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Abstract Background In recent years, several giant pandas have suffered from testicular tumor, which has seriously affected giant panda health. However, the pathogenesis of testicular tumor in giant panda is still unclear. Studies have shown that miRNAs are involved in the occurrence and development of a variety of cancers. However, the effect of miRNAs on giant panda testicular tumor has been little studied. Therefore, this study explored the pathogenesis of giant panda testicular tumor through miRNA and mRNA sequencing, and screened out diagnostic markers of testicular tumor. Results Combined with phenotypic symptoms and pathological section results, three giant pandas were diagnosed with testicular tumor and divided into tumor group, and three other giant pandas were divided into normal group. A total of 29 differentially expressed miRNAs (DEmiRNAs) were screened by blood miRNA-seq, and 3149 target gene candidates were predicted. Functional enrichment analysis showed that the target genes were mainly involved in intermembrane lipid transfer and ATP-dependent chromatin remodeling. However, only 5 DEmiRNAs were screened by miRNA-seq of blood-derived exosomes and 364 target genes were predicted, which were mainly involved in antigen processing and presentation. In addition, 216 differentially expressed genes (DEGs) were screened by RNA-seq, and functional enrichment analysis showed that tumor-specific DEGs significantly enriched to protein phosphorylation. Spearman correlation analysis of miRNA-mRNA showed that the expressions of miR-331-3p and PKIG were significantly positively correlated (spearman = 0.943, p

In the era of national big data strategies and burgeoning data markets, privacy-preserving databases play a crucial role in establishing an environment that is open, shared, and governed. Central to the construction of such databases is searchable encryption (SE), a fundamental cryptographic technology that enables efficient searching within encrypted data without the need for decryption. Among various SE schemes, attribute-based SE (ABSE) provides advantages in access control, data authenticity, and retrieval efficiency. However, a substantial limitation of most current ABSE implementations is their inability to support flexible SQL query methods in relational databases, as well as more granular query policies. Moreover, the reliance on traditional algebraic structures, such as bilinear pairing, renders these systems susceptible to quantum computing attacks. To address these challenges, this study presents a novel architecture for privacy-preserving databases that accommodates the SQL query language used in relational databases. This architecture is divided into two parts: clients and cloud outsourcing services. Within this framework, all data are in a ciphertext form outside of client access, and the data table in the cloud-based privacy-preserving database comprises four types of fields: public, encrypted index, encrypted data, and confidential fields. Upon receiving an SQL query from a user, the privacy-preserving SQL engine translates it into a private SQL language. This enables cryptographic retrieval of the encrypted index fields by converting the SQL query policy into several query credentials linked with the policy. These credentials facilitate the retrieval of encrypted data fields from the database, matching their index with the policy. The retrieved encrypted data fields can then be decrypted using the user’s private key at the client’s end for confirming the user’s identity. To provide cryptographic support for this privacy-preserving database architecture, we propose a retrieval-policy ABSE (RP-ABSE) scheme built upon a key-policy attribute-based encryption framework. The security of RP-ABSE is underpinned by a hard problem over an ideal lattice, particularly short integer solutions and learning with error problems. A notable advancement in this scheme is the binding of the secure query policy to the query credentials rather than the encrypted index fields. This binding ensures that encrypted data can be cryptographically retrieved by different query policies, eliminating the need for updating the encrypted data when query policies change. Simultaneously, we introduce a small policy matrix to optimize the generation of secure query policies and mitigate cumulative errors during the index matching process. Ultimately, this study proves that the query credential satisfies unforgeability under chosen policy attacks and that the RP-ABSE scheme achieves semantic security under chosen plaintext attacks involving policy and identity queries. Therefore, the proposed privacy-preserving database architecture offers crucial technique support for the development of data market mechanisms and data governance systems.

Periodontitis is a chronic inflammatory disease caused by plaque that destroys the alveolar bone tissues, resulting in tooth loss. Poor eradication of pathogenic microorganisms, persistent malignant inflammation and impaired osteo-/angiogenesis are currently the primary challenges to control disease progression and rebuild damaged alveolar bone. However, existing treatments for periodontitis fail to comprehensively address these issues. Herein, an injectable composite hydrogel (SFD/CS/ZIF-8@QCT) encapsulating quercetin-modified zeolitic imidazolate framework-8 (ZIF-8@QCT) is developed. This hydrogel possesses thermo-sensitive and adhesive properties, which can provide excellent flowability and post-injection stability, resist oral fluid washout as well as achieve effective tissue adhesion. Inspirationally, it is observed that SFD/CS/ZIF-8@QCT exhibits a rapid localized hemostatic effect following implantation, and then by virtue of the sustained release of zinc ions and quercetin exerts excellent collective functions including antibacterial, immunomodulation, pro-osteo-/angiogenesis and pro-recruitment, ultimately facilitating excellent alveolar bone regeneration. Notably, our study also demonstrates that the inhibition of osteo-/angiogenesis of PDLSCs under the periodontitis is due to the strong inhibition of energy metabolism as well as the powerful activation of oxidative stress and autophagy, whereas the synergistic effects of quercetin and zinc ions released by SFD/CS/ZIF-8@QCT are effective in reversing these biological processes. Overall, our study presents innovative insights into the advancement of biomaterials to regenerate alveolar bone in periodontitis.

Abstract Background The Yangtze River Economic Belt, as a core economic region in China, is facing the dual challenges of an aging population and growing healthcare demand, and the balanced development and optimal allocation of nursing human resources is crucial to the region’s healthcare system. An in-depth study of the regional differences and convergence of nursing human resources in the region will provide a key basis for policy makers to achieve equity and efficiency in healthcare services and meet the growing demand for healthcare. Aim To analyze the regional differences and convergence characteristics of nursing human resource levels in the Yangtze River Economic Belt, and to provide scientific references for optimizing regional nursing human resource allocation. Methods Based on the panel data of 107 cities in the Yangtze River Economic Belt from 2010 to 2020, the regional differences and their sources were analyzed by using Dagum’s Gini coefficient, and the convergence characteristics were examined by the coefficient of variation and spatial convergence model. Results The average value of the number of nursing human resources in the Yangtze River Economic Belt is 2,132,300 people, with obvious regional differences, and the hypervariable density difference (53.01%) is the main source of the regional differences; there are obvious trends of σ-convergence and conditional β-convergence of the level of nursing human resources in the overall and the three major regions of the upstream, midstream, and downstream, and different factors have different moderating effects on the speed of spatial convergence in the other areas. Conclusion The implementation of precise policies for nursing human resources in different regions of the Yangtze River Economic Belt steadily reduces the regional differences between the upper, middle, and lower reaches and enhances the spatial linkage between regions of nursing human resources to improve the quality of nursing human resources.

