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We delved into a category of output feedback nonlinear systems that are distinguished by unmodeled dynamics, quantized input delays, and dynamic uncertainties. We introduce a novel finite-time adaptive dynamic surface control scheme developed through the construction of a first-order nonlinear filter. This approach integrates Young's inequality with neural network technologies. Then, to address unmodeled dynamics, the scheme incorporates a dynamic signal and utilizes Radial Basis Function (RBF) neural networks to approximate unknown smooth functions. Furthermore, an auxiliary function is devised to mitigate the impact of input quantization delays on the system's performance. The new controller design is both simple and effective, addressing the "hasingularity" problems typically associated with traditional finite-time controls. Theoretical analyses and simulation outcomes confirm the effectiveness of this approach, guaranteeing that all signals in the system are confined within a finite period.

Abstract MicroRNAs(miRNAs) are promising biomarkers for early esophageal squamous cell carcinoma (ESCC) detection and prognostic prediction. This study aimed to explore the potential biomarkers and molecular pathogenesis in the early diagnosis of ESCC. Firstly, 48 differentially expressed miRNAs (DEMs) and 1319 differentially expressed genes (DEGs) were identified between 94 ESCC tissues and 13 normal esophageal tissues in TCGA. From miRNA–mRNA regulatory network, there are 6558 target genes of the 48 DEMs, where 400 target genes are also among 1319 DEGs. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment indicate that the 400 DEGs significantly enriched in cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and oocyte meiosis. And there are 66 DEGs among these six biological pathways, which we called GO-DEGs. From miRNA–mRNA regulatory network, 32 DEMs regulated the 66 GO-DEGs, where 22 DEMs were verified by different types of experiments in ESCC tissues, cells, or serum from the literature. For the other novel 10 DEMs, single-factor Cox regression analysis show that only hsa-miR-34b-3p showed no significant correlation with the overall survival of ESCC patients. Finally, we obtained the novel 9 ESCC-related DEMs, where three are down-regulated, and six are up-regulated. We analyzed the expression trends of target genes for five miRNAs and identified three significantly different miRNAs (hsa-miR-205-3p, hsa-miR-452-3p, and hsa-miR-6499-3p) confirmed by qPCR. Moreover, the stage-specific miRNAs were also suggested. These three qPCR validated miRNAs are also specific to the early stages of ESCC: hsa-miR-452-3p is specific to Stage I, II and III; hsa-miR-205-3p is specific in Stage II and III; and hsa-miR-6499-3p is Stage II specific. They might be the potential biomarkers for ESCC stage diagnosis. This study identified three novel miRNA markers potentially related to the diagnosis of ESCC and participated in the occurrence and development of ESCC through cell cycle, proteoglycans in cancer, p53 signaling pathway, protein digestion and absorption, transcriptional dysregulation in cancer, and signaling pathway for oocyte meiosis.

Lithium-ion batteries have been widely used as key carriers of electrochemical energy storage owing to their excellent performance. However, manufacturing defects or non-compliance with safety norms can easily trigger thermal runaway in lithium batteries, leading to safety accidents such as fires and explosions. This highlights the urgent need for advanced lithium battery fire suppression technology. This paper provides a comprehensive analysis of the fire characteristics and thermal runaway mechanisms of lithium batteries, based on a review of relevant literature. Additionally, it examines various fire extinguishing agents and strategies, highlighting the two primary requirements for managing and preventing thermal disasters associated with lithium batteries: fire suppression and cooling. For lithium battery fires, this study introduces and compares the fire extinguishing mechanisms, and the fire extinguishing and cooling efficiency of different types of extinguishing agents: gas-based, water-based, and solid agents. The comparison considers multiple perspectives, such as extinguishing and cooling capacity, insulation, toxicity, residue and cost. Notably, C6F12O exhibits excellent fire extinguishing capabilities, while water mist demonstrates superior cooling performance. To enhance fire extinguishing and cooling effects, new strategies and devices are analyzed, such as cooperative fire extinguishing, intermittent spray and fire extinguishing microcapsules. The study also summarizes the limitations of current extinguishing agents for suppressing lithium battery fires and the shortcomings of extinguishing strategies, offering several methods for improving the performance of extinguishing agents. Collaboration between early fire detection technology and fire suppression technology can achieve early warning and precise fire extinguishing effects. According to the specific characteristics of lithium battery fires, a comprehensive analysis from the perspectives of fire behavior, thermal behavior and system toxicity is essential. The development of an ideal extinguishing agent with high thermal conductivity, high insulation, clean, cost-effective and non-toxic byproducts can be achieved using additives or new formulations. By developing more efficient new extinguishing strategies, it is possible to effectively govern and prevent battery thermal disasters.

