Miracle-dz/UniFAR-FTUs huggingface dataset:
Executive dysfunction in an Egyptian sample of adult participants with epilepsy: a case–control study

© 2019 Egyptian Journal of Psychiatry | Published by W Objective The present study aimed to detect the executive function deficits that may affect patients with idiopathic epilepsy and the factors that influence such affection. Study design A case–control study was conducted. Materials and methods A total of 40 adult patients aged from 20 to 50 years, with idiopathic epilepsy recruited from the outpatient clinic of South Valley and Assiut University hospital and a similar number of age-matched and sex-matched controls were included. Participants completed Wechsler Intelligence Scale and neuropsychological tests including Wisconsin card sorting test, trail making test (trails A and B), Conners’ continuous performance test, and digit span tests. Results Relative to the control group, patients poorly performed on most of executive functions, with the longer duration of illness and the higher frequency of seizures being the most evident factors that showed a positive correlation with the executive dysfunction. However, age at onset, type of seizures, and family history of epilepsy had no significant correlation on neuropsychological test performance. Conclusion One of the main domains of evaluation of the patients with chronic epilepsy should be the cognitive domain. A large number of studies shed light on such hypothesis. Executive dysfunction in patients with epilepsy may share negatively in their quality of life, so it should be a target of diagnosis and therapy.
Cognitive and psychological evaluation of a sample of egyptian patients with behcet’s disease without neurological manifestations: a case–control study

Objective Behcet’s disease (BD) is a chronic autoimmune multisystemic vasculitis of unknown cause that affects one case per 170 000 persons in the USA. There are few studies in the literature that targeted BD patient group for cognitive and psychological evaluation and scarce studies that evaluated the patients with BD without neurological manifestations. In this study, we aimed to assess those who have BD without neurological manifestations for cognitive and psychological impairments. Patients and methods A case–control study was conducted. A total of 45 consecutive adult patients, aged 18–60 years, diagnosed with BD without neurological manifestations were evaluated for cognitive and psychological impairments and compared with 30 age-matched and sex-matched healthy control participants. Detailed clinical evaluation was done including disease activity measurement using Behçet’s Disease Current Activity Form. Participants completed a group of neuropsychological assessment including Memory Assessment Scale, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Short Form 36 Quality-Of-Life questionnaire, and Global Assessment of Functioning scale. Results Compared with the control group, patients with BD scored lower in Memory Assessment Scale (total and subscores), Short Form 36 Quality-Of-Life questionnaire, and Global Assessment of Functioning scores. BD group showed significantly higher prevalence of depression and anxiety. Conclusion BD without neurological manifestations was associated with cognitive and psychological impairment, and this was not restricted to cases with neuro-BD.
Effective Diagnosis of Alzheimer’s Disease via Multimodal Fusion Analysis Framework

Alzheimer’s disease (AD) is a complex neurodegenerative disease involving a variety of pathogenic factors, and the etiology detection of this disease has been a major concern of researchers. Neuroimaging is a basic and important means to explore the problem. It is the main current scientific research direction for combining neuroimaging with other modal data to dig deep into the potential information of AD through the complementarities among multiple data points. Machine learning methods possess great potentiality and have reached some achievements in this research area. A few studies have proposed some solutions to the effects of multimodal data fusion, however, the overall analytical framework for data fusion and fusion result analysis has thus far been ignored. In this paper, we first put forward a novel multimodal data fusion method, and further present a new machine learning framework of data fusion, classification, feature selection, and disease-causing factor extraction. The real dataset of 37 AD patients and 35 normal controls (NC) with functional magnetic resonance imaging (fMRI) and genetic data was used to verify the effectiveness of the framework, which was more accurate in classification and optimal feature extraction than other methods. Furthermore, we revealed disease-causing brain regions and genes, such as the olfactory cortex, insula, posterior cingulate gyrus, lingual gyrus, CNTNAP2, LRP1B, FRMD4A, and DAB1. The results show that the machine learning framework could effectively perform multimodal data fusion analysis, providing new insights and perspectives for the diagnosis of Alzheimer’s disease.
Badminton Players’ Moral Intentions: A Factorial Survey Study Into Personal and Contextual Determinants

