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Abstract The integration of gray and green infrastructure has proven to be a feasible approach for managing stormwater in established urban areas. However, evaluating the specific contributions of such coupled strategies is challenging. This study introduced a novel integrated hydrological-hydrodynamic model that takes into account the layout of low-impact development (LID) facilities along with pipeline alignment and rehabilitation. Reliable results from modeling were used to assess the individual contribution of LID and improved drainage facilities to urban flooding mitigation. We selected a natural island in Guangzhou City, China, as the study site. The results indicate that combining three LID measures, namely green roofs, sunken green spaces, and permeable pavements, can reduce total runoff by 41.7% to 25.89% for rainfall recurrence periods ranging from 1 year to 100 years, and decrease the volume of nodal overflow by nearly half during rainfall events of less than 10-year return period. By integrating LID measures with the upgraded gray infrastructure, the regional pipeline overloading condition is substantially alleviated, resulting in a significant improvement in pipeline system resilience. For urban flooding control, it is recommended to integrate sufficient green space and avoid pipe-laying structural issues during urban planning and construction. The findings may assist stakeholders in developing strategies to best utilize gray and green infrastructure in mitigating the negative effects of urban flooding.

Cancer cell invasion relies on an equilibrium between cell deformability and the biophysical constraints imposed by the extracellular matrix (ECM). However, there is little consensus on the nature of the local biomechanical alterations in cancer cell dissemination in the context of three-dimensional (3D) tumor microenvironments (TMEs). While the shortcomings of two-dimensional (2D) models in replicating in situ cell behavior are well known, 3D TME models remain underutilized because contemporary mechanical quantification tools are limited to surface measurements. Here, we overcome this major challenge by quantifying local mechanics of cancer cell spheroids in 3D TMEs. We achieve this using multimodal mechano-microscopy, integrating optical coherence microscopy-based elasticity imaging with confocal fluorescence microscopy. We observe that non-metastatic cancer spheroids show no invasion while showing increased peripheral cell elasticity in both stiff and soft environments. Metastatic cancer spheroids, however, show ECM-mediated softening in a stiff microenvironment and, in a soft environment, initiate cell invasion with peripheral softening associated with early metastatic dissemination. This exemplar of live-cell 3D mechanotyping supports that invasion increases cell deformability in a 3D context, illustrating the power of multimodal mechano-microscopy for quantitative mechanobiology in situ.

BackgroundSepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death.MethodsGenetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank.ResultsAfter FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant.ConclusionsThe identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field.

Abstract Tendinopathy is one of the most common musculoskeletal diseases, and mechanical overload is considered its primary cause. However, the underlying mechanism through which mechanical overload induces tendinopathy has not been determined. In this study, we identified for the first time that tendon cells can release extracellular mitochondria (ExtraMito) particles, a subtype of medium extracellular particles (mEPs), into the environment through a process regulated by mechanical loading. RNA sequencing systematically revealed that oxygen-related reactions, extracellular particles, and inflammation were present in diseased human tendons, suggesting that these factors play a role in the pathogenesis of tendinopathy. We simulated the disease condition by imposing a 9% strain overload on three-dimensional mouse tendon constructs in our cyclic uniaxial stretching bioreactor. The three-dimensional mouse tendon constructs under normal loading with 6% strain exhibited an extended mitochondrial network, as observed through live-cell confocal laser scanning microscopy. In contrast, mechanical overload led to a fragmented mitochondrial network. Our microscopic and immunoblot results demonstrated that mechanical loading induced tendon cells to release ExtraMito particles. Furthermore, we showed that mEPs released from tendon cells overloaded with a 9% strain (mEP9%) induced macrophage chemotaxis and increased the production of proinflammatory cytokines, including IL-6, CXCL1, and IL-18, from macrophages compared to mEP0%, mEP3%, and mEP6%. Partial depletion of the ExtraMito particles from mEP9% by magnetic-activated cell sorting significantly reduced macrophage chemotaxis. N-acetyl-L-cysteine treatment preserved the mitochondrial network in overloaded tendon cells, diminishing overload-induced macrophage chemotaxis toward mEP9%. These findings revealed a novel mechanism of tendinopathy; in an overloaded environment, ExtraMito particles convey mechanical response signals from tendon cells to the immune microenvironment, culminating in tendinopathy.

Abstract Background To investigate the prevalence of common sexually transmitted infections (STIs) and the association of STI/human papillomavirus co-infection in young and middle-aged women with previous abnormal cervical findings referred for colposcopy. Methods 719 cervical-swab cytobrush specimens were obtained from women aged ≤ 50 years who were referred for colposcopy at Peking University First Hospital due to previous abnormal cervical findings. HPV 21 typing and a panel of pathogenic STIs were tested for using the 21 HPV GenoArray Diagnostic Kit (HBGA-21PKG; HybriBio, Ltd., Chaozhou, China) and a nucleic acid STI detection kit (HybriBio Ltd. Guangzhou, China), after which colposcopy with multipoint positioning biopsy was performed. Results The overall prevalence of STIs among HPV positive women with previous abnormal cervical cancer screening results was 63.7% (458/719), with Ureaplasma parvum serovar 3, Ureaplasma parvum serovar 6 and herpes simplex virus type 2 having significantly higher prevalence among high-risk HPV positive patients (19.3%, Χ2 = 5.725, P = 0.018; 21.5%, Χ2 = 4.439, P = 0.035; 5.7%, Χ2 = 4.184, P = 0.048). Among patients positive for the high-risk human papillomavirus, the prevalence of Neisseria gonorrhoeae infection in human papillomavirus 16/18 positive patients was significantly higher than that in other patients (2.5%, Χ2 = 4.675; P = 0.043). Histopathologically, Chlamydia trachomatis infection was more frequently detected in lower than or equal to low-grade squamous intraepithelial lesion infection status (13.0%, Χ2 = 3.368; P = 0.041). Conclusions The high prevalence of HPV coinfection with other sexually transmitted pathogens, particularly Ureaplasma parvum serovar 3, Ureaplasma parvum serovar 6, and herpes simplex virus type 2, calls for routine STI screening and effective STI prevention and management in patients with abnormal cervical cancer screening results.