Abstract Background and objectives Lung cancer is one of the prevailing malignancies worldwide. Surgical interventions hold an important position in the treatment framework for lung cancer. Pleural metastasis is often assumed to be a surgical contraindication, but not all instances of pleural metastasis can be accurately identified before surgery. The question of how to address pleural metastasis detected intraoperatively is still undecided. Methods This retrospective study included 187 lung cancer patients who underwent surgery from 2005 to 2017 in whom pleural metastasis was discovered incidentally during the operation. Data on demographic, surgical, pathological, postoperative treatment, and survival information were collected for further analysis. Results For patients with intraoperatively detected pleural metastasis, two independent protective prognostic factors were receiving primary tumor resection (compared to only receiving pleural nodule biopsy, HR = 0.079, p = 0.022) and receiving postoperative adjuvant chemotherapy (HR = 0.081, p

Abstract By applying nonlinear mixed‐effect (NLME) models, model‐integrated evidence (MIE) approaches are able to analyze bioequivalence (BE) data with pharmacokinetic end points that have sparse sampling, which is problematic for non‐compartmental analysis (NCA). However, MIE approaches may suffer from inflation of type I error due to underestimation of parameter uncertainty and to the assumption of asymptotic normality. In this study, we developed a MIE BE analysis method that is based on a pre‐defined model and consists of several steps including model fitting, uncertainty assessment, simulation, and BE determination. The presented MIE approach has several improvements compared with the previously reported model‐integrated methods: (1) treatment, sequence, and period effects are only added to absorption parameters (such as relative bioavailability and rate of absorption) instead of all PK parameters; (2) a simulation step is performed to generate confidence intervals of the pharmacokinetic metrics for BE assessment; and (3) in an effort to maintain type I error, two more advanced parameter uncertainty evaluation approaches are explored, a nonparametric (case resampling) bootstrap, and sampling importance resampling (SIR). To evaluate the developed method and compare the uncertainty assessment methods, simulation experiments were performed for BE studies using a two‐way crossover design with different amounts of information (sparse to rich designs) and levels of variability. Based on the simulation results, the method using SIR for parameter uncertainty quantification controls type I error at the nominal level of 0.05 (i.e., the significance level set for BE evaluation) even for studies with small sample size and/or sparse sampling. As expected, our MIE approach for BE assessment exhibited higher power than the NCA‐based method, especially as the data becomes sparser and/or more variable.

Abstract Conventional approaches for establishing bioequivalence (BE) between test and reference formulations using non‐compartmental analysis (NCA) may demonstrate low power in pharmacokinetic (PK) studies with sparse sampling. In this case, model‐integrated evidence (MIE) approaches for BE assessment have been shown to increase power, but may suffer from selection bias problems if models are built on the same data used for BE assessment. This work presents model averaging methods for BE evaluation and compares the power and type I error of these methods to conventional BE approaches for simulated studies of oral and ophthalmic formulations. Two model averaging methods were examined: bootstrap model selection and weight‐based model averaging with parameter uncertainty from three different sources, either from a sandwich covariance matrix, a bootstrap, or from sampling importance resampling (SIR). The proposed approaches increased power compared with conventional NCA‐based BE approaches, especially for the ophthalmic formulation scenarios, and were simultaneously able to adequately control type I error. In the rich sampling scenario considered for oral formulation, the weight‐based model averaging method with SIR uncertainty provided controlled type I error, that was closest to the target of 5%. In sparse‐sampling designs, especially the single sample ophthalmic scenarios, the type I error was best controlled by the bootstrap model selection method.

Abstract Activation and selective oxidation of inert C(sp 3)–H bonds remain one of the most challenging tasks in current synthetic chemistry due to the inherent inertness of C(sp 3)–H bonds. In this study, inspired by natural monooxygenases, we developed a coordination polymer with naphthalenediimide (NDI)-based ligands and binuclear iron nodes. The mixed-valence FeIIIFeII species and chlorine radicals (Cl•) are generated via ligand-to-metal charge transfer (LMCT) between FeIII and chlorine ions. These Cl• radicals abstract a hydrogen atom from the inert C(sp 3)–H bond of alkanes via hydrogen atom transfer (HAT). In addition, NDI converts oxygen to 1O2 via energy transfer (EnT), which then coordinates to FeII, forming an FeIV = O intermediate for the selective oxidation of C(sp 3)–H bonds. This synthetic platform, which combines photoinduced EnT, LMCT and HAT, provides a EnT-mediated parallel multiphoton excitation strategy with kinetic synergy effect for selective C(sp 3)–H oxidation under mild conditions and a blueprint for designing coordination polymer-based photocatalysts for C(sp 3)–H bond oxidation.

Abstract Background Chronic heat stress (CHS) is a detrimental environmental stressor with a negative impact on the meat quality of broilers. However, the underlying mechanisms are not fully understood. This study investigates the effects of CHS on long non-coding RNA (lncRNA) expression and muscle injury in broilers, with a focus on its implications for meat quality. Results The results showed that CHS diminished breast muscle yield, elevated abdominal fat deposition, induced cellular apoptosis (P

Abstract The intrinsic oncogenic mechanisms and properties of the tumor microenvironment (TME) have been extensively investigated. Primary features of the TME include metabolic reprogramming, hypoxia, chronic inflammation, and tumor immunosuppression. Previous studies suggest that senescence‐associated secretory phenotypes that mediate intercellular information exchange play a role in the dynamic evolution of the TME. Specifically, hypoxic adaptation, metabolic dysregulation, and phenotypic shifts in immune cells regulated by cellular senescence synergistically contribute to the development of an immunosuppressive microenvironment and chronic inflammation, thereby promoting the progression of tumor events. This review provides a comprehensive summary of the processes by which cellular senescence regulates the dynamic evolution of the tumor‐adapted TME, with focus on the complex mechanisms underlying the relationship between senescence and changes in the biological functions of tumor cells. The available findings suggest that components of the TME collectively contribute to the progression of tumor events. The potential applications and challenges of targeted cellular senescence‐based and combination therapies in clinical settings are further discussed within the context of advancing cellular senescence‐related research.