Abstract Background Uncorrected refractive error (URE) is one of the main causes of visual impairments. URE may reduce interaction and learning in the classroom, leading to social isolation, irreversible amblyopia, lack of external knowledge, and restrictions on education and employment opportunities. Our aim was to investigate the prevalence and related factors of URE in adolescents using epidemiological surveys and questionnaire surveys related to lifestyle habits. Methods A cross-sectional school-based study was conducted in Nantong, China, including adolescents 12–19 years of age from 16 schools. URE was defined as presenting visual acuity worse than 6/12 and improving to ≥ 1 lines after correction in either eye. Univariate and multivariate logistic regression analyses were used to investigate specific correlations between URE and related lifestyle parameters. Non-cycloplegic autorefraction was assessed for each adolescent. Results A total of 2,910 adolescents were analyzed, of which 50.3% (n = 1,465) were male, and 49.7% (n = 1,445) were female. The mean age was 15.23 ± 1.77 years. The overall prevalence of URE was 23.7%. The total prevalence of REC and eREC was 85.1% and 71.7%, respectively, and both of them showed an increasing trend with age (Ptrend = 0.018 and Ptrend = 0.019, respectively). A higher prevalence of URE was related to myopia, anisometropia, and increased daily use of electronic products. Timely visual examination by medical institutions, more extracurricular homework, and older age were protective factors for URE. Among the 689 adolescents with URE, 362 (52.5%) did not receive any refractive correction, and 327 (47.5%) used corrected glasses. Conclusion URE was highly prevalent among adolescents in China. Myopia was the most important risk factor for URE. The impact of anisometropia and increased daily use of electronic devices on URE was significant. Timely visual examinations by medical institutions served as an effective protective factor against URE. Further research on adjusting intervention strategies is therefore needed to eliminate preventable visual impairments.

Abstract Characterizing multipartite quantum systems is crucial for quantum computing and many-body physics. The problem, however, becomes challenging when the system size is large and the properties of interest involve correlations among a large number of particles. Here we introduce a neural network model that can predict various quantum properties of many-body quantum states with constant correlation length, using only measurement data from a small number of neighboring sites. The model is based on the technique of multi-task learning, which we show to offer several advantages over traditional single-task approaches. Through numerical experiments, we show that multi-task learning can be applied to sufficiently regular states to predict global properties, like string order parameters, from the observation of short-range correlations, and to distinguish between quantum phases that cannot be distinguished by single-task networks. Remarkably, our model appears to be able to transfer information learnt from lower dimensional quantum systems to higher dimensional ones, and to make accurate predictions for Hamiltonians that were not seen in the training.

Abstract Rosacea is a chronic inflammatory skin disorder, whose underlying cellular and molecular mechanisms remain obscure. Here, we generate a single-cell atlas of facial skin from female rosacea patients and healthy individuals. Among keratinocytes, a subpopulation characterized by IFNγ-mediated barrier function damage is found to be unique to rosacea lesions. Blocking IFNγ signaling alleviates rosacea-like phenotypes and skin barrier damage in mice. The papulopustular rosacea is featured by expansion of pro-inflammatory fibroblasts, Schwann, endothelial and macrophage/dendritic cells. The frequencies of type 1/17 and skin-resident memory T cells are increased, and vascular mural cells are characterized by activation of inflammatory pathways and impaired muscle contraction function in rosacea. Most importantly, fibroblasts are identified as the leading cell type producing pro-inflammatory and vasodilative signals in rosacea. Depletion of fibroblasts or knockdown of PTGDS, a gene specifically upregulated in fibroblasts, blocks rosacea development in mice. Our study provides a comprehensive understanding of the aberrant alterations of skin-resident cell populations and identifies fibroblasts as a key determinant in rosacea development.

Abstract Background Measures in operations management are pivotal for monitoring and assessing various aspects of hospital performance. Existing literature highlights the importance of regularly updating key management measures to reflect changing trends and organizational goals. Advancements in machine learning (ML) have presented promising opportunities for enhancing the process of updating operations management measures. However, their specific application and performance remain relatively unexplored. We aimed to investigate the feasibility and effectiveness of using common ML techniques to identify and update key measures in hospital operations management. Methods Historical data on 43 measures on financial balance and quality of care under 4 categories were retrieved from the BI system of a regional health system in Central China. The dataset included 17 surgical and 15 non-surgical departments over 48 months. Four common ML techniques, linear models (LM), random forest (RF), partial least squares (PLS), and neural networks (NN), were used to identify the most important measures. Ordinary least square was employed to investigate the impact of the top 10 measures. A ground truth validation compared the ML-identified key measures against the humanly decided strategic measures from annual meeting minutes. Results For financial balancing, inpatient treatment revenue was an important measure in 3/4 years, followed by equipment depreciation costs. The measures identified using the same technique differed between years, though RF and PLS yielded relatively consistent results. For quality of care, none of the ML-identified measures repeated over the years. Those consistently important over four years differed almost entirely among four techniques. On ground truth validation, the 2016–2019 ML-identified measures were among the humanly identified measures, with the exception of equipment depreciation from the 2019 dataset. All the ML-identified measures for quality of care failed to coincide with the humanly decided measures. Conclusions Using ML to identify key hospital operational measures is viable but performance of ML techniques vary considerably. RF performs best among the four techniques in identifying key measures in financial balance. None of the ML techniques seem effective for identifying quality of care measures. ML is suggested as a decision support tool to remind and inspire decision-makers in certain aspects of hospital operations management.

