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Abstract Interleukin-18, a member of the interleukin − 1 family of cytokines, is upregulated in glioma. However, its effects on glioma remain unclear. This study aimed to explore the role and underlying mechanisms of interleukin-18 expression in glioma. Here, we demonstrated that interleukin-18 enhanced resistance to temozolomide by increasing proliferation and inhibiting apoptosis in cultured glioma cells. Further in vivo studies revealed that interleukin-18 promoted temozolomide resistance in BALB/c nude mice bearing tumor. Mechanical exploration indicated that interleukin-18 stimulation could activate the PI3K/AKT signaling pathway in glioma cells, and PI3K inhibition could reduce the temozolomide resistance promoted by interleukin-18. We found that interleukin-18 upregulated CD274 expression in glioma, revealing its potential effects on the microenvironment. Furthermore, we established a tumor xenograft model and explored the therapeutic efficacy of anti-interleukin-18 monoclonal antibody. Targeting interleukin-18 prolonged survival and attenuated CD274 expression in the mice bearing tumor. Combined treatment with anti-interleukin-18 and anti-PD-1 monoclonal antibody showed better efficacy in suppressing tumor growth than either treatment alone in mice bearing tumor. Collectively, these data present that interleukin-18 promotes temozolomide chemoresistance in glioma cells via PI3K/Akt activation and establishes an immunosuppressive milieu by modulating CD274. This study highlights the therapeutic value of interleukin-18 in glioma.

Abstract Background Influenza outbreaks have occurred frequently these years, especially in the summer of 2022 when the number of influenza cases in southern provinces of China increased abnormally. However, the exact evidence of the driving factors involved in the prodrome period is unclear, posing great difficulties for early and accurate prediction in practical work. Methods In order to avoid the serious interference of strict prevention and control measures on the analysis of influenza influencing factors during the COVID-19 epidemic period, only the impact of meteorological and air quality factors on influenza A (H3N2) in Xiamen during the non coronavirus disease 2019 (COVID-19) period (2013/01/01-202/01/24) was analyzed using the distribution lag non-linear model. Phylogenetic analysis of influenza A (H3N2) during 2013–2022 was also performed. Influenza A (H3N2) was predicted through a random forest and long short-term memory (RF-LSTM) model via actual and forecasted meteorological and influenza A (H3N2) values. Results Twenty nine thousand four hundred thirty five influenza cases were reported in 2022, accounting for 58.54% of the total cases during 2013–2022. A (H3N2) dominated the 2022 summer epidemic season, accounting for 95.60%. The influenza cases in the summer of 2022 accounted for 83.72% of the year and 49.02% of all influenza reported from 2013 to 2022. Among them, the A (H3N2) cases in the summer of 2022 accounted for 83.90% of all A (H3N2) reported from 2013 to 2022. Daily precipitation(20–50 mm), relative humidity (70–78%), low (≤ 3 h) and high (≥ 7 h) sunshine duration, air temperature (≤ 21 °C) and O3 concentration (≤ 30 µg/m3, > 85 µg/m3) had significant cumulative effects on influenza A (H3N2) during the non-COVID-19 period. The daily values of PRE, RHU, SSD, and TEM in the prodrome period of the abnormal influenza A (H3N2) epidemic (19–22 weeks) in the summer of 2022 were significantly different from the average values of the same period from 2013 to 2019 (P

To reveal the mechanism of shear failure of en-echelon joints under cyclic loading, such as during earthquakes, we conducted a series of cyclic shear tests of en-echelon joints under constant normal stiffness (CNS) conditions. We analyzed the evolution of shear stress, normal stress, stress path, dilatancy characteristics, and friction coefficient and revealed the failure mechanisms of en-echelon joints at different angles. The results show that the cyclic shear behavior of the en-echelon joints is closely related to the joint angle, with the shear strength at a positive angle exceeding that at a negative angle during shear cycles. As the number of cycles increases, the shear strength decreases rapidly, and the difference between the varying angles gradually decreases. Dilation occurs in the early shear cycles (1 and 2), while contraction is the main feature in later cycles (3−10). The friction coefficient decreases with the number of cycles and exhibits a more significant sensitivity to joint angles than shear cycles. The joint angle determines the asperities on the rupture surfaces and the block size, and thus determines the subsequent shear failure mode (block crushing and asperity degradation). At positive angles, block size is more greater and asperities on the rupture surface are smaller than at nonpositive angles. Therefore, the cyclic shear behavior is controlled by block crushing at positive angles and asperity degradation at negative angles.

Abstract At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) specimens. We used metatranscriptome to analyze the lower respiratory tract microbiome (LRTM) and host immune response. The diversity of the LRTM in LRTIs significantly decreased, manifested by a decrease in the abundance of normal microbiota and an increase in the abundance of opportunistic pathogens. The upregulated differentially expressed genes (DEGs) in the LRTIs group were mainly enriched in infection immune response-related pathways. Klebsiella pneumoniae had the most significant increase in abundance in LRTIs, which was strongly correlated with host infection or inflammation genes TNFRSF1B, CSF3R, and IL6R. We combined LRTM and host transcriptome data to construct a machine-learning model with 12 screened features to discriminate LRTIs and non-LRTIs. The results showed that the model trained by Random Forest in the validate set had the best performance (ROC AUC: 0.937, 95% CI: 0.832–1). The independent external dataset showed an accuracy of 76.5% for this model. This study suggests that the model integrating LRTM and host transcriptome data can be an effective tool for LRTIs diagnosis.

Objectives: Hypervirulent carbapenem-resistant Klebsiella pneumoniae (hv-CRKp) poses a significant threat to public health. This study reports an infection related to hv-CRKp in a premature infant and reveals its colistin resistance and evolutionary mechanisms within the host. Methods: Three KPC-producing CRKp strains were isolated from a patient with sepsis and CRKp osteoarthritis who had been receiving colistin antimicrobial therapy. The minimum inhibitory concentrations (MICs) of ceftazidime, ceftazidime-avibactam (CAZ-AVI), meropenem, imipenem, tigecycline, amikacin, minocycline, sulfamethoxazole/trimethoprim, ciprofloxacin, levofloxacin, aztreonam, cefepime, cefoperazone/sulbactam, piperacillin/tazobactam, and colistin were determined using the microbroth dilution method. The whole-genome sequencing analysis was conducted to determine the sequence types (STs), virulence genes, and antibiotic resistance genes of the three CRKp strains. Results: Whole-genome sequencing revealed that all three CRKp strains belonged to the ST11 clone and carried a plasmid encoding blaKPC-2. The three strains all possessed the iucABCDiutA virulence cluster, peg-344 gene, and rmpA/rmpA2 genes, defining them as hv-CRKp. Further experiments and whole-genome analysis revealed that a strain of K. pneuomniae had developed resistance to colistin. The mechanism found to be responsible for colistin resistance was a deletion mutation of approximately 9000 bp including the mgrB gene. Conclusion: This study characterizes colistin resistance of the ST11 clone hv-CRKp during colistin treatment and its rapid evolution within the host.

