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The dialysis membrane is the most important component of hemodialyzer, and its performance depends on the feasibility and biocompatibility of removing toxic solutes. However, when the membrane material is in contact with blood directly, plasma proteins will quickly adsorb on the surface of the membrane and bind to the glycoprotein receptors on platelets, resulting in platelet activation, coagulation cascade and complement activation. This will inevitably induce coagulation and thrombosis, threatening the health and life safety of patients. In order to confer favorable anticoagulant properties upon hemodialysis membranes, it is imperative to modify the membrane materials, including surface microstructure, surface charge and wettability, thereby ensuring their controllability in terms of blood compatibility. The modification technology of the membrane was summarized. The challenges and improvement strategies faced by hemodialysis membranes in the current stage of anal dilation was elaborated. It was clarified that most of the current anticoagulant modification strategies have the problem of poor stability and easy detachment, while the modification process usually involves the usage of organic solvents and chemicals. This review also puts forward prospect on the developing direction of anticoagulant modification technology for dialysis membranes: 1) developing intelligent responsive materials to achieve dynamic anticoagulant functions; 2) constructing a biomimetic membrane surface to reduce the body's rejection reaction; 3) designing dynamic and renewable surfaces that can self-recover or regenerate; 4) carrying out green modification methods which can not only achieve efficient anticoagulant modification but also reduce environmental pollution.

Abstract Targeted protein delivery with nanocarriers holds significant potential to enhance therapeutic outcomes by precisely directing proteins to specific organs or tissues. However, the complex interactions between nanocarriers and the biological environment pose considerable challenges in designing effective targeted delivery vehicles. In this study, we address this challenge by leveraging DNA-barcoded high-throughput screening. We construct a nanocapsule library via in-situ polymerization, incorporating various monomers to create nanocapsules with unique surface properties. In vitro and in vivo screening, using female mice, identify nanocapsules with high cell association and different biodistribution. Our investigation into kidney-enriched nanocapsules highlights the crucial role of polymer composition in biodistribution, demonstrating the potential of surface engineering for precise control over nanoparticle distribution. The kidney-enriched nanocapsule successfully delivers catalase, showcasing its therapeutic potential in mitigating cisplatin-induced acute kidney injury. Overall, our study presents an approach for identifying protein delivery vehicles, with the capacity to broaden the application of proteins as therapeutic agents or research tools.

Carbon fiber (CF)-reinforced epoxy resin (ER)-based composites are promising materials with many application prospects. However, the chemical inertness of the CF surface leads to poor interfacial bonding with the matrix, adversely affecting the mechanical properties, which are regarded as an insurmountable obstacle for their practical applications. Modifying the surface morphology of CFs to increase roughness and constructing a gradient modulus interface layer with rigid-flexible structures of polyimide (PI) on the CF surface to enhance the affinity between CFs and ER. Additionally, the multi-layer interface mitigates internal and external stress concentrations to improve the mechanical properties of the material. Notably, the addition of a flexible PI nanolayer significantly reduces the brittleness of epoxy-based composites, promoting ductile fracture. The reduced contact angle of CFs in polar and non-polar solutions after modification indicates that polydopamine (PDA) and highly polar PI enhance chemical compatibility at the composite interface, increasing the overall surface energy of the CF. Additionally, thermogravimetric analysis tests reveal that the excellent heat resistance of PI significantly enhances the thermal stability of the polymer on the modified CF surface. In conclusion, this work provides a feasible method for constructing novel gradient modulus interfacial layers with nanostructured rigid-flexible architectures in ER, offering new insights for designing next-generation advanced composites.

Abstract Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the in-situ study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17 dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects.

Abstract The microRNA156 (miR156) has been widely studied in plants, however, the characterization of the miR156 family of genes in wheat and their expression patterns under abiotic stress are not completely clear. In this study, a total of 20 miR156 family members, referred to as tae-miR156a to tae-miR156t, were identified in wheat with their loci mapped to various chromosomes. These members were divided into five subgroups: miR156a/b/c/d/e/f, miR156g/h/i, miR156j/k, miR156l/m/n/o/p/q, and miR156r/s/t. They were highly conserved during evolution. The prediction of cis-elements in the tae-MIR156(s) promoter region revealed that the tae-MIR156(s) had diverse cis-acting elements; of these, 15 tae-MIR156(s) and 6 tae-MIR156(s) were found to be drought-responsive elements and cold-responsive elements, respectively. And the prediction target genes of tae-miR156(s) are mainly SPL transcription factor genes. Expression analysis based on quantitative real-time polymerase chain reaction (qRT‒PCR) showed that miR156(s) have different expression levels in the various wheat tissues, and the subgroups’ response to abiotic stress varied. Among them, miR156g/h/i were strongly induced in the root of cold and heat stress, and miR156a/b/c/d/e/f were significantly increased in roots after drought stress, whereas miR156r/s/t were highly inhibited in leaves and roots after salt stress. These findings imply that tae-miR156(s) are involved in stress response in wheat, and they provide new fundamental knowledge for further analysis of the function of miR156 and its regulatory mechanism in response to abiotic stress.

Abstract. Background:. Substantial progress in air pollution control has brought considerable health benefits in China, but little is known about the spatio-temporal trends of economic burden from air pollution. This study aimed to explore their spatio-temporal features of disease burden from air pollution in China to provide policy recommendations for efficiently reducing the air pollution and related disease burden in an era of a growing economy. Methods:. Using the Global Burden of Disease method and willingness to pay method, we estimated fine particulate matter (PM2.5) and/or ozone (O3) related premature mortality and its economic burden across China, and explored their spatio-temporal trends between 2005 and 2017. Results:. In 2017, we estimated that the premature mortality and economic burden related to the two pollutants were RMB 0.94 million (68.49 per 100,000) and 1170.31 billion yuan (1.41% of the national gross domestic product [GDP]), respectively. From 2005 to 2017, the total premature mortality was decreasing with the air quality improvement, but the economic burden was increasing along with the economic growth. And the economic growth has contributed more to the growth of economic costs than the economic burden decrease brought by the air quality improvement. The premature mortality and economic burden from O3 in the total loss from the two pollutants was substantially lower than that of PM2.5, but it was rapidly growing. The O3-contribution was highest in the Yangtze River Delta region, the Fen-Wei Plain region, and some western regions. The proportion of economic burden from PM2.5 and O3 to GDP significantly declined from 2005 to 2017 and showed a decreasing trend pattern from northeast to southwest. Conclusion:. The disease burden from O3 is lower than that of PM2.5, the O3-contribution has a significantly increasing trend with the growth of economy and O3 concentration.

Visible-light induced direct C–H difluoromethylation of quinoxalinones with 2-((difluoromethyl)sulfonyl)benzo[d]thiazole has been developed for the first time. A broad range of quinoxalinones were well tolerated and reacted with difluorosulfone smoothly to give the corresponding products in moderate to good yields. Notably, no external photocatalyst or oxidant was required, which provides a practical and green protocol to access difluoromethylated quinoxalinones. Finally, the control experiments demonstrated a radical mechanism, and the density functional theory (DFT) calculations indicated the radicals were generated through the formation of an electron donor−acceptor (EDA) complex.

