Consistent and Specific Multi-View Functional Brain Networks Fusion for Autism Spectrum Disorder Diagnosis

Functional brain networks (FBN) based on resting-state functional magnetic resonance imaging (rs-fMRI) have become an important tool for exploring underlying organization patterns in the brain, which can provide an objective basis for brain disorders such as autistic spectrum disorder (ASD). Due to its importance, researchers have proposed a number of FBN estimation methods. However, most existing methods only model a type of functional connection relationship between brain regions-of-interest (ROIs), such as partial correlation or full correlation, which is difficult to fully capture the subtle connections among ROIs since these connections are extremely complex. Motivated by the multi-view learning, in this study we propose a novel Consistent and Specific Multi-view FBNs Fusion (CSMF) approach. Concretely, we first construct multi-view FBNs (i.e., multiple types of FBNs modelling various relationships among ROIs), and then these FBNs are decomposed into a consistent representation matrix and their own specific matrices which capture their common and unique information, respectively. Lastly, to obtain a better brain representation, it is fusing the consistent and specific representation matrices in the latent representation spaces of FBNs, but not directly fusing the original FBNs. This potentially makes it more easily to find the comprehensively brain connections. The experimental results of ASD identification on the ABIDE datasets validate the effectiveness of our proposed method compared to several state-of-the-art methods. Our proposed CSMF method achieved 72.8% and 76.67% classification performance on the ABIDE dataset.

Microscopic damage evolution of anisotropic rocks under indirect tensile conditions: Insights from acoustic emission and digital image correlation techniques

The anisotropy induced by rock bedding structures is usually manifested in the mechanical behaviors and failure modes of rocks.Brazilian tests are conducted for seven groups of shale specimens featuring different bedding angles. Acoustic emission (AE) and digital image correlation (DIC) technologies are used to monitor the in-situ failure of the specimens. Furthermore, the crack morphology of damaged samples is observed through scanning electron microscopy (SEM). Results reveal the structural dependence on the tensile mechanical behavior of shales. The shale disk exhibits compression in the early stage of the experiment with varying locations and durations. The location of the compression area moves downward and gradually disappears when the bedding angle increases. The macroscopic failure is well characterized by AE event location results, and the dominant frequency distribution is related to the bedding angle. The b-value is found to be stress-dependent.The crack turning angle between layers and the number of cracks crossing the bedding both increase with the bedding angle, indicating competition between crack propagations. SEM results revealed that the failure modes of the samples can be classified into three types:tensile failure along beddings with shear failure of the matrix, ladder shear failure along beddings with tensile failure of the matrix, and shear failure along multiple beddings with tensile failure of the matrix.

A Novel Method for Solving Nonlinear Schrödinger Equation with a Potential by Deep Learning

The improved physical information neural network algorithm has been proven to be used to study integrable systems. In this paper, the improved physical information neural network algorithm is used to study the defocusing nonlinear Schrödinger (NLS) equation with time-varying potential, and the rogue wave solution of the equation is obtained. At the same time, the influence of the number of network layers, neurons and the number of sampling points on the network performance is studied. Experiments show that the number of hidden layers and the number of neurons in each hidden layer affect the relative L2-norm error. With fixed configuration points, the relative norm error does not decrease with the increase in the number of boundary data points, which indicates that in this case, the number of boundary data points has no obvious influence on the error. Through the experiment, the rogue wave solution of the defocusing NLS equation is successfully captured by IPINN method for the first time. The experimental results of this paper are also compared with the results obtained by the physical information neural network method and show that the improved algorithm has higher accuracy. The results of this paper will be contributed to the generalization of deep learning algorithms for solving defocusing NLS equations with time-varying potential.

Characteristics of coseismic water level changes at Tangshan well for the Wenchuan MS_8.0 earthquake and its larger aftershocks

Coseismic water level changes which may have been induced by the Wenchuan Ms8.0 earthquake and its 15 larger aftershocks （Ms〉5.4） have been observed at Tangshan well. We analyze the correlation between coseismic parameters （maximum amplitude, duration, coseismic step and the time when the coseismic reach its maximum amplitude） and earthquake parameters （magnitude, well-epicenter distance and depth）, and then compare the time when the coseismic oscillation reaches its maximum amplitude with the seismogram from Douhe seismic station which is about 16.3 km away from Tangshan well. The analysis indicates that magnitude is the main factor influencing the induced coseismic water level changes, and that the well-epicenter distance and depth have less influence. Ms magnitude has the strongest correlation with the coseismic water level changes comparing to Mw and ML magnitudes. There exists strong correlation between the maximum amplitude, step size and the oscillation duration. The water level oscillation and step are both caused by dynamic strain sourcing from seismic waves. Most of the times when the oscillations reach their maximum amplitudes are between S and Rayleigh waves. The coseismic water level changes are due to the co-effect of seismic waves and hydro-geological environments.

