Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondrial DNA has strong selective effects across the nuclear genome

Oxidative phosphorylation requires gene products encoded in both the nuclear and mitochondrial genomes, and is the primary source of cellular energy in eukaryotes. As a result, functional integration between the genomes is essential for efficient ATP generation in these organisms. Although within populations this integration is presumably maintained by coevolution, both the importance of coevolution in speciation and mitochondrial disease, and the strength of selection for maintenance of coevolved genotypes are widely questioned. In this study, we crossed populations of the intertidal copepod, Tigriopus californicus, to disrupt putatively coevolved mitonuclear genotypes in reciprocal F2 hybrids. We utilized inter-individual variation in developmental rate, a proxy for fitness, among these hybrids to assess the strength of selection imposed on the nuclear genome by alternate mitochondrial genotypes. There was substantial variation in developmental rate among hybrid individuals, and in vitro ATP synthesis rates of mitochondria isolated from high fitness hybrids were approximately twice those of mitochondria isolated from low fitness individuals. Furthermore, we used Pool-seq to reveal large deviations in nuclear allele frequencies in hybrids, which favored maternal alleles in only high fitness individuals of each reciprocal cross. Therefore, our most fit hybrids had partial recovery of coevolved genotypes, indicating that mitonuclear effects underlie individual-level variation in developmental rate and that inter-genomic compatibility is critical for high fitness. These results demonstrate that mitonuclear interactions have profound impacts on both physiological performance and the evolutionary trajectory of the nuclear genome.
Identification of key genes and pathways in Ewing’s sarcoma patients associated with metastasis and poor prognosis

Background: Ewing sarcoma (ES) is the second commonest primary malignant bone neoplasm. Metastatic status at diagnosis strongly predicted poor prognosis of Ewing sarcoma patients. Yet little was known about the underlying mechanism of ES metastasis. Purpose:This study intended to identify the relationship between key genes/pathways and metastasis/poor prognosis in Ewing's sarcoma patients by using bioinformatic method. Methods: In this study, multi-center sequencing data were obtained from the GEO database, including gene and miRNA expression profile and prognosis information of ES patients. Differentially expressed genes (DEGs) were identified between primary and metastasis ES samples by the GEO2R online tool. Gene ontology (Go) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses of DEGs were performed. And PPI network analyses were conducted. The ES patient’s prognostic information was employed for survival analysis, and the potential relationship between miRNAs and key genes was analyzed. Results: The results showed that a total of 298 and 428 DEGs were screened out in metastasis samples based on GSE17618 and GSE12102 dataset compared to primary samples respectively. The most significantly enriched KEGG pathway was the mismatch repair (MMR) pathway. MSH2, MSH6, RPA2, and RFC2 that belong to the MMR pathway were identified as key genes. Moreover, the expression of key genes was increased in metastasis samples compared with primary ones and was associated with poor event-free and overall survival of ES patients. The negative correlation of the expression level of the key genes with patients prognosis also supported by TCGA sarcoma database. Furthermore, knockdown of EWSR/FLI1 fusion in ES cell line A673 down-regulates the expression of the 4 key genes was revealed by GDS4962. Conclusion: In conclusion, the present study indicated that the key genes promote our understanding of the molecular mechanisms underlying the development of ES metastasis, and might be used as molecular targets and diagnostic biomarkers for the treatment of ES.
The Transfer of Human Trust in Robot Capabilities across Tasks

Trust is crucial in shaping human interactions with one another and with robots. This work investigates how human trust in robot capabilities transfers across tasks. We present a human-subjects study of two distinct task domains: a Fetch robot performing household tasks and a virtual reality simulation of an autonomous vehicle performing driving and parking maneuvers. Our findings lead to a functional view of trust and two novel predictive models---a recurrent neural network architecture and a Bayesian Gaussian process---that capture trust evolution and transfer via latent task representations. Experiments show that the two proposed models outperform existing approaches when predicting trust across unseen tasks and participants. These results indicate that (i) a task-dependent functional trust model captures human trust in robot capabilities more accurately, and (ii) trust transfer across tasks can be inferred to a good degree. The latter enables trust-based robot decision-making for fluent human-robot interaction. In particular, our models can be used to derive robot policies that mitigate under-trust or over-trust by human teammates in collaborative multi-task settings.
Detection of virulence genes of enterotoxigenic Staphylococcus aureus isolated from chicken meat cuts by using PCR