Abstract Verticillium dahliae is a soil-borne hemibiotrophic fungal pathogen that threatens cotton production worldwide. In this study, we assemble the genomes of two V. dahliae isolates: the more virulence and defoliating isolate V991 and nondefoliating isolate 1cd3-2. Transcriptome and comparative genomics analyses show that genes associated with pathogen virulence are mostly induced at the late stage of infection (Stage II), accompanied by a burst of reactive oxygen species (ROS), with upregulation of more genes involved in defense response in cotton. We identify the V991-specific virulence gene SP3 that is highly expressed during the infection Stage II. V. dahliae SP3 knock-out strain shows attenuated virulence and triggers less ROS production in cotton plants. To control the disease, we employ polyethyleneimine-coated MXene quantum dots (PEI-MQDs) that possess the ability to remove ROS. Cotton seedlings treated with PEI-MQDs are capable of maintaining ROS homeostasis with enhanced peroxidase, catalase, and glutathione peroxidase activities and exhibit improved tolerance to V. dahliae. These results suggest that V. dahliae trigger ROS production to promote infection and scavenging ROS is an effective way to manage this disease. This study reveals a virulence mechanism of V. dahliae and provides a means for V. dahliae resistance that benefits cotton production.

Bacterial vaginosis (BV) is an infection of the genital tract characterized by disturbance of the normally Lactobacilli-dominated vaginal flora due to the overgrowth of Gardnerella and other anaerobic bacteria. Gardnerella vaginalis, an anaerobic pathogen and the major pathogen of BV, produces sialidases that cleave terminal sialic acid residues off of human glycans. By desialylation, sialidases not only alter the function of sialic acid-containing glycoconjugates but also play a vital role in the attachment, colonization and spread of many other vaginal pathogens. With known pathogenic effects, excellent performance of sialidase-based diagnostic tests, and promising therapeutic potentials of sialidase inhibitors, sialidases could be used as a biomarker of BV. This review explores the sources of sialidases and their role in vaginal dysbiosis, in aims to better understand their participation in the pathogenesis of BV and their value in the diagnosis and treatment of BV.

Due to the complexity of the spatial environment and poor lighting conditions in underground coal mines, the images obtained by vision devices are prone to problems such as insufficient contrast and poor texture details, which seriously affect the reliability of the work of vision devices and limit further image-based intelligent applications. To improve the contrast of low-illumination images in underground mines while enhancing their texture details, a deep neural network-based low-illumination image enhancement model is proposed, which contains three sub-networks, namely, decomposition network, illumination adjustment network and reflection reconstruction network. The decomposition network decomposes the underground coal mine image into light and reflection components; the light adjustment network effectively reduces the parameters of the model using depth-separable convolutional structure and strengthens the feature extraction ability of the network; in addition, the MobileNet network structure is introduced to further lighten the light adjustment network while maintaining its feature extraction accuracy and effectively realizing the contrast adjustment of light components; the reflection reconstruction network introduces a residual network structure to improve the contrast adjustment of light components. Finally, the processed illumination and reflection components are fused based on Retinex theory to obtain enhanced images, which achieve contrast enhancement and detail enhancement of underground mine images, overcoming the problems of detail loss, blurred edges, and lack of contrast and clarity of the enhanced image that exist in existing enhancement algorithms. Numerical experiments show that the proposed model can effectively enhance the texture details of the image while improving the contrast of underground mine images, and has good stability and robustness, which can well meet the needs of low-light image enhancement in coal mines.

This study focuses on investigating the newly proposed sliding–rolling friction composite seismic isolation bearing. It begins by establishing the dynamic equilibrium equation for the structure. Subsequently, this paper proposes a calculation model for the sliding–rolling friction composite seismic isolation bearing, integrating fundamental theories of structural dynamic response analysis and numerical solution methods. Utilizing finite element analysis software ABAQUS (2021), the mechanical properties of the seismic isolation bearing are comprehensively assessed. Through this evaluation, the optimal parameters of the seismic isolation bearing are determined. The findings reveal that the optimal parameters include a friction coefficient (μ) of 0.04, four U-type dampers at 45° angles, a width of 60 mm, five balls, and two shims.

