This article presents W-IQ-TREE, an intuitive and user-friendly web interface and server for IQ-TREE, an efficient phylogenetic software for maximum likelihood analysis. W-IQ-TREE supports multiple ...sequence types (DNA, protein, codon, binary and morphology) in common alignment formats and a wide range of evolutionary models including mixture and partition models. W-IQ-TREE performs fast model selection, partition scheme finding, efficient tree reconstruction, ultrafast bootstrapping, branch tests, and tree topology tests. All computations are conducted on a dedicated computer cluster and the users receive the results via URL or email. W-IQ-TREE is available at http://iqtree.cibiv.univie.ac.at It is free and open to all users and there is no login requirement.
Fuzzy set theory, extensively applied in abundant disciplines, has been recognized as a plausible tool in dealing with uncertain and vague information due to its prowess in mathematically ...manipulating the knowledge of imprecision. In fuzzy-data comparisons, exploring the general ranking measure that is capable of consistently differentiating the magnitude of fuzzy numbers has widely captivated academics’ attention. To date, numerous indices have been established; however, counterintuition, less discrimination, and/or inconsistency on their fuzzy-number rating outcomes have prohibited their comprehensive implementation. To ameliorate their manifested ranking weaknesses, this paper proposes a unified index that multiplies weighted-mean and weighted-area discriminatory components of a fuzzy number, respectively, called centroid value and attitude-incorporated left-and-right area. From theoretical proof of consistency property and comparative studies for triangular, triangular-and-trapezoidal mixed, and nonlinear fuzzy numbers, the unified index demonstrates conspicuous ranking gains in terms of intuition support, consistency, reliability, and computational simplicity capability. More importantly, the unified index possesses the consistency property for ranking fuzzy numbers and their images as well as for symmetric fuzzy numbers with an identical altitude which is a rather critical property for accurate matching and/or retrieval of information in the field of computer vision and image pattern recognition.
The COVID-19 pandemic has imposed a heavy burden on health care systems and governments. Health literacy (HL) and eHealth literacy (as measured by the eHealth Literacy Scale eHEALS) are recognized as ...strategic public health elements but they have been underestimated during the pandemic. HL, eHEALS score, practices, lifestyles, and the health status of health care workers (HCWs) play crucial roles in containing the COVID-19 pandemic.
The aim of this study is to evaluate the psychometric properties of the eHEALS and examine associations of HL and eHEALS scores with adherence to infection prevention and control (IPC) procedures, lifestyle changes, and suspected COVID-19 symptoms among HCWs during lockdown.
We conducted an online survey of 5209 HCWs from 15 hospitals and health centers across Vietnam from April 6 to April 19, 2020. Participants answered questions related to sociodemographics, HL, eHEALS, adherence to IPC procedures, behavior changes in eating, smoking, drinking, and physical activity, and suspected COVID-19 symptoms. Principal component analysis, correlation analysis, and bivariate and multivariate linear and logistic regression models were used to validate the eHEALS and examine associations.
The eHEALS had a satisfactory construct validity with 8 items highly loaded on one component, with factor loadings ranked from 0.78 to 0.92 explaining 76.34% of variance; satisfactory criterion validity as correlated with HL (ρ=0.42); satisfactory convergent validity with high item-scale correlations (ρ=0.80-0.84); and high internal consistency (Cronbach α=.95). HL and eHEALS scores were significantly higher in men (unstandardized coefficient B=1.01, 95% CI 0.57-1.45, P<.001; B=0.72, 95% CI 0.43-1.00, P<.001), those with a better ability to pay for medication (B=1.65, 95% CI 1.25-2.05, P<.001; B=0.60, 95% CI 0.34-0.86, P<.001), doctors (B=1.29, 95% CI 0.73-1.84, P<.001; B 0.56, 95% CI 0.20-0.93, P=.003), and those with epidemic containment experience (B=1.96, 95% CI 1.56-2.37, P<.001; B=0.64, 95% CI 0.38-0.91, P<.001), as compared to their counterparts, respectively. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures (B=0.13, 95% CI 0.10-0.15, P<.001; B=0.22, 95% CI 0.19-0.26, P<.001), had a higher likelihood of healthy eating (odds ratio OR 1.04, 95% CI 1.01-1.06, P=.001; OR 1.04, 95% CI 1.02-1.07, P=.002), were more physically active (OR 1.03, 95% CI 1.02-1.03, P<.001; OR 1.04, 95% CI 1.03-1.05, P<.001), and had a lower likelihood of suspected COVID-19 symptoms (OR 0.97, 95% CI 0.96-0.98, P<.001; OR 0.96, 95% CI 0.95-0.98, P<.001), respectively.