Context Pancreatic ductal adenocarcinoma (PDAC), which is characterized by its malignant nature, presents challenges for early detection and is associated with a poor prognosis. Any strategy that can interfere with the beginning or earlier stage of PDAC greatly delays disease progression. In response to this intractable problem, the exploration of new drugs is critical to reduce the incidence of PDAC.Objective In this study, we summarize the mechanisms of pancreatitis-induced PDAC and traditional Chinese medicine (TCM) theory and review the roles and mechanisms of botanical drugs and their natural compounds that can inhibit the process of pancreatitis-induced PDAC.Methods With the keywords ‘chronic pancreatitis’, ‘TCM’, ‘Chinese medicinal formulae’, ‘natural compounds’, ‘PDAC’ and ‘pancreatic cancer’, we conducted an extensive literature search of the PubMed, Web of Science, and other databases to identify studies that effectively prevent PDAC in complex inflammatory microenvironments.Results We summarized the mechanism of pancreatitis-induced PDAC. Persistent inflammatory microenvironments cause multiple changes in the pancreas itself, including tissue damage, abnormal cell differentiation, and even gene mutation. According to TCM, pancreatitis-induced PDAC is the process of ‘dampness-heat obstructing the spleen and deficiency due to stagnation’ induced by a variety of pathological factors. A variety of botanical drugs and their natural compounds, such as Chaihu classical formulae, flavonoids, phenolics, terpenoids, etc., may be potential drugs to interfere with the development of PDAC via reshaping the inflammatory microenvironment by improving tissue injury and pancreatic fibrosis.Conclusions Botanical drugs and their natural compounds show great potential for preventing PDAC in complex inflammatory microenvironments.

Cerebral cavernous malformation (CCM) is a polygenic disease with intricate genetic interactions contributing to quantitative pathogenesis across multiple factors. The principal pathogenic genes of CCM, specifically KRIT1, CCM2, and PDCD10, have been reported, accompanied by a growing wealth of genetic data related to mutations. Furthermore, numerous other molecules associated with CCM have been unearthed. However, tackling such massive volumes of unstructured data remains challenging until the advent of advanced large language models. In this study, we developed an automated analytical pipeline specialized in single nucleotide variants (SNVs) related biomedical text analysis called BRLM. To facilitate this, BioBERT was employed to vectorize the rich information of SNVs, while a deep residue network was used to discriminate the classes of the SNVs. BRLM was initially constructed on mutations from 12 different types of TCGA cancers, achieving an accuracy exceeding 99%. It was further examined for CCM mutations in familial sequencing data analysis, highlighting an upstream master regulator gene fibroblast growth factor 1 (FGF1). With multi-omics characterization and validation in biological function, FGF1 demonstrated to play a significant role in the development of CCMs, which proved the effectiveness of our model. The BRLM web server is available at http://1.117.230.196.

Based on the daily temperature data of 99 national meteorological stations in Beijing-Tianjin-Hebei region from March to May 1961 to 2020， the statistical methods such as Mann-Kendall trend test were used to analyze spatial and temporal distribution characteristics of late spring coldness from frequency， duration days and ratio of occurring stations to all stations， and the risk probability of different levels of late spring coldness was evaluated based on the information diffusion theory.The results indicated that： In the past 30 years， 2570 cases of late spring coldness occurred at 99 national meteorological stations， with the mildest and the least severe.In terms of frequency， the mild and moderate late spring coldness decreased from north to south， while severe late spring coldness decreased from northeast to southwest， the mild， moderate-severe and the total late spring coldness were most in April， the inter-annual occurrence frequency showed a downward trend， with a significant decrease from March to May and May.In terms of total duration days， mild and severe late spring coldness decreased from northeast to southwest， with moderate late spring coldness showing a pattern of high in north and south and low in middle.The average duration days of mild late spring coldness at each station was not significantly different， while the difference was significant in moderate and severe late spring coldness， the average duration days increased sharply with the increase of level.The annual mean duration days of late spring coldness was 6.9 d·a-1， showing a downward trend， with a decrease rate of 1.5 d·（10a）-1.The ratio of the stations showed an inter-annual downward trend in duration days was 88.9%， with 35 stations showing a significant decrease and the southern region experiencing a greater decrease than the northern region.The inter-annual downward trend in ratio of late spring coldness stations in March to May and May was significant， with the highest ratios of mild and moderate-severe late spring coldness in April， and the ratio of mild late spring coldness was much higher than that of moderate-severe late spring coldness in each month.The risk of late spring coldness decreased in a stepwise manner as the level increased， The stations with risk was mild and a return period of about 2 years or less was about 34.3% of all stations， mainly in Beijing， Shijiazhuang， Xingtai and Handan； The stations with risk was moderate and a return period of 5~10 years and 10 years or less was about 90% of all stations， and the former was concentrated at the north and south ends of Beijing-Tianjin-Hebei region， while the latter was mostly located in the central part of Beijing-Tianjin-Hebei region.The risk of severe late spring coldness in the research area was relatively low， with up to 97% of severe stations with a return period of about 25 years or less.

