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Introduction: The aim of this study was to develop a prognostic model for chronic lymphocytic leukemia (CLL). Methods: GEO2R was used to retrieve the gene expression data of CLL and normal B cells from the Gene Expression Omnibus (GEO; GSE22529 and GSE50006 datasets) database. Practical Extraction and Report Language was used to extract the gene expression and overall survival (OS) data of CLL patients from the Chronic Lymphocytic Leukemia – ES (CLLE-ES) project in the International Cancer Genome Consortium (ICGC) database. Cox regression with Lasso was used to create and validate a prognostic model for CLL. Results: A total of 267 genes exhibited differential expression between CLL and normal B cells. Cox univariate analysis identified 14 DEGs that correlated with OS. Lasso multivariate evaluation demonstrated that AKAP12 and IGFBP4 are independent prognostic factors for CLL. Kaplan-Meier survival analysis revealed a significant association between the estimated risk score and survival. The area under the receiver operating characteristic curve was calculated to be 0.97, indicating high predictive accuracy. In addition, high AKAP12 and IGFBP4 risk scores were associated with the high incidence of trisomy 12q. Conclusion: Taken together, AKAP12 and IGFBP4 are independent prognostic factors for CLL. [ABSTRACT FROM AUTHOR]

• Specific probiotics improve renal function in kidney transplantation. • Used safely in kidney transplantation. • A potential strategy for lowering the dosages of immunosuppressants. The majority of kidney recipients are a subset of chronic kidney disease. Our previous study demonstrated that the combination of Lactobacillus plantarum and Lactobacillus paracasei (Lm) had the highest clearance ability of uremic toxins and improved kidney function in a mouse model. This study aimed to evaluate Lm in improving graft function, effects on immunosuppressants, and safety in transplant recipients. We retrospectively reviewed 24 patients. Twelve of them take Lm regularly; we compared the creatinine measurements and estimated glomerular filtration rate 3 months before and after Lm using a 2-tailed Wilcoxon matched-pairs signed-rank test while also evaluating the drug level of immunosuppressants and infection events. Other 12 patients who do not have Lm for evaluation of laboratory calibration and compared the proportion of improving creatinine using Fisher's exact test. The creatinine decreased by 0.06 mg/dL (P =. 02), and the estimated glomerular filtration rate increased by 3.1 mL/min/1.73 m2 (P =. 03) after Lm supplementation. This pilot study revealed the association of higher incidence (odds ratio 13.3, 95% CI 1.64-77.2, P =. 01) of decreasing creatinine in transplant recipients using Lm. Furthermore, results showed a trend of higher trough levels of tacrolimus and sirolimus, which might provide a potential strategy for reducing the dosages of immunosuppressants. Our findings revealed an association between a higher incidence of decreasing creatinine in kidney transplant recipients using Lm, which may also provide a potential strategy for reducing the acquired dosages of immunosuppressants. [Display omitted] [ABSTRACT FROM AUTHOR]

• PTMA expression is significantly increased in CRC patients. • PTMA enhances LD accumulation in CRC cells. • PTMA-dependent LD production facilitates CRC chemoresistance. • PTMA promotes chemoresistance by regulating SREBP-1-mediated lipogenesis. • PTMA promotes the acetylation and activation of STAT3 to support LD biogenesis and chemoresistance. Colorectal cancer (CRC) affects millions of people worldwide. Chemoresistance seriously impairs the therapeutic effects. Lipid droplets (LDs) abnormally accumulate in CRC supported chemoresistance. Exploring the mechanism of LD-induced chemoresistance is extremely important for improving prognosis of CRC patients. The expression of PTMA was increased in both CRC tissues and cells, which was positively correlated with LD production. PTMA facilitated chemoresistance to gemcitabine by inducing LD production in CRC cells. PTMA enhanced LD biogenesis and chemoresistance to gemcitabine by promoting SREBP-1-mediated lipogenesis and STAT3 activation in CRC. [ABSTRACT FROM AUTHOR]

Nanosecond pulse output at megahertz level is wide interest because of its potential application in the experiment of cell function electric field regulation and accelerator electron gun injector. In this article, a pulse generator based on the combination of the Blumlein pulse forming line and the boost method is proposed. Different from the traditional Blumlein line, in this module, the RLC circuit is used to improve the pulse voltage amplitude and energy conversion efficiency. According to the different inductance values, the generator has two working modes: discontinuous and continuous with different output characteristics. RF-Si-mosfet is used as the main switch and used dual-switch timing logic control to adjust the output waveform parameters. It can obtain the output pulse frequency two times the switching frequency, effectively reducing the single switching loss. By constructing a prototype, the pulsewidth of 5 ns, maximum repetition of 10 MHz and 2.5-kW peak power is realized. In addition, a dc equivalent pulse method is proposed, which is suitable for the thermal simulation of switching at high frequency and gives the heat dissipation measures. The effectiveness is verified by simulation and experiment. [ABSTRACT FROM AUTHOR]

The acoustic imaging results in the diffuse field are seriously affected by reverberation. The acoustic source localization algorithms based on the free-field assumption will produce many artifacts in the reverberant environment. To achieve accurate acoustic source localization in a reverberant environment, a sound field morphological component analysis (SF-MCA) model and an enhanced alternating direction method of multipliers (ADMM) algorithm are proposed in this article. First, the solution of the inhomogeneous Helmholtz equation is analyzed to characterize the acoustic components. Second, Green’s function and plane-wave basis function serve as dictionaries for sparse representation of the acoustic signal in the frequency domain, and the corresponding decomposition coefficients are obtained by the enhanced ADMM algorithm. Finally, the accurate acoustic imaging results are realized in the reverberant chamber space with strong reverberation ($T_{20}=174.30\,\,\text {ms}$). Experiments demonstrate the validation of the proposed SF-MCA method. The acoustic imaging obtained by the proposed SF-MAC dereverberation model is far superior to the acoustic imaging that treats the reverberation as the general Gaussian noise. [ABSTRACT FROM AUTHOR]

This article proposes a variational Bayesian (VB) inference based on the nonsynchronous array measurement (NAM) (VB-NAM) method in order to obtain the fast and robust localization of low-frequency acoustic sources. To enlarge the aperture size compared with the prototype array, the NAM is performed to measure the acoustic pressures with low-frequency based on the forward power propagation model. The implementation of the NAM can be reformulated into a cross-spectral matrix (CSM) completion problem. Then, to solve the inverse problem of the NAM power propagation model, the VB inference based on the Student-t priors and Kullback–Leibler (KL) divergence optimization is proposed. The advantages of the proposed VB-NAM benefit from the optimization of matrix inversion and adaptive estimation of regularization parameters. The contribution of the adaptive parameter evaluation is to reduce the impact of multiple interferences (such as additive noise and the matrix completion error) in NAM. Finally, both simulations at 800 Hz and experimental results at 1000 Hz are presented to show the validation of the proposed VB-NAM method, even under the anisotropic Gaussian noise conditions. Algorithm performance and iteration process are analyzed to demonstrate the efficiency and robustness. [ABSTRACT FROM AUTHOR]

It is valuable to improve the resolution and speed of acoustic beamforming in real-time measurement, especially fault location, noise mapping, and so on. However, multiplication of the power transfer matrix takes much time in the iteration of the deconvolution algorithm. This article proposes a novel method based on the convolution approximation and GPU platform to obtain acoustic imaging with a high resolution quickly. First, the power propagation matrix is approximated by a symmetric Toeplitz block Toeplitz (STBT) matrix, which can transform the product of matrix and vector into the convolution of two smaller patterns. Three different convolution kernels are derived for the convolution operation, including 2-D variant convolution kernel, 2-D invariant convolution kernel, and 1-D separable invariant convolution kernel. Then, the regularization deconvolution algorithm with the convolution kernel is derived. Besides, the relation between approximation error, time cost, and setting parameters is discussed. The results show that the separable invariant convolution kernel can obtain the fastest imaging and relatively accurate localization, while the time consumption of the variant kernel is the highest. Simulations and experiments are operated on the CPU and GPU to make a comparison, which validates that our proposed deconvolution-GPU implementation can significantly improve the computation speed for the matrix on a large scale. [ABSTRACT FROM AUTHOR]