Abstract Clinical metagenomics (CMg) Nanopore sequencing can facilitate infectious disease diagnosis. In China, sub-lineages ST11-KL64 and ST11-KL47 Carbapenem-resistant Klebsiella pneumoniae (CRKP) are widely prevalent. We propose PathoTracker, a specially compiled database and arranged method for strain feature identification in CMg samples and CRKP traceability. A database targeting high-prevalence horizontal gene transfer in CRKP strains and a ST11-only database for distinguishing two sub-lineages in China were created. To make the database user-friendly, facilitate immediate downstream strain feature identification from raw Nanopore metagenomic data, and avoid the need for phylogenetic analysis from scratch, we developed data analysis methods. The methods included pre-performed phylogenetic analysis, gene-isolate-cluster index and multilevel pan-genome database and reduced storage space by 10-fold and random-access memory by 52-fold compared with normal methods. PathoTracker can provide accurate and fast strain-level analysis for CMg data after 1 h Nanopore sequencing, allowing early warning of outbreaks. A user-friendly page ( http://PathoTracker.pku.edu.cn/ ) was developed to facilitate online analysis, including strain-level feature, species identifications and phylogenetic analyses. PathoTracker proposed in this study will aid in the downstream analysis of CMg.

To investigate the inhibitory effects and mechanism of ε-poly-L-lysine (ε-PL) against the Lasiodiplodia theobromae causing fruit rot on postharvest passions, the changes of L. theobromae mycelial growth, conductivity, malonaldehyde content, intracellular materials leakage, contents of cell membrane and cell wall components, adenosine triphosphatase activity, propidium iodide staining, and Fourier transform infrared spectroscopy were determined after being treated with ε-PL, and the inhibition effects of ε-PL on L. theobromae-induced fruit rot of harvested passion fruits were studied. In vitro assay showed that ε-PL inhibited the mycelial growth of L. theobromae, and the inhibitory effects increased with increasing ε-PL concentration. The optimal inhibitory concentration of ε-PL was 10 mg/mL. Additionally, ε-PL might increase the conductivity and malondialdehyde content, promote the leakage of intercellular nucleic acid and protein, decrease the contents of ergosterol, total lipids and chitin, reduce the activity of adenosine triphosphate. Moreover, ε-PL also changed the mycelial morphology of L. theobromae, resulting in the mycelial distortion, and lowered the number of methylene, methyl, hydroxyl and carbon-oxygen bonds in mycelium of L. theobromae. Furthermore, ε-PL could suppress the L. theobromae-induced fruit rot development of harvested passion fruits. Therefore, ε-PL could display the antifungal activity on L. theobromae through destroying the structure of cell membrane and cell wall, promoting the leakage of intracellular materials, disordering the energy metabolism, and destroying the structure of biological macromolecules.

Abstract Background Haematological patients exhibit immune system abnormalities that make them susceptible to viral infections. Understanding the relationship between the virome in the blood plasma of haematological patients and their clinical characteristic is crucial for disease management. We aimed to explore the presence of viral pathogens and identify close associations between viral infections and various clinical features. Results A total of 21 DNA viruses and 6 RNA viruses from 12 virus families were identified from 1383 patients. Patients with haematological diseases exhibited significantly higher diversity, prevalence, and co-detection rates of viral pathogens. During fever episodes, pathogen detection was notably higher, with Epstein-Barr virus (EBV) and Mucorales infections being the most probable culprits for fever symptoms in non-haematological patients. The detection rate of torque teno virus (TTV) significantly increases in haematological patients after transplantation and during primary lung infections. Additionally, TTV-positive patients demonstrate significantly higher absolute neutrophil counts, while C-reactive protein and procalcitonin levels are notably lower. Furthermore, TTV, cytomegalovirus, and parvovirus B19 (B19V) were found to be more prevalent in non-neutropenic patients, while non-viral pathogenic infections, such as Gram-negative bacteria and Mucorales, were more common in neutropenic patients. Pegivirus C (HPgV-C) infection often occurred post-transplantation, regardless of neutropenia. Additionally, some viruses such as TTV, B19V, EBV, and HPgV-C showed preferences for age and seasonal infections. Conclusions Analysis of the plasma virome revealed the susceptibility of haematological patients to plasma viral infections at specific disease stages, along with the occurrence of mixed infections with non-viral pathogens. Close associations were observed between the plasma virome and various clinical characteristics, as well as clinical detection parameters. Understanding plasma virome aids in auxiliary clinical diagnosis and treatment, enabling early prevention to reduce infection rates in patients and improve their quality of life. Video Abstract

BackgroundThe Epithelial–Mesenchymal Transition (EMT) is a very important process involved in cancer invasion and metastasis. Additionally, the Cathepsin K (CTSK) gene is closely related to the degradation of the extracellular matrix, which is a critical component of the EMT. The purpose of this study was to determine the relationships between EMT-related genes and immune cell infiltration and their prognostic value in Thyroid carcinoma (THCA). The effect of the CTSK gene on the aggressive biological features of THCA was assessed.MethodsWithin the framework of the present study, the THCA cohort was analyzed in detail based on data obtained from The TCGA database in the context of the EMT. The TCGA-THCA cohort was then divided into two groups, namely, high- and low-risk groups, based on the calculated EMT scores. Finally, based on the findings from the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm, LASSO regression analysis, and Kaplan−Meier plotter, we selected five genes (CTSK, C3ORF80, FBLN2, PRELP and SRPX2) associated with patient prognosis. Furthermore, this study examined the presence of various immune cells within the THCA samples using three distinct algorithms, namely ssGSEA, xCell, and MCPcounter. Additional studies have been conducted to establish the roles of CTSK in THCA cell proliferation and migration using various assays, such as CCK8, colony formation, EdU proliferation, Transwell migration and wound healing assays. Additionally, the involvement of CTSK in the regulation of various EMT-related markers was confirmed using Western blot analysis.ResultsBased on EMT scores, TCGA-THCA patients were further divided into two groups, and the study revealed that patients in the high-risk group had a worse prognosis than those in the low-risk group. Among the five genes linked to the prognostic value of EMT (CTSK, C3ORF80, FBLN2, PRELP, and SRPX2), CTSK exhibited notably elevated expression in the high-risk cohort. This group also exhibited pronounced immune cell infiltration, with a marked correlation observed between CTSK expression and the levels of macrophages, MDSCs, and various T-cell subtypes. Furthermore, in vitro studies demonstrated that reducing CTSK expression led to significant reductions in THCA cell viability; clonogenic, proliferative, motility and migratory capacities; and the expression of key EMT-related proteins, including N-cadherin, vimentin, slug, and snail.ConclusionOur results suggest that the expression of CTSK, a gene associated with the EMT, may be associated with THCA onset and progression and thus may serve as a promising prognostic biomarker.

Cyclic shear tests on rock joints serve as a practical strategy for understanding the shear behavior of jointed rock masses under seismic conditions. We explored the cyclic shear behavior of en-echelon and how joint persistence and test conditions (initial normal stress, normal stiffness, shear velocity, and cyclic distance) influence it through cyclic shear tests under CNS conditions. The results revealed a through-going shear zone induced by cyclic loads, characterized by abrasive rupture surfaces and brecciated material. Key findings included that increased joint persistence enlarged and smoothened the shear zone, while increased initial normal stress and cyclic distance, and decreased normal stiffness and shear velocity, diminished and roughened the brecciated material. Shear strength decreased across shear cycles, with the most significant reduction in the initial shear cycle. After ten cycles, the shear strength damage factor D varied from 0.785 to 0.909. Shear strength degradation was particularly sensitive to normal stiffness and cyclic distance. Low joint persistence, high initial normal stress, high normal stiffness, slow shear velocity, and large cyclic distance were the most destabilizing combinations. Cyclic loads significantly compressed en-echelon joints, with compressibility highly dependent on normal stress and stiffness. The frictional coefficient initially declined and then increased under a rising cycle number. This work provides crucial insights for understanding and predicting the mechanical response of en-echelon joints under seismic conditions.

