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Abstract Intervertebral disc degeneration (IVDD), a disease associated with ageing, is characterised by a notable increase in senescent nucleus pulposus cells (NPCs) as IVDD progresses. However, the specific mechanisms that regulate the senescence of NPCs remain unknown. In this study, we observed impaired autophagy in IVDD-NPCs, which contributed to the upregulation of NPCs senescence and the senescence-associated secretory phenotype (SASP). The dysregulated SASP disrupted NPCs viability and initiated extracellular matrix degradation. Conversely, the restoration of autophagy reversed the senescence phenotype by inhibiting GATA binding protein 4 (GATA4). Moreover, we made the novel observation that a cross-talk between histone H3 lysine 4 trimethylation (H3K4me3) modification and N6-methyladenosine(m6A)-methylated modification regulates autophagy in IVDD-NPCs. Mechanistically, lysine methyltransferase 2A (KMT2A) promoted the expression of methyltransferase-like 3 (METTL3) through H3K4me3 modification, whereas METTL3-mediated m6A modification reduced the expression of autophagy-associated 4a (ATG4a) by attenuating its RNA stability, leading to autophagy damage in NPCs. Silencing KMT2A and METTL3 enhanced autophagic flux and suppressed SASP expression in IVDD-NPCs. Therefore, targeting the H3K4me3-regulated METTL3/ATG4a/GATA4 axis may represent a promising new therapeutic strategy for IVDD.

Abstract There are significant differences in distributed generators (DGs) distribution and load characteristics between different voltage levels, which makes it difficult to match sources and loads. We focus on the problem of different consumption capacities at different voltage levels and the divergence of interests among investment entities, and propose a coordinated planning model for DGs and soft open points (SOPs) based on the Stackelberg game. Firstly, a model of a multi‐voltage level distribution networks (DNs) is constructed based on SOPs. Next, the source‐load matching degree is proposed as a measure of the degree of matching between sources and loads in the DN, and the source‐load consumption rate is selected as an indicator to evaluate the impact of the load on DG consumption. Following this, the interest demands of DG investors and distribution company (DisCo) in multi‐voltage levels DN are analyzed, a planning mode based on the Stackelberg game is proposed, and this is solved by combining the genetic algorithm with second‐order cone programming. Finally, the effectiveness of the planning model is tested and verified using an improved IEEE 28‐node system. The results show that the proposed model improves the DG consumption capacity of DNs with multiple voltage levels while protecting the interests of DG investors and DisCo.

Abstract Septic cardiomyopathy (SCM), a complication initiated by sepsis, presents a significant clinical challenge, leading to increased mortality rates. However, the mechanisms of SCM have not been fully uncovered. Our study involved analyzing RNA sequencing (RNA-seq) data from rat heart tissue, along with utilizing molecular docking and molecular dynamics (MD) simulations, to discover key targets and potential pharmacological actions of the calcitonin gene-related peptide (CGRP) against SCM. A lipopolysaccharide-induced SCM model was established in rats (LPS 10 mg/kg, intraperitoneal (i.p.)). Thereafter, the myocardial tissues from the three groups of rats (Ctrl group, LPS group, and CGRP group) (n = 5) were extracted and underwent RNA-seq, followed by bioinformatics analyses. The qPCR-validated hub targets potentially interacting with CGRP were identified. Following this, homology modeling was utilized to obtain the 3D structure of hub targets, and molecular docking was conducted to evaluate the interaction between CGRP and hub targets. MD simulations (300 ns) were performed to confirm the findings further. Our findings demonstrated that CGRP significantly lowered mortality in SCM rats. 633 DEGs were affected by LPS, contrasted with the Ctrl group. 96 DEGs were affected by CGRP compared to the LPS group. In total, ten fully annotated CGRP-triggered hub genes were obtained. The molecular docking and MD simulations indicate that the relationship between CGRP and eight hub genes is extremely strong. This research offers a thorough examination of the possible objectives and fundamental molecular processes of CGRP in combating SCM, laying the groundwork for investigating the potential protective mechanisms of CGRP against SCM.

Abstract Eosinophils, traditionally associated with allergic phenomena, play a pivotal role in inflammatory responses. Despite accumulating evidence suggesting their pro-inflammatory function upon activation, the underlying mechanisms governing eosinophil activation remain incompletely characterized. In this study, we investigate the local activation of pulmonary and colon eosinophils within the inflammatory microenvironment. Leveraging transcriptional sequencing, we identify TGF-β as a putative regulator of eosinophil activation, leading to the secretion of granule proteins, including peroxidase. Genetic deletion of TGF-β receptors on eosinophils resulted in the inhibition of peroxidase synthesis, affirming the significance of TGF-β signaling in eosinophil activation. Using models of HDM-induced asthma and DSS-induced colitis, we demonstrate the indispensability of TGF-β-driven eosinophil activation in both disease contexts. Notably, while TGF-β signaling did not significantly influence asthmatic inflammation, its knockout conferred protection against experimental colitis. This study delineates a distinct pattern of eosinophil activation within inflammatory responses, highlighting the pivotal role of TGF-β signaling in regulating eosinophil behavior. These findings deepen our comprehension of eosinophil-related pathophysiology and may pave the way for targeted therapeutic approaches in allergic and inflammatory diseases.

The jet can be applied to the yaw control of a projectile, however, the complex interaction of the jet with the supersonic mainstream makes the flow field complex and yaw force unpredictable. To reveal the evolution of flow structures under different pressure ratios (PRs), or momentum flux ratios, a transverse sonic jet injected into a supersonic laminar crossflow has been studied numerically. Large-eddy simulations are employed to simulate the flow fields and evolution tendency of flow structures under different PRs of 10, 50, 100, 300, and 500. Our results show clearly the shock and flow structures of the jet interaction with crossflow under different PRs. Moreover, we find that, with the increase of PR, a larger upstream recirculation zone (RZ) and jet shock core appear, which accelerates the transformation of the bow shock (BoS) and the instability of the jet shear layer due to its stronger interaction with the crossflow. In addition, a high PR also accelerates RZ instability and produces a strong compressing effect on the major counter-rotating vortex pair in the jet flow, which makes the streamwise vortex tube stronger in the wake. These findings provide important information for applications of jet control of projectiles.

Summary: Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a severe inflammatory condition that remains refractory; however, its molecular mechanisms are largely unknown. Previous studies have shown numerous compounds containing 4-indolyl-2-aminopyrimidine that display strong anti-inflammatory properties. In our research, we identified that a 4-Indole-2-Arylaminopyrimidine derivative named “IAAP” suppressed lipopolysaccharide (LPS)-induced inflammation. Immunoprecipitation and liquid chromatography-tandem mass spectrometry (LC-MS/MS) identified that IAAP interacts with a lysosomal cysteine protease, cathepsin L (CTSL), and restrains its activity. The nuclear factor kappa B (NF-κB) family plays a central role in controlling innate immunity. Canonical NF-κB activation, such as stimulation with lipopolysaccharide (LPS), typically involves the degradation of A20. We observed that IAAP suppression of CTSL prevented the LPS-induced degradation of A20, thereby ameliorating NF-κB activation. This study identifies CTSL as a crucial regulator of A20/NF-κB signaling and suggests IAAP as a potential lead compound for developing drugs to treat ALI/ARDS.

