Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping Inequalities in the Physical, Built and Social Environment in Population-Based Studies of Brain Health

This mini-tutorial describes how combining aggregate-level data about the physical, built and social environment can facilitate our understanding of factors shaping the human brain and, in turn, brain health. It provides entry-level information about methods and approaches one can use to uncover how inequalities in the local environment lead to health inequalities in general, and those in brain health in particular. This background knowledge should be helpful to those who are interested in using neuroimaging to investigate how environmental factors shape inter-individual variations in the human brain.
Development and Validation of a Risk Score for Predicting Invasive Candidiasis in Intensive Care Unit Patients by Incorporating Clinical Risk Factors and Lymphocyte Subtyping

Objective To develop and validate a rapid invasive candidiasis (IC)-predictive risk score in intensive care unit (ICU) patients by incorporating clinical risk factors and parameters of lymphocyte subtyping. Methods A prospective cohort study of 1054 consecutive patients admitted to ICU was performed. We assessed the clinical characteristics and parameters of lymphocyte subtyping at the onset of clinical signs of infection and their potential influence on IC diagnosis. A risk score for early diagnosis of IC was developed and validated based on a logistic regression model. Results Sixty-nine patients (6.5%) had IC. Patients in the cohort (N=1054) were randomly divided into a development (n=703) or validation (n=351) cohorts. Multivariate logistic regression identified that CD8+ T-cell count ≤143 cells/mm3, receipt of high-dose corticosteroids (dose ≥50 mg prednisolone equivalent), receipt of carbapenem/tigecycline, APACHE II score≥15, (1,3)-β-D-glucan (BDG) positivity and emergency gastrointestinal/hepatobiliary (GIT/HPB) surgery were significantly related with IC. IC risk score was calculated using the following formula: CD8+ T-cell count ≤143 cells/mm3 + receipt of high-dose corticosteroids + receipt of carbapenem/tigecycline + APACHE II score ≥15 + BDG positivity + emergency GIT/HPB surgery ×2. The risk scoring system had good discrimination and calibration with area under the receiver operating characteristic (AUROC) curve of 0.820 and 0.807, and a non-significant Hosmer-Lemeshow test P=0.356 and P=0.531 in the development and validation cohorts, respectively. We categorized patients into three groups according to risk score: low risk (0-2 points), moderate risk (3-4 points) and high risk (5-7 points). IC risk was highly and positively associated with risk score (Pearson contingency coefficient=0.852, P for trend=0.007). Candida score had a moderate predicting efficacy for early IC diagnosis. The AUROC of the risk score was significantly larger than that of Candida score (0.820 versus 0.711, Z=2.013, P=0.044). Conclusions The predictive scoring system, which used both clinical factors and CD8+ T cell count, served as a clinically useful predictive model for rapid IC diagnosis in this cohort of ICU patients. Clinical Trial Registration chictr.org. cn, identifier ChiCTR-ROC-17010750.
The Effect of Outcome vs. Process Accountability-Focus on Performance: A Meta-Analysis

Background The foundation of a safe practice is accountability, especially outcome- rather than process-focused accountability, particularly during pandemics such as COVID-19. Accountability is an essential behavior that promotes congruence between nursing actions and standards associated with quality of care. Moreover, the scant research examining whether one accountability focus is superior in motivating humans to better task performance yields inconclusive results. Aims Systematically examine the effect of an outcome- vs. process-accountability focus on performance and identify any moderating variables. Design Systematic review and meta-analysis. Data sources PsycINFO, Medline, PubMed, Scopus, and CINAHL databases, with all publications to November 2020. Review methods A systematic search using Systematic Reviews and Meta-Analyses (PRISMA) guidelines was performed. Statistical analysis and forest plots were performed using MetaXL 5.3. Heterogeneity was presented using I2 statistics and Q tests, and possible publication bias was assessed with a Doi plot and the LFK index. Results Seven studies representing nine experiments involving 1,080 participants were included. The pooled effect of the nine experiments on task performance failed to show significant differences (mean = −0.09; 95% Confidence Interval [95%CI]: −0.21, 0.03), but a significant moderating effect of task complexity was demonstrated. Specifically, outcome accountability exerts a beneficial effect in complex tasks (mean = −0.48 [95%CI: −0.62, −0.33]) whereas process accountability improves the performance in simpler tasks (mean = 0.96 [95%CI: 0.72, 1.20]). Conclusion These findings demonstrated that accountability focus by itself cannot serve as a sole motivator of better performance, because task complexity moderates the link between accountability focus and task performance. Outcome accountability exerts a beneficial effect for more-complex tasks, whereas process accountability improves the performance of simpler tasks. These findings are crucial in nursing, where it is typically assumed that a focus on outcomes is more important than a focus on processes.
Comparative Ionomics and Metabolic Responses and Adaptive Strategies of Cotton to Salt and Alkali Stress