Abstract Accurate monitoring of wheat phenological stages is essential for effective crop management and informed agricultural decision-making. Traditional methods often rely on labour-intensive field surveys, which are prone to subjective bias and limited temporal resolution. To address these challenges, this study explores the potential of near-surface cameras combined with an advanced deep-learning approach to derive wheat phenological stages from high-quality, real-time RGB image series. Three deep learning models based on three different spatiotemporal feature fusion methods, namely sequential fusion, synchronous fusion, and parallel fusion, were constructed and evaluated for deriving wheat phenological stages with these near-surface RGB image series. Moreover, the impact of different image resolutions, capture perspectives, and model training strategies on the performance of deep learning models was also investigated. The results indicate that the model using the sequential fusion method is optimal, with an overall accuracy (OA) of 0.935, a mean absolute error (MAE) of 0.069, F1-score (F1) of 0.936, and kappa coefficients (Kappa) of 0.924 in wheat phenological stages. Besides, the enhanced image resolution of 512 × 512 pixels and a suitable image capture perspective, specifically a sensor viewing angle of 40° to 60° vertically, introduce more effective features for phenological stage detection, thereby enhancing the model’s accuracy. Furthermore, concerning the model training, applying a two-step fine-tuning strategy will also enhance the model’s robustness to random variations in perspective. This research introduces an innovative approach for real-time phenological stage detection and provides a solid foundation for precision agriculture. By accurately deriving critical phenological stages, the methodology developed in this study supports the optimization of crop management practices, which may result in improved resource efficiency and sustainability across diverse agricultural settings. The implications of this work extend beyond wheat, offering a scalable solution that can be adapted to monitor other crops, thereby contributing to more efficient and sustainable agricultural systems.

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a Priority 1 (Critical) pathogen urgently requiring new antibiotics. Polymyxins are a last-line option against CRAB-associated infections. This transcriptomic study utilized a CRAB strain to investigate mechanisms of bacterial killing with polymyxin B, colistin, colistin B, and colistin/sulbactam combination therapy. After 4 h of 2 mg/L polymyxin monotherapy, all polymyxins exhibited common transcriptomic responses which primarily involved disruption to amino acid and fatty acid metabolism. Of the three monotherapies, polymyxin B induced the greatest number of differentially expressed genes (DEGs), including for genes involved with fatty acid metabolism. Gene disturbances with colistin and colistin B were highly similar (89 % common genes for colistin B), though effects on gene expression were generally lower (0–1.5-fold in most cases) with colistin B. Colistin alone (2 mg/L) or combined with sulbactam (64 mg/L) resulted in rapid membrane disruption as early as 1 h. Transcriptomic analysis of this combination revealed that the effects were driven by colistin, which included disturbances in fatty acid synthesis and catabolism, and inhibition of nutrient uptake. Combination therapy produced substantially higher fold changes in 72 % of DEGs shared with monotherapy, leading to substantially greater reductions in fatty acid biosynthesis and increases in biofilm, cell wall, and phospholipid synthesis. This indicates synergistic bacterial killing with the colistin/sulbactam combination results from a systematic increase in perturbation of many genes associated with bacterial metabolism. These mechanistic insights enhance our understanding of bacterial responses to polymyxin mono- and combination therapy and will assist to optimize polymyxin use in patients.

Abstract Background Ensuring that the scale and hierarchical structure of health human resources are rational, and that medical services are efficient and fair, is an important task of practical significance. On this basis, examining the impact of health human resources on the level of medical services presents a new and formidable challenge. This study aims to delve into how the scale and hierarchical structure of health human resources in China’s four major economic regions affect the fairness and efficiency of medical services, and to identify optimization strategies. Methods This study utilizes provincial panel data from China’s four major economic regions spanning the years 2009 to 2021. Initially, it provides a statistical description of the current state of health human resources and the level of medical services. Subsequently, it employs a fixed-effects model to analyze the impact of the scale and hierarchical structure of health human resources, as well as their interactive effects, on the fairness and efficiency of medical services, and discusses the interactive mechanisms between medical service fairness and medical service efficiency. Furthermore, after conducting a comprehensive evaluation of the level of medical services using the entropy weight method, it explores the regional heterogeneity and temporal dynamics in the influence of the scale and hierarchical structure of health human resources on the level of medical services. Finally, the study examines the scientific validity and rationality of the research findings through various robustness checks, including the substitution of research variables and models. Results The study found that the scale of health human resources has a promoting effect on the equity of medical services (β ≤ 0.643, p ≤ 0.01), but exhibits an inhibitory effect on the efficiency of medical services (β ≥ -0.079, p ≤ 0.1); the hierarchical structure of health human resources shows a positive impact on both the equity and efficiency of medical services (βequity ≤ 0.160, p ≤ 0.01; βefficiency ≤ 0.341, p ≤ 0.05); at the same time, the results indicate that the interactive effect of the scale and hierarchical structure of health human resources promotes equity in medical services (β = 0.067, p ≤ 0.01), but restricts the efficiency of medical services (β ≥ -0.039, p ≤ 0.01); the mechanism by which health human resources affect the level of medical services in China’s western and northeastern regions is more pronounced than in the central and eastern regions; after the implementation of the “Healthy China 2030” Planning Outline, the role of health human resources in the level of medical services has been strengthened; in the robustness tests, the model remains robust after replacing the core explanatory variables, with R2 maintained between 0.869 and 0.972, and the dynamic GMM model test shows a significant second-order lag in the level of medical services (βequity ≤ 0.149, p ≤ 0.01; βefficiency ≤ 0.461, p ≤ 0.01); the channel test results prove that managerial personnel and other technical personnel are key pathways in regulating the impact of medical staff on the level of medical services. Conclusion This study provides an in-depth analysis of the impact of health human resources on the level of medical services, revealing that both the scale and hierarchical structure of health human resources significantly affect the equity and efficiency of medical services. Furthermore, the influence of health human resources on the level of medical services exhibits regional heterogeneity and temporal characteristics. Robustness tests ensure the scientific validity and robustness of the research conclusions. This provides effective references for optimizing the allocation of health human resources and improving the level of medical services.

