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Abstract\nHIGHLIGHTSCFRP laminates are commonly used in aircraft structures due to their high structural efficiency. The phenomenon-based failures of CFRP laminates have poor predictability for the complex failure process with buckling and matrix fractures. This work carried out seven shear tests of CFRP laminates. It also attempts to reveal its failure characteristic points by directly modeling the measured strain data based on the relative deformation distribution catastrophe. The failure characteristic points are revealed by constructing the stressing state modes/parameters and applying the clustering analysis criterion, whose accuracy can be verified by comparing the shear failure characteristic points of nondestructive/impacted CFRP laminates.Conduct 7 nondestructive/impacted CFRP laminates shear tests.Construct the modes and characteristic parameters characterizing the shear-stressing state of CFRP laminates.Applying clustering analysis criterion to reveal the characteristic loads of CFRP laminates.Verify the accuracy and robustness of the characteristic loads. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is one of the core driving forces for the next breeding stage, and Breeding 4.0. Genotype matrix based on single‐nucleotide polymorphisms (SNPs) is often used in ML for genome‐to‐phenotype prediction. Genotype matrix has an inherent defect, as the feature spaces it generates across different individuals or groups are inconsistent, and this hinders the application of ML. To overcome the challenge, a genome descriptor, Genic SNPs Composition Tool (GSCtool) is developed, which counts the number of SNPs in each gene of the genome so the dimension of the feature vectors equals the number of annotated genes in a species. Compared to using the genotype matrix, using GSCtool significantly decreases the model training time and has a higher accuracy of phenotype prediction. GSCtool also achieves good performance in variety identification, which is useful in crop variety protection. In general, GSCtool will help facilitate the application and study of genomic ML. The source code and test data of GSCtool are freely available at https://github.com/SZJhacker/GSCtool and https://gitee.com/shenzijie/GSCtool. [ABSTRACT FROM AUTHOR]

As a classic issue, structural seismic bearing capacity could not be accurately predicted since it was based on a structural ultimate state with inherent uncertainty. This result led to rare research efforts to discover structures' general and definite working laws from their experimental data. This study is to reveal the seismic working law of a bottom frame structure from its shaking table strain data by applying structural stressing state theory: (1) The tested strains are transformed into generalized strain energy density (GSED) values. (2) The method is proposed to express the stressing state mode and the corresponding characteristic parameter. (3) According to the natural law of quantitative and qualitative change, the Mann–Kendall criterion detects the mutation feature in the evolution of characteristic parameters versus seismic intensity. Moreover, it is verified that the stressing state mode also presents the corresponding mutation feature, which reveals the starting point in the seismic failure process of the bottom frame structure. (4) The Mann–Kendall criterion distinguishes the elastic–plastic branch (EPB) feature in the bottom frame structure's normal working process, which could be taken as the design reference. This study presents a new theoretical basis to determine the bottom frame structure's seismic working law and update the design code. Meanwhile, this study opens up the application of seismic strain data in structural analysis. [ABSTRACT FROM AUTHOR]

In this paper, a finite element model (FEM) is developed based on a set of circular steel tube reinforced concrete (CTRC) columns with axial compression and eccentric compression tests. The stressing state characteristics of the FEM are modeled in the form of characteristic pairs (mode-characteristic parameters) based on the structural stressing state theory and the proposed correlation modeling method. The slope increasing criterion is applied to the correlation characteristic parameter curve to obtain the characteristic point Q where the CTRC stressing state undergoes a qualitative change, and the characteristic point Q is defined as the new failure load point of the CTRC column. By selecting the element strain energy density at different locations of the FEM for correlation stressing state modeling and dividing the correlation stressing state sub-modes (concrete, steel tube, vertical reinforcement, and stirrup reinforcement), the structural stressing state theory and the rationality of the proposed correlation stressing state modeling method are verified. In addition, the certainty and reasonableness of the failure load points of the CTRC columns are revealed and verified. [ABSTRACT FROM AUTHOR]

