Published: July 2019

Purpose
The purpose of this paper is to investigate issues relevant to service quality and propose a conceptual model addressing the convictions held by consumers in relation to the service quality of sport services as regards spectators and their influence on sport consumption.

Design/methodology/approach
A quantitative method was used for the purpose of this study and 1,643 questionnaires were gathered and analyzed. The current research intended to employ an integrated service quality model within the scope of sport spectating. The model included five fundamental factors and they were examined in association with the behavioral intentions that spectators have. By combining all these factors and aspects, it was attempted to shape consumers’ general perception regarding quality in service. The model of the research considers quality in service to be a hierarchical construct comprising many dimensions and it is observed that service quality can be classified into five factors, all of which can be defined by a variety of corresponding sub-factors.

Findings
The outcomes showed that four of the suggested factors regarding quality (i.e. game quality, augmented service quality, interaction quality and outcome quality) had an important as well as favorable influence on sport consumption.

Research limitations/implications
The empirical evidence for this research is derived from one specific professional sport event (European Basketball League) and spectators who took part were from Greece. Future research could use a wider sample of sport events and the participation of spectators from various countries is necessary before such findings are generalized.

Originality/value
The present research provides a contemporary analysis of factors influencing sport spectators anticipated quality and their influence on sport consumption.
“… They don’t really listen to people”
Authors: Creswick Helen , Dowthwaite Liz , Koene Ansgar , Perez Vallejos Elvira , Portillo Virginia , Cano Monica , Woodard Christopher 
Published: July 2019

PurposeThe voices of children and young people have been largely neglected in discussions of the extent to which the internet takes into account their needs and concerns. This paper aims to highlight young people’s lived experiences of being online.Design/methodology/approachResults are drawn from the UnBias project’s youth led discussions, “Youth Juries” with young people predominantly aged between 13 and 17 years.FindingsWhilst the young people are able to use their agency online in some circumstances, many often experience feelings of disempowerment and resignation, particularly in relation to the terms and conditions and user agreements that are ubiquitous to digital technologies, social media platforms and other websites.Practical implicationsAlthough changes are afoot as part of the General Data Protection Regulation (herein the GDPR) to simplify the terms and conditions of online platforms (European Union, 2016), it offers little practical guidance on how it should be implemented to children. The voices and opinions of children and young people are put forward as suggestions for how the “clear communication to data subjects” required by Article 12 of the GDPR in particular should be implemented, for example, recommendations about how terms and conditions can be made more accessible.Originality/valueChildren and young people are an often overlooked demographic of online users. This paper argues for the importance of this group being involved in any changes that may affect them, by putting forward recommendations from the children and young people themselves.
Viewpoint: the role of cancer resource center services on men's health
Authors: Rosenbaum Mark S. , Contreras Ramírez German 
Published: July 2019

Purpose
This paper aims to develop a conceptual framework that clarifies the social supportive role of cancer resource center services in the lives of men with cancer and its impact on their perceived quality of life.

Design/methodology/approach
Personal reflections.

Findings
The authors put forth a conceptual framework which shows that men with cancer may perceive the availability of four types of social support from others present in a cancer resource center. The perceived availability of social support is posited to enhance their perceptions of their quality of life.

Research limitations/implications
The study yields propositions that may be empirically tested by services and health researchers in future studies. In addition, the research findings may not extend to terminally ill male cancer patients.

Practical implications
Given the health benefits associated with social support, health-care professionals, social workers and cancer center directors should encourage their male cancer patients to participate in cancer resource programing and activities.

Social implications
Cancer resource centers offer male cancer patients opportunities to enhance their quality of life beyond the use of pharmaceutical drugs or professional medical treatment. The health benefits may lower costs associated with medical expenses.

