bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detecting Myocardial Infarction by Electrocardiogram Machine Learning Models With Greater Accuracy; A Technical Advance Article
Authors: Sudaraka M.D.S. , Abeyagunawardena I. , Silva E. S. De , Abeyagunawardena S 
Published: January 2021

Abstract
BackgroundElectrocardiogram (ECG) is a key diagnostic test in cardiac investigation. Interpretation of ECG is based on the understanding of normal electrical patterns produced by the heart and alterations of those patterns in specific disease conditions. With machine learning techniques, it is possible to interpret ECGs with increased accuracy. However, there is a lacuna in machine learning models to detect myocardial infarction (MI) coupled with the affected territories of the heart. MethodsThe dataset was obtained from the University of California, Irvine, Machine Learning Repository. It was filtered to obtain observations categorized as Normal, Ischemic changes, Old Anterior MI and Old Inferior MI. The dataset was randomly split into a training set (70%) and a test set (30%). 73 out of the 270 ECG features were selected based on the changes observed following MI, after excluding predictors that had near zero variance across the observations. Three machine learning classification models (Bootstrap Aggregation Decision Trees, Random Forest, Multi-layer Perceptron) were trained using the training dataset, optimizing for the Kappa statistic and the parameter tuning was achieved with repeated 10-fold cross validation. Accuracy and Kappa of the samples were used to evaluate performance between the models. ResultsThe Random Forest model identified old anterior and old inferior MIs with 100% sensitivity and specificity and all 4 categorized observations with an overall accuracy of 0.9167 (95% CI 0.8424 - 0.9633). Both the Bootstrap Aggregation Decision Trees and the Multi-layer Perceptron models identified old anterior MIs with 100% sensitivity and specificity and their overall accuracies for all 4 observations were 0.8958 (95% CI 0.8168 - 0.9489) and 0.8542 (95% CI 0.7674 - 0.9179) respectively.Conclusion With a medically informed feature selection we were able to identify old anterior MI with 100% sensitivity and specificity by all three models in this study, and old inferior MI with 100% sensitivity and specificity by Random Forest Model. If the data set can be improved it is possible to utilize these machine learning models in hospital setting to identify cardiac emergencies by incorporating them into cardiac monitors, until trained personnel become available.
Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
Authors: Zhao Yifan , Cai Huiyu , Zhang Zuobai , Tang Jian , Li Yue 
Published: January 2021

Abstract
The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, integrative analysis of scRNA-seq data remains a challenge largely due to batch effects. We present single-cell Embedded Topic Model (scETM), an unsupervised deep generative model that recapitulates known cell types by inferring the latent cell topic mixtures via a variational autoencoder. scETM is scalable to over 10^6 cells and enables effective knowledge transfer across datasets. scETM also offers high interpretability and allows the incorporation of prior pathway knowledge into the gene embeddings. The scETM-inferred topics show enrichment in cell-type-specific and disease-related pathways.
Observation of laser-assisted electron scattering in superfluid helium
Authors: Treiber Leonhard , Thaler Bernhard , Heim Pascal , Stadlhofer Michael , Kitzler-Zeiler Markus , Koch Markus 
Published: January 2021

Abstract
Laser-assisted electron scattering (LAES), a light-matter interaction process that facilitates energy transfer between strong light fields and free electrons, has so far been observed only in gas phase. Here we report on the observation of LAES at condensed phase particle densities, for which we create nano-structured systems consisting of a single atom or molecule surrounded by a superfluid He shell of variable thickness (32-340 Å). We observe that free electrons, generated by femtosecond strong-field ionization of the core particle, can gain several tens of photon energies due to multiple LAES processes within the liquid He shell. Supported by 3D scattering simulations, these results provide the first insight into the interplay of LAES energy gain/loss and dissipative electron movement in a liquid. Our results reveal that LAES could significantly increase the temporal resolution of ultrafast electron microscopy, potentially to the attosecond regime.
Assessing and Improving Fitness to Drive in the Elderly People: a Scoping Review of Policies and Guidelines
Authors: Mohammaddokht Salar , Saadati Mohammad , Kashefimehr Babak , Azami-Aghdash Saber 
Published: January 2021

