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Abstract Background Esophageal squamous cell carcinoma (ESCC) is often diagnosed at advanced stages due to the inherent limitations of current screening methodologies. Central to evaluating tumor invasion and prognostic assessment in ESCC is the integrity of the basement membrane (BM). However, current research on the implications of BM-related genes (BMRGs) in diagnosing ESCC remains sparse. Methods We performed a comprehensive analysis using single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, alongside gene expression profiles acquired from GEO and The Cancer Genome Atlas (TCGA) databases. This identified differentially expressed BMRGs in ESCC. Employing LASSO, RF, and SVM-RFE, we selected potential BM biomarkers and crafted a diagnostic nomogram for ESCC, validated by ROC curves and AUC values. We also explored immune infiltration and biological mechanisms through consensus clustering and GSVA, and utilized single cell trajectory analysis and GSCALite to study gene distributions and pathways. In vitro experiments further elucidated the role of these genes in ESCC carcinogenesis. Results Here, we discovered that ESCC cell types exhibited markedly elevated BM-related scores. Our analysis pinpointed seven BM genes upregulated and linked to immune infiltration, showcasing unique gene expression profiles and varying immune cell densities across the BM-related subtypes. Furthermore, a robust positive correlation was observed between these genes expression and EMT activity. The knockdown of BGN significantly suppressed cell proliferation, migration, invasion, while also augmenting cell viability following chemotherapy drug treatment. Conclusion Our study identified seven key BMRGs (BGN, LAMB3, SPARC, MMP1, LUM, COL4A1, and NELL2) and established a diagnostic nomogram for ESCC. Of noteworthy significance is the discovery of BGN as a promising drug target, indicating a novel strategy for future clinical combination therapies in ESCC.

Energy storage systems (ESSs) operate as independent market participants and collaborate with photovoltaic (PV) generation units to enhance the flexible power supply capabilities of PV units. However, the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood. This study introduces a dual-timescale dynamics model that integrates a spot market clearing (SMC) model into a system dynamics (SD) model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems (IESSs) with that of an ESS integrated within a PV (PV-ESS). Furthermore, this study aims to ascertain the optimal allocation of the PV-ESS. First, SD and SMC models were set up. Second, the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem, a dual-timescale model was constructed. Finally, a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation. Additionally, negative electricity prices were considered during clearing processes. The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS, helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

IntroductionOvarian cancer is one of the three most common gynecological cancers, with the highest mortality rate among gynecological malignancies. Previous studies on the environmental and socioeconomic (ESE) factors that affect ovarian cancer incidence (OCI) have generally only considered the net effects of single variables, while the synergistic effects among multiple factors have yet to be explored.MethodsBased on a sample of 30 provinces in Mainland China, an ESE configuration model was constructed in this study, using a fuzzy-set qualitative comparative analysis approach to empirically explore the configuration effects of multiple ESE factors on OCI.Results(1) Education, marriage, income, insurance, urbanization, and environment alone do not constitute the necessary conditions for high or low OCI, indicating a need to comprehensively consider the configuration effects of these six conditions. (2) There are two configurations for high OCI: “configuration of environmental pollution under low socioeconomic development” and “configuration of insurance deficiency under high socioeconomic development.” (3) There are two configurations for low OCI: “configuration of insurance adequacy under low socioeconomic development” and “configuration of insurance adequacy under low urbanization.”ConclusionThe main contribution of this study is its focus on the configuration mechanism of ESE factors, enhancing understanding of the synergistic effects among the multiple factors that affect OCI. The study also provides valuable policy implications for decision-makers to formulate comprehensive health policies for the prevention and treatment of ovarian cancer.

IntroductionGBS (group B streptococcus) is an opportunistic pathogen that can colonize healthy individuals but presents significant challenges in clinical obstetrics and gynecology, as it can cause miscarriage, preterm birth, and invasive infections in newborns. To develop specific and personalized preventative strategies, a better understanding of the epidemiological characteristics and pathogenic features of GBS is essential.MethodsWe conducted a comprehensive strain-level genomic analysis of GBS, examining serotype and genotype distributions, as well as the composition and correlations of virulence genes using the blastn-short mode of the BLAST program(v2.10.0+), mlstsoftware (https://github.com/tseemann/mlst), Snippy (v4.6.0), FastTree (v2.1.11) and iTOL. The coding sequence region of virulence factors was annotated by Prodigal (v2.6.3) and Glimmer(v3.02b). We further identified host protein interacting with Srr2 by mass spectrometry analysis.ResultsWhile certain genotypes showed strong serotype consistency, there was no significant association between overall serotypes and genotypes. However, the composition of virulence genes was more closely related to the phylogeny of GBS, among which simultaneous presence of Srr2 and HygA exhibit significant association with hypervirulence. Tubulin emerged as the most distinct and abundant hit. The specific interaction of Tubulin with Srr2-BR, rather than Srr1-BR, was further confirmed by immunoblotting.DiscussionConsidering the impact of cytoskeleton rearrangement on GBS pathogenesis, this observation offers a plausible explanation for the hypervirulence triggered by Srr2. Collectively, our findings indicate that in the future clinical practice, virulence gene detection should be given more attention to achieve precise GBS surveillance and disease prevention.

This editorial summarizes the papers selected for publication in the Special Issue on Climate Change Mitigation and Adaptation in Power and Energy Systems (CMAP). After a rigorous review of 86 submitted manuscripts, 23 papers were accepted for publication. These accepted papers cover various aspects of climate change mitigation and adaptation and are classified as follows: boosting renewable energy efficiency (two papers), climate resilience strategies (four papers), decarbonization strategies (four papers), renewable energy integration (five papers), policies, incentives, and science communications (four papers), and the role of energy markets (four papers). The Guest Editorial Board is optimistic that this Special Issue will serve as a rich resource, offering invaluable insights to propel future research and advancements in climate change mitigation and adaptation.

Summary: In this study, we obtained the whole genome sequence of GCRV-DY197 and investigated the localization, post-translational modifications, and host interactions of the 11 viral proteins encoded by GCRV-DY197 in grass carp ovary (GCO) cells. The whole genome sequence is 24,704 kb and contains 11 segments (S1–S11). Subcellular localization showed that the VP1, VP2, VP3, VP5, VP56, and VP35 proteins were localized in both cytoplasm and nucleus, whereas the NS79, VP4, VP41, VP6, and NS38 proteins were localized in the cytoplasm. The NS79 and NS38 proteins were phosphorylated, and the ubiquitination modification sites were identified in VP41 and NS38. An interaction network containing 9 viral proteins and 140 host proteins was also constructed. These results offer a theoretical basis for an in-depth understanding of the biochemical characteristics and pathogenic mechanism of GCRV-II.