Abstract Background Bioterrorism is an important topic in the field of biosecurity. Nurses, the largest group of healthcare workers, play a critical role in addressing the threat of bioterrorism. This study aimed to examine the present level of bioterrorism knowledge, attitudes, and practices among nurses. It also explored the relationships among bioterrorism knowledge, attitudes, and practices, as well as demographic variables that influence the scores of each dimension. Methods A descriptive correlational research design was conducted using a convenience sample of 429 nurses in five tertiary general hospitals in Tianjin. Registered nurses with six months or more of work experience, currently still working in hospitals, and volunteering to participate in the study are included; otherwise, they are excluded. A structured questionnaire with four components was used: sociodemographic characteristics, knowledge of bioterrorism, attitudes toward bioterrorism, and practices related to bioterrorism. The acquired data were analyzed using the Mann‒Whitney test, Kruskal‒Wallis test, Spearman correlation analysis, and multiple linear regression. This study followed the STROBE guidelines. Results The study ultimately included 429 valid surveys. The mean score for bioterrorism knowledge was satisfactory (33.06 ± 4.87), the mean score for bioterrorism attitudes was good (23.83 ± 5.23), and the mean score for bioterrorism practices was poor (10.94 ± 6.51). There was a significant negative correlation between bioterrorism knowledge and attitudes (r=-0.38, p

ObjectiveTo investigate the knowledge and influencing factors of willingness to receive human papillomavirus (HPV) vaccination among senior primary school students in Guangdong province, and to provide a reference for relevant departments to formulate policies. MethodsUsing stratified multistage cluster sampling and a self-developed questionnaire, 1 610 students in grades 5 and 6 from 7 primary schools in the Pearl River Delta region, eastern, western, and northern regions of Guangdong province were selected to participate in a self-administered, on-site, anonymous survey from June to October 2022. The students′ awareness of HPV, knowledge of HPV vaccination, willingness to receive HPV vaccination, and factors influencing willingness to receive HPV vaccination were analyzed.ResultsFor a total of 1 314 participants with valid responses, the HPV awareness and HPV vaccine knowledge rates were 61.49% and 66.13%, respectively, and the HPV vaccine uptake rate was 74.73%. Multivariate logistic regression analysis showed that participants who were female (odds ratio [OR] = 2.15, 95% confidence interval [95%CI]: 1.60 – 2.80), lived in an urban area (OR = 1.56, 95%CI: 1.20 – 2.02), and from the Pearl River Delta region (OR = 3.64, 95%CI: 2.28 – 5.81) and the northern region of the province (OR = 5.65, 95%CI: 4.00 – 7.97) were more likely to have heard of HPV, and the participants were female (OR = 2.11, 95%CI: 1.60 – 2.78), lived in an urban area (OR = 1.45, 95%CI: 1.11 – 1.89), and from the Pearl River Delta region (OR = 5.20, 95%CI: 3.06 – 8.83) and the northern region of the province (OR = 6.30, 95%CI: 4.39 – 9.06) were more likely to have heard of HPV vaccine; the results also showed that the participants who were female (OR = 7.07, 95%CI: 4.89 – 10.21), had heard of HPV (OR = 1.94, 95%CI: 1.29 – 2.93), and were aware of HPV vaccine (OR = 1.65, 95%CI: 1.07 – 2.55) were more likely to be willing to receive HPV vaccination. ConclusionAwareness of HPV and knowledge of HPV vaccine are not high among senior primary school students in Guangdong province, but willingness to receive HPV vaccination is relatively high. Residential area, living region and gender are the main factors influencing HPV awareness and HPV vaccine knowledge and willingness to receive HPV vaccination among the students.

Abstract Purpose To evaluate the repeatability and agreement of two swept-source optical coherence tomographers and Scheimpflug imaging for corneal curvature in healthy subjects to obtain data on the clinical application of a new device. Methods This prospective study was conducted in January and February 2021 with 100 healthy subjects at the Eye Hospital of Wenzhou Medical University. Simulated keratometry (Sim-K), posterior keratometry (Kp), total corneal power (TCP), and total corneal astigmatism (TCA) were measured with CASIA2, Anterion, and Pentacam. Within-subject standard deviation (Sw), repeatability coefficient (RC), coefficient of variation (CoV), and intraclass correlation coefficient (ICC) were used to assess inter-device repeatability. Bland–Altman analysis was performed to determine inter-device agreement. Results The three devices showed good repeatability for Sim-K, Kp, and TCP with all ICC > 0.980. Pentacam showed the highest repeatability (ICC ≥ 0.993; ICC ≥ 0.993) while the CASIA2 demonstrated the lowest repeatability (ICC: ≥ 0.986; ICC: ≥ 0.985) for Sim-K and TCP. Anterion and CASIA2 revealed better repeatability (ICC ≥ 0.998; ICC ≥ 0.981) for Kp than Pentacam (ICC ≥ 0.980). Pentacam and Anterion showed good repeatability for TCA (ICC: 0.935 and 0.916), whereas the CASIA2 showed moderate repeatability (ICC: 0.836). Three instruments demonstrated good agreement with the maximum absolute 95% Limits of agreement (LoA) of 1.00 D for Sim-K, Kp, and TCP. Wide LoA were found for TCA with the maximum absolute 95% LoA ≥ 0.66 D between the three devices. Conclusions In healthy subjects, the three devices (Pentacam, Anterion and CASIA2) displayed comparable repeatability and accuracy for SimK, Kp, and TCP, and could be used interchangeably for these parameters. However, TCA measured by the three devices was not interchangeable. Trial registration Chinese Clinical Trial Registry Center (10/10/2020, ChiCTR2000038959).

Abstract Background Peripheral immunity and neuroinflammation interact with each other and they play important roles in the pathophysiology of idiopathic Parkinson’s disease (IPD). There have been very few real-world reports on the relationship between peripheral immune inflammation and motor phenotypes of IPD. This study aimed to investigate the potential correlation between peripheral inflammatory indicators and motor subtypes in patients with IPD. Methods This observational, prospective case-control study examined patients with IPD and healthy controls (HC) matched for age and sex between September 2021 and July 2023 at the Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University. The levels of peripheral inflammatory indicators were collected from each patient with IPD and HCs. Differences in the levels of peripheral inflammatory indicators among groups were compared. Binary logistic regression analysis was used to explore the inflammatory mechanism underlying the motor subtype of IPD. Results A total number of 94 patients with IPD were recruited at the Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University between September 2021 and July 2023, including 49 males and 45 females, and 37 healthy volunteers matched for age and sex were also enrolled as the control group. Of the 94 patients with IPD, 42.6% performed as the TD motor subtype and 57.4% performed as the AR motor subtype. NLR and the plasma levels of IL-1βand TNF-α in the IPD group were higher than those in the HC group (P

Abstract To optimize the current college sports data information management system, this study combines the Apriori association rule algorithm with web application development technology to upgrade the management system. Firstly, this study explores novel log mining techniques in genetic algorithms and web application development technology. Secondly, by integrating log mining techniques to optimize the Apriori algorithm, associations between sports data and information are discovered. Through the optimized algorithm, this study identifies key association rules of sports data information and validates the optimized system’s reliability and effectiveness through experiments. The experimental results show that the running time of the traditional Apriori algorithm exponentially grows with the increase in information volume, while the optimized execution efficiency is improved by approximately 10–15%. Additionally, the average retrieval accuracy of this optimized system can reach 98.3%, although the retrieval time also increased by 23%. Therefore, the technology and algorithms proposed in this study have certain application value in the sports information management system and contribute to the optimization of data information management in this field.

Abstract Solid fuel combustion exposure is a leading global health risk factor, yet evidence on its effects, especially on vulnerable children, is sparse. This large-scale, multi-center prospective study aimed to address this gap by involving 9997 schoolchildren across China between 2013 and 2015. Here we show that lung function levels exhibited a marginally significant decline among children exposed to solid fuel usage. Specifically, FVC and FEV1 decreased by 21.2 mL (95% CI: −15.7, 58.1) and 24.1 mL (−8.4, 56.6), respectively. Additionally, PEF, FEF25 and FEF75 decreased by 25.7 mL/s (−46.5, 98.0), 32.7 mL/s (−42.7, 108.2), and 35.4 mL/s (−5.9, 76.7), respectively. Persistent exposure to solid fuel usage in children led to greater lung damage. Children with allergy history were more susceptible to solid fuel exposure. Our study highlights the adverse impact of solid fuel usage on children and the need to promote clean fuel usage for this vulnerable population.