Improving and maintaining high ethical standards among athletes is a major challenge in sports, which requires sufficient knowledge on athletes’ moral intentions. This study advances our knowledge on athletes’ moral intentions by examining the personal and contextual determinants (factors) that influence moral intentions of badminton players. In a factorial survey study, a total of 171 participants were asked to respond to scenarios describing moral dilemmas in the context of badminton. This approach allows combining advantages from both classical experiments and survey methods, enabling the determination of the underlying principles of the judgments and intentions of respondents. Multilevel analysis indicated that intention to engage in the described behavior was impacted by both the act and the gender of the subject. This study complements previous research on athletes’ moral intentions by the advanced method of factorial survey, while supporting the development of more specific approaches in the promotion of ethical behavior in sports.
Transcriptome Profiling Reveals Differential Effect of Interleukin-17A Upon Influenza Virus Infection in Human Cells

Influenza A virus (IAV) has developed elegant strategies to utilize cellular proteins and pathways to promote replication and evade the host antiviral response. Identification of these sabotaged host factors could increase the number of potential antiviral drug targets. Here, IAV A/PR/8/34 (PR8)- and A/California/04/2009-infected A549 and 293T cells displayed differential virus replication. To determine the host cellular responses of A549 and 293T cells to IAV infection, RNA-seq was used to identify differentially expressed genes. Our data revealed that IAV-infected A549 cells activated stronger virus-sensing signals and highly expressed cytokines, which play significant roles in initiating the innate immune and inflammatory responses. In addition, IAV-infected 293T cells displayed weak immune signaling and cytokine production. Remarkably, IL-17A and associated genes were highly enriched in IAV-infected 293T cells. Furthermore, IL-17A can partially facilitate A549 cell infection by the PR8 strain and PR8-infected IL-17A knock-out mice consistently exhibited decreased weight loss and reduced lung immunopathology, as compared to controls. This work uncovered the differential responses of cells infected with two H1N1 IAV strains and the potential roles of IL-17A in modulating virus infection.
Understanding the Business Value Creation Process for Business Intelligence Tools in the UAE

Background: In today’s dynamically changing business environment, organizations are constantly striving to improve their organizational performance, and the use of business intelligence (BI) aids in this process. This is a key reason why BI has captured the attention of many academicians and practitioners. Most of the research on BI highlights its importance and the ways in which it facilitates decision-making; however, there is limited research on how the use of BI tools and applications benefits the organization by enabling it to convert the millions of dollars spent on BI investment into business value. This study validates the “business value of BI” framework by evaluating the business value creation process for BI tools in the UAE. Method: The data for this empirical study were collected via interviews with 15 middle managers from various industries in the UAE, with a focus on BI tools and the use of BI in their organizations. Results: The results show that a business value creation process for BI exists and that it is divided into three subprocesses: the BI conversion process, BI use process, and BI competitive process. Conclusions: The use of BI has become necessary for organizations to compete effectually. The results of this study identify the various BI tools that organizations in the UAE use. Furthermore, the results highlight the business value creation process of BI tools and how the effective use BI offers an information advantage that facilitates decision-making and eventually promotes financial and non-financial benefits for the organization.
Towards a Flexible Experience of Data Provenance Summarization