Originality/value
This study contributes to an emerging paradigm in services marketing. It is one of the first papers to focus on the socially supportive role that cancer resource center services may assume in the lives of men with cancer and those surviving the disease.
Hybrid active contour model and deep belief network based approach for brain tumor segmentation and classification
Authors: Ratna Raju Ayalapogu , Pabboju Suresh , Rajeswara Rao Ramisetty 
Published: July 2019

Purpose
Brain tumor segmentation and classification is the interesting area for differentiating the tumorous and the non-tumorous cells in the brain and classifies the tumorous cells for identifying its level. The methods developed so far lack the automatic classification, consuming considerable time for the classification. In this work, a novel brain tumor classification approach, namely, harmony cuckoo search-based deep belief network (HCS-DBN) has been proposed. Here, the images present in the database are segmented based on the newly developed hybrid active contour (HAC) segmentation model, which is the integration of the Bayesian fuzzy clustering (BFC) and the active contour model. The proposed HCS-DBN algorithm is trained with the features obtained from the segmented images. Finally, the classifier provides the information about the tumor class in each slice available in the database. Experimentation of the proposed HAC and the HCS-DBN algorithm is done using the MRI image available in the BRATS database, and results are observed. The simulation results prove that the proposed HAC and the HCS-DBN algorithm have an overall better performance with the values of 0.945, 0.9695 and 0.99348 for accuracy, sensitivity and specificity, respectively.

Design/methodology/approach
The proposed HAC segmentation approach integrates the properties of the AC model and BFC. Initially, the brain image with different modalities is subjected to segmentation with the BFC and AC models. Then, the Laplacian correction is applied to fuse the segmented outputs from each model. Finally, the proposed HAC segmentation provides the error-free segments of the brain tumor regions prevailing in the MRI image. The next step is to extract the useful features, based on scattering transform, wavelet transform and local Gabor binary pattern, from the segmented brain image. Finally, the extracted features from each segment are provided to the DBN for the training, and the HCS algorithm chooses the optimal weights for DBN training.

Findings
The experimentation of the proposed HAC with the HCS-DBN algorithm is analyzed with the standard BRATS database, and its performance is evaluated based on metrics such as accuracy, sensitivity and specificity. The simulation results of the proposed HAC with the HCS-DBN algorithm are compared against existing works such as k-NN, NN, multi-SVM and multi-SVNN. The results achieved by the proposed HAC with the HCS-DBN algorithm are eventually higher than the existing works with the values of 0.945, 0.9695 and 0.99348 for accuracy, sensitivity and specificity, respectively.

Originality/value
This work presents the brain tumor segmentation and the classification scheme by introducing the HAC-based segmentation model. The proposed HAC model combines the BFC and the active contour model through a fusion process, using the Laplacian correction probability for segmenting the slices in the database.
Classification of drug‐induced hERG potassium‐channel block from electrocardiographic T‐wave features using artificial neural networks
Authors: Morettini Micaela , Peroni Chiara , Sbrollini Agnese , Marcantoni Ilaria , Burattini Laura 
Published: July 2019

AbstractBackgroundHuman ether‐à‐go‐go‐related gene (hERG) potassium‐channel block represents a harmful side effect of drug therapy that may cause torsade de pointes (TdP). Analysis of ventricular repolarization through electrocardiographic T‐wave features represents a noninvasive way to accurately evaluate the TdP risk in drug‐safety studies. This study proposes an artificial neural network (ANN) for noninvasive electrocardiography‐based classification of the hERG potassium‐channel block.MethodsThe data were taken from the “ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects” Physionet database; they consisted of median vector magnitude (VM) beats of 22 healthy subjects receiving a single 500 μg dose of dofetilide. Fourteen VM beats were considered for each subject, relative to time‐points ranging from 0.5 hr before to 14.0 hr after dofetilide administration. For each VM, changes in two indexes accounting for the early and the late phases of repolarization, ΔERD30% and ΔTS/A, respectively, were computed as difference between values at each postdose time‐point and the predose time‐point. Thus, the dataset contained 286 ΔERD30%‐ΔTS/A pairs, partitioned into training, validation, and test sets (114, 29, and 143 pairs, respectively) and used as inputs of a two‐layer feedforward ANN with two target classes: high block (HB) and low block (LB). Optimal ANN (OANN) was identified using the training and validation sets and tested on the test set.ResultsTest set area under the receiver operating characteristic was 0.91; sensitivity, specificity, accuracy, and precision were 0.93, 0.83, 0.92, and 0.96, respectively.ConclusionOANN represents a reliable tool for noninvasive assessment of the hERG potassium‐channel block.