Our aim was to investigate the effect of artificial liver blood purification treatment on the survival of severe/critical patients with coronavirus disease 2019 (COVID‐19). A total of 101 severe and critical patients with coronavirus SARS‐CoV‐2 infection were enrolled in this open, case‐control, multicenter, prospective study. According to the patients' and their families' willingness, they were divided into two groups. One was named the treatment group, in which the patients received artificial liver therapy plus comprehensive treatment (n = 50), while the other was named the control group, in which the patients received only comprehensive treatment (n = 51). Clinical data and laboratory examinations, as well as the 28‐day mortality rate, were collected and analyzed. Baseline data comparisons on average age, sex, pre‐treatment morbidity, initial symptoms, vital signs, pneumonia severity index score, blood routine examination and biochemistry indices etc. showed no difference between the two groups. Cytokine storm was detected, with a significant increase of serum interleukin‐6 (IL‐6) level. The serum IL‐6 level decreased from 119.94 to 20.49 pg/mL in the treatment group and increased from 40.42 to 50.81 pg/mL in the control group (P <.05), indicating that artificial liver therapy significantly decreased serum IL‐6. The median duration of viral nucleic acid persistence was 19 days in the treatment group (ranging from 6 to 67 days) and 17 days in the control group (ranging from 3 to 68 days), no significant difference was observed (P =.36). As of 28‐day follow‐up,17 patients in the treatment group experienced a median weaning time of 24 days, while 11 patients in the control group experienced a median weaning time of 35 days, with no significant difference between the two groups (P =.33). The 28‐day mortality rates were 16% (8/50) in the treatment group and 50.98% (26/51) in the control group, with a significant difference (z = 3.70, P <.001). Cytokine storm is a key factor in the intensification of COVID‐19 pneumonia. The artificial liver therapy blocks the cytokine storm by clearing inflammatory mediators, thus preventing severe cases from progressing to critically ill stages and markedly reducing short‐term mortality. [ABSTRACT FROM AUTHOR]

In heavy rain situations, the clarity of both human vision and computer vision is significantly reduced. Rain removal GAN-based networks have been proposed as a means of resolving this problem. However, such methods have only a limited effectiveness in improving the object detection accuracy. Accordingly, this study commences by analyzing the object detection performance before and after rain removal, respectively. We propose an integrated framework for improving the object detection performance in heavy rain images based on the analysis results. The experimental results show that the proposed framework yields an improved IoU and reduces the error rate compared with existing methods. [ABSTRACT FROM AUTHOR]

The fan noise is the primary component of aero-engine noise. Duct acoustic modal identification is essential for analyzing the mechanism of fan noise generation and propagation. The acoustic modal in the duct can be identified by the measurement of the microphone array mounted on the duct wall. It is generally assumed in the conventional modal identification methods that the modal coefficients are independent of each other. However, the realistic duct acoustic modal coefficients exhibit significant statistical dependence. A Boltzmann machine(BM) model considering the statistical dependence between modal coefficients is proposed for recovering the modal coefficients in this paper. The modal coefficients are estimated using a block coordinate optimization method in a Bayesian framework. Moreover, the modal Boltzmann parameters can be learned iteratively by the BM. The effectiveness of the proposed method is verified by numerical simulations and experimental tests. It turns out that the modal coefficients can be accurately identified by the proposed method, and a more significant sparsity is shown by the results. In addition, the statistical dependence between the modal coefficients can be captured by the BM. • A Boltzmann machine modeling method that considers the statistical dependence between the modal coefficients is proposed. • The modal coefficients and the modal Boltzmann parameters can be estimated adaptively and iteratively. • The accuracy and robustness of the modal identification results are analyzed. • The proposed method is evaluated in Spinning Mode Synthesizer experiments. [ABSTRACT FROM AUTHOR]

The localization of cyclostationary sound sources is important for rotating machinery noise source identification and fault diagnosis. Cyclostationary sound sources are a special class of nonstationary sound sources, which exhibit periodic changes in statistics. Most of the conventional sound source identification methods are based on the stationary sound source assumption, which do not consider the cyclostationarity of the radiated sound field by rotating machinery. Thus, they are hard to localize the acoustic sources with different cyclic frequencies. In this paper, a novel technique of localizing the cyclostationary acoustic sources with different cyclic frequencies is proposed. First, the cyclostationary conventional beamforming (CSCBF) method is deviated. In CSCBF, the cyclic-cross-spectral matrix (CCSM) is defined considering all the cross cyclic spectral correlation (CSC) between different microphones in the array. The left steering vector and right steering vector are constructed to focus the CCSM on each scanning grid point at a given combination of cyclic frequency and spectral frequency. Then, the high resolution cyclostationary beamforming (HR-CSBF) is further developed to improve the spatial resolution of CSCBF. In HR-CSBF, two linear equations according to the property of CSC is established as the acoustic inverse problems. With the sparse distribution of the cyclostationary sources in the space as the prior knowledge, the iterated Bayesian focusing (IBF) is utilized to obtain a robust and sparse solution in HR-CSBF. Numerical simulations and experiments are conducted to validate the proposed methods. To explore the potential applications of the proposed methods, the localization of high pressure pump (HPP) and rolling bearing with outer-race failure are also used to evaluate the effectiveness of the proposed methods. It turns out that both CSCBF and HR-CSBF can localize the cyclostationary sources with different cyclic frequencies. Compared with CSCBF, HR-CSBF can achieve a higher spatial resolution in the obtained acoustic map. [ABSTRACT FROM AUTHOR]

Understanding the infiltration and solidification processes of liquid 5083Al alloy into Al2O3 three-dimensional reticulated porous ceramic (Al2O3(3D) RPC) is essential for optimizing the microstructure and properties of Al2O3(3D)/5083Al interpenetrating phase composites (IPCs) prepared by low-pressure infiltration process (LPIP). This study employs ProCAST software to simulate the infiltration and solidification processes of liquid 5083Al with pouring velocities (PV) of 0.4 m/s infiltrating into Al2O3(3D) RPC preforms with varying porosities at different pouring temperatures (PT) to prepare Al2O3(3D)/5083Al IPCs using LPIP. The results demonstrate that pore diameter of Al2O3(3D) RPC preforms and PT of liquid 5083Al significantly influence the of the infiltration. Solidification process analysis reveals that the Al2O3(3D) RPC preform with smaller pore diameters allows the lower pouring velocity of 5083Al to solidify faster compared to the preform with larger pore diameters. Al2O3(3D)/5083Al IPCs were prepared successfully from Al2O3(3D) RPC porosity of 15 PPI with liquid 5083Al at PV 0.4 m/s and PT 800 °C using LPIP, resulting in nearly fully dense composites, where both Al2O3(3D) RPCs and 5083Al interpenetrate throughout the microstructure. The infiltration and solidification defects were reduced under air pressure of 0.3 MPa (corresponding to PV of 0.4 m/s) during LPIP. Finite volume method simulations are in good agreement with experimental data, validating the suitability of the simplified model for Al2O3(3D) RPCs in the infiltration simulation. [ABSTRACT FROM AUTHOR]

Human norovirus (HuNoV) is the main cause of acute non-bacterial gastroenteritis worldwide. There is no vaccine currently available to prevent HuNoV infection. HuNoV is a highly mutated virus, and its genetic diversity and the lack of cross-protection between different genotypes hinder the broadly protective vaccine development. Among various genotypes, GI.1 is the prototype strain, and GII.4 currently predominates the prevalence of HuNoV. In this work, guided by the structural alignment of GI.1 and GII.4 HuNoV capsid proteins, several chimeric virus-like particles (VLPs) were designed to achieve cross-immunity against these two HuNoV genotypes. The neutralizing epitopes of HuNoV have been identified to be mainly located at the loop regions of VP1 protein exposed on the HuNoV surface. In this study, the exposed loops of GII.4 VP1 protein were grafted into the scaffold of GI.1 genotype to produce the chimeric VLPs. The designed chimeric VLPs were recombinantly expressed by the Hansenula polymorpha expression system developed by our laboratory. Mice were immunized with the chimeric VLPs plus aluminum adjuvant, and then the antibody responses were detected by using the enzyme-linked immunosorbent assay and the histo-blood group antigen-VLP interaction blocking assay. The experimental results show that two of the designed chimeric VLPs induced cross-reactive IgG and cross-blocking antibodies against both the parental GI.1 and GII.4 genotypes of HuNoV. The results also imply that the transplant site design is important to maintain the immunogenicity of foreign epitopes on the scaffold carrier. Our studies may provide a valuable strategy for the development of cross-reactive HuNoV vaccines. IMPORTANCE Human norovirus (HuNoV) is highly infectious and can result in severe illnesses in the elderly and children. So far, there is no effective antiviral drug to treat HuNoV infection, and thus, the development of HuNoV vaccines is urgent. However, NoV evolves rapidly, and currently, at least 10 genogroups with numerous genotypes have been found. The genetic diversity of NoV and the lack of cross-protection between different genotypes pose challenges to the development of broadly protective vaccines. In this study, guided by structural alignment between GI.1 and GII.4 HuNoV VP1 proteins, several chimeric-type virus-like particles (VLPs) were designed through surface-exposed loop grafting. Mouse immunization studies show that two of the designed chimeric VLPs induced cross-immunity against both GI.1 and GII.4 HuNoVs. To our knowledge, this is the first designed chimeric VLPs that can induce cross-immune activities across different genogroups of HuNoV, which provides valuable strategies for the development of cross-reactive HuNoV vaccines. [ABSTRACT FROM AUTHOR]