In high-latitude areas, the icing period is inevitable during winter. In view of the special mechanical environment of ice cracks faced during underwater launching in low-temperature ice zones, it is of great engineering value to expand the application of submarine-launched marine equipment in a low-temperature ice zone. The presence of floating ice inevitably enhances the nonlinearity of submarine-launched vehicles during high-speed water exit. A 6-degree-of-freedom(DOF) motion model of the vehicle was built by using the dynamic fluid interaction module(DFBI). Through comparative analysis of the underwater and cross-water motion stages of the submarine-launched vehicle under different ice hole sizes and shapes, the influence of ice holes on the evolution of the water-exit cavity was explored. The findings indicate that the ice hole has an obvious binding effect on the cavity during the process of water exit, and the binding effect increases with the decrease in ice hole size. For the same shape of the ice hole, a smaller ice hole size is accompanied by a greater impact on the pitching motion characteristics of the vehicle. For the same ice hole size, the circular ice hole has a greater impact on the pitching motion characteristics of the vehicle than square and triangular ice holes.

Abstract Malignant pleural effusion (MPE) is a common occurrence in advanced cancer and is often linked with a poor prognosis. Eosinophils were reported to involve in the development of MPE. However, the role of eosinophils in MPE remains unclear. To investigate this, we conducted studies using both human samples and mouse models. Increased eosinophil counts were observed in patients with MPE, indicating that the higher the number of eosinophils is, the lower the LENT score is. In our animal models, eosinophils were found to migrate to pleural cavity actively upon exposure to tumor cells. Intriguingly, we discovered that a deficiency in eosinophils exacerbated MPE, possibly due to their anti-tumor effects generated by modifying the microenvironment of MPE. Furthermore, our experiments explored the role of the C-C motif chemokine ligand 11 (CCL11) and its receptor C-C motif chemokine receptor 3 (CCR3) in MPE pathology. As a conclusion, our study underscores the protective potential of eosinophils against the development of MPE, and that an increase in eosinophils through adoptive transfer of eosinophils or increasing their numbers improved MPE.

Abstract Increased levels of cytosolic DNA in lung tissues play an important role in acute lung injury. However, the detailed mechanisms involved remain elusive. Here, we found that cyclic GMP-AMP synthase (cGAS, a cytosolic DNA sensor) expression was increased in airway epithelium in response to increased cytosolic DNA. Conditional deletion of airway epithelial cGAS exacerbated acute lung injury in mice, cGAS knockdown augmented LPS-induced production of interleukin (IL)-6 and IL-8. Mechanically, deletion of cGAS augmented expression of phosphorylated CREB (cAMP response element-binding protein), and cGAS directly interacted with CREB via its C-terminal domain. Furthermore, CREB knockdown rescued the LPS-induced excessive inflammatory response caused by cGAS deletion. Our study demonstrates that airway epithelial cGAS plays a protective role in acute lung injury and confirms a non-canonical cGAS-CREB pathway that regulates the inflammatory responses in airway epithelium to mediate LPS-induced acute lung injury.

Abstract Patients with chronic obstructive pulmonary disease (COPD) who exhibit elevated blood eosinophil levels often experience worsened lung function and more severe emphysema. This implies the potential involvement of eosinophils in the development of emphysema. However, the precise mechanisms underlying the development of eosinophil-mediated emphysema remain unclear. In this study, we employed single-cell RNA sequencing to identify eosinophil subgroups in mouse models of asthma and emphysema, followed by functional analyses of these subgroups. Assessment of accumulated eosinophils unveiled distinct transcriptomes in the lungs of mice with elastase-induced emphysema and ovalbumin-induced asthma. Depletion of eosinophils through the use of anti-interleukin-5 antibodies ameliorated elastase-induced emphysema. A particularly noteworthy discovery is that eosinophil-derived cathepsin L contributed to the degradation of the extracellular matrix, thereby leading to emphysema in pulmonary tissue. Inhibition of cathepsin L resulted in a reduction of elastase-induced emphysema in a mouse model. Importantly, eosinophil levels correlated positively with serum cathepsin L levels, which were higher in emphysema patients than those without emphysema. Expression of cathepsin L in eosinophils demonstrated a direct association with lung emphysema in COPD patients. Collectively, these findings underscore the significant role of eosinophil-derived cathepsin L in extracellular matrix degradation and remodeling, and its relevance to emphysema in COPD patients. Consequently, targeting eosinophil-derived cathepsin L could potentially offer a therapeutic avenue for emphysema patients. Further investigations are warranted to explore therapeutic strategies targeting cathepsin L in emphysema patients.

In wireless communication and radar systems, long-distance signal transmission poses significant challenges that affect overall system performance. In this paper, we propose an innovative bistatic radar cross section (RCS) testing system designed to address these challenges, with a particular focus on its long-distance signal transmission capabilities. This system is capable of accurately measuring the RCS of a target and improving multipath channel modeling accuracy by using precise RCS values. The integrated upper computer software extracts amplitude and phase information from received echo signals, processes these data, and provides detailed outputs including the target’s RCS, one-dimensional image, and two-dimensional image. The experimental results obtained prove that this system can not only achieve effective long-distance signal transmission but also substantially enhance the accuracy of RCS measurements, offering reliable support for multipath channel modeling. However, the conclusions drawn are preliminary and require further experimental validation to fully substantiate this system’s performance. Future work will focus on improving system accuracy, minimizing the impact of environmental noise, and optimizing data-processing methods to enhance the efficiency of wireless communication and radar applications.

Underwater image enhancement technology is crucial for the human exploration and exploitation of marine resources. The visibility of underwater images is affected by visible light attenuation. This paper proposes an image reconstruction method based on the decomposition–fusion of multi-channel luminance data to enhance the visibility of underwater images. The proposed method is a single-image approach to cope with the condition that underwater paired images are difficult to obtain. The original image is first divided into its three RGB channels. To reduce artifacts and inconsistencies in the fused images, a multi-resolution fusion process based on the Laplace–Gaussian pyramid guided by a weight map is employed. Image saliency analysis and mask sharpening methods are also introduced to color-correct the fused images. The results indicate that the method presented in this paper effectively enhances the visibility of dark regions in the original image and globally improves its color, contrast, and sharpness compared to current state-of-the-art methods. Our method can enhance underwater images in engineering practice, laying the foundation for in-depth research on underwater images.

In this manuscript, we survey a numerical algorithm based on the combination of the homotopy perturbation method and the Sadik transform for solving the time-fractional nonlinear modified shallow water waves (called Kawahara equation) within the frame of the Caputo–Prabhakar (CP) operator. The nonlinear terms are handled with the assistance of the homotopy polynomials. The stability analysis of the implemented method is studied by using S-stable mapping and the Banach contraction principle. Also, we use the fixed-point method to determine the existence and uniqueness of solutions in the given suggested model. Finally, some numerical simulations are illustrated to display the accuracy and efficiency of the present numerical method. Moreover, numerical behaviors are captured to validate the reliability and efficiency of the scheme.

Breast cancer is one of the most common causes of death in women. Early signs of breast cancer can be an abnormality depicted on breast images like breast ultrasonography. Unfortunately, ultrasound images contain a lot of noise, which greatly increases the difficulty for doctors to interpret them. In recent years, computer-aided diagnosis (CAD) has been widely used in medical images, reducing the workload of doctors and the probability of misdiagnosis. However, it still faces the following challenges in clinical practice: one is the lack of interpretability, and another is that the accuracy is not high enough. In this paper, we propose a classification model of breast ultrasound images that leverages tumor boundaries as prior knowledge and strengthens the model to guide classification. Furthermore, we employ the advantages of convolutional neural network (CNN) to extract local features and Transformer to extract global features to achieve information balance and complementarity between the two neural network models which increase the recognition performance of the model. Additionally, an explanation method is used to generate visual results, thereby improving the poor interpretability of deep learning models. Finally, we evaluate the model on the BUSI dataset and compare it with other CNN and Transformer models. Experimental results show that the proposed model obtains an accuracy of 0.9870 and an F1 score of 0.9872, achieving state-of-the-art performance.

