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Abstract Background Chronic kidney disease (CKD) is a global health challenge with diverse etiologies. However, research on the incidence trends of CKD attributable to specific causes remains limited, and the incidence and mortality rates vary across regions. This study aims to identify the patterns and temporal trends of CKD incidence, providing valuable information for the development of targeted prevention strategies and interventions. Methods CKD data from the 2021 Global Burden of Disease Study (1990–2021) were analyzed by sex, region, country, cause, and Socio-demographic Index (SDI). Disease burden was assessed using age-standardized incidence (ASIR), mortality rates (ASMR), and estimated annual percentage changes (EAPC). Decomposition analysis evaluated population aging, growth, and epidemiological impacts. The autoregressive integrated moving average (ARIMA) model was used to predict the burden of CKD from 2021 to 2031, and the age-period-cohort (APC) model was employed to assess the effects of age, time, and cohort. Health inequality was analyzed using Slope Index of Inequality (SII) and Concentration Index (CI). Results In 2021, Saudi Arabia had the highest ASIR, while Mauritius had the highest mortality. China and India contributed the most cases and deaths. ARIMA forecasts CKD cases will rise to 22.21 million and deaths to 1.81 million by 2031. Epidemiological changes drove incidence growth in medium SDI regions and mortality in high SDI regions. EAPC correlated with ASIR and ASMR. APC analysis showed incidence peaked between 70–80 years, with earlier cohorts facing higher risks. Unknown causes, type 2 diabetes, and hypertension were the leading CKD etiologies. From 1990–2021, health inequality in CKD incidence and mortality worsened, especially in high SDI regions, where the mortality CI shifted from 0.05 to − 0.09. Conclusions This study estimated the temporal trends of CKD incidence and mortality globally, as well as at the national and regional levels, from 1990 to 2021. It was observed that countries with higher socio-demographic index (SDI) exhibited unfavorable trends, suggesting that these countries should develop more targeted and specific strategies to address the growing burden of CKD.

Abstract Background Serum vitamin D deficiency is intricately linked to metabolic disorders, however, evidence on its association with continuous metabolic risk in children and adolescents remains insufficient. This study aims to elucidate the relationship between serum vitamin D levels and continuous metabolic risk. Methods The cross-sectional analysis involved 4490 participants aged 6 ~ 18, and the longitudinal investigation included 1398 individuals aged 6 ~ 12 years. Serum 25(OH)D concentrations were quantified using liquid chromatography-mass spectrometry. Continuous Metabolic syndrome risk score (CMSRS), incorporating waist, blood pressure, blood lipid levels, and glucose metabolism as four components, utilizes age- and gender-specific Z scores to evaluate metabolic risk. Restricted cubic splines (RCS) were used to visualize dose–response relationships and generalized linear models (GLM) were used to estimate potential associations. Mediation analysis was used to evaluate the mediating role of levels of Neutrophil-to-lymphocyte ratio (NLR). Results The RCS indicated a negative linear association between serum 25(OH)D levels and CMSRS (P-overall = 0.0066, P-nonlinear = 0.1393). GLM revealed that compared to Q1, with the quartiles of serum 25(OH)D concentrations increase, the β value ranged from 0.028 (95% CI: − 0.093, 0.037) to 0.001(95%CI: − 0.067, 0.069), and then to -0.074 (95%CI: -0.146, -0.003, P for trend = 0.0659). For every 10 ng/mL increase in serum 25(OH)D concentration corresponded to the β value change -0.058 (95%CI: -0.098, -0.017). This association was more pronounced in younger or overweight/obese individuals. Furthermore, in the longitudinal study, as the baseline quartile of serum 25(OH)D concentration increased, the estimated change of subsequent CMSRS indicated a decreasing trend, ranging from -0.085 (95%CI: -0.203, 0.032) to -0.166 (95%CI: − 0.285, − 0.046), and then to − 0.174 (95%CI: − 0.296, -0.053, P for trend = 0.0031). The mediating proportion of levels of NLR was 7.2%. Conclusions Higher serum 25(OH)D concentration is significantly associated with reduced CMSRS in children and adolescents, and adequate serum vitamin D levels play a prominent role in preventing long-term metabolic disorders, partly meditating by inflammation in peripheral blood.

Bio-asphalt has a great application prospect in the replacement of petroleum-based asphalt to pave and maintain asphalt pavement. However, the problems of flow-induced crystallization and phase separation caused by flow-induced crystallization had severely restricted its application. This paper describes the progress of research on preparation, property evaluation and phase separation mechanism of bio-asphalt. The advantages and disadvantages of preparation methods of bio-asphalt are states. The fundamental physical and rheological properties of bio-asphalt are investigated, especially for flow-induced crystallization. There exists obvious flow-induced crystallization because bio-asphalt is rich in waxes that crystallize easily. Owing to the existence of excess biochar, bio-asphalt appears phase separation. A brief review of the effect of bio-oil and biochar on asphalt volatile organic compounds (VOCs) is presented. Research find that bio-oil/biochar are not only replenish the light components of asphalt, but also improve the flow-induced crystallization and phase separation of bio-asphalt. There exists synergistic effect of biochar and bio-oil in asphalt modification. Moreover, biochar can improve the durability of bio-oil modified asphalt, but excessive addition of biochar to bio-oil modified asphalt can cause phase separation. Adding an appropriate amount of bio-oil and biochar to asphalt can improve its high-temperature resistance, low-temperature crack resistance, and system compatibility.

Abstract Chimp optimization algorithm (CHOA) is a recently developed nature-inspired technique that mimics the swarm intelligence of chimpanzee colonies. However, the original CHOA suffers from slow convergence and a tendency to reach local optima when dealing with multidimensional problems. To address these limitations, we propose TASR-CHOA, a twofold adaptive stochastic reinforced variant. The TASR-CHOA algorithm integrates two novel methodologies: a stochastic approach to improve the speed at which convergence is achieved and a dual adaptive weighting approach to optimize the exploration of early patterns, which refer to initial trends or behaviors in the algorithm’s convergence process during the early stages of iterations and the exploitation of subsequent tendencies, indicating how these initial trends develop over time as the algorithm iterates and refines its search. To evaluate TASR-CHOA, we apply it to 29 conventional optimization benchmark functions, 10 IEEE CEC-06 benchmarks, 30 complicated IEEE CEC-BC benchmark functions, and ten well-known benchmark real-world challenges. We evaluate TASR-CHOA against 4 categorical optimization techniques as well as 18 top IEEE CEC-BC algorithms. Based on our broad investigation done using three statistical tests, we claim that TASR-CHOA outperforms the majority of the algorithms since within a position takes the best place, 54 out of 73 evaluation functions and engineering problems. In other cases, the results are almost the same as those of SHADE and CMA-ES over several comparisons. As an illustrative application of this joint approach, a computer-aided fire detection task is performed using a deep convolutional neural network combined with TASR-CHOA. We also outline the algorithm executed in steps, indicating computational complexity, which is O(NI×NV) + O(NI×NV×6) + O(NI×NV + 2×NI×NV) as a function of number of individuals (NI) and dimensions (NV).

Transjugular intrahepatic portosystemic shunt (TIPS) is an essential procedure for the treatment of portal hypertension but can result in hepatic encephalopathy (HE), a serious complication that worsens patient outcomes. Investigating predictors of HE after TIPS is essential to improve prognosis. This review analyzes risk factors and compares predictive models, weighing traditional scores such as Child-Pugh, Model for End-Stage Liver Disease (MELD), and albumin-bilirubin (ALBI) against emerging artificial intelligence (AI) techniques. While traditional scores provide initial insights into HE risk, they have limitations in dealing with clinical complexity. Advances in machine learning (ML), particularly when integrated with imaging and clinical data, offer refined assessments. These innovations suggest the potential for AI to significantly improve the prediction of post-TIPS HE. The study provides clinicians with a comprehensive overview of current prediction methods, while advocating for the integration of AI to increase the accuracy of post-TIPS HE assessments. By harnessing the power of AI, clinicians can better manage the risks associated with TIPS and tailor interventions to individual patient needs. Future research should therefore prioritize the development of advanced AI frameworks that can assimilate diverse data streams to support clinical decision-making. The goal is not only to more accurately predict HE, but also to improve overall patient care and quality of life.

As urbanization accelerates and buildings become more complex, fire emergency evacuation has become increasingly challenging. Traditional evacuation plans often struggle with slow response times and suboptimal path planning in real-time dynamic and complex fire scenarios. To address these issues, this study proposes the IoT-based DWM-Evac model for fire emergency evacuation path planning. The model leverages IoT technology by using various sensors placed inside buildings to monitor fire incidents and spread in real-time, collecting critical data such as temperature, smoke concentration, and flame location. It integrates Dynamic Graph Neural Networks (DGNN), Whale Optimization Algorithm (WOA), and Markov Decision Process (MDP) to enhance path efficiency and safety. Experimental results indicate that the DWM-Evac model achieves an average evacuation time of 315 s in a virtual mall environment, 25 s shorter than traditional plans, with an average path length of 255 meters and a path safety score of 0.92, higher than the traditional plan’s 0.88. The application of IoT in fire emergency management not only improves response speed but also optimizes path planning, significantly enhancing personnel safety.