The eHEALS is a valid and reliable survey tool. Gender, ability to pay for medication, profession, and epidemic containment experience were independent predictors of HL and eHEALS scores. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures, healthier lifestyles, and a lower likelihood of suspected COVID-19 symptoms. Efforts to improve HCWs' HL and eHEALS scores can help to contain the COVID-19 pandemic and minimize its consequences.
The recent COVID-19 pandemic poses a serious threat to global public health, thus there is an urgent need to define the molecular mechanisms involved in SARS-CoV-2 spike (S) protein-mediated virus ...entry that is essential for preventing and/or treating this emerging infectious disease. In this study, we examined the blocking activity of human COVID-19 convalescent plasma by cell-cell fusion assays using SARS-CoV-2-S-transfected 293 T as effector cells and ACE2-expressing 293 T as target cells. We demonstrate that the SARS-CoV-2 S protein exhibits a very high capacity for membrane fusion and is efficient in mediating virus fusion and entry into target cells. Importantly, we find that COVID-19 convalescent plasma with high titers of IgG neutralizing antibodies can block cell-cell fusion and virus entry by interfering with the SARS-CoV-2-S/ACE2 or SARS-CoV-S/ACE2 interactions. These findings suggest that COVID-19 convalescent plasma may not only inhibit SARS-CoV-2-S but also cross-neutralize SARS-CoV-S-mediated membrane fusion and virus entry, supporting its potential as a preventive and/or therapeutic agent against SARS-CoV-2 as well as other SARS-CoV infections.
Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is ...not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%. IQ-TREE is freely available at http://www.cibiv.at/software/iqtree.
•SARS-CoV-2 specific T cell responses are generated in some convalescent subjects.•None of the single SARS-CoV-2 peptides could induce T cell responses universally.•SARS-CoV-2 specific T cell ...responses positively correlated with B cell response.
The COVID-19 pandemic caused by SARS-CoV-2 infection poses a serious threat to public health. An explicit investigation of COVID-19 immune responses, particularly the host immunity in recovered subjects, will lay a foundation for the rational design of therapeutics and/or vaccines against future coronaviral outbreaks. Here, we examined virus-specific T cell responses and identified T cell epitopes using peptides spanning SARS-CoV-2 structural proteins. These peptides were used to stimulate peripheral blood mononuclear cells (PBMCs) derived from COVID-19-recovered subjects, followed by an analysis of IFN-γ-secreting T cells by enzyme-linked immunosorbent spot (ELISpot). We also evaluated virus-specific CD4 or CD8 T cell activation by flow cytometry assay. By screening 52 matrix pools (comprised of 315 peptides) of the spike (S) glycoprotein and 21 matrix pools (comprised of 102 peptides) spanning the nucleocapsid (N) protein, we identified 28 peptides from S protein and 5 peptides from N protein as immunodominant epitopes. The immunogenicity of these epitopes was confirmed by a second ELISpot using single peptide stimulation in memory T cells, and they were mapped by HLA restrictions. Notably, SARS-CoV-2 specific T cell responses positively correlated with B cell IgG and neutralizing antibody responses to the receptor-binding domain (RBD) of the S protein. Our results demonstrate that defined levels of SARS-CoV-2 specific T cell responses are generated in some, but not all, COVID-19-recovered subjects, fostering hope for the protection of a proportion of COVID-19-exposed individuals against reinfection. These results also suggest that these virus-specific T cell responses may induce protective immunity in unexposed individuals upon vaccination, using vaccines generated based on the immune epitopes identified in this study. However, SARS-CoV-2 S and N peptides are not potently immunogenic, and none of the single peptides could universally induce robust T cell responses, suggesting the necessity of using a multi-epitope strategy for COVID-19 vaccine design.