The arrangement of eccentric bracing has a significant impact on the seismic performance of structures. However, there is no further stipulation on different forms of eccentric bracing in the current Chinese code. At the same time, there is a lack of research on the seismic loss of eccentrically braced structures by Chinese domestic scholars. Therefore, this paper designs different forms of eccentrically braced frames and analyzes them according to the concept of seismic engineering based on performance, which provides some reference for the selection of the eccentrically braced steel frame structure layout in future engineering practice. In this paper, K-shaped, V-shaped, and D-shaped eccentrically braced steel frame structures with 3, 5, and 8 floors are designed, and the finite element analysis model is used for static napping and dynamic time history analysis. The results show that the K-shaped eccentrically braced structure has the best performance in bearing capacity and stiffness and has good seismic and collapse resistance performance. In the FEMA P-58 seismic assessment and vulnerability assessment, it is found that the V-shaped eccentrically braced structure has the smallest loss. However, it is necessary to fully consider the acceleration sensitivity of the non-structural components in the design. In general, the seismic performance of the eccentrically braced structure is improved by the energy dissipation beam yielding to consume energy, which provides a useful reference for structural design.

In the past, scholars have studied the creep of UHPC, mainly in compression and tension but not bending creep. In this research, 20 ultra-high performance concrete (UHPC) beams were tested for bending creep under long-term loading, and the changes of beam deflection, temperature, and humidity with time were obtained for 445 days of continuous loading. The deflection patterns of UHPC beams with time were analyzed for different steel fiber content, curing systems, water/binder ratio, sand/binder ratio, and stress levels. The results showed that steel fiber had an obvious inhibition effect on initial deflection, but a dosage of steel fiber too high would offset part of the inhibition effect of steel fiber on creep. The use of heat treatment had a better inhibition of creep in the later stage of UHPC, but heat treatment must be matched with necessary moisture content, and hot water maintenance was the most efficient. Both a high water/binder ratio and high stress level increased the bending creep of the specimen. Bending creep increased with the increase in the sand/binder ratio. Therefore, attention should be paid to the total amount and ratio of cementitious materials and fine aggregates in UHPC.

BackgroundThis study sought to illustrate whether urinary strontium levels were related to developing chronic kidney disease (CKD) in the United States population.MethodsA total of 5,005 subjects were identified from the National Health and Nutrition Examination Survey 2011–2016. Survey-weighted logistic regression analysis, multivariate linear regression analysis, restricted cubic spline (RCS) plots curve and stratified analyses were undertaken to explicate the correlation between urinary strontium and CKD.ResultsWith the increase of urinary strontium, the incidence rate of CKD and urinary albumin to creatinine ratio (UACR) levels gradually decreased, and estimated glomerular filtration rate (eGFR) levels gradually increased. After controlling all confounders, only urinary strontium in the fourth quartile was correlated to a lower CKD prevalence (OR: 0.59; 95% CI, 0.44–0.79) compared to the lowest quartile. Multivariate linear regression analysis showed that urinary strontium was positively correlated with eGFR but negatively with UACR. RCS curve suggested a nonlinear relationship between urinary strontium and CKD (P for non-linearity

Long non-coding RNAs (lncRNAs) are commonly known for their important characters in cancer progression. LncRNA MAFG-antisense 1 (AS1) (MAFG-AS1) has been discovered as a novel oncogenic lncRNA for several years. Accumulating data have demonstrated abnormal overexpression of MAFG-AS1 in various human cancers, including breast, bladder, liver, gastric, and lung. Importantly, through regulating various microRNAs and cell signaling pathways, MAFG-AS1 has been demonstrated to exhibit various biological effects, including proliferation, metastasis, and epithelial-mesenchymal transition (EMT). Meanwhile, abnormal overexpression of MAFG-AS1 is closely linked with histological grade, TNM stage, extensive depth of invasion, poor OS, and lymph node metastasis (LNM). In the present review, the authors summarized the previous studies on the biological properties, molecular mechanisms, and clinicopathological characters of MAFG-AS1 in human cancers. In summary, MAFG-AS1 is a promising prognostic biological marker and potential therapeutic target for cancer treatment.

IntroductionThe geriatric nutritional risk index (GNRI), a nutritional screening tool specifically for the aging population, has been proven to be associated with worse outcomes in chronic kidney disease patients, especially in the hemodialysis population. However, the predictive validity of GNRI in critically ill elderly patients with acute kidney injury (AKI) is yet to be determined. This analysis sought to examine the prognostic effects of GNRI on elderly AKI patients in intensive care units (ICUs).MethodsWe collected elderly AKI patient-relevant data from the Medical Information Mart for Intensive Care III database. AKI was diagnosed and staged according to the “Kidney Disease Improving Global Outcomes” criteria. In the study, 1-year mortality was considered the primary outcome, whereas in-hospital, ICU, 28-day and 90-day mortality, and prolonged length of stay in ICU and hospital were selected as the secondary outcomes.ResultsIn all, 3,501 elderly patients with AKI were selected for this study, with a 1-year mortality rate of 36.4%. We classified the study population into low (≤98) and high (>98) GNRI groups based on the best cutoff value. The incidence of endpoints was remarkably lower in patients with elevated GNRI (p < 0.001). When stratified by the AKI stage, patients with high GNRI at AKI stages 1, 2, and 3 had markedly lower 1-year mortality than those with low GNRI (all p < 0.05). The multivariable regression analysis identified the independent prognostic ability of GNRI on the research outcomes (all p < 0.05). Restricted cubic spline exhibited a linear correlation between GNRI and 1-year death (p for non-linearity = 0.434). The prognostic implication of GNRI on 1-year mortality was still significant in patients with the most subgroups.ConclusionIn critically ill elderly patients with AKI, elevated GNRI upon admission was strongly correlated with a lower risk of unfavorable outcomes.