Abstract
Background: Several countries in the world have distinct policies and frameworks to assessment and promote fitness to drive in the elderly. Accordingly, this study has been conducted to analyze the processes, models, and policies to assessment fitness to drive and improving driving in the elderly in the world.Method: Expected data were collected using keywords older, old, elderly, aging, ageing, senior, polic*, process, programme, plan, guideline, framework, driving capacity, driving eligibility, safe drive, fitness to drive, renewal driving license, commercial driver, driving qualification, driving ability, driving evaluation, driving assessment and their Persian equivalents from various English-language databases included: PubMed, Web of Science, Scopus, Embase, and Persian-language databases Included: IranDoc, SID, and MagIran. In this study, the Arkesy and O’Malley frameworks were employed.Results: Eventually, 24 papers and reports were included in the study. Vision assessment was the main item to judge the fitness to drive in the elderly, followed by driving assessment, cognitive assessment, and motor assessment. The in-person, postal, and online renewal of license were the most common method of renewal. General practitioners were the principal performers to measure driving fitness. In most all reports and papers, there were policies on empowering the elderly driver, including providing safe driving tips, optional driving skills tests, holding retraining courses, and so on. The most significant supporting policies included introducing alternative transportation to preserve the independence of the elderly. This study explained that clinical assessment is normally performed in drivers older than 75 years old to diagnose disorders and treat and prevent them in distinct time periods.Conclusion: Most high-income countries have worthwhile experience in measuring and improving the fitness to drive in the elderly and enforce different laws according to environmental, social, and political conditions. Utilizing these experiences by considering economic and social differences can be useful and practical for middle and low-income countries.
Validation of the German Version of the Work and Social Adjustment Scale in a Sample of Depressed Patients
Authors: Heissel Andreas , Bollmann Julian , Kangas Maria , Abula Kahar , Rapp Michael , Sanchez Alba 
Published: January 2021

Abstract
Background: Depression is one of the key factors contributing to difficulties in one’s ability to work, and serves as one of the major reasons why employees apply for psychotherapy and receive insurance subsidization of treatments. Hence, an increasing and growing number of studies rely on workability assessment scales as their primary outcome measure. The Work and Social Assessment Scale (WSAS) has been documented as one of the most psychometrically reliable and valid tools to serve that purpose. Yet, the application of the WSAS in Germany has been limited due to the paucity of a valid questionnaire in the German language. The objective of the present study was to translate the WSAS into German and test its psychometric properties in a sample of adults with depression. Methods: 277 patients (M = 48.3 years, SD =11.1) with mild to moderately severe depression were recruited. A multistep translation from English into the German language was performed and the factorial validity, criterion validity, convergent validity, internal consistency, and floor and ceiling effects were examined. Results: The confirmatory factor analysis results confirmed the one-factor structure of the WSAS. Significant correlations with the WHODAS 2-0 questionnaire, a measure of functionality, demonstrated good convergent validity. Significant correlations with depression and quality of life demonstrated good criterion validity. The WSAS also demonstrated strong internal consistency (α = .89), and the absence of floor and ceiling effects indicated good sensitivity of the instrument. Conclusions: The results of the present study demonstrated that the German version of the WSAS has good psychometric properties comparable to other international versions of this scale. The findings recommend a global assessment of psychosocial functioning with the sum score of the WSAS, but also suggest the interpretation of the individual items to improve treatment and the concomitant research.Trial registration ISRCTN identifier: ISRCTN28972230. Date of registration June 26th 2018.
Combination With Glucocoriticoids and/or Immunosuppressants Brings Few Benefits in Patients With Primary Biliary Cholangitis
Authors: Wang Zilong , Jin Rui , Hao Mei , Xie Yandi , Wang Hao , Feng Bo 
Published: January 2021

Abstract
Objective To compare the efficacy of ursodeoxycholic acid (UDCA) monotherapy, and UDCA combined with glucocorticoids and/or immunosuppressants for patients with primary biliary cholangitis (PBC), and to search for relevant factors influencing the efficacy. Methods This retrospective study enrolled 266 patients who were initially diagnosed with PBC were grouped according to different treatment regimes. We analyzed and compared demographic characteristics, immune parameters, biochemistry profiles and other indicators collected at baseline, six months and one year of treatment. The prognosis was evaluated by Paris II standard and GLOBE score. T test, chi-square test and logistic regression were used for statistical analysis. Results According to Paris II standard and GLOBE score, there was no significant difference in one-year response rate and GLOBE score among the three treatment schemes (P > 0.05). GLOBE score > 0.3 indicated a decrease of the long-term survival rate, it was found that the long-term survival rate of the triple therapy group was significantly improved compared with the monotherapy group (p=0.005). Multivariate logistic regression analysis showed that PLT, ALP and ALB levels were risk factors for poor response. For the patients whose IgG levels were elevated but below twice upper limit of normal (ULN), the clinical benefit from combination therapy was not significant compared with monotherapy (p>0.05). Conclusion: Compared with monotherapy, the double therapy did not improve the one-year efficacy and long-term survival rate of PBC patients. However, triple therapy may improve the long-term survival rate of patients, although it does not significantly improve the one-year efficacy.
Using the Geometric Average Hazard Ratio in Sample Size Calculation for Time-to-event Data With Composite Endpoints
Authors: Martínez Jordi Cortés , Geskus Ronald B , Kim KyungMann , Melis Guadalupe Gómez 
Published: January 2021