This study investigated the biological activity of essential oils (EOs) and their main components (caryophyllene and cuminol) against Tribolium castaneum larvae and Lasioderma serricorne adults. EOs were extracted from both flowers and leaves of Elsholtzia stauntoni. The results indicated that the EOs derived from both flowers and leaves, as well as their main components (caryophyllene and cuminol), exhibited contact activities with LD50 values of 35.11, 43.66, 15.44, and 26.05 µg/larva, respectively, against T. castaneum larvae. Moreover, they demonstrated obvious contact toxicities with LD50 values of 14.15, 11.18, 17.81, and 13.91 µg/adult, respectively, against L. serricorne adults. Additionally, EOs from both flowers and leaves exhibited fumigant activities against T. castaneum larvae (LC50 = 24.42 and 62.54 mg/L) and L. serricorne adults (LC50 = 15.26 and 24.29 mg/L). Furthermore, the EOs of flowers and leaves and their main components (caryophyllene and cuminol) remained significantly repellency to T. castaneum larvae and L. serricorne adults within the testing concentration range of 78.63-15.83 nL/cm2 after 12 h of exposure. These findings suggested that the EO from E. stauntoni and its two major components could potentially be developed as a natural insecticide for controlling T. castaneum larvae and L. serricorne adults. [ABSTRACT FROM AUTHOR]

Background: Identification of promising targeted antigens that exhibited cancer-specific expression is a crucial step in the development of novel antibody-targeted therapies. We here aimed to investigate the anti-tumor activity of a novel monoclonal antibody (mAb) 11C9 and identify the antibody tractable target in the hepatocellular cancer stem cells (HCSCs). Methods: The identification of the targeted antigen was conducted using SDS-PAGE, western blot, mass spectrometry, and co-immunoprecipitation. Silence of HSP90 was induced by siRNA interference. Positive cells were sorted by fluorescence-activated cell sorting. Double-immunofluorescent (IF) staining and two-color flow cytometry detected the co-expression. Self-renewal, invasion, and drug resistance were assessed by sphere formation, matrigel-coated Transwell assay, and CCK-8 assay, respectively. Tumorigenicity was evaluated in mouse xenograft models. RNA-seq and bioinformatics analysis were performed to explore the mechanism of mAb 11C9 and potential targets. Results: MAb 11C9 inhibited invasion and self-renewal abilities of HCC cell lines and reversed the cisplatin resistance. HSP90 (~ 95 kDa) was identified as a targeted antigen of mAb 11C9. Tissue microarrays and online databases revealed that HSP90 was overexpressed in HCC and associated with a poor prognosis. FACS and double-IF staining showed the co-expression of HSP90 and CSCs markers (CD90 and ESA). In vitro and in vivo demonstrated the tumorigenic potentials of HSP90. The inhibition of HSP90 by siRNA interference or 17-AAG inhibitor both decreased the number of invasion, sphere cells, and CD90+ or ESA+ cells, as well as reversed the resistance. Bioinformatics analysis and western blot verified that HSP90 activated Wnt/β-catenin signaling. Conclusions: The study preliminarily revealed the anti-tumor activity of mAb 11C9. More importantly, we identified HSP90 as a targeted antigen of mAb 11C9, which functions as an oncogene in phenotype shaping, stemness maintenance, and therapeutic resistance by activating Wnt/β-catenin signaling. [ABSTRACT FROM AUTHOR]

A one‐pot strategy for the synthesis of substituted isocoumarin, flavone, and isoquinolinedione derivatives through a switchable C‐arylation/lactonization or SNAr reaction from a wide range of soft nucleophiles and o‐quinol acetates has been developed. This base‐mediated protocol proceeds under transition‐metal‐free conditions and selectively affords various heteroarenes in 13–98% yields from readily prepared or commercially available 1,3‐dicarbonyl and α‐EWG‐substituted carbonyl compounds. The synthetic utility is further demonstrated in the synthesis of potential anti‐HIV and anti‐coronavirus derivatives and COX‐2 inhibitors. In addition, detailed experimental and computational studies are performed to provide an intensive understanding and strong support of the reaction mechanism. [ABSTRACT FROM AUTHOR]

We propose an effective highest occupied d‐orbital modulation strategy engendered by breaking the coordination symmetry of sites in the atomically precise Cu nanocluster (NC) to switch the product of CO2 electroreduction from HCOOH/CO to higher‐valued hydrocarbons. An atomically well‐defined Cu6 NC with symmetry‐broken Cu−S2N1 active sites (named Cu6(MBD)6, MBD=2‐mercaptobenzimidazole) was designed and synthesized by a judicious choice of ligand containing both S and N coordination atoms. Different from the previously reported high HCOOH selectivity of Cu NCs with Cu−S3 sites, the Cu6(MBD)6 with Cu−S2N1 coordination structure shows a high Faradaic efficiency toward hydrocarbons of 65.5 % at −1.4 V versus the reversible hydrogen electrode (including 42.5 % CH4 and 23 % C2H4), with the hydrocarbons partial current density of −183.4 mA cm−2. Theoretical calculations reveal that the symmetry‐broken Cu−S2N1 sites can rearrange the Cu 3d orbitals with dx2-y2 ${d_{x^2 - y^2 } }$ as the highest occupied d‐orbital, thus favoring the generation of key intermediate *COOH instead of *OCHO to favor *CO formation, followed by hydrogenation and/or C−C coupling to produce hydrocarbons. This is the first attempt to regulate the coordination mode of Cu atom in Cu NCs for hydrocarbons generation, and provides new inspiration for designing atomically precise NCs for efficient CO2RR towards highly‐valued products. [ABSTRACT FROM AUTHOR]

We propose an effective highest occupied d‐orbital modulation strategy engendered by breaking the coordination symmetry of sites in the atomically precise Cu nanocluster (NC) to switch the product of CO2 electroreduction from HCOOH/CO to higher‐valued hydrocarbons. An atomically well‐defined Cu6 NC with symmetry‐broken Cu−S2N1 active sites (named Cu6(MBD)6, MBD=2‐mercaptobenzimidazole) was designed and synthesized by a judicious choice of ligand containing both S and N coordination atoms. Different from the previously reported high HCOOH selectivity of Cu NCs with Cu−S3 sites, the Cu6(MBD)6 with Cu−S2N1 coordination structure shows a high Faradaic efficiency toward hydrocarbons of 65.5 % at −1.4 V versus the reversible hydrogen electrode (including 42.5 % CH4 and 23 % C2H4), with the hydrocarbons partial current density of −183.4 mA cm−2. Theoretical calculations reveal that the symmetry‐broken Cu−S2N1 sites can rearrange the Cu 3d orbitals with dx2-y2 ${d_{x^2 - y^2 } }$ as the highest occupied d‐orbital, thus favoring the generation of key intermediate *COOH instead of *OCHO to favor *CO formation, followed by hydrogenation and/or C−C coupling to produce hydrocarbons. This is the first attempt to regulate the coordination mode of Cu atom in Cu NCs for hydrocarbons generation, and provides new inspiration for designing atomically precise NCs for efficient CO2RR towards highly‐valued products. [ABSTRACT FROM AUTHOR]

The stiffnesses of embankments and culverts differ in the transition sections of high-speed railways (HSRs) due to their different supporting conditions. The dynamic irregularity caused by the different stiffnesses makes this transition area the weakest part of high-speed railways. Graded crushed stone combined with 5% cement is typically used to fill the subgrade in these transition areas. Thus, three different particle size ratios of crushed stone were matched and tested regarding the construction parameters to explore the most suitable materials to fill the roadbed in a transition section. Then, field dynamic tests were carried out on the culvert–embankment–culvert transition area where trains run at speeds of 5–360 km/h. A time-domain analysis of the test data was performed to obtain the laws of variation that cause the dynamic characteristics to change with the railway line and roadbed layer and the changes induced by a train's running speed, operating direction, and axle weight. The results indicate that (i) it is feasible to fill transition section roadbeds with well-graded crushed stone combined with 5% cement with optimal water contents; (ii) extreme dynamic responses in some special sections are observed, suggesting the value of taking special measures at the transition section. For example, the sections 14.5 m and 30 m from the 679 culvert and the bed layer should be specially stabilized; (iii) the train's axle load and driving direction show a great effect on corresponding sections and layers but present a small effect on the sections and layers nearby; and (iv) 260 km/h is a critical speed. [ABSTRACT FROM AUTHOR]