Abstract Background Klebsiella pneumoniae (KP), responsible for acute lung injury (ALI) and inflammation of the gastrointestinal tract, is a zoonotic pathogen that poses a threat to livestock farming worldwide. Nevertheless, there is currently no validated vaccine to prevent KP infection. The development of mucosal vaccines against KP using Lactobacillus plantarum (L. plantarum) is an effective strategy. Results Firstly, the L. plantarum strains NC8-pSIP409-aCD11c’ and NC8-pLc23-aCD11c were constructed via homologous recombination to express the aCD11c protein either inducibly or constitutively. Both NC8-pSIP409-aCD11c’ and NC8-pLc23-aCD11c strains could enhance the adhesion and invasion of L. plantarum on bone marrow-derived dendritic cells (BMDCs), and stimulate the activation of BMDCs compared to the control strain NC8-pSIP409 in vitro. Following oral immunization of mice with NC8-pSIP409-aCD11c’ and NC8-pLc23-aCD11c, the cellular, humoral, and mucosal immunity were significantly improved, as evidenced by the increased expression of CD4+ IL-4+ T cells in the spleen, IgG in serum, and secretory IgA (sIgA) in the intestinal lavage fluid (ILF). Furthermore, the protective effects of L. plantarum against inflammatory damage caused by KP infection were confirmed by assessing the bacterial loads in various tissues, lung wet/dry ratio (W/D), levels of inflammatory cytokines, and histological evaluation, which influenced T helper 17 (Th17) and regulatory T (Treg) cells in peripheral blood and lung. Conclusions Both the inducible and constitutive L. plantarum strains NC8-pSIP409-aCD11c’ and NC8-pLc23-aCD11c have been found to stimulate cellular and humoral immunity levels and alleviate the inflammatory response caused by KP infection. These findings have provided a basis for the development of a novel vaccine against KP.

The individual effects of cropping patterns and planting densities on cotton yield formation and resource utilization have been extensively studied in the arid regions of western China, but research on their combined impacts remains limited. This study hypothesized that optimizing cropping patterns and planting densities would enhance hydrothermal resource productivity and cotton yield in the region. To test this, a two-year field experiment (2022–2023) employed a split-plot design with two main planting patterns (four rows per film and six rows per film) and three planting densities (low, medium, and high) as subplots. Using internet of sensor technology, soil temperature and moisture were monitored to assess their spatial and temporal distributions. The effects of planting pattern, density, and their interactions on cotton yield, yield components, biomass accumulation, and water and heat utilization were evaluated. The interaction between pattern and density significantly influenced cotton yield, harvest index, and water productivity, with planting density exerting a stronger effect on water productivity than planting pattern. In 2023, the four-row pattern at low and medium densities produced higher yields than the high-density treatment. Over the two-year period, the four-row, low-density treatment achieved 8.77 % and 13.40 % greater water productivity than the medium- and high-density treatments, respectively, while the six-row, medium-density treatment outperformed low and high densities, increasing water productivity by 3.64 % and 8.74 %. Seed cotton yield was also higher, with a 2.88 % and 6.15 % increase in the four-row, low-density treatment and an 8.51 % and 4.79 % increase in the six-row, medium-density treatment compared to higher-density treatments. The study further analyzed spatial and temporal variations in soil moisture and temperature and their link to resource productivity and cotton yield. Soil water content differences ranged from 0.10 to 0.90 mm in the four-row pattern and from 0.20 to 0.70 mm in the six-row pattern between low- and high-density treatments. Planting density significantly affected soil temperature during flowering and boll-setting stages. Lint and seed cotton yields showed positive correlations with soil heat production efficiency (PEsoil) and negative correlations with water production efficiency (WPc), with optimal patterns observed in the four-row, low-density and six-row, medium-density treatments. These findings explain why these configurations led to a higher harvest index and enhanced hydrothermal resource productivity. This study provides valuable insights into the optimal configurations for maximizing cotton yield and resource efficiency in arid regions, supporting sustainable cotton production under resource-limited conditions.

Idiopathic CD4 lymphopenia (ICL) is a rare non–HIV-related syndrome, characterized by a reduced CD4 T-cell count and a predisposition to various opportunistic infections. However, Talaromyces marneffei (TM) infection has rarely been reported in ICL patients. Here, we report a previously healthy 48-year-old male patient who presented with fever, headache, fatigue, vomiting, and poor appetite. Mycological cultures from blood, bone marrow, liver and spleen were positive for TM. The immunodeficiency evaluation revealed a CD4 T-lymphocyte count of 32 cells/μL, with a negative HIV test. After receiving co-treatment with amphotericin B and voriconazole, the patient showed clinical improvement. At 1-year follow-up, the CD4 T-cell count remained decreased despite the complete resolution of symptoms. The appearance of disseminated TM infection in non-HIV patients should prompt an investigation for the possibility of ICL, as the clinical manifestations can be severe.

Summary: Background: Due to global climate change, high temperature and heatwaves have become critical issues that pose a threat to human health. An effective early warning system is essential to mitigate the health risks associated with high temperature and heatwaves. However, most of the current heatwave early warning systems are not adequately developed based on the heat-health risk model, and the health impact of hot weather has not been well managed in most countries. Methods: This study proposed a “full-season coverage and population health-oriented graded early-warning” concept and developed a heat-health surveillance, forecast and early warning (HHSEW) model. The exposure-response (E-R) relationship between temperature and mortality was analyzed through a two-stage approach using time-series analysis data from 323 counties across China for the period 2013–2018. The premature mortality curve at each temperature percentile was plotted and four temperature-percentile points on the curve were determined as the thresholds of the pre-warning and warning levels 1–3 based on the variations in the rates of the segmental slopes on the curve. The HHSEW model was evaluated by comparing the frequency, the mortality risk of all-cause and cause-specific diseases, the predicted numbers of premature deaths, and the heat-related health economic burden at each warning level with those of the current high temperature early warning systems. Findings: The HHSEW model determined five levels, including seasonal surveillance, pre-warning, and warning levels 1–3. There was a gradual increase in the mortality risks of all-cause and cause-specific diseases along with the increase of warning levels. The risk of all-cause mortality increased by 9.79% (95% CI: 8.59%–11.01%), 22.62% (95% CI: 19.49%–25.83%), 28.36% (95% CI: 24.72%–32.10%), and 33.87% (95% CI: 28.89%–39.06%) at the pre-warning level, warning level 1, warning level 2, and warning level 3, respectively. Through our HHSEW model, 94,008 heat-related all-cause deaths were predicted annually in the 337 major cities of China, which was much larger than the number (14,858) of the China Meteorological Administration (CMA) heatwave early-warning system currently used in China. It was estimated that the proper implementation of the HHSEW-based early warning system would save 220 billion CNY in heat-related health burden compared to the current heatwave early-warning system. Interpretation: The HHSEW model has been proven to surpass the current heatwave early warning system. With its full-season coverage and graded warning levels for heat-related health risks, the HHSEW model and system can provide timely early warnings to the public, leading to significant health benefits. This methodology, labeled “full-season coverage and population health-oriented graded early-warning”, should be implemented globally to mitigate the escalating health risks associated with high temperature. Funding: National Natural Science Foundation of China (82425051, 42071433, 42305196, 82241051) and the Special Foundation of Basic Science and Technology Resources Survey of Ministry of Science and Technology of China (2017FY101204).