In the realm of autonomous driving tort, a significant disparity exists in the parties’ access to autonomous driving data and essential technical information, resulting in challenges in unilateral proof. The traditional burden of proof framework in driving litigation is inadequate for direct application in the autonomous driving sphere. As we approach the era of widespread autonomous driving operations, there is an urgent need to clarify and redefine the allocation of the burden of proof in specific litigations. Utilizing comparative legal analysis and case studies, this paper delves into the disparities in the legislative provisions concerning the burden of proof for autonomous driving in Germany and China. China can learn from Germany’s legislative precedence in shifting the burden of proof for “product defect” and “fault” onto the manufacturer, thereby requiring the infringed party to merely furnish preliminary evidence indicating a “causal relationship between the defect and the damage”. This approach mitigates the evidentiary burden on the aggrieved party, clarifies the litigation procedures, incentivizes manufacturers to enhance the technology, reinforces risk management, and ultimately facilitates the progression of autonomous driving technology.

Shear-keyed inter-modular connections (IMCs) are integral components of high-rise modular steel structures (MSSs), providing robust interconnectivity to support grouped tubular columns across modules, thereby introducing column discontinuities and distinctive structural behavior. This study conducted a comprehensive numerical assessment and theoretical analysis of the axial compression behavior of grouped tubular columns based on a validated finite element model (FEM), which captured the member-to-structural level behavior of steel hollow section (SHS) columns and accommodated geometric imperfections. An FEM was initially developed and validated using 28 axial compression tests documented in the literature, comprising 15 tests on cold-formed and 13 on hot-rolled steel hollow section (SHS) columns. The primary parameters explored in tests included material properties (stainless/carbon), processing methods (cold-formed/hot-rolled), cross-section sizes (D/B), cross-sectional or member slenderness ratios (D/tc, B/tc, or Lc/r), and the number of columns (1, 7, and 11). A comprehensive parametric numerical study involving 103 grouped tubular column FEMs then investigated the influence of initial imperfection, shear-key height (Lt), thickness (tt), steel tube length (D), width (B), thickness (tc), and height (Lc) alongside the effects of space between tube and key, and the gap between tubes. The results indicated that the load-shortening behavior of the grouped columns consists of linear elastic, inelastic, and recession stages. The failure modes observed primarily displayed an S-shaped pair of inward and outward local buckling on the outer sides and double S-shaped local buckling on the interior sides. The buckling arose near the shear key or at 1/4 or 1/2 of the column height. None of the considered models experienced global buckling. Increasing tt, Lt, tc, D, or B enhances strength and stiffness, while Lc or Lc/r linearly affects stiffness and ductility. The columns’ nominal axial strength was reduced because of the shear keys, which decreased compression yielding and caused localized elastic buckling. Subsequently, the theoretical analysis revealed that the design codes do not capture this behavior, and thus, their capacity estimate yields inaccurate findings. This discrepancy renders existing code prediction equations, including those from Indian (IS800), New Zealand (NZS400), European (EC3:1-1), Canadian (CSA S16), American (AISC360-16), and Chinese (GB50017) standards, as well as the model proposed by Li et al., non-conservative. To assure conservative results, the paper recommended modification of existing standards and proposed prediction equations based on a fourth-order differential equation that describes the actual behavior of modular steel columns grouped with shear keys. The proposed design approach accurately predicted the axial compression capacity of modular steel-grouped columns, proving conservative yet effective. This provides valuable data that could transform design and construction techniques for MSSs, extending to various column and IMC forms through adaptable design parameters. This enhancement in structural performance and safety significantly contributes to the advancement of modular construction practices.

Objective To investigate the willingness of whole blood donors to donate apheresis platelets and analyze its influencing factors. Methods A total of 400 whole blood donors from Kunshan Blood Station and Leshan Blood Station from January to May, 2023 were surveyed by random sampling, and their willingness to donate apheresis platelets were analyzed by univariate analysis and binary logistic regression analysis. Results A total of 386 valid questionnaires were collected, with a recovery rate of 96.5%. Among the 386 whole blood donors, 177 were willing to donate apheresis platelets, accounting for 45.9%. Univariate analysis showed that gender, age, education level, blood donation times, average blood donation volume, adverse reactions to blood donation, understanding of platelets, and family members' attitude towards blood donation were the main factors affecting the willingness of whole blood donors to donate platelets, and binary logistic regression analysis showed that gender, age, blood donation times, average blood donation volume, understanding of platelets and family members' attitude towards blood donation were the main factors. Conclusion Targeted recruitment of whole blood donors should be conducted to recruit more apheresis platelet donors, so as to meet clinical demand of apheresis platelets.

Abstract Background and objective In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artificial intelligence (AI) and immunohistochemistry (IHC)-stained whole-slide images (WSIs) of colorectal cancer (CRC) patients to quantitatively assess the spatial associations between tumor cells and immune cells. To achieve this, we employ the Morisita-Horn ecological index (Mor-index), which allows for a comprehensive analysis of the spatial distribution patterns between tumor cells and immune cells within the TME. Materials and methods In this study, we employed a combination of deep learning technology and traditional computer segmentation methods to accurately segment the tumor nuclei, immune nuclei, and stroma nuclei within the tumor regions of IHC-stained WSIs. The Mor-index was used to assess the spatial association between tumor cells and immune cells in TME of CRC patients by obtaining the results of cell nuclei segmentation. A discovery cohort (N = 432) and validation cohort (N = 137) were used to evaluate the prognostic value of the Mor-index for overall survival (OS). Results The efficacy of our method was demonstrated through experiments conducted on two datasets comprising a total of 569 patients. Compared to other studies, our method is not only superior to the QuPath tool but also produces better segmentation results with an accuracy of 0.85. Mor-index was quantified automatically by our method. Survival analysis indicated that the higher Mor-index correlated with better OS in the discovery cohorts (HR for high vs. low 0.49, 95% CI 0.27–0.77, P = 0.0014) and validation cohort (0.21, 0.10–0.46,

Abstract The RNA 5-methylcytosine (m5C) modification has been demonstrated to be an important epigenetic regulator and to impact colorectal cancer (CRC) progression. However, the potential roles of m5C modification in immune cell infiltration in the CRC tumor microenvironment (TME) remain unknown. The m5C modification phenotypes were comprehensively evaluated based on 14 m5C regulators in a meta-CRC cohort of 1792 patients and systematically correlated with the m5C modification phenotypes, immune cell infiltration characteristics and known biological processes. The m5Cscore model was constructed by principal component analysis (PCA) algorithms to quantify the m5C modification phenotypes of individual CRC samples and was used to predict the immunotherapy response. We identified three m5C modification phenotypes associated with distinct clinical outcomes and biological processes among the 1792 meta-CRC patients. Three phenotypes with a highly consistent TME landscape and characteristics were revealed: immune excluded, immune desert and immune inflammation. The meta-CRC patients were divided into high and low m5Cscore subgroups based on the m5Cscore. The m5Cscore was confirmed to have a negative correlation with infiltrating immune cells and PD-L1 expression and a positive correlation with tumor mutation burden (TMB), mutation rate and microsatellite instability (MSI) score. Moreover, patients in the low m5Cscore group had better immunotherapy responses and significant durable survival benefits in independent anti-PD-1/L1 immunotherapy cohorts for the immune checkpoint inhibitor (ICI) therapeutic strategy. This study revealed that m5C modification plays a crucial role in TME composition and complexity. Comprehensive evaluation of the m5C modification phenotypes of individual patients will enhance our understanding of TME characteristics and promote the application of more appropriate and personalized treatment strategies.