Positively charged nanofiltration (NF) technology is considered a green and low-cost method for mono/divalent cation separation. Nevertheless, the separation rejection mechanisms of these NF membranes have yet to be extensively investigated. In this work, we fabricated a thin-film composite (TFC) hollow-fiber (HF) NF membrane with a positively charged surface via modification of the nascent interfacial polymerization layer using a branched polyethyleneimine (BPEI)/ethanol solution. Then, we extensively investigated its selective separation mechanism for mono/divalent cations. We proposed and proved that there exists a double-charged layer near the membrane surface, which helps to repel the divalent cations selectively via Donnan exclusion while promoting the fast penetration of monovalent cations. Meanwhile, the membrane skin layer is loose and hydrophilic due to the loose BPEI structure and the abundance of amine groups, as well as the changed fabrication conditions. In this way, we achieved very good mono/divalent cation selectivity and relatively high water permeance for the as-prepared HF NF membrane. We also obtained good anti-fouling, anti-scaling, and acid resistance, and long-term stability as well, which are urgently needed during practical application. Furthermore, we successfully amplified this HF NF membrane and proved that it has broad application prospects in mono/divalent cation separation.

Male sterility is a valuable trait for watermelon breeding, as watermelon hybrids exhibit obvious heterosis. However, the underlying regulatory mechanism is still largely unknown, especially regarding the related non-coding genes. In the present study, approximately 1035 differentially expressed genes (DEGs), as well as 80 DE-lncRNAs and 10 DE-miRNAs, were identified, with the overwhelming majority down-regulated in male-sterile floral buds. Enrichment analyses revealed that the general phenylpropanoid pathway as well as its related metabolisms was predicted to be altered in a mutant compared to its fertile progenitor. Meanwhile, the conserved genetic pathway DYT1-TDF1-AMS-MS188-MS1, as well as the causal gene ClAMT1 for the male-sterile mutant Se18, was substantially disrupted during male reproductive development. In addition, some targets of the key regulators AMS and MS188 in tapetum development were also down-regulated at a transcriptional level, such as ABCG26 (Cla004479), ACOS5 (Cla022956), CYP703A2 (Cla021151), PKSA (Cla021099), and TKPR1 (Cla002563). Considering lncRNAs may act as functional endogenous target mimics of miRNAs, competitive endogenous RNA networks were subsequently constructed, with the most complex one containing three DE-miRNAs, two DE-lncRNAs, and 21 DEGs. Collectively, these findings not only contribute to a better understanding of genetic regulatory networks underlying male sterility in watermelon, but also provide valuable candidates for future research.

The phosphoinositide 3-kinase (PI3K) signaling pathway is well-known for its important role in cancer growth, proliferation and migration. The activation of PI3K pathway is always connected with endocrine resistance and poor prognosis in cancers. Alpelisib, a selective inhibitor of PI3K, has been demonstrated to be effective in combination with endocrine therapy in HR+ PIK3CA-mutated advanced breast cancer in preclinical and clinical trials. Recently, the synergistic effects of alpelisib combined with targeted agents have been widely reported in PIK3CA-mutated cancer cells, such as breast, head and neck squamous cell carcinoma (HNSCC), cervical, liver, pancreatic and lung cancer. However, previous reviews mainly focused on the pharmacological activities of alpelisib in breast cancer. The synergistic therapeutic potential of alpelisib in other cancers has not yet been well reviewed. In this review, an extensive study of related literatures (published until December 20, 2022) regarding the anti-cancer functions and synergistic effects of alpelisib was carried out through the databases. Useful information was extracted. We summarized the preclinical and clinical studies of alpelisib in combination with targeted anti-cancer agents in cancer treatment (excluding breast cancer). The combinations of alpelisib and other targeted agents significantly improved the therapeutic efficacy both in preclinical and clinical studies. Unfortunately, synergistic therapies still could not effectively avoid the possible toxicities and adverse events during treatment. Finally, some prospects for the combination studies in cancer treatment were provided in the paper. Taken together, this review provided valuable information for alpelisib in preclinical and clinical applications.