The arthroconidial yeast-like species currently classified in the asexual genera Geotrichum and Saprochaete and the sexual genera Dipodascus, Galactomyces and Magnusiomyces are frequently associated with dairy and cosmetics production, fruit rot and human infection. However, the taxonomic system of these fungi has not been updated to accommodate the new nomenclature code adopting the “one fungus, one name” principle. Here, we performed phylogenetic analyses of these yeast-like species based on the sequences of the internal transcribed spacer (ITS) region and the D1/D2 domain of the large subunit of the rRNA gene. Two monophyletic groups were recognised from these species. One group contained Dipodascus, Galactomyces, and Geotrichum species and the other Magnusiomyces and Saprochaete species. We thus assigned the species in each group into one genus and selected the genus name Geotrichum for the first group and Magnusiomyces for the second one based on the principle of priority of publication. Five new Geotrichum species were identified from arthroconidial yeast strains recently isolated from various sources in China. The new species are described as Ge. dehoogii sp. nov., Ge. fujianense sp. nov., Ge. maricola sp. nov., Ge. smithiae sp. nov., and Ge. sinensis sp. nov.

The covered karst collapse has the characteristics of concealment, suddenness, uncertainty, and mechanism complexity, which leads to its prevention and treatment more difficult. In the process of covered karst collapse, soil caves formed in the overlying soil, develop and expand until the surface collapse. Numerical simulation such as the finite element method is an effective method of soil cave collapse; however, the finite element method can not solve the problem of large deformation of rock mass such as particle migration and soil collapse. Based on the analysis of the geological conditions of karst collapse in Jiangshan city, Zhejiang province, this study used the particle flow code (PFC) to simulate the formation process of covered karst soil cave and then to reveal the displacement of special soil particles, the development trend of cracks, and the change of system imbalance force on a micro level. The multi-field variation characteristics of the formation of covered karst soil cave under external force conditions were reproduced. The results show that the development process of karst soil cave could be summarized into three stages including crack generation, connected surface formation, and particle peeling. As the karst soil cave began to develop, there was a good consistency among the displacement curve of soil particles, the penetration degree of cracks, and the unbalance force, and the vertical expansion speed was larger than the horizontal speed. The critical flow velocity of the initial soil cavity is 0.104 cm/s when the overburden soil is clay. This study can provide basic information for the treatment of karst collapse.

Abstract An increased risk of target organ damage (TOD) has been reported in patients with primary aldosteronism (PA). However, there is relatively little related research on the correlation between the degree of TOD and those with and without PA in newly diagnosed hypertensive patients. The aim of this study was to assess the association between PA and TOD among patients with newly diagnosed hypertension. Newly diagnosed hypertensive patients were consecutively recruited from January 2015 to June 2020 at the University of Hong Kong‐Shenzhen Hospital. Patients were stratified into those with and without PA. Data for left ventricular mass index (LVMI), carotid intima‐media thickness (CIMT) and plaque, and microalbuminuria were systematically collected. A total of 1044 patients with newly diagnosed hypertension were recruited, 57 (5.5%) of whom were diagnosed with PA. Patients with PA had lower blood pressure, serum lipids, body mass index, and plasma renin activity and a higher incidence of hypokalemia than those without PA. In contrast, the prevalence of left ventricular hypertrophy, increased CIMT, and microalbuminuria was higher in patients with PA than in those without PA. Multivariable regression analysis demonstrated that PA was independently associated with increased LVMI, CIMT and microalbuminuria. Among patients with newly diagnosed hypertension, those with PA had more severe TOD, including a higher LVMI, CIMT and microalbuminuria, than those without PA. These findings emphasize the need for screening TOD in newly diagnosed hypertension due to underlying PA.

Abstract To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.

Abstract Binding of Staphylococcus aureus protein A (SPA) to osteoblasts induces apoptosis and inhibits bone formation. Bone marrow-derived mesenchymal stem cells (BMSCs) have the ability to differentiate into bone, fat and cartilage. Therefore, it was important to analyze the molecular mechanism of SPA on osteogenic differentiation. We introduced transcript sequence data to screen out differentially expressed genes (DEGs) related to SPA-interfered BMSC. Protein–protein interaction (PPI) network of DEGs was established to screen biomarkers associated with SPA-interfered BMSC. Receiver operating characteristic (ROC) curve was plotted to evaluate the ability of biomarkers to discriminate between two groups of samples. Finally, we performed GSEA and regulatory analysis based on biomarkers. We identified 321 DEGs. Subsequently, 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap and Kif14) were identified by hubba algorithm in PPI. ROC analysis showed that six biomarkers could clearly discriminate between normal differentiated and SPA-interfered BMSC. Moreover, we found that these biomarkers were mainly enriched in the pyrimidine metabolism pathway. We also constructed '71 circRNAs-14 miRNAs-5 mRNAs' and '10 lncRNAs-5 miRNAs-2 mRNAs' networks. Kntc1 and Asf1b genes were associated with rno-miR-3571. Nek2 and Asf1b genes were associated with rno-miR-497-5p. Finally, we found significantly lower expression of six biomarkers in the SPA-interfered group compared to the normal group by RT-qPCR. Overall, we obtained 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap, and Kif14) related to SPA-interfered BMSC, which provided a theoretical basis to explore the key factors of SPA affecting osteogenic differentiation.

Abstract Floating Production Storage and Offloading (FPSO) unit being an offshore vessel, storing and producing crude oil, prior to crude oil being transported by accompanying shuttle tanker. Critical mooring/hawser strains during offloading operation have to be accurately predicted, in order to maintain operational safety and reliability. During certain types of offloading, excessive hawser tensions may occur, causing operational risks. Current study examines FPSO vessel’s dynamic reactions to hydrodynamic wave-induced loads, given realistic in situ environmental conditions, utilizing the AQWA software package. Current study advocates novel multi-dimensional spatiotemporal risks assessment approach, that is particularly well suited for large dataset analysis, based on numerical simulations (or measurements). Advocated multivariate reliability methodology may be useful for a variety of marine and offshore systems that must endure severe environmental stressors during their intended operational lifespan. Methodology, presented in this study provides advanced capability to efficiently, yet accurately evaluate dynamic system failure, hazard and damage risks, given representative dynamic record of multidimensional system’s inter-correlated critical components. Gaidai risk assessment method being novel dynamic multidimensional system’s lifetime assessment methodology. In order to validate and benchmark Gaidai risk assessment method, in this study it was applied to FPSO and potentially LNG (i.e., Liquid Natural Gas) vessels dynamics. Major advantage of the advocated approach is that there are no existing alternative risk assessment methods, able to tackle unlimited number of system’s dimensions. Accurate multi-dimensional risk assessment had been carried out, based on numerically simulated data, partially verified by available laboratory experiments. Confidence intervals had been given for predicted dynamic high-dimensional system risk levels.