The dual frequency Heterogeneous Network (HetNet), including sub-6 GHz networks together with Millimeter Wave (mmWave), achieves the high data rates of user in the networks with hotspots. The cache-enabled HetNets with hotspots are investigated using an analytical framework in which Macro Base Stations (MBSs) and hotspot centers are treated as two independent homogeneous Poisson Point Processes (PPPs), and locations of Small Base Stations (SBSs) and users are modeled as two Poisson Cluster Processes (PCPs). Under the PCP-based modeling method and the Most Popular Caching (MPC) scheme, we propose a cache-enabled association strategy for HetNets with limited storage capacity. The performance of association probability and coverage probability is explicitly derived, and Monte Carlo simulation is utilized to verify that the results are correct. The outcomes of the simulation present the influence of antenna configuration and cache capacities of MBSs and SBSs on network performance. Numerical optimization of the standard deviation ratio of SBSs and users of association probability is enabled by our analysis.

BackgroundThe emergence of new SARS-CoV-2 variants, the resulting reinfections, and post–COVID-19 condition continue to impact many people’s lives. Tracking websites like the one at Johns Hopkins University no longer report the daily confirmed cases, posing challenges to accurately determine the true extent of infections. Many COVID-19 cases with mild symptoms are self-assessed at home and reported on social media, which provides an opportunity to monitor and understand the progression and evolving trends of the disease. ObjectiveWe aim to build a publicly available database of COVID-19–related tweets and extracted information about symptoms and recovery cycles from self-reported tweets. We have presented the results of our analysis of infection, reinfection, recovery, and long-term effects of COVID-19 on a visualization website that refreshes data on a weekly basis. MethodsWe used Twitter (subsequently rebranded as X) to collect COVID-19–related data, from which 9 native English-speaking annotators annotated a training dataset of COVID-19–positive self-reporters. We then used large language models to identify positive self-reporters from other unannotated tweets. We used the Hibert transform to calculate the lead of the prediction curve ahead of the reported curve. Finally, we presented our findings on symptoms, recovery, reinfections, and long-term effects of COVID-19 on the Covlab website. ResultsWe collected 7.3 million tweets related to COVID-19 between January 1, 2020, and April 1, 2024, including 262,278 self-reported cases. The predicted number of infection cases by our model is 7.63 days ahead of the official report. In addition to common symptoms, we identified some symptoms that were not included in the list from the US Centers for Disease Control and Prevention, such as lethargy and hallucinations. Repeat infections were commonly occurring, with rates of second and third infections at 7.49% (19,644/262,278) and 1.37% (3593/262,278), respectively, whereas 0.45% (1180/262,278) also reported that they had been infected >5 times. We identified 723 individuals who shared detailed recovery experiences through tweets, indicating a substantially reduction in recovery time over the years. Specifically, the average recovery period decreased from around 30 days in 2020 to approximately 12 days in 2023. In addition, geographic information collected from confirmed individuals indicates that the temporal patterns of confirmed cases in states such as California and Texas closely mirror the overall trajectory observed across the United States. ConclusionsAlthough with some biases and limitations, self-reported tweet data serves as a valuable complement to clinical data, especially in the postpandemic era dominated by mild cases. Our web-based analytic platform can play a significant role in continuously tracking COVID-19, finding new uncommon symptoms, detecting and monitoring the manifestation of long-term effects, and providing necessary insights to the public and decision-makers.

BackgroundThe increased risks for cardiovascular comorbidities and cardiovascular diseases (CVD) in populations with normal weight obesity (NWO) have not been well-identified. We aimed to study their associations in an adult population in South China.MethodsBased on the CVD prevalence of 4% in Shenzhen and a calculated sample size of 6,000, a cross-sectional study with a multi-stage stratified cluster sampling method was conducted in Shenzhen City. The cardiovascular comorbidities being studied were abdominal obesity (AO), diabetes, hypertension, dyslipidemia, metabolic syndrome, and chronic kidney disease, while the CVD events were occurrences of myocardial infarction and strokes. Questionnaire surveys, physical examinations, and laboratory tests were performed. NWO was defined as a condition with the highest tertile of body fat percentage (BF%) among the normal body mass index (BMI) range (18.5-23.9 kg/m2). Continuous data were reported as mean [standard deviation (SD)] and categorical data as percentages (%). CVD comorbidities and CVD events and their detection rates in different groups were compared using ANONA analysis and Chi-squared test. Spearman's correlation coefficients between BF% and cardiometabolic abnormalities were calculated by partial correlation analysis. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for BF%, CVD comorbidities, and CVD events, adjusted for multiple confounders.ResultsAmong the total 6,240 subjects who completed the study and had BMI and BF% data available, 3,086 had normal BMI. The prevalence of NWO was 16.36%, with 13.15% for men and 19.54% for women. With confounders adjusted, the risks of AO (OR = 6.05, 95%CI = 3.40-10.75), essential hypertension (OR = 1.56, 95%CI = 1.09-2.22), dyslipidemia (OR = 1.85, 95%CI = 1.49-2.29), and metabolic syndrome (OR = 4.61, 95%CI = 2.32-9.18) were significantly increased in the populations with NWO compared with the population without NWO (P < 0.05). BF% was not significantly associated with the risk of CVD events in the total (OR = 1.56, 95%CI = 0.83-2.93), male (OR = 1.00, 95%CI = 0.44-2.30), and female populations (OR = 2.53, 95%CI = 0.91-7.06).ConclusionNWO was found to be positively associated with CVD comorbidities but not with CVD events. The current study provides a ground to conduct further studies on whether body fat affects the risk of occurrence of CVD events and the underlying mechanisms in the future.

This study explored whether and how prohexadione calcium (Pro-Ca) regulated wheat tolerance to drought stress (DS). Findings displayed that DS had significant influence on antioxidant metabolism, water balance and the photosynthesis. DS significantly improved the activity level of enzymatic antioxidants superoxide dismutase (SOD), catalase (CAT), peroxidase (POD) and ascorbate peroxidase (APX), the contents of non-enzymatic antioxidants ascorbic acid (AsA) and glutathione (GSH), electrolyte leakage (EL), malondialdehyde (MDA), and the contents of osmotic regulatory substances soluble protein (SP), soluble sugars (SS) and proline (Pro), compared with control. Whereas DS significantly reduced transpiration rate (Tr), stomatal conductance (gs) and relative water content (RWC), photosynthetic pigments chlorophyll and carotenoid contents, net photosynthetic rate (Pn), maximum photochemical efficiency of PSII (Fv/Fm), plant height and biomass. Compared to DS, Pro-Ca plus DS significantly promoted the antioxidant metabolism by improving the activity level of SOD, CAT, POD and APX and increasing AsA and GSH contents, which in turn reduced MDA content and EL. In addition, Pro-Ca plus DS significantly maintained water balance by promoting the accumulation of osmolytes SP, SS and Pro, which in turn increased RWC, Tr and gs. Pro-Ca plus DS also significantly promoted photosynthesis by increasing the contents of the above photosynthetic pigments, Pn and Fv/Fm, thereby promoting plant growth. These findings indicated that Pro-Ca was a potential agent to improve wheat tolerance under water deficit.