Summary: Background: Shotgun metagenomic next-generation sequencing (mNGS) is widely used to detect pathogens in bronchoalveolar lavage fluid (BALF). However, mNGS is complex and expensive. This study explored the feasibility of targeted next-generation sequencing (tNGS) in distinguishing lower respiratory tract infections in clinical practice. Methods: We used 229 retrospective BALF samples to establish thresholds and diagnostic values in a prospective cohort of 251 patients. After target pathogen selection, primer and probe design, optimization experiments, and bioinformatics analysis, multiplex PCR-based tNGS (mp-tNGS) and hybrid capture-based tNGS (hc-tNGS), targeting 198 and 3060 pathogens (DNA and RNA co-detection workflow) were established and performed. Findings: mp-tNGS and hc-tNGS took 10.3 and 16 h, respectively, with low sequencing data sizes of 0.1 M and 1 M reads, and test costs reduced to a quarter and half of mNGS. The LoDs of mp-tNGS and hc-tNGS were 50–450 CFU/mL. mp-tNGS and hc-tNGS were highly accurate, with 86.5% and 87.3% (vs. 85.5% for mNGS) sensitivities and 90.0% and 88.0% (vs. 92.1% for mNGS) specificities. tNGS detection rates for casual pathogens were 84.3% and 89.5% (vs. 88.5% for mNGS), significantly higher than conventional microbiological tests (P

Background and aim: A genome-wide association study has indicated the association of numerous genes in the 6p21.3 region with chronic hepatitis B virus (HBV) infection. In this study, we screened 12 representative single-nucleotide polymorphisms (SNPs) from the 6p21.3 region and investigated their association with the risk of chronic hepatitis B (CHB) to better understand the molecular etiology underlying CHB risk in the Han Chinese population. Methods: Between March 2021 and November 2022, we included 183 patients with CHB (case group) and 196 with natural HBV clearance (control group). Allele typing of the selected SNPs was performed using snapshot technology. The correlation between the 12 chosen SNPs and the risk of chronic HBV infection was examined using binary logistic regression analysis. Interacting genes of the variants were identified, and expression quantitative trait loci (eQTL) were analyzed using the 3DSNP database. Results: We validated 12 previously reported CHB susceptibility sites, including rs1419881 of transcription factor 19 (TCF19), rs3130542 and rs2853953 of human leukocyte antigen (HLA)-C, rs652888 of euchromatic histone-lysine-methyltransferase 2 (EHMT2), rs2856718, rs9276370, rs7756516, and rs7453920 of HLA-DQ, rs378352 of HLA-DOA, and rs3077, rs9277535, and rs9366816 of HLA-DP. Logistic regression analyses revealed that polymorphisms such as rs9276370, rs7756516, rs7453920, rs3077, rs9277535, and rs9366816 were positively correlated with natural HBV clearance in the dominant model. Conversely, rs3130542 and rs378352 were identified as risk factors for CHB. Haplotype analysis revealed that rs9276370, rs7756516, and rs7453920 in HLA-DQ were TTG and GCA haplotypes. Although the TTG haplotype was positively correlated with a higher risk of CHB, the GCA haplotype significantly influenced the natural clearance of HBV. Bioinformatics analysis demonstrated that rs378352, rs3077, and rs9366816 were located within enhancer states; rs3077 and rs9366816 overlapped with nine transcription factor-binding sites, whereas rs378352 altered five sequence motifs. Furthermore, eQTL analysis demonstrated the functional tendencies of eight statistically significant SNPs (rs3130542, rs9276370, rs7756516, rs7453920, rs378352, rs3077, rs9277535, and rs9366816). Conclusions: Genetic variations within the 6p21.3 region were associated with chronic HBV infection in the Han Chinese population in southern China. Furthermore, the GCA haplotype including rs9276370, rs7756516, and rs7453920 of HLA-DQ contributed significantly to natural HBV clearance, implying that multiple SNPs exert a cumulative allelic effect on HBV infection.

Q fever is a worldwide distribution disease caused by Coxiella burnetii（C. burnetii）, an obligate intracellular, Gram-negative acidophilic bacterium belonging to γ-proteobacterium. Most patients present with acute Q-fever accompanied by atypical flu-like symptoms, with only 1%–5% of cases may develop into persistent and focally infected foci, mainly manifest as endocarditis, osteomyelitis and prosthetic arthritis. In this case, the patient experienced an unexplained and uninterrupted fever up to 39.2 °C for a week, accompanied by chills and headaches, as well as abnormal liver function. The laboratory reported negative results for blood culture and respiratory-associated pathogens, however, the metagenomic next-generation sequencing (mNGS) reported that detection of 20 sequence reads of C. burnetii in the patient's peripheral blood. In addition, the patient had traveled to Sri Lanka, Iraq and Saudi Arabia before illness. In clinical, the treatment regimen was adjusted from empirically intravenous moxifloxacin 400 mg a day for 1 week to continuously oral minocyline 100 mg twice daily for 2 weeks. The patient was in good health without any adverse sequelae during outpatient visitation and the phone calls follow-up. In conclusion, the mNGS does provide an early and timely diagnostic basis for rare and difficult to culture pathogens, which contributes to the success of clinical anti-infection.

Summary: Klebsiella pneumoniae carbapenemase (KPC) poses a major public health risk. Understanding its transmission dynamics requires examining the epidemiological features of related plasmids. Our study compiled 15,660 blaKPC-positive isolates globally over the past two decades. We found extensive diversity in the genetic background of KPC, with 23 Tn4401-related and 341 non-Tn4401 variants across 163 plasmid types in 14 genera. Intra-K. pneumoniae and cross-genus KPC transmission patterns varied across four distinct periods. In the initial periods, plasmids with narrow host ranges gradually established a survival advantage. In later periods, broad-host-range plasmids became crucial for cross-genera transmission. In total, 61 intra-K. pneumoniae and 66 cross-genus transmission units have been detected. Furthermore, phylogenetic reconstruction dated the origin of KPC transmission back to 1991 and revealed frequent exchanges across countries. Our research highlights the frequent and transient spread events of KPC mediated by plasmids across multiple genera and offers theoretical support for high-risk plasmid monitoring.

In this paper, we investigate a hybrid satellite-unmanned aerial vehicle (UAV) relay network (HSURN) with rate splitting multiple access (RSMA), where the terminal transmits a superposition of the common and private signals with different power levels, and the UAV operates in half-duplex decode-and-forward (DF) mode to assist communication between terminals and satellites. With the RSMA scheme, we investigate the joint optimization problem of terminal-UAV association (TUA) and power allocation (PA) of both the terminals and UAVs for the common and private signals under the constraint of limited resources to maximize the achievable sum rate. Given the non-convexity of the original problem, it is decoupled into two subproblems. The TUA subproblem is solved via deep Q-network (DQN). The PA subproblem is solved by successive convex approximation (SCA) and Lagrange dual approach. Afterward, an alternate iterative algorithm is developed by iteratively performing the outputs of two subproblems. Numerical results verify that compared with the traditional transmission schemes, our proposed RSMA scheme is more beneficial to information transmission. Compared with the existing algorithms, the proposed algorithm can achieve the flexible association between UAV and the serviced terminal by adjusting the splitting strategy of common and private signals in dynamic network environment.