We provide the necessary and sufficient characterizations on a pair of positive radial functions so that the two-weight Hardy inequalities hold true on homogeneous groups, one of most general ...subclasses of nilpotent Lie groups. We also present a simple condition on a couple of positive radial weight functions for the
L
p
−Hardy type inequalities to be valid.
Myeloid-derived suppressor cells (MDSCs) contribute to HIV progression by impairing antiviral immunity; however, the mechanisms responsible for MDSC development during HIV infection are incompletely ...understood. HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) is a long noncoding RNA (lncRNA) that plays a pivotal role in regulating myeloid cell development via targeting HOXA1. The role of HOTAIRM1--HOXA1 in the differentiation and functions of MDSCs during HIV infection remains unclear.
In this study, we measured MDSC induction and suppressive functions by flow cytometry, RT-PCR, and co-culture experiments using CD33 myeloid cells derived from people living with HIV (PLHIV) on antiretroviral therapy (ART). We also manipulated the HOTAIRM1--HOXA1 axis in myeloid cells using knockdown and overexpression approaches.
We demonstrate that HOTAIRM1 and HOXA1 expressions are reciprocally upregulated and are responsible for increased levels of immunosuppressive molecules, such as arginase 1 (Arg1), inducible nitric oxide synthase (iNOS), signal transducer and activator of transcription 3 (STAT3), and reactive oxygen species (ROS), in CD33 myeloid cells derived from PLHIV on ART. We found that overexpression of HOTAIRM1 or HOXA1 in CD33 cells isolated from healthy individuals promoted the differentiation and suppressive functions of MDSCs, whereas silencing of HOTAIRM1 or HOXA1 expression in MDSCs derived from PLHIV significantly inhibited the frequency of MDSCs and expressions of the immunosuppressive molecules and reduced their immunosuppressive effects on T cells.
These results indicate that the HOTAIRM1--HOXA1 axis enhances differentiation and suppressive functions of MDSCs and could be a potential therapeutic target for immunomodulation during latent HIV infection.
This study constructs an automatic model for detecting and classifying asphalt pavement crack. Image processing techniques including steerable filters, projective integral of image, and an enhanced ...method for image thresholding are employed for feature extraction. Different scenarios of feature selection have been attempted to create data sets from digital images. These data sets are then employed to train and verify the performance of machine learning algorithms including the support vector machine (SVM), the artificial neural network (ANN), and the random forest (RF). The feature set that consists of the properties derived from the projective integral and the properties of crack objects can deliver the most desirable outcome. Experimental results supported by the Wilcoxon signed-rank test show that SVM has achieved the highest classification accuracy rate (87.50%), followed by ANN (84.25%), and RF (70%). Accordingly, the proposed automatic approach can be helpful to assist transportation agencies and inspectors in the task of pavement condition assessment.
Crack detection is a crucial task in periodic pavement survey. This study establishes and compares the performance of two intelligent approaches for automatic recognition of pavement cracks. The ...first model relies on edge detection approaches of the Sobel and Canny algorithms. Since the implementation of the two edge detectors require the setting of threshold values, Differential Flower Pollination, as a metaheuristic, is employed to fine-tune the model parameters. The second model is constructed by the implementation of the Convolution Neural Network (CNN) – a deep learning algorithm. CNN has the advantage of performing the feature extraction and the prediction of crack/non-crack condition in an integrated and fully automated manner. Experimental results show that the model based on CNN achieves a good prediction performance of Classification Accuracy Rate (CAR) = 92.08%. This performance is significantly better than the method based on the edge detection algorithms (CAR = 79.99%). Accordingly, the proposed CNN based crack detection model is a promising alternative to support transportation agencies in the task of periodic pavement inspection.
•Two approaches for automatic recognition of pavement crack are constructed.•The first approach relies on the Sobel and Canny edge detection algorithms.•The second approach employs deep neural network.•Edge detection based model attains an accuracy rate of 79.99%.•Deep neural network achieves a superior accuracy rate of 92.08%.
PDF