IntroductionThe marine economy has played an important role in stabilizing national economic growth and ensuring economic security. Achieving high-quality and sustainable development of the marine economy is a strategic task for China to build a maritime power. Confronting various risk factors such as financial crises, natural disasters, geopolitical conflicts, industrial transformation, and public health security, etc., marine economic resilience (MER) has received widespread attention in recent years and is considered to be crucial for high-quality and sustainable development of the marine economy. MethodsThis study takes 11 coastal provinces in China as cases, integrates 6 condition variables by building a Resistance capability-Recovery capability-Renewal capability (3R) configuration model, and uses the fuzzy-set qualitative comparative analysis (fsQCA) approach to empirically explore the configuration effect between multiple land factors and MER. Results and discussion(1) None of the 6 conditions in the three dimensions of resistance capability, recovery capability, and renewal capability alone constitute the necessary conditions for strong or weak MER, indicating that a single condition has weak explanatory power for MER; (2) There are two configurations for strong MER: Strong Resistance-Recovery Type and Comprehensive Strong Type. Industrial structure, governmental capability, and digital economy are the core conditions for strong MER configurations; (3) There are four weak MER configurations: Comprehensive Weak Type, Weak Recovery-Renewal Type, Weak Resistance-Recovery Type I, and Weak Resistance-Recovery Type II. This study may expand the research scope of MER influencing factors and enriching the research perspective of land-sea integration, as well as providing decision-makers with practical policy implications.

Abstract Background Apolipoprotein A1 (ApoA1) is a member of the apolipoprotein family with diverse functions. It is associated with the pathogenesis and prognosis of several types of tumors. However, the role of serum apolipoprotein A1 (ApoA1) in the prognosis of patients with diffuse large B-cell lymphoma (DLBCL) remains unclear. This study aimed to elucidate its influence on clinical outcomes in patients with DLBCL. Methods We retrospectively analyzed a cohort of 1583 consecutive DLBCL patients admitted to the Fujian Medical University Union Hospital between January 2011 and December 2021. 949 newly diagnosed DLBCL patients who met the inclusion criteria were enrolled for statistical analysis. Receiver operating characteristic curve analysis was performed to determine the optimal cut-off value for serum ApoA1 levels for prognostic prediction among patients with DLBCL. The correlations between serum ApoA1 levels and clinical and laboratory parameters were analyzed. Prognostic significance was analyzed using univariate and multivariate Cox proportional hazards models. Results Newly diagnosed patients with DLBCL demonstrated low serum ApoA1 levels (upper limit of normal), poorer performance status (Eastern Cooperative Oncology Group score of 2–4), higher percentage of advanced stage and non-germinal center B-cell (non-GCB) subtype, more cases of > 1 extranodal site, higher International Prognostic Index (IPI) score (3–5), and higher incidence of relapse or refractory diseases compared with those with high serum ApoA1 levels (≥ 0.925 g/L). Low serum ApoA1 levels were an independent adverse prognostic factor for overall survival (OS) but not progression-free survival (PFS). Conclusions Low serum ApoA1 levels were associated with poor treatment response and inferior survival in newly diagnosed patients with DLBCL.

Because they have foundations with two or more different elevations, the mechanical performance of structures in mountain cities is significantly different from that of common structures. Our simulation method and the parameters of a typical bolt steel plate-based dry connection joint were verified based on the static load test of a fully assembled substructure against progressive collapse. The load–displacement curves and the displacement–time history curves of the failure point of six kinds of column removal conditions were obtained by using static nonlinear and dynamic nonlinear analysis methods, establishing a different number of dropped stories and spans for the prefabricated step-terrace frame structure models. Based on the ultimate load amplification factor and the maximum dynamic displacement at the failure point, the progressive collapse performance of prefabricated frame structures in mountain cities, including the number of dropped stories and spans, was obtained. The results show that the progressive collapse performance of a prefabricated step-terrace frame structure is inferior to that of a common prefabricated frame structure. The progressive collapse performance is stronger when the upper ground columns fail than that when the dropped ground columns fail. The progressive collapse performance of the prefabricated step-terrace frame structure decreases gradually with the increase in the number of dropped stories and increases gradually with the increase in the number of dropped spans. With the increase in the number of dropped stories, the redundancy of the structure is reduced, and the progressive collapse performance of the dropped stories is reduced by more than that of the upper stories. The increase in the number of dropped spans increases the redundancy of the structure, and the improvement in the progressive collapse performance of the dropped stories is greater than that of the upper stories. This paper provides a reference for the progressive-collapse-resistant design of step-terrace frame structures in mountain cities.

Modified Jiawei Juanbi decoction (MJD) is used for the treatment of early-stage knee osteoarthritis (KOA). Here, modified Jiawei Juanbi decoction (MJD) was employed for the treatment of early-stage knee osteoarthritis (KOA) and its mechanisms were assessed via metabonomics and network pharmacology. A total of 24 male Sprague-Dawley rats were randomly allocated into a normal control group, a model group, and an MJD group (n = 8 rats per group). Each rat group was further equally divided into two subgroups for investigation for either 14 or 28 days. A rat model of early-stage KOA was constructed and rats were treated with MJD. Effects were evaluated based on changes in knee circumference, mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL). We also analyzed histopathological changes in articular cartilage. High-resolution mass spectrometry was used to analyze the chemical profile of MJD, identifying 228 components. Using an LC-Q-TOF-MS metabonomics approach, 33 differential metabolites were identified. The relevant pathways significantly associated with MJD include arginine and proline metabolism, vitamin B6 metabolism, as well as the biosynthesis of phenylalanine, tyrosine and tryptophan. The system pharmacology paradigm revealed that MJD contains 1027 components and associates with 1637 genes, of which 862 disease genes are related to osteoarthritis. The construction of the MJD composition-target-KOA network revealed a total of 140 intersection genes. A total of 39 hub genes were identified via integration of betweenness centrality values greater than 100 using CytoHubba. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed several significantly affected signaling pathways including the HIF-1, AGE-RAGE (in diabetic complications), IL-17, rheumatoid arthritis and TNF pathways. Integrated-omics and network pharmacology approaches revealed a necessity for further detailed investigation focusing on two major targets, namely NOS2 and NOS3, along with their essential metabolite (arginine) and associated pathways (HIF-1 signaling and arginine and proline metabolism). Real-time PCR validated significantly greater downregulation of NOS2 and HIF-1ɑ in the MJD as compared to the model group. Molecular docking analysis further confirmed the binding of active MJD with key active components. Our findings elucidate the impact of MJD on relevant pathophysiological and metabolic networks relevant to KOA and assess the drug efficacy of MJD and its underlying mechanisms of action.

Abstract Pathological cardiac hypertrophy is the leading cause of heart failure and has an extremely complicated pathogenesis. TEA domain transcription factor 1 (TEAD1) is recognized as an important transcription factor that plays a key regulatory role in cardiovascular disease. This study aimed to explore the role of TEAD1 in cardiac hypertrophy and to clarify the regulatory role of small ubiquitin‐like modifier (SUMO)‐mediated modifications. First, the expression level of TEAD1 in patients with heart failure, mice, and cardiomyocytes is investigated. It is discovered that TEAD1 is modified by SUMO1 during cardiac hypertrophy and that the process of deSUMOylation is regulated by SUMO‐specific protease 1 (SENP1). Lysine 173 is an essential site for TEAD1 SUMOylation, which affects the protein stability, nuclear localization, and DNA‐binding ability of TEAD1 and enhances the interaction between TEAD1 and its transcriptional co‐activator yes‐associated protein 1 in the Hippo pathway. Finally, adeno‐associated virus serotype 9 is used to construct TEAD1 wild‐type and KR mutant mice and demonstrated that the deSUMOylation of TEAD1 markedly exacerbated cardiomyocyte enlargement in vitro and in a mouse model of cardiac hypertrophy. The results provide novel evidence that the SUMOylation of TEAD1 is a promising therapeutic strategy for hypertrophy‐related heart failure.