Our study aims to investigate the serum levels of anti-nucleosome antibody (ANuA) isotypes in patients with systemic lupus erythematosus (SLE) and clarify ANuA isotypes that may diagnose and predict SLE. We detected anti-nucleosome antibodies (ANuA) in the serum from 120 patients with SLE, 99 patients suffering from other autoimmune diseases (OAD), and 50 healthy controls by performing IgG-, IgA-, and IgM-specific ELISAs. The serum levels of total anti-nuclear antibodies (ANA IgG), ANuA IgG subclasses (IgG1, IgG2, IgG3, and IgG4), anti-dsDNA antibodies, and the avidities of ANA IgG were also analysed using ELISAs. The levels of three ANuA isotypes (IgG, IgA, and IgM) were significantly higher in patients with SLE than in patients with OAD and healthy controls (p < 0.05). Moreover, the concentrations of ANuA isotypes increased in the active SLE and lupus nephritis (LN) groups and in patients with SLE presenting high-avidity IgG ANA (p < 0.05). Furthermore, ANuA isotype levels decreased significantly with drug therapy, while anti-dsDNA IgG levels decreased with the same trend. Additionally, ANuA isotypes were positively related to the SLEDAI (SLE Disease Activity Index) score, RAI (relative avidity index) of high-avidity IgG ANAs, and serum anti-dsDNA IgG levels. Last, the sensitivity and specificity values for SLE were 83.33 and 96.67% for ANuA IgG, 85.83 and 93.33% for ANuA IgA, and83.33 and 86.67% for ANuA IgM, respectively. The sensitivity and specificity values for LN were 61.67 and 96.67% for ANuA IgG, 49.17 and 96.67% for ANuA IgA, and 52.50 and 96.67% for ANuA IgM, respectively. In conclusion, we evaluated whether ANuA isotypes represent a diagnostic tool to predict SLE activity and define subsets of patients with LN. [ABSTRACT FROM AUTHOR]

The plant architecture of higher plants is regulated through environmental and genetic factors, as well as phytohormones. Phytohormones play a critical role in regulating shoot branching. We determined the branching phenotype of D16 and N99-6, the content of strigolactones, the genetic expression level, and the interaction between auxin and strigolactones. We found that the branching development of the two soybean varieties under shading was significantly slower than that under normal light. The average branch length of N99-6 decreased by 40.9% after shading; however, the branch length of D16 was not significantly affected. Meanwhile, the branch formation rate in D16 was significantly higher than in N99-6. In addition, after shading treatment, the content of strigolactones in D16 and N99-6 axillary buds increased significantly, and the expression of phytochrome genes, PhyA and PhyB, showed opposite changes. However, strigolactone synthesis gene GmMAX4 and signal transduction gene GmMAX2 expression levels of D16 were lower than those of N99-6 after 24 h of shading. In addition, the application of strigolactone inhibitor TIS108 and auxin inhibitor NPA to soybean had no significant effect on the branch phenotype. The expression of the GmMAX2 gene was significantly up-regulated after the external application of the auxin analog, and the expression of auxin transporter gene GmPINI was significantly down-regulated after external application of the strigolactone analog under shade. In this study, we investigated the adverse effect of shade on soybean branching development, which may be due to the interaction of strigolactones with auxins. [ABSTRACT FROM AUTHOR]

The Arctic sea ice decline and associated change in maritime accessibility have created a pressing need for sea ice thickness (SIT) predictions. This study developed a linear Markov model for the seasonal prediction of modelassimilated SIT. It tested the performance of physically relevant predictors by a series of sensitivity tests. As measured by the anomaly correlation coefficient (ACC) and root-mean-square error (RMSE), the SIT prediction skill was evaluated in different Arctic regions and across all seasons. The results show that SIT prediction has better skill in the cold season than in the warm season. The model performs best in the Arctic basin up to 12 months in advance with ACCs of 0.7–0.8. Linear trend contributions to model skill increase with lead months. Although monthly SIT trends contribute largely to the model skill, the model remains skillful up to 2-month leads with ACCs of 0.6 for detrended SIT predictions in many Arctic regions. In addition, the Markov model’s skill generally outperforms an anomaly persistence forecast even after all trends were removed. It also shows that, apart from SIT itself, upper-ocean heat content (OHC) generally contributes more to SIT prediction skill than other variables. Sea ice concentration (SIC) is a relatively less sensitive predictor for SIT prediction skill than OHC. Moreover, the Markov model can capture the melt-to-growth season reemergence of SIT predictability and does not show a spring predictability barrier, which has previously been observed in regional dynamical model forecasts of September sea ice area, suggesting that the Markov model is an effective tool for SIT seasonal predictions. [ABSTRACT FROM AUTHOR]

Despite the proven safety and clinical efficacy of the Measles vaccine, many countries are seeing new heights of vaccine hesitancy or refusal, and are experiencing a resurgence of measles infections as a consequence. With the use of novel machine learning tools, we investigated the prevailing negative sentiments related to Measles vaccination through an analysis of public Twitter posts over a 5-year period. We extracted original tweets using the search terms related to "measles" and "vaccine," and posted in English from January 1, 2017, to December 15, 2022. Of these, 155,363 tweets were identified to be negative sentiment tweets from unique individuals, through the use of Bidirectional Encoder Representations from Transformers (BERT) Named Entity Recognition and SieBERT, a pretrained sentiment in English analysis model. This was followed by topic modeling and qualitative thematic analysis performed inductively by the study investigators. A total of 11 topics were generated after applying BERTopic. To facilitate a global discussion of results, the topics were grouped into four different themes through iterative thematic analysis. These include (a) the rejection of "anti-vaxxers" or antivaccine sentiments, (b) misbeliefs and misinformation regarding Measles vaccination, (c) negative transference due to COVID-19 related policies, and (d) public reactions to contemporary Measles outbreaks. Theme 1 highlights that the current public discourse may further alienate those who are vaccine hesitant because of the disparaging language often used, while Themes 2 and 3 highlight the typology of misperceptions and misinformation underlying the negative sentiments related to Measles vaccination and the psychological tendency of disconfirmation bias. Nonetheless, the analysis was based solely on Twitter and only tweets in English were included; hence, the findings may not necessarily generalize to non-Western communities. It is important to further understand the thinking and feeling of those who are vaccine hesitant to address the issues at hand. [ABSTRACT FROM AUTHOR]

Over the past few decades, stimuli‐responsive materials have been widely applied to porous surfaces. Permeability and conductivity control of ions confined in nanochannels modified with stimuli‐responsive materials, however, have been less investigated. In this work, the permeability and conductivity control of ions confined in nanochannels of anodic aluminum oxide (AAO) templates modified with thermo‐responsive poly(N‐isopropylacrylamide) (PNIPAM) brushes are demonstrated. By surface‐initiated atom transfer radical polymerization (SI‐ATRP), PNIPAM brushes are successfully grafted onto the hexagonally packed cylindrical nanopores of AAO templates. The surface hydrophilicities of the membranes can be reversibly altered because of the lower critical solution temperature (LCST) behavior of the PNIPAM polymer brushes. From electrochemical impedance spectroscopy (EIS) analysis, the temperature‐gating behaviors of the AAO‐g‐PNIPAM membranes exhibit larger impedance changes than those of the pure AAO membranes at higher temperatures because of the aggregation of the grafted PNIPAM chains. The reversible surface properties caused by the extended and collapsed states of the polymer chains are also demonstrated by dye release tests. The smart thermo‐gated and ion‐controlled nanoporous membranes are suitable for future smart membrane applications. [ABSTRACT FROM AUTHOR]

• Fluorine-free mold flux containing boron was found to bring severe boron pollution. • Particulate matter and wastewater containing boron were the main contaminants. • Na was found to aggravate boron pollution by weakening the amorphous network. The boron emission into air and water during the use of fluorine-free mold flux containing boron was systematically investigated to evaluate the corresponding environmental impacts. Unexpectedly, boron in mold flux was volatilized in the form of NaBO 2 particulate matter as Na 2 O was added to mold flux. Besides, boron remained in the used mold flux residue was found to be linearly released into leachate continuously, and Na+ existed in the borosilicate network accelerated the hydrolysis of the network and the dissolution of boron by increasing no-bridging oxygen and converting BO 4 groups into fragile BO 3 groups. Considering the negative effect of Na 2 O on the stabilization of boron in mold flux, limiting the addition of Na 2 O in fluorine-free mold flux containing boron will further minimize the pollution originating from the use of mold flux. [ABSTRACT FROM AUTHOR]

Classical swine fever (CSF), caused by classical swine fever virus (CSFV), is a highly contagious disease in pigs. In Taiwan, the emerging genotype 2.1 (G2.1) CSFV caused sporadic outbreaks in 1994 and replaced the previous G3.4 CSFV in the field. The shift of CSFV genotypes to G2 CSFV was also observed in several CSFV-affected countries. The present study aimed to explore the mechanism of the genotype shift of CSFV. Two groups of specific pathogen-free (SPF) pigs were first inoculated with either G2.1 or G3.4 CSFV (single-inoculated group) and housed together with naïve SPF pigs (cohabitating group). The results showed that peak viremia, viral loads in blood and tissues, and viral shedding of G2.1 were consistently higher than those of G3.4 CSFV in single-inoculated and cohabitating pigs. The phenomenon of superinfection exclusion (SIE), characterized by the prevention of secondary infection by a primary infection, was readily observed in CSFV single-inoculated pigs. Interestingly, coinfection of both genotypes of CSFV was observed in 3 out of 4 cohabitating pigs, while only one pig was infected with G2.1 CSFV alone. These findings suggest that the genetic shift in CSFV in the field may be in part the consequence of SIE. • CSFV genotype 2.1 replicated more efficiently than genotype 3.4 in pigs. • CSFV genotype 2.1 shed more virus than genotype 3.4 in oral secretions and feces. • The superinfection exclusion phenomenon was readily observed in CSFV single-inoculated pigs. • In cohabitating pigs coinfected with both genotypes 2.1 and 3.4, the latter was gradually replaced. • Superinfection exclusion may contribute to the genetic shift in the prevalent CSFV in the field. [ABSTRACT FROM AUTHOR]