In complex data analysis or applications, it is often necessary to collect, aggregate and manipulate large amount of data from multiple sources. Data provenance and their approximated summarizations have been proven to be helpful for recording and understanding user behaviors in these aspects. The growing urgency for providing timely feedbacks and the increasing need to explore more possible summarization options create a much bigger new challenge: exploring more extensive state-space under shorter response time constraints and fulfilling more complex requirements at the same time. In this work, we propose that this can be achieved by relaxing the greedy strategy adopted by existing approaches and by introducing a more flexible optimization strategy based on incremental and adaptive sampling. Our evaluations show that, compared to existing approaches, summarization processes guided by our strategy may produce more flexible and satisfying service data provenance summarization results at smaller temporal and spatial resource costs.
DESIGN AND EVALUATION OF OPEN SPHERICAL MICROPHONE ARRAYS

Beamforming with a spherical microphone array has become an attractive tool for sound source localization in cabin environments. To provide a reliable localization solution with high performance , the first step is to optimize the array design. In this paper, the spatial resolution and dynamic range of an open spherical array with various microphone arrangements are evaluated, which are used as metrics for optimal array design. Several popular approaches for evenly distributing points on a sphere are investigated such that the array response is as isotropic as possible. In addition to the conventional beamforming, a state-of-the-art algorithm called functional beam-forming is also implemented. The objective is twofold: first is to improve spatial resolution and dynamic range significantly; and second is to verify that array configurations have a consistent effect on localization performance, regardless of beamforming algorithms.
ACAT1 and Metabolism-Related Pathways Are Essential for the Progression of Clear Cell Renal Cell Carcinoma (ccRCC), as Determined by Co-expression Network Analysis

Kidney cancer ranks as one of the top 10 causes of cancer death; this cancer is difficult to detect, difficult to treat, and poorly understood. The most common subtype of kidney cancer is clear cell renal cell carcinoma (ccRCC) and its progression is influenced by complex gene interactions. Few clinical studies have investigated the molecular markers associated with the progression of ccRCC. In this study, we collected microarray profiles of 72 ccRCCs and matched normal samples to identify differentially expressed genes (DEGs). Then a weighted gene co-expression network analysis (WGCNA) was conducted to identify co-expressed gene modules. By relating all co-expressed modules to clinical features, we found that the brown module and Fuhrman grade had the highest correlation (r = −0.8, p = 1e-09). Thus, the brown module was regarded as a clinically significant module and subsequently analyzed. Functional annotation showed that the brown module focused on metabolism-related biological processes and pathways, such as fatty acid oxidation and amino acid metabolism. We then performed a protein-protein interaction (PPI) network to identify the hub nodes in the brown module. It is worth noting that only one candidate, acetyl-CoA acetyltransferase (ACAT1), was considered to be the final target most relevant to the Fuhrman grade of ccRCC, by applying the intersection of hub genes in the co-expressed network and the PPI network. ACAT1 was subsequently validated using another two external microarray datasets and the TCGA dataset. Intriguingly, validation results indicated that ACAT1 was negatively correlated with four grades of ccRCC, which was also consistent with our results from qRT-PCR analysis and immunohistochemistry staining of clinical samples. Overexpression of ACAT1 inhibited the proliferation and migration of human ccRCC cells in vitro. In addition, the Kaplan-Meier survival curve showed that patients with a lower expression of ACAT1 showed a significantly lower overall survival rate and disease-free survival rate, indicating that ACAT1 could act as a prognostic and recurrence/progression biomarker of ccRCC. In summary, we found and confirmed that ACAT1 might help to identify the progression of ccRCC, which might have important clinical implications for enhancing risk stratification, therapeutic decision, and prognosis prediction in ccRCC patients.
Oxygen Consumption Characteristics in 3D Constructs Depend on Cell Density

Oxygen is not only crucial for cell survival but also a determinant for cell fate and function. However, the supply of oxygen and other nutrients as well as the removal of toxic waste products often limit cell viability in 3-dimensional (3D) engineered tissues. The aim of this study was to determine the oxygen consumption characteristics of 3D constructs as a function of their cell density. The oxygen concentration was measured at the base of hepatocyte laden constructs and a tightly controlled experimental and analytical framework was used to reduce the system geometry to a single coordinate and enable the precise identification of initial and boundary conditions. Then dynamic process modeling was used to fit the measured oxygen vs. time profiles to a reaction and diffusion model. We show that oxygen consumption rates are well-described by Michaelis-Menten kinetics. However, the reaction parameters are not literature constants but depend on the cell density. Moreover, the average cellular oxygen consumption rate (or OCR) also varies with density. We discuss why the OCR of cells is often misinterpreted and erroneously reported, particularly in the case of 3D tissues and scaffolds.
Determinants of Cloud Computing Adoption: A Comparative Study