ABSTRACT Cryptosporidium parvum has gained much attention as a major cause of diarrhea in the world, particularly in those with compromised immune systems. The data currently available on how the immune system recognizes C. parvum are growing rapidly, but we lack data on the interactions among host major histocompatibility complex (MHC) diversity and parasitic T-cell epitopes. To identify antigenic epitopes in a murine model, we performed systematic profiling of H-2Kb-restricted peptides by screening the dominant Cryptosporidium antigens. The results revealed that the glycoprotein-derived epitope Gp40/15-SVF9 induced an immunodominant response in C. parvum-recovered C57BL/6 mice, and injection of the cytotoxic-T-lymphocyte (CTL) peptide with the adjuvant activated peptide-specific CD8+ T cells. Notably, the SVF9 epitope was highly conserved across Cryptosporidium hominis, C. parvum, and many other Cryptosporidium species. SVF9 also formed stable peptide-MHC class I (MHC I) complexes with HLA-A*0201, suggesting cross-reactivity between H-2Kb and human MHC I specificities. Crystal structure analyses revealed that the interactions of peptide-MHC surface residues of H-2Kb and HLA-A*0201 are highly conserved. The hydrogen bonds of H-2Kb–SVF9 are similar to those of a dominant epitope presented by HLA-A*0201, which can be recognized by a public human T-cell receptor (TCR). Notably, we found double conformations in position 4 (P4), 5 (P5) of the SVF9 peptide, which showed high flexibility, and multiple peptide conformations generated more molecular surfaces that can potentially be recognized by TCRs. Our findings demonstrate that an immunodominant C. parvum epitope and its homologs from different Cryptosporidium species and subtypes can benefit vaccine development to combat cryptosporidiosis. IMPORTANCE Adaptive immune responses and T lymphocytes have been implicated as important mechanisms of parasite-induced protection. However, the role of CD8+ T lymphocytes in the resolution of C. parvum infection is largely unresolved. Our results revealed that the glycoprotein-derived epitope Gp40/15-SVF9 induced an immunodominant CD8+ T-cell response in C57BL/6 mice. Crystal structure analyses revealed that the interactions of the H-2Kb–SVF9 peptide are similar to those of a dominant epitope presented by HLA-A*0201, which can be recognized by human TCRs. In addition, we found double conformations of the SVF9 peptide, which showed high flexibility and multiple peptide conformations that can potentially be recognized by TCRs.

Abstract Background Type 2 diabetes mellitus (T2DM) is a common metabolic disease with significant health, social, and economic consequences. Traditional Chinese medicine (TCM) could effectively regulate blood sugar and influence gut microbiota in T2DM patients. Preliminary studies showed that the Coptis root and ginseng (RG) formula could relieve insulin resistance and prevent the progression of diabetes in mice. Objectives The purpose of this study is to explore the efficacy and safety of RG formula in the treatment of adult patients with T2DM, as well as observing its effects on gut microbiota. Methods and analysis This trial is a randomized, double-blind, placebo-controlled study. A total of 60 participants will be randomized in a 1:1 ratio into an experiment group (RG formula) and a control group (placebo). Patients in both groups will be given diabetes education and basic blood glucose control. Glucose-lowering drugs with significant influence on gut microbiota will be avoided. This trial will last 25 weeks including 1-week run-in, 12-week intervention, and 12-week follow-up visit. The primary outcome is the change in the HbA1c. The secondary outcomes comprise the change in the fasting blood glucose (FBG), postprandial blood glucose (PBG), fasting insulin (FIL), fasting C-peptide(C-P), insulin resistance index (IRI), inflammatory factors, and species abundance of gut microbiota between the two groups. Safety of medication will also be evaluated. The correlation analysis will be explored between the glycemic indicators, inflammatory factors, and abundance of gut microbiota. Discussion This study will provide the clinical evidence for the efficacy of RG formula in regulating blood sugar and influencing gut microbiota, which will be beneficial to form the integrated therapeutic regimen in T2DM with TCM. Trial registration “Clinical Study on the Intervention of Coptis Root and Ginseng,” Chinese Clinical Trials Registry ChiCTR 2100042126 . Registered on 14 January 2021

Abstract Aim To understand the social network status of older adults with type 2 diabetes mellitus (T2DM) in Beijing, China and explore its related factors. Design A cross‐sectional survey using a sample of convenience was conducted. Methods From April to September 2019, Lubben Social Network Scale‐6 (LSNS‐6) was used to evaluate the social network of 300 older adults with T2DM from the outpatient and inpatient departments of three hospitals and five communities in Beijing. Self‐designed demographics and clinical sheets, Summary of Diabetes Self‐Care Activities Scale, Social Support Rating Scale and Geriatric Depression Scale‐15 were used to investigate the related factors of their social networks. The Equator Research Checklist used in this study is STROBE checklist. Results The score of LSNS‐6 of the older adults was 16.75 ± 7.02 (scale: 0 ~ 30), the score of family network dimension was 8.32 ± 3.63 (scale: 0 ~ 15), and friends network dimension was 8.43 ± 4.74 (scale: 0 ~ 15). Additionally, 22.67% of the older adults had social isolation. Social support, medical payment, self‐assessed health status, residential arrangement and smoking status were associated with the social network level of the older adults with T2DM (p

During the Multi-Object Tracking (MOT) process, the effectiveness of Re-Identification (Re-ID) is typically contingent upon the performance of detection. In particular, detection errors may result in the blurring of Re-ID features, thereby diminishing the efficacy of Re-ID. In particular, Re-ID exhibits poor robustness in intricate scenarios such as distance and scale alterations, occlusion, and crowding. Meanwhile, the frequent occurrence of object occlusion can result in the interruption of object tracking, thereby impacting the tracking efficiency. To address these issues, a novel MOT method approach that leverages Re-ID enhancement and association correction is proposed. Through an unanchored, one-stage backbone network with CenterNet as the detector, the object position is detected by predicting the heatmap of the object center point. A constraint on the Predicted Distance Difference Loss (PDDL) is then designed for the response value of the predicted heatmap, effectively enhancing the detection accuracy and reduce the detection bias. To address the issue of Re-ID reliance on detection accuracy and enhance its robustness, an Effective Feature Graph Convolutional Neural network (EFGCN) is proposed. This approach expands learnable effective features by constructing a graph model that enhances them through a GCN model of heatmap true value locations and surrounding response value locations. Additionally, a target trajectory Association Correction Module (ACM) is introduced in the association phase to handle interruptions and trajectory fragments caused by occlusion. By improving data association for tracking judgment when dealing with occluded targets and considering the relationship between trajectory fragmentation and the detection of low-scoring targets, attempts are made to continue with tracking occluded targets to form complete object associations. The proposed method is evaluated on the MOT16 and MOT17 datasets and compared with other algorithms. The results demonstrate that it is highly effective.