Thamnaconus septentrionali has excellent breeding characteristics, is omnivorous, easy to domesticate, is especially suitable for netting, cleans the netting, and effectively reduces labor-costs. T. septentrionali is available in various sizes and is raised in the market at 100 g. Under water temperature of 18–25 ℃, after 5–6 months of breeding, it reaches commercial size. As the Yellow Sea and Bohai Sea are cold in winter, a suitable breeding cycle for green fins is from May to November annually. Under natural conditions, the spawning period of T. septentrionali in the Yellow Sea and Bohai Sea is from early May to early June, making good use of the suitable breeding cycle of net box culture. Therefore, reproductive regulation is required to advance the reproductive period of T. septentrionali. Previous studies have primarily focused on the expression and functional analysis of individual genes. In contrast, no studies exist on the overall expression analysis of gonad-related genes based on histology. Herein, we conducted the first transcriptome sequencing analysis of the spermatophores and ovaries of T. septentrionali using an Illumina high-throughput sequencing platform. Overall, 165, 981, 523 raw reads were sequenced from the cDNA, and 161, 234, 846 clean reads were obtained after quality control. The Q20 of each sample was > 98.43%, Q30 was > 95.25%, and GC content of the sample bases was greater than 52.31%. Our findings indicate that the sequencing data are accurate, of good quality, and were used for subsequent analyses. The obtained unigenes were annotated in the NR (NCBI non-redundant protein sequences), NT (NCBI nucleotide sequences), PFAM (protein family), KOG (euKaryotic Ortholog Groups), SwissProt (a manually annotated and reviewed protein sequence database), GO (Gene Ontology), and KO (KEGG Orthology) databases, and 24, 009, 35, 057, 18, 453, 26, 971, 30, 294, 11, 420, and 21, 613 unigenes were annotated, respectively. The KEGG annotation results were divided into five major categories: organic systems, with 2, 115 genes in nine pathways; metabolism, with 1, 444 genes in 12 pathways; environmental information processing, with 1, 200 genes in three pathways; and genetic information processing, with 1, 128 genes in four pathways. Environmental information processing (1, 200 genes in three pathways), genetic information processing (1, 128 genes in four pathways), and cellular processes (1, 128 genes in four pathways). The number of genes enriched in cellular process-related pathways was 927 distributed in four related pathways. The signal transduction pathway was the most annotated KEGG pathway with 804 genes. The experiment used 24, 546 unigenes annotated in the KOG database, which were then classified into 26 categories based on their function. The largest number of unigenes were annotated in the signal transduction mechanism category (5, 411), followed by the general function prediction-only category (4, 252 unigenes), and posttranslational modification, protein folding and chaperone category (1, 713 unigenes). Unigene posttranslational modification, protein turnover, chaperones; transcription, 1, 613; and other related functions. There were 18, 954 differentially expressed genes (DEGs) in the spermatophore and ovary transcriptomes of the T. septentrionali, with 11, 265 genes up-regulated and 7, 689 down-regulated in the ovary relative to the spermatophore. The GO functional enrichment analysis revealed that DEGs were most enriched in the cellular component of biological processes, intracellular component of the cellular component subclass, and nucleic acid binding of the molecular functional subclass. GO analysis of the DEGs in males and females provided a partial list of genes associated with the reproductive process (GO: 0022414), sexual reproduction (GO: 0019953), gamete formation (GO: 0007276,), sex differentiation (GO: 0007548), and gonad development (GO: 00084060). To further characterize the specific functions of the DEGs in the spermatophores and ovaries of T. septentrionali, the enriched signaling pathways were further analyzed using the KEGG database. In total, 154 KEGG pathways were included, of which the top 30 were selected. The functional pathways with the highest number of expressed genes were closely associated with gonadal sex differentiation and development, including the insulin signaling pathway, steroid hormone biosynthesis, FoxO signaling pathway, M-TOR signaling pathway, and progesterone-mediated oocyte maturation. Among these, the FoxO signaling pathway regulatory genes are expressed in multiple processes, such as cell cycle control, apoptosis, and gluconeogenesis. The insulin signaling pathway plays an important role in regulating developmental, metabolic, and lifespan physiological processes, and the insulin signaling pathway is involved in gonadal development and maturation. Nine DEGs, bmp2, sox3, figla, hsd17b1, cyp19a, cyp17, foxl2, star, and amh, were selected for real-time fluorescence quantitative PCR (qRT-PCR) validation. The qPCR results were consistent with those of RNA-seq analysis. GO and KEGG enrichment results were analyzed and revealed that amh, cyp17, and star are imperative in male spermatogenesis of T. septentrionali; bmp2, foxl2, cyp19a, figla, and hsd17b1 are essential in female oogenesis and ovarian steroidogenesis. By comparing the transcriptome expression differences between the spermatophore and ovary of T. septentrionali, we elucidated the gene expression characteristics of the spermatophore and ovary, laying the foundation for future research on the mechanism of reproductive development of T. septentrionali and providing theoretical support for optimizing reproductive regulation techniques.

Fish skin is a multipurpose tissue with important functions—protection, perception, and hormone metabolism—in the fish body. As a byproduct of fish processing, it can be used as a material for extracting collagen, making leather, and related pathological research. However, there have been few reports on the tissue structure of fish skin. This study aimed to analyze the structural characteristics of Thamnaconus septentrionalis fish skin in order to provide a reference for the utilization of its resources. Six T. septentrionalis samples were selected and their skins were observed using frozen sectioning, skeletal, hematoxylin & eosin (H & E), Periodic acid-Schiff (PAS), Masson, Van Gieson (VG) staining, and scanning electron microscopy. The images obtained by slice scanning were analyzed using SlideViewer (3DHISTECH), ImageJ, and Photoshop software. The SEM images were analyzed using ImageJ and Photoshop software. SPSS25.0 software was used to analyze the data of epidermal and squamous layers, conical bone bulge, basal layer, and dermis thicknesses. The results showed that the histological structure of the skin comprised four parts: epidermis, scale layer, dermis, and subcutaneous tissue. The thickness of the epidermal layer was (26.81±7.48) μm. This layer was mainly composed of epithelial and basal cells but also contained a large number of mucus cells. The scale layer consisted of the spine of conical bone and a substrate. The thickness of this layer was (22.49±5.19) μm, and there were two to four rows of the spine of conical bone with different diameters, different bending degrees at the top, and a height of (257.13±10.41) μm unevenly distributed on the base plate. The average thickness of the dermis was (176.97±21.11) μm, and the dermis thickness of the head was lower than that of the middle part of the body, but higher than that of the tail, mainly composed of collagen fiber. The subcutaneous tissue layer was mainly comprised of collagen fibers and non-fibrous stroma. In this study, the histological pattern of the skin of T. septentrionalis was mapped according to its characteristics, providing valuable information for fish skin resource usage.

Abstract Objective The family physician team has become the core carrier for delivery primary health care in China. This study aimed to measure the effect of the network structural characteristics of family physician team processes on health performance. Strategic recommendations for optimizing the family physician team processes with a view to improving performance were presented. Methods A cross-sectional survey was conducted from October to December 2021 in Qianjiang in Hubei Province and Changsha in Hunan Province. Task performance, contextual performance, social networks, and sociodemographic characteristics were collected. Social network analysis was conducted to calculate density and centralization, then hierarchical linear regression analysis was employed to explore the relationship between the network structural characteristics of family physician team processes and performance. Results In total, 88 family physician teams attended in this investigation. The transition processes of family physician team showed a distinctive low density (0.272 ± 0.112), high centralization (0.866 ± 0.197) network structure. For family physician team, the density of action processes significantly and positively affected task performance (B = 0.600, P

Abstract Background With orthopedic surgery increasing year on year, the main challenges in bone drilling are thermal damage, mechanical damage, and drill skid. The need for new orthopedic drills that improve the quality of surgery is becoming more and more urgent. Methods Here, we report the skidding mechanism of drills at a wide range of inclination angle and propose two crescent drills (CDTI and CDTII). The anti-skid performance and drilling damage of the crescent drills were analyzed for the first time. Inclined bone drilling experiments were carried out with crescent drills and twist drills and real-time drilling forces and temperatures were collected. Results The crescent drills are significantly better than the twist drill in terms of anti-skid, reducing skidding forces, thrust forces and temperature. The highest temperature is generated close to the upper surface of the workpiece rather than at the hole exit. Finally, the longer crescent edge with a small and negative polar angle increases the rake angle of the cutting edge and reduces thrust forces but increases skidding force and temperature. This study can promote the development of high-quality orthopedic surgery and the development of new bone drilling tools. Conclusion The crescent drills did not skid and caused little drilling damage. In comparison, the CDTI performs better in reducing the skidding force, while the CDTII performs better in reducing the thrust force.

BACKGROUND: Diabetic retinopathy (DR) is one of the serious complications of diabetes mellitus (DM). Many studies have identified the risk factors associated with DR, but there is not much evidence on the importance of these factors for DR. This study aimed to investigate the associated factors for patients with type 2 DM (T2DM) and calculate the importance of the identified factors. MATERIALS AND METHODS: Using probability proportionate to size sampling method in this community-based cross-sectional study, 22 community health service centers were selected from 10 administrative districts in Shenzhen, China. Approximately 60 T2DM patients were recruited from each center. The participants completed a structural questionnaire, had their venous blood collected, and underwent medical examinations and fundus photography. Logistic regression models were used to identify the risk factors of DR. The classification and regression tree (CART) model was used to calculate the importance of the identified risk factors. RESULTS: This study recruited 1097 T2DM patients, 266 of whom were identified as having DR, yielding a prevalence rate of 24.3% (95% confidence interval [CI]: 21.7%–26.9%). Results showed that a longer duration of DM, indoor-type lifestyle, and higher levels of hemoglobin A1c (HbA1c) or urea increased the risk of DR. Patients with HbA1c values ≥7% were about 2.45 times (odds ratio: 2.45; 95% CI: 1.83–3.29) more likely to have DR than their counterparts. The CART model found that the values of variable importance for HbA1c, DM duration, lifestyle (i.e., indoor type), and urea were 48%, 37%, 10%, and 4%, respectively. CONCLUSION: The prevalence of DR is high for T2DM patients who receive DM health management services from the primary healthcare system. HbA1c is the most important risk factor for DR. Integration of DR screening and HbA1c testing into the healthcare services for T2DM to reduce vision impairment and blindness is urgently warranted.