Biocontrol is an effective technology for managing mycotoxin contamination in food, and the improvement of its application depends largely on revealing the degradation mechanisms at the molecular level. Research in this area is much less than that on the screening of degrading strains. In a previous study, Meyerozyma guilliermondii AF01 was confirmed to exert degradation and adsorption effects on aflatoxin B1 (AFB1). In this study, a potential degradation gene, MG2-4, was mined using a combination of bioinformatics and chemical approaches. The gene was heterologously expressed in Escherichia coli Rosetta DE3, and the recombinant protein, Mg aldo–keto reductase (AKR), reacted with AFB1 in vitro. Moreover, MgAKR rapidly removed AFB1. The degradation product was identified as aflatoxicol using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry, which is the same as the degradation product of the AF01 strain. This study reveals that MG2-4 is the key AFB1-degrading enzyme gene in the AF01 strain and lays the foundation for improving AFB1 removal using the AF01 strain.

The response to climate change and air pollution control demonstrates strong synergy across scientific mechanisms, targets, strategies, and governance systems. This report, based on a monitoring indicator system for coordinated governance of air pollution and climate change, employs an interdisciplinary approach combining natural and social sciences. It establishes 20 indicators across five key areas: air pollution and climate change, governance systems and practices, structural transformation and technologies, atmospheric components and emission reduction pathways, and health impacts and co-benefits. This report tries to provide actionable insights into the interconnectedness of air pollution and climate governance. It highlights key policy gaps, presents updated indicators, and offers a refined monitoring framework to track progress toward China's dual goals of reducing emissions and improving air quality. Compared to previous editions, this year's report has updated four key indicators: meteorological impacts on air quality, climate change and its effects, governance policies, and low-carbon building energy systems. The aim is to further refine the monitoring framework, track progress, and establish a comprehensive theory for collaborative governance while identifying challenges and proposing solutions for China's pathway to carbon neutrality and clean air. The report comprises six chapters. The executive summary chapter is followed by analyzing air pollution and climate change interactions. Governance systems and practices are discussed in the third chapter, focusing on policy implementation and local experiences. The fourth chapter addresses structural transformations and emission reduction technologies, including energy and industrial shifts, transportation, low-carbon buildings, carbon capture and storage, and power systems. The fifth chapter outlines atmospheric component dynamics and emission pathways, presenting insights into emission drivers and future strategies. The sixth chapter assesses health impacts and the benefits of coordinated actions. Since 2019, China Clean Air Policy Partnership has produced annual reports on China's progress in climate and air pollution governance, receiving positive feedback. In 2023, the report was co-developed with Tsinghua University's Carbon Neutrality Research Institute, involving over 100 experts and multiple academic forums. The collaboration aims to continuously improve the indicator system and establish the report as a key resource supporting China's efforts in pollution reduction, carbon mitigation, greening, and sustainable growth.

Due to the prevalence of academic anxiety among primary school students and its long-term effect on the physical and mental health, researchers have carried out a lot of research on it. According to the control-value theory of achievement emotions, this cross-sectional study sought to explore the relationship between students’ future orientation and academic anxiety, to reveal the mediating effect of achievement goal orientations, and to test gender difference. A total of 5,330 students in grades 4–6 from 8 primary schools in China were included in the questionnaire-based investigation. The results showed that (1) girls’ academic anxiety, master-avoidance, and performance-avoidance goal orientations were significantly higher than those of boys, while performance-approach goal orientation was significantly lower than those of boys; (2) future orientation significantly positively predicted academic anxiety; (3) achievement goal orientation played a mediating role between future orientation and academic anxiety; and (4) there was a significant gender difference in this mediating effect. The four areas of achievement goal orientations have a complete mediating effect on academic anxiety for boys, but the master-approach and master-avoidance goal orientations play a partial mediating role between future orientation and academic anxiety for girls. This study contributes to deep understanding of academic anxiety among Chinese pupils, and implications for academic emotions research and educational practice.

Abstract Background Unfavorable temperatures significantly constrain the quality formation of Dendrobium officinale, severely limiting its food demand. Salicylic acid (SA) enhances the resistance of D. officinale to stress and possesses various analogs. The impact and mechanism of the SA family on improving the quality of D. officinale under adverse temperature conditions remains unclear. Results Combined with molecular docking analysis, chlorophyll fluorescence and metabolic analysis after treatments with SA analogues or extreme temperatures are performed in this study. The results demonstrate that both heat and cold treatments impede several main parameters of chlorophyll fluorescence of D. officinale, including the ΦPSII parameter, a sensitive growth indicator. However, this inhibition is mitigated by SA or its chemically similar compounds. Comprehensive branch imaging of ΦPSII values revealed position-dependent improvement of tolerance. Molecular docking analysis using a crystal structure model of NPR4 protein reveals that the therapeutic effects of SA analogs are determined by their binding energy and the contact of certain residues. Metabolome analysis identifies 17 compounds are considered participating in the temperature-related SA signaling pathway. Moreover, several natural SA analogs such as 2-hydroxycinnamic acid, benzamide, 2-(formylamino) benzoic acid and 3-o-methylgallic acid, are further found to have high binding ability to NPR4 protein and probably enhance the tolerance of D. officinale against unfavorable temperatures through flavone and guanosine monophosphate degradation pathways. Conclusions These results reveal that the SA family with a high binding capability of NPR4 could improve the tolerance of D. officinale upon extreme temperature challenges. This study also highlights the collaborative role of SA-related natural compounds present in D. officinale in the mechanism of temperature resistance and offers a potential way to develop protective agents for the cultivation of D. officinale.

Photonic signal processing offers a versatile and promising toolkit for contemporary scenarios ranging from digital optical communication to analog microwave operation. Compared to its electronic counterpart, it eliminates inherent bandwidth limitations and meanwhile exhibits the potential to provide unparalleled scalability and flexibility, particularly through integrated photonics. However, by far the on-chip solutions for optical signal processing are often tailored to specific tasks, which lacks versatility across diverse applications. Here, we propose a streamlined chip-level signal processing architecture that integrates different active and passive building blocks in silicon-on-insulator (SOI) platform with a compact and efficient manner. Comprehensive and in-depth analyses for the architecture are conducted at levels of device, system, and application. Accompanied by appropriate configuring schemes, the photonic circuitry supports loading and processing both analog and digital signals simultaneously. Three distinct tasks are facilitated with one single chip across several mainstream fields, spanning optical computing, microwave photonics, and optical communications. Notably, it has demonstrated competitive performance in functions like image processing, spectrum filtering, and electro-optical bandwidth equalization. Boasting high universality and a compact form factor, the proposed architecture is poised to be instrumental for next-generation functional fusion systems.

Stent(s) insertion is a common form of surgery for patients with cardiovascular diseases, and is associated with a high rate of hospital readmission. This study aims to investigate the acute association between PM2.5 exposure and hospital readmission for patients with cardiovascular disease and a history of stent(s) insertion. The records of hospital admission were collected from the Beijing Municipal Commission of Health and Family Planning Information Center between 1st January 2013 and 31st December 2017. Subsequent hospital readmission records for patients with a history of stent(s) insertion or without any surgery were extracted. The conditional logistic regression model was applied to investigate the association between PM2.5 concentration and cardiovascular disease readmission in patients who had undergone stent(s) insertion or without any surgery. A total of 81,468 patients who had a history of stent(s) insertion were included in this study. Of these, 17,224 patients (21.1 % of the total number of patients) were readmitted 27,749 times due to cardiovascular disease. The median daily PM2.5 concentration was 62.8 μg/m3 with an interquartile range (IQR) of 71.5 μg/m3. The excess risk (ER) associated 10 μg/m3 increase in PM2.5 concentration for readmission due to cardiovascular disease was 0.48 % (95 % CI: 0.09 %, 0.87 %) in patients with a history of stent(s) insertion. Patients who had stent(s) insertion at the vessel bifurcation site showed the highest risk of readmission for cardiovascular disease when exposed to PM2.5; the ER was 4.12 % (95 % CI: 1.60 %, 6.70 %). PM2.5 was significantly associated with angina pectoris and readmission for chronic ischemic heart disease in patients with a history of stent(s) insertion. PM2.5 had a significant association with cardiovascular readmission among patients with a history of insertion of stent(s). Patients who had vessel bifurcation treated showed the highest risk of readmission.