Background: Bone defect therapy is a common clinical challenge for orthopedic and clinical physicians worldwide, and the therapeutic effect affects the physiological function and healthy life quality of millions of patients. Compared with traditional autogenous bone transplants, bone xenografts are attracting attention due to their advantages of unlimited availability and avoidance of secondary damage. However, there is currently a lack of bibliometric analysis on bone xenograft. This study aimed to use bibliometric methods to analyze the literature on bone xenograft from 2013 to 2023, to explore the current status, hotspots, and future trends of research in this field, and to promote its development and progress. Methods: Using the Web of Science Core Collection database, we retrieved and collected publication data related to xenogeneic bone grafting materials worldwide from January 2013 to March 2023. Origin (2021), CiteSpace (6.2.R2 standard), and an online bibliometric platform were used for bibliometric analysis and data visualization. Results: A total of 3395 documents were retrieved, and 686 eligible papers were selected. The country and institutions with the highest number of publications and centrality were the United States (125 papers, centrality = 0.44) and the University of Zurich (29 papers, centrality = 0.28), respectively. The most cited author was Araujo MG (163 times), and the author with the most significant centrality was Froum SJ (centrality = 0.09). The main keyword clusters were “tissue engineering”, “sinus floor elevation”, “dental implants”, “tooth extraction”, and “bone substitutes”. The most significant bursting keywords in the last three years were “platelet rich fibrin”. Conclusions: Research on bone xenograft is steadily growing and will continue to rise. Currently, research hotspots and directions are mainly focused on dental implants related to bone-augmentation techniques and bone tissue engineering. In the future, research hotspots and directions may focus on decellularization technology and investigations involving platelet-rich fibrin.

Perioperative neurocognitive disorders (PNDs) are frequent complications associated with cognitive impairment during the perioperative period, including acute postoperative delirium and long-lasting postoperative cognitive dysfunction. There are some risk factors for PNDs, such as age, surgical trauma, anesthetics, and the health of the patient, but the underlying mechanism has not been fully elucidated. Pyroptosis is a form of programmed cell death that is mediated by the gasdermin protein and is involved in cognitive dysfunction disorders. The canonical pathway induced by nucleotide oligomerization domain (NOD)-, leucine-rich repeat (LRR)- and pyrin domain-containing protein 3 (NLRP3) inflammasomes contributes to PNDs, which suggests that targeting NLRP3 inflammasomes may be an effective strategy for the treatment of PNDs. Therefore, inhibiting upstream activators and blocking the assembly of the NLRP3 inflammasome may attenuate PNDs. The present review summarizes recent studies and systematically describes the pathogenesis of NLRP3 activation and regulation and potential therapeutics targeting NLRP3 inflammasomes in PNDs patients.

Abstract Background Internet medical care has been advancing steadily, especially during the coronavirus disease 2019 pandemic, the development momentum of Internet medical care in China is more vigorous. This study aimed to explore the factors associated with using the Internet for medical information, to examine the popularisation and implementation of Internet medical treatment and feasible strategies, and promote the further development of Internet medical treatment. Methods A cross-sectional study was conducted on 408 medical patients who had used online medical services. The one-way analysis of variance or independent samples t-test was used to compare the differences in the influence of demographic characteristics on behavioural intentions of different people seeking medical care. Pearson’s correlation was used to evaluate the correlation between different measurement variables. A mediation regression analysis was used to explore the mediating role of trust in Internet medical care. Results The difference in the influence of Internet medical use frequency on the behavioural intention of different participants was statistically significant (F = 3.311, P = 0.038). Among the influencing factors, personal trust propensity (r = 0.387, P

Background: The identification of aortic dissection (AD) at baseline plays a crucial role in clinical practice. Non-contrast CT scans are widely available, convenient, and easy to perform. However, the detection of AD on non-contrast CT scans by radiologists currently lacks sensitivity and is suboptimal.Methods: A total of 452 patients who underwent aortic CT angiography (CTA) were enrolled retrospectively from two medical centers in China to form the internal cohort (341 patients, 139 patients with AD, 202 patients with non-AD) and the external testing cohort (111 patients, 46 patients with AD, 65 patients with non-AD). The internal cohort was divided into the training cohort (n = 238), validation cohort (n = 35), and internal testing cohort (n = 68). Morphological characteristics were extracted from the aortic segmentation. A deep-integrated model based on the Gaussian Naive Bayes algorithm was built to differentiate AD from non-AD, using the combination of the three-dimensional (3D) deep-learning model score and morphological characteristics. The areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to evaluate the model performance. The proposed model was also compared with the subjective assessment of radiologists.Results: After the combination of all the morphological characteristics, our proposed deep-integrated model significantly outperformed the 3D deep-learning model (AUC: 0.948 vs. 0.803 in the internal testing cohort and 0.969 vs. 0.814 in the external testing cohort, both p < 0.05). The accuracy, sensitivity, and specificity of our model reached 0.897, 0.862, and 0.923 in the internal testing cohort and 0.730, 0.978, and 0.554 in the external testing cohort, respectively. The accuracy for AD detection showed no significant difference between our model and the radiologists (p > 0.05).Conclusion: The proposed model presented good performance for AD detection on non-contrast CT scans; thus, early diagnosis and prompt treatment would be available.