The self-organizing map (SOM) represents high-dimensional input samples by a 2-dimensional output topological structure, whereby similar input samples are mapped onto the same output unit or neighboring units on a map for visualization. Although many extended SOM models have been proposed, the need to determine a grid structure of SOM before learning, and the lack of adaptability to rapid changes in input data have not yet been fully overcome. This research proposes an adaptive growing grid (AGG) model, which is a novel neural self-organizing map (SOM), for projecting high-dimensional input samples onto an output grid. Due to the need for a grid structure for visualization, the AGG uses both growing and pruning functions and an adaptive learning process in order to adapt its output grid structure and learning function to constantly and rapidly changing input data in a non-stationary environment. The proposed AGG is tested on four basic data sets and one cross-domain data set. In addition, the t -test is used to test whether the proposed AGG outperforms the benchmark model, the growing grid (GG). Based on three evaluation measures, i.e. average quantization error (AQE), topographic error (TE) and dead unit ratio (DUR), the AGG significantly outperforms the GG in a non-stationary environment. [ABSTRACT FROM AUTHOR]

Intelligent mechanical fault diagnosis techniques have been extensively developed in recent years. Owing to the advantage of data privacy protection, federated learning has recently received increasing attention; this approach can utilize monitoring data from multiple local clients to train an optimal global diagnosis model. However, low-quality data are often present for some clients, including mislabeled data and incomplete data that lack some health states. Furthermore, the data distributions are usually different across different clients owing to variations in machine operating conditions. Therefore, the performance of the federated diagnostic model may be limited by low-quality data and data distribution discrepancies. To address this issue, a federated transfer learning method with low-quality knowledge filtering and dynamic model aggregation is proposed. First, a dynamic filter is designed by filtering out low label probabilities predicted by low-quality source domain models to construct high-confidence pseudo-labels for the target domain data. Then, the batch normalized maximum mean discrepancy (BN-MMD) distance metric is introduced into the training loss function to reduce the data distribution discrepancy between the source clients and the target client without private data leakage. While building the global model in each training round, a dynamic model aggregation algorithm is proposed to mitigate the influence of low-quality clients. This algorithm evaluates the weight of each client according to its contribution to the total consensus diagnostic knowledge and then aggregates the local models with adaptive weights. Consequently, it can overcome the drawback of the classical federated averaging (FedAvg) algorithm, where all local clients are assigned the same weight when constructing the global model. Experiments are conducted on three bearing datasets under various loads and speeds. Compared with some existing diagnostic methods, the proposed federated transfer learning method can reduce the impact of low-quality data and achieve higher diagnostic accuracy while preserving data privacy. • A novel federated transfer learning method is proposed for bearing fault diagnosis. • Low-quality knowledge of some source clients is eliminated by a dynamic filter. • A dynamic model aggregation algorithm is derived to obtain an optimal global model. [ABSTRACT FROM AUTHOR]

Artificial emotional intelligence (AEI) is an important ability for intelligent systems. Representing emotional states as a continuous sentiment intensity could achieve a more fine-grained sentiment application than traditional categorical approaches. By using sentiment intensity, the main challenge of the existing variational autoencoder methods lies in distinguishing emotional information from semantic information. Practically, it is difficult to ensure that the input training texts do not contain any sentiment. If the disentangled latent variable for text generation contains sentiment features that conflict with the assigned sentiment, the generated texts will be messy. Therefore, we propose a decoupled variational autoencoder (VAE) with interactive attention to solve this problem. The proposed method applies a sentiment decoupler to extract the sentiment from the text. Then, sentiment embeddings are applied to map the intensities into the latent space. To enhance the representation ability of sentiment embeddings and the performance of the decoder, we consider affective text generation as a process of denoising, design a noisy sampling strategy in training, and then continuously update the emotional information with variational attention through a dynamic update mechanism. Extensive experiments are conducted on the Yelp dataset and the Amazon dataset, and the experimental results show that our method outperforms other VAE-based methods in fine-grained affective text generation. [ABSTRACT FROM AUTHOR]

Para-aortic lymph node (PALN) metastasis is a rare pattern of systemic metastasis from colorectal cancer (CRC) [[1]]. In Video S1, we present a novel application of NIR/ICG imaging during laparoscopic PALN dissection to prevent incomplete dissection of metachronous PALN metastases from rectal cancer. Indocyanine green fluorescence imaging guided laparoscopic para-aortic lymphadenectomy for rectal cancer with para-aortic lymph node metastasis - a video vignette. [Extracted from the article]

In this manuscript, we study the non-Hermitian spin-1/2 XY model in the presence of the alternating, imaginary and transverse magnetic fields. For the two-site spin system, we solve exactly the energy spectrum and phase diagram and also calculate the ground-state and thermal entanglements by using the concept of the concurrence. It is found that the two-site concurrence in the eigenstate which only depends on the imaginary magnetic field η is always equal to one in the region of P T symmetry, while it decreases with η in the P T -symmetric broken region; especially, the first derivative of concurrence shows the non-analytic behavior at the exceptional point, and the same is true in the case of the biorthogonal basis, which indicates that the concurrence can characterize the phase transition in this non-Hermitian system. The interesting thing is that η weakens the thermal entanglement when the system is isotropic and enhances the entanglement when the system belongs to the Ising universality class. For the one-dimensional spin chain, the magnetization and entanglement are further studied by using the two-spin cluster mean-field approximation. The results show that their variations have opposite trends with the magnetic fields. Moreover, the system exists the first-order quantum phase transitions for some anisotropic parameters in the P T -symmetry region, and the entanglement changes suddenly at the quantum phase transition point. [ABSTRACT FROM AUTHOR]

We present a straightforward approach to develop a high-detectivity silicon (Si) sub-bandgap near-infrared (NIR) photodetector (PD) based on textured Si/Au nanoparticle (NP) Schottky junctions coated with graphene film. This is a photovoltaic-type PD that operates at 0 V bias. The texturing of Si is to trap light for NIR absorption enhancement, and Schottky junctions facilitate sub-bandgap NIR absorption and internal photoemission. Both Au NPs and the texturing of Si were made in self-organized processes. Graphene offers additional pathways for hot electron transport and to increase photocurrent. Under 1319 nm illumination at room temperature, a responsivity of 3.9 mA/W and detectivity of 7.2 × 1010 cm × (Hz)1/2/W were obtained. Additionally, at −60 °C, the detectivity increased to 1.5 × 1011 cm × (Hz)1/2/W, with the dark current density reduced and responsivity unchanged. The result of this work demonstrates a facile method to create high-performance Si sub-bandgap NIR PDs for promising applications at ambient temperatures. [ABSTRACT FROM AUTHOR]

Background: RGB photographs are a powerful tool for dynamically estimating crop growth. Leaves are related to crop photosynthesis, transpiration, and nutrient uptake. Traditional blade parameter measurements were labor-intensive and time-consuming. Therefore, based on the phenotypic features extracted from RGB images, it is essential to choose the best model for soybean leaf parameter estimation. This research was carried out to speed up the breeding procedure and provide a novel technique for precisely estimating soybean leaf parameters. Results: The findings demonstrate that using an Unet neural network, the IOU, PA, and Recall values for soybean image segmentation can achieve 0.98, 0.99, and 0.98, respectively. Overall, the average testing prediction accuracy (ATPA) of the three regression models is Random forest > Cat Boost > Simple nonlinear regression. The Random forest ATPAs for leaf number (LN), leaf fresh weight (LFW), and leaf area index (LAI) reached 73.45%, 74.96%, and 85.09%, respectively, which were 6.93%, 3.98%, and 8.01%, respectively, higher than those of the optimal Cat Boost model and 18.78%, 19.08%, and 10.88%, respectively, higher than those of the optimal SNR model. Conclusion: The results show that the Unet neural network can separate soybeans accurately from an RGB image. The Random forest model has a strong ability for generalization and high accuracy for the estimation of leaf parameters. Combining cutting-edge machine learning methods with digital images improves the estimation of soybean leaf characteristics. [ABSTRACT FROM AUTHOR]

Glandular secretory trichomes (GSTs) can secrete and store a variety of specific metabolites. By increasing GST density, valuable metabolites can be enhanced in terms of productivity. However, the comprehensive and detailed regulatory network of GST initiation still needs further investigation. By screening a complementary DNA library derived from young leaves of Artemisia annua, we identified a MADS-box transcription factor, AaSEPALLATA1 (AaSEP1), that positively regulates GST initiation. Overexpression of AaSEP1 in A. annua substantially increased GST density and artemisinin content. The HOMEODOMAIN PROTEIN 1 (AaHD1)-AaMYB16 regulatory network regulates GST initiation via the jasmonate (JA) signaling pathway. In this study, AaSEP1 enhanced the function of AaHD1 activation on downstream GST initiation gene GLANDULAR TRICHOMESPECIFIC WRKY 2 (AaGSW2) through interaction with AaMYB16. Moreover, AaSEP1 interacted with the JA ZIM-domain 8 (AaJAZ8) and served as an important factor in JA-mediated GST initiation. We also found that AaSEP1 interacted with CONSTITUTIVE PHOTOMORPHOGENIC 1 (AaCOP1), a major repressor of light signaling. In this study, we identified a MADS-box transcription factor that is induced by JA and light signaling and that promotes the initiation of GST in A. annua. [ABSTRACT FROM AUTHOR]