This article presents two quantum algorithms for computing the product of a circulant matrix and a vector. The arithmetic complexity of the first algorithm is O(Nlog2N) in most cases. For the second algorithm, when the entries in the circulant matrix and the vector take values in C or R, the complexity is O(Nlog2N) in most cases. However, when these entries take values from positive real numbers, the complexity is reduced to O(log3N) in most cases, which presents an exponential speedup compared to the classical complexity of O(NlogN) for computing the product of a circulant matrix and vector. We apply this algorithm to the convolution calculation in quantum convolutional neural networks, which effectively accelerates the computation of convolutions. Additionally, we present a concrete quantum circuit structure for quantum convolutional neural networks.

Abstract Although the MAPK/MEK/ERK pathway is prevalently activated in colorectal cancer (CRC), MEK/ERK inhibitors show limited efficiency in clinic. As a downstream target of MAPK, ELK4 is thought to work primarily by forming a complex with SRF. Whether ELK4 can serve as a potential therapeutic target is unclear and the transcriptional regulatory mechanism has not been systemically analyzed. Here, it is shown that ELK4 promotes CRC tumorigenesis. Integrated genomics‐ and proteomics‐based approaches identified SP1 and SP3, instead of SRF, as cooperative functional partners of ELK4 at genome‐wide level in CRC. Serum‐induced phosphorylation of ELK4 by MAPKs facilitated its interaction with SP1/SP3. The pathological neoangiogenic factor LRG1 is identified as a direct target of the ELK4‐SP1/SP3 complex. Furthermore, targeting the ELK4‐SP1/SP3 complex by combination treatment with MEK/ERK inhibitor and the relatively specific SP1 inhibitor mithramycin A (MMA) elicited a synergistic antitumor effect on CRC. Clinically, ELK4 is a marker of poor prognosis in CRC. A 9‐gene prognostic model based on the ELK4‐SP1/3 complex‐regulated gene set showed robust prognostic accuracy. The results demonstrate that ELK4 cooperates with SP1 and SP3 to transcriptionally regulate LRG1 to promote CRC tumorigenesis in an SRF‐independent manner, identifying the ELK4‐SP1/SP3 complex as a potential target for rational combination therapy.

Polymeric immunoglobulin (Ig) receptor-like (pIgRL) molecules have been identified in teleost fish. However, compared to functional studies of their related genes (e.g., mammalian CD300 family) in eliminating pathogen invasion while preserving homeostasis, the roles of pIgRL in teleost fish remain unclear. In this study, we demonstrated that a pair of pIgRL molecules in zebrafish, pIgRL3.5 and pIgRL4.2, were highly expressed in the intestine and immune cells. Moreover, we constructed an Edwardsiella piscicida infection model, which induced strong inflammatory responses in the zebrafish intestine. Interestingly, pIgRL3.5 and pIgRL4.2 exhibited opposite inducible expression patterns in response to bacterial infection, suggesting that they perform different roles. More importantly, by conducting overexpression and knockdown experiments, our findings demonstrated that zebrafish pIgRL3.5 played a protective role in host defense against E. piscicida infection by inhibiting excessive inflammatory responses. In contrast, pIgRL4.2 facilitated pathogen growth and dissemination in zebrafish intestine. Collectively, our findings are the first to demonstrate that a pair of pIgRL molecules in teleost fish play opposite roles in mucosal immune response to bacterial infection. Therefore, our results provide crucial insights into the conserved role of pIgRL molecules in immune regulatory functions throughout vertebrate evolution.

Phosphorus metabolism in laying hens is a highly dynamic process over the course of the 24 h egg-laying cycle. Adjusting the phosphorus feeding regimen according to the daily egg-laying cycle may help to improve phosphorus utilization efficiency. Hy-Line Brown layers (n = 120; 70 wk old) were offered 4 different phosphorus daily regimens: (1) RR, fed regular phosphorus at both 09:00 and 17:00; (2) RL, fed regular phosphorus at 09:00 and low phosphorus at 17:00; (3) LR, fed low phosphorus at 09:00 and regular phosphorus at 17:00; (4) LL, fed low phosphorus at both 09:00 and 17:00. The regular and low phosphorus diets contained 0.32% and 0.14% non-phytate phosphorus, respectively. The feeding trial lasted for 12 wk. As a result, layers on the RL regimen had decreased laying rate (P 0.05); (2) decreased phosphorus excretion (P

Abstract Prelithiation technology is widely considered a feasible route to raise the energy density and elongate the cycle life of lithium‐ion batteries. The principle of prelithiation is to introduce extra active Li ions in the battery so that the lithium loss during the first charge and long‐term cycling can be compensated. Such an effect does not need to change the major electrode material or battery structure and is compatible with the majority of current lithium‐ion battery production lines. At this stage, various prelithiation methods have been reported, some of which are already in the pilot‐scale production stage. But there is still no definitive development roadmap for prelithiation. In this review, we first introduce the influence of prelithiation on electrochemical performance from a theoretical point of view and then compare the pros and cons of different prelithiation methods in different battery manufacturing stages. Finally, we discuss the challenges and future development trends of prelithiation. We aim to build up a bridge between academic research and industrial application. Some engineering problems in the promotion of prelithiation technique are extensively discussed, including not only the implementation of prelithiation but also some collateral issues on battery designing and management.

With the global trend of pursuing clean energy and decarbonization, power systems have been evolving in a fast pace that we have never seen in the history of electrification. This evolution makes the power system more dynamic and more distributed, with higher uncertainty. These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period. The conventional computing approaches will not be sufficient for future power systems. This paper provides a historical review of computing for power system operation and planning, discusses technology advancements in high performance computing (HPC), and describes the drivers for employing HPC techniques. Some high performance computing application examples with different HPC techniques, including the latest quantum computing, are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future.

With the rapid development of urbanization, the rate of abandonment of arable land in China's mountainous areas has accelerated. Solving the phenomenon of abandonment of arable land has become an important issue in managing the use of China’s arable land, the key to which lies in the development of specialty agriculture using the unique natural environment of mountainous areas. This paper scrutinizes both the horizontal and vertical distribution of specialty agriculture in these areas, drawing upon the “One Village, One Product” dataset provided by the Chinese Ministry of Agriculture and Rural Development. The findings reveal that the horizontal distribution pattern of specialty agriculture exhibits the formation of eight primary clusters. It is intriguing to observe that a majority of these clusters are situated at the intersection of two or three provincial administrative units, with the largest cluster occurring at the border of Chengdu and Chongqing. In terms of the vertical distribution pattern, the specialty agriculture in China’s mountainous areas are mainly distributed at low altitudes, i.e., below 500 m, and at gentle slopes of 4°–8°, and with increases in altitude or slope, the overall amount of specialty agriculture declines rapidly.

Objective To study the genotypes of ABO ambiguous blood group samples(n=20) and identify their molecular biological characteristics. Methods The serological phenotype of the samples was analyzed by serological techniques. Seven exons of ABO gene were amplified by polymerase chain reaction (PCR) and the PCR products were directly sequenced; the genotypes and sequences of ABO subtypes were analyzed. Results The serological phenotypes of 20 samples presenting ABO ambiguous blood group were as follows: weak A antigen (n=5), weak A antigen combined with anti-A1 antibody (n=5), normal A antigen combined with anti-A1 antibody (n=2), weak B antigen (n=8). The genotypes of them were as follows: Ax02/O01 (n=3), Ael07/O01 (n=2), B313/O01 (n=2), A204/O02 (n=1), A220/O01 (n=1), Ael07/O02 (n=1), Ael02/O01 (n=1), Ael02/O02 (n=1), Ax03/O01 (n=1), Ax03/O02 (n=1), B313/O02 (n=1), B302/O01 (n=1), B302/O02 (n=1), Bw19/O02 (n=1), A102/B313 (n=1) and A101/Bw37 (n=1). Conclusion ABO genotyping technology can accurately identify the ambiguous blood group of samples, provide definite genetic information of blood group and ensure the safety of clinical transfusion.