With the advent of the fifth-generation (5G) and beyond mobile communications, a plethora of Internet-of-Things (IoTs) applications, such as intelligent factories, smart transportation, and others are rapidly evolving. 5G and beyond networks support three typical application scenarios, i.e., ultra-reliable and low-latency communications (URLLC), enhanced mobile broadband (eMBB) and massive machine type communication (mMTC), each of which renders a distinct set of quality of service in terms of reliability, latency, transmission rate and connectivity. URLLC is seen as a crucial technology for supporting critical applications because of its emphasis on rare and extreme events, as well as its strict demands for low latency and high reliability [1]. For example, in order to effectively support applications like robot control, autonomous vehicles, and virtual reality, it is necessary to have an end-to-end delay threshold of 1 to 10 milliseconds and a block error rate (BLER) between 10−5 and 10−7 [2]. Due to the unique limitations of increased reliability and reduced latency, URLLC traffic often involves very brief transmission blocklengths, making Shannon’s capacity theorem irrelevant [3], [4]. On the other hand, existing cellular systems face difficulties in meeting the stringent quality of service (QoS) criteria needed for URLLC due to structural constraints. Therefore, it is essential to have advanced network architectures and various access technologies in order to achieve URLLC.

Introduction: Previous studies have evaluated metagenomic next-generation sequencing (mNGS) of cell-free DNA (cfDNA) for pathogen detection in blood and body fluid samples. However, no study has assessed the diagnostic efficacy of mNGS using cellular DNA. Objectives: This is the first study to systematically evaluate the efficacy of cfDNA and cellular DNA mNGS for pathogen detection. Methods: A panel of seven microorganisms was used to compare cfDNA and cellular DNA mNGS assays concerning limits of detection (LoD), linearity, robustness to interference, and precision. In total, 248 specimens were collected between December 2020 and December 2021. The medical records of all the patients were reviewed. These specimens were analysed using cfDNA and cellular DNA mNGS assays, and the mNGS results were confirmed using viral qPCR, 16S rRNA, and internal transcribed spacer (ITS) amplicon next-generation sequencing. Results: The LoD of cfDNA and cellular DNA mNGS was 9.3 to 149 genome equivalents (GE)/mL and 27 to 466 colony-forming units (CFU)/mL, respectively. The intra- and inter-assay reproducibility of cfDNA and cellular DNA mNGS was 100%. Clinical evaluation revealed that cfDNA mNGS was good at detecting the virus in blood samples (receiver operating characteristic (ROC) area under the curve (AUC), 0.9814). In contrast, the performance of cellular DNA mNGS was better than that of cfDNA mNGS in high host background samples. Overall, the diagnostic efficacy of cfDNA combined with cellular DNA mNGS (ROC AUC, 0.8583) was higher than that of cfDNA (ROC AUC, 0.8041) or cellular DNA alone (ROC AUC, 0.7545). Conclusion: Overall, cfDNA mNGS is good for detecting viruses, and cellular DNA mNGS is suitable for high host background samples. The diagnostic efficacy was higher when cfDNA and cellular DNA mNGS were combined.

The efficiency of collecting and distributing goods has been improved by establishing railway lines that serve new automated container terminals (ACTs) and by constructing central railway stations close to ports. To aid in this process, intelligent guided vehicles (IGVs), which are renowned for their flexibility and for the convenience with which one can adjust their number and speed, have been developed to be used as horizontal transport vehicles that can transport goods between the railway yard and the front of the port. However, they also introduce some difficulties and complexities that affect terminal scheduling. Therefore, we took the automated rail-mounted container gantry crane (ARMG) scheduling problem as our main research object in this study. We established a mixed-integer linear programming (MILP) model to minimize the makespan of ARMGs, designed an adaptive large neighborhood search (ALNS) algorithm, and explored the influence of IGV configuration on ARMG scheduling through a series of experiments applied to a series of large-scale numerical examples. The experimental results show that increasing the number of IGVs can improve the operational efficiency of railway yards, but this strategy reduces the overall time taken for the ARMG to complete various tasks. Increasing or decreasing the speed of the IGVs within a given range has a clear effect on the problem at hand, while increasing the IGV travel speed can effectively reduce the time required for the ARMG to complete various tasks. Operators must properly adjust the IGV speed to meet the requirements of the planned operation.

Shale oil is mainly stored in the nano–micro-pores of shale in the form of adsorption or in a free state. Among them, only free-state oil is the main contributor to shale oil production under natural elastic energy. Therefore, it is crucial to evaluate the movability of crude oil effectively. In this paper, focusing on the Jurassic shale oil reservoir core in the middle-eastern Sichuan region of China, low-field nuclear magnetic resonance (NMR) technology is used to analyze the basic characteristics of shale oil core samples. Experiments on the low-field NMR one-dimensional and two-dimensional spectrum characteristics of the original core, heat-treated core, and thermogravimetric-treated shale core are carried out. The effects of the TG-MS method, T2 method, and the volatilization of light oil components on the movability of shale oil reservoirs are analyzed, and the movability characteristics of shale oil reservoirs in the middle-eastern Sichuan region are preliminarily clarified. The results show that under thermal treatment, the distribution range of the two-dimensional spectrum of the core oil occurrence area is significantly reduced, and the T1 and T2 distribution ranges are reduced by 10.9% and 60.7%, respectively. According to the TG-MS method, the mobile oil, bound oil, and adsorbed oil account for 74.7%, 8.1%, and 17.2%, respectively. The quantitative calculation of movable oil saturation by NMR combined with heat treatment is 65.6%, which is lower than that calculated using the thermogravimetric method. In order to calculate the movability more accurately, the scale effect between different samples should be considered. This study could provide a theoretical basis for the subsequent shale oil development program.

Objective: To investigate the optimal process for preparing peppermint essential oil/β-cyclodextrin (β-CD) inclusion complex using high-speed shearing combined with freeze-drying. Methods: The effects of freeze-drying and vacuum drying, high-speed shearing, and stirring on the encapsulation process were compared. Based on single-factor experiments, the ratio of β-CD to essential oil, encapsulation temperature, and mass fraction of β-CD were considered as influencing factors. The comprehensive score of oil content and encapsulation efficiency was used as an evaluation index to investigate the Box-Behnken response surface method for optimizing the encapsulation process. The content of pulegone in the inclusion complex was measured by high-performance liquid chromatography (HPLC). Fourier transform infrared spectroscopy (FTIR) was used to characterize the inclusion complex. Results: The yield of inclusion complex prepared by freeze-drying was higher, with an average yield of 97.6%. The oil content and encapsulation efficiency by the high-speed shearing method were relatively high, being about 3% and 19% higher than those by the stirring method, respectively. The optimized conditions were as follows: The weight ratio of β-CD to volatile oil was 9:1 (g/mL), the encapsulation temperature was 55 ℃, and the mass fraction of β-CD was 17%. Under these conditions, the essential oil content was 10.9%, the encapsulation efficiency was 97.6%, the comprehensive score was 99.7, the RSD value was 1.59%, and the optimized process was stable and feasible. The content of pulegone in the inclusion complex was found to be 2.465 mg/g by HPLC. The formation of the peppermint oil/β-CD inclusion complex was confirmed by analysis using FTIR. Conclusion: The combination of high-speed shearing and freeze-drying for the preparation of peppermint essential oil inclusion complex had the advantages of high efficiency, simple process, and it improved theyield, would provide guidance for the production process.