Evidence theory is widely used to deal with the fusion of uncertain information, but the fusion of conflicting evidence remains an open question. To solve the problem of conflicting evidence fusion in single target recognition, we proposed a novel evidence combination method based on an improved pignistic probability function. Firstly, the improved pignistic probability function could redistribute the probability of multi-subset proposition according to the weight of single subset propositions in a basic probability assignment (BPA), which reduces the computational complexity and information loss in the conversion process. The combination of the Manhattan distance and evidence angle measurements is proposed to extract evidence certainty and obtain mutual support information between each piece of evidence; then, entropy is used to calculate the uncertainty of the evidence and the weighted average method is used to correct and update the original evidence. Finally, the Dempster combination rule is used to fuse the updated evidence. Verified by the analysis results of single-subset proposition and multi-subset proposition highly conflicting evidence examples, compared to the Jousselme distance method, the Lance distance and reliability entropy combination method, and the Jousselme distance and uncertainty measure combination method, our approach achieved better convergence and the average accuracy was improved by 0.51% and 2.43%. [ABSTRACT FROM AUTHOR]

To explore the differences in type I hypersensitivity-induced inflammatory response among children of different age groups with acute appendicitis. We selected children diagnosed with "acute appendicitis" who underwent surgery in the Department of General Surgery of Anhui Provincial Children's Hospital from January 2022 to June 2022 and collected their basic data. We divided them into two groups according to age: the infant group (less than 3 years old) and the pediatric group (3–14 years old). The gender, age, onset time, hospital stay, preoperative white blood cells, percentage of neutrophils, C-reactive protein (CRP), and enzyme-linked immunosorbent assay (ELISA) were collected to determine the levels of immunoglobulin E (IgE), interleukin-4 (IL-4), interleukin-5 (IL-5), interleukin-6 (IL-6), and interleukin-9 (IL-9) in appendicular lavage fluid, and the differences between the two groups were compared. There were 15 children in the infant group and 15 in the pediatric group. There was no significant difference between the two groups with respect to onset time and gender. The hospitalization time in the pediatric group was (5.7 ± 2.1) d, the preoperative white blood cells were (14.3 ± 3.7) × 10^9/mL, neutrophil percentage was (84.5 ± 6.3)%, and CRP was (20.0 ± 17.9) mg/mL. The hospitalization time of the infant group was (8.0 ± 3.1) d, the preoperative white blood cells were (19.0 ± 3.8) × 10^9/mL, neutrophil percentage was (77.8 ± 10.4)%, and CRP was (42.5 ± 25.0) mg/mL. The differences between the two groups were significant. There was no significant difference in IL-5 concentration between the two groups in the appendicular lavage fluid. IgE (610.74 ± 72.56) ng/mL, IL-4 (30.80 ± 12.04) ng/mL, IL-6 (118.09 ± 14.29) ng/mL, IL-9 (133.94 ± 16.00) ng/mL were found in the infant group, and IgE (495.61 ± 95.09) ng/mL, IL-4 (22.68 ± 7.05) ng/mL, IL-6 (98.22 ± 22.18) ng/mL and IL-9 (107.86 ± 27.34) ng/mL were found in the pediatric group, and the differences between the two groups were statistically significant. The inflammatory response in children with acute appendicitis was associated with type I hypersensitivity-induced inflammatory responses, and the type I hypersensitivity was more intense in children in the lower age group. • Explored the possible pathogenesis of acute appendicitis in children. • Explore the differences in type I hypersensitivity-induced specific inflammatory response among children of different age groups with acute appendicitis. • The inflammatory response in children with acute appendicitis was associated with type I hypersensitivity-induced specific inflammatory responses. • The type I hypersensitivity was more intense in children in the lower age group. [ABSTRACT FROM AUTHOR]

• A disease occurrence characterized by fever and rash was monitored in China. • The etiological and epidemiological investigation was initiated. • We proved that a novel species of genus Ehrlichia was its pathogen. • We named the new species as " Candidatus Ehrlichia erythraense". From March to June 2021, the reported number of clinically diagnosed endemic typhus in Anhui and Hubei provinces of China nearly increased four-fold compared with the monthly average numbers in last 5 years. An etiological and epidemiological investigation was initiated. The clinical specimens from the reported patients and the potential vector ticks were collected for molecular and serological detection, as well as cell culturing assay to identify the potential pathogen. Polymerase chain reaction and sequence analysis of rrs and groEL showed that the pathogen from these patients was Ehrlichia sp., isolated from Haemaphysalis longicornis attached to these patients. The phylogenetic analysis based on 39 Ehrlichia genomes suggested that it should be taxonomically classified as a novel species, tentatively named " Candidatus Ehrlichia erythraense". A total of 19 of 106 cases were confirmed as Candidatus Ehrlichia erythraense infections by polymerase chain reaction, sequencing, and/or serological tests. The most frequent symptoms were fever (100%), rashes (100%), asthenia (100%), anorexia (100%), and myalgia (79%). The occurrence of the disease presenting with fever and rashes in Anhui and Hubei provinces was caused by a novel species of the genus Ehrlichia ; physicians need to be aware of this newly-discovered pathogen to ensure appropriate testing, treatment, and regional surveillance. [ABSTRACT FROM AUTHOR]

Fungal spoilage of postharvest grains poses serious problems with respect to food safety, human health, and the economic value of grains. The protection of cereal grains from deleterious fungi is a critical aim in postharvest grain management. Considering the bulk volume of grain piles in warehouses or bins and food safety, fumigation with natural gaseous fungicides is a promising strategy to control fungal contamination on postharvest grains. Increasing research has focused on the antifungal properties of biogenic volatiles. This review summarizes the literature related to the effects of biogenic volatiles from microbes and plants on spoilage fungi on postharvest grains and highlights the underlying antifungal mechanisms. Key areas for additional research on fumigation with biogenic volatiles in postharvest grains are noted. The research described in this review supports the protective effects of biogenic volatiles against grain spoilage by fungi, providing a basis for their expanded application in the management of postharvest grains. Key points: • Biogenic volatile compounds with inhibitory effects against fungi on postharvest grains are reviewed. • Mechanisms underlying antifungal effects of biogenic volatiles are discussed. • Biogenic volatiles have promising applications for the prevention of postharvest grain spoilage by fungi. [ABSTRACT FROM AUTHOR]

Background: As of 2023, coronavirus disease 2019 (COVID-19) is still spreading globally. Therefore, we aim to integrate non-critical COVID-19 high-frequency and high-targeting Chinese medicines to provide a reference for clinical prescriptions to improve COVID-19-related symptoms. Materials and methods: The information on non-critical COVID-19 high-frequency Chinese medicines in the diagnosis and treatment of COVID-19 was obtained by the TCM inheritance support platform. Using network pharmacology and molecular docking technology, high-targeting Chinese medicines with good docking activity with COVID-19 receptors angiotensin-converting enzyme-II (ACE2), 3CLpro and tyrosine-protein kinase receptor UFO (AXL) were obtained. A new prescription for non-critical COVID-19 was established by integrating high-frequency and high-targeting Chinese medicines. Rats with acute lung injury induced by lipopolysaccharide were used as the experimental model. The histopathological changes in the lungs of rats in each group were observed by hematoxylin-eosin staining. The lung coefficient of rats was measured. The levels of IL-6, TNF-a, and IL-1ß in serum were detected by enzyme-linked immunosorbent assay. The mRNA and protein levels of ACE2 and AXL in lung tissue were detected by real-time quantitative polymerase chain reaction and western blot. Results: Through data mining, it was found that there were 39 high-frequency traditional Chinese medicines for non-critical COVID-19 in the diagnosis and treatment guidelines. According to network pharmacology and molecular docking, 30 highly targeted traditional Chinese drugs for COVID-19 were found. The new prescriptions for non-critical COVID-19 were comprehensively obtained, including Glycyrrhizae Radix, Ephedra Herba, Amygdalus Communis Vas, Gypsum Fibrosum, Descurainiae Semen, Atractylodes Lancea, Scutellariae Radix, Amomum Tsao-Ko Crevostet, Forsythiae Fructus, Pogostemon cablin, Magnolia Officinalis. Compared with the LPS-induced lung injury model group, the medium dose of the new prescription group had significantly alleviated pathological changes in lung tissue, decreased lung coefficient, decreased contents of IL-6, TNF-a and IL-1ß, and increased mRNA and protein expression of ACE2 and AXL (P < 0.05). Conclusion: Based on data mining, network pharmacology and molecular docking technology, the new prescription for non-critical COVID-19 established by this method has an anti-inflammatory effect on rats with acute lung injury induced by lipopolysaccharide and can provide a reference for clinicians to alleviate the symptoms related to non-critical COVID-19. [ABSTRACT FROM AUTHOR]