Thirty dog bone-shaped specimens were tested to study the effects of steel fiber mixed with seven kinds of non-metallic fibers on the tensile properties of ultra-high-performance concrete (UHPC). Through experiments and micromorphological analysis, the effects of hybrid fibers on the compressive strength, tensile strength, peak strain, fracture energy, and characteristic length of UHPC were analyzed. The results showed that the hybrid fiber-reinforced UHPC showed good ductile failure characteristics, which reflected the good crack resistance and toughening effect of different fibers. The tensile stress–strain curves of UHPC with different hybrid fibers can be divided into two parts: ascending section and softening section, and the softening section was greatly affected by the type and content of fibers. Basalt fiber with a diameter of 0.02 mm had the most obvious strengthening effect on UHPC, and polyvinyl alcohol fiber with a diameter of 0.2 mm and length of 8 mm had the best toughening effect. The mixing of steel fiber and non-metallic fiber cannot only reduce the preparation cost but also improve the fracture energy and toughness of UHPC.

Building Information Modeling (BIM) has become the development trend in the architecture, engineering, and construction (AEC) industry. BIM discipline competition is an effective way for students of AEC-related disciplines to integrate theory with practice, and it is a key link to cultivate qualified BIM practitioners. This study takes participants of the 8th National College BIM Graduation Design Innovation Competition as the research objects. The Technology Acceptance Model and the Theory of Planned Behavior are combined to build a driving factor model of the competitions. Contestants of the competition were asked to complete online questionnaires, and 451 valid samples were finally obtained. Structural Equation Modeling was used to fit the theoretical model, and it was found that: Behavioral Intention to use BIM is directly and positively affected by Attitude, Perceived Behavioral Control, and Perceived Usefulness, as well as indirectly and positively affected by Perceived Usefulness and Perceived Eased of Usefulness. Competition Results is directly and positively affected by Behavioral Intention to use BIM, Perceived Behavioral Control, and Facilitating Conditions. It is also indirectly and positively affected by Attitude, Perceived Behavior Control, Perceived Usefulness, and Perceived Eased of Usefulness. The results show that the situation of students’ participation in BIM competition can be optimized by increasing the publicity and promotion of BIM and related policies, strengthening the construction of supporting teaching facilities, building the integrated curriculum system of BIM technology, and strengthening teacher training. This study provides a theoretical reference for further BIM practice, and it would help improve the corresponding teaching organization and enhance the internal drive of students’ BIM learning.

Megatall and supertall buildings often adopt megastructure systems characterized by secondary structure systems, and the serviceability problem caused by wind-induced vibrations often becomes the dominant factor in the structural design. Because the deformation of a supertall building usually presents bending characteristics, a viscous damped outrigger can reduce the wind-induced vibration of a supertall building with the installation of a small number of viscous dampers. However, time history analysis of the prototype model considering the nonlinear characteristics of viscous dampers is time-consuming, which is not conducive for iterative design optimization. Additionally, the conventional simplified model composed of one cantilever beam cannot be used for the analysis and design of a viscous damped outrigger. In this study, a simplified wind-induced vibration prediction model is proposed based on the mechanical characteristics of megastructures. This simplified model is a plane model that includes both core walls and frames whose member size can be extracted from the original structure. Parametric analysis shows that the simplified model has high acceleration prediction accuracy. An optimal design method combined with the simplified model, which aims to minimize the damped outrigger system cost, is proposed. A 600-m supertall building is presented as a case study. The accuracy and effectiveness of the simplified model and the optimal design method proposed in this study are illustrated. Thus, applying this optimal design method in combination with the simplified model can save significant analysis and design time and is conducive to the application of viscous damped outriggers in practical engineering.

Partial occlusion and background clutter in camera video surveillance affect the accuracy of video-based person re-identification (re-ID). To address these problems, we propose a person re-ID method based on random erasure of frame sampling and temporal weight aggregation of mutual information of partial and global features. First, for the case in which the target person is interfered or partially occluded, the frame sampling–random erasure (FSE) method is used for data enhancement to effectively alleviate the occlusion problem, improve the generalization ability of the model, and match persons more accurately. Second, to further improve the re-ID accuracy of video-based persons and learn more discriminative feature representations, we use a ResNet-50 network to extract global and partial features and fuse these features to obtain frame-level features. In the time dimension, based on a mutual information–temporal weight aggregation (MI–TWA) module, the partial features are added according to different weights and the global features are added according to equal weights and connected to output sequence features. The proposed method is extensively experimented on three public video datasets, MARS, DukeMTMC-VideoReID, and PRID-2011; the mean average precision (mAP) values are 82.4%, 94.1%, and 95.3% and Rank-1 values are 86.4%, 94.8%, and 95.2%, respectively.