The expression and function of miR-376a-3p/DLX axis in gastric cancer cells

Gastric cancer(GC)was referred to a malignant tumor of the digestive tract originating from the epithelium of gastric mucosa.Transcription factor DLX5 was verified as an oncogene in various types of tumors,while miR-376a-3p was speculated as a tumor suppressor.Based on the bioinformatics database,we hypothesized that miR-376a participated in the regulation of GC development by targeting DLX5.Compared with adjacent tissue,a significant increase of DLX5 expression was determined in GC tissues,but the expression level is significantly reduced in miR-376a.Similar expression signature of DLX5 and miR-376a was also determined between 4 GC cells(HGC,SGC,MGC,and AGS cell lines)and GES cell line.The level of DLX5 was notably reduced in HGC and MGC cell lines after miR-376a-3p overexpression,and increased after miR-376a-3p inhibition.Then,the inhibition role of miR-376a-3p on DLX5 was further proved by dualluciferase reporter assay.Gain-of-function experiments showed that upregulation of miR-376a-3p in GC cells could inhibit the ability of epithelial-mesenchymal transition,proliferation,and invasion,and enhance the GC cell apoptosis level.However,these roles of miR-376a-3p could be abolished by DLX5 overexpression.This study confirmed that reduction of miR-376a-3p expression level in GC cells would lead to the increase in cell growth and invasion,indicating that upregulation of miR-376a-3p might have a potential therapeutic role on GC.

Liquid metal compartmented by polyphenol-mediated nanointerfaces enables high-performance thermal management on electronic devices

The exponentially increasing heat generation in electronic devices,induced by high power density and miniaturization,has become a dominant issue that affects carbon footprint,cost,performance,reliability,and lifespan.Liquid metals(LMs)with high thermal conductivity are promising candidates for effective thermal management yet are facing pump-out and surface-spreading issues.Confinement in the form of metallic particles can address these problems,but apparent alloying processes elevate the LM melting point,leading to severely deteriorated stability.Here,we propose a facile and sustainable approach to address these challenges by using a biogenic supramolecular network as an effective diffusion barrier at copper particle-LM(EGaIn/Cu@TA)interfaces to achieve superior thermal conduction.The supramolecular network promotes LM stability by reducing unfavorable alloying and fluidity transition.The EGaIn/Cu@TA exhibits a record-high metallic-mediated thermal conductivity(66.1 W m^(-1) K^(-1))and fluidic stability.Moreover,mechanistic studies suggest the enhanced heat flow path after the incorporation of copper particles,generating heat dissipation suitable for computer central processing units,exceeding that of commercial silicone.Our results highlight the prospects of renewable macromolecules isolated from biomass for the rational design of nanointerfaces based on metallic particles and LM,paving a new and sustainable avenue for high-performance thermal management.

Developing an efficient CRISPR-dCas9-TVderived transcriptional activation system to create three novel cotton germplasm materials

Dear Editor,With the development of CRISPR-Cas technology,an RNAguided CRISPR activation system has been developed in plants,in which a dead Cas9(dCas9)nuclease is fused to transcriptional activators to regulate the transcription of endogenous genes(Li et al.,2017;Liu et al.,2017;Manghwar et al.,2020;Ming et al.,2020;Pan et al.,2021).Precise upregulation of gene transcription is emerging as a promising approach for functional genomics research,molecular breeding,and germplasm innovation.However,there have been no reports on the use of the CRISPR-dCas9 transcriptional activation system in cotton.

Near infrared light-induced dynamic modulation of enzymatic activity through polyphenol-functionalized liquid metal nanodroplets

Dynamic manipulation of enzymatic activity is a challenging task for applications in chemical and pharmaceutical industries due to the difficult modification and variable conformation of various enzymes.Here, we report a new strategy for reversible dynamic modulation of enzymatic activity by near-infrared light-induced photothermal conversion based on polyphenol-functionalized liquid metal nanodroplets(LM). The metal-phenolic nanocoating not only provides colloidal stability of LM nanodroplets but also generates nanointerfaces for the assembly of various enzymes on the LM nanodroplets. Upon near infrared(NIR) irradiation, the localized microenvironmental heating through photothermal effect of the LM nanodroplets allows tailoring the enzymatic activity without affecting the bulk temperature. A library of functional enzymes, including proteinase K, glucoamylase, glucose oxidase, and Bst DNA polymerase, is integrated to perform a reversible control and enhanced activities even after five times of cycles, demonstrating great potential in bacterial fermentation, bacteriostasis, and target gene amplification.