Soil salinization and alkalization severely inhibit agriculture. However, the response mechanisms of cotton to salt stress or alkali stress are unclear. Ionomics and metabolomics were used to investigate salt and alkali stresses in cotton roots and leaves. Compared with the control, salt-treated and alkali-treated cotton plants showed 51.8 and 53.0% decreases in biomass, respectively. Under salt stress, the concentration of N decreased in roots but increased in leaves, and the concentrations of P and K increased in roots but decreased in leaves. Salt stress inhibited Ca, B, N, and Fe uptake and Mg, K, P, S, and Cu transport, but promoted Mo, Mn, Zn, Mg, K, P, S, and Cu uptake and Mo, Mn, Zn, B, N, and Fe transport. Under alkali stress, the concentrations of N and P in roots and leaves decreased, while the concentrations of K in roots and leaves increased. Alkali stress inhibited P, Ca, S, N, Fe, and Zn uptake and N, P, Mg and B transport, but promoted K, Mn, Cu, Mo, Mg, and B uptake and K, Mn, Cu, Mo, Fe, and Zn transport. Under salt stress in the leaves, 93 metabolites increased, mainly organic acids, amino acids, and sugars, increased in abundance, while 6 decreased. In the roots, 72 metabolites increased, mainly amino acids, organic acids, and sugars, while 18 decreased. Under alkali stress, in the leaves, 96 metabolites increased, including organic acids, amino acids, and sugars, 83 metabolites decreased, including organic acids, amino acids, and sugars; In the roots, 108 metabolites increased, including organic acids, amino acids, and sugars. 83 metabolites decreased, including organic acids and amino acids. Under salt stress, cotton adapts to osmotic stress through the accumulation of organic acids, amino acids and sugars, while under alkali stress, osmoregulation was achieved via inorganic ion accumulation. Under salt stress, significant metabolic pathways in the leaves and roots were associated with amino acid and organic acid metabolism, sugar metabolism was mainly used as a source of energy, while under alkali stress, the pathways in the leaves were related to amino acid and linoleic acid metabolism, β-Oxidation, TCA cycle, and glycolysis were enhanced to provide the energy needed for life activities. Enhancing organic acid accumulation and metabolism in the roots is the key response mechanism of cotton to alkalinity.
An Efficient Evaluation System Accelerates α-Helical Antimicrobial Peptide Discovery and Its Application to Global Human Genome Mining