In some automated container terminals, railway lines have been implemented into the port, saving container transfer time. However, the equipment scheduling level of the railway yard needs to be improved for managers. In the equipment scheduling of loading and unloading containers for railway trains, the operation modes “full unloading and full loading” and “synchronous loading and unloading” are often adopted. Due to the long length of the railway yard and the line of one train, there are two ways to arrange loading and unloading tasks for automated rail-mounted gantry cranes (ARMGs): one is to pre-assign tasks for ARMGs, and the other is to not pre-assign tasks for ARMGs. To investigate the efficacy of these different operation modes and methods of assigning tasks, this study formulated three mixed-integer linear programming (MILP) models with the goal of minimizing the ARMG task completion time. An adaptive large neighborhood search algorithm was used to tackle the scheduling problem. The scheduling effects of different operation modes and methods for assignment tasks were compared in terms of their calculation time and the completion time of ARMG tasks. Notably, the findings reveal that, with an increase in the number of tasks, the “pre-assign” task arrangement had a limited effect on the completion time of the ARMG tasks, made the calculation time shorter, and reduced the complexity of the problem. From the perspective of the completion time of ARMG tasks, the time under the “synchronous loading and unloading” operation mode was less than that of the “full unloading and full loading” operation mode. Therefore, it is recommended that the managers of the railway yard in an automated container terminal adopt the “synchronous loading and unloading” operation mode but determine the task assignment method according to decision time requirements. In addition, when the number of tasks is large, to decrease the time to complete ARMG tasks, the manager can adopt the “non-pre-assign” task distribution method.

Clear-air echo studies are usually based on isotropic turbulence theory. But the theory has been considered incomplete by modern turbulence theory. The intermittence of turbulence can reveal obvious shortcomings in the existing studies of clear-air echoes. The mechanism of clear-air echo scattering needs to be supplemented. This paper introduces the troposcatter theory, normally used in over-the-horizon communication, to fill the gap left by Bragg scattering. By treating radar as a self-transmitted and self-received device, the equivalent transmission loss of weather radar is established and compared with the recommendations of the Radiocommunication Sector of the International Telecommunication Union (ITU-R). The results show that the S-band radar transmission loss aligns with ITU-R recommendations. There is also a linear regression relationship between the radar transmission loss and height, which conforms to the troposcatter theory. This means that the theory of troposcatter scattering is a supplement to the theory of Bragg scattering. Tropospheric scattering can be thought of as general Bragg scattering. Meanwhile, based on ITU-R recommendations, this study also provides a new way for the recognition of biological echoes.

Meteorological radars, as remote sensing instruments, play a vital role in observing clouds and precipitation. However, due to the complexity of hydrometeors in shape, density, diameter, orientation, and particle size distributions, accurate quantification of the inner microphysical characteristics of a cloud/precipitation system is challenging for a single-frequency radar. Recently, the advancement in scattering theory of hydrometeors, computer science, and hardware manufacturing (such as millimeter-wave devices) has stimulated the application of multi-frequency radars, bringing novel observations for an improved understanding of cloud and precipitation microphysics. Over the past few years, the multi-frequency vertical detection techniques have evolved from the new retrieval methods being enlightened by scattering theory to a new stage of the crucial microphysical processes being revealed by field observations. In this paper, from the perspectives of liquid and frozen hydrometeor microphysics, we introduce the key techniques used for dual- and triple-frequency radar retrieval techniques based on the scattering and attenuation of hydrometeors. Meanwhile, enlightened by the scattering of hydrometeors, we propose that the multi-frequency radar detecting techniques are developing from the classical W/Ka/X wavelengths to a "triple-frequency plus" stage, involving radars with shorter wavelengths and/or longer wavelengths. With spaceborne radars being developed from single-frequency to dual-frequency radars, the improvement of ground-based multi-frequency radars is expected to provide crucial support to future spaceborne multi-frequency radar missions.

Abstract Given that bromine possesses similar properties but extra merits of easily synthesizing and polarizing comparing to homomorphic fluorine and chlorine, it is quite surprising very rare high-performance brominated small molecule acceptors have been reported. This may be caused by undesirable film morphologies stemming from relatively larger steric hindrance and excessive crystallinity of bromides. To maximize the advantages of bromides while circumventing weaknesses, three acceptors (CH20, CH21 and CH22) are constructed with stepwise brominating on central units rather than conventional end groups, thus enhancing intermolecular packing, crystallinity and dielectric constant of them without damaging the favorable intermolecular packing through end groups. Consequently, PM6:CH22-based binary organic solar cells render the highest efficiency of 19.06% for brominated acceptors, more excitingly, a record-breaking efficiency of 15.70% when further thickening active layers to ~500 nm. By exhibiting such a rare high-performance brominated acceptor, our work highlights the great potential for achieving record-breaking organic solar cells through delicately brominating.

Named entity recognition (NER) and relation extraction (RE) are two important technologies employed in knowledge extraction for constructing knowledge graphs. Uni-modal NER and RE approaches solely rely on text information for knowledge extraction, leading to various limitations, such as suboptimal performance and low efficiency in recognizing polysemous words. With the development of multi-modal learning, multi-modal named entity recognition (MNER) and multi-modal relation extraction (MRE) have been introduced to improve recognition performance. However, existing MNER and MRE methods often encounter reduced efficiency when the text includes unrelated images. To address this problem, we propose a novel multi-modal network framework for named entity recognition and relation extraction called RSRNeT. In RSRNeT, we focus on extracting visual features more fully and designing a multi-scale visual feature extraction module based on ResNeSt network. On the other hand, we also emphasize fusing multi-modal features more comprehensively while minimizing interference from irrelevant images. To address this issue, we propose a multi-modal feature fusing module based on RoBERTa network. These two modules enable us to learn superior visual and textual representations, reducing errors caused by irrelevant images. Our approach has undergone extensive evaluation and comparison with various baseline models on MNER and MRE tasks. Experimental results show that our method achieves state-of-the-art performance in recall and F1 score on three public datasets: Twitter2015, Twitter2017 and MNRE.

ObjectivesStaphylococcal small-colony variants (SCVs) are common in cardiac implantable electronic device (CIED) infections. This is the first retrospective and multi-case study on CIED infections due to staphylococcal SCVs, aiming to provide a theoretical basis for the clinical management of CIED and device-related infections caused by staphylococcal SCVs.MethodsNinety patients with culture positive CIED infections were enrolled between 2021 and 2022. We compared the demographic and clinical characteristics of patients with and without SCVs and performed genomic studies on SCVs isolates.ResultsCompared to patients without SCVs, those with SCVs had a longer primary pacemaker implantation time and were more likely to have a history of device replacement and infection. They showed upregulated inflammatory indicators, especially higher NEUT% (52.6 vs. 26.8%, P = 0.032) and they had longer hospital stays (median 13 vs. 12 days, P = 0.012). Comparative genomics analysis was performed on Staphylococcus epidermidis wild-type and SCVs. Some genes were identified, including aap, genes encoding adhesin, CHAP domain-containing protein, LPXTG cell wall anchor domain-containing protein, and YSIRK-type signal peptide-containing protein.ConclusionStaphylococcal SCVs affect the clinical characteristics of CIED infections. The process of staphylococcal SCVs adherence, biofilm formation, and interaction with neutrophils play a vital role.