Sweetpotato is an important crop whose roots are consumed by people worldwide. Meloidogyne enterolobii stands out as a highly deleterious variant among the species of root-knot nematode that causes significant damage in sweetpotato. In the present study, the activity of four nematicides against M. enterolobii was assessed both in vitro and in growth cabinet experiments. After 48 hours of exposure, fluopyram and cyclobutrifluram had a greater negative effect on the motility of M. enterolobii second-stage juveniles (J2s) compared to fluensulfone and hymexazol, with respective median effective concentration (EC50) values of 0.204, 0.423, 22.335 and 216.622 mg L−1. When M. enterolobii eggs were incubated for 72 hours at the highest concentration of each nematicides, the inhibitory hatching effect of cyclobutrifluram (2.5 mg L−1), fluopyram (1.25 mg L−1) and fluensulfone (80 mg L−1) surpassed 85%, whereas hymexazol (640 mg L−1) was only 67%. Similar results were observed in growth cabinet experiments as well. The disease index (DI) and gall index (GI) were significantly decreased by all four nematicides compared to the control. However, the application of hymexazol did not yield a statistically significant difference in the egg masses index compared to the control, a finding which may be attributed to its potentially limited penetrability through the eggshell barrier. Overall, this study has demonstrated that all four nematicides effectively suppress M. enterolobii in sweetpotato, and this is the first report on the nematicidal activity of cyclobutrifluram and hymexazol against M. enterolobii.

Abstract Compound heat anomalies associated with humidity, such as compound hot-dry events and hot-wet events, pose greater health risks than single heat anomalies. Here, we utilize ambulance dispatch data along with air temperature and relative humidity to study human impacts on these events in China. We show that relying solely on temperature without considering humidity may underestimate the health risks of these events on populations. Over the past 40 years, anthropogenic activities have increased hot-dry events by 2.34 times and decreased hot-wet events by 0.63 times, especially in the Yangtze River region, compared to natural forcing. We also speculate that, in the future up to 2060, under the carbon-neutral scenario, the frequencies of high health-risk hot-dry events and hot-wet events caused by human activities can be reduced by one-half and over one-fifth, respectively, compared to the high-emissions scenario. These findings provide guidance for assessing health risks under global warming.

Abstract Quadrotor unmanned aerial vehicles (QUAVs) have attracted significant research focus due to their outstanding Vertical Take-Off and Landing (VTOL) capabilities. This research addresses the challenge of maintaining precise trajectory tracking in QUAV systems when faced with external disturbances by introducing a robust, two-tier control system based on sliding mode technology. For position control, this approach utilizes a virtual sliding mode control signal to enhance tracking precision and includes adaptive mechanisms to adjust for changes in mass and external disruptions. In controlling the attitude subsystem, the method employs a sliding mode control framework that secures system stability and compliance with intermediate commands, eliminating the reliance on precise models of the inertia matrix. Furthermore, this study incorporates a deep learning approach that combines Particle Swarm Optimization (PSO) with the Long Short-Term Memory (LSTM) network to foresee and mitigate trajectory tracking errors, thereby significantly enhancing the reliability and safety of mission operations. The robustness and effectiveness of this innovative control strategy are validated through comprehensive numerical simulations.

Abstract Backgrounds To our knowledge, there is no available nationwide data on omicron symptom patterns in China mainland. We aim to determine the acute and long COVID-19 symptoms in the omicron-dominant period and to evaluate its association with risk factors. Methods We designed a cross-sectional nationwide study and data about self-reported symptoms were collected by an online platform named Wenjuanxing. Eligible participants were aged 25–65 years and were symptomatic. In this study, the ratios of the number of people of different ages and genders were weighted by the data from the Seventh National Census (2020 years), and validated by a published nationwide representative study through comparing smoking rates. Descriptive indicators were calculated for demographic characteristics, diagnosis ways, and duration time, acute symptoms, hospitalization, severity and long COVID-19 symptoms. And, the associations between risk factors and acute and long COVID-19 symptoms were analyzed by multivariable logistic regression models. Results A total of 32,528 individuals diagnosed as COVID-19 infection from October 1, 2022 to February 21, 2023 were included. The first three acute symptoms of COVID-19 infection were fever (69.90%), headache (62.63%), and sore throat (54.29%), respectively. The hospitalization rate within 7 days was 3.07% and symptoms disappearance rate within 21 days was 68.84%, respectively. Among 3983 COVID-19 patients with 3 months or more time difference between first infection and participation into the study, the long COVID-19 rate was 19.68% and the primary symptoms were muscle weakness (19.39%), headache (17.98%) and smell/taste disorder (15.18%). Age groups, smoking, marriage status and vaccination were risk factors for numbers of acute phase symptoms and long COVID-19 symptoms. Lastly, female and current smokers also showed more numbers of symptoms during acute infection period. Conclusions In Chinese mainland, our respondent indicated that current smokers and women were associated with acute COVID-19 symptoms, which should be treated with caution due to the lack of representative.

Abstract In geological engineering and related fields, accurately and quickly identifying lithology and assessing rock strength are crucial for ensuring structural safety and optimizing design. Traditional rock strength assessment methods mainly rely on field sampling and laboratory tests, such as uniaxial compressive strength (UCS) tests and velocity tests. Although these methods provide relatively accurate rock strength data, they are complex, time-consuming, and unable to reflect real-time changes in field conditions. Therefore, this study proposes a new method based on artificial intelligence and neural networks to improve the efficiency and accuracy of rock strength assessments. This research utilizes a Transformer + UNet hybrid model for lithology identification and an optimized ResNet-18 model for determining rock weathering degrees, thereby correcting the strength of the tunnel face surrounding rock. Experimental results show that the Transformer + UNet hybrid model achieves an accuracy of 95.57% in lithology identification tasks, while the optimized ResNet model achieves an accuracy of 96.13% in rock weathering degree determination. Additionally, the average relative error in tunnel face strength detection results is only 9.33%, validating the feasibility and effectiveness of this method in practical engineering applications. The multi-model neural network system developed in this study significantly enhances prediction accuracy and efficiency, providing robust scientific decision support for tunnel construction, thereby improving construction safety and economy.