Antimicrobial peptides (AMPs), as an important part of the innate immune system of an organism, is a kind of promising drug candidate for novel antibiotics due to their unique antibacterial mechanism. However, the discovery of novel AMPs is facing a great challenge due to the complexity of systematic experiments and the poor predictability of antimicrobial activity. Here, a novel and comprehensive screening system, the Multiple Descriptor Multiple Strategy (MultiDS), was proposed based on 59 physicochemical and structural parameters, three strategies, and four algorithms for the mining of α-helical AMPs. This approach was applied to mine the encrypted peptide antibiotics from the global human genome, including introns and exons. A library of approximately 70 billion peptides with 15–25 amino acid residues was screened by the MultiDS system and generated a list of peptides with the Multiple Descriptor Index (MD index) scores, which was the core part of the MultiDS system. Sixty peptides with top MD scores were chemically synthesized and experimentally tested their antimicrobial activity against 10 kinds of Gram-positive bacteria, Gram-negative bacteria (including drug-resistant pathogens). A total of fifty-nine out of 60 (98.3%) peptides exhibited antimicrobial activity (MIC ≤ 64 μg/mL), and 24 out of 60 (40%) peptides showed high activity (MIC ≤ 2 μg/mL), validating the MultiDS system was an effective and predictive screening tool with high hit rate and superior antimicrobial activity. For further investigation, AMPs S1, S2, and S3 with the highest MD scores were used to treat the skin infection mouse models in vivo caused by Escherichia coli, drug-resistance Escherichia coli, and Staphylococcus aureus, respectively. All of S1, S2, and S3 showed comparable therapeutic effects on promoting infection healing to or even better than the positive drug levofloxacin. A mechanism study discovered that rapid bactericidal action was caused by cell membrane disruption and content leakage. The MultiDS system not only provides a high-throughput approach that allows for the mining of candidate AMPs from the global genome sequence but also opens up a new route to accelerate the discovery of peptide antibiotics.
Exploring the Applicability of Calorespirometry to Assess Seed Metabolic Stability Upon Temperature Stress Conditions—Pisum sativum L. Used as a Case Study

The availability of phenotyping tools to assist breeding programs in the selection of high-quality crop seeds is of obvious interest with consequences for both seed producers and consumers. Seed germination involves the activation of several metabolic pathways, such as cellular respiration to provide the required ATP and reducing power. This work tested the applicability of calorespirometry, the simultaneous measurement of heat and CO2 rates, as a phenotyping tool to assess seed respiratory properties as a function of temperature. The effect of temperature on seed germination was evaluated after 16 h of seed imbibition by calorespirometric experiments performed in isothermal mode at 15, 20, 25, and 28°C on the seeds of three cultivars of peas (Pisum sativum L.) commonly used in conventional agriculture (cvs. ‘Rondo’, ‘Torta de Quebrar’, and ‘Maravilha d’América’). Significant differences in metabolic heat rate and CO2 production rate (RCO2) as well as in the temperature responses of these parameters were found among the three cultivars. A seed germination trial was conducted during the 6 days of imbibition to evaluate the predictive power of the parameters derived from the calorespirometric measurements. The germination trial showed that the optimal germination temperature was 20°C and low germination rates were observed at extreme temperatures (15 or 28°C). The cv. ‘Torta de Quebrar’ showed significantly higher germination in comparison with the other two cultivars at all three temperatures. In comparison with the other two cultivars, ‘Torta de Quebrar’ has the lowest metabolic heat and CO2 rates and the smallest temperature dependence of these measured parameters. Additionally, ‘Torta de Quebrar’ has the lowest values of growth rate and carbon use efficiency calculated from the measured variables. These data suggest that calorespirometry is a useful tool for phenotyping physiologic efficiency at different temperatures during early germination stages, and can determine the seeds with the highest resilience to temperature variation, in this case ‘Torta de Quebrar’.
Kr-h1, a Cornerstone Gene in Insect Life History

Insect life cycle is coordinated by hormones and their downstream effectors. Krüppel homolog1 (Kr-h1) is one of the crucial effectors which mediates the actions of the two critical hormones of insects, the juvenile hormone (JH) and 20-hydroxyecdysone (20E). It is a transcription factor with a DNA-binding motif of eight C2H2 zinc fingers which is found to be conserved among insect orders. The expression of Kr-h1 is fluctuant during insect development with high abundance in juvenile instars and lower levels in the final instar and pupal stage, and reappearance in adults, which is governed by the coordination of JH, 20E, and miRNAs. The dynamic expression pattern of Kr-h1 is closely linked to its function in the entire life of insects. Over the past several years, accumulating studies have advanced our understanding of the role of Kr-h1 during insect development. It acts as a universal antimetamorphic factor in both hemimetabolous and holometabolous species by directly inhibiting the transcription of 20E signaling genes Broad-Complex (Br-C) and Ecdysone induced protein 93F (E93), and steroidogenic enzyme genes involved in ecdysone biosynthesis. Meanwhile, it promotes vitellogenesis and ovarian development in the majority of studied insects. In addition, Kr-h1 regulates insect behavioral plasticity and caste identity, neuronal morphogenesis, maturation of sexual behavior, as well as embryogenesis and metabolic homeostasis. Hence, Kr-h1 acts as a cornerstone regulator in insect life.
Modified Adenosines Sensitize Glioblastoma Cells to Temozolomide by Affecting DNA Methyltransferases