Objectives The routine teaching mode of diabetes mellitus (DM) is divided into various sub-majors of medical laboratory, which is not conducive to clinical laboratory physicians quickly mastering relevant knowledge. A novel DM laboratory testing pathway is established to improve teaching efficiency and enhance the effects of talent cultivation in laboratory medicine. Methods The guidelines and expert consensuses of DM were gathered from professional websites and databases. The clinical laboratory diagnostic pathway was formulated, and the questionnaire and mutual evaluation were used to evaluate the teaching effectiveness of 8-year undergraduate students enrolled in 2018 and enrolled in 2019, respectively. Results Clinical laboratory physicians developed and approved the DM clinical laboratory diagnostic pathway, which included the entire process of DM diagnosis and differential diagnosis, drug selection, treatment impact monitoring, prognosis evaluation, etc. The results of the questionnaires showed that, in comparison to the teaching mode used with the students enrolled in 2018 and enrolled in 2019, the percentages of more improvement and significant improvement were significantly increased ( P

Abstract Objectives Available literature documents that ischemic stroke can disrupt the morphology and function of mitochondria and that the latter in other disease models can be preserved by neuropilin-1 (NRP-1) via oxidative stress suppression. However, whether NRP-1 can repair mitochondrial structure and promote functional recovery after cerebral ischemia is still unknown. This study tackled this very issue and explored the underlying mechanism. Methods Adeno-associated viral (AAV)-NRP-1 was stereotaxically inoculated into the cortex and ipsilateral striatum posterior of adult male Sprague-Dawley (SD) rats before a 90-min transient middle cerebral artery occlusion (tMCAO) and subsequent reperfusion. Lentivirus (LV)-NRP-1 was transfected into rat primary cortical neuronal cultures before a 2-h oxygen-glucose deprivation and reoxygenation (OGD/R) injury to neurons. The expression and function of NRP-1 and its specific protective mechanism were investigated by Western Blot, immunofluorescence staining, flow cytometry, magnetic resonance imaging, transmission electron microscopy, etc. The binding was detected by molecular docking and molecular dynamics simulation. Results Both in vitro and in vivo models of cerebral ischemia/reperfusion (I/R) injury presented a sharp increase in NRP-1 expression. The expression of AAV-NRP-1 markedly ameliorated the cerebral I/R-induced damage to the motor function and restored the mitochondrial morphology. The expression of LV-NRP-1 alleviated mitochondrial oxidative stress and bioenergetic deficits. AAV-NRP-1 and LV-NRP-1 treatments increased the wingless integration (Wnt)-associated signals and β-catenin nuclear localization. The protective effects of NRP-1 were reversed by the administration of XAV-939. Conclusions NRP-1 can produce neuroprotective effects against I/R injury to the brain by activating the Wnt/β-catenin signaling pathway and promoting mitochondrial structural repair and functional recovery, which may serve as a promising candidate target in treating ischemic stroke.

Abstract Background Bloodstream infection (BSI) is a serious hematopoietic stem cell transplantation (HSCT) complication. The intestinal microbiome regulates host metabolism and maintains intestinal homeostasis. Thus, the impact of microbiome on HSCT patients with BSI is essential. Methods Stool and serum specimens of HSCT patients were prospectively collected from the pretransplant conditioning period till 4 months after transplantation. Specimens of 16 patients without BSI and 21 patients before BSI onset were screened for omics study using 16S rRNA gene sequencing and untargeted metabolomics. The predictive infection model was constructed using LASSO and the logistic regression algorithm. The correlation and influence of microbiome and metabolism were examined in mouse and Caco-2 cell monolayer models. Results The microbial diversity and abundance of Lactobacillaceae were remarkably reduced, but the abundance of Enterobacteriaceae (especially Klebsiella quasipneumoniae) was significantly increased in the BSI group before onset, compared with the non-BSI group. The family score of microbiome features (Enterobacteriaceae and Butyricicoccaceae) could highly predict BSI (AUC = 0.879). The serum metabolomic analysis showed that 16 differential metabolites were mainly enriched in the primary bile acid biosynthesis pathway, and the level of chenodeoxycholic acid (CDCA) was positively correlated with the abundance of K. quasipneumoniae (R = 0.406, P = 0.006). The results of mouse experiments confirmed that three serum primary bile acids levels (cholic acid, isoCDCA and ursocholic acid), the mRNA expression levels of bile acid farnesol X receptor gene and apical sodium-dependent bile acid transporter gene in K. quasipneumoniae colonized mice were significantly higher than those in non-colonized mice. The intestinal villus height, crypt depth, and the mRNA expression level of tight junction protein claudin-1 gene in K. quasipneumoniae intestinal colonized mice were significantly lower than those in non-colonized mice. In vitro, K. quasipneumoniae increased the clearance of FITC-dextran by Caco-2 cell monolayer. Conclusions This study demonstrated that the intestinal opportunistic pathogen, K. quasipneumoniae, was increased in HSCT patients before BSI onset, causing increased serum primary bile acids. The colonization of K. quasipneumoniae in mice intestines could lead to mucosal integrity damage. The intestinal microbiome features of HSCT patients were highly predictive of BSI and could be further used as potential biomarkers.

Abstract Compressive data gathering (CDG) is an adequate method to reduce the amount of data transmission, thereby decreasing energy expenditure for wireless sensor networks (WSNs). Sleep scheduling integrated with CDG can further promote energy efficiency. Most of existing sleep scheduling methods for CDG were formulated as centralized optimization problems which introduced many extra control message exchanges. Meanwhile, a few distributed methods usually adopted stochastic decision which could not adapt to variance in residual energy of nodes. A part of nodes were prone to prematurely run out of energy. In this paper, a reinforcement learning-based sleep scheduling algorithm for CDG (RLSSA-CDG) is proposed. Active nodes selection is modeled as a finite Markov decision process. The mode-free Q learning algorithm is used to search optimal decision strategies. Residual energy of nodes and sampling uniformity are considered into the reward function of the Q learning algorithm for load balance of energy consumption and accurate data reconstruction. It is a distributed algorithm that avoids large amounts of control message exchanges. Each node takes part in one step of the decision process. Thus, computation overhead for sensor nodes is affordable. Simulation experiments are carried out on the MATLAB platform to validate the effectiveness of the proposed RLSSA-CDG against the distributed random sleep scheduling algorithm for CDG (DSSA-CDG) and the original sparse-CDG algorithm without sleep scheduling. The simulation results indicate that the proposed RLSSA-CDG outperforms the two contrast algorithms in terms of energy consumption, network lifetime, and data recovery accuracy. The proposed RLSSA-CDG reduces energy consumption by 4.64% and 42.42%, respectively, compared to the DSSA-CDG and the original sparse-CDG, prolongs life span by 57.3%, and promotes data recovery accuracy by 84.7% compared to the DSSA-CDG.

Harvested wampee fruit is susceptible to disease, resulting in postharvest losses. Acidic electrolyzed water (AEW), a safe and innovative sterilization technology, plays a role in enhancing disease resistance in harvested produce. In this study, the efficacy of AEW in delaying wampee disease development was assessed, along with its association with disease resistance metabolism. Wampee fruit was treated with AEW (pH 2.5) at different available chlorine concentrations (ACCs) (20, 40, 60, and 80 mg/L) and subsequently stored at 25 °C for 8 days. Results revealed that 40 mg/L ACC in AEW (pH 2.5) was most effective in improving the postharvest quality of wampee fruit. Compared with control wampee fruit, those treated with 40 mg/L ACC in AEW exhibited lower incidence of fruit disease, higher pericarp lignin content, and higher activities of pericarp disease resistance enzymes (DREs), such as cinnamate-4-hydroxylase, phenylalanine ammonia-lyase, chitinase, β-1,3-glucanase, polyphenol oxidase, 4-coumarate CoA ligase, and cinnamyl alcohol dehydrogenase. These results suggested that AEW elevated DRE activities, promoted lignin accumulation, and ultimately enhanced disease resistance, suppressed disease development, and improved storage quality in harvested wampee fruit. Consequently, AEW emerged as a safe technology to mitigate the disease development and enhance the storage quality of harvested wampee fruit.