Hippo signalling is often deregulated in cancers. Here the authors show that CK2 enhances the cooperation of HHEX with YAP-TEAD complex to promote colorectal tumorigenesis.

BackgroundThe previous researches show that infertile patients have a higher incidence of endometritis and endometrial polyps, and the occurrence of these two diseases is related to changes in the microbiota of the genital tract. We aim to determine the composition and changing characteristics of the microbiota in the genital tract (especially the endometrium) of infertile patients with chronic endometritis or endometrial polyps, and find the correlation between it and the occurrence of diseases.MethodsThis is a prospective study. We collected genital tract biopsy samples from 134 asymptomatic infertile patients receiving assisted reproductive therapy before embryo transfer. Through pathological examination and 16S ribosomal RNA(16S rRNA) sequencing, we determined the distribution of chronic endometritis and endometrial polyps in these patients, as well as their distribution of reproductive tract microorganisms.ResultsCompared with the normal control group, the microbial group of reproductive tract in patients with chronic endometritis and endometrial polyps is changed, and there are significant species differences and relative abundance differences in the vagina, cervix and uterine cavity. Lactobacillus, the dominant flora of female genital tract, showed a change in abundance in patients with endometrial diseases. Endometrial microbiota composed of Staphylococcus, Gardnerella, Atopobium, Streptococcus, Peptostreptococcus, Chlamydia, Fusobacterium, Acinetobacter, etc. are related to chronic endometritis and endometrial polyps.ConclusionThe results showed that, compared with the normal control group, the endometrial microbiota of infertile patients with chronic endometritis or endometrial polyps did have significant changes in the relative abundance distribution of species, suggesting that changes in local microecology may be an important factor in the occurrence of disease, or even adverse pregnancy outcomes. The further study of endometrial microecology may provide a new opportunity to further improve the diagnosis and treatment strategy of chronic endometritis.

The exploration of important biomarkers associated with cancer development is crucial for diagnosing cancer, designing therapeutic interventions, and predicting prognoses. The analysis of gene co-expression provides a systemic perspective on gene networks and can be a valuable tool for mining biomarkers. The main objective of co-expression network analysis is to discover highly synergistic sets of genes, and the most widely used method is weighted gene co-expression network analysis (WGCNA). With the Pearson correlation coefficient, WGCNA measures gene correlation, and uses hierarchical clustering to identify gene modules. The Pearson correlation coefficient reflects only the linear dependence between variables, and the main drawback of hierarchical clustering is that once two objects are clustered together, the process cannot be reversed. Hence, readjusting inappropriate cluster divisions is not possible. Existing co-expression network analysis methods rely on unsupervised methods that do not utilize prior biological knowledge for module delineation. Here we present a method for identification of outstanding modules in a co-expression network using a knowledge-injected semi-supervised learning approach (KISL), which utilizes apriori biological knowledge and a semi-supervised clustering method to address the issue existing in the current GCN-based clustering methods. To measure the linear and non-linear dependence between genes, we introduce a distance correlation due to the complexity of the gene-gene relationship. Eight RNA-seq datasets of cancer samples are used to validate its effectiveness. In all eight datasets, the KISL algorithm outperformed WGCNA when comparing the silhouette coefficient, Calinski-Harabasz index and Davies-Bouldin index evaluation metrics. According to the results, KISL clusters had better cluster evaluation values and better gene module aggregation. Enrichment analysis of the recognition modules demonstrated their effectiveness in discovering modular structures in biological co-expression networks. In addition, as a general method, KISL can be applied to various co-expression network analyses based on similarity metrics. Source codes for the KISL and the related scripts are available online at https://github.com/Mowonhoo/KISL.git.

Abstract The air-filled organs (AOs) of vertebrates (lungs and swim bladders) have evolved unique functions (air-breathing or buoyancy control in water) to adapt to different environments. Thus far, immune responses to microbes in AOs have been described exclusively in the lungs of tetrapods. Similar to lungs, swim bladders (SBs) represent a mucosal surface, a feature that leads us to hypothesize a role for SB in immunity. In this study, we demonstrate that secretory IgT (sIgT) is the key SB immunoglobulin (Ig) responding to the viral challenge, and the only Ig involved in viral neutralization in that organ. In support of these findings, we found that the viral load of the SB from fish devoid of sIgT was much higher than that of control fish. Interestingly, similar to the lungs in mammals, the SB represents the mucosal surface in fish with the lowest content of microbiota. Moreover, sIgT is the main Ig class found coating their surface, suggesting a key role of this Ig in the homeostasis of the SB microbiota. In addition to the well-established role of SB in buoyancy control, our findings reveal a previously unrecognized function of teleost SB in adaptive mucosal immune responses upon pathogenic challenge, as well as a previously unidentified role of sIgT in antiviral defense. Overall, our findings indicate that despite the phylogenetic distance and physiological roles of teleost SB and mammalian lungs, they both have evolved analogous mucosal immune responses against microbes which likely originated independently through a process of convergent evolution.

Abstract Observability and detectability analyses are often used to guide the measurement setup and select the estimation models used in dynamic state estimation (DSE). Yet, marginally observable states of a synchronous machine prevent the direct application of conventional observability and detectability analyses in determining the existence of a DSE observer. To address this issue, the authors propose to identify the marginally observable states and their associate eigenvalues by finding the smallest perturbation matrices that make the system unobservable. The proposed method extends the observability and detectability analyses to marginally observable estimation models, often encountered in the DSE of a synchronous machine. The effectiveness and application of the proposed method are illustrated on the IEEE 10‐machine 39‐bus system, verified using the unscented Kalman filter and the extended Kalman filter, and compared with conventional methods. The proposed analysis method can be applied to guide the selection of estimation models and measurements to determine the existence of a DSE observer in power‐system planning.

The mechanical behavior of steel–concrete–steel (SCS) sandwich composite structures under low- or high-velocity impact loading has garnered increasing attention from researchers in recent decades. However, to date, limited effort has been dedicated to studying the residual resistance of SCS sandwich composite structures following impact damage. In a previous investigation, the authors developed a rubberized lightweight high-ductility cement composite (RLHDC) for implementation in double-layer steel–RLHDC–steel composite panels and examined the dynamic response of these panels under impact. To further explore the residual performance of impact-damaged composite panels, the present study conducts flexural tests on nine such panels. The study quantifies and analyzes the effects of various connector types, connector spacing, number of concrete layers, rubber powder content, and number of impacts on the residual flexural resistance of the impact-damaged composite panels. Detailed analysis is conducted on the failure modes, load–displacement curves, strain curves, and load–slip curves of the impact-damaged specimens. The test results reveal that the impact-damaged composite panels experience flexural failure with bond slip under static load. The residual flexural performance is found to be sensitive to the number of concrete layers and number of impacts. Finite element (FE) simulations are performed using LS-DYNA to investigate the residual flexural behavior of the impact-damaged composite panels. The restart method is employed in the simulations to mimic the post-impact static loading scenario. The agreement between the FE results and the experimental findings validates the model and provides a straightforward and effective approach for studying the residual performance of composite structures. An expanded parameter analysis leveraging the calibrated FE model indicates that the steel plate’s thickness and strength predominantly influence the composite panel’s residual resistance, whereas the influence from concrete strength proves less consequential.