The present study was performed on 120 random samples of fresh chicken meat cuts of Drumstick, thigh and breast (40 of each) which were purchased from different supermarkets and retail chicken butchers at Kaliobia Governorate, for detection of virulence genes responsible for Staphylococcus. aureus enterotoxins production by using PCR.A total of 33 examined samples were positive for S.aureus counts represented as 13(32.5%) from drumstick samples; 11(27.5%) from thigh samples and 9(22.5%) from breast samples. The results revealed that 8 strains out of 10 random examined strains by SETRPLA test were enterotoxigenic and classified according to type of toxin into (3A;1C,2D and 2A&C). Moreover, PCR results cleared that; sea gene was detected in 4 studied strains; seb gene in one strain and sec; sed and see genes were detected in 3 strains out of 10 studied strains.
Characterizing Bone Mineral Density Using Lumbar Spine Computed Tomography Attenuation in Patients With Distal Radius Fractures

Introduction: This study examines how many patients with distal radius fracture (DRF) eligible for bone health evaluation could potentially be screened using bone mineral density (BMD) estimation by L1 vertebra computed tomography (CT) attenuation obtained for other purposes. Materials and Methods: For all adult patients with DRF who presented over a 5-year period, we recorded the age, sex, dual-energy X-ray absorptiometry (DXA) results up to 3 years prior to injury or 1 year post-injury, and L1 CT attenuation on any CT including L1 that had been performed within 6 months of their fracture. 1 We compared the availability of L1 CT attenuation measurement to the rate of DXA scan use. We calculated the percentage of patients with osteoporosis and compared attenuation results to DXA results in those patients where both tests were available. Results: Of 1853 patients with DRF, an L1 CT had been obtained in 195 patients. Of the 685 patients who met criteria for osteoporosis screening, 253 (37%) patients had undergone only DXA screening, 68 (10%) patients had an L1 CT only, and 18 (2%) patients had both tests. Of the 86 patients who met criteria for osteoporosis screening and had an adequate CT, 67 (78%) demonstrated L1 attenuation <135 HU, and 79 (92%) had CT attenuation <160 HU. Discussion: Our study found that 10% of patients with a distal radius fracture who met the criteria for osteoporosis screening had a CT scan that could be used to estimate bone density and that the majority of those patients met criteria for osteoporosis based on CT attenuation. Conclusions: Utilization of opportunistic BMD screening with L1 CT attenuation offers the potential to increase osteoporosis screening from 40% to 50% of eligible patients and make the diagnosis of osteoporosis in an additional 8% of patients with DRF at no additional cost.
Enhance the Power of Sentiment Analysis

: Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.
Gang Wang Research Statement 1. Security in Social Computing Systems

The explosive growth of user data on the Internet has introduced significant security threats. In recent years, large data breaches and malicious content distribution (spam, malware) become prevalent. With the rapid adoption of mobile and wearable devices, user data now includes a wide range of personal mobile and physical data. It ranges from GPS location traces, to biometrics data, to user interaction data with vehicles and other physical infrastructures.
Lung Recruitability in Severe Acute Respiratory Distress Syndrome Requiring Extracorporeal Membrane Oxygenation.

OBJECTIVES Quantification of potential for lung recruitment may guide the ventilatory strategy in acute respiratory distress syndrome. However, there are no quantitative data on recruitability in patients with severe acute respiratory distress syndrome who require extracorporeal membrane oxygenation. We sought to quantify potential for lung recruitment and its relationship with outcomes in this cohort of patients. DESIGN A single-center, retrospective, observational cohort study. SETTING Tertiary referral severe respiratory failure center in a university hospital in the United Kingdom. PATIENTS Forty-seven adults with severe acute respiratory distress syndrome requiring extracorporeal membrane oxygenation. INTERVENTION None. MEASUREMENTS AND MAIN RESULTS In patients with severe acute respiratory distress syndrome-mainly of pulmonary origin (86%)-the potential for lung recruitment and the weight of nonaerated, poorly aerated, normally aerated, and hyperaerated lung tissue were assessed at low (5 cmH2O) and high (45 cmH2O) airway pressures. Patients were categorized as high or low potential for lung recruitment based on the median potential for lung recruitment value of the study population. The median potential for lung recruitment was 24.3% (interquartile range = 11.4-37%) ranging from -2% to 76.3% of the total lung weight. Patients with potential for lung recruitment above the median had significantly shorter extracorporeal membrane oxygenation duration (8 vs 13 d; p = 0.013) and shorter ICU stay (15 vs 22 d; p = 0.028), but mortality was not statistically different (24% vs 46%; p = 0.159). CONCLUSIONS We observed significant variability in potential for lung recruitment in patients with severe acute respiratory distress syndrome requiring extracorporeal membrane oxygenation. Patients with high potential for lung recruitment had a shorter ICU stay and shorter extracorporeal membrane oxygenation duration.
Talent Management, Employee Recognition and Performance in the Research Institutions