This paper reveals the failure characteristic points of the spiral reinforced column during the damage process by modeling and analyzing the stressing state of the column with the test and finite element output data. At the same time, the structural stressing state theory and the correlation modeling analysis method's applicability to spiral reinforced concrete columns are verified. First, a finite element model was established based on the literature's spiral reinforced concrete column tests. Then, correlation modeling was performed on the test strain data to obtain correlation characteristic pairs (mode-characteristic parameters), and stressing state modeling was performed on the internal energy and element strain energy data from the finite element model to obtain stressing state characteristic pairs. The slope increment criterion is applied to the obtained stressing state characteristic parameter curves to reveal the characteristic point Q, defined as the failure starting point. The reasonableness of the failure starting point is further verified by observing the cloud diagram of the finite element model in the vicinity of the characteristic point Q. In general, the correlation modeling method proposed in this paper can provide a new reference for structural stressing state analysis. In addition, the failure starting point of spiral reinforced concrete columns revealed in this paper can be used as a design reference. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "The Stressing State Features of a Bottom Frame Structure Revealed from the Shaking Table Strain Data" by Zhang et al. The correction addresses mistakes in Figures 1 and 2, as well as Table 3, which were published incorrectly due to the authors' negligence. The corrected figures and table are provided in the document. The authors state that these mistakes do not affect the scientific conclusions of the article. The original publication has been updated accordingly. [Extracted from the article]

The stability analysis and controller design problems for the fractional-order (FO) direct-drive permanent magnet synchronous generator (FOD-PMSG) wind turbine with parameter uncertainties and external disturbance are addressed. Takagi–Sugeno (T-S) model is used to approximate nonlinearities, and the parallel distributed compensation (PDC) technique is employed to construct the fuzzy state feedback controller. In order to suppress the external disturbance more effectively, the global Mittag-Leffler stability definition satisfying the H∞ performance index is proposed for the first time. Using the FO Lyapunov direct method, applying the Cauchy matrix inequality (CMI), and combining with the Schur complement lemma, the sufficient conditions of Mittag-Leffler stability meeting the H∞ performance index are given in the form of linear matrix inequalities (LMIs). Simulation results clearly show that the proposed control scheme can make the system get rid of the chaotic state quickly and have strong robustness under parameter uncertainties and external disturbance varying randomly. [ABSTRACT FROM AUTHOR]

In this paper, by inserting the logarithm cost function of the normalized subband adaptive filter algorithm with the step-size scaler (SSS-NSAF) into the sigmoid function structure, the proposed sigmoid-function-based SSS-NSAF algorithm yields improved robustness against impulsive interferences and lower steady-state error. In order to identify sparse impulse response further, a series of sparsity-aware algorithms, including the sigmoid L0 norm constraint SSS-NSAF (SL0-SSS-NSAF), sigmoid step-size scaler improved proportionate NSAF (S-SSS-IPNSAF), and sigmoid L0 norm constraint step-size scaler improved proportionate NSAF (SL0-SSS-IPNSAF), is derived by inserting the logarithm cost function into the sigmoid function structure as well as the L0 norm of the weight coefficient vector to act as a new cost function. Since the use of the fix step size in the proposed SL0-SSS-IPNSAF algorithm, it needs to make a trade-off between fast convergence rate and low steady-state error. Thus, the convex combination version of the SL0-SSS-IPNSAF (CSL0-SSS-IPNSAF) algorithm is proposed. Simulations in acoustic echo cancellation (AEC) scenario have justified the improved performance of these proposed algorithms in impulsive interference environments and even in the impulsive interference-free condition. [ABSTRACT FROM AUTHOR]