There is still a significant gap between most high-tech fields in China and developed countries, and the relationship between the economic resilience of innovation systems and the innovation capability of the high-tech industry has received attention. Using data from 30 provinces in China, this study adopts the fuzzy-set qualitative comparative analysis approach to analyze the relationship between economic resilience and high-tech industry innovation capability, and the findings are as follows: (1) Technological talents and economic development are necessary conditions for explaining the high innovation capability of high-tech industries. (2) The combination of economic resilience and different factors constitutes the equivalent configuration of two high innovation capabilities and four low innovation capabilities. (3) Under high-intensity technological competition between governments, the increased agglomeration of technological talents, and high-quality economic development, the strengthening of economic resilience is conducive to enhancing the innovation capability of high-tech industries. (4) Under low-intensity technological competition between governments, a well-developed technology market, and increased agglomeration of technological talents, the strengthening of economic resilience is adverse to enhancing the innovation capability of high-tech industries. The main contribution of this study is to clarify the configuration mechanism of economic resilience that acts on the innovation capability of the high-tech industry and reveal the complex interaction between economic resilience and multiple factors.

As big-science infrastructures (BSIs) become the new infrastructure to support the construction of strong science and technology in China, how to choose an operation mode that is more conducive to achieving the construction goals of BSIs has become a current focus issue. The existing literature focuses more on the governance relationship between BSIs and universities or research institutes, while the important role of government has not yet been thoroughly analyzed. This study argues that government plays a fundamental role in the selection of operation modes for BSIs. Therefore, this study builds an evolutionary game model between the government and the contractor based on the perspective of asset specificity by analyzing the practical basis for the strategic choices of the government and the contractor for the operation of BSIs. The model is numerically simulated and analyzed. The research results indicate that the government’s decisions on operation strategies, outsourcing strategies, and the combination of the two significantly affect the strategic choices of the contractor, thereby affecting whether the government can obtain the value of asset specificity of BSIs. The government’s choice of the “independent operation” strategy or the combination “dependent operation + controlled outsourcing” strategy is more conducive to encouraging the contractor to choose the “cooperation” strategy for producing specific value for BSIs. The main contribution of this study is to clarify that the allocation of the government control right is the key factor in obtaining the value of asset specificity of BSIs.

Uncovering the mechanisms underlying phytoplankton community assembly remains a major challenge in freshwater ecology. The roles of environmental filtering and spatial processes in shaping phytoplankton metacommunity in Tibetan floodplain ecosystems under various hydrological conditions are still unclear. Here, multivariate statistics and a null model approach were used to compare the spatiotemporal patterns and assembly processes of phytoplankton communities in the river-oxbow lake system of Tibetan Plateau floodplain between non-flood and flood periods. The results showed that phytoplankton communities had significant seasonal and habitat variations, with the seasonal variations being more remarkable. Phytoplankton density, biomass, and alpha diversity were distinctly lower in the flood than non-flood period. The habitat differences (rivers vs. oxbow lakes) in phytoplankton community were less pronounced during the flood than non-flood period, most likely due to the increased hydrological connectivity. There was a significant distance–decay relationship only in lotic phytoplankton communities, and such relationship was stronger in the non-flood than flood period. Variation partitioning and PER-SIMPER analysis showed that the relative role of environmental filtering and spatial processes affecting phytoplankton assemblages varied across hydrological periods, with environmental filtering dominating in the non-flood period and spatial processes in the flood period. These results suggest that the flow regime plays a key role in balancing environmental and spatial factors in shaping phytoplankton communities. This study contributes to a deeper understanding of ecological phenomena in highland floodplains and provides a theoretical basis for floodplain ecosystem maintenance and ecological health management.

Recent studies have revealed that neural functions are involved in possibly every aspect of a cancer development, serving as bridges connecting microenvironmental stressors, activities of intracellular subsystems, and cell survival. Elucidation of the functional roles played by the neural system could provide the missing links in developing a systems-level understanding of cancer biology. However, the existing information is highly fragmented and scattered across the literature and internet databases, making it difficult for cancer researchers to use. We have conducted computational analyses of transcriptomic data of cancer tissues in TCGA and tissues of healthy organs in GTEx, aiming to demonstrate how the functional roles by the neural genes could be derived and what non-neural functions they are associated with, across different stages of 26 cancer types. Several novel discoveries are made, including i) the expressions of certain neural genes can predict the prognosis of a cancer patient; ii) cancer metastasis tends to involve specific neural functions; iii) cancers of low survival rates involve more neural interactions than those with high survival rates; iv) more malignant cancers involve more complex neural functions; and v) neural functions are probably induced to alleviate stresses and help the associated cancer cells to survive. A database, called NGC, is developed for organizing such derived neural functions and associations, along with gene expressions and functional annotations collected from public databases, aiming to provide an integrated and publicly available information resource to enable cancer researchers to take full advantage of the relevant information in their research, facilitated by tools provided by NGC.

ObjectiveThis study aimed to compare the dynamics of lower and upper genital tract microbiota in normal term pregnancy, histological chorioamnionitis (HCA), and clinical chorioamnionitis (CCA) patients to provide a reference for the diagnosis and treatment of chorioamnionitis (CAM) patients.MethodsWe prospectively collected vaginal and cervical secretions, as well as placenta tissues, fetal membranes, and amniotic fluid from normal-term pregnant women, HCA and CCA patients. Then, we performed genomic DNA extraction and PCR amplification for all samples. The eligible samples were analyzed by 16S ribosomal RNA (16S rRNA) sequencing. Additionally, all placenta tissues were histopathologically examined, and neonatal pharyngeal swabs and placenta tissues from the HCA and CCA groups were subjected to microbial culture.ResultsA total of 85 term pregnant women were enrolled in this study, including 34 in the normal group (N), 37 in the HCA group, and 14 in the CCA group. A total of 171 qualified samples were analyzed by 16S rRNA sequencing. The results suggested that the cervical microbiota was highly similar to the vaginal microbiota in normal term parturients, with Lactobacillus as the dominant bacterium. Moreover, there was no difference in the alpha and beta diversity of vaginal microbiota between the N, HCA, and CCA groups at the genus level. Besides, no significant differences were detected in cervical microbiome among the three groups. Regarding intrauterine microorganisms, the N and HCA groups had similar microbial composition but were different from the CCA group. No microbe was detected in the placental tissue of normal term parturients, while some microorganisms were found in the intrauterine amniotic fluid and fetal membrane samples. Regardless of cultivation or 16S rRNA sequencing, an extremely low microbial positive rate was detected in HCA and CCA intrauterine samples. Compared to the normal group, Lactobacillus was significantly reduced in the CCA group intrauterine, and Ureaplasma and Enterococcus increased with no statistically significant.ConclusionThe N, HCA and CCA groups had similar composition of vaginal and cervical microflora. Some normal-term pregnant women can harbor non-pathogenic microbiota in the uterine cavity. Sterile inflammation is more frequent than microbial-associated inflammation in term HCA and CCA parturients.