Abstract
Background: Sample size calculation is a key point in the design of a randomized controlled trial. With time-to-event outcomes, it’s often based on the logrank test. We provide a sample size calculation method for a composite endpoint (CE) based on the geometric average hazard ratio (gAHR) in case the proportional hazards assumption can be assumed to hold for the components, but not for the CE. Methods: The required number of events, sample size and power formulae are based on the non-centrality parameter of the logrank test under the alternative hypothesis which is a function of the gAHR. We use the web platform, CompARE, for the sample size computations. A simulation study evaluates the empirical power of the logrank test for the CE based on the sample size in terms of the gAHR. We consider different values of the component hazard ratios, the probabilities of observing the events in the control group and the degrees of association between the components. We illustrate the sample size computations using two published randomized controlled trials. Their primary CEs are, respectively, progression-free survival (time to progression of disease or death) and the composite of bacteriologically confirmed treatment failure or Staphilococcus aureus related death by 12 weeks. Results: For a target power of 0.80, the simulation study provided mean (± SE) empirical powers equal to 0.799 (±0.004) and 0.798 (±0.004) in the exponential and non-exponential settings, respectively. The power was attained in more than 95% of the simulated scenarios and was always above 0.78, regardless of compliance with the proportional-hazard assumption.Conclusions: The geometric average hazard ratio as an effect measure for a composite endpoint has a meaningful interpretation in the case of non-proportional hazards. Furthermore it is the natural effect measure when using the logrank test to compare the hazard rates of two groups and should be used instead of the standard hazard ratio.
A Bioelectric Model of Carcinogenesis, Including Propagation of Cell Membrane Depolarization and Reversal Therapies
Authors: Carvalho Joao 
Published: January 2021

Abstract
As the main theory of carcinogenesis, the Somatic Mutation Theory, increasingly presents difficulties to explain some experimental observations, different theories are being proposed. A major alternative approach is the Tissue Organization Field Theory, which explains cancer origin as a tissue regulation disease instead of having a mainly cellular origin. This work fits in the latter hypothesis, proposing the bioelectric field, in particular the cell membrane polarization state, and ionic exchange through ion channels and gap junctions, as an important mechanism of cell communication and tissue organization and regulation. Taking into account recent experimental results and proposed bioelectric models, a computational model of cancer initiation was developed, including the propagation of a cell depolarization wave in the tissue under consideration. Cell depolarization leads to a change in its state, with the activation and deactivation of several regulation pathways, increasing cell proliferation and motility, changing its epigenetic state to a more stem cell-like behavior without the requirement of genomic mutation. The intercellular communication via gap junctions leads, in certain circum stances, to a bioelectric state propagation to neighbor cells, in a chain-like reaction, till an electric discontinuity is reached. However, this is a reversible process, and it was shown experimentally that, by implementing a therapy targeted on cell ion exchange channels, it is possible to reverse the state and repolarize cells. This mechanism can be an important alternative way in cancer prevention, diagnosis and therapy, and new experiments are proposed to test the presented hypothesis.
Algebraic Graph-assisted Bidirectional Transformers for Molecular Prediction
Authors: Chen Dong , Gao Kaifu , Nguyen Duc , Chen Xin , Jiang Yi , Wei Guowei , Pan Feng 
Published: January 2021

Abstract
The ability of quantitative molecular prediction is of great significance to drug discovery, human health, and environmental protection. Despite considerable efforts, quantitative prediction of various molecular properties remains a challenge. Although some machine learning models, such as bidirectional encoder from transformer, can incorporate massive unlabeled molecular data into molecular representations via a self-supervised learning strategy, it neglects three-dimensional (3D) stereochemical information. Algebraic graph, specifically, element-specific multiscale weighted colored algebraic graph, embeds complementary 3D molecular information into graph invariants. We propose an algebraic graph-assisted bidirectional transformer (AGBT) model by fusing representations generated by algebraic graph and bidirectional transformer, as well as a variety of machine learning algorithms, including decision trees, multitask learning, and deep neural networks. We validate the proposed AGBT model on five benchmark molecular datasets, involving quantitative toxicity and partition coefficient. Extensive numerical experiments suggest that AGBT outperforms all other existing methods for all these molecular predictions.
Diffusion Model-based Understanding of Unconscious Affective Priming in Continuous Flash Suppression
Authors: Kim Minchul , Kim Jeeyeon , Kim Jaejoong , Jeong Bumseok 
Published: January 2021