Cancers of the digestive system are malignant diseases. Our study focused on colon cancer, esophageal cancer (ESCC), rectal cancer, gastric cancer (GC), and rectosigmoid junction cancer to identify possible biomarkers for these diseases. The transcriptome data were downloaded from the TCGA database (The Cancer Genome Atlas Program), and a network was constructed using the WGCNA algorithm. Two significant modules were found, and coexpression networks were constructed. CytoHubba was used to identify hub genes of the two networks. GO analysis suggested that the network genes were involved in metabolic processes, biological regulation, and membrane and protein binding. KEGG analysis indicated that the significant pathways were the calcium signaling pathway, fatty acid biosynthesis, and pathways in cancer and insulin resistance. Some of the most significant hub genes were hsa-let-7b-3p , hsa-miR-378a-5p , hsa-miR-26a-5p , hsa-miR-382-5p , and hsa-miR-29b-2-5p and SECISBP2 L , NCOA1 , HERC1 , HIPK3 , and MBNL1 , respectively. These genes were predicted to be associated with the tumor prognostic reference for this patient population. [ABSTRACT FROM AUTHOR]

Background A novel coronavirus (CoV), severe acute respiratory syndrome (SARS)–CoV-2, has infected >75 000 individuals and spread to >20 countries. It is still unclear how fast the virus evolved and how it interacts with other microorganisms in the lung. Methods We have conducted metatranscriptome sequencing for bronchoalveolar lavage fluid samples from 8 patients with SARS–CoV-2, and also analyzed data from 25 patients with community-acquired pneumonia (CAP), and 20 healthy controls for comparison. Results The median number of intrahost variants was 1–4 in SARS–CoV-2–infected patients, ranged from 0 to 51 in different samples. The distribution of variants on genes was similar to those observed in the population data. However, very few intrahost variants were observed in the population as polymorphisms, implying either a bottleneck or purifying selection involved in the transmission of the virus, or a consequence of the limited diversity represented in the current polymorphism data. Although current evidence did not support the transmission of intrahost variants in a possible person-to-person spread, the risk should not be overlooked. Microbiotas in SARS–CoV-2–infected patients were similar to those in CAP, either dominated by the pathogens or with elevated levels of oral and upper respiratory commensal bacteria. Conclusion SARS–CoV-2 evolves in vivo after infection, which may affect its virulence, infectivity, and transmissibility. Although how the intrahost variant spreads in the population is still elusive, it is necessary to strengthen the surveillance of the viral evolution in the population and associated clinical changes. [ABSTRACT FROM AUTHOR]

Motivation Methylation and transcription factors (TFs) are part of the mechanisms regulating gene expression. However, the numerous mechanisms regulating the interactions between methylation and TFs remain unknown. We employ machine-learning techniques to discover the characteristics of TFs that bind to methylation sites. Results The classical machine-learning analysis process focuses on improving the performance of the analysis method. Conversely, we focus on the functional properties of the TF sequences. We obtain the principal properties of TFs, namely, the basic polar and hydrophobic Ile amino acids affecting the interaction between TFs and methylated DNA. The recall of the positive instances is 0.878 when their basic polar value is >0.1743. Both basic polar and hydrophobic Ile amino acids distinguish 74% of TFs bound to methylation sites. Therefore, we infer that basic polar amino acids affect the interactions of TFs with methylation sites. Based on our results, the role of the hydrophobic Ile residue is consistent with that described in previous studies, and the basic polar amino acids may also be a key factor modulating the interactions between TFs and methylation. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The completion of the rice genome sequence paved the way for rice functional genomics research. Additionally, the functional characterization of transcription factors is currently a popular and crucial objective among researchers. Transcription factors are one of the groups of proteins that bind to either enhancer or promoter regions of genes to regulate expression. On the basis of several typical examples of transcription factor analyses, we herein summarize selected research strategies and methods and introduce their advantages and disadvantages. This review may provide some theoretical and technical guidelines for future investigations of transcription factors, which may be helpful to develop new rice varieties with ideal traits. [ABSTRACT FROM AUTHOR]