Abstract This paper aims to provide insight into talent management and employee recognition variables, in an effort to understand if these management practices are, in a way, implemented in the Research Institutions in Qatar. It also aims to examine the link of these two constructs to employee performance and to suggest a pathway to improve the current practices, if any, in order to enhance the work performance. The sample of the study consisted of 180 full time employees who were randomly selected and surveyed using an online personalized questionnaire. The results of the empirical research uncover that talent management and employee recognition can significantly affect the level of employee performance, as well contributing to the organizational success and positioning. This study also found that talent management and employee recognition are interrelated variables that affect employee performance. Talent Management and employee performance are seen as strategic tools to implement strategic objectives and to enhance employees and organization’s performance. The study concludes with a set of recommendations for both practitioners and researchers working in Qatar and beyond. The results of the study emphasize the importance of managing employee recognition in shaping work performance. It seems to be individuals’ need for recognition, esteem and social status continues to be a higher order need irrespective of time and context. This paper is the first paper in Qatar and the Middle East that examines the role of talent management and employee recognition in shaping employee performance in the context of research institutions.
Evidence of functional species sorting by rainfall and biotic interactions: A community monolith experimental approach

Understanding the mechanisms that underlie species assembly is a central concern in community ecology. Abiotic and biotic filters are probabilistic ‘sieves’ that allow species with certain functional traits to become a part of the community, or not. We manipulated natural plant assemblies in order to identify variations in the timings of biotic and abiotic filters that determine community trait assemblies. We extracted soil portions when the investigated annual plant community was in its seed phase (‘community monolith’), thereby maintaining the structure and similar soil characteristics to the field conditions. Community monoliths were subjected to experimental manipulation in terms of the rainfall timing and amount, and perturbations of the biological soil crust (BSC; intact vs. perturbed). We surveyed the experimental community assembly over time based on the functional diversity by considering important functional traits in different life stages. We found that autumn droughts acted as abiotic filters by favouring the germination and establishment of species with greater investment in the root biomass. Under severe droughts (66% water reduction), the experimental assemblies were dominated by species with functional traits adapted to water shortage conditions: high leaf dry matter content, low specific leaf area, small individual size, low reproductive ratio and high root:shoot ratio. We identified two roles of BSCs in annual plant species assemblies: (a) as a biotic filter that limited the establishment of species based on seed size, and (b) as a buffer against water stress conditions by reducing soil evapotranspiration. Synthesis. We demonstrated the importance of the timing and amount of rainfall for shaping annual plant communities, and identified germination filters as the main process that determined community assemblies. Our results suggest that the phenotypic integration of functional traits facilitates resistance to drought during the life cycle. The BSC–annual plant relationship shifted from negative, by acting as a germination filter, to positive, by acting as a buffer in later stages. Climatic fluctuations and fine scale biotic determinants of spatial heterogeneity emerged as sources of changes in the community assembly in time and space to possibly promote species coexistence and trait differences among the communities studied.
Inverse Associations of Schistosoma mansoni Infection and Metabolic Syndromes in Humans: A Cross-Sectional Study in Northeast Ethiopia