Many studies have confirmed that PM2.5 exposure can cause a variety of diseases. Because people spend most of their time indoors, exposure to PM2.5 in indoor environments is critical to population health. Large-population, long-term, continuous, and accurate indoor PM2.5 data are important but scarce because of the difficulties in monitoring the indoor air quality on a large scale. Model simulation provides a new research direction. In this study, an advanced machine learning model was constructed using environmental health big data to predict the daily indoor PM2.5 concentration data in 22 typical air pollution cities in China from 2013 to 2017. The test R2 value of this model reached as high as 0.89, and the RMSE of the model was 9.13. The predicted annual indoor PM2.5 concentrations of the cities ranged from 54.6 μg/m3 to 82.7 μg/m3, and showed a decreasing trend year by year. The pollution level exceeds the recommended AQG level of PM2.5 and has potential impact on human health. The results could take a breakthrough in obtaining accurate big data of indoor PM2.5 and contribute to research on the indoor air quality and human health in China. Synopsis: This study established a machine learning model and predicted indoor PM2.5 big data, which could support the research of indoor PM2.5 and health.

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Abstract The pathogenesis of Parkinson's disease (PD) is closely related to the gut microbiota, and microecological therapies based on gut probiotics have received widespread attention, among which Bifidobacterium has been demonstrated to have a potential neuroprotective effect, but specific mechanisms have been lacking in the investigation. Here, we show that Bifidobacterium longum subsp. longum CCFM1029 significantly inhibited LPS‐induced inflammatory responses in microglia and alleviated 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced motor dysfunction, dopaminergic neuronal damage, and neuroinflammation in PD mice. Subsequently, the mechanism of action of CCFM1029 in PD was systematically elucidated by the neurochemical and biochemical analysis in PD mice, together with microbiomic and metabolomic analysis. It was found that CCFM1029 intervention restores dysbiosis in the gut microbiota linked to PD and reverses alterations in microbial metabolites. We established the interactions among the gut microbiota, metabolites, and brain by integrating behavioral and neurophysiological data with changes in the composition of the gut microbiota and metabolomic characteristics. We found that CCFM1029 intervention increases levels of the beneficial gut microbial metabolites indole‐3‐acrylic acid and short‐chain fatty acid (acetic and butyric acid) and decreases levels of the neuroinflammation‐associated metabolite N‐acetylhistamine. To summarize, our findings suggest CCFM1029 as a novel dietary supplement can prevent and mitigate the progression of PD through the microbiota‐gut‐brain axis.

Abstract Sanghuangporus vaninii is a traditional edible and medicinal fungi with a long history in China. Recent studies have focused on its potential in treating diabetes, although the underlying mechanism remains unclear. This study aimed to investigate the antidiabetic and hypolipidemic effects of the formula of S. vaninii compounds (SVC) in diabetic mice and explore the potential improvement in the intestinal microbiota. Oral administration of SVC significantly reduced fasting blood glucose and improved insulin sensitivity and lipid indexes. In addition to its direct effects on glucose levels and insulin sensitivity, SVC was found to have an impact on the intestinal microbiota. The levels of short‐chain fatty acids receiving SVC intervention increased, and 16S rRNA sequencing revealed changes in the abundances of certain bacteria, such as Harryflintia, Helicobacter, Candidatus_Soleaferrea, Klebsiella, and Candidatus_Stoquefichus. These bacteria were found to be negatively associated with glucose and lipid indexes and positively related to body weight and insulin sensitivity. Overall, this study highlights the potential of SVC in treating diabetes and provides a novel perspective for understanding its antidiabetic mechanism through modulation of the intestinal microbiota.

Both ambient fine particulate matter (PM2.5) and aging are important urban concerns. However, the associations between PM2.5 constituents and the acceleration of aging (AA) remain unclear. We included 16,051 adults (aged 25–80 years) with 19,252 medical observations in Taiwan during 2008−2017. 2-year average PM2.5 and its five major constituents were assessed using a two-stage machine learning model at a resolution of 1 km2. AA was determined by the difference between the Klemera–Doubal biological age and chronological age. A linear mixed model (LMM) with inverse probability weights was used to examine the associations between AA and air pollution. In a semi-randomized study design, we applied a post-matching LMM to assess the impacts of changes in air pollution exposure on AA. Each interquartile range increase in ambient PM2.5, SO4-2, NO3–, NH4+, organic matters (OM), and black carbon (BC) was associated with a 0.20 (95 %confidence interval [CI]: 0.17–0.24), 0.19 (0.15–0.23), 0.14 (0.11–0.18), 0.21 (0.17–0.24), 0.22 (0.19–0.26) and 0.25 (0.21–0.28) year increase in AA, respectively. BC was generally associated with the greatest increase in AA as compared to other constituents. We did not find evident thresholds in their concentration–response associations. Participants exposed to increased levels of PM2.5, SO4-2, NO3–, NH4+, OM, and BC experienced an increase in AA of 0.11 (−0.07–0.29), 0.20 (0.02–0.39), 0.15 (−0.02–0.33), 0.12 (−0.07–0.31), 0.24 (0.07–0.41), and 0.30 (0.07–0.52) years, respectively, compared to those exposed to decreased/unchanged levels. Long-term exposure to ambient PM2.5 and its constituents may accelerate biological aging among Chinese adults. Exposed to increased levels may further aggregate the aging process. This study suggests that reducing exposure to air pollution is beneficial, even for residents within moderately-to-highly polluted regions, such as Taiwan. Rigorous regulation of PM2.5 and its constituents may prevent the acceleration of biological age.

IntroductionHyperlipidemic acute pancreatitis (HLAP) is a form of pancreatitis induced by hyperlipidemia, posing significant diagnostic challenges due to its complex lipid metabolism disturbances.MethodsThis study compared the serum lipid profiles of HLAP patients with those of a healthy cohort using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify distinct lipid metabolites. Logistic regression and LASSO regression were used to develop a diagnostic model based on the lipid molecules identified.ResultsA total of 393 distinct lipid metabolites were detected, impacting critical pathways such as fatty acid, sphingolipid, and glycerophospholipid metabolism. Five specific lipid molecules were selected to construct a diagnostic model, which achieved an area under the curve (AUC) of 1 in the receiver operating characteristic (ROC) analysis, indicating outstanding diagnostic accuracy.DiscussionThese findings highlight the importance of lipid metabolism disturbances in HLAP. The identified lipid molecules could serve as valuable biomarkers for HLAP diagnosis, offering potential for more accurate and early detection.

Machine learning has been a powerful tool to study various models in many fields, which requires plenty of data to ensure accuracy. It is a challenge to reduce the dependence on the amount of data and ensure that the predictions are both accurate and physical. We develop a theory-guided neural network (TgNN) to explore the ground states of two-component spin–orbit coupled Bose–Einstein condensation in two-dimension. Only randomly selected few data from the twelve ground states as training data, TgNN performs higher accuracy, broader generalization ability and stronger robustness than deep neural network (DNN). Moreover, in the neighborhood of the phase transition where the predictions of DNN have obvious deviations, while TgNN still keeps relative accuracy. TgNN is less dependent on data and exhibits potential for high-dimensional and complicated models.