In this paper, two arctangent-based normalized subband adaptive filter (Arc-NSAF) algorithms are proposed, which are derived from two different forms of arctangent cost function and their difference is the order of the arctangent computation and the summation operation of the normalized subband error signal. Benefiting from the excellent property of the arctangent function for suppressing impulsive interferences, the proposed Arc-NSAF algorithms not only possess good robustness against impulsive interferences, but also obtain faster convergence rate for the colored input signals. To further improve the convergence performance of the Arc-NSAFs when identifying sparse system, the proportionate versions of the Arc-NSAF algorithms are also proposed. Simulation results have demonstrated the superiority of the proposed algorithms in impulsive interferences environments as compared to their respective competitors. [ABSTRACT FROM AUTHOR]

A correction for the article "Genomic Diversity of Severe Acute Respiratory Syndrome–Coronavirus 2 in Patients With Coronavirus Disease 2019" is presented, which is published in the January 2020 issue of the periodical.

Abstract\nHIGHLIGHTSThe high specific strength and stiffness of carbon fiber-reinforced polymer (CFRP) stiffened plates make them popular in aerospace and other fields. Nevertheless, CFRP stiffened plates have unique characteristics and complicated and diversified failure patterns, so it is impossible to determine its failure law with a uniform failure criterion accurately. Its load-carrying capacity has always been calculated on the conservative side of empirical estimation. This work uses the stressing state theory to investigate the stressing state evolution of composite stiffened plates under axial loading. It conducts three CFRP stiffened plates of the same configuration from a thermodynamic perspective. By equating stiffened plates to thermodynamic systems, the measured strain data are modeled as state variables, and renormalization and clustering algorithms are applied to determine the phase transition loads of the structure, while the characteristic points before and after normalization are verified for their reasonableness and stability. Accordingly, this work reveals the failure laws of CFRP stiffened plates by applying a thermodynamic-based method. It characterizes the structural failure features by defining catastrophe points throughout the failure process, which provides a new reference for the failure analysis and strength design of CFRP stiffened plates.Three full-scale CFRP stiffened plates of the same configuration were tested by axial loading.A network-free renormalization was applied to construct modes and characteristic parameters of CFRP stiffened plates.A clustering algorithm was applied to reveal the phase transition loads of CFRP stiffened plates.The stability and accuracy of the phase transition loads of CFRP stiffened plates are verified. [ABSTRACT FROM AUTHOR]

The lysin motif (LysM) family comprise a number of defense proteins that play important roles in plant immunity. The LysM family includes LysM-containing receptor-like proteins (LYP) and LysM-containing receptor-like kinase (LYK). LysM generally recognizes the chitin and peptidoglycan derived from bacteria and fungi. Approximately 4000 proteins with the lysin motif (Pfam PF01476) are found in prokaryotes and eukaryotes. Our study identified 57 LysM genes and 60 LysM proteins in wheat and renamed these genes and proteins based on chromosome distribution. According to the phylogenetic and gene structure of intron–exon distribution analysis, the 60 LysM proteins were classified into seven groups. Gene duplication events had occurred among the LysM family members during the evolution process, resulting in an increase in the LysM gene family. Synteny analysis suggested the characteristics of evolution of the LysM family in wheat and other species. Systematic analysis of these species provided a foundation of LysM genes in crop defense. A comprehensive analysis of the expression and cis-elements of LysM gene family members suggested that they play an essential role in defending against plant pathogens. The present study provides an overview of the LysM family in the wheat genome as well as information on systematic, phylogenetic, gene duplication, and intron–exon distribution analyses that will be helpful for future functional analysis of this important protein family, especially in Gramineae species. [ABSTRACT FROM AUTHOR]