In the Post-COVID-19 Era, with the continuous improvement of the technical level, virtual teams are constantly evolving, and the relationship between leadership and the construction of virtual teams has received more and more attention. It is of great significance to explore the influence of participatory leadership on the construction of virtual teams from a psychological perspective by building a multi-agent simulation model. Based on a simulation platform of NetLogo, the results showed that (1) Participatory leadership is conducive to the expansion of the scale of virtual teams by providing greater space for the development of the members of virtual teams and meeting the team members’ requirements of planning and promotion in the environment, which is decentralized and non-authoritative. (2) However, losing management is not conducive to building a reasonable structure of team members under participatory leadership. (3) The scale of virtual teams and the efficiency of the virtual teams all depend on the relationship between participatory leadership, organizational trust, incentive mode, and the balance between cooperation and competition.

Floodplains play essential roles in the ecological functions of regional environments. The merging and coalescence of bacterial communities in aquatic environments results in periodic patterns driven by regular hydrological activities, which may, in turn, influence ecological activities. However, the degree of bacterial community coalescence in the lateral and vertical directions as well as the underlying hydrological mechanism of floodplain ecosystems is poorly understood. Therefore, we investigated the spatiotemporal patterns and coalescence processes of planktonic and sedimentary bacterial communities during normal and high-water periods in a floodplain ecosystem of the Yellow River source region. We classified bacterial operational taxonomic units (OTUs) based on 16S rRNA gene sequencing, and quantified community coalescence by calculating the proportions of overlapping OTUs, the contributions of upstream sources to downstream sinks, and positive/negative cohesion. The results revealed major differences in the composition and diversity of planktonic and sedimentary bacterial communities. Bacterial community diversity in the high-water period was higher than in the normal period. Laterally, hydrological connectivity promoted the immigration and coalescence of bacterial communities to oxbow lakes in both the mainstream and tributaries, with the coalescence degree of planktonic bacteria (2.9%) higher than that of sedimentary bacteria (1.7%). Vertically, the coalescence degree of mainstream planktonic and sedimentary bacterial communities was highest, reaching 2.9%. Co-occurrence network analysis revealed that hydrological connectivity increased the complexity of the bacterial network and enhanced the coalescence of keystone species to oxbow lakes. Furthermore, community coalescence improved the competitiveness and dispersal of bacterial communities. This study demonstrated that coalescence of bacterial communities is driven by hydrological connectivity in a floodplain ecosystem. Further studies should investigate the processes of bacterial community coalescence in floodplains in more detail, which could provide new approaches for environmental protection and ecological function preservation.

The high-tech industry is important in supporting China’s construction of a high-quality modern economic system. The high-tech industry markets are spaces for the supply and transaction of high-tech products. The existing research lacks in-depth discussions on the constituent factors and shaping mechanisms of the high-tech industry market. This paper constructs the market field configuration model of the high-tech industry and studies the impact of the market field configuration of the high-tech industry in 30 provinces of China on the innovation performance of the high-tech industry using the fuzzy-set qualitative comparative analysis method. The findings are as follows: (1) The three structural variables of network, institution, and cognition cannot individually constitute the necessary conditions for explaining the high or low innovation performance of high-tech industries; (2) Three high-tech industry market field configurations can lead to high innovation performance, and the condition combination among different configurations has a substitution effect; (3) Four high-tech industry market field configurations will lead to low innovation performance, in which the lack of multiple conditions in the network, system, and cognition is the main reason for the market failure. The research conclusions of this study highlight the cognitive role of market construction and the configuration characteristics of effective high-tech industry market fields, which provides practical enlightenment for China to improve the innovation performance of high-tech industries.

Wafer bin maps (WBMs) are essential test data in semiconductor manufacturing. WBM defect classification can provide critical information for the improvement of manufacturing processes and yield. Although deep-learning-based automatic defect classification models have demonstrated promising results in recent years, they require a substantial amount of labeled data for training, and manual labeling is time-consuming. Such limitations impede the practical application of existing algorithms. This study introduces a low-data defect classification algorithm based on contrastive learning. By employing momentum contrastive learning, the network extracts effective representations from large-scale unlabeled WBMs. Subsequently, a prototypical network is utilized for fine-tuning with only a minimal amount of labeled data to achieve low-data classification. Experimental results reveal that the momentum contrastive learning method improves the defect classification performance by learning feature representation from large-scale unlabeled data. The proposed method attains satisfactory classification accuracy using a limited amount of labeled data and surpasses other comparative methods in performance. This approach allows for the exploitation of information derived from large-scale unlabeled data, significantly reducing the reliance on labeled data.

Soybean meal is a class of by-products obtained from the processing of soybean products. Despite its high nutritional value, the presence of glycoside isoflavones limits human use of soybean meal. This study evaluated the effect of solid-state fermentation (SSF) with different edible mushroom mycelia (Pleurotus ostreatus, Hericium erinaceus, and Flammulina velutipes) on the proximate composition, antioxidant properties, and physicochemical properties of fermented soybean meal powder (SP). The results revealed that fermented SP had a higher nutritional value when compared to SP. P. ostreatus was the most pronounced among the three species. Crude protein content was found to have increased by 9.49%, while the concentration of glutamate and aspartic acid increased by 23.39% and 23.16%, respectively. SSF process significantly increased the total polyphenol content (TPC) and aglycone isoflavone content by 235.9% and 324.12%, respectively, resulting in increased antioxidant activity (evaluated by the DPPH, •OH, ABTS+ assays). Microstructural changes in fermented SP and nutrient degradation and utilization were observed. Thus, fermented SP can be used as a raw material with enhanced nutritional properties to develop new functional foods, such as plant-based foods represented by plant meat. It provides a promising approach for increasing the added value of soybean meal.

ObjectiveTo determine the effect of laser needle-knife on vertebroarterial morphology, fibrinogen and blood viscosity in a rabbit model of cervical spondylotic arteriopathy (CSA) and the mechanism of action involved.MethodsA number of 40 healthy common grade rabbits were divided into four groups: normal control, model, acupuncture, and laser needle knife group. The normal control group does not establish a CSA rabbit model, and the other groups all establish a CSA rabbit model, but they are treated in different ways. CSA model rabbits were treated with acupuncture and moxibustion at “fengchi” and “cervical Jiaji” points, rabbits in the laser needle knife group were treated with “Jiaji” points, and the acupuncture points were punctured with the laser needle knife. The location of the acupuncture points is determined according to the acupoint map of the experimental map. The right vertebroarterial morphology before and after the treatment was analyzed by scanning electron microscope, and FIB concentration and blood viscosity were determined using the coagulation method.ResultsAfter the treatment, the capillary and micropore hyperplasia in the laser needle knife group were more evident than that in the model group. Acupuncture and laser needle knife therapy can reduce whole blood viscosity (1/s, 5/s), and that the distinction between the two treatments is not statistically evident.ConclusionAcupuncture and laser needle knife can regulate the coagulation and fibrinolysis system in CSA, stimulate capillary and micropore hyperplasia, reduce blood viscosity, and improve blood circulation, which may be one of the therapeutic mechanisms behind the laser needle knife treatment of CSA.