When a symbol or a type has been "frozen" (namely, a type of which an individual only produces one individual of the same type), its spread pattern will be changed and this change will affect the long-term behavior of the whole system. However, in a frozen system, the ξ -matrix and the offspring mean matrix are no longer primitive so that the Perron–Frobenius theorem cannot be applied directly when predicting the spread rates. In this paper, our goal is to characterize these key matrices and analyze the spread rate under more general settings both in the topological and random spread models with frozen symbols. More specifically, we propose an algorithm for explicitly computing the spread rate and relate the rate with the eigenvectors of the ξ -matrix or offspring mean matrix. In addition, we reveal that the growth of the population is exponential and that the composition of the population is asymptotically periodic. Furthermore, numerical experiments are provided as supporting evidence for the theory. [ABSTRACT FROM AUTHOR]

• We evaluated the efficacy of intermittent theta-burst stimulation (iTBS) in postoperative care across two cortical targets. • iTBS reduced anaesthetic pump attempts. • This effect was unique to DLPFC stimulation while M1 had no effect. Repetitive transcranial magnetic stimulation (rTMS) may be a relevant method to assist postoperative pain. However, studies to date have only used conventional 10 Hz rTMS and targeted the DLPFC for postoperative pain. A more recent form of rTMS, termed intermittent Theta Burst Stimulation (iTBS), enables to increase cortical excitability in a short period of time. This preliminary double-blind, randomised, sham controlled study was designed to evaluate the efficacy of iTBS in postoperative care across two distinct stimulation targets. A group of 45 patients post laparoscopic surgery were randomised to receive a single session of iTBS over either the dorsolateral prefrontal cortex (DLPFC), primary motor cortex (M1), or Sham stimulation (1:1:1 ratio). Outcome measurements were number of pump attempts, total anaesthetic volume used, and self-rated pain experience, assessed at 1 hour, 6 hours, 24 hours, and 48 hours post stimulation. All randomised patients were analysed (n = 15 in each group). Compared to Sham stimulation, DLPFC-iTBS reduced pump attempts at 6 (DLPFC = 0.73 ± 0.88, Sham = 2.36 ± 1.65, P = 0.031), 24 (DLPFC = 1.40 ± 1.24, Sham = 5.03 ± 3.87, P = 0.008), and 48 (DLPFC = 1.47 ± 1.41, Sham = 5.87 ± 4.34, P = 0.014) hours post-surgery, whereby M1 stimulation had no effect. No group effect was observed on total anaesthetics, which was mainly provided through the continuous administration of opioids at a set speed for each group. There was also no group or interaction effect on pain ratings. Pump attempts were positively associated with pain ratings in the DLPFC (r = 0.59, P = 0.02) and M1 (r = 0.56, P = 0.03) stimulation. Our findings show that iTBS to the DLPFC reduces pump attempts for additional anaesthetics following a laparoscopic surgery. However, reduced pump attempts by DLPFC stimulation did not translate into a significantly smaller volume of total anaesthetic, due to the continuous administration of opioids at a set speed for each group. Our findings therefore provide preliminary evidence for iTBS targeting the DLPFC to be used to improve postoperative pain management. [ABSTRACT FROM AUTHOR]

The microphone array is widely used in acoustics as a non-contact measurement tool, which can obtain multi-dimensional information about the sound source, such as spatial, time, and frequency. The microphone array is not always used in an ideal anechoic chamber environment, making the sound source signal contaminated with the background interference. The separation of the sound source signal from the complex background interference is very challenging, especially when arrays are used in wind tunnel measurements. A probability model on the time–frequency matrix is constructed in this paper to address this issue. The background interference is constructed by the Gaussian mixture model to fit its complex probability distributions adaptively. The sound source signal is constructed as a low-rank model according to its correlation characteristics on the microphones. The distributions of parameters involved in the low-rank and Gaussian mixture model are estimated through variational Bayesian inference, which can realize the separation of the sound source signal from the complex background interference. The performance of the proposed method is evaluated by the numerical simulation and the DLR closed wind tunnel experimental. The robustness and the effectiveness of extracting the sound source signal from the complex background interference are also verified. • Complex interference suppression in the microphone array measurement is investigated. • A hierarchical parametric framework is constructed based on the low-rank and Gaussian mixture model. • The optimal model parameters are adaptively determined by the Variational Bayesian inference. • The proposed method can effectively remove the interference for acoustic imaging in the DLR wind tunnel test. [ABSTRACT FROM AUTHOR]

Background: RNA 5-methyluridine (m5U) modifications are obtained by methylation at the C5 position of uridine catalyzed by pyrimidine methylation transferase, which is related to the development of human diseases. Accurate identification of m5U modification sites from RNA sequences can contribute to the understanding of their biological functions and the pathogenesis of related diseases. Compared to traditional experimental methods, computational methods developed based on machine learning with ease of use can identify modification sites from RNA sequences in an efficient and time-saving manner. Despite the good performance of these computational methods, there are some drawbacks and limitations. Results: In this study, we have developed a novel predictor, m5U-SVM, based on multi-view features and machine learning algorithms to construct predictive models for identifying m5U modification sites from RNA sequences. In this method, we used four traditional physicochemical features and distributed representation features. The optimized multi-view features were obtained from the four fused traditional physicochemical features by using the two-step LightGBM and IFS methods, and then the distributed representation features were fused with the optimized physicochemical features to obtain the new multi-view features. The best performing classifier, support vector machine, was identified by screening different machine learning algorithms. Compared with the results, the performance of the proposed model is better than that of the existing state-of-the-art tool. Conclusions: m5U-SVM provides an effective tool that successfully captures sequence-related attributes of modifications and can accurately predict m5U modification sites from RNA sequences. The identification of m5U modification sites helps to understand and delve into the related biological processes and functions. [ABSTRACT FROM AUTHOR]

Pain is the main symptom of osteoarthritis, which severely reduces the patients' quality of life. Stimulated neuroinflammation and elevated mitochondrial oxidative stress are associated arthritis pain. In the present study, arthritis model was established by intra-articular injection of complete Freund's adjuvant (CFA) on mice. Knee swelling, pain hypersensitivity and motor disability were observed in CFA-induced mice. In spinal cord, neuroinflammation was triggered and presented as severe infiltration of inflammatory cells and up-regulated expressions of glial fibrillary acidic protein (GFAP), nuclear factor-kappaB (NF-κB), PYD domains-containing protein 3 (NLRP3), cysteinyl aspartate specific proteinase (caspase-1) and interleukin-1 beta (IL-1β). Mitochondrial function was disrupted and characterized as elevated expressions of B-cell lymphoma 2 (Bcl-2)-associated X protein (Bax), dihydroorotate dehydrogenase (DHODH) and cytochrome C (Cyto C), and reduced expressions of Bcl-2 and Mn-superoxide dismutase (Mn-SOD) activity. Meanwhile, as a potential target for pain management, glycogen synthase kinase-3 beta (GSK-3β) activity was up-regulated in CFA induced mice. To explore potential therapeutic options for arthritis pain, GSK-3β inhibitor TDZD-8 was intraperitoneally injected for three days on CFA mice. Animal behavioral tests found that TDZD-8 treatment elevated mechanical pain sensitivity, suppressed spontaneous pain and recovered motor coordination. Morphological and protein expression analysis indicated that TDZD-8 treatment decreased spinal inflammation score and inflammatory related protein levels, recovered mitochondrial related protein levels, and increased Mn-SOD activity. In summary, TDZD-8 treatment inhibits GSK-3β activity, reduces mitochondrial mediated oxidative stress, suppresses spinal inflammasome response, and alleviates arthritis pain. [ABSTRACT FROM AUTHOR]

Background: Norovirus is a leading cause of acute gastroenteritis among children. Previous studies based on symptomatic infections indicated that mutations, rather than recombination drove the evolution of the norovirus ORF2. These characteristics were found in hospital-based symptomatic infections, whereas, asymptomatic infections are frequent and contribute significantly to transmission. Methods: We conducted the first norovirus molecular epidemiology analysis covering both symptomatic and asymptomatic infections derived from a birth cohort study in the northern China. Results: During the study, 14 symptomatic and 20 asymptomatic norovirus infections were detected in 32 infants. Out of the 14 strains that caused symptomatic infections, 12 strains were identified as GII.3[P12], and others were GII.4[P31]. Conversely, 17 asymptomatic infections were caused by GII.4[P31], two by GII.2[P16], and one by GII.4[P16]. Regardless of symptomatic and asymptomatic infections, the mutations were detected frequently in the ORF2 region, and almost all recombination were identified in the RdRp-ORF2 region. The majority of the mutations were located around the predefined epitope regions of P2 subdomain indicating a potential for immune evasion. Conclusion: The role of symptomatic as well as asymptomatic infections in the evolution of norovirus needs to be evaluated continuously. [ABSTRACT FROM AUTHOR]