AlphaMissense identifies 23 million human missense variants as likely pathogenic, but only 0.1% have been clinically classified. To experimentally validate these predictions, chemical mutagenesis presents a rapid, cost-effective method to produce billions of mutations in model organisms. However, the prohibitive costs and limitations in the throughput of whole-genome sequencing (WGS) technologies, crucial for variant identification, constrain its widespread application. Here, we introduce a Tn5 transposase-assisted tagmentation technique for conducting WGS in Caenorhabditis elegans , Escherichia coli , Saccharomyces cerevisiae , and Chlamydomonas reinhardtii. This method, demands merely 20 min of hands-on time for a single-worm or single-cell clones and incurs a cost below 10 US dollars. It effectively pinpoints causal mutations in mutants defective in cilia or neurotransmitter secretion and in mutants synthetically sterile with a variant analogous to the B-Raf Proto-oncogene, Serine/Threonine Kinase (BRAF) V600E mutation. Integrated with chemical mutagenesis, our approach can generate and identify missense variants economically and efficiently, facilitating experimental investigations of missense variants in diverse species. [ABSTRACT FROM AUTHOR]

Asymmetric cell divisions (ACDs) generate two daughter cells with identical genetic information but distinct cell fates through epigenetic mechanisms. However, the process of partitioning different epigenetic information into daughter cells remains unclear. Here, we demonstrate that the nucleosome remodeling and deacetylase (NuRD) complex is asymmetrically segregated into the surviving daughter cell rather than the apoptotic one during ACDs in Caenorhabditis elegans . The absence of NuRD triggers apoptosis via the EGL-1-CED-9-CED-4-CED-3 pathway, while an ectopic gain of NuRD enables apoptotic daughter cells to survive. We identify the vacuolar H + -adenosine triphosphatase (V-ATPase) complex as a crucial regulator of NuRD's asymmetric segregation. V-ATPase interacts with NuRD and is asymmetrically segregated into the surviving daughter cell. Inhibition of V-ATPase disrupts cytosolic pH asymmetry and NuRD asymmetry. We suggest that asymmetric segregation of V-ATPase may cause distinct acidification levels in the two daughter cells, enabling asymmetric epigenetic inheritance that specifies their respective life-versus-death fates., Competing Interests: ZX, YC, ZZ, ZS, ZG, ZZ, LX, ZD, GO, WL No competing interests declared, (© 2023, Xie et al.)

The nucleosome remodeling and deacetylase (NuRD) complex is essential for gene expression and cell fate determination, and missense mutations of NuRD caused neurodevelopmental diseases. However, the molecular pathogenesis of clinic NuRD variants is unknown. Here, we introduced a clinic CHD3 (L915F) variant into Caenorhabditis elegans homologue LET-418, impairing germline and vulva development and ultimately causing animal sterility. Our ATAC-seq and RNA-seq analyses revealed that this variant generated an abnormal open chromatin structure and disrupted the expression of developmental genes. Through genetic suppressor screens, we uncovered that intragenic mutations, likely renovating NuRD activity, restored animal viability. We also found that intergenic mutations in nucleosome remodeling factor NURF that counteracts NuRD rescued abnormal chromatin structure, gene expression, and animal sterility. We propose that two antagonistic chromatin-remodeling factors coordinate to establish the proper chromatin status and transcriptome and that inhibiting NURF may provide insights for treatment of NuRD mutation-related diseases.

Rationale: Alteration of human respiratory microbiota had been observed in coronavirus disease (COVID-19). How the microbiota is associated with the prognosis in COVID-19 is unclear. Objectives: To characterize the feature and dynamics of the respiratory microbiota and its associations with clinical features in patients with COVID-19. Methods: We conducted metatranscriptome sequencing on 588 longitudinal oropharyngeal swab specimens collected from 192 patients with COVID-19 (including 39 deceased patients) and 95 healthy controls from the same geographic area. Meanwhile, the concentration of 27 cytokines and chemokines in plasma was measured for patients with COVID-19. Measurements and Main Results: The upper respiratory tract (URT) microbiota in patients with COVID-19 differed from that in healthy controls, whereas deceased patients possessed a more distinct microbiota, both on admission and before discharge/death. The alteration of URT microbiota showed a significant correlation with the concentration of proinflammatory cytokines and mortality. Specifically, Streptococcus -dominated microbiota was enriched in recovered patients, and showed high temporal stability and resistance against pathogens. In contrast, the microbiota in deceased patients was more susceptible to secondary infections and became more deviated from the norm after admission. Moreover, the abundance of S. parasanguinis on admission was significantly correlated with prognosis in nonsevere patients (lower vs. higher abundance, odds ratio, 7.80; 95% CI, 1.70-42.05). Conclusions: URT microbiota dysbiosis is a remarkable manifestation of COVID-19; its association with mortality suggests it may reflect the interplay between pathogens, symbionts, and the host immune status. Whether URT microbiota could be used as a biomarker for diagnosis and prognosis of respiratory diseases merits further investigation.