Plasmon-induced hot-electron transfer from metal nanostructures is being intensely pursed in current photocatalytic research, however it remains elusive whether molecular-like metal clusters with excitonic behavior can be used as light-harvesting materials in solar energy utilization such as photocatalytic methanol steam reforming. In this work, we report an atomically precise Cu13 cluster protected by dual ligands of thiolate and phosphine that can be viewed as the assembly of one top Cu atom and three Cu4 tetrahedra. The Cu13H10(SR)3(PR’3)7 (SR = 2,4-dichlorobenzenethiol, PR’3 = P(4-FC6H4)3) cluster can give rise to highly efficient light-driven activity for methanol steam reforming toward H2 production.

The contribution of spike photosynthesis to grain yield (GY) has been overlooked in the accurate spectral prediction of yield. Thus, it’s essential to construct and estimate a yield-related phenotypic trait considering spike photosynthesis. Based on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years, our objectives were to (i) construct a yield-related phenotypic trait (spike–leaf composite indicator, SLI) accounting for the contribution of the spike to photosynthesis, (ii) develop a novel spectral index (enhanced triangle vegetation index, ETVI3) sensitive to SLI, and (iii) establish and evaluate SLI estimation models by integrating spectral indices and machine learning algorithms. The results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area index. ETVI3 maintained a strong correlation with SLI throughout the growth stage, whereas the correlations of other spectral indices with SLI were poor after spike emergence. Integrating spectral indices and machine learning algorithms improved the estimation accuracy of SLI, with the most accurate estimates of SLI showing coefficient of determination, root mean square error (RMSE), and relative RMSE values of 0.71, 0.047, and 26.93%, respectively. These results provide new insights into the role of fruiting organs for the accurate spectral prediction of GY. This high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.

Abstract Despite the growing attention on blockchain, phishing activities have surged, particularly on newly established chains. Acknowledging the challenge of limited intelligence in the early stages of new chains, we propose ADA-Spear-an automatic phishing detection model utilizing adversarial domain adaptive learning which symbolizes the method’s ability to penetrate various heterogeneous blockchains for phishing detection. The model effectively identifies phishing behavior in new chains with limited reliable labels, addressing challenges such as significant distribution drift, low attribute overlap, and limited inter-chain connections. Our approach includes a subgraph construction strategy to align heterogeneous chains, a layered deep learning encoder capturing both temporal and spatial information, and integrated adversarial domain adaptive learning in end-to-end model training. Validation in Ethereum, Bitcoin, and EOSIO environments demonstrates ADA-Spear’s effectiveness, achieving an average F1 score of 77.41 on new chains after knowledge transfer, surpassing existing detection methods.

Abstract The colloidal gold nanoparticle (AuNP)‐based colorimetric lateral flow assay (LFA) is one of the most promising analytical tools for point‐of‐care disease diagnosis. However, the low sensitivity and insufficient accuracy still limit its clinical application. In this work, a machine learning (ML)‐optimized colorimetric LFA with ultrasound enrichment is developed to achieve the sensitive and accurate detection of tau proteins for early screening of Alzheimer's disease (AD). The LFA device is integrated with a portable ultrasonic actuator to rapidly enrich microparticles using ultrasound, which is essential for sample pre‐enrichment to improve the sensitivity, followed by ML algorithms to classify and predict the enhanced colorimetric signals. The results of the undiluted serum sample testing show that the protocol enables efficient classification and accurate quantification of the AD biomarker tau protein concentration with an average classification accuracy of 98.11% and an average prediction accuracy of 99.99%, achieving a limit of detection (LOD) as sensitive as 10.30 pg mL−1. Further point‐of‐care testing (POCT) of human plasma samples demonstrates the potential use of LFA in clinical trials. Such a reliable lateral flow immunosensor with high precision and superb sensing performance is expected to put LFA in perspective as an AD clinical diagnostic platform.

BackgroundConstipation is a common symptom in maintenance hemodialysis patients and greatly affects the quality of survival of hemodialysis patients. Fecal microbiota transplantation and probiotics are feasible treatments for functional constipation, but there is still a gap in the research on the characteristics of gut flora in patients with maintenance hemodialysis combined with constipation. The aim of this study is to clarify the characteristics of the intestinal flora and its changes in maintenance hemodialysis patients with constipation.MethodsFecal samples were collected from 45 participants, containing 15 in the maintenance hemodialysis constipation group,15 in the maintenance hemodialysis non-constipation group and 15 in the healthy control group. These samples were analyzed using 16S rRNA gene sequencing. The feature of the intestinal microbiome of maintenance hemodialysis constipation group and the microbiome differences among the three groups were elucidated by species annotation analysis, α-diversity analysis, β-diversity analysis, species difference analysis, and predictive functional analysis.ResultsThe alpha diversity analysis indicated that maintenance hemodialysis constipation group was less diverse and homogeneous than maintenance hemodialysis non-constipation group and healthy control group. At the genus level, the top ten dominant genera in maintenance hemodialysis constipation group patients were Enterococcus, Escherichia-Shigella, Bacteroides, Streptococcus, Bifidobacterium, Ruminococcus_gnavus_group, Lachnospiraceae_unclassified, Faecalibacterium, Akkermansia and UCG-002. Compared with non-constipation group, the Enterococcus, Rhizobiales_unclassified, Filomicrobium, Eggerthella, Allobaculum, Prevotella_7, Gordonibacter, Mitochondria_unclassified, Lachnoanaerobaculum were significantly higher in constipation group (p