The data layer devices in the Software Defined Network (SDN) play an important role in packet forwarding. However, whether the forwarding task can be efficiently completed by the node has not attracted enough attention. A method called TrustBlock is proposed in this paper, which introduces trust as a security attribute in SDN routing planning. Besides, in order to enhance the integrity and controllability of trust evaluation, the double-layer blockchain architecture is established. In the first layer, the behavior data of the node is recorded, and then the trust calculation is performed in the second layer. In the evaluation model, nodes' trust is calculated from three aspects: direct trust, indirect trust and historical trust. Firstly, from the perspective of security, blockchain is used to achieve identity authentication of nodes, after that, from the perspective of reliability, the forwarding status is used to calculate the trust value. Secondly, consensus algorithm is used to filter malicious recommendation trust value and prevent colluding attacks. Finally, the adaptive historical trust weight is designed to prevent the periodic attack. In this paper, the entropy method is used to determine the weight of each evaluation attribute, which can avoid the problem that the subjective judgment method is not adaptable to the weight setting. Simulation results show that the detection rate of the TrustBlock is up to 98.89%, which means this model can effectively identify the abnormal nodes in SDN. Moreover, it is attractive in terms of integrity and controllability.

Cold stress is a major environmental factor that detrimentally affects plant growth and development. Melatonin has been shown to confer plant tolerance to cold stress through activating the C-REPEAT BINDING FACTOR (CBF) pathway; however, the underlying modes that enable this function remain obscure. In this study, we investigated the role of H2O2 and Ca2+ signaling in the melatonin-induced CBF pathway and cold tolerance in watermelon (Citrullus lanatus L.) through pharmacological, physiological, and genetic approaches. According to the results, melatonin induced H2O2 accumulation, which was associated with the upregulation of respiratory burst oxidase homolog D (ClRBOHD) during the early response to cold stress in watermelon. Besides, melatonin and H2O2 induced the accumulation of cytoplasmic free Ca2+ ([Ca2+]cyt) in response to cold. This was associated with the upregulation of cyclic nucleotide-gated ion channel 2 (ClCNGC2) in watermelon. However, blocking of Ca2+ influx channels abolished melatonin- or H2O2-induced CBF pathway and cold tolerance. Ca2+ also induced ClRBOHD expression and H2O2 accumulation in early response to cold stress in watermelon. Inhibition of H2O2 production in watermelon by RBOH inhibitor or in Arabidopsis by AtRBOHD knockout compromised melatonin-induced [Ca2+]cyt accumulation and melatonin- or Ca2+-induced CBF pathway and cold tolerance. Overall, these findings indicate that melatonin induces RBOHD-dependent H2O2 generation in early response to cold stress. Increased H2O2 promotes [Ca2+]cyt accumulation, which in turn induces H2O2 accumulation via RBOHD, forming a reciprocal positive-regulatory loop that mediates melatonin-induced CBF pathway and subsequent cold tolerance.

Convolutional neural networks (CNNs) have demonstrated great achievement in increasing the accuracy and stability of medical image segmentation. However, existing CNNs are limited by the problem of dependency on the availability of training data owing to high manual annotation costs and privacy issues. To counter this limitation, domain adaptation (DA) and few-shot learning have been extensively studied. Inspired by these two categories of approaches, we propose an optimization-based meta-learning method for segmentation tasks. Even though existing meta-learning methods use prior knowledge to choose parameters that generalize well from few examples, these methods limit the diversity of the task distribution that they can learn from in medical image segmentation. In this paper, we propose a meta-learning algorithm to augment the existing algorithms with the capability to learn from diverse segmentation tasks across the entire task distribution. Specifically, our algorithm aims to learn from the diversity of image features which characterize a specific tissue type while showing diverse signal intensities. To demonstrate the effectiveness of the proposed algorithm, we conducted experiments using a diverse set of segmentation tasks from the Medical Segmentation Decathlon and two meta-learning benchmarks: model-agnostic meta-learning (MAML) and Reptile. U-Net and Dice similarity coefficient (DSC) were selected as the baseline model and the main performance metric, respectively. The experimental results show that our algorithm maximally surpasses MAML and Reptile by 2% and 2.4% respectively, in terms of the DSC. By showing a consistent improvement in subjective measures, we can also infer that our algorithm can produce a better generalization of a target task that has few examples.

Rural infrastructure has rather fixed users compared to urban infrastructure. This study evaluated the effect of rural infrastructure construction from the perspective of farmers. First, this study revised the American Customer Satisfaction Index (ACSI) model and selected a performance appraisal index for rural infrastructure based on this revised model. Then, the study adopted an interpretive structural model (ISM), analyzed the influence of each index factor, and developed a hierarchical directed graph. Finally, based on the mutual-influence relationships among the index factors in the hierarchical directed graph, a performance appraisal analytic network process (ANP) model was established. Based on discussions with rural college students and rural households in Sichuan, China, 246 questionnaires were obtained pertaining to rural infrastructure, and an empirical analysis was conducted. The results indicated that the performance of rural infrastructure construction is not very good. In particular, the full use of infrastructure and its role in improving the environment were found to be the worst. Meanwhile, the possibility of building information transparency and the longitudinal comparison of perceived performance appraisal results were the best. The performance of rural infrastructure construction was evaluated based on the perceptions of the direct users of rural infrastructure, and the relationship between the factors and the weight was measured reasonably. The proposed method was found to be workable and the analysis results reliable and effective.