IntroductionMultiple linked single nucleotide polymorphisms (SNPs) have shown potential in personal identification and mixture detection. However, the limited number of marker and sequencing errors have obstructed accurate DNA typing.MethodsTo develop more candidate loci, the diversity value (D-value) was introduced as a new parameter for screening the novel polymorphic multiple linked-SNP markers, referred to as multi-SNP. In this study, a “FD Multi-SNP Mixture Kit” comprising 567 multi-SNPs was developed for mixture detection. Additionally, a new computational error correction method was applied as a quality control approach for sequencing data.ResultsThe results demonstrated higher typing success rates than the conventional CE typing method. For single-source DNA, approximately 70–80 loci were detected with a DNA input of 0.009765625 ng. More than 65% of the minor alleles were distinguishable at 1 ng DNA with a frequency of 0.5% in 2- to 4-person mixtures.ConclusionThis study offers a polymorphic and high-resolution detection method for DNA genotyping and complex mixture detection, providing an alternative strategy for addressing challenging mixed DNA traces.

Abstract Regional population mortality correlates with regional socioeconomic development. This study aimed to identify the key socioeconomic factors influencing mortality patterns in Chinese provinces. Using data from the Seventh Population Census, we analyzed mortality patterns by gender and urban‒rural division in 31 provinces. Using a functional regression model, we assessed the influence of fourteen indicators on mortality patterns. Main findings: (1) China shows notable gender and urban‒rural mortality variations across age groups. Males generally have higher mortality than females, and rural areas experience elevated mortality rates compared to urban areas. Mortality in individuals younger than 40 years is influenced mainly by urban‒rural factors, with gender becoming more noticeable in the 40–84 age group. (2) The substantial marginal impact of socioeconomic factors on mortality patterns generally becomes evident after the age of 45, with less pronounced differences in their impact on early-life mortality patterns. (3) Various factors have age-specific impacts on mortality. Education has a negative effect on mortality in individuals aged 0–29, extending to those aged 30–59 and diminishing in older age groups. Urbanization positively influences the probability of death in individuals aged 45–54 years, while the impact of traffic accidents increases with age. Among elderly people, the effect of socioeconomic variables is smaller, highlighting the intricate and heterogeneous nature of these influences and acknowledging certain limitations.

Abstract In this comprehensive genome-wide study, we identified and classified 83 Xylanase Inhibitor Protein (XIP) genes in wheat, grouped into five distinct categories, to enhance understanding of wheat's resistance to Fusarium head blight (FHB), a significant fungal threat to global wheat production. Our analysis reveals the unique distribution of XIP genes across wheat chromosomes, particularly at terminal regions, suggesting their role in the evolutionary expansion of the gene family. Several XIP genes lack signal peptides, indicating potential alternative secretion pathways that could be pivotal in plant defense against FHB. The study also uncovers the sequence homology between XIPs and chitinases, hinting at a functional diversification within the XIP gene family. Additionally, the research explores the association of XIP genes with plant immune mechanisms, particularly their linkage with plant hormone signaling pathways like abscisic acid and jasmonic acid. XIP-7A3, in particular, demonstrates a significant increase in expression upon FHB infection, highlighting its potential as a key candidate gene for enhancing wheat's resistance to this disease. This research not only enriches our understanding of the XIP gene family in wheat but also provides a foundation for future investigations into their role in developing FHB-resistant wheat cultivars. The findings offer significant implications for wheat genomics and breeding, contributing to the development of more resilient crops against fungal diseases.

BackgroundIn recent years, regional high-temperature weather in summer occurs frequently in China. Heat stroke is the most representative meteorological disease caused by high temperature. In order to improve monitoring, early warning, prevention, and control of heat stroke, it is of great significance to understand the epidemiological characteristics of heat stroke and the associated impact of heatwave. ObjectiveTo understand the epidemiological characteristics of heat stroke cases in Jinan City, and to explore the effects of heatwave exposure on heat stroke. MethodsCase reports of heat stroke and daily data of meteorological factors in Jinan City from 2017 to 2022 were collected. We described the temporal, population, and regional distribution characteristics of heat stroke cases in Jinan City, and used a time-stratified case-crossover design combined with conditional logistic regression model to explore the effects of heatwave exposure on heat stroke under 12 heatwave definitions (different combinations of intensity and duration). The cut-off percentiles used for heatwave definitions were the 90th (P90), 95th (P95), 97.5th (P97.5), and 99th (P99) percentiles of daily mean temperature; the durations were ≥ 2 d, ≥ 3 d, and ≥ 4 d, respectively. Pi(k), where i is temperature threshold, and k is duration. For example, the definition of a heatwave was notated as P90(2), indicating that the daily mean temperature is ≥ P90 and lasts for ≥ 2 d. Alternatively, lag01 denotes the cumulative lag effect with a 1 d lag, and so on. ResultsA total of 1394 cases of heat stroke were reported in Jinan City from 2017 to 2022, including 581 mild cases and 813 severe cases, and 85 deaths were reported, with a cumulative fatality rate of 6.10%. The cases of heat stroke reported each year during the study period were concentrated from June to August and peaked in July (665 cases, 47.70%). The sex ratio of males to females in heat stroke cases was 2.02:1. A high incidence of heat stroke was in 50-89 years, with a smaller peak occurring in the age group of 50-59 years and a larger peak in the age group of 70-79 years, respectively. The high-incidence areas of heat stroke were distributed in the western part of Jinan City where city centers situated (Tianqiao District, 274 cases, 19.66%; Huaiyin District, 223 cases, 16.00%) and in the surrounding rural areas (Pingyin County, 254 cases, 18.22%). The effect of heatwave exposure on heat stroke was statistically significant during the study period. The largest effect estimates for the effect on heat stroke occurred under the heatwave definitions of P99(2), P97.5(3), and P97.5(4) at lag04, lag03, and lag04, where corresponding OR (95%CI) values were 9.27 (4.71, 14.24), 8.95 (6.17, 12.98), and 8.22 (4.91, 13.78), respectively. The exposure-response curve showed that the risk of heat stroke tended to increase with the increase of average daily temperature. ConclusionJuly is the key period for the occurrence of heat stroke among Jinan City residents, while male cases are predominant, more serious cases, age concentration in the 50-89 years. The occurrence of heatwave can further increase the risk of heat stroke with a significant lag effect.

Abstract Background A subset of Graves’ disease (GD) patients develops refractory hyperthyroidism, posing challenges in treatment decisions. The predictive value of baseline characteristics and early therapy indicators in identifying high risk individuals is an area worth exploration. Methods A prospective cohort study (2018–2022) involved 597 newly diagnosed adult GD patients undergoing methimazole (MMI) treatment. Baseline characteristics and 3-month therapy parameters were utilized to develop predictive models for refractory GD, considering antithyroid drug (ATD) dosage regimens. Results Among 346 patients analyzed, 49.7% developed ATD-refractory GD, marked by recurrence and sustained Thyrotropin Receptor Antibody (TRAb) positivity. Key baseline factors, including younger age, Graves’ ophthalmopathy (GO), larger goiter size, and higher initial free triiodothyronine (fT3), free thyroxine (fT4), and TRAb levels, were all significantly associated with an increased risk of refractory GD, forming the baseline predictive model (Model A). Subsequent analysis based on MMI cumulative dosage at 3 months resulted in two subgroups: a high cumulative dosage group (average ≥ 20 mg/day) and a medium–low cumulative dosage group (average

Endometriosis is an estrogen-dependent inflammatory gynecological disease whose pathogenesis is unclear. C-C motif chemokine ligand 18 (CCL18), a chemokine, is involved in several inflammatory diseases. In this study, we aimed to investigate the role of CCL18 in endometriosis and its underlying mechanisms. Human endometrium and peritoneal fluid were obtained from women with and without endometriosis for molecular studies. The expression level of CCL18 in each tissue sample was examined by RNA sequencing analysis, quantitative PCR analysis and immunohistochemistry staining. The effects of CCL18 on cell migration, tube formation and neurite growth were investigated in vitro using primary endometrial cells, human umbilical vein endothelial cells (HUVECs) and dorsal root ganglion (DRG) neurons, respectively. Moreover, the development of endometriosis in mice was studied in vivo by blocking CCL18. CCL18 was shown to be overexpressed in endometrial foci and peritoneal fluid in women with endometriosis and was positively correlated with endometriosis pain. In vitro, CCL18 promoted the migration of ectopic endometrial cells, tube formation of HUVECs, and nerve outgrowth of DRG neurons. More importantly, inhibition of CCL18 significantly suppressed lesion development, angiogenesis, and nerve infiltration in a mouse model of endometriosis. In conclusion, CCL18 may play a role in the progression of endometriosis by increasing endometrial cell migration and promoting neuroangiogenesis.