Microplastic (MP) transport patterns under open channel shear flow remain unclear. This study investigates the transport laws of MPs at various flow velocities, MP densities, sizes and concentrations in the U-shaped experimental flume and the numerical flume based on Lattice Boltzmann Method (LBM). The results indicate that the average horizontal particle velocity and the transport distances of Polyvinyl chloride (PVC) and Polystyrene (PS) particles increase with the average cross-sectional flow velocity, while the average vertical particle velocity decreases with it. The total average particle velocity closely matches the average vertical particle velocity, regardless of the variation in MP size, density and concentration. Formula-based analysis reveals that the acceleration of spherical MP transport mainly depends on the particle size and its consequent relative drag force term (RDFT) under the conditions with a single type of MP particles, but on the particle density and its consequent RDFT and relative gravity term (RGT) in the case concerning different types of MP particles with identical particle sizes. The average horizontal particle velocity maximum of PVC and PS are both strongly correlated with the average flow velocity maximum in the cross-section. This correlation lowers with the MP particle size and concentration, and is independent of MP density. Our findings can provide reference for the prevention and control of MP pollution in rivers.

Abstract Temporomandibular joint osteoarthritis (TMJOA) is a commonly encountered degenerative joint disease in oral and maxillofacial surgery. Recent studies have shown that the excessive unbalanced activation of Wnt/β‐catenin signaling is connected with the pathogenesis of TMJOA and due to the inability to inhibit the over‐activated Wnt pathway, while Wnt16‐deficient mice has a more severe Knee OA. However, the efficacy of direct intra‐TMJ injection of Wnt16 for the relief of TMJOA is still not directly confirmed. Moreover, small‐molecule drugs such as Wnt16 usually exhibit short‐lived efficacy and poor treatment adherence. Therefore, in order to obtain a stable release of Wnt16 both in the short and long term, this study fabricates a double‐layer slow‐release Wnt16 carrier based on mesoporous silica nanospheres (MSNs) encased within hyaluronic acid (HA) hydrogels. The biofunctional hydrogel HA/Wnt16@MSN is analyzed both in vitro and in vivo to evaluate the treatment of TMJOA. As a result, it shows superior pro‐cartilage matrix restoration and inhibition of osteoclastogenesis ability, and effectively inhibits the over‐activation of the Wnt/β‐catenin pathway. Taken together, biofunctional hydrogel HA/Wnt16@MSN is a promising candidate for the treatment of TMJOA.

Water and nitrogen (N) are recognized as the primary determinants influencing the development and output of winter wheat. They affect the growth of winter wheat not only through their own changes, but also through their interaction. The translocation and accumulation of pre- and post-anthesis assimilates (including dry matter and N) are important physiological processes in winter wheat, which are closely related to the resource use efficiency and yield. However, a dearth of research exists that examines the complex interplay between varying water levels, especially severe water deficit, and N deficiency levels on the growth dynamics of winter wheat. The purpose of this study was to quantify and compare the effects of different degrees of water deficit and N interaction on assimilate translocation, water and N use efficiency and yield of winter wheat. A four-year long-term field experiment conducted under the rain-out shelter including four irrigation and two N levels was launched during 2019–2023. This method avoided the impact of precipitation on water treatment and helped to achieve serious water deficit treatment. The findings indicated that the higher N application improved the wheat's ability by 49.6 % - 362.3 % to utilize the available soil water. The pre- and post-anthesis translocation and accumulation of assimilates (including dry matter and N) in winter wheat increase alongside elevated levels of water and N application, except under severe water deficit treatment. Plants under mild to moderate water deficit were better able to translocate the pre-anthesis assimilates. However, the severe water deficit hindered the re-translocation of assimilates before anthesis. Providing additional N during periods of severe water scarcity leads to a 13.4 % - 44.7 % reduction in water use efficiency (WUE). Furthermore, both the irrigation water use efficiency and WUE diminished by 10.3 % - 60.5 % and 4.5 % - 41.4 % with higher levels of irrigation, while improved by 24.4 % - 48.2 % and 12.6 % - 39.4 % with higher N application rates. Conversely, N partial factor productivity and N use efficiency followed the opposite trend. Similar to WUE, increasing N application under severe water deficit would result in a yield reduction of 38.7 %. The reduction in crop yield resulting from severe water stress was primarily ascribed to the decline in the kernels number per spike (up to 74.9 %), with the reduction in spike number per unit area following closely behind (up to 29.1 %). This integrated approach, combining resource use efficiency with a detailed assessment of assimilate dynamics, provides a holistic view of how water and N management strategies impact winter wheat performance. The findings will offer precise insights for developing targeted irrigation and N scheduling strategies for sustaining both winter wheat production and environmental sustainability.

BackgroundTo date, no randomized controlled trials have specifically addressed behavior changes after HIV self-testing (HIVST) among transgender women. ObjectiveThis study aims to evaluate the effects of HIVST on changes in HIV testing behavior, frequency of condomless sex, and partner numbers among transgender women in China. MethodsParticipants were recruited from 2 Chinese cities using both online and offline methods. Transgender women were randomly assigned to receive an HIVST intervention. Data from the previous 3 months were collected at baseline, 3 months, and 6 months. The primary outcome was the mean change in the number of HIV tests among transgender women during the 6-month follow-up. An intention-to-treat analysis was conducted. The statistical analysis used analysis of covariance and linear mixed-effects models. ResultsFrom February to June 2021, and 255 transgender women were recruited, of which only 36.5% (93/255) had a steady job, and 27.1% (69/255) earned less than US $414.9 of income per month. They were randomly assigned to the intervention (n=127) and control (n=128) groups. At 6 months, the mean number of HIV tests was 2.14 (95% CI 1.80-2.48) in the intervention group and 1.19 (95% CI 0.99-1.40) in the control group (P