Abstract Porous ceramics were synthesized using porcelain tile polishing residue (PTPR) and slaked lime (Ca(OH)2) as a reinforcing agent through a hydrothermal autoclaving method. The process parameters, including the quantity of slaked lime added, the hydrothermal autoclaving temperature, and the reaction duration, were optimized meticulously. The composition, structure, thermal and physical properties of the samples were thoroughly analyzed via Brunauer–Emmett–Teller (BET) measurements, powder X-ray diffraction (PXRD), and scanning electron microscopy (SEM). The results indicated that the incorporation of slaked lime and hydrothermal autoclaving led to the formation of calcium silicate hydrate, which corresponded with an enhancement in the strength of the sample. Notably, when the quantity of slaked lime added was optimized at 30 wt%, the formation of tobermorite (5CaO·6SiO2·5H2O) was detected. At a hydrothermal autoclaving temperature of 150 °C, the formation of only sheet-like calcium silicate hydrate was observed. In contrast, at an elevated temperature of 180 °C and 210 °C, needle-like tobermorite was successfully synthesized. The porous ceramic with the most favorable structure was obtained through autoclaving at 180 °C for 10 h with 30 wt% slaked lime, exhibiting a total pore volume of 0.11 mL/g, a specific surface area of 26.35 m2/g, and a mesoporous volume fraction of 90.40%.

Abstract Background Tooth autotransplantation (TAT) is a surgical procedure involving the extraction of a tooth from one location and its subsequent transplantation into another alveolar socket within the same individual. This innovative treatment approach holds significant promise. Nonetheless, the potential recipients exhibit a limited level of awareness and understanding of this procedure. This study investigated the knowledge, attitudes, and practices (KAP) among patients with combined dentition defects and non-functional impacted teeth toward TAT. Methods This web-based cross-sectional study was conducted between December 2022 and February 2023 at one hospital. A self-designed questionnaire was developed to collect demographic information of the patients and assess their knowledge, attitudes, and practices toward TAT. Results A total of 533 valid questionnaires were collected. The mean knowledge, attitude, and practice scores were 5.55 ± 2.38 (possible range: 0–10), 26.82 ± 2.46 (possible range, 8–40), and 27.45 ± 7.40 (possible range, 9–45), respectively. Conclusion The participants had insufficient knowledge, negative attitudes, and passive practices toward TAT. Targeted interventions should be implemented to improve the understanding and practice of TAT among patients with dentition defects.

Abstract Although the association between persistent hypertension and the compromise of both micro‐ and macro‐circulatory functions is well recognized, a significant gap in quantitative investigations exploring the interplay between microvascular and macrovascular injuries still exists. In this study, the authors looked into the relationship between brachial‐ankle pulse wave velocity (baPWV) and hypertensive retinopathy in treated hypertensive adults. The authors conducted a cross‐sectional study of treated hypertensive patients with the last follow‐up data from the China Stoke Primary Prevention Trial (CSPPT) in 2013. With the use of PWV/ABI instruments, baPWV was automatically measured. The Keith‐Wagener‐Barker classification was used to determine the diagnosis of hypertensive retinopathy. The odds ratio (OR) and 95% confidence interval (CI) for the connection between baPWV and hypertensive retinopathy were determined using multivariable logistic regression models. The OR curves were created using a multivariable‐adjusted restricted cubic spline model to investigate any potential non‐linear dose‐response relationships between baPWV and hypertensive retinopathy. A total of 8514 (75.5%) of 11,279 participants were diagnosed with hypertensive retinopathy. The prevalence of hypertensive retinopathy increased from the bottom quartile of baPWV to the top quartile: quartile 1: 70.7%, quartile 2: 76.1%, quartile 3: 76.7%, quartile 4: 78.4%. After adjusting for potential confounders, baPWV was positively associated with hypertensive retinopathy (OR = 1.05, 95% CI, 1.03–1.07, p

Abstract Background Wooden breast (WB) myopathy is a common myopathy found in commercial broiler chickens worldwide. Histological examination has revealed that WB myopathy is accompanied by damage to the pectoralis major (PM) muscle. However, the underlying mechanisms responsible for the formation of WB in broilers have not been fully elucidated. This study aimed to investigate the potential role of hypoxia-mediated programmed cell death (PCD) in the formation of WB myopathy. Results Histological examination and biochemical analysis were performed on the PM muscle of the control (CON) and WB groups. A significantly increased thickness of the breast muscle in the top, middle, and bottom portions (P