In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.

The conventional Archie formula struggles with the interpretation of water saturation from resistivity well log data due to the increasing complexity of exploration targets. This challenge has prompted researchers to explore alternative physical parameters, such as acoustic characteristics, for breakthroughs. Clarifying the influencing factors of porous media acoustic characteristics is one of the most important approaches to help understanding the mechanism of acoustic characteristics of carbonate reservoirs. The article uses digital rock technology to characterize the pore structure, quantitatively identify fractures and pore structures in carbonate rocks, and establish digital models. Through conventional acoustic testing, the pressure wave (P-wave) and shear wave (S-wave) velocities of rock samples at different water saturations are obtained, and the dynamic elastic modulus is calculated. A finite element calculation model is established using the digital rock computational model to provide a basis for fluid saturation calculation methods. Based on real digital rock models, different combinations of virtual fractures are constructed, and factors affecting acoustic parameters are analyzed. The study finds that as porosity increases, the velocity difference between porous cores and fractured cores also increases. These findings provide important technical support and a theoretical basis for interpreting acoustic well logging data and evaluating carbonate reservoirs with different pore and fracture types.

The Internet of Things (IoT) serves as a crucial element in interconnecting diverse devices within the realm of smart technology. However, the energy consumption of IoT technology has become a notable challenge and an area of interest for researchers. With the aim of achieving an IoT with low power consumption, green IoT has been introduced. The use of unmanned aerial vehicles (UAVs) represents a highly innovative approach for creating a sustainable green IoT network. UAVs offer advantages in terms of flexibility, mobility, and cost. Moreover, device-to-device (D2D) communication is essential in emergency communications, due to its ability to support direct communication between devices. The intelligent reflecting surface (IRS) is also a hopeful technology which reconstructs the radio propagation environment and provides a possible solution to reduce co-channel interference resulting from spectrum sharing for D2D communications. The investigation in this paper hence focuses on energy-efficient UAV-IRS-assisted D2D communications for green IoT. In particular, a problem of optimization aimed at maximizing the system’s average energy efficiency (EE) is formulated, firstly, by simultaneously optimizing the power coefficients of all D2D transmitters, the UAV’s trajectory, and the base station (BS)’s active beamforming, along with the IRS’s phase shifts. Second, to address the problem, we develop a multi-agent twin delayed deep deterministic policy gradient (MATD3)-based scheme to find a near-optimal solution, where D2D transmitters, the BS, and the UAV cooperatively learn to improve EE and suppress the interference. To conclude, numerical simulations are conducted to assess the availability of the proposed scheme, and the simulation results demonstrate that the proposed scheme surpasses the baseline approaches in both convergence speed and EE performance.

This paper addresses the issue of the difficulty in obtaining inter-turn fault (ITF) samples in electric motors, specifically in permanent magnet-synchronous motors (PMSMs), where the number of ITF samples in the stator windings is severely lacking compared to healthy samples. To effectively identify these faults, an improved fault diagnosis method based on the combination of a cycle-generative adversarial network (GAN) and a deep autoencoder (DAE) is proposed. In this method, the Cycle GAN is used to expand the collection of fault samples for PMSMs, while the DAE enhances the capability to extract and analyze these fault samples, thus improving the accuracy of fault diagnosis. The experimental results demonstrate that Cycle GAN exhibits an excellent capability to generate ITF fault samples. The proposed method achieves a diagnostic accuracy rate of up to 98.73% for ITF problems.

Food-derived angiotensin-I-converting enzyme (ACE)-inhibitory peptides have gained attention for their potent and safe treatment of hypertensive disorders. However, there are some limitations of conventional methods for preparing ACE-inhibitory peptides. In this study, in silico hydrolysis, the quantitative structure–activity relationship (QSAR) model, LC-MS/MS, inhibition kinetics, and molecular docking were used to investigate the stability, hydrolyzability, in vitro activity, and inhibition mechanism of bioactive peptides during the actual hydrolysis process. Six novel ACE-inhibitory peptides were screened from the Larimichthys crocea protein (LCP) and had low IC50 values (from 0.63 ± 0.09 µM to 10.26 ± 0.21 µM), which were close to the results of the QSAR model. After in vitro gastrointestinal simulated digestion activity of IPYADFK, FYEPFM and NWPWMK were found to remain almost unchanged, whereas LYDHLGK, INEMLDTK, and IHFGTTGK were affected by gastrointestinal digestion. Meanwhile, the inhibition kinetics and molecular docking results were consistent in that ACE-inhibitory peptides of different inhibition forms could effectively bind to the active or non-central active centers of ACE through hydrogen bonding. Our proposed method has better reproducibility, accuracy, and higher directivity than previous methods. This study can provide new approaches for the deep processing, identification, and preparation of Larimichthys crocea.

A multi-purpose prototype test system is developed to study the mechanical behavior of tunnel supporting structure, including a modular counterforce device, a powerful loading equipment, an advanced intelligent management system and an efficient noncontact deformation measurement system. The functions of the prototype test system are adjustable size and shape of the modular counterforce structure, sufficient load reserve and accurate loading, multi-connection linkage intelligent management, and high-precision and continuously positioned noncontact deformation measurement. The modular counterforce structure is currently the largest in the world, with an outer diameter of 20.5 m, an inner diameter of 16.5 m and a height of 6 m. The case application proves that the prototype test system can reproduce the mechanical behavior of the tunnel lining during load-bearing, deformation and failure processes in detail.

Abstract We study two-to-two scattering amplitudes of a scalar particle of mass m. For simplicity, we assume the presence of ℤ2 symmetry and that the particle is ℤ2 odd. We consider two classes of amplitudes: the fully nonperturbative ones and effective field theory (EFT) ones with a cut-off scale M. Using the primal numerical method which allows us to impose full non-linear unitarity, we construct novel bounds on various observables in 2 ≤ d ≤ 4 space-time dimensions for both classes of amplitudes. We show that our bounds are much stronger than the ones obtained by using linearized unitarity or positivity only. We discuss applications of our bounds to constraining EFTs. Finally, we compare our bounds to the amplitude in ϕ 4 theory computed perturbatively at weak coupling, and find that they saturate the bounds.

To improve nutritive value and quality of chiffon cake, Haematococcus pluvialis powder was added to chiffon cake in this study. Nutrients of H. pluvialis was determined by HPLC and GC-MS. Using automatic color difference meter and texture analyser to explore the color and texture of chiffon cake with different levels of H. pluvialis. Antioxidant activity of chiffon cake and the effect of baking on astaxanthin were also investigated. The results showed that the content of astaxanthin, carbohydrate, protein and fatty acid was 20.93±0.41 mg/g DCW, 25.56%±0.94%, 19.97%±0.13% and 27.11%±0.25%. The color of chiffon cake turned orange red gradually, the hardness, elasticity and chewiness of chiffon cake were gradually increased, and antioxidant activity was improved with the increase of H. pluvialis addition. Specific volume was highest with the addition of 2.0% H. pluvialis. Scavengingrate of DPPH and hydroxyl radical increased by 119.92% and 9.17% with the addition of 4.0% H. pluvialis compared with the control group. The content of astaxanthin decreased sharply with the loss rate of 49.37%~62.17% after baking. Besides, algal fishy smell emitted with the addition of H. pluvialis increased, which affected the flavor of chiffon cake. Therefore, 1.0%~2.0% of H. pluvialis was appropriate for chiffon cake to improve its quality and nutritive value.