Glioblastoma (GBM) is the most common and lethal primary malignant brain tumor, and due to its unique features, its management is certainly one of the most challenging ones among all cancers. N6-isopentenyladenosine (IPA) and its analog N6-benzyladenosine (N6-BA) are modified nucleosides endowed with potent antitumor activity on different types of human cancers, including GBM. Corroborating our previous finding, we demonstrated that IPA and N6-BA affect GBM cell line proliferation by modulating the expression of the F-box WD repeat domain-containing-7 (FBXW7), a tumor suppressor with a crucial role in the turnover of many proteins, such as SREBPs and Mcl1, involved in malignant progression and chemoresistance. Luciferase assay revealed that IPA-mediated upregulation of FBXW7 translates in transcriptional inactivation of its oncogenic substrates (Myc, NFkB, or HIF-1α). Moreover, downregulating MGMT expression, IPA strongly enhances the killing effect of temozolomide (TMZ), producing a favorable sensitizing effect starting from a concentration range much lower than TMZ EC50. Through DNA methyltransferase (DNMT) activity assay, analysis of the global DNA methylation, and the histone modification profiles, we demonstrated that the modified adenosines behave similar to 5-AZA-dC, known DNMT inhibitor. Overall, our results provide new perspectives for the first time, suggesting the modified adenosines as epigenetic tools able to improve chemo- and radiotherapy efficacy in glioblastoma and potentially other cancers.
Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model

Computer science plays an important role in modern dynamic health systems. Given the collaborative nature of the diagnostic process, computer technology provides important services to healthcare professionals and organizations, as well as to patients and their families, researchers, and decision-makers. Thus, any innovations that improve the diagnostic process while maintaining quality and safety are crucial to the development of the healthcare field. Many diseases can be tentatively diagnosed during their initial stages. In this study, all developed techniques were applied to tuberculosis (TB). Thus, we propose an optimized machine learning-based model that extracts optimal texture features from TB-related images and selects the hyper-parameters of the classifiers. Increasing the accuracy rate and minimizing the number of characteristics extracted are our goals. In other words, this is a multitask optimization issue. A genetic algorithm (GA) is used to choose the best features, which are then fed into a support vector machine (SVM) classifier. Using the ImageCLEF 2020 data set, we conducted experiments using the proposed approach and achieved significantly higher accuracy and better outcomes in comparison with the state-of-the-art works. The obtained experimental results highlight the efficiency of modified SVM classifier compared with other standard ones.
Amiloride-Insensitive Nat-H(cid:1) Exchange: A Candidate Mediator of Erythrocyte Nat-Li(cid:1) Countertransport

Erythrocyte Na(cid:1)-Li(cid:1) countertransport shows an increased activity in essential hypertension and diabetic nephropathy, but its nature remains unknown. This amiloride-insensitive membrane transport may not be a mode of operation of the amiloride-sensitive NHE1, the only Na(cid:1)-H(cid:1) exchange isoform found in human erythrocytes. Whether an independent, although unknown, amiloride-insensitive isoform mediates Na(cid:1)-Li(cid:1) countertransport is unclear. Na(cid:1)-H(cid:1) exchange activity was measured in acid-loaded erythrocytes. Dimethylamiloride, a specific inhibitor of Na(cid:1)-H(cid:1) exchange and phloretin, a known inhibitor of Na(cid:1)-Li(cid:1) countertransport, gave a reduction in Htdriven Na(cid:1) influx (by 31 and 37%, respectively). This effect was additive, and a 66% reduction in H(cid:1)-driven Na(cid:1) influx was found in the presence of both inhibitors. Internal
Two functionally distinct heme/iron transport systems are virulence determinants of the fish pathogen Flavobacterium psychrophilum