Background: This study investigates the determinants that influence the user's behavioral intention to use cloud computing in adopter and non-adopter firms. The research model is based on the theory of the Valence Framework of Behavioral Beliefs and Technology Acceptance Model (TAM). The present study examined the factors of perceived ease of use, perceived usefulness, perceived ubiquity, perceived benefits, perceived costs and perceived risks in determining behavioral intention to use cloud computing for the adopter and non-adopter firms. Method: Data were collected using a questionnaire-based survey method. The valid responses received were 458. The sample size of adopters and non-adopter of cloud computing were 239 and 219, respectively. Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM) was used for data analysis. Data analysis was done separately for both samples of the adopter and non-adopter firms The results showed that, for adopters firms, perceived usefulness, perceived ease of use, ubiquity, perceived benefits, and perceived risks were found to have a significant and direct influence on behavioral intention to use cloud computing. For non-adopters, perceived usefulness, perceived ubiquity, perceived benefits, perceived costs, and perceived risks were found to have a significant and direct influence on behavioral intention to use cloud computing. A comparison testing was also performed by examining the difference in the strength of path coefficients between adopters and non-adopters firms. Results: The findings showed that the impact of favorable factors of perceived ubiquity and perceived benefits were found relatively more significant in the case of adopter firms than negative factors. Likewise, the impact of negative factors of perceived risks and perceived costs were found relatively more significant in the case of non-adopter firms. Conclusions : The major contribution of this study is that it contributes to the understanding of progressive changes in the impact of behavioral beliefs and cognitive factors on behavioral intention to use cloud computing in adopter and non-adopter firms. This study also provides managers' practical understandings for cloud computing adoption during each phase of the adoption process.
Circulating Tumor Biomarkers in Meningiomas Reveal a Signature of Equilibrium Between Tumor Growth and Immune Modulation

Meningiomas are primary central nervous system (CNS) tumors that originate from the arachnoid cells of the meninges. Recurrence occurs in higher grade meningiomas and a small subset of Grade I meningiomas with benign histology. Currently, there are no established circulating tumor markers which can be used for diagnostic and prognostic purposes in a non-invasive way for meningiomas. Here, we aimed to identify potential biomarkers of meningioma in patient sera. For this purpose, we collected preoperative (n = 30) serum samples from the meningioma patients classified as Grade I (n = 23), Grade II (n = 4), or Grade III (n = 3). We used a high-throughput, multiplex immunoassay cancer panel comprising of 92 cancer-related protein biomarkers to explore the serum protein profiles of meningioma patients. We detected 14 differentially expressed proteins in the sera of the Grade I meningioma patients in comparison to the age- and gender-matched control subjects (n = 12). Compared to the control group, Grade I meningioma patients showed increased serum levels of amphiregulin (AREG), CCL24, CD69, prolactin, EGF, HB-EGF, caspase-3, and decreased levels of VEGFD, TGF-α, E-Selectin, BAFF, IL-12, CCL9, and GH. For validation studies, we utilized an independent set of meningioma tumor tissue samples (Grade I, n = 20; Grade II, n = 10; Grade III, n = 6), and found that the expressions of amphiregulin and Caspase3 are significantly increased in all grades of meningiomas either at the transcriptional or protein level, respectively. In contrast, the gene expression of VEGF-D was significantly lower in Grade I meningioma tissue samples. Taken together, our study identifies a meningioma-specific protein signature in blood circulation of meningioma patients and highlights the importance of equilibrium between tumor-promoting factors and anti-tumor immunity.
Genetic Features of mcr-1 Mediated Colistin Resistance in CMY-2-Producing Escherichia coli From Romanian Poultry