Summary: Background: Currently, the diagnostic testing for the primary origin of liver metastases (LMs) can be laborious, complicating clinical decision-making. Directly classifying the primary origin of LMs at computed tomography (CT) images has proven to be challenging, despite its potential to streamline the entire diagnostic workflow. Methods: We developed ALMSS, an artificial intelligence (AI)-based LMs screening system, to provide automated liver contrast-enhanced CT analysis for distinguishing LMs from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), as well as subtyping primary origin of LMs as six organ systems. We processed a CECT dataset between January 1, 2013 and June 30, 2022 (n = 3105: 840 HCC, 354 ICC, and 1911 LMs) for training and internally testing ALMSS, and two additional cohorts (n = 622) for external validation of its diagnostic performance. The performance of radiologists with and without the assistance of ALMSS in diagnosing and subtyping LMs was assessed. Findings: ALMSS achieved average area under the curve (AUC) of 0.917 (95% confidence interval [CI]: 0.899–0.931) and 0.923 (95% [CI]: 0.905–0.937) for differentiating LMs, HCC and ICC on both the internal testing set and external testing set, outperformed that of two radiologists. Moreover, ALMSS yielded average AUC of 0.815 (95% [CI]: 0.794–0.836) and 0.818 (95% [CI]: 0.790–0.842) for predicting six primary origins on both two testing sets. Interestingly, ALMSS assigned origin diagnoses for LMs with pathological phenotypes beyond the training categories with average AUC of 0.761 (95% [CI]: 0.657–0.842), which verify the model's diagnostic expandability. Interpretation: Our study established an AI-based diagnostic system that effectively identifies and characterizes LMs directly from multiphasic CT images. Funding: National Natural Science Foundation of China, Guangdong Provincial Key Laboratory of Medical Image Processing.

It is long observed that females tend to live longer than males in nearly every country. However, the underlying mechanism remains elusive. In this study, we discovered that genetic associations with longevity are on average stronger in females than in males through bio-demographic analyses of genome-wide association studies (GWAS) dataset of 2178 centenarians and 2299 middle-age controls of Chinese Longitudinal Healthy Longevity Study (CLHLS). This discovery is replicated across North and South regions of China, and is further confirmed by North-South discovery/replication analyses of different and independent datasets of Chinese healthy aging candidate genes with CLHLS participants who are not in CLHLS GWAS, including 2972 centenarians and 1992 middle-age controls. Our polygenic risk score analyses of eight exclusive groups of sex-specific genes, analyses of sex-specific and not-sex-specific individual genes, and Genome-wide Complex Trait Analysis using all SNPs all reconfirm that genetic associations with longevity are on average stronger in females than in males. Our discovery/replication analyses are based on genetic datasets of in total 5150 centenarians and compatible middle-age controls, which comprises the worldwide largest sample of centenarians. The present study's findings may partially explain the well-known male-female health-survival paradox and suggest that genetic variants may be associated with different reactions between males and females to the same vaccine, drug treatment and/or nutritional intervention. Thus, our findings provide evidence to steer away from traditional view that “one-size-fits-all” for clinical interventions, and to consider sex differences for improving healthcare efficiency. We suggest future investigations focusing on effects of interactions between sex-specific genetic variants and environment on longevity as well as biological function.

The quantum network correlations play significant roles in long distance quantum communication, quantum cryptography and distributed quantum computing. Generally it is very difficult to characterize the multipartite quantum network correlations such as nonlocality, entanglement and steering. In this paper, we propose the network and the genuine network quantum steering models from the aspect of probabilities in the star network configurations. Linear and nonlinear inequalities are derived to detect the network and genuine network quantum steering when the central party performs one fixed measurement. We show that our criteria can detect more quantum network steering than that from the violation of the n-locality quantum networks. Moreover, it is shown that biseparable assemblages can demonstrate genuine network steering in the star network configurations.

Influenza viruses are the leading cause of upper respiratory tract infections, leading to several global pandemics and threats to public health. Due to the continuous mutation of influenza A viruses, there is a constant need for the development of novel antiviral therapeutics. Recently, natural antimicrobial peptides have provided an opportunity for the discovery of anti-influenza molecules. Here, we designed several peptides based on pheasant cathelicidin and tested their antiviral activities and mechanisms against the H1N1 virus. Of note, the designed peptides Pc-4 and Pc-5 were found to inhibit replication of the H1N1 virus with an IC50 = 8.14 ± 3.94 µM and 2.47 ± 1.95 µM, respectively. In addition, the cyclic peptide Pc-5 was found to induce type I interferons and the expression of interferon-induced genes. An animal study showed that the cyclic peptide Pc-5 effectively inhibited H1N1 virus infection in a mouse model. Taken together, our work reveals a strategy for designing cyclic peptides and provides novel molecules with therapeutic potential against influenza A virus infection.

AlCrFeNi multi-component alloys with excellent mechanical properties have been designed and extensively investigated in recent years. The massive fabrication of sheets will be an effective way for industrial application, where hot rolling is the inevitable process. After hot rolling, the mechanical properties could be further tailored. In this study, the effects of heat treatments on a dual-phase Al17Cr10Fe36Ni36Mo1 hot-rolled plate were systematically investigated, including: (i) annealing (700 °C, 850 °C, 1000 °C and 1150 °C for 1 h, respectively), (ii) solution and single aging (1150 °C for 1 h and 700 °C for 4 h), (iii) solution and double aging (1150 °C for 1 h, 700 °C for 4 h and 650 °C for 1 h). The B2 precipitates with varied morphologies were observed in the FCC matrix of the hot-rolled alloy after a heat treatment range from 700 °C to 1000 °C for 1 h, and the BCC particles in the B2 matrix were dissolved when the heat treatment temperature was higher than 1000 °C. The hot-rolled alloy heat treated at 700 °C for 1 h had the highest yield strength, and the hot-rolled alloy treated at 1150 °C for 1 h showed the lowest yield strength. After a solution at 1150 °C for 1 h, aging at 700 °C for 4 h and 650 °C for 1 h, the L12 phase and BCC particles were precipitated in the FCC and B2 matrices, and B2 nanoprecipitates were observed around the FCC grain boundaries. The solution and double aging alloy exhibit the tensile strength of 1365.7 ± 9.5 MPa, a fracture elongation of 14.2 ± 1.5% at 20 °C, a tensile strength of 641.4 ± 6.0 MPa, and a fracture elongation of 16.9 ± 1.0% at 700 °C, showing great potential for application.