The lysin motif (LysM) family comprise a number of defense proteins that play important roles in plant immunity. The LysM family includes LysM-containing receptor-like proteins (LYP) and LysM-containing receptor-like kinase (LYK). LysM generally recognizes the chitin and peptidoglycan derived from bacteria and fungi. Approximately 4000 proteins with the lysin motif (Pfam PF01476) are found in prokaryotes and eukaryotes. Our study identified 57 LysM genes and 60 LysM proteins in wheat and renamed these genes and proteins based on chromosome distribution. According to the phylogenetic and gene structure of intron-exon distribution analysis, the 60 LysM proteins were classified into seven groups. Gene duplication events had occurred among the LysM family members during the evolution process, resulting in an increase in the LysM gene family. Synteny analysis suggested the characteristics of evolution of the LysM family in wheat and other species. Systematic analysis of these species provided a foundation of LysM genes in crop defense. A comprehensive analysis of the expression and cis-elements of LysM gene family members suggested that they play an essential role in defending against plant pathogens. The present study provides an overview of the LysM family in the wheat genome as well as information on systematic, phylogenetic, gene duplication, and intron-exon distribution analyses that will be helpful for future functional analysis of this important protein family, especially in Gramineae species.

Rice and maize are the principal food crop species worldwide. The mechanism of gene regulation for the yield of rice and maize is still the research focus at present. Seed size, weight and shape are important traits of crop yield in rice and maize. Most members of three gene families, APETALA2/ethylene response factor, auxin response factors and MADS, were identified to be involved in yield traits in rice and maize. Analysis of molecular regulation mechanisms related to yield traits provides theoretical support for the improvement of crop yield. Genetic regulatory network analysis can provide new insights into gene families with the improvement of sequencing technology. Here, we analyzed the evolutionary relationships and the genetic regulatory network for the gene family members to predicted genes that may be involved in yield-related traits in rice and maize. The results may provide some theoretical and application guidelines for future investigations of molecular biology, which may be helpful for developing new rice and maize varieties with high yield traits., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Chen, Shen, Xu, Zhao and Zou.)

In response to the current coronavirus disease 2019 (COVID-19) pandemic, it is crucial to understand the origin, transmission, and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which relies on close surveillance of genomic diversity in clinical samples. Although the mutation at the population level had been extensively investigated, how the mutations evolve at the individual level is largely unknown. Eighteen time-series fecal samples were collected from nine patients with COVID-19 during the convalescent phase. The nucleic acids of SARS-CoV-2 were enriched by the hybrid capture method. First, we demonstrated the outstanding performance of the hybrid capture method in detecting intra-host variants. We identified 229 intra-host variants at 182 sites in 18 fecal samples. Among them, nineteen variants presented frequency changes > 0.3 within 1-5 days, reflecting highly dynamic intra-host viral populations. Moreover, the evolution of the viral genome demonstrated that the virus was probably viable in the gastrointestinal tract during the convalescent period. Meanwhile, we also found that the same mutation showed a distinct pattern of frequency changes in different individuals, indicating a strong random drift. In summary, dramatic changes of the SARS-CoV-2 genome were detected in fecal samples during the convalescent period; whether the viral load in feces is sufficient to establish an infection warranted further investigation., (Copyright © 2020 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.)