BackgroundPregnancy, a transformative phase, is often fraught with considerable psychological stress. Within the context of Chinese culture, characterized by intricate family dynamics, societal expectations, and deeply rooted traditional beliefs, the manifestation of stress during pregnancy may present with distinct nuances. The adaptation and validation of the Perceived Stress Scale (PSS-10) for the Chinese context are pivotal for a nuanced understanding and effective intervention for the stressors encountered by pregnant women in China.MethodsThis study enrolled a cohort of 990 pregnant women who completed both the PSS-10 and the Chinese Mental Health Scale (CMHS). The internal consistency reliability was assessed using Cronbach’s α and McDonald’s omega. The construct validity was explored through Exploratory Factor Analysis (EFA), while Confirmatory Factor Analysis (CFA) was utilized to validate the scale’s structural integrity. Criterion-related validity was established by correlating PSS-10 scores with CMHS scores, thereby assessing the scale’s convergent and discriminant validity.ResultsThe result demonstrated PSS-10 had robust internal consistency, with Cronbach’s α coefficients and McDonald’s omega (Composite reliability) were more than 0.70 for the scale and its constituent sub-factors. EFA and parallel analysis revealed two salient factors with eigenvalues surpassing 1.0, which accounted for 60.58% and 63.22% of the variance among the second and third trimester samples, respectively. The CFA confirmed the two-factor model’s congruence with the PSS-10’s structure in both sub-samples, with excellent model fit indicated by the fit indices: Standardized Root Mean Residual (SRMR) below 0.08 and both Comparative Fit Index (CFI) and Goodness of Fit Index (GFI) above 0.90. Additionally, the correlation analysis with CMHS scores substantiated the PSS-10’s concurrent validity.ConclusionThe PSS-10 exhibits commendable psychometric properties, rendering it a pertinent and reliable instrument for assessing perceived stress among pregnant women in China. This validation underscores the PSS-10’s utility in psychological research and clinical practice pertaining to Chinese pregnant populations.

Introduction Stimulating acupoints is beneficial for improving heart health but the clinical efficacy of transcutaneous electrical acupoint stimulation (TEAS) as a complementary therapy for chronic coronary syndromes (CCSs) remains unclear. This study aims to evaluate whether TEAS can alleviate angina severity in patients with CCS and to explore the potential mechanisms underlying TEAS.Methods and analysis This study, conducted across two clinical centres, involved 90 participants distributed equally into three groups via simple randomisation (1:1:1 ratio). The research cycle was 28 weeks including a 4-week baseline, 12-week treatment and 12-week follow-up period. All groups will receive basic treatment with the TEAS group additionally receiving 36 sessions of TEAS stimulation over the 12 weeks. The two control groups will either undergo sham TEAS or no additional intervention alongside their basic treatment. The primary outcome is the 6-minute walk test; eight other indicators will serve as secondary outcomes.Ethics and dissemination Approval for this study was granted by the Medical Research Ethics Committee of the Third Clinical Affiliated Hospital of Changchun University of Chinese Medicine in May 2023. Findings will be disseminated through peer-reviewed publications.Trial registration number ChiCTR2400079383.

Photosynthetic bacteria (PSB) has shown significant potential as a drug or drug delivery system owing to their photothermal capabilities and antioxidant properties. Nevertheless, the actualization of their potential is impeded by inherent constraints, including their considerable size, heightened immunogenicity and compromised biosafety. Conquering these obstacles and pursuing more effective solutions remains a top priority. Similar to extracellular vesicles, bacterial outer membrane vesicles (OMVs) have demonstrated a great potential in biomedical applications. OMVs from PSB encapsulate a rich array of bioactive constituents, including proteins, nucleic acids, and lipids inherited from their parent cells. Consequently, they emerge as a promising and practical alternative. Unfortunately, OMVs have suffered from low yield and inconsistent particle sizes. In response, bacteria-derived nanovesicles (BNVs), created through controlled extrusion, adeptly overcome the challenges associated with OMVs. However, the differences, both in composition and subsequent biological effects, between OMVs and BNVs remain enigmatic. In a groundbreaking endeavor, our study meticulously cultivates PSB-derived OMVs and BNVs, dissecting their nuances. Despite minimal differences in morphology and size between PSB-derived OMVs and BNVs, the latter contains a higher concentration of active ingredients and metabolites. Particularly noteworthy is the elevated levels of lysophosphatidylcholine (LPC) found in BNVs, known for its ability to enhance cell proliferation and initiate downstream signaling pathways that promote angiogenesis and epithelialization. Importantly, our results indicate that BNVs can accelerate wound closure more effectively by orchestrating a harmonious balance of cell proliferation and migration within NIH-3T3 cells, while also activating the EGFR/AKT/PI3K pathway. In contrast, OMVs have a pronounced aptitude in anti-cancer efforts, driving macrophages toward the M1 phenotype and promoting the release of inflammatory cytokines. Thus, our findings not only provide a promising methodological framework but also establish a definitive criterion for discerning the optimal application of OMVs and BNVs in addressing a wide range of medical conditions.

In order to verify the effect of emulsifiers on the digestion of whole nutrient emulsion in vitro, three whole nutrient emulsions respectively containing octenyl succinic acid starch (OS), Zein, and phospholipids (PL) were prepared through shear and high-pressure homogenization. The pH-stat method was used to simulate the in vitro digestion process of whole nutrient emulsion, and the effects of OS, Zein Pickering emulsifier and PL traditional emulsifier on the digestion characteristics of whole nutrient emulsion were studied. The particle size distribution, zeta potential, microstructure, and lipid digestibility of whole nutrient emulsion during digestion were measured. The results showed that during the simulated digestion process, the particle sizes of the three emulsions showed a trend of first increasing and then decreasing, and the absolute values of zeta potential showed a trend of first decreasing and then increasing. After digestion, the potential values of OS emulsion, Zein emulsion, and PL emulsion were −14.53, −19.90, and −18.80 mV, respectively. The oil drops of Zein emulsion were most hydrolyzed by lipase and the final free fatty acid release rates of Zein emulsion, OS emulsion, and PL emulsion were 20.54%, 17.21%, and 14.29%, respectively. Pickering whole nutrient emulsion had a higher in vitro lipid digestion rate than traditional whole nutrient emulsion, which was conducive to the digestion and absorption of whole nutrient emulsion lipids and helped to improve the bioavailability of lipid soluble bioactive components in emulsion.

The morphological characteristics, ecological habits, and physiological structures of fish vary rapidly in the early growth and development stage. Understanding the changes in the postembryonic early development morphology of organs or tissues could provide basic information for the classification or identification of fish and the investigation or utilization of early resources. Morphological characteristic observation is one of the most commonly used methods. The existing studies on the early development of a certain trait in the late larval and juvenile stage are unclear. Most of the digital images are side views, resulting in a lack of dorsal views, ventral views, or local images, which is not conducive to the understanding of larval and juvenile. In this study, the variations in observable, measurable, and countable traits in postembryonic early development of Thamnaconus septentrionalis were explored using optical microscopy and stereomicroscopy. The observable traits included the developmental changes of yolk sac, scales, and notochord curvature. The measurable traits included the growth changes of total length, body length, body height, and oral fissure. The countable characters included the number of fins in the second dorsal fin, anal fin, caudal fin, and the number of pterygiophore. The results showed that at (23.0±1.0) ℃, the newly hatched larvae moved up and down in the water, with a phenomenon of convergent clustering under light irradiation; the pectoral fin appeared at 1 d, and the heart rate was approximately 50 beats/min; the optic capsule was completely black, the maxillar appeared, the oral fissure extended below the eyes, the yolk sac disappeared, and the first dorsal fin base appeared at 4 d; the girdle was single and colorless and began from the front edge of the belly, the oil globule disappeared, and the pelvic fin base appeared at 7 d; the first dorsal fin base and pelvic fin base broke membrane at 8 d; the first dorsal fin and pelvic fin were significantly longer than before, transparent rounded scales were observed at 9 d; swimming ability was improved, indicated by hovering back and forth gnawing pool wall, transversally conical barbs appeared at the base of the first dorsal fin at 11 d; the swim bladder and postcleithrum on both sides of the belly were clearly visible at 12 d; the second dorsal fin and anal fin pterygiophore appeared at 14 d, the second dorsal fin pterygiophore spans seven sarcomeres and the anal fin pterygiophore spans six sarcomeres. There are 10~12 melanin masses in the second dorsal fin and 5~6 in the anal fin, the conical teeth appeared on the upper and lower jaws at 16 d; the second dorsal fin and anal fin were differentiated at 19 d; the swim bladder fills about 25% of the abdominal cavity; notochord curves upward clearly and the stalk of caudal fin came out at 20 d; the fin strips of the second dorsal fin, anal fin, and caudal fin were well-developed at 24 d; the open mouth was round and changed from swallowing to sucking at 30 d, and the rainbow cells were colorful and the body surface near the gill was the most dense; the abdominal cavity has a strong metallic texture, the hard spine of the pelvic fin was degraded, close to the girdle at 39 d; 4~5 black bands were arranged regularly on the body, and the lateral line was consistent with the vertebral column at 50 d. The R2 values of the curve equations of measurable traits were all greater than 0.90. The height of the first dorsal fin increased exponentially 4~30 d. The visual sac increased linearly from 0~11 d to 11~20 d, and the increment of 0~11 d was less than that of 11~20 d, while the increment of 21~30 d was exponential. The oral fissure in 4~13 d and 22~30 d increased linearly, while that in 13~22 d decreased linearly. The total length, body length, and body height increased linearly before the inflection point and exponentially after the inflection point, which was concentrated in 19~23 d. The number of fin pterygiophore of the second dorsal fin was 31~36, while that in the anal fin was 33~35. The number of pectoral fins and caudal fins were 15~18 and 12, respectively. In conclusion, metamorphosis occurs in the postembryonic early development of T. septentrionalis, showing an allometric growth pattern, with a slow linear growth in the rotifer-feeding stage and a fast exponential growth in the artemia-feeding stage. The changes in the first dorsal fin and pelvic fin were correlated with age in days. The changes in the second dorsal and anal fins were correlated with the total length. This study enriches the early biological theory of T. septentrionalis and provides basic data for the investigation or utilization of its seedling breeding and resources. The partial enlarged detail is helpful for scholars to further understand the larval or juvenile fish and perform deep research.