Abstract Radiotherapy combined with immune checkpoint blockade holds great promise for synergistic antitumor efficacy. Targeted radionuclide therapy delivers radiation directly to tumor sites. LNC1004 is a fibroblast activation protein (FAP)-targeting radiopharmaceutical, conjugated with the albumin binder Evans Blue, which has demonstrated enhanced tumor uptake and retention in previous preclinical and clinical studies. Herein, we demonstrate that 68Ga/177Lu-labeled LNC1004 exhibits increased uptake and prolonged retention in MC38/NIH3T3-FAP and CT26/NIH3T3-FAP tumor xenografts. Radionuclide therapy with 177Lu-LNC1004 induced a transient upregulation of PD-L1 expression in tumor cells. The combination of 177Lu-LNC1004 and anti-PD-L1 immunotherapy led to complete eradication of all tumors in MC38/NIH3T3-FAP tumor-bearing mice, with mice showing 100% tumor rejection upon rechallenge. Immunohistochemistry, single-cell RNA sequencing (scRNA-seq), and TCR sequencing revealed that combination therapy reprogrammed the tumor microenvironment in mice to foster antitumor immunity by suppressing malignant progression and increasing cell-to-cell communication, CD8+ T-cell activation and expansion, M1 macrophage counts, antitumor activity of neutrophils, and T-cell receptor diversity. A preliminary clinical study demonstrated that 177Lu-LNC1004 was well-tolerated and effective in patients with refractory cancers. Further, scRNA-seq of peripheral blood mononuclear cells underscored the importance of addressing immune evasion through immune checkpoint blockade treatment. This was emphasized by the observed increase in antigen processing and presentation juxtaposed with T cell inactivation. In conclusion, our data supported the efficacy of immunotherapy combined with 177Lu-LNC1004 for cancer patients with FAP-positive tumors.

Introduction: Entry into the viable but nonculturable (VBNC) state is a survival strategy adopted by bacteria to survive harsh environment. Although VBNC cells still have metabolic activity, they lose the ability to form colonies on nonselective culture media. Thus, conventional bacterial detection methods, such as plate counting, are unable to detect the presence of VBNC cells. When the environmental conditions are appropriate, VBNC cells can initiate resuscitation, posing a great risk to the safety of public health. The study of the VBNC resuscitation mechanism could provide new insights into the prevention and control of VBNC resuscitation. Objectives: Uncovering the molecular mechanism of VBNC cell resuscitation by investigating the role of O-antigen ligase (RfaL) in inhibiting the resuscitation of Escherichia coli O157:H7 in the VBNC state. Methods: RfaL was screened and verified as a resuscitation inhibitor of VBNC Escherichia coli O157:H7 by detecting resuscitation curve and time-lapse microscopy. The mechanism of RfaL impacts VBNC E. coli resuscitation was investigated by detecting the single cell ATP content, metabolomic changes, NAD(H) content and new protein biosynthesis of WT and ΔrfaL at different stage of resuscitation. Results: Mutation of rfaL, which encoded an O-antigen ligase, markedly shortened the resuscitating lag phase. Further studies indicated that ΔrfaL VBNC cells contained higher ATP levels, and ATP consumption during the resuscitating lag phase was highly correlated with resuscitation efficiency. Metabolomic analysis revealed that ATP was utilized to activate the Handler and salvage pathways to synthesize NAD+, balancing redox reactions to recover cell activity and promote cell resuscitation. Conclusion: Our findings revealed a strategy employed by VBNC cells for revival, that is, using residual ATP to primarily recover metabolic activity, driving cells to exit dormancy. The synthesis pathway of lipopolysaccharide (LPS) in rfaL null mutant was inhibited and could supply more ATP to synthesis NAD+ and promote resuscitation.

Background: Codonopsis pilosula is a traditional herb widely used in Asian countries. As regulatory institutions increasingly acknowledge its medicinal and food-related characteristics, the attention from scholars is expected to increase rapidly. However, an overview and reports on research focus on this promising herb are currently lacking. Therefore, the objective of this study was to fill this knowledge gap by conducting a systematic review of relevant literature to explore the developing history and research focus on C. pilosula. This research is of significant importance in gaining a deeper understanding of the potential benefits and application areas of C. pilosula. Method: The output, institutions, countries, authors, highly cited publications, frontier focus and funding agencies of C. pilosula were analyzed using VOSviewer, CiteSpace, and COOC software. Results: The development of C. pilosula experienced 3 stages: initial stage (1979–2002), fast stage (2003–2012), and explosive stage (2013-present), with each stage showing linear growth. Worldwide attention from 1292 institutions in 27 countries have been paid, with China leading in output and collaboration. Lanzhou University in China contributed most publications with Fangdi Hu as a core specialist facilitating collaborations in agricultural and pharmacological research. A stable cooperation network has formed among researchers from different fields, focusing on pharmacological activity, chemical constituents, quality control, and medication rules. The research focus updated timely with new scientific frontiers occur. Medication rules, data mining, molecular docking, traditional Chinese medicine, gut microbiota, and polysaccharide are frontier focus presently and in the near future. Significant attention and funding have been provided by the national and local government of Gansu province in China. Conclusion: Research on C. pilosula is thriving, particularly in China, with a promising future in traditional Chinese medicine and pharmacology. This study provides valuable insights for future research directions and contributes to the effective development of C. pilosula.