Dynamic surface control (DSC) is a recognized nonlinear control approach for high-order systems. However, as the complexity of the system increases and the first-order filter (FOF) is introduced, there exists a singularity problem, i.e., the control input will reach infinity. This limits the application of the DSC algorithm to a class of real-world systems with complex dynamics. To address the problem of singularity, we present a novel DSC approach called nonsingular dynamic surface control (NDSC), which completely avoids the singularity problem and significantly improves the overall control performance. NDSC includes a nonsingular hypersurface, which is constructed by the error between system states and virtual control inputs. Then the nonsingular hypersurface will be applied to derive the corresponding control law with the aid of the DSC approach to ensure the output of the system can track arbitrary desired trajectories. NDSC has the following novel features: (1) finite time asymptotic stabilization can be guaranteed; (2) the performance of NDSC is insensitive to the FOF’s parameter variation once the maximum tracking error of FOF is bounded, which significantly reduces reliance on the control sampling frequency. We thoroughly evaluate the proposed NDSC algorithm in an unmanned aerial vehicle (UAV) system with an underactuated nature. Finally, the simulation results illustrate and highlight the effectiveness and superiority of the proposed control algorithm.

Background Although the anti-PD-1+LAG-3 and the anti-PD-1+CTLA-4 combinations are effective in advanced melanoma, it remains unclear whether their mechanisms of action overlap.Methods We used single cell (sc) RNA-seq, flow cytometry and IHC analysis of responding SM1, D4M-UV2 and B16 melanoma flank tumors and SM1 brain metastases to explore the mechanism of action of the anti-PD-1+LAG-3 and the anti-PD-1+CTLA-4 combination. CD4+ and CD8+ T cell depletion, tetramer binding assays and ELISPOT assays were used to demonstrate the unique role of CD4+T cell help in the antitumor effects of the anti-PD-1+LAG-3 combination.Results The anti-PD-1+CTLA-4 combination was associated with the infiltration of FOXP3+regulatory CD4+ cells (Tregs), fewer activated CD4+T cells and the accumulation of a subset of IFNγ secreting cytotoxic CD8+T cells, whereas the anti-PD-1+LAG-3 combination led to the accumulation of CD4+T helper cells that expressed CXCR4, TNFSF8, IL21R and a subset of CD8+T cells with reduced expression of cytotoxic markers. T cell depletion studies showed a requirement for CD4+T cells for the anti-PD-1+LAG-3 combination, but not the PD-1-CTLA-4 combination at both flank and brain tumor sites. In anti-PD-1+LAG-3 treated tumors, CD4+T cell depletion was associated with fewer activated (CD69+) CD8+T cells and impaired IFNγ release but, conversely, increased numbers of activated CD8+T cells and IFNγ release in anti-PD-1+CTLA-4 treated tumors.Conclusions Together these studies suggest that these two clinically relevant immune checkpoint inhibitor (ICI) combinations have differential effects on CD4+T cell polarization, which in turn, impacted cytotoxic CD8+T cell function. Further insights into the mechanisms of action/resistance of these clinically-relevant ICI combinations will allow therapy to be further personalized.

ABSTRACT: Cockfighting is popular worldwide, dating back to 2,800 BC. Primarily, 5 modern Chinese gamecock breeds exist, located in the northeast (Luxi and Henan), west (Turpan), south (Xishuangbanna), and southeast (Zhangzhou) of China. However, whether Chinese gamecocks were derived from a single origin or multiple origins remains controversial. Therefore, this study used next-generation resequencing data to elucidate the origin of Chinese gamecocks by constructing genome-wide and SRY-box transcription factor 5 (SOX5) gene phylogenetic trees. Data from 161 chickens from 27 breeds, including 9 gamecock breeds, were included. Before constructing the SOX5 gene tree, we validated that the pea-comb phenotype mutation in all gamecock breeds was attributed to copy number variation in intron 1 of the SOX5 gene, as previously reported. The specific region was chr1: 65,838,000 to 65,846,000. The phylogenetic tree results suggested that Zhangzhou and Xishuangbanna gamecocks have a monophyletic origin, while Luxi, Henan, and Turpan gamecocks have a common ancestor. Our study provides genome-wide evidence that Chinese gamecocks have multiple origins and advances the understanding of the genetic mechanisms of the pea-comb characteristic.

Abstract Background Cluster analysis is utilized frequently in scientific theory and applications to separate data into groups. A key assumption in many clustering algorithms is that the data was generated from a population consisting of multiple distinct clusters. Clusterability testing allows users to question the inherent assumption of latent cluster structure, a theoretical requirement for meaningful results in cluster analysis. Results This paper proposes methods for clusterability testing designed for high-dimensional data by utilizing sparse principal component analysis. Type I error and power of the clusterability tests are evaluated using simulated data with different types of cluster structure in high dimensions. Empirical performance of the new methods is evaluated and compared with prior methods on gene expression, microarray, and shotgun proteomics data. Our methods had reasonably low Type I error and maintained power for many datasets with a variety of structures and dimensions. Cluster structure was not detectable in other datasets with spatially close clusters. Conclusion This is the first analysis of clusterability testing on both simulated and real-world high-dimensional data.

Abstract For lightweight steel frame structures consisting of steel H-beams and cold-formed steel columns filled with concrete, seismic performance comparison tests and numerical simulation analyses were performed for bare and infilled frames. The effects of the lightweight wall panels, the axial compression ratio and the wall thickness of the steel sections of the columns on the seismic properties of the structure were investigated. The failure of the bare frame was concentrated in the weld fractures at the beam-column joints. When the wall panels were embedded in the frame, the damage was concentrated at the corners and edges of the wall panels and the connectors. The wall panels significantly improved the initial stiffness of the frame, early energy dissipation and resistance, and the wall panel energy dissipation rate was initially as great as 91%. As the axial compression ratio increased, the resistance of the structure significantly decreased. Under monotonic loading, the resistance on the structure with an axial compression ratio of 0.4 was reduced by nearly 44% compared to the structure without axial compression. Increasing the wall thickness of the steel sections of the columns increased the load-bearing capacity of the structure, but the increase diminished with increasing wall thickness.

Abstract Liver hepatocellular carcinoma (LIHC) is one of the most common malignancies and places a heavy burden on patients worldwide. HAUS augmin-like complex subunit 5 (HAUS5) is involved in the occurrence and development of various cancers. However, the functional role and significance of HAUS5 in LIHC remain unclear. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and Gene Expression Omnibus (GEO) databases were used to analyze the mRNA expression of HAUS5. The value of HAUS5 in predicting LIHC prognosis and the relationship between HAUS5 and clinicopathological features were assessed by the Kaplan–Meier plotter and UALCAN databases. Functional enrichment analyses and nomogram prediction model construction were performed with the R packages. The LinkedOmics database was searched to reveal co-expressed genes associated with HAUS5. The relationship between HAUS5 expression and immune infiltration was explored by searching the TISIDB database and single-sample gene set enrichment analysis (ssGSEA). The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA) databases were used to evaluate HAUS5 protein expression. Finally, the effect of HAUS5 on the proliferation of hepatoma cells was verified by CCK-8, colony formation and EdU assays. HAUS5 is aberrantly expressed and associated with a poor prognosis in most tumors, including LIHC. The expression of HAUS5 is significantly correlated with clinicopathological indicators in patients with LIHC. Functional enrichment analysis showed that HAUS5 was closely related to DNA replication, cell cycle and p53 signaling pathway. HAUS5 may serve as an independent risk factor for LIHC prognosis. The nomogram based on HAUS5 had area under the curve (AUC) values of 0.74 and 0.77 for predicting the 3-year and 5-year overall survival (OS) of LIHC patients. Immune correlation analysis showed that HAUS5 was significantly associated with immune infiltration. Finally, the results of in vitro experiments showed that when HAUS5 was knocked down, the proliferation of hepatoma cells was significantly decreased. The pan-oncogene HAUS5 is a positive regulator of LIHC progression and is closely associated with a poor prognosis in LIHC. Moreover, HAUS5 is involved in immune infiltration in LIHC. HAUS5 may be a new prognostic marker and therapeutic target for LIHC patients.