Abstract Optical switches are desired in telecom and datacom as an upgrade to electrical ones for lower power consumption and expenses while improving bandwidth and network transparency. Compact, integrated optical switches are attractive thanks to their scalability, readiness for mass production, and robustness against mechanical disturbances. The basic unit relies mostly on a microring resonator or a Mach–Zehnder interferometer for binary “bar” and “cross” switching. Such single-mode structures are often wavelength / polarization dependent, sensitive to phase errors and loss-prone. Furthermore, when they are cascaded to a network, the number of control units grows quickly with the port count, causing high complexity in electronic wiring and drive circuit integration. Herein, we propose a new switching method by thermo-optic waveguide lens. Essentially, this multimode waveguide forms a square law medium by a pair of heater electrodes and focuses light within a chip by robust 1 × 1 imaging. A 1 × 24 basic switch is demonstrated with 32 electrodes and only two are biased at a time for a chosen output. By two-level cascading, the switch expands to 576 ports and only four electrodes are needed for one path. The chips are fabricated on wafer scale in a low-budget laboratory without resorting to foundries. Yet, the performance goes beyond state of the art for low insertion loss, low wavelength dependence and low polarization dependence. This work provides an original, alternative, and practical route to construct large-scale optical switches, enabling broad applications in telecom, datacom and photonic computing.

As the proportion of renewable energy sources integrated into the power grid increases, it imposes significant volatility on the grid, leading to uneven load distribution across certain transmission lines. Rotating Power Flow Controllers (RPFCs) based on Rotating Phase-Shifting Transformers (RPSTs) offer a viable solution to such issues in lines rated at 10 kV and below. This paper begins with a brief introduction to RPFCs, followed by the modeling of their topology for a single-circuit line and the derivation of active and reactive power flow formulas. Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. Using Matlab/Simulink simulations, this strategy was compared with adaptive adjustment strategies, verifying that it exhibits reduced power fluctuations and overshoots during the adjustment process, thus confirming the effectiveness of the adjustment scheme. By leveraging this algorithm in conjunction with simulations, a Q-P operating range diagram for transmission lines was plotted, determining the adjustable range of actual power.

Rainfall is of vital importance to terrestrial ecosystems and its intermittent characteristics have a profound impact on plant growth, soil biogeochemical cycles, and water resource management. Rainfall frequency, one of the key statistics of rainfall intermittency, has received relatively little research attention. Leveraging scale-dependent relationships in rainfall frequencies and using various global precipitation datasets, we found most grid-scale rainfall frequencies are relatively large and do not converge to the field-scale frequencies as grid size decreases. Specifically, these differences are as high as 41.8% for the Global Precipitation Climatology Project (GPCP) and 74.8% for the fifth-generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5), which are much larger than the differences in mean rainfall rates but can be partially corrected by redefining wet days with higher rainfall thresholds. These differences across most regions of the world should be interpreted as the inherent biases associated with the model structure or algorithms used for deriving precipitation data and cannot be reduced simply by increasing the data resolutions. Such biases could propagate into the hydrological process and influence the calibration of the rainfall-runoff process, one of the key nonlinear relationships in land surface modeling. We, therefore, call for urgent research into this topic to avoid misunderstandings of rainfall intermittency and ensure its proper application in various fields.

Introduction: Current anti-rheumatic drugs are primarily modulating immune cell activation, yet their effectiveness remained suboptimal. Therefore, novel therapeutics targeting alternative mechanisms, such as synovial activation, is urgently needed. Objectives: To explore the role of Midline-1 (Mid1) in synovial activation. Methods: NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were used to establish a subcutaneous xenograft model. Wild-type C57BL/6, Mid1-/-, Dpp4-/-, and Mid1-/- Dpp4-/- mice were used to establish a collagen-induced arthritis model. Cell viability, cell cycle, qPCR and western blotting analysis were used to detect MH7A proliferation, dipeptidyl peptidase-4 (DPP4) and Mid1 levels. Co-immunoprecipitation and proteomic analysis identified the candidate protein of Mid1 substrates. Ubiquitination assays were used to determine DPP4 ubiquitination status. Results: An increase in Mid1, an E3 ubiquitin ligase, was observed in human RA synovial tissue by GEO dataset analysis, and this elevation was confirmed in a collagen-induced mouse arthritis model. Notably, deletion of Mid1 in a collagen-induced arthritis model completely protected mice from developing arthritis. Subsequent overexpression and knockdown experiments on MH7A, a human synoviocyte cell line, unveiled a previously unrecognized role of Mid1 in synoviocyte proliferation and migration, the key aspects of synovial activation. Co-immunoprecipitation and proteomic analysis identified DPP4 as the most significant candidate of Mid1 substrates. Mechanistically, Mid1 promoted synoviocyte proliferation and migration by inducing ubiquitin-mediated proteasomal degradation of DPP4. DPP4 deficiency led to increased proliferation, migration, and inflammatory cytokine production in MH7A, while reconstitution of DPP4 significantly abolished Mid1-induced augmentation of cell proliferation and activation. Additionally, double knockout model showed that DPP4 deficiency abolished the protective effect of Mid1 defect on arthritis. Conclusion: Overall, our findings suggest that the ubiquitination of DPP4 by Mid1 promotes synovial cell proliferation and invasion, exacerbating synovitis in RA. These results reveal a novel mechanism that controls synovial activation, positioning Mid1 as a promising target for therapeutic intervention in RA.

This research aims to quantify the spatial pattern of urban land use/land cover (LULC) change while considering environmental effects. This paper integrates historical Landsat imagery, The Environment for Visualizing Images (ENVI), geographical information system (GIS), and socioeconomic data to determine the spatial–temporal urban LULC dynamics and the conversion of LULC in response to the rapid urbanization from 1992 to 2022. Principle component analysis and multiple linear regression are used to determine and model the relationship between the socioeconomic factors and the changes for identifying the driving forces. The results indicate that impervious surfaces have exponentially increased, expanding more than two times from 2,348 to 4,795 km2, in contrast to bare lands, which drastically declined by 95%, from 1,888 to 87 km2. Water bodies have always been relatively fewer, at approximately 100 km2. In addition, the majority of farmland in Jinan City is concentrated in the northern region with a steady area in the range of 2,100–2,900 km2, while the majority of woodland located in the southern region declined from 3,774.52 km2 (37%) to 3,088.28 km2 (30%). Economic development, population growth, and climate change are the primary factors that have an obvious impact on LULC changes. HIGHLIGHTS This paper integrates remote sensing images, ENVI, geographical information system, and socioeconomic data to determine the spatial–temporal urban land use/land cover.; Principle component analysis and multiple linear regression are used to determine the relationship between the socioeconomic factors and the changes for identifying the driving forces.; The results indicate a rocketing increase of impervious surfaces, which expanded more than two times from 2,348 to 4,795 km2.;

Under the pressure of environmental issues, decarbonization of the entire energy system has emerged as a prevalent strategy worldwide. The evolution of China’s power system will increasingly emphasize the integration of variable renewable energy (VRE). However, the rapid growth of VRE will pose substantial challenges to the power system, highlighting the importance of power system planning. This letter introduces Grid Optimal Planning Tool (GOPT), a planning tool, and presents the key findings of our research utilizing GOPT to analyze the transition pathway of China’s power system towards dual carbon goals. Furthermore, the letter offers insights into key technologies essential for driving the future transition of China’s power system.