Abstract
Affective states influence our decisions even when processed unconsciously. Continuous flash suppression (CFS) is a new variant of binocular rivalry that can be used to render the prime invisible and thus unconscious. Nonetheless, it is unclear how prior information from emotional faces provided by CFS influences subsequent decision making. Here, we employed the CFS priming task to examine the effect of nonconscious information on the evaluation of target words as either positive or negative. The hierarchical diffusion model was used to investigate the underlying mechanisms. Two experiments were performed to investigate the effects of facial identity and facial expression. As a result, a significant affective priming effect on response time was observed only for angry faces but not happy and neutral faces. The results of diffusion model analyses revealed that both the drift rate and nondecisional process are accountable for the ‘positive bias’ - the processing advantage of positive over negative stimuli. Priming effects of facial identity were mapped onto the drift rate and eliminated ‘positive bias’. Meanwhile, positive emotional faces increased the nondecision time with negative target words. The model-based analysis implies that both facial identity and emotion are processed under CFS.
Evaluation of Temporomandibular Disorders Among Dental Students of Saudi Arabia Using Diagnostic Criteria/temporomandibular Disorders (DC/TMD) and Its Association With Biographic, Academic, and Psychosocial Parameters – A Cross-sectional Study
Authors: SRIVAST KUMAR CHANDAN , SHRIVASTAVA DEEPTI , Khan Zafar Ali , Nagarajappa Anil Kumar , Mousa Mohammed Assayed , Hamza May Othman , Al-Johani Khalid , Alam Mohammad Khursheed 
Published: January 2021

Abstract
Background: Temporomandibular disorders (TMD) are a board category of conditions arising from the various components of the temporomandibular joint (TMJ) complex. Bio-psychosocial model is the most accepted theory describing the etiopathogenesis of TMD. Dental students are vulnerable to psychological disorders including anxiety, depression and stress. Hence, the aim of the current study was to evaluate the TMD among dental students of various academic levels and explore the association of TMD with biographic, academic, and psychosocial parameters. Methods: A total of 246 students of a dental school in Saudi Arabia were chosen for the study. After getting consent, all students were examined as per the diagnostic criteria/Temporomandibular disorders (DC/TMD) including components from axis-I and axis-II. Results: The overall cross-sectional prevalence of TMD was found to be 36.99%. Pain arising from the jaw, temple, and peri-auricular area was the most commonly reported symptom and elicited sign during examination. Among the pain-related TMD, myalgia was the commonest diagnosed condition, whereas disc displacement with reduction was found prevalent in intra-articular disorder category. Female (OR=1.94; P=0.004), married (OR=1.74; P=0.04), and students in clinical levels (OR=1.65; P=0.03) were shown to have significantly higher risk to develop TMD. Among the psychosocial parameters, parafunctional habits (OR=2.10; P<0.001) and anxiety (OR=1.55; P=0.04) are shown to increase risk of developing TMD. Students with any TMD reported to have significantly higher pain intensity (OR=1.68; P=0.01) and jaw functional limitations (OR=1.45; P=0.008). Conclusion: Dental students especially in the clinical levels were shown to poses higher risk of developing TMD, hence strategies such as academic counselling and objective evaluation via rubrics should be planned to modify the administration of the curriculum, training methods and evaluation process.
Detection of Unknown Ototoxic Adverse Drug Reactions: An Electronic Healthcare Record-Based Longitudinal Nationwide Cohort Analysis
Authors: Lee Suehyun , Cha Jaehun , Kim Jong-Yeup , Son Gil Myeong , Kim Dong-Kyu 
Published: January 2021

Abstract
Ototoxic medications can lead to significant morbidity. Thus, pre-marketing clinical trials have assessed new drugs that have ototoxic potential. Nevertheless, several ototoxic side effects of drugs may remain undetected. Hence, we sought to retrospectively investigate the potential risk of ototoxic adverse drug reactions among commonly used drugs via a longitudinal cohort study. An electronic health records-based data analysis with a propensity-matched comparator group was carried out. This study was conducted using the MetaNurse algorithm for standard nursing statements on electronic healthcare records and the National Sample Cohort obtained from the South Korea National Health Insurance Service. Five target drugs capable of causing ototoxic adverse drug reactions were identified using MetaNurse; two drugs were excluded after database-based analysis because of the absence of bilateral hearing loss events in patients. Survival analysis, log-rank test, and Cox proportional hazards regression models were used to calculate the incidence, survival rate, and hazard ratio of bilateral hearing loss among patients who were prescribed candidate ototoxic drugs. The adjusted hazard ratio of bilateral hearing loss was 1.31 (1.03–1.68), 2.20 (1.05–4.60), and 2.26 (1.18–4.33) in cimetidine, hydroxyzine, and sucralfate users, respectively. Our results indicated that hydroxyzine and sucralfate may cause ototoxic adverse drug reactions in patients. Thus, clinicians should consider the risk of ototoxicity when prescribing these drugs.