Colistin is a last resort antibiotic used for the treatment of human infections associated with carbapenemase-producing Enterobacteriales. Here, we evaluated the occurrence of mcr-1 and -2 plasmid-mediated colistin resistance in colistin and/or carbapenem resistant human clinical Enterobacteriales and other gram-negative bacteria (n = 543) as well as third generation cephalosporin-resistant (3GCR) Escherichia coli isolates from poultry abattoir workers (n = 15) and poultry fecal samples (n = 92) collected from two geographically separate abattoirs in Romania. which revealed that mcr-1 was present within four sequence types (STs): ST744 (n = 7), ST57 (n = 7), ST156 (n = 2), and ST10 (n = 1). Within STs, serotypes were conserved and, notably, all except one of the mcr-1-positive isolates were found to exhibit fluoroquinolone-resistance (FQR) associated SNPs in both gyrA and parC. While there were variations in genotypes, all isolates belonging to ST744, ST57, and ST156 were rich in resistance determinants, carrying aminoglycoside-modifying enzymes genes, sulfonamide resistance gene blaTEM–1 as well as blaCMY–2 AmpC β-lactamase resistance genes. They also exhibited high similarity in carriage of virulence genes; ST10, however, only carried the mcr-1 gene. Whole genome sequencing (WGS) analysis also revealed that although the mcr-1 gene was identified in a diverse population of E. coli, two STs (ST57 and ST744) predominated and interestingly, were found in isolates across both abattoirs providing evidence for clonal transmission. Also, two main genomic contexts of mcr-1 isolates were revealed with all ST57 isolates harboring the mcr-1 gene between two copies of ISApl1 (or the Tn6330 transposon) whilst a common mcr-1 containing scaffold, highly similar to IncX type mcr-1-bearing plasmids (pWI2-mcr, Accession number: LT838201), was present among mcr-1 isolates of varying phylogenetic backgrounds (ST10, ST744 and ST156). The high prevalence of the mcr-1 gene in poultry E. coli isolates with co-resistance to cephalosporins and quinolones, in a country where antimicrobial use in food production species is poorly regulated, is concerning and the findings from this study should lead to better surveillance of antimicrobial resistance (AMR) in food-production animals in Romania.
Characterizing Local Dynamic Stability of Lumbar Spine Sub-regions During Repetitive Trunk Flexion-Extension Movements

Using a technique of tracking intersegmental spine kinematics via skin surface markers, this study aimed to estimate local dynamic spine stability across smaller sub-regions (or segments) of the lumbar spine while also considering the impact of an external pelvic constraint during repetitive movements. Sixteen participants (10 males) performed two trials [Free Motion (FM), Pelvis Constrained (PC)] each consisting of 65 repetitive trunk flexion-extension movements to assess dynamic spine stability using maximum Lyapunov exponents (LyE). First, results indicated that LyE obtained from analysis of 30 repetitive flexion-extension movements did not differ from those obtained from analysis of greater numbers of repetitive movements, which aligns with results from a previous study for the whole lumbar spine. Next, for both males and females, and FM and PC trials, the most caudal region of the lumbar spine behaved the most dynamically stable, while upper lumbar regions behaved the most dynamically unstable. Finally, females demonstrated greater lumbar and intersegmental stability (lower LyE) during PC trials compared to FM, while males demonstrated slightly decreased lumbar and intersegmental stability (higher LyE) during PC trials compared to FM; this resulted in PC trials, but not FM trials, being different between sexes. Altogether, these data show that dynamic stability of lumbar spine sub-regions may be related to the proximity of the motion segment to rigid skeletal structures, and that consideration is needed when deciding whether to constrain the pelvis during analyses of dynamic spine stability.