Sunflowers are widely cultivated as a cash crop in the Inner Mongolia Autonomous Region, China. However, due to the lack of efficient resource utilization techniques, most of the sunflower stalks are discarded. In the Hetao irrigation area, the problem of desertification has prompted the limited use of sunflower straw to construct physical sand barriers for windbreaks and sand stabilization. In response to this, this study focuses on synthesizing a cellulose ether sand-fixing material using sunflower straw, the primary agricultural waste in Denkou County, Hetao irrigation district. This material enhances the effective adhesion between sand grains, reduces porosity among loose sand grains, and inhibits sand grain movement. The findings from this study conclusively demonstrate that the sand-fixing materials under investigation meet international standards for mechanical properties. They effectively transform loose, unconnected sand grains into a state with strong adhesion properties.

The occurrence and ecological risks of 16 polycyclic aromatic hydrocarbons (PAHs) in different types of urban road runoff in Beijing during two typical rainfall events were studied. The average concentration of PAHs in road runoff particulate was in the order of Guanyuanqiao Road (ring road, 15,175 ng/L) > Huayuanqiao Road (primary road, 4,792 ng/L) > Dongcheng Alley (alley, 4,774 ng/L) > Nansihuan Viaduct (viaduct, 770 ng/L), much higher than dissolved PAHs. The total concentration of ∑16PAHs decreased with runoff scouring. Rainfall conditions and the accumulation of PAHs in the early rainfall period show a significant impact on PAHs pollution. The event mean concentration range of PAHs is 674–21,596 ng/L, following in the order of ring road > primary road > alley > viaduct. The proportion of four-ring PAHs was the highest. The first flush effect of PAHs is found in both rainfall events, and the effect of different ring PAHs is relatively similar. The content of PAHs is positively correlated with the amount of total organic carbon and suspended substance in runoff (r2> 0.72). The ecological risk assessment indicated that PAHs in road runoff except viaduct road corresponded to high risk. HIGHLIGHTS Polycyclic aromatic hydrocarbon (PAH) concentration decreased with runoff scouring and particulate PAHs was much higher than dissolved PAHs.; The event mean concentration of PAHs in road runoff is 674–21,596 ng/L where four-ring PAHs is most.; The first flush of PAHs occurs and the effect of different ring PAHs is similar.; PAHs amount is positively correlated with total organic carbon and suspended substance in runoff (r2 > 0.72).; PAHs in road runoff except for viaduct road corresponded to high ecological risk.;

Driver distraction detection not only helps to improve road safety and prevent traffic accidents, but also promotes the development of intelligent transportation systems, which is of great significance for creating a safer and more efficient transportation environment. Since deep learning algorithms have very strong feature learning abilities, more and more deep learning-based driver distraction detection methods have emerged in recent years. However, the majority of existing deep learning-based methods are optimized only through the constraint of classification loss, making it difficult to obtain features with high discrimination, so the performance of these methods is very limited. In this paper, to improve the discrimination between features of different classes of samples, we propose a high-discrimination feature learning strategy and design a driver distraction detection model based on Swin Transformer and the highly discriminative feature learning strategy (ST-HDFL). Firstly, the features of input samples are extracted through the powerful feature learning ability of Swin Transformer. Then, the intra-class distance of samples of the same class in the feature space is reduced through the constraint of sample center distance loss (SC loss), and the inter-class distance of samples of different classes is increased through the center vector shift strategy, which can greatly improve the discrimination of different class samples in the feature space. Finally, we have conducted extensive experiments on two publicly available datasets, AUC-DD and State-Farm, to demonstrate the effectiveness of the proposed method. The experimental results show that our method can achieve better performance than many state-of-the-art methods, such as Drive-Net, MobileVGG, Vanilla CNN, and so on.

The simultaneous localization and mapping (SLAM) technique provides long-term near-seafloor navigation for autonomous underwater vehicles (AUVs). However, the stability of descriptors generated by interest point detectors remains a challenge in the hydrothermal environment. This paper proposes a dual-branch feature generalization method, incorporating volumetric density and color distribution for enhanced robustness. The method utilizes shared descriptors and a feature confidence mechanism, combining neural radiance fields with Gaussian splatting models, ensuring fast and accurate feature generalization. The proposed approach improves recall while maintaining matching accuracy, ensuring stability and robustness in feature matching. This method achieves stable and reliable feature matching in a simulated hydrothermal environment.

Hydrogen energy is a green and environmentally friendly energy source, as well as an excellent energy carrier. Hydrogen storage technology is a key factor in its commercial development. Solid hydrogen storage methods represented by using metal hydride (MH) materials have good application prospects, but there are still problems of higher heat transfer resistance and slower hydrogen absorption and release rate as the material is applied to reactors. This study innovatively proposed an array-type MH hydrogen storage reactor based on external water-cooled jacket heat exchange, aiming to improve the heat transfer efficiency and absorption reaction performance, and optimize the absorption kinetics encountered in practical applications of LaNi5 hydrogen storage material in reactors. A mathematical model was built to compare the hydrogen absorption processes of the novel array-type and traditional reactors. The results showed that, with the same water-cooled jacket, the hydrogen absorption rate of the array-type reactor can be accelerated by 2.78 times compared to the traditional reactor. Because of the existence of heat transfer enhancement limits, the increase in the number of array elements and the flow rate of heat transfer fluid (HTF) has a limited impact on the absorption rate improvement of the array-type reactor. To break the limits, the hydrogen absorption pressure, as a direct driving force, can be increased. In addition, the increased pressure also increases the heat transfer temperature difference, thereby further improving heat transfer and absorption rate. For instance, at 3 MPa, the hydrogen absorption time can be shortened to 147 s.

Abstract Non‐invasive, real‐time, dynamic, and quantitative molecular imaging has been developed to facilitate disease diagnosis, drug development, and pathological analysis at the molecular level. Qualitative and quantitative analysis and imaging of physiological processes at the molecular level can be achieved with advanced molecular imaging by employing imaging contrast agents in combination with traditional imaging modalities, such as optical imaging, ultrasound imaging, magnetic resonance imaging, single‐photon emission computed tomography, and positron emission tomography. With the aid of molecular imaging, absorption, distribution, metabolism, excretion, and other processes of drugs in various animals can be monitored quantitatively, and in vivo pharmacokinetics and pharmacodynamics can be simulated before clinical trials, which significantly shorten the period for drug development and reduce the number of animals participating in various tests. Here, the role of molecular imaging in drug target validation, drug screening, drug sensitivity analysis, pharmacokinetics research, drug efficacy evaluation, and other processes of chemical and biological drug research and development is summarized. Molecular imaging has become a powerful and effective tool in the research and development of various drugs for the treatment of a variety of diseases. Advanced molecular imaging can provide important support for disease and drug research, which will accelerate drug discovery and development.

Pien Tze Huang (PZH), a class-1 nationally protected traditional Chinese medicine (TCM), has been used to treat liver diseases such as hepatitis; however, the effect of PZH on the progression of sepsis is unknown. Here, we reported that PZH attenuated lipopolysaccharide (LPS)-induced sepsis in mice and reduced LPS-induced production of proinflammatory cytokines in macrophages by inhibiting the activation of mitogen-activated protein kinase (MAPK) and nuclear factor-kappa B (NF-κB) signalling. Mechanistically, PZH stimulated signal transducer and activator of transcription 3 (STAT3) phosphorylation to induce the expression of A20, which could inhibit the activation of NF-κB and MAPK signalling. Knockdown of the bile acid (BA) receptor G protein-coupled bile acid receptor 1 (TGR5) in macrophages abolished the effects of PZH on STAT3 phosphorylation and A20 induction, as well as the LPS-induced inflammatory response, suggesting that BAs in PZH may mediate its anti-inflammatory effects by activating TGR5. Consistently, deprivation of BAs in PZH by cholestyramine resin reduced the effects of PZH on the expression of phosphorylated-STAT3 and A20, the activation of NF-κB and MAPK signalling, and the production of proinflammatory cytokines, whereas the addition of BAs to cholestyramine resin-treated PZH partially restored the inhibitory effects on the production of proinflammatory cytokines. Overall, our study identifies BAs as the effective components in PZH that activate TGR5-STAT3-A20 signalling to ameliorate LPS-induced sepsis.