ObjectiveThis study aims to explore the influence of combining autologous platelet-rich gel (APG) with continuous vacuum-sealed drainage (CVSD) and the exogenous recombinant human acidic fibroblast growth factor (rh-aFGF) on the healing processes of diabetic foot ulcers (DFU). The primary objective is to elucidate the complex molecular mechanisms associated with DFU, providing innovative perspectives for its treatment.MethodsNinety patients diagnosed with DFU were randomly allocated into three distinct groups. Group A underwent CVSD following wound cleansing to facilitate healing. In Group B, in addition to conventional treatment, negative pressure wound therapy was applied, and rh-aFGF was introduced into normal saline for lavage, building upon the procedures of Group A. Group C received APG along with the interventions applied in Group B. The clinical efficacy of each group was systematically observed and analyzed. Additionally, changes in plasma oxidative stress, inflammatory markers, vascular endothelial growth factor (VEGF), and pigment epithelium-derived factor (PEDF) were assessed both before treatment and 14 days post-treatment.ResultsFollowing treatment, all groups exhibited commendable clinical efficacy. Group C demonstrated a superior wound healing rate, reduced frequency of dressing changes, and shorter wound healing duration (P< 0.05). Compared to baseline measurements, the levels of superoxide dismutase and PEDF increased, while malondialdehyde, VEGF, interleukin-6, interleukin-8, and monocyte chemotactic factor MCP-1 decreased in the wound tissue across all groups. Notably, Group C showed the most significant improvement in clinical efficacy and fortification of molecular mechanisms against oxidative stress (all P< 0.05).ConclusionsThe integrative therapeutic approach combining APG with CVSD and rh-aFGF demonstrates notable efficacy in advancing wound healing. This effectiveness is evident through the reduced frequency of dressing changes and alleviation of wound-related pain. Additionally, the treatment regimen improves the cure rate for challenging, refractory wounds. These favorable outcomes can be attributed to the reduction of oxidative stress levels, attenuation of the local inflammatory response, and the enhancement of the balance between PEDF and VEGF.

ObjectivePhysical activity (PA) plays an important role in human health. However, the relationship between the PA and dysthyreosis was not clear. This study aimed to explore this question.MethodsWe performed a population-based study on the basis of the participant’s information that was collected from the National Health and Nutrition Examination Survey (NHANES) database. The association of the thyroid hormone and total PA metabolic equivalent task (MET) were assessed via linear regression analysis with adjusting for different covariates. Moreover, we also used path analysis to explore the causality between PA, thyroid hormone index, and dysthyreosis. The restricted cubic spline analysis was used to explore the non-linear relationship between the thyroid hormone index and the PA total MET.ResultsA total of 2118 participants aged≥20, including 969 females and 1149 males, were collected from NHANES. The linear regression with multivariate adjustment suggested a linear relationship between the PA total MET and Thyroid-Stimulating Hormone Index (TSHI), and Thyroid Feedback Quantile-Based Index (TFQI), respectively. And TFQI and dysthyresis occurrence were significantly correlated (P

In patients with rheumatoid arthritis (RA), intestinal flora imbalance and butyrate metabolism disorders precede clinical arthritis and are associated with the pathogenesis of RA. This imbalance can alter the immunology and intestinal permeability of the intestinal mucosa, leading to damage to the intestinal barrier. In this context, bacteria and their metabolites can enter the bloodstream and reach the distant target tissues of the host, resulting in local inflammation and aggravating arthritis. Additionally, arthritis is also exacerbated by bone destruction and immune tolerance due to disturbed differentiation of osteoclasts and adaptive immune cells. Of note, butyrate is a metabolite of intestinal flora, which not only locally inhibits intestinal immunity and targets zonulin and tight junction proteins to alleviate intestinal barrier-mediated arthritis but also inhibits osteoclasts and autoantibodies and balances the immune responses of T and B lymphocytes throughout the body to repress bone erosion and inflammation. Therefore, butyrate is a key intermediate linking intestinal flora to the host. As a result, restoring the butyrate-producing capacity of intestinal flora and using exogenous butyrate are potential therapeutic strategies for RA in the future.

The surface plasmon resonance (SPR) biosensor technology is a novel optical analysis method for studying intermolecular interactions. Owing to in-depth research on traditional Chinese medicine (TCM) in recent years, comprehensive and specific identification of components and target interactions has become key yet difficult tasks. SPR has gradually been used to analyze the active components of TCM owing to its high sensitivity, strong exclusivity, large flux, and real-time monitoring capabilities. This review sought to briefly introduce the active components of TCM and the principle of SPR, and provide historical and new insights into the application of SPR in the analysis of the active components of TCM.

In arid areas, biodegradable film has recently had the potential to replace polyethylene (PE) film to address plastic pollution. However, the positive effect of biodegradable film on soil moisture and salt control is weaker than that of PE film. Magnetized irrigation water technology is expected to compensate for this limitation. This study comprised a field experiment in 20212023 to study how two types of biodegradable film (M1, black; M2, transparent) and six magnetization intensity on irrigation water (T0, 0 Gs; T1, 1000 Gs; T2, 2000 Gs; T3, 3000 Gs; T4, 4000 Gs; T5, 5000 Gs) affect the degradation rate of biodegradable film, soil watersalt distribution, growth, and quality of processing tomatoes. The traditional PE film mulching and non-magnetized irrigation were used as the control group (MPET0). The results demonstrated that magnetized water irrigation slowed down the degradation rate of biodegradable film. In addition, the magnetized irrigation water can redistributed the soil water-salt patterns under the biodegradable film, improving the soil water content and salt leaching efficiency, with better results in M1 than in M2. Moreover, magnetized water irrigation promoted the growth of tomato leaf area under the biodegradable film, enhancing photochemical efficiency and potential activity of PSII, thereby improving fruit yield, quality, and water use efficiency of tomato. Principal component analysis showed that the comprehensive score of M1T3 treatment was the highest throughout the three years. Furthermore, M1T3 treatment has the highest processing tomato economic benefits during 2021–2023 (24634986 CNY hm2 more than MPET0). Therefore, the use of 3000 Gs magnetized irrigation water combined with black biodegradable film is conducive to improving soil water and salt conditions, reducing residual film pollution, and improving the yield and quality of processing tomatoes, thus ensuring the sustainable development of oasis agriculture.