Background: Recent animal and retrospective human studies have demonstrated that Schistosoma mansoni infection may have potential to protect against development of metabolic syndromes. Thus, the aim of this study was to assess metabolic panel among S. mansoni egg positives and egg negatives in stool examinations. This study was a cross-sectional study, conducted involving 120 participants from S. mansoni endemic town (Kemise) and 61 from non-endemic town (Kombolcha), Northeast Ethiopia. Stool samples were collected and examined for S. mansoni and other helminths using Kato-Katz method. Furthermore, blood samples were collected and used for determination of blood sugar, lipid profile tests, insulin, and C-reactive protein. Data were analyzed using SPSS software version 20. Chi-square test, independent mean t-test, and logistic regression models were employed on data. P values less than . 05 were considered as statistically significant. Results: S. mansoni infected participants (n = 41; all from Kemise) had significantly lower levels of fasting blood sugar, low prevalence of dyslipidemia (at least one or more abnormal lipid profile tests; total cholesterol, low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], and triglycerides) as compared with controls (n = 79 in Kemise and 61 in Kombolcha). Moreover, logistic regression model indicated that with the adjusted odds ratios, there was significant inverse association between S. mansoni infection and impaired fasting glucose (adjusted odds ratio −0.181, 95% confidence interval: 0.042-0.774). Conclusions: Low fasting blood sugar and reduced prevalence of dyslipidemia in S. mansoni egg positive participants might suggest inverse association of S. mansoni infection and development of metabolic syndromes. Furthermore, large-scale studies are recommended to assess the role of S. mansoni egg and/or worm antigens in modulating the host metabolic profile and reducing the risk of metabolic syndromes, including diabetes mellitus and cardiovascular diseases.
Within-Individual Canalization Contributes to Age-Related Increases in Trait Repeatability: A Longitudinal Experiment in Red Knots

Age-related increases in the repeatable expression of labile phenotypic traits are often assumed to arise from an increase in among-individual variance due to differences in developmental plasticity or by means of state-behavior feedbacks. However, age-related increases in repeatability could also arise from a decrease in within-individual variance as a result of stabilizing trait expression, that is, canalization. Here we describe age-related changes in within-individual and among-individual variance components in two correlated traits—gizzard mass and exploration behavior—in a medium-sized shorebird, the red knot (Calidris canutus). Increased repeatability of gizzard mass came about due to an increase in among-individual variance, unrelated to differences in developmental plasticity, together with decreases in within-individual variance consistent with canalization. We also found canalization of exploration but no age-related increase in overall repeatability, which suggests that showing predictable expression of exploration behavior may be advantageous from a very young age onward. Contrasts between juveniles and adults in the first year after their capture provide support for the idea that environmental conditions play a key role in generating among-individual variation in both gizzard mass and exploration behavior. Our study shows that stabilization of traits occurs under constant conditions: with increased exposure to predictable cues, individuals may become more certain in their assessment of the environment allowing traits to become canalized.
Fostering preschoolers positive behaviour and attitude towards Down syndrome by Down syndrome doll play

ABSTRACT The current pilot study examines pre-schooler’s play behaviour involving dolls with and without facial characteristics of Down syndrome over a period of 16 weeks. Play behaviours were categorized into one of 3 behavioural categories with predefined observational scoring grids: prosocial, antisocial, or neutral/no behaviour. Participants also individually received an adapted version of the Preschool Racial Attitude Measure, to assess in- and outgroup attitudes of participants towards children with Down syndrome. Positive and negative attitudes and behaviours towards Down syndrome dolls were analysed over time with pre and post-measurements. Results showed that, whereas children showed negative behaviour towards the Down syndrome doll at the start of the experiment, this negative behaviour disappeared by the end of the experiment. Furthermore, children showed significantly more positive play behaviour during the experiment towards the Down syndrome dolls. The results of this pilot study indicate that playing with Down syndrome dolls at preschool age can potentially be used as a low cost, non-invasive prevention program to foster future positive behaviours towards Down syndrome, setting the stage for interactions with real children with Down syndrome in inclusive education. Implications for meeting the needs of children with Down syndrome and their peers in inclusive education are discussed.
Predicting the performance and emission characteristics of a Mahua oil-hydrogen dual fuel engine using artificial neural networks

ABSTRACT The current research work aims at developing the Artificial Neural Network (ANN) model to predict the performance and emission behavior of diesel-powered engine. Conventional diesel engine was converted into dual fuel mode using high octane and high cetane fuels. Several experiments were performed with varying high-octane fuel flow rate and constant flow of high cetane fuel. These data were used for training and testing the ANN model. Feed forward back propagation algorithm was used to predict the performance and emission behavior of dual fuel engine. Engine load, high octane fuel flow rate, fuel injection pressure and fuel injection timing were used as input parameters of ANN model whereas BTE, EGT, HC, CO, NO, and smoke were used as output prediction parameters. The accuracy of the predicted values was determined by means of MSE and Regression coefficient. Finally, the study concludes that there is a credible behavior between ANN predicted values and experimental values for performance and emission behavior of dual fuel engine.