Optical sensors using fiber Bragg gratings (FBGs) have become an alternative to traditional electronic sensors thanks to their immunity against electromagnetic interference, their applicability in harsh environments, and other advantages. However, the complexity and high cost of the FBG interrogation systems pose a challenge for the wide deployment of such sensors. Herein, we present a clean and cost-effective method for interrogating an FBG temperature sensor using a micro-chip called the waveguide spectral lens (WSL) and a standard CMOS camera. This interrogation system can project the FBG transmission spectrum onto the camera without any free-space optical components. Based on this system, an FBG temperature sensor is developed, and the results show good agreement with a commercial optical spectrum analyzer (OSA), with the respective wavelength-temperature sensitivity measured as 6.33 pm/°C for the WSL camera system and 6.32 pm/°C for the commercial OSA. Direct data processing on the WSL camera system translates this sensitivity to 0.44 μm/°C in relation to the absolute spatial shift of the FBG spectra on the camera. Furthermore, a deep neural network is developed to train the spectral dataset, achieving a temperature resolution of 0.1 °C from 60 °C to 120 °C, while direct processing on the valley/dark line detection yields a resolution of 7.84 °C. The proposed hardware and the data processing method may lead to the development of a compact, practical, and low-cost FBG interrogator.

The simultaneous localization and mapping (SLAM) technique provides long-term near-seafloor navigation for autonomous underwater vehicles (AUVs). However, the stability of the interest point detector (IPD) remains challenging in the seafloor environment. This paper proposes an optical–acoustic fusion interest point detector (OAF-IPD) using a monocular camera and forward-looking sonar. Unlike the artificial feature detectors most underwater IPDs adopt, a deep neural network model based on unsupervised interest point detector (UnsuperPoint) was built to reach stronger environmental adaption. First, a feature fusion module based on feature pyramid networks (FPNs) and a depth module were integrated into the system to ensure a uniform distribution of interest points in depth for improved localization accuracy. Second, a self-supervised training procedure was developed to adapt the OAF-IPD for unsupervised training. This procedure included an auto-encoder framework for the sonar data encoder, a ground truth depth generation framework for the depth module, and optical–acoustic mutual supervision for the fuse module training. Third, a non-rigid feature filter was implemented in the camera data encoder to mitigate the interference from non-rigid structural objects, such as smoke emitted from active vents in hydrothermal areas. Evaluations were conducted using open-source datasets as well as a dataset captured by the research team of this paper from pool experiments to prove the robustness and accuracy of the newly proposed method.

Factories play a crucial role in economic and social development. However, fire disasters in factories greatly threaten both human lives and properties. Previous studies about fire detection using deep learning mostly focused on wildfire detection and ignored the fires that happened in factories. In addition, lots of studies focus on fire detection, while smoke, the important derivative of a fire disaster, is not detected by such algorithms. To better help smart factories monitor fire disasters, this paper proposes an improved fire and smoke detection method based on YOLOv8n. To ensure the quality of the algorithm and training process, a self-made dataset including more than 5000 images and their corresponding labels is created. Then, nine advanced algorithms are selected and tested on the dataset. YOLOv8n exhibits the best detection results in terms of accuracy and detection speed. ConNeXtV2 is then inserted into the backbone to enhance inter-channel feature competition. RepBlock and SimConv are selected to replace the original Conv and improve computational ability and memory bandwidth. For the loss function, CIoU is replaced by MPDIoU to ensure an efficient and accurate bounding box. Ablation tests show that our improved algorithm achieves better performance in all four metrics reflecting accuracy: precision, recall, F1, and mAP@50. Compared with the original model, whose four metrics are approximately 90%, the modified algorithm achieves above 95%. mAP@50 in particular reaches 95.6%, exhibiting an improvement of approximately 4.5%. Although complexity improves, the requirements of real-time fire and smoke monitoring are satisfied.

Neural network accelerator based on photonic‐integrated circuits is emerging as a promising technology for fast, power‐efficient, and parallel computing. Under such technology, optics is mainly used for linear transformations, e.g., through an array of cascaded switching networks. Nonlinear activation is implemented either electronically requiring extra optical–electrical conversion or via nonlinear optical materials that often suffer from high loss, large power consumption, and difficulty in integration. Herein, an optical neural chip with only one multimode waveguide, fabricated using low‐cost linear optical materials, plus seven heater electrodes to control the multimode interference, is proposed. The nonlinear networks are intrinsically integrated in the electrical‐to‐optical signal conversion through the waveguide. The linear computation, in the electronic domain, is included in the mandatory step to convert the input matrix to the intermediate current values on the seven electrodes. Though extremely simple, the proposed system can classify nonlinear datasets and images by optical readout with high accuracy and without calibration. Prospects for future development are given at the end. In this work, an alternative route is offered to exploiting the classic multimode interference for advanced optical computing applications.

Summary: Autophagy is an essential degradation and recycling process that maintains cellular homeostasis during stress or nutrient deprivation. However, certain types of tumors such as pancreatic cancers can circumvent autophagy inhibition to sustain growth. The mechanism that autophagy-deficient pancreatic ductal adenocarcinoma (PDAC) uses to grow under nutrient deprivation is poorly understood. Our data show that nutrient deprivation in PDAC results in UDP-glucose dehydrogenase (UGDH) degradation, which is dependent on autophagic cargo receptor sequestosome 1 (p62). Moreover, we demonstrate that accumulated UGDH is indispensable for autophagy-deficient PDAC cells proliferation by promoting hyaluronic acid (HA) synthesis upon energy deprivation. Using an orthotopic mouse model of PDAC, we find that inhibition of HA synthesis by targeting UGDH in PDAC reduces tumor weight. Thus, the combined inhibition of HA and autophagy might be an attractive strategy for PDAC treatment.

Non-motor symptoms are prevalent among individuals with Parkinson’s disease (PD) and seriously affect patient quality of life, even more so than motor symptoms. In the past decade, an increasing number of studies have investigated non-motor symptoms in PD. The present study aimed to comprehensively analyze the global literature, trends, and hotspots of research investigating non-motor symptoms in PD through bibliometric methods. Studies addressing non-motor symptoms in the Web of Science Core Collection (WoSCC), published between January 2013 and December 2022, were retrieved. Bibliometric methods, including the R package “Bibliometrix,” VOS viewer, and CiteSpace software, were used to investigate and visualize parameters, including yearly publications, country/region, institution, and authors, to collate and quantify information. Analysis of keywords and co-cited references explored trends and hotspots. There was a significant increase in the number of publications addressing the non-motor symptoms of PD, with a total of 3,521 articles retrieved. The United States was ranked first in terms of publications (n = 763) and citations (n = 11,269), maintaining its leadership position among all countries. King’s College London (United Kingdom) was the most active institution among all publications (n = 133) and K Ray Chaudhuri was the author with the most publications (n = 131). Parkinsonism & Related Disorders published the most articles, while Movement Disorders was the most cited journal. Reference explosions have shown that early diagnosis, biomarkers, novel magnetic resonance imaging techniques, and deep brain stimulation have become research “hotspots” in recent years. Keyword clustering revealed that alpha-synuclein is the largest cluster for PD. The keyword heatmap revealed that non-motor symptoms appeared most frequently (n = 1,104), followed by quality of life (n = 502), dementia (n = 403), and depression (n = 397). Results of the present study provide an objective, comprehensive, and systematic analysis of these publications, and identifies trends and “hot” developments in this field of research. This work will inform investigators worldwide to help them conduct further research and develop new therapies.

Mass timber construction has been emerging in architecture because of exceptional durability, sustainability, and versatility. This work applies the 3-point bending test to a reduced-scale wooden stick with a supporting span of 16.5 cm, under loads up to 560 times its self-weight under raised environmental temperatures up to 300 °C in the oven. The experiments quantify the deformation, critical shear stress of rupture, and degradation mass losses of the heated wood before ignition and combustion, while the numerical model further analyses the detailed thermomechanical responses. Results show that with increasing temperature, the deflection of loaded wooden sticks increases, driven by drying, thermal creep deformation, and thermal degradation. Moreover, the critical shear stress and temperature for wooden sticks rupture decrease, primarily caused by the thermal degradation of wood. The effects of fire-scene temperature on bending strength and modulus of elasticity on the loss of load-bearing capacity for wooden sticks are further quantified with numerical simulation. This work reveals the pre-ignition thermomechanical behaviours of wood under fire scenes, which supports early warnings for ignition and collapse, fire resilience design, and structural-fire stability assessment for wooden structures.

Inspired by mobile edge computing (MEC), edge learning has gained a momentum by directly performing model training at network edge without sending massive data to a centralized data center. However, the quality of model training will be affected by the limited communication and computing resources of network edge. In this paper, how to improve the training performance of a federated learning system aided by intelligent reflecting surface (IRS) over vehicle platooning networks is studied, where multiple platoons train a shared federated learning model. Multi-platoon cooperation can alleviate the pressure of data processing caused by the limited computing resources of single platoon. Meanwhile, IRS can enhance the inter-platoon communication in a cost-effective and energy-efficient manner. Firstly, the federated learning optimization problem of maximizing the learning accuracy is formulated by jointing platoon scheduling, bandwidth allocation and phase shifts at the IRS to maximize the number of scheduled platoon. Specifically, in the proposed learning architecture each platoon updates the learning model with its own data and uploads it to the global model through IRS-based wireless networks. Then, a method based on sequential optimization algorithm (SOA) and a group-based optimization method are analyzed for single IRS aided and large-scale IRS aided communication, respectively. Finally, a platoon scheduling scheme is designed based on the communication reliability and computing reliability of platoons. Simulation results demonstrate that large-scale IRS assisted communication can effectively improve the reliability of multi-user communication networks. The scheduling scheme based on learning reliability balances the communication performance and computing performance of platoons.