Background: Temperature affects influenza transmission; however, currently, limited evidence exists about its effect in China at the national and city levels as well as how temperature can be integrated into influenza interventions. Methods: Meteorological, pollutant, and influenza data from 201 cities in mainland China between 2013 and 2018 were analyzed at both the city and national levels to investigate the relationship between temperature and influenza prevalence. We examined the impact of temperature on the time-varying reproduction number (Rt) using generalized additive quasi-Poisson regression models combined with the distributed lag nonlinear model. Threshold temperatures were determined for seven regions based on the early warning threshold of serious influenza outbreaks, set at Rt = 1.2. A multivariate random-effects meta-analysis was employed to assess region-specific associations. The excess risk (ER) index was defined to investigate the correlation between Rt and temperature, modified based on seasonal and regional characteristics. Results: At the national level and in the central, northern, northwestern, and southern regions, temperature was found to be negatively correlated with relative risk, whereas the shapes of the data curves for the eastern, southwestern, and northeastern regions were not well defined. Low temperatures had an observable effect on influenza prevalence; however, the effects of high temperatures were not obvious. At an Rt of 1.2, the threshold temperatures for reaching a warning for serious influenza outbreaks were − 24.3 °C in the northeastern region, 16.6 °C in the northwestern region, and between 1℃ and 10 °C in other regions. Conclusion: The study findings revealed that temperature had a varying effect on influenza transmission trends (Rt) across different regions in China. By identifying region-specific temperature thresholds at Rt = 1.2, more effective early warning systems for influenza outbreaks could be tailored. These findings emphasize the significance of the region-specific adaptation of influenza prevention and control measures.

This study selects Beijing from 1980 to 2020 as the research area, utilizing high temporal resolution land use data to analyze through the habitat quality module of the InVEST model. Unlike previous research, this study employs the Theil-Sen Median method and Mann-Kendall test to analyze the trend changes in habitat quality more accurately. This method has significant advantages in dealing with non-linear and non-normally distributed data over long time series, providing a more accurate and reliable analysis of habitat quality trends. Methodologically, the study first collects and organizes the land use type data of Beijing from 1980 to 2020, then uses the habitat quality module of the InVEST model to process and analyze the data of each year, assessing the impact of different land use types on habitat quality. Subsequently, the Theil-Sen Median method and Mann-Kendall test are used to analyze the time series trend of habitat quality, to identify and quantify the trend and significance of habitat quality changes. The results show that over the past 40 years, the area of construction land in Beijing has significantly expanded, leading to a compression of other types of land. The spatial distribution of habitat quality shows a clear difference between the two sides divided by a line connecting the northeast and southwest, with the west side being the area of good habitat quality and the east side being poorer. In the past 10 years, the overall habitat quality has improved, but most areas still show a decreasing trend, especially in the western and northern mountainous areas where habitat quality has significantly declined. Based on these findings, it is recommended that future urban planning and land management should pay more attention to the protection and improvement of habitat quality, especially the restoration work for areas with poor habitat quality.

La intención de realizar esta investigación parte de las observaciones y reflexiones personales sobre la inserción y la inclusión de la comunidad china en la sociedad española. Para realizar un estudio a fondo, el presente trabajo se desarrolla centrándose en la transición escolar de alumnado inmigrado de origen chino al sistema educativo español. Por ello, nos acercamos a la vivencia migratoria y la experiencia escolar, siendo dos piezas clave para entender el proceso. Asimismo, buscamos reflexionar sobre las historias singulares construidas por los dos protagonistas, basado en varios factores principales como el idioma, el apoyo familiar entre otros aspectos. Empezamos con una reflexión sobre los retos y desafíos encarados por el alumnado inmigrado, la definición del migrante de la generación 1,5, y los conceptos en torno a la educación intercultural en España, a la raíz de cual surgen las preguntas que nos ayudarán a diseñar el estudio y a marcar los objetivos. De cara a la realización, nos situamos desde la metodología cualitativa, adoptando la entrevista semiestructurada a dos jóvenes de nacionalidad china como método de la recogida de información. Tras el análisis de los datos, se observa un papel de vital importancia que desempeña el profesorado en la transición del alumnado chino, en particular, en la expectativa académica del alumnado inmigrante y su potencialidad de finalizar con éxito sus estudios.

Abstract Sparganii Rhizoma-Curcumae Rhizoma (SR-CR) is a classic drug pair for the treatment of castration-resistant prostate cancer (CRPC), but its mechanism has not been clarified. The study aims to elucidate the potential mechanism of SR-CR in the management of CRPC. The present study employed the TCMSP as well as the SwissTargetPrediction platform to retrieve the chemical composition and targets of SR-CR. The therapeutic targets of CRPC were identified through screening the GeneCards, Disgenet, and OMIM databases. Subsequently, the Venny online platform was utilized to identify the shared targets between the SR-CR and CRPC. The shared targets were enrichment analysis using the Bioconductor and Kyoto encyclopedia of genes and genomes (KEGG) databases. The active ingredients and core targets were verified through molecular docking and were validated using PC3 cells in the experimental validation phase. A total of 7 active ingredients and 1126 disease targets were screened from SR-CR, leading to a total of 59 shared targets. Gene Ontology (GO) analysis resulted in 1309 GO entries. KEGG pathways analysis yielded 121 pathways, primarily involving cancer-related signaling pathways. The results from molecular docking revealed stable binding interactions between the core ingredients and the core targets. In vitro cellular assays further demonstrated that SR-CR effectively suppressed the activation of the Prostate cancer signaling pathway in PC3 cells, leading to the inhibition of cell proliferation and promotion of apoptosis. The SR-CR exert therapeutic effects on CRPC by inhibiting cell proliferation and promoting apoptosis through the Prostate cancer signaling pathway.

Desalination technology, including thermal and membrane methods, holds great promise as a viable solution to alleviate the scarcity of freshwater resources. The membrane distillation technology, among various membrane separation technologies, exhibits remarkable potential for economic and sustainable freshwater production due to its low energy consumption and exceptional desalination capability. However, the performance of membrane distillation is significantly constrained by membrane fouling and temperature polarization, which severely impedes its large-scale implementation. Consequently, extensive research efforts have been devoted to membrane modification strategies aimed at enhancing fouling resistance and minimizing temperature polarization. Based on this foundation, the present study provides a concise overview of membrane fouling and temperature polarization, elucidating their detrimental impacts on the progress of membrane distillation. The present study provides an analysis of the current research status regarding the mitigation of membrane fouling through the development of specialized wettable surfaces and the reduction of temperature polarization via controlled heating. Furthermore, this work highlights the existing challenges faced by membrane distillation membranes. It is recommended that future research on membrane distillation membranes should focus on the following aspects: 1) Utilizing materials with high thermal conductivity and strong light absorption properties to fabricate membranes with limited field heating functionality and specialized wettable surfaces; 2) Developing a versatile membrane distillation system capable of accommodating feed liquids containing multiple pollutants; 3) Designing an integrated Janus membrane, incorporating a hydrophilic layer with high thermal conductivity and light absorption capabilities.