A sustainable thermochemical conversion of animal biomass to N-heterocycles

The production of high-valued organonitrogen chemicals,especially N-heterocycles,requires artificial N_(2)fixation accompanied by the consumption of fossil resources.To avoid the use of these energy-and resource-intensive processes,we develop a sustainable strategy to convert nitrogen-rich animal biomass into N-heterocycles through a thermochemical conversion process(TCP)under atmospheric pressure.A high percentage of N-heterocycles(87.51%)were obtained after the TCP of bovine skin due to the abundance of nitrogen-containing amino acids(e.g.,glycine,proline,and L-hydroxyproline).Animal biomass with more diverse amino acid composition(e.g.,muscles)yielded higher concentrations of amines/amides and nitriles after TCP.In addition,by introducing catalysts(KOH for pyrrole and Al_(2)O_(3)for cyclo-Gly-Pro)to TCP,the production quantities of pyrrole and cyclo-Gly-Pro increased to 30.79 mg g^(-1)and 38.88 mg g^(-1),respectively.This approach can be used to convert the significant animal biomass waste generated annually from animal culls into valued organonitrogen chemicals while circumventing NH3-dependent and petro-chemical-dependent synthesis routes.

Transcriptome Profiling Reveals Auxin and Cytokinin Regulating Somatic Embryogenesis in Different Sister Lines of Cotton Cultivar CCRI24

To get a broader view on the molecular mechanisms underlying somatic embryogenesis （SE） in cotton （Gossypium hirsutum L.）, global analysis of cotton transcriptome dynamics during SE in different sister lines was performed using RNA-Seq. A total of 204 349 unigenes were detected by de novo assembly of the 214 977 462 Illumina reads. The quantitative reverse transcription-polymerase chain reaction （qRT-PCR） measurements were positively correlated with the RNA-Seq results for almost all the tested genes （R2 -- 0.841, correlation was significant at the 0.01 level）. Different phytohormone （auxin and cytokinin） concentration ratios in medium and the endogenous content changes of these two phytohormones at two stages in different sister lines suggested the roles of auxin and cytokinin during cotton SE. On the basis of global gene regulation of phytohormone-related genes, numerous genes from all the differentially expressed transcripts were involved in auxin and cytokinin biosynthesis and signal transduction pathways. Analyses of differentially expressed genes that were involved in these pathways revealed the substantial changes in gene type and abundance between two sister lines. Isolation, cloning and silencing/ overexpressing the genes that revealed remarkable up- or down-expression during cotton SE were important. Furthermore, auxin and cytokinin play a primary role in SE, but potential cross-talk with each other or other factors remains unclear.

Prediction of VIGS efficiency by the Sfold program and its reliability analysis in Gossypium hirsutum

Genetic transformation in some plant species, including cotton （Gossypium hirsutum）, is hampered by laborious and time-consuming processes and often unachievable. Virus-induced gene silencing （VIGS） by double-stranded RNAs can serve as a reverse-genetics tool to determine gene function. However, knockdown levels vary greatly when using a tobacco rattle virus-based vector that carries different cDNA fragments of a gene. How to choose the optional target fragment for high interference efficiency is very challenging. Addressing this challenge requires increasing the efficacy of small interference RNA （siRNA） in target fragment. Here, we describe a method to assess VIGS efficiency by comparing the following parameters of siRNA in target sequence： the disruptionenergy of the target （△Gdisruption）, the differential stability of siRNA duplex ends （DSSE）, and the internal stability at positions 9-14 of the siRNA antisense strand （AIS）, which are calculated by Sfold program （http：//sfold.wadsworth. org）. We find that the siRNAs with low mGdisruption, high DSSE and high AIS have high activity and easily result in high VIGS efficiency by experimentally testing the actual knockdown levels of the four target genes, GhPDS, GhCLA1, GhAOS1, and GhCXE1 via choosing different target sequences for each gene. Therefore, the Sfold pro- gram can be used to analyze target sequences when car- rying out VIGS design to increase gene-silencing effects in plants.

Overexpressed BRH1, a RING finger gene, alters rosette leaf shape in Arabidopsis thaliana

Leaves are the most important plant parts for photosynthesis and respiration. Many genes are involved in determining leaf shape;however, little is known about the effects of brassinosteroid (BR) signaling-pathway genes on the development of leaf shape. Here, the brassinosteroid-responsive RING-H2 (BRH1) gene, which is suppressed by 24-epi-brassinolide treatment, was isolated from Arabidopsis thaliana. The amino acid sequence contained a highly conserved RING finger domain. In a phylogenetic analysis,BRH1 clustered closely with GLYMA11G02470.1. The leaves of brh1 mutant plants were not much different to those of the wild-type, while transgenic plants with high BRH1 expression levels had rounder rosette leaves. Mutants of the BR synthesis pathway also had a similar round leaf phenotype, and greater BRH1 expression levels. Moreover, the related marker genes KNAT1,AtHB13 and ROT4, which are known to control leaf shape, altered transcriptional levels in both transgenic BRH1 and BR-synthesis mutant lines. Thus, BRH1 may be involved in the BR signaling pathway and regulate the growth and development of rosette leaves. Research on BRH1 may prove valuable for understanding the regulatory mechanism of leaf shape and improving the leaf shapes of ornamental plants.