Abstract Background Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. It has been reported that the overexpression of DNA damage-inducible transcript 4 gene (DDIT4) is associated with resistance to neoadjuvant chemotherapy and poor prognosis in patients with TNBC. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases. Methods RNA sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Sequencing data were further analyzed by the R package “edgeR” and “clusterProfiler” to identify the profile of differentially expressed genes (DEGs) and annotate gene functions. The prognostic and predictive value of DDIT4 expression in patients with TNBC was further validated by published online data resources, including TIMER, UALCAN, Kaplan–Meier plotter, and LinkedOmics, and GeneMANIA and GSCALite were used to investigate the functional networks and hub genes related to DDIT4, respectively. Results Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues and found that patients with DDIT4 overexpression showed poor survival outcomes. Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression, but correlated positively with immune checkpoint molecules. Furthermore, DDIT4 and its hub genes (ADM, ENO1, PLOD1, and CEBPB) involved in the activation of apoptosis, cell cycle, and EMT pathways. Eventually, we found ADM, ENO1, PLOD1, and CEBPB showed poor overall survival in BC patients. Conclusion In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential molecular targets and improve therapeutic strategies against TNBC.

Six polycyclic aromatic hydrocarbons (PAHs) including naphthalene (Nap), fluorene (Flu), phenanthrene (Phe), fluoranthene (Fla), pyrene (Pyr), and chrysene (Chr) were detected in runoff from five athletic fields during three rainfall events. The event mean concentration (EMC) of ∑6PAHs ranged from 3.96 to 23.23 μg/L, which was much higher than the EMC in urban traffic area runoff. Except for Nap, the PAH concentrations followed in the order of artificial turf > badminton court > basketball court > plastic runway > optennis court. The surface characteristics of the athletic fields, such as the composition of materials and roughness, played an essential role in the release of PAHs. ∑6PAHs concentration during the 2nd rainfall event (July 22nd) was the highest among the three rainfall events, indicating that high rainfall intensity facilitated the PAHs release. PAHs during three rainfall events showed little first flush effect except for the artificial turf during the 2nd (22nd July) and 3rd (29th July) rainfall events. The first flush effect could be affected by rainfall characters, PAH properties, and surface characteristics of athletic fields. Ecological risk assessment showed that PAHs in runoff corresponded to moderate-to-high risk, while health risk assessment showed that PAHs could pose a potential carcinogenic danger to human health via dermal contact. HIGHLIGHTS The event mean concentration of ∑6PAHs in athletic field runoff ranged from 3.96 to 23.23 μg/L.; 4-ring PAHs were more significant than 2- and 3-ring PAHs.; High rainfall intensity facilitated the PAHs release.; The first flush effect was affected by rainfall, PAH properties and athletic field surface characters.; PAHs in runoff corresponded to moderate-to-high risk but pose a potential carcinogenic danger to human health via dermal contact.;

Abstract Background Shenzhen has made great efforts to address the tobacco epidemic in the past decade. This study aims to evaluate the current status of the tobacco epidemic among adolescent in Shenzhen, China. Methods The multi-stage random cluster sampling method was used in the school-based cross-sectional study in 2019 and a total of 7,423 junior and high school (both senior and vocational) students were recruited. Information on cigarette use was collected by the electronic questionnaire. Logistic regression analysis was used to examine the associations between current cigarette use and associated factors. ORs with their 95% CIs were reported. Results The prevalence of current cigarette use among adolescents was 2.3%, with boys (3.4%) significantly higher than girls (1.0%). Smoking rates in junior high schools, senior high schools, and vocational senior high schools were 1.0%, 2.7%, and 4.1%, respectively. The results of multivariate logistic regression analysis indicated that gender, age, parental smoking, teachers smoking in schools, friends smoking, exposure to tobacco marketing, and misconceptions about cigarette use were associated factors for adolescent smoking behaviour. Conclusions The prevalence of current smoking was relatively low among adolescent in Shenzhen, China. Personal characteristics, family, and school were associated with current adolescent smokers.

Abstract Positive human–agent relationships can effectively improve human experience and performance in human–machine systems or environments. The characteristics of agents that enhance this relationship have garnered attention in human–agent or human–robot interactions. In this study, based on the rule of the persona effect, we study the effect of an agent’s social cues on human–agent relationships and human performance. We constructed a tedious task in an immersive virtual environment, designing virtual partners with varying levels of human likeness and responsiveness. Human likeness encompassed appearance, sound, and behavior, while responsiveness referred to the way agents responded to humans. Based on the constructed environment, we present two studies to explore the effects of an agent’s human likeness and responsiveness to agents on participants’ performance and perception of human–agent relationships during the task. The results indicate that when participants work with an agent, its responsiveness attracts attention and induces positive feelings. Agents with responsiveness and appropriate social response strategies have a significant positive effect on human–agent relationships. These results shed some light on how to design virtual agents to improve user experience and performance in human–agent interactions.

Traffic sign detection plays a vital role in assisted driving and automatic driving. YOLOv5, as a one-stage object detection solution, is very suitable for Traffic sign detection. However, it suffers from the problem of false detection and missed detection of small objects. To address this issue, we have made improvements to YOLOv5 and subsequently introduced YOLOv5-TS in this work. In YOLOv5-TS, a spatial pyramid with depth-wise convolution is proposed by replacing maximum pooling operations in spatial pyramid pooling with depth-wise convolutions. It is applied to the backbone to extract multi-scale features at the same time prevent feature loss. A Multiple Feature Fusion module is proposed to fuse multi-scale feature maps multiple times with the purpose of enhancing both the semantic expression ability and the detail expression ability of feature maps. To improve the accuracy in detecting small even extra small objects, a specialized detection layer is introduced by utilizing the highest-resolution feature map. Besides, a new method based on k-means++ is proposed to generate stable anchor boxes. The experiments on the data set verify the usefulness and effectiveness of our work.

The aim of this study is to address the trajectory-tracking control problem of benthic autonomous underwater vehicles (AUVs) subjected to model uncertainties and extra disturbance. In order to estimate lumped uncertainties and reconstruction speed information, this paper designs a robust prescribed-time extended state observer (RPTESO), and its prescribed time can be directly designed as an explicit parameter, without relying on the initial state of the system and complex parameter settings. In addition, an adaptive law is designed to improve the robustness of RPTSEO and reduce overshoot on the premise of ensuring convergence speed. Then, a non-singular robust practical predefined-time sliding mode control (RPPSMC) considering the hydrodynamic characteristics of AUV is designed, and the predefined time can be directly set by an explicit parameter. The RPPSMC is designed based on the lumped uncertainties estimated using RPTESO, so as to improve the control accuracy of the controller in a complex environment. Theoretical analysis and simulations demonstrated the effectiveness and superiority of the proposed method.

Objective: In order to improve the added value of eggplant peel, the best method of phenolic compounds from eggplant peel (EPP), as well as its hypoglycemic impact in vitro and in vivo were studied. Methods: EPP was extracted by ultrasonic-assisted method. The extraction parameters of EPP were optimized by single factor experiments and orthogonal experiment with yield as evaluation index. The inhibitory rate of EPP on α-glucosidase and its effects on body weight, fasting glucose, and glucose tolerance in mice were analyzed to evaluate its hypoglycemic efficacy in vitro and in vivo. Results: The optimal extraction conditions were as follows: Ultrasonic power 540 W, solid-liquid ratio 1:50 g/mL, extraction temperature 50 ℃ and extraction time 50 min. The extraction yield of EPP was 43.21%. The inhibitory rate on α-glucosidase increased with the increase of EPP concentration, and the inhibition rate of α-glucosidase was 45.46% with 1 mg/mL EPP. The body weight, fasting blood glucose and glucose tolerance of diabetic mice could be improved by EPP, and it had a significant hypoglycemic effect on diabetic mice. Conclusion: This study confirmed that EPP had hypoglycemic effect, which laid a theoretical foundation for comprehensive development and utilization of eggplant peel.

Highlights It is first disclosed that the key to the efficient regular Ag-perovskite solar cells (PSCs) is a tunneling layer (silver iodide, AgI) that is in situ formed by the natural reaction between Ag and the migrated iodide. Based on the discovery, an ultrathin and uniform tunneling layer can be deposited on the fragile perovskite/charge transport layer to enrich the options of electrodes for efficient and stable regular PSCs.