The development of new drugs is a long and costly process, Computer-aided drug design reduces development costs while computationally shortening the new drug development cycle, in which DTA (Drug-Target binding Affinity) prediction is a key step to screen out potential drugs. With the development of deep learning, various types of deep learning models have achieved notable performance in a wide range of fields. Most current related studies focus on extracting the sequence features of molecules while ignoring the valuable structural information; they employ sequence data that represent only the elemental composition of molecules without considering the molecular structure maps that contain structural information. In this paper, we use graph neural networks to predict DTA based on corresponding graph data of drugs and proteins, and we achieve competitive performance on two benchmark datasets, Davis and KIBA. In particular, an MSE of 0.227 and CI of 0.895 were obtained on Davis, and an MSE of 0.127 and CI of 0.903 were obtained on KIBA.

International trade relations between countries have enabled the integration of global oil trade while also creating a platform for the risk diffusion of oil supply cuts. The global energy supply shortages sparked by the Covid-19 pandemic has made the problem even more pronounced. This study develops a network-based dynamics model based on the modified bootstrap percolation theory to simulate the cascading diffusion of oil supply shortages. We assess the destructive effects of exporting countries’ cuts in oil exports on global oil trade relations and the vulnerability of importing countries when they encounter oil supply shortages. The cascading diffusion of oil supply breakdown occurs less frequently from 2015 to 2019, proving that the entire network’s antirisk capacity strengthens over time. The coronavirus pandemic has impaired the robustness of the oil trade network in 2020. OPEC’s export influence has continued to decline in recent years. The diversified evolution of the oil supply is conducive to the stability of the oil trade economy. This paper analyzes the risk propagation mechanism in the global oil trade and conducts a case study. The results have a specific early warning effect on regional oil supply risks.

Abstract Tobacco bacterial wilt has seriously affected tobacco production. Ethyl methanesulfonate (EMS) induced tobacco bacterial wilt resistant mutants are important for the control of tobacco bacterial wilt. High-throughput sequencing technology was used to study the rhizosphere bacterial community assemblages of bacterial wilt resistant mutant tobacco rhizosphere soil (namely KS), bacterial wilt susceptible tobacco rhizosphere soil (namely GS) and bulk soil (namely BS) in Xuancheng, Huanxi, Yibin and Luzhou. Alpha analysis showed that the bacterial community diversity and richness of KS and GS in the four regions were not significantly different. However, analysis of intergroup variation in the top 15 bacterial communities in terms of abundance showed that the bacterial communities of KS and GS were significantly different from BS, respectively. In addition, pH, alkali-hydrolysable nitrogen (AN) and soil organic carbon (SOC) were positively correlated with the bacterial community of KS and negatively correlated with GS in the other three regions except Huanxi. Network analysis showed that the three soils in the four regions did not show a consistent pattern of network complexity. PICRUSt functional prediction analysis showed that the COG functions were similar in all samples. All colonies were involved in RNA processing and modification, chromatin structure and dynamics, etc. In conclusion, our experiments showed that rhizosphere bacterial communities of tobacco in different regions have different compositional patterns, which are strongly related to soil factors.

In this study, one-dimensional grating coupler on single-crystal lithium niobate thin film (lithium niobate on insulator, LNOI) that also served as a polarization splitter was designed. The coupler could separate both orthogonal polarization states into two opposite directions while coupled light from a standard single-mode fiber to a waveguide on LNOI at the same time. Using segmented and apodized designing, the peak coupling efficiencies (CEs) around telecommunication wavelength 1550 nm for fundamental TE and TM modes of −2.82 dB and −2.83 dB, respectively, were achieved. The CEs could be optimized to −1.97 dB and −1.8 dB when a metal layer was added below the silicon dioxide layer.

This study addresses the growing concern over the impact of small unmanned aerial vehicles (UAVs), particularly rotor UAVs, on air traffic order and public safety. We propose a novel method for micro-Doppler feature extraction in multi-rotor UAVs within the time-frequency transform domain. Utilizing competitive learning particle swarm optimization (CLPSO), our approach divides population dynamics into three subgroups, each employing unique optimization mechanisms to enhance local search capabilities. This method overcomes limitations in traditional Particle Swarm Optimization (PSO) algorithms, specifically in achieving global optimal solutions. Our simulation and experimental results demonstrate the method’s efficiency and accuracy in extracting micro-Doppler features of rotary-wing UAVs. This advancement not only facilitates UAV detection and identification but also significantly contributes to the fields of UAV monitoring and airspace security.

Abstract Severe eosinophilic asthma (SEA) is a therapy-resistant respiratory condition with poor clinical control. Treatment efficacy and patient compliance of current therapies remain unsatisfactory. Here, inspired by the remarkable success of chimeric antigen receptor-based cellular adoptive immunotherapies demonstrated for the treatment of a variety of malignant tumors, we engineered a cytokine-anchored chimeric antigen receptor T (CCAR-T) cell system using a chimeric IL-5-CD28-CD3ζ receptor to trigger T-cell-mediated killing of eosinophils that are elevated during severe asthma attacks. IL-5-anchored CCAR-T cells exhibited selective and effective killing capacity in vitro and restricted eosinophil differentiation with apparent protection against allergic airway inflammation in two mouse models of asthma. Notably, a single dose of IL-5-anchored CCAR-T cells resulted in persistent protection against asthma-related conditions over three months, significantly exceeding the typical therapeutic window of current mAb-based treatments in the clinics. This study presents a cell-based treatment strategy for SEA and could set the stage for a new era of precision therapies against a variety of intractable allergic diseases in the future.

PurposeLaparoscopic proximal gastrectomy with double-tract reconstruction (LPG-DTR) and laparoscopic proximal gastrectomy with tube-like stomach reconstruction (LPG-TLR) are both function-preserving procedures performed for treating AEG. However, there is no clinical consensus on the selection of digestive tract reconstruction after proximal gastrectomy, and the best way to reconstruct the digestive tract remains controversial. This study aimed at comparing the clinical outcomes of LPG-DTR and LPG-TLR to provide some reference to the choice of AEG surgical modalities.MethodsThis was a multicenter, retrospective cohort study. we collected clinicopathological and follow-up data of patients with consecutive cases diagnosed with AEG from January 2016 to June 2021 in five medical centers. According to the way of digestive tract reconstruction after tumor resection, patients who underwent LPG-DTR or LPG-TLR were included in the present study. Propensity score matching (PSM) was performed to balance baseline variables that might affect the study outcomes. The QOL of the patients was evaluated using the Visick grade.ResultsA total of 124 eligible consecutive cases were finally included. Patients in both groups were matched using the PSM method, and 55 patients from each group were included in the analysis after PSM. There was no statistically significant difference between the two groups in terms of the operation time, amount of intraoperative blood loss, days of postoperative abdominal drainage tube placement, postoperative hospitalization days, total hospitalization cost, the total number of lymph nodes cleared, and the number of positive lymph nodes (P>0.05). There was a statistically significant difference between the two groups in terms of time to first flatus after surgery and postoperative soft food recovery time (P0.05).ConclusionThe anti-reflux effect and quality of life of LPG-DTR for AEG were comparable to those of LPG-TLR. Compared with LPG-TLR, LPG-DTR provide better nutrition status for patients with AEG. LPG-DTR is a superior reconstruction method after proximal gastrectomy.