In this paper, high-grade serous ovarian cancer (HGSOC) is studied, which is the most common histological subtype of ovarian cancer. We use a new analytical procedure to combine the bulk RNA-Seq sample for ovarian cancer, mRNA expression-based stemness index (mRNAsi), and single-cell data for ovarian cancer. Through integrating bulk RNA-Seq sample of cancer samples from TCGA, UCSC Xena and single-cell RNA-Seq (scRNA-Seq) data of HGSOC from GEO, and performing a series of computational analyses on them, we identify stemness markers and survival-related markers, explore stem cell populations in ovarian cancer, and provide potential treatment recommendation. As a result, 171 key genes for capturing stem cell characteristics are screened and one vital cancer stem cell subpopulation is identified. Through further analysis of these key genes and cancer stem cell subpopulation, more critical genes can be obtained as LCP2, FCGR3A, COL1A1, COL1A2, MT-CYB, CCT5, and PAPPA, are closely associated with ovarian cancer. So these genes have the potential to be used as prognostic biomarkers for ovarian cancer.

Building regional innovation systems (RISs) has become an important measure for China to implement an innovation-driven development strategy, but a moderately complex way to describe the characteristics of the RISs is needed for aiding the implementation of this strategy. Based on the subject-resource-environment (SRE) framework with five secondary conditions, this study takes 31 regions in China as cases, and studies the innovation capability of the RISs by using the fuzzy-set qualitative comparative analysis (fsQCA) approach. The findings are as follows: (1) Different combinations of the five conditions have generated two high and one low innovation capability configurations of RISs. (2) The two configurations of high innovation capability are the independent-investment type and the independent-open type. (3) The configuration of low innovation capability is the core-resource-deficiency type. This study has simplified the complexity of the RISs to a certain extent and revealed that the matching effect among core conditions is the key to obtaining high innovation capability. The conclusions provide practical implications for the RISs in China to acquire appropriate innovation capabilities according to their resource endowment conditions.

A teleost’s kidney was divided into head kidney and trunk kidney. The head kidney is an important lymphatic organ, while the trunk kidney mainly performs osmotic pressure regulation and excretion functions. Previous studies have shown that the teleost’s head kidney exerts a strong immune response against pathogen invasion, while the mechanism of immune response in the trunk kidney is still rarely reported. Therefore, in this study, we established an Infectious hematopoietic necrosis virus (IHNV) immersion infection model to compare the similarities and differences of immune response mechanisms between the head kidney and trunk kidney against viral infection. The results showed that IHNV infection causes severe tissue damage and inflammatory reaction in the head and trunk kidney, triggers a series of interferon cascade reactions, and produces strong immune response. In addition, the transcriptome data showed that the head kidney and trunk kidney had similar immune response mechanisms, which showed that the NOD-like receptor signaling pathway and Toll-like receptor signaling pathway were activated. In conclusion, despite functional differentiation, the teleost’s trunk kidney still has a strong immune response, especially the interferon-stimulated genes, which have stronger immune response in the trunk kidney than in the head kidney when responding to IHNV infection. This study contributes to a more comprehensive understanding of the teleost immune system and enriches the theory of kidney immunity in teleosts.

Attention is increasingly being paid to the influence of hinterland cities on port competitiveness, but in-depth research is lacking on the formation conditions and mechanism of hinterland cities’ influence on port competitiveness. Based on the technology–organization–environment (TOE) framework and the characteristics of Chinese government organizational behavior, in this study, we used fuzzy-set qualitative comparative analysis (fsQCA) to conduct a condition configuration analysis of 21 coastal ports and their hinterland cities in China. The findings showed the following: (1) The technology, organization, and environment conditions of hinterland cities cannot provide the necessary conditions for high or low port competitiveness alone: different combinations of these conditions have produced three high and four low port competitiveness configurations. (2) The three configurations of high port competitiveness are the organization–environment, economy–balance, and finance–balance types. Adequate government financial supply, high tertiary industry proportion, good economic development, and market openness are the core conditions required for achieving high port competitiveness. (3) The four configurations of low port competitiveness are finance–facilities–environment, capability–finance–environment, technology–finance–economy, and capability–industry–economy restrictions. Here, low-level innovation capability, inadequate government financial supply, and low tertiary industry proportion are the core conditions leading to low port competitiveness. We revealed the concurrent synergistic effect of the three conditions of technology, organization, and environment in hinterland cities and demonstrated the causal complexity and asymmetry of the impact of hinterland cities on port competitiveness. Our conclusions provide empirical evidence that will aid hinterland cities in formulating differentiated port competitiveness promotion policies according to their own conditions and endowments.

Background: Intestinal obstruction caused by intestinal fibrosis is a common and serious complication of Crohn's disease (CD). Intestinal fibroblasts, the main effector cells mediating gastrointestinal fibrosis, are activated during chronic inflammation. However, the mechanism of fibroblast activation in CD has not been well elucidated. Methods: Fibroblasts isolated from stenotic and nonstenotic intestines of CD patients were used for RNA sequencing. Immunohistochemical and immunofluorescent staining was performed to evaluate the correlation between intestinal fibrosis and YAP/TAZ expression in our CD cohort and a DSS-induced chronic colitis murine model. A Rho-associated coiled-coil-containing protein kinase 1 (ROCK1) inhibitor was used to explore the ROCK1-YAP/TAZ axis in intestinal fibroblasts in vitro and DSS-induced chronic colitis murine model in vivo. Findings: The expression of YAP/TAZ was significantly upregulated in stenotic fibroblasts, which was associated with the YAP/TAZ target gene signature. YAP/TAZ knockdown suppressed the activation of intestinal fibroblasts. In intestinal fibroblasts, YAP/TAZ were activated by the Rho-ROCK1 signalling pathway. High YAP/TAZ expression was positively correlated with ROCK1 expression, which is a prognostic marker for intestinal obstruction in CD patients. Interpretation: YAP/TAZ activation can lead to fibroblast activation and intestinal obstruction in CD. The effect of ROCK1 inhibitor on alleviating intestinal fibrosis is associated with YAP/TAZ inhibition. Targeted inhibition of YAP/TAZ in fibroblasts may be a potential therapeutic strategy to suppress intestinal fibrosis in CD. Funding: This work was supported by the National Key R&D Program of China (2019YFC1316002), the NSFC (81873547, 82073201, 81874177, 82000481) and the Shanghai Sailing Program (20YF1429400).

Apple fruit ring rot (FRR), caused by Botryosphaeria dothidea, is a worldwide disease that impacts Asian apple production regions. However, no substantial progress has thus far been made toward the mapping of candidate genes or the development of effective genetic makers. In this five-year study, the resistance of 1,733 F1 hybrids from the cross ‘Jonathan’ × ‘Golden Delicious’ was phenotyped by non-wounding inoculation with four B. dothidea isolates. We first conducted systematic comparison of different analytic strategies for bulk segregant analysis by re-sequencing (BSA-Seq) and obtained suitable one for outbreeding species such as Malus. Forty-six quantitative trait loci (QTL) for resistance/susceptibility to the four isolates, including one QTL ‘hotspot’ on chromosome 14, were identified via BSA-Seq. Using integrated multi-omics strategies including RNA-sequencing, parental re-sequencing, BSA-Seq and meta-analysis of RNA-sequencing, fifty-seven candidate genes and corresponding functional mutations from the QTL were predicted. Functional mutations located on the candidate genes were validated using kompetitive allele-specific PCR in hybrids and Malus germplasm accessions with extremely resistant/susceptible phenotypes. Ten effective markers for apple ring rot were developed. The results provide an example of rapid candidate gene mapping for complex traits in outbreeding species.