Background and aims: The sodium taurocholate co-transporting polypeptide (NTCP) is a functional receptor for the hepatitis B virus (HBV), and it is critical for bile acid homeostasis. Previous studies of the association between the S267F variant and chronic hepatitis B (CHB) have generated conflicting results. This study analyzed the correlation between the NTCP S267F variant and CHB susceptibility by using a large sample of participants classified by gender and age, and this study also analyzed the relationship between this variant and the level of serum total bile acids. Methods: In total, 543 patients with CHB and 429 control subjects underwent S267F variant genotyping using SNaPshot technology. Logistic regression was utilized to evaluate any association of the NTCP S267F variant with CHB susceptibility. Results: The S267F variant was inversely correlated with the risk of chronic HBV infection in both the dominant model (GG genotype vs. AG genotype: odds ratio (OR) = 0.46, 95% confidence interval (CI) 0.30–0.71, P

Abstract Purpose To report a rare case of biliary candidiasis in a host with normal immunity. Methods Laboratory tests indicated an elevated G level of 1000 pg/ml. Microscopic examination of pathological sections demonstrated multiple, narrow base, budding yeast cells following Grocott's methenamine silver staining and periodic acid‐Schiff staining. Subsequent sequence analysis supported the diagnosis of biliary candidiasis. Results A 31‐year‐old previously healthy man developed obstructive jaundice under no obvious inducement. He experienced cholecystectomy and biliary drainage. Surgical specimens revealed granulomatous chronic inflammation in the gallbladder, liver, bile ducts and mesenteric lymph nodes. He was misdiagnosed with tuberculosis and received antituberculosis treatment. However, his condition did not improve. He was finally diagnosed with biliary candidiasis and administered the antifungal treatment with fluconazole. His symptoms improved after such treatment. Conclusions We reported a case of biliary candidiasis that mimicked IgG4‐RD in a host with normal immunity. Our findings highlighted the need for pathological diagnosis in patients with symptoms resembling IgG4‐RD.

Abstract The strain-temperature cross-sensitivity problem easily occurs in the engineering strain monitoring of the self-sensing embedded with fiber Bragg grating (FBG) sensors. In this work, a theoretical investigation of the strain-temperature cross-sensitivity has been performed using the temperature reference grating method. To experimentally observe and theoretically verify the problem, the substrate materials, the preloading technique, and the FBG initial central wavelength were taken as main parameters. And a series of sensitivity coefficients calibration tests and temperature compensation tests have been designed and carried out. It was found that when the FBG sensors were embedded on different substrates, their coefficients of the temperature sensitivity were significantly changed. Besides, the larger the coefficients of thermal expansion (CTE) of substrates were, the higher the temperature sensitivity coefficients would be. On the other hand, the effect of the preloading technique and FBG initial wavelength was negligible on both the strain monitoring and temperature compensation. In the case of similar substrates, we did not observe any difference between temperature sensitivity coefficients of the temperature compensation FBG with one free end or two free ends. The curves of the force along with temperature were almost overlapped with minor differences (less than 1%) gained by FBG sensors and pressure sensors, which verified the accuracy of the temperature compensation method. We suggest that this work can provide efficient solutions to the strain-temperature cross-sensitivity for engineering strain monitoring with the self-sensing element embedded with FBG sensors.

ABSTRACT Staphylococcus aureus is subdivided into lineages termed sequence types (STs), infections of which necessitate the expression of virulence factors and metabolic adaptation to the host niche. Given that mechanisms underlying the dynamic replacement of sequence types in S. aureus populations have yet to be sufficiently determined, we investigated the role of metabolic determinants in epidemic clones. mleS, encoding the NAD+-dependent malolactic enzyme, was found to be carried by the epidemic clones ST59 and ST398, although not by ST239 and ST5. The genomic location of mleS in the metabolism-associated region flanked by the thiol-specific redox system and glycolysis operon implies that it plays significant roles in metabolism and pathogenesis. Mouse skin abscess caused by the BS19-mleS mutant strain (isogenic mleS mutant in an ST59 isolate) was significantly attenuated and associated with reductions in interleukin-6 (IL-6) and lactic acid production. mleS deletion also impaired S. aureus biofilm formation and survival in RAW264.7 cells. The BS19-mleS-mutant was also characterized by reduced ATP and lactic acid production under microaerobic conditions; however, NAD+/NADH levels remained unaffected. mleS is thus identified as an epidemiological marker that plays an important role in the microaerobic metabolism and pathogenesis of epidemic S. aureus clones. IMPORTANCE Given the importance of metabolic adaptation during infection, new insights are required regarding the pathogenesis of S. aureus, particularly for epidemic clones. We accordingly investigated the role of metabolic determinants that are unique to the epidemic clones ST59 and ST398. Our results provide evidence that the NAD+-dependent malolactic enzyme-coding gene mleS is an epidemiological marker that plays an important role in the microaerobic metabolism and pathogenesis of epidemic S. aureus clones.

Microwave surface emissivity is complex and variable, leading to increased difficulty in accurately retrieving atmospheric parameters and assimilating satellite microwave observations over land. The Community Radiative Transfer Model (CRTM) land emissivity model is a useful tool for providing microwave emissivity over complex surfaces. By combining the model with ground measurements from a mobile multi-surface observing system at the Xianghe site, China, the performance of the land emissivity model is evaluated over grass and sand surfaces. The simulated and measured emissivity agrees at both polarizations over the grassland surface but a more significant difference is observed at the horizontal polarization over the sand surface. To solve this problem, the Q/H module for soil reflectance roughness correction in the CRTM emissivity model was replaced with the Qp module for the sand surface. This results in a significant improvement in the horizontal polarization simulation, with the corresponding mean bias error (MBE) reducing from 0.08 in the Q/H module to less than 0.03. The adjustment demonstrates that the Qp module more effectively corrects the roughness effect on horizontally polarized emissivity for bare soil surfaces. For grassland, the CRTM emissivity model with the Q/H module demonstrates accurate simulations, showing its suitability for vegetated land surfaces.

Metagenomic data from cerebrospinal fluid was used to genotype Neisseria meningitidis in patients with invasive meningococcal disease and trace the origin of the pathobiont, providing a phylogeographic analysis of the strain’s evolution in China and its global spread.

Abstract In this paper, a piecewise sine waveguide (PWSWG) is proposed as the slow-wave structure (SWS) to develop high-power terahertz (THz) traveling wave tubes (TWTs). The PWSWG is an improvement over the rectangular waveguide wherein its two E-planes simultaneously oscillate up and down along the longitudinal direction. The oscillation curve in the H-plane is a piecewise sine curve formed by inserting line segments into the peaks and troughs of the sine curve. The simulation analysis and experimental verification show that the PWSWG offers the advantages of large interaction impedance and excellent electromagnetic transmission performance. Furthermore, the calculation results of beam–wave interaction show that the TWT based on PWSWG SWS can generate a radiated power of 253.1 W at the typical frequency of 220 GHz, corresponding to a gain of 37.04 dB and an interaction efficiency of 6.92%. Compared with the conventional SWG TWTs, the PWSWG TWT has higher interaction efficiency and shorter saturation tube length. In conclusion, the PWSWG proposed in this paper can be considered a suitable SWS for high-power THz radiation sources.