ABSTRACT Bacterial pathogens have a critical impact on aquaculture, a sector that accounts for half of the human fish consumption. Flavobacterium psychrophilum (phylum Bacteroidetes) is responsible for bacterial cold-water disease in salmonids worldwide. The molecular factors involved in host invasion, colonization and haemorrhagic septicaemia are mostly unknown. In this study, we identified two new TonB-dependent receptors, HfpR and BfpR, that are required for adaptation to iron conditions encountered during infection and for virulence in rainbow trout. Transcriptional analyses revealed that their expression is tightly controlled and upregulated under specific iron sources and concentrations. Characterization of deletion mutants showed that they act without redundancy: BfpR is required for optimal growth in the presence of high haemoglobin level, while HfpR confers the capacity to acquire nutrient iron from haem or haemoglobin under iron scarcity. The gene hfpY, co-transcribed with hfpR, encodes a protein related to the HmuY family. We demonstrated that HfpY binds haem and contributes significantly to host colonization and disease severity. Overall, these results are consistent with a model in which both BfpR and Hfp systems promote haem uptake and respond to distinct signals to adapt iron acquisition to the different stages of pathogenesis. Our findings give insight into the molecular basis of pathogenicity of a serious pathogen belonging to the understudied family Flavobacteriaceae and point to the newly identified haem receptors as promising targets for antibacterial development.
Top 50 Cited Bone Graft Orthopedic Papers

The purpose of this research is to recognize the highest 50 most-mentioned articles in the literature concentrating on bone grafts. That has been accomplished with the use of the Scopus database and the search slogan "bone grafts," and we inquired for the 50 most-cited articles on bone grafting. The study was completed in September 2020. We investigated the articles issued between 1970 and 2020. The articles were organized and classified based on the total number of citations. We appraised the following information relating to each article: first author, year of publication, journal, and title. A total of 1,580 studies matched our search standards, of which the 50 most-cited extended between 1,862 and 403 citations. Seven articles were cited more than 1,000 times. The article by Marx et al. was the maximum-cited article, with 1,862 citations, followed by Younger et al.'s with 1,461 and Giannoudis et al.'s with 1,245. The majority of the studies originated from the United States (n = 30) and were published in the 2000s. Biomaterials was the most regular destination journal (n = 8), followed by the Journal of Bone and Joint Surgery American series (n = 7). A maximum of the articles focused on the different types of bone grafts and their alternatives including bone tissue engineering (n=29). Our investigation of the highest 50 articles linking to bone grafting has emphasized the most significant papers in the field. These cover a wide-ranging variety of topics including types, management, and mechanism of action of bone grafts. To recognize the present treatment guidelines and how the use of bone grafting has grown, it is vital to know the most-cited articles relating to this grafting.
Experiments and results on DTN for IOT III Urbanet collaboration

This document presents the full study of the DTN (Delay Tolerant Network) within IOT (Internet Of Things) context. The motivation for using generic protocols able to handle the constraints due to the IOT is highlighted with the choice of the Bundle Protocol. A study of existing implementations of this protocol is realised within a sensor context. We justify the choices made for our implementation, then we define the mechanisms which we test with the Cooja platform by following the protocol of tests we have developed. The results of the experiments are analysed.
The Impact of Teaching Materials on Learning Computer Programming Languages in Kurdistan Region Universities and Institutes

It is evident that learning and teaching computer programming are considered as one of the striking challenges in academic environments. Meanwhile, selecting the correct and appropriate materials can leave an enormous impact in learning computer programming languages. However, recently this argument has been put under scrutiny as to which types of materials motivate learners to learn computer programming languages as well as enhance learning outcomes. Therefore, the main objective of this study is to investigate the current teaching and learning materials of computer programming languages in Kurdistan region of Iraq universities. Additionally, another aim is to give a rigorous analysis of how materials help students to learn computer programming language. A further focus is to identify the difficulties of learning computer programming languages at undergraduate level which constitutes technical Diploma and Bachelor. The last but not the least, this paper examines new approaches to teaching programming languages as a cognitive model for programming education.