Summary: The nuclear factor κB (NF-κB) pathway plays essential roles in innate and adaptive immunity, but little is known how NF-κB signaling is compartmentalized and spatiotemporally activated in the cytoplasm. Here, we show that the lipogenesis signal cascade Scap-SREBP1-S1P/S2P orchestrates the homeostasis and spatiotemporal activation of NF-κB. SREBP cleavage-activating protein (Scap) and sterol regulatory element-binding protein 1 (SREBP1) form a super complex with inhibitors of NF-κB α (IκBα) to associate NF-κB close to the endoplasmic reticulum (ER). Upon lipopolysaccharide (LPS) stimulation, Scap transports the complex to the Golgi apparatus, where SREBP1 is cleaved by site-1 protease (S1P)/S2P, liberating IκBα for IκB kinase (Ikk)-mediated phosphorylation and subsequent activation of NF-κB. Loss of Scap or inhibition of S1P or S2P diminishes, while SREBP1 deficiency augments, LPS-induced NF-κB activation and subsequent inflammatory responses. Our results reveal the Scap-SREBP1 complex as an additional cytoplasmic checkpoint for NF-κB homeostasis and unveil the Golgi apparatus as the optimal cellular platform for NF-κB activation, providing insights into the crosstalk between lipogenesis signaling and immunity.

The Cosmonaut Sea is an under-studied area and a “white spot” for macrobenthos research. Here, we report on the species diversity and community structure of macrobenthos collected using tringle trawls on the 38th Chinese National Antarctic Research Expedition (CHINARE) in the Cosmonaut Sea, East Antarctica. A total of 11 tringle trawls were deployed at different depths across the shelf, slope and seamount of the Cosmonaut Sea. A total of 275 macrobenthic species were found from 207 to 1994 m. The species richness per station varied from 23 to 89. Echinoderms (100 species), arthropods (48 species) and mollusks (36 species) were the most dominant groups. Echinoderms and arthropods dominated in abundance at seamount stations, and echinoderms, arthropods and polychaetes dominated in abundance at slope stations, while bryozoans, corals, ascidians and sponges were abundant on the Cosmonaut Sea shelf. Depth was the major driving force influencing the distribution of macrobenthos. The main components were two core communities. One was dominated by sessile suspension feeders and associated fauna. Variants of this community include sponges and bryozoans. The other core community was dominated by mobile deposit feeders, infauna and grazers–epifauna, which included arthropods and echinoderms. The results showed that the slope (40–50° E, 65–67° S) of the Cosmonaut Sea may be an important area with complex ecological processes. The results of this study contribute to the knowledge of species diversity and communities of macrobenthos in the Cosmonaut Sea and provide monitoring data for future ecosystem health assessments and better protection.

An extremely low hydraulic conductivity of cohesive soil causes a low transport rate of water and solute, with a time-consuming result, as we all know. Stable isotopes (δD and δ18O) and in situ monitoring systems of the data about soil water, rainfall, and groundwater were used to analyze the soil moisture migration pattern, using a conceptual model in the field test site, simulated by Hydrus 1D. The results show that multiple rainfalls’ accumulations can cause the water to recharge from soil moisture to micro-confined groundwater, gradually. The soil moisture dynamic change is composed of a dehydration period and absorption period; the cohesive soil water content below 5.0 m was affected by the micro-confined groundwater level and dehydrated in advance due to the level decline. The thick cohesive soil profile can be divided into a shallow mixing zone (0–2 m), steady zone (2–5 m), and deep mixing zone (5–15 m). The effective precipitation recharge was 234 mm and the average infiltration recharge coefficient (Rc) was 0.1389, but the water exchange between the cohesive soil moisture and groundwater was 349 mm in two hydrological years. This paper reveals the moisture migration and recharge pattern of low-permeability thick cohesive soil in a humid area with a micro-confined groundwater aquifer; this is of great significance for groundwater resources evaluation and environmental protection in humid climate plain areas.

In recent years, the realm of deep learning has witnessed significant advancements, particularly in object detection algorithms. However, the unique challenges posed by remote sensing images, such as complex backgrounds, diverse target sizes, dense target distribution, and overlapping or obscuring targets, demand specialized solutions. Addressing these challenges, we introduce a novel lightweight object detection algorithm based on Yolov5s to enhance detection performance while ensuring rapid processing and broad applicability. Our primary contributions include: firstly, we implemented a new Lightweight Asymmetric Detection Head (LADH-Head), replacing the original detection head in the Yolov5s model. Secondly, we introduce a new C3CA module, incorporating the Coordinate Attention mechanism, strengthening the network’s capability to extract precise location information. Thirdly, we proposed a new backbone network, replacing the C3 module in the Yolov5s backbone with a FasterConv module, enhancing the network’s feature extraction capabilities. Additionally, we introduced a Content-aware Feature Reassembly (content-aware reassembly of features) (CARAFE) module to reassemble semantic similar feature points effectively, enhancing the network’s detection capabilities and reducing the model parameters. Finally, we introduced a novel XIoU loss function, aiming to improve the model’s convergence speed and robustness during training. Experimental results on widely used remote sensing image datasets such as DIOR, DOTA, and SIMD demonstrate the effectiveness of our proposed model. Compared to the original Yolov5s algorithm, we achieved a mean average precision (mAP) increase of 3.3%, 6.7%, and 3.2%, respectively. These findings underscore the superior performance of our proposed model in remote sensing image object detection, offering an efficient, lightweight solution for remote sensing applications.

Shuanglong Cave is a famous national scenic spot.The proposed Jinhua Mountain Tunnel is located about 12 km northeast of the Shuanglong Cave Scenic Area in Jinhua City, Zhejiang Province.The excavation of the Jinhua Mountain Tunnel may cause the karst water in Shuanglong Cave Scenic Area to be drained.At the same time, the tunnel may also be possiblely suffer the danger of karst water inrush.Based on the theory of groundwater flow system, combined with the survey results of hydrogeological conditions in the study area, the division of karst groundwater flow systems, the analysis of the geological structure of the key karst distribution areas at the exit of the tunnel, and the results of hydrogeochemical tests, the hydraulic connection between the two karst groundwater flow systems where the Shuanglong Cave and the tunnel site are located and the possibility of water inrush were analyzed.The results show that: if the tunnel exit section is exposed to the karst aquifer and drained, it will only affect the limited karst groundwater and fissure water around it, and will not directly connect to the large-scale karst groundwater flow system on the west side of the study area; during the tunnel construction and operation period, the karst groundwater in the Shuanglong Cave Scenic Area will basically not be affected, and the karst groundwater in the Shuanglong Cave will not pose a direct threat of water inrush at the exit section of the tunnel.In the study of water inrush source in karst areas, the rational division of karst groundwater flow systems based on the theory of groundwater flow system and analysis of the hydraulic connections between the systems are necessary prerequisites for analyzing the source of water inrush and preventing water inrush disasters.