Typically, relationship between well logs and lithofacies is complex, which leads to low accuracy of lithofacies identification. Machine learning (ML) methods are often applied to identify lithofacies using logs labelled by rock cores. However, these methods have accuracy limits to some extent. To further improve their accuracies, practical and novel ensemble learning strategy and principles are proposed in this work, which allows geologists not familiar with ML to establish a good ML lithofacies identification model and help geologists familiar with ML further improve accuracy of lithofacies identification. The ensemble learning strategy combines ML methods as sub-classifiers to generate a comprehensive lithofacies identification model, which aims to reduce the variance errors in prediction. Each sub-classifier is trained by randomly sampled labelled data with random features. The novelty of this work lies in the ensemble principles making sub-classifiers just overfitting by algorithm parameter setting and subdataset sampling. The principles can help reduce the bias errors in the prediction. Two issues are discussed, videlicet (1) whether only a relatively simple single-classifier method can be as sub-classifiers and how to select proper ML methods as sub-classifiers; (2) whether different kinds of ML methods can be combined as sub-classifiers. If yes, how to determine a proper combination. In order to test the effectiveness of the ensemble strategy and principles for lithofacies identification, different kinds of machine learning algorithms are selected as sub-classifiers, including regular classifiers (LDA, NB, KNN, ID3 tree and CART), kernel method (SVM), and ensemble learning algorithms (RF, AdaBoost, XGBoost and LightGBM). In this work, the experiments used a published dataset of lithofacies from Daniudi gas field (DGF) in Ordes Basin, China. Based on a series of comparisons between ML algorithms and their corresponding ensemble models using the ensemble strategy and principles, conclusions are drawn: (1) not only decision tree but also other single-classifiers and ensemble-learning-classifiers can be used as subclassifiers of homogeneous ensemble learning and the ensemble can improve the accuracy of the original classifiers; (2) the ensemble principles for the introduced homogeneous and heterogeneous ensemble strategy are effective in promoting ML in lithofacies identification; (3) in practice, heterogeneous ensemble is more suitable for building a more powerful lithofacies identification model, though it is complex. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the diagnostic performance of the histogram array and convolutional neural network (CNN) based on diffusion-weighted imaging (DWI) with multiple b-values under magnetic resonance imaging (MRI) to distinguish pancreatic ductal adenocarcinomas (PDACs) from solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine neoplasms (PNENs). This retrospective study consisted of patients diagnosed with PDACs (n = 132), PNENs (n = 45) and SPNs (n = 54). All patients underwent 3.0-T MRI including DWI with 10 b values. The regions of interest (ROIs) of pancreatic tumor were manually drawn using ITK-SNAP software, which included entire tumor at DWI (b = 1500 s/m2). The histogram array was obtained through the ROIs from multiple b-value data. PyTorch (version 1.11) was used to construct a CNN classifier to categorize the histogram array into PDACs, PNENs or SPNs. The area under the curves (AUCs) of the histogram array and the CNN model for differentiating PDACs from PNENs and SPNs were 0.896, 0.846, and 0.839 in the training, validation and testing cohorts, respectively. The accuracy, sensitivity and specificity were 90.22%, 96.23%, and 82.05% in the training cohort, 84.78%, 96.15%, and 70.0% in the validation cohort, and 81.72%, 90.57%, and 70.0% in the testing cohort. The performance of CNN with AUC of 0.865 for this differentiation was significantly higher than that of f with AUC = 0.755 (P = 0.0057) and α with AUC = 0.776 (P = 0.0278) in all patients. The histogram array and CNN based on DWI data with multiple b-values using MRI provided an accurate diagnostic performance to differentiate PDACs from PNENs and SPNs. • CNN is proposed to differentiate PDACs from non-PDACs by converting DWI into an image of histogram array. • AUCs of histogram array and CNN for diagnosing PDACs are 0.896, 0.846, and 0.839 in training, validating and testing cohorts. • The performance of histogram array and CNN for diagnosing PDACs is higher than that of DWI parameters in all patients. [ABSTRACT FROM AUTHOR]

In the conceptual frame of "One Health", the safety crisis caused by various toxicological issues due to chemical exposure is of great concern. The urgent demand for environmentally safe chemicals is increasing the awareness of the importance of designing non-toxic chemical molecules. The expanding toxicological data can provide a foundation for studying interactions between the living organisms and environment. However, a large amount of toxicological data is fragmented and scattered in the literature and online resources. Thus, to promote the more efficient use of toxicological information, further collection and collation of the current toxicity data is urgent. In the present review, we discuss the application of existing toxicological data to support environmental risk assessment and guide green chemical design. The importance of chemical toxicity data for human health and ecological risk assessment, trends of available chemical toxicity data, details of the common structural features associated with different toxicity endpoints, and applications of toxicological big data in toxicity prediction combined with artificial intelligence are described and discussed. Additionally, based on the systematic collection and analysis of the current toxicity data, a reorganized toxicological databank is provided to cover a wider range of organic chemicals and tested species. It is expected that this work can contribute to the study of organic structural toxicity, chemical toxicity prediction, environmental risk assessment, and safer chemical design. [ABSTRACT FROM AUTHOR]

Steel fiber-reinforced ultra-high-performance concrete (UHPC) is becoming an important type of concrete reinforcement. After mixing with the reinforced steel fibers, the UHPC has perfect flex resistance, shear strength, crack resistance, shock resistance, and anti-seepage. In this study, the influence of straight, corrugated, and hooked brass-coated steel fibers (BCSFs) on the microstructure, mechanical properties, and crack expansion mechanism of ultra-high-performance concrete (UHPC) with varying content of 1–6 wt.% under different curing times were investigated. Field emission scanning electron microscopy and energy dispersive X-ray spectrometry were employed to characterize the microstructure of the BCSF-reinforced UHPC mix specimens. X-ray computed tomography was employed to determine the porosity of the BCSF-reinforced UHPC mix specimens. The obtained results indicate the flexural strength and compressive strength of BCSF-reinforced UHPC mix specimens are enhanced, along with increasing the content of BCSFs reinforcement with different shapes (straight, corrugated, and hooked). The embedded BCSFs play a major role in the adhesive property and stress transfer of the BCSFs–UHPC matrix interface. Different from many studies, the flexural strength of mix UHPC with straight BCSFs is higher than those with corrugated and hooked BCSFs. However, the compressive strength of UHPC with corrugated BCSFs is higher than those with straight and hooked BCSFs. The flexural strength of mix UHPC with 6 wt.% straight BCSFs at 28 days reaches the maximum value of 26.2 MPa, and the compressive strength of UHPC with 6 wt.% corrugated BCSFs at 28 days reaches the maximum value of 142.3 MPa. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the porosity in mix UHPC reduces gradually from 18.4% to 8.3%. The length of average crack spacing is dependent on the straight BCSF content. With the increase in straight BCSF content from 1 wt.% to 6 wt.%, the average crack length reduces gradually from 34.2 mm to 12.1 mm, and the average crack width reduces gradually from 0.78 mm to less than 0.1 mm. During crack extension, part of the energy in the UHPC mixture specimen with the 6 wt.% BCSF content flows into the crack tip region converted into the work dissipated during the bridging process. The crack propagation resistance of the UHPC mixture with straight BCSFs was improved compared with those with corrugated and hooked BCSFs. The bond strength between the BCSFs and UHPC matrix was enhanced by using vibrational mixing, and the brass film coated on the BCSFs contributes to increase the flexural and compressive strength of the UHPC mixture. [ABSTRACT FROM AUTHOR]

Repopulation of residual tumor cells impedes curative radiotherapy, yet the mechanism is not fully understood. It is recently appreciated that cancer cells adopt a transient persistence to survive the stress of chemo-or targeted therapy and facilitate eventual relapse. Here, it is shown that cancer cells likewise enter a "radiation-tolerant persister" (RTP) state to evade radiation pressure in vitro and in vivo. RTP cells are characterized by enlarged cell size with complex karyotype, activated type I interferon pathway and two gene patterns represented by CST3 and SNCG. RTP cells have the potential to regenerate progenies via viral budding-like division, and type I interferon-mediated antiviral signaling impaired progeny production. Depleting CST3 or SNCG does not attenuate the formation of RTP cells, but can suppress RTP cells budding with impaired tumor repopulation. Interestingly, progeny cells produced by RTP cells actively lose their aberrant chromosomal fragments and gradually recover back to a chromosomal constitution similar to their unirradiated parental cells. Collectively, this study reveals a novel mechanism of tumor repopulation, i.e., cancer cell populations employ a reversible radiation-persistence by poly- and de-polyploidization to survive radiotherapy and repopulate the tumor, providing a new therapeutic concept to improve outcome of patients receiving radiotherapy. [ABSTRACT FROM AUTHOR]