At present, there are many reconstructed datasets at the global scale. To test the applicability of these datasets in the China seas, the study comprehensively analyzes the reliability and accuracy of reconstructed sea level datasets in capturing nuanced temporal patterns of sea level changes in the China Seas. This study applied analysis methods or indicators such as time series, Taylor plots, correlation coefficients, growth rates, and standard deviations. Ocean Data Assimilations (ODAs) outperform Tide Gauge Reconstructions (TGRs) in terms of correlation with measured data in the nearshore, while TGRs exhibit superior capability in capturing oceanic sea level variability. Although the ODAs and TGRs both suffer from the underestimation of sea level variability in China as well as in neighboring seas, the TGRs perform better than the former. ODAs show inconsistency in reflecting the rate of sea level rise, but they, particularly the China Ocean Reanalysis (CORA), demonstrate a better correlation with satellite altimetry datasets. Meanwhile, both of them can reflect the Pacific Decadal Oscillation (PDO) well. TGRs, relying on oceanic tide gauge stations, suffer from poor correlation with tide gauge stations due to limited coverage. Reconstruction discrepancies are attributed to methodological differences and data assimilation techniques. Future studies should explore alternative variables like sea surface temperature and so on to enhance sea-level reconstruction, especially in regions with sparse tide gauge coverage.

The phyllospheric microbial composition of tobacco plants is influenced by multiple factors. Disease severity level is one of the main influencing factors. This study was designed to understand the microbial community in tobacco wildfire disease with different disease severity levels. Tobacco leaves at disease severity level of 1, 5, 7, and 9 (L1, L5, L7, and L9) were collected; both healthy and diseased leaf tissues for each level were collected. The community structure and diversity in tobacco leaves with different disease severity levels were compared using high-throughput technique and Biolog Eco. The results showed that in all healthy and diseased tobacco leaves, the most dominant bacterial phylum was Proteobacteria with a high prevalence of genus Pseudomonas; the relative abundance of Pseudomonas was most found at B9 diseased samples. Ascomycota represents the most prominent fungal phylum, with Blastobotrys as the predominant genus. In bacterial communities, the Alpha diversity of healthy samples was higher than that of diseased samples. In fungal community, the difference in Alpha diversity between healthy and diseased was not significant. LEfSe analysis showed that the most enriched bacterial biomarker was unclassified_Gammaproteobacteria in diseased samples; unclassified_Alcaligenaceae were the most enrich bacterial biomarker in healthy samples. FUNGuild analysis showed that saprotroph was the dominated mode in health and lower diseased samples, The abundance of pathotroph–saprotroph and pathotroph–saprotroph–symbiotroph increases at high disease levels. PICRUSt analysis showed that the predominant pathway was metabolism function, and most bacterial gene sequences seem to be independent of the disease severity level. The Biolog Eco results showed that the utilization rates of carbon sources decrease with increasing disease severity level. The current study revealed the microbial community’s characteristic of tobacco wildfire disease with different disease severity levels, providing scientific references for the control of tobacco wildfire disease.

Summary: Background: Over 40% of pregnant women in the USA are obese which negatively affects fetal development and offspring health. Maternal obesity (MO) leads to fibrotic infiltration in multiple tissues and organs of offspring during their adulthood although the origin and mechanisms are unclear. Methods: C57BL/6J female mice were fed a control and high-fat diet to mimic MO condition. Embryonic somatic tissues were obtained at E9.5, E11.5, and E13.5 (equivalent to 6 weeks of human pregnancy) from control (CON) and MO mice for single-cell RNA-sequencing (scRNA-seq). To explore the role of AMP-activated protein kinase (AMPK), AMPK was activated by metformin and A769662, and knocked out in embryonic mesenchymal cells (EMC) using AMPKα1 floxed mice. Findings: Using unsupervised clustering, we identified three major cell populations with fibrogenic capacity. Compared to CON, the population of fibrogenic cells increased dramatically (by ∼125%) due to MO, supporting an embryonic origin of fibrosis in the offspring. MO induced inflammatory response and elevated expression of transforming growth factor β (TGFβ) signalling and fibrogenic genes in embryos. MO inhibited AMPK and its activation by metformin and A769662 inhibited TGFβ signalling and fibrogenesis. Interpretation: MO profoundly enhances embryonic fibrogenesis, explaining the origin of fibrosis in the offspring of mothers living with obesity. Our data underscore the importance of early intervention, before 5–6 weeks of pregnancy, in improving embryonic development, and AMPK is an amiable target for suppressing excessive fibrogenesis in MO embryos to assist increasing populations of obese mothers having healthy children. Funding: This work was funded by National Institutes of Health Grant R01HD067449.

Background: Teacher well-being, encompassing emotional, psychological, and social dimensions, significantly influences teaching effectiveness. Understanding the factors that enhance teacher well-being and effectiveness is crucial, particularly amidst global teacher shortages and high turnover rates. Method: The present study gathered data from 252 university-level foreign language teachers from eight provinces in China. Participants completed measures assessing well-being (using the PERMA model), teaching effectiveness, and life satisfaction scales through online surveys. Data were analyzed using JASP and SPSS for regression and mediation analyses. Results: The findings revealed that Positive emotions and relationships significantly predicted life satisfaction, while accomplishment significantly predicted teaching effectiveness. Both teaching effectiveness and overall well-being were significant predictors of life satisfaction. However, teaching effectiveness did not significantly mediate the relationship between overall well-being and life satisfaction, indicating that these factors independently contribute to life satisfaction. Conclusion: Our findings share the inclusion of PERMA principles in enhancing teaching effectiveness and life satisfaction among foreign language teachers. Constructive future directions are suggested for professional development for improving teacher well-being and effectiveness.