Abstract Osteoporosis is a widely observed condition characterized by the systemic deterioration of bone mass and microarchitecture, which increases patient susceptibility to fragile fractures. The intricate mechanisms governing bone homeostasis are substantially impacted by extracellular vesicles (EVs), which play crucial roles in both pathological and physiological contexts. EVs derived from various sources exert distinct effects on osteoporosis. Specifically, EVs released by osteoblasts, endothelial cells, myocytes, and mesenchymal stem cells contribute to bone formation due to their unique cargo of proteins, miRNAs, and cytokines. Conversely, EVs secreted by osteoclasts and immune cells promote bone resorption and inhibit bone formation. Furthermore, the use of EVs as therapeutic modalities or biomaterials for diagnosing and managing osteoporosis is promising. Here, we review the current understanding of the impact of EVs on bone homeostasis, including the classification and biogenesis of EVs and the intricate regulatory mechanisms of EVs in osteoporosis. Furthermore, we present an overview of the latest research progress on diagnosing and treating osteoporosis by using EVs. Finally, we discuss the challenges and prospects of translational research on the use of EVs in osteoporosis.

Vehicular Edge Computing (VEC) is a promising technique to accommodate the computation-intensive and delay-sensitive tasks through offloading the tasks to the RoadSide-Unit (RSU) equipped with edge computing servers or neighboring vehicles. Nevertheless, the limited computation resources of edge computing servers and the mobility of vehicles make the offloading policy design very challenging. In this context, through considering the potential transmission gains brought by the mobility of vehicles, we propose an efficient computation offloading and resource allocation scheme in VEC networks with two kinds of offloading modes, i.e., Vehicle to Vehicle (V2V) and Vehicle to RSU (V2R). We define a new cost function for vehicular users by incorporating the vehicles’ offloading delay, energy consumption, and expenses with a differentiated pricing strategy, as well as the transmission gain. An optimization problem is formulated to minimize the average cost of all the task vehicles under the latency and computation capacity constraints. A distributed iterative algorithm is proposed by decoupling the problem into two subproblems for the offloading mode selection and the resource allocation. Matching theory-based and Lagrangian-based algorithms are proposed to solve the two subproblems, respectively. Simulation results show the proposed algorithm achieves low complexity and significantly improves the system performance compared with three benchmark schemes.

Chrysanthemum morifolium cv. Fubaiju (CMF) is regarded as one of the three most renowned varieties of white Chrysanthemum in China, and different extraction methods have significant effects on its composition and activities. Therefore, six extractions were used in this study to assess the effects on extracts. The basic chemical composition showed that hot water extract (Hw) had the highest total phenolic content, alkali water immersion-assisted hot water extract (Al) had the highest content of protein, and enzyme-assisted hot water extract (Enz) had the highest content of carbohydrate. The UPLC-Q-Exactive-MS results evinced the presence of 19 small-molecule compounds, including chlorogenic acid, caffeic acid, tuberonic acid glucoside, luteolin-7-O-rutinoside, and other substances. In addition, the antioxidant test found that the Hw exhibited the best 1,1-diphenyl-2-picrylhydrazyl (DPPH) (82.05 ± 1.59 mM TE/mg) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) (61.91 ± 0.27 mM TE/mg) scavenging ability. The anti-glycation test demonstrated that Enz possessed the most pronounced inhibitory effect on glycation products, including fructosamine and advanced glycation end products (AGEs). Additionally, the Enz also exhibited the most significant inhibitory effect on the protein oxidation product N’-formylkynurenine. The correlation analysis revealed that there was a close relationship between antioxidant properties and glycation resistance of extracts, and tuberonic acid glucoside, 1,3-di-O-caffeoylquinic acid, 1,4-Dicaffeoylquinic acid, quercetin-7-O-β-D-glucopyranoside, and isochlorogenic acid B were key small molecule components that affected activities. In summary, the extracts of CMF can be regarded as an excellent antioxidant and anti-glycosylation agent.

Abstract Matrix vesicles (MVs) have shown strong effects in diseases such as vascular ectopic calcification and pathological calcified osteoarthritis and in wound repair of the skeletal system due to their membranous vesicle characteristics and abundant calcium and phosphorus content. However, the role of MVs in the progression of osteoporosis is poorly understood. Here, we report that annexin A5, an important component of the matrix vesicle membrane, plays a vital role in bone matrix homeostasis in the deterioration of osteoporosis. We first identified annexin A5 from adherent MVs but not dissociative MVs of osteoblasts and found that it could be sharply decreased in the bone matrix during the occurrence of osteoporosis based on ovariectomized mice. We then confirmed its potential in mediating the mineralization of the precursor osteoblast lineage via its initial binding with collagen type I to achieve MV adhesion and the subsequent activation of cellular autophagy. Finally, we proved its protective role in resisting bone loss by applying it to osteoporotic mice. Taken together, these data revealed the importance of annexin A5, originating from adherent MVs of osteoblasts, in bone matrix remodeling of osteoporosis and provided a new strategy for the treatment and intervention of bone loss.

Abstract Background Cystic echinococcosis (CE) is a parasitic zoonotic disease caused by the larval stage of Echinococcus granulosus. The liver and lungs are the most common sites for infection. Infection of the intradural spine is rare. Case presentation A 45-year-old woman of Han ethnicity presented with a chronic history of recurrent lumbar pain. Magnetic resonance imaging of the lumbar spine revealed the classical characteristic of multiple cystic lesions of variable sizes, manifesting a “bunch of grapes” appearance, localized within the spinal canal at the L4–L5 vertebral level. In the meanwhile, metagenomic next-generation sequencing identified Echinococcosis granulosa. The patient underwent surgery to remove the cyst entirely and subsequently took albendazole 400 mg orally twice daily for 6 months. Conclusion Spinal CE should be suspected in patients with multiple spinal cystic lesions and zoonotic exposure. metagenomic next-generation sequencing serves as a robust diagnostic tool for atypical pathogens, particularly when conventional tests are inconclusive. Prompt and aggressive treatment for spinal cystic echinococcosis is imperative, and further research is warranted for improved diagnostic and therapeutic strategies.

Abstract Sand and Dust Storms (SDS) pose considerable health risks worldwide. Previous studies only indicated risk of SDS on overall mortality. This nationwide multicenter time-series study aimed to examine SDS-associated mortality risks extensively. We analyzed 1,495,724 deaths and 2024 SDS events from 1 February to 31 May (2013–2018) in 214 Chinese counties. The excess mortality risks associated with SDS were 7.49% (95% CI: 3.12–12.05%), 5.40% (1.25–9.73%), 4.05% (0.41–7.83%), 3.45% (0.34–6.66%), 3.37% (0.28–6.55%), 3.33% (0.07–6.70%), 8.90% (4.96–12.98%), 12.51% (6.31–19.08%), and 11.55% (5.55–17.89%) for ischemic stroke, intracerebral hemorrhagic stroke, hypertensive heart disease, myocardial infarction, acute myocardial infarction, acute ischemic heart disease, respiratory disease, chronic lower respiratory disease, and chronic obstructive pulmonary disease (COPD), respectively. SDS had significantly added effects on ischemic stroke, chronic lower respiratory disease, and COPD mortality. Our results suggest the need to implement public health policy against SDS.