Identification of causative genes or genetic variants associated with phenotype traits benefits the genetic improvement of animals. CISH plays a role in immunity and growth, however, the upstream transcriptional factors of porcine CISH and the genetic variations in these factors remain unclear. In this study, we firstly identified the minimal core promoter of porcine CISH and confirmed the existence of STATx binding sites. Overexpression and RT-qPCR demonstrated STAT5A increased CISH transcriptional activity (P < 0.01) and mRNA expression (P < 0.01), while GATA1 inhibited CISH transcriptional activity (P < 0.01) and the following mRNA expression (P < 0.05 or P < 0.01). Then, the putative functional genetic variations of porcine STAT5A were screened and a PCR-SSCP was established for genotype g.508A>C and g.566C>T. Population genetic analysis showed the A allele frequency of g.508A>C and C allele frequency of g.566C>T was 0.61 and 0.94 in Min pigs, respectively, while these two alleles were fixed in the Landrace population. Statistical analysis showed that Min piglets with CC genotype at g.566C>T or Hap1: AC had higher 28-day body weight, 35-day body weight, and ADG than TC or Hap3: CT animals (P < 0.05, P < 0.05). Further luciferase activity assay demonstrated that the activity of g.508A>C in the C allele was lower than the A allele (P < 0.05). Collectively, the present study demonstrated that STAT5A positively regulated porcine CISH transcription, and SNP g.566C>T in the STAT5A was associated with the Min piglet growth trait.

Abstract Background Growing evidence has shown that the prognosis for colon cancer depends on changes in microenvironment. The purpose of this study was to elucidate the prognostic value of long noncoding RNAs (lncRNAs) related to immune microenvironment (IM) in colon cancer. Methods Single sample gene set enrichment analysis (ssGSEA) was used to identify the subtypes of colon cancer based on the immune genomes of 29 immune signatures. Cox regression analysis identified a lncRNA signatures associated with immune infiltration. The Tumor Immune Estimation Resource database was used to analyze immune cell content. Results Colon cancer samples were divided into three subtypes by unsupervised cluster analysis. Cox regression analysis identified an immune infiltration-related 5-lncRNA signature. This signature combined with clinical factors can effectively improve the predictive ability for the overall survival (OS) of colon cancer. At the same time, we found that the expression of H19 affects the content of B cells and macrophages in the microenvironment of colon cancer and affects the prognosis of colon cancer. Finally, we constructed the H19 regulatory network and further analyzed the possible mechanisms. We found that knocking down the expression of H19 can significantly inhibit the expression of CCND1 and VEGFA. At the same time, the immunohistochemical assay found that the expression of CCND1 and VEGFA protein was significantly positively correlated with the infiltration of M2 type macrophages. Conclusion The findings may help to formulate clinical strategies and understand the underlying mechanisms of H19 regulation. H19 may be a biomarker for targeted treatment of colon cancer.

The present study aimed to search for functional mutations within the promoter of porcine STAT3 and to provide causative genetic variants associated with piglet diarrhea. We firstly confirmed that STAT3 expressed higher in the small intestine than in the spleen, stomach and large intestine of SPF piglets, respectively (P < 0.05). Then, 10 genetic variations in the porcine STAT3 promoter region was identified by direct sequencing. Among them, three mutations SNP1: g.−870 G>A, SNP2: g.−584 A>C and a 6-bp Indel in the promoter region that displayed significant differential transcriptional activities were identified. Association analyses showed that SNP1: g.−870 G>A was significantly associated with piglet diarrhea (P < 0.05) and the GG animals had lower diarrhea score than AA piglets (P < 0.01) in both Min and Landrace population. Further functional analysis revealed that E2F6 repressed the transcriptional efficiency of STAT3 in vitro, by binding the G allele of SNP1. The present study suggested that SNP1: g.−870 G>A was a piglet diarrhea-associated variant that directly affected binding with E2F6, leading to changes in STAT3 transcription which might partially contribute to piglet diarrhea susceptibility or resistance.

Introduction: The timely alleviation of symptoms is essential for managing community-acquired pneumonia (CAP). Juhongtanke oral solution is a traditional marketed Chinese patent medicine believed to ease CAP symptoms. The currently available evidence is based on a few retrospective studies of patients with various types of pneumonia, whereas robust randomized controlled trials (RCTs) that support this notion are lacking.Material and methods: In this multi-center, prospective RCT, patients were randomly allocated to receive routine treatment alone or a combination of Juhongtanke oral solution (20 mL q8h) for 5 days and maintained for an additional 3-day safety observation period. The primary outcome was Breathlessness, Cough, and Sputum Scale (BCSS) score evaluated on day 5. Secondary outcomes included the evaluation of cough and dyspnea items in the Visual Analogue Scale (VAS) from days 1–5, remission rate in BCSS and VAS during the treatment course, and the length of hospitalization and in-hospital mortality.Results: Of 272 patients assessed for eligibility, 240 were enrolled in the study (n =120 per group). The mean difference in BCSS evaluated on day 5 was a median 1 point [95%CI (1.00, 2.00)], significantly lower in the treatment group compared with the control group (p < 0.001). Similar results were observed in VAS on day 5, with statistics of a median 2 points [95%CI (1.40, 2.50)] in the cough item and a median 1 point [95%CI (0.50, 2.00)] in the dyspnea item, significantly lower in the treatment group compared with the control group (both p < 0.001). The treatment group had a favorable outcome in BCSS and VAS remission rate assessments compared with the control group, with 99.50% vs. 89.17% in BCSS (p = 0.01), 98.33% vs. 75% in the cough item of VAS (p < 0.001), and 88.33% vs. 62.50% in the dyspnea item of VAS (p < 0.001), respectively. No notable adverse effects were observed during the study. No differences were observed in the length of hospitalization between groups (with a median of 7 days for both groups, p = 0.871).Conclusion: Juhongtanke oral solution may be considered to alleviate the clinical symptoms of CAP.

ObjectiveTo search for significant biomarkers associated with sudden death (SD).MethodsDifferential genes were screened by comparing the whole blood samples from 15 cases of accidental death (AD) and 88 cases of SD. The protein-protein interaction (PPI) network selects core genes that interact most frequently. Machine learning is applied to find characteristic genes related to SD. The CIBERSORT method was used to explore the immune-microenvironment changes.ResultsA total of 10 core genes (MYL1, TNNC2, TNNT3, TCAP, TNNC1, TPM2, MYL2, TNNI1, ACTA1, CKM) were obtained and they were mainly related to myocarditis, hypertrophic myocarditis and dilated cardiomyopathy (DCM). Characteristic genes of MYL2 and TNNT3 associated with SD were established by machine learning. There was no significant change in the immune-microenvironment before and after SD.ConclusionDetecting characteristic genes is helpful to identify patients at high risk of SD and speculate the cause of death.

Spherical robots have fully wrapped shells, which enables them to walk well on complex terrains, such as swamps, grasslands and deserts. At present, path planning algorithms for spherical robots mainly focus on finding the shortest path between the initial position and the target position. In this paper, an improved A* algorithm considering energy consumption is proposed for the path planning of spherical robots. The optimization objective of this algorithm is to minimize both the energy consumption and path length of a spherical robot. A heuristic function constructed with the energy consumption estimation model (ECEM) and the distance estimation model (DEM) is used to determine the path cost of the A* algorithm. ECEM and DCM are established based on the force analysis of the spherical robot and the improved Euclidean distance of the grid map, respectively. The effectiveness of the proposed algorithm is verified by simulation analysis based on a 3D grid map and a spherical robot moving with uniform velocity. The results show that compared with traditional path planning algorithms, the proposed algorithm can minimize the energy consumption and path length of the spherical robot as much as possible.