IntroductionRadioresistance remains a significant challenge in the treatment of glioblastoma multiforme (GBM), the most prevalent and lethal brain cancer in adults. Metabolic alterations are known to contribute to radioresistance by activating antioxidant responses and promoting DNA repair. However, the role of circular RNAs in this process, particularly circFOXO3, is not well understood.MethodsIn this study, we investigated the expression of circFOXO3 in glioma cells exposed to radiation and in recurrent GBM tissues. We performed knockdown and overexpression experiments in vitro and in vivo to assess the effects of circFOXO3 on radiosensitivity. Metabolomic profiling was conducted to explore the metabolic changes associated with circFOXO3 overexpression following irradiation.ResultsOur results showed significant upregulation of circFOXO3 in glioma cells upon radiation exposure and in recurrent GBM tissues. Knockdown of circFOXO3 increased radiosensitivity both in vitro and in vivo, whereas overexpression of circFOXO3 attenuated radiosensitivity. Metabolomic analysis revealed substantial alterations in lipid and organic compound profiles between circFOXO3-overexpressing and control groups. Additionally, circFOXO3 suppression increased proapoptotic protein levels (Caspase 7 and Bax) and decreased anti-apoptotic protein Bcl-2 levels following radiotherapy.DiscussionThese findings demonstrate the pivotal role of circFOXO3 in promoting tumor radioresistance through metabolic modulation, suggesting that circFOXO3 could serve as a potential diagnostic and therapeutic target for GBM.

An ontology is a structured framework that categorizes entities, concepts, and relationships within a domain to facilitate shared understanding, and it is important in computational linguistics and knowledge representation. In this paper, we propose a novel framework to automatically extend an existing ontology from streaming data in a zero-shot manner. Specifically, the zero-shot ontology extension framework uses online and hierarchical clustering to integrate new knowledge into existing ontologies without substantial annotated data or domain-specific expertise. Focusing on the medical field, this approach leverages Large Language Models (LLMs) for two key tasks: Symptom Typing and Symptom Taxonomy among breast and bladder cancer survivors. Symptom Typing involves identifying and classifying medical symptoms from unstructured online patient forum data, while Symptom Taxonomy organizes and integrates these symptoms into an existing ontology. The combined use of online and hierarchical clustering enables real-time and structured categorization and integration of symptoms. The dual-phase model employs multiple LLMs to ensure accurate classification and seamless integration of new symptoms with minimal human oversight. The paper details the framework's development, experiments, quantitative analyses, and data visualizations, demonstrating its effectiveness in enhancing medical ontologies and advancing knowledge-based systems in healthcare.

ABSTRACT: Wooden breast (WB) myopathy is a common myopathy found in commercial broiler chickens worldwide. Although extensive research on WB has been conducted using transcriptomics, effectively screening and analyzing key target information remains a challenge. In this present study, 5 transcriptomic datasets obtained from the National Center for Biotechnology Information (NCBI) were used. A meta-analysis was conducted to identify meta-differentially expressed genes (meta-DEGs) involved in the response of broilers to WB myopathy. These meta-DEGs were further analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA), supplemented by protein-protein interaction (PPI) network construction to pinpoint hub genes. These analyses help to reveal key genes, pathways, and biological processes associated with WB myopathy. The results showed that 645 up-regulated and 99 down-regulated significant meta-DEGs (|log2FC| ≥0.6, P-Meta < 0.05, and present in at least 4 datasets) were identified. GO analysis showed that multiple fibrosis-related pathways/biological processes, such as cell adhesion, connective tissue development, and collagen-rich extracellular matrix, as well as calcium ion binding were significantly upregulated. PPI analysis identified TGFB3, COL1A1, COL1A2, and COL3A1 as central hub genes involved in the fibrotic processes. KEGG analysis revealed significant upregulation of apoptosis and lysosomal pathways, with an enrichment of Ca2+-related signals and lysosomal cathepsins within the apoptosis pathway. Additionally, GSEA indicated a suppression of the tricarboxylic acid (TCA) cycle and the mitochondrial electron transport chain (ETC) in WB myopathy, with PPI analysis also identifying specific hub genes associated with these pathways.In conclusion, our comprehensive analysis of meta-DEGs elucidated key biological processes and pathways implicated in WB myopathy, including fibrosis, apoptosis, altered calcium signaling, and metabolic disruption. The identification of specific hub genes offers avenues for further investigation into the pathogenesis of this condition, potentially guiding targeted therapeutic strategies.

ABSTRACT: This study aims to develop an experimental model of high lactate levels in broilers to mimic the condition of birds under stress or diseases and evaluate its consequent effects on meat quality. The injection sites and dosage effects were compared separately in 2 experiments. Experiment 1 includes 3 injection sites: intraperitoneal injection, intramuscular injection, and subcutaneous injection. Experiment 2 was a dosage experiment based on the results of Experiment 1: sodium lactate intraperitoneal injection group with 1.5, 3, 6 mM concentration. The results showed that injecting sodium lactate intraperitoneally, intramuscularly, or subcutaneously all significantly decreased body weight and breast muscle weight while elevating lactic acid levels in both the blood and breast muscle of broilers. Moreover, all 3 injection methods caused a significant reduction in pH24h and an increase in the shear force value of breast muscle. In addition, dose-response experiments of intraperitoneal injection showed that a concentration of 3 mM and 6 mM were significantly decreased body weight and breast muscle weight in broiler chickens, accompanied by a notable increase in breast muscle lactate content. Compared to the control group, intraperitoneal injections of 1.5 mM, 