The spatial gradients of protein and starch in wheat grains affected the grain milling characteristics and flour utilization. The increase in compound heat stress and drought stress (HDS) due to global climate change threatens wheat grain yield and quality parameters, but the impacts of extreme climate events on the gradients of protein and starch in wheat grains remain unclear. In this study, two-year, environment-controlled experiments with four heat stress levels (17/27, 21/31, 25/35, and 29/39°C) and three drought stress levels (30 %, 55 %, and 75 % field capacity) were conducted to investigate the effects of HDS on the gradients of protein and starch concentrations within the five grain layers. The results showed that HDS resulted in significantly greater protein concentrations, while resulting in lower starch concentrations in the wheat grain layers. Among the five layers, the endosperm layers exhibited the greatest increase in protein concentration under HDS, but the starch concentration under HDS decreased in the order of husk > aleurone > endosperm layer. HDS unevenly altered the protein and starch concentrations of the five grain layers. There was significant linear relationship between relative protein and starch concentration with accumulated heat degree days (AHDD). With a 1°C·d increase in AHDD, the protein concentration in the five grain layers increased by 1.17–2.19 %, while the starch concentration decreased by 0.62–0.90 %, depending on the drought stress levels. A significant linear relationship was also observed between the relative protein and starch concentrations and evapotranspiration (ET). A 1 mm increase in ET led to a protein concentration decrease of 0.58–0.76 % in P1-P5, with a corresponding starch concentration increase of 0.28–0.46 %, depending on cultivar and treatment stages. Our results indicate that HDS significantly impacts the grain quality parameters for the flour milling process and human diet and will provide important insights into adapting wheat quality to climate change.

The restoration of digital images holds practical significance due to the fact that degradation of digital image data on the internet is common. State-of-the-art image restoration methods usually employ end-to-end trained networks. However, we argue that a network trained with diverse image pairs is not optimal for restoring line drawings which have extensive plain backgrounds. We propose a line-drawing restoration framework which takes a restoration neural network as backbone and processes an input degraded line drawing in two steps. First, a proposed mask-predicting network predicts a line mask which indicates the possible location of foreground and background in the potential original line drawing. Next, we feed the degraded input line drawing together with the predicted line mask into the backbone restoration network. The traditional L1 loss for the backbone restoration network is substituted with a masked Mean Square Error (MSE) loss. We test our framework on two classical image restoration tasks: JPEG restoration and super-resolution, and experiments demonstrate that our framework can achieve better quantitative and visual results in most cases.

Avalanche photodiodes (APDs) produce noise during operation, which affects the device performance. However, the previous research on its noise is mainly theoretical analysis and is only reflected as optical noise. Therefore, according to the characteristics of APD material and the mechanism of noise generation, the main noise of the device is analyzed in this paper. First, the test method of noise in APDs is established, including testing of dark noise, optical noise, and multiplication noise in high frequency bands. The main noises in APDs are 1/f noise, thermal noise, shot noise, generation recombination noise, and multiplication shot noise, and shot noise is suppressed by Fermi–Dirac distribution and Coulomb action. Second, the reliability of APDs is evaluated by measuring and analyzing the noise parameters of the device through thermal aging experiments. It is concluded that the defects introduced by thermal aging can be reflected by the change in noise, which is consistent with the results in the literature. This method can comprehensively obtain the noise in APDs, which is helpful to improve the working efficiency, life, and reliability of the device.

The ultrasound-assisted extraction technique was used for extracting polysaccharides of Tricholoma matsutake (PTM) in this work. The effects of different parameters, i.e., solid-to-liquid ratio, ultrasonic power, extraction time, and extraction temperature on the PTM yield were optimized using a rotatable, orthogonal central composite design. In the derived optimal conditions, the PTM yield was 16.97 ± 0.06%, which corresponded well with the regression model predicted value of 16.85%. The extracted PTM was purified, and the structural characteristics and antioxidant activities were investigated. The PTM was found to be composed mainly of fructose, mannose, glucose, and galactose with a molar molecular ratio of 1:2.25:9.35:5, and an average molecular weight of 90,100 Da. High antioxidant effects of PTM were seen in the tests of DPPH, hydroxyl, and ABTS radical scavenging, along with a moderate superoxide radical scavenging rate.

The current work presents spatiotemporal analysis of areal windspeeds, using state-of-the-art Gaidai multivariate hazards evaluation approach. Environmental dynamic systems being challenging to forecast using existing reliability methods due to their high dimensionality and intricate nonlinear cross-correlations between different environmental system essential dimensions or components. Developing novel multivariate reliability methods for dynamic environmental systems may assist contemporary research on the global climate change effects. Multivariate Gaidai risks evaluation approach is especially well-suited for multi-dimensional structural and environmental dynamic systems, that have been monitored physically or numerically simulated across a representative time-lapse. The current study made use of raw in-situ windspeed data, collected by NOAA (i.e., National Oceanic and Atmospheric Administration) buoys near the Hawaiian Islands in the North Pacific. Resilient island communities/infrastructure can be designed, using advocated multivariate risk/hazard assessment methodology, particularly those that are close to the ocean and hence subject to extreme weather.As was demonstrated in this study, even given limited underlying dataset, it is feasible to conservatively estimate environmental system’s hazard risks. Novel non-parametric deconvolution extrapolation scheme has been utilized to accurately assess hazard risks.

This study investigates the prevalence and risk factors associated with venous thrombotic events in patients receiving (ECMO) support. Systematic review and meta-analysis of case-control and cohort studies. PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus, and ProQuest databases from inception through November 25, 2023.Case-control and cohort studies focusing on the prevalence and risk factors for venous thrombotic events in patients supported by ECMO. Identification of risk factors and calculation of incidence rates. Nineteen studies encompassing 10,767 participants were identified and included in the analysis. The pooled prevalence of venous thrombotic events among patients receiving ECMO support was 48% [95% confidence interval (CI) 0.37–0.60, I 2 = 97.18%]. Factors associated with increased incidence rates included longer duration of ECMO support (odds ratio [OR] 1.08, 95% CI 1.07-1.09, I 2 = 49%), abnormal anti-coagulation monitoring indicators (OR 1.02, 95% CI 1.00-1.04, I 2 = 84%), and type of ECMO cannulation (OR 1.77, 95% CI 1.14-3.34, I 2 = 64%). The pooled prevalence of venous thrombotic events in patients with ECMO support is high. Increased risk is associated with extended duration of ECMO support, abnormal anti-coagulation monitoring, and specific types of ECMO cannulation.