Combined heat and power economic dispatch (CHPED) problem aims to optimally schedule the output of generating units with minimum fuel cost, which is a highly non-linear, non-convex and large-scale global optimization problem with many practical constraints. The complexity of the problem demands solution methods with powerful search ability, robustness, and computational efficiency. This paper proposes a heterogeneous evolving cuckoo search (HECS) algorithm with a novel constraint-handling mechanism to solve the large-scale CHPED problem considering valve-point effect. Based on the cuckoo search algorithm, we apply a comprehensive learning strategy to enhance the search ability in the high-dimensional environment, and a heterogeneous evolving strategy to improve the robustness of the algorithm. Moreover, we develop a novel constraint-handling mechanism that uses strict mathematical methods to repair unfeasible solutions and avoid redundant calculation. 5 tests are conducted on 24-unit, 48-unit, 84-unit, 96-unit, and 192-unit systems and the results are compared with the state-of-the-art algorithms published in the year 2015-2019. The comparisons show that the HECS could annually save millions of dollars in some large-scale systems, which verify its effectiveness.

The fish intestinal mucosa is among the main sites through which environmental microorganisms interact with the host. Therefore, this tissue not only constitutes the first line of defense against pathogenic microorganisms but also plays a crucial role in commensal colonization. The interaction between the mucosal immune system, commensal microbiota, and viral pathogens has been extensively described in the mammalian intestine. However, very few studies have characterized these interactions in early vertebrates such as teleosts. In this study, rainbow trout (Oncorhynchus mykiss) was infected with infectious hematopoietic necrosis virus (IHNV) via a recently developed immersion method to explore the effects of viral infection on gut immunity and microbial community structure. IHNV successfully invaded the gut mucosa of trout, resulting in severe tissue damage, inflammation, and an increase in gut mucus. Moreover, viral infection triggered a strong innate and adaptive immune response in the gut, and RNA−seq analysis indicated that both antiviral and antibacterial immune pathways were induced, suggesting that the viral infection was accompanied by secondary bacterial infection. Furthermore, 16S rRNA sequencing also revealed that IHNV infection induced severe dysbiosis, which was characterized by large increases in the abundance of Bacteroidetes and pathobiont proliferation. Moreover, the fish that survived viral infection exhibited a reversal of tissue damage and inflammation, and their microbiome was restored to its pre−infection state. Our findings thus demonstrated that the relationships between the microbiota and gut immune system are highly sensitive to the physiological changes triggered by viral infection. Therefore, opportunistic bacterial infection must also be considered when developing strategies to control viral infection.

BackgroundAmine oxidase copper containing 1 (AOC1) is a gene whose biological function in colorectal cancer (CRC) has not been elucidated. Therefore, the purpose of this study was to investigate the clinical significance of AOC1 expression in CRC and its biological function in CRC cell lines.Materials and MethodsAOC1 expression levels were examined in paired CRC and peritumoral tissues, and distant liver metastatic tissues were examined using quantitative real-time PCR, western blotting, and immunohistochemistry staining. The log-rank test and Cox regression model were used to analyze the relationship between AOC1 expression and prognosis. Proliferation assays (Cell Counting Kit‐8 and colony formation assays), migration assays (Transwell and wound healing assays) and xenograft tumor formation in nude mice were performed to assess the biological role of AOC1 in CRC cells.ResultsAOC1 expression significantly increased in human CRC tissues, especially in liver metastases, and was associated with a worse prognosis. In addition, AOC1 had higher expression in tumor organoids than in normal organoids, suggesting that it was highly expressed in the tumor epithelium. Functional analysis demonstrated that AOC1 knockdown inhibited the proliferation and migration of CRC cells by inducing EMT in vitro. Xenograft tumor formation in nude mice showed that knockdown of AOC1 inhibited the tumor xenografts growth in vivo.ConclusionHigh expression of AOC1 was significantly associated with worse clinical outcomes, was an independent risk factor for poor prognosis, and promoted aggressive CRC cell phenotypes. AOC1 is expected to become a novel biomarker for predicting the prognosis of patients with CRC and an effective therapeutic target in clinical practice.

BackgroundWe investigated the prognostic effects and their patterns of immune infiltration of hippo pathway core genes in lung squamous cell carcinoma, in order to find some clues for underlying mechanisms of LUSC tumorigenesis and help developing new therapeutic methods.MethodsThe mutational data, transcriptome data and corresponding clinical medical information of LUSC patients were extracted from The Cancer Genome Atlas (TCGA) database. Differential expression genes (DEGs) and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were explored. Survival analysis for the hippo core genes and the prognostic model were performed. Immune infiltration was estimated by CIBERSORT algorithm and some immune checkpoints-related genes were further investigated.ResultsOverall, 551 LUSC samples were included in our study, consisting of 502 LUSC tumor samples and 49 adjacent normal samples, respectively. There were 1910 up-regulated DEGs and 2253 down-regulated DEGs were finally identified. The top five mutational hippo pathway core genes were LATS1 (4%), WWC1 (2%), TAOK1 (2%), TAOK3 (2%), and TAOK2 (2%), respectively. the mutation of LATS2 was highly associated with co-mutational NF2 (P

BackgroundThere have been limited treatment therapies for lung squamous cell carcinoma (LUSC). M6A-related genes may be the next therapeutic targets for LUSC. In this study, we explored the prognostic role and mutational characteristics of m6A-related genes in LUSC.MethodsLUSC gene expression data, mutational data, and corresponding clinical information were extracted from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified, and the mutation characteristics of LUSC patients were explored. Then, m6A-related genes were extracted and the correlations among the genes were detected. Finally, the prognostic roles of the genes were investigated and the nomogram model was developed. Besides, the protein–protein interaction (PPI) network was used to explore the potential interactions among the genes.ResultsIn total, there are 551 LUSC samples enrolled in our study, containing 502 LUSC tumor samples and 49 adjacent normal LUSC samples, respectively. There were 2970 upregulated DEGs and 1806 downregulated DEGs were further explored. IGF2BP1 and RBM15 had significant co-occurrence frequency (p < 0.05). Besides, METTL14 and ZC3H13 or YTHDF3 also had significant co-occurrence frequency (p < 0.05). All the m6A-related genes represent the positive correlation. WTAP was identified as a prognostic gene in the TCGA database while YTHDC1 and YTHDF1 were identified as prognostic genes. In multivariate Cox analysis, YTHDF1, age, pN stage, pTNM stage, and smoking were all identified as significant prognostic factors for OS.ConclusionWe investigated the expression patterns and mutational characteristics of LUSC patients and identified three potential independent prognostic m6A-related genes (WTAP, YTHDC1, and YTHDF1) for OS in LUSC patients.

Massive open online courses (MOOCs) have attracted much interest from educational researchers and practitioners around the world. There has been an increase in empirical studies about MOOCs in recent years, most of which used questionnaire surveys and quantitative methods to collect and analyze data. This study explored the research topics and paradigms of questionnaire-based quantitative research on MOOCs by reviewing 126 articles available in the Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) databases from January 2015 to August 2020. This comprehensive overview showed that: (a) the top three MOOC research topics were the factors influencing learners’ performance, dropout rates and continuance intention to use MOOCs, and assessing MOOCs; (b) for these three topics, many studies designed questionnaires by adding new factors or adjustments to extant theoretical models or survey instruments; and (c) most researchers used descriptive statistics to analyze data, followed by the structural equation model, and reliability and validity analysis. This study elaborated on the relationship of research topics and key factors in the research models by building factors-goals (F-G) graphs. Finally, we proposed some directions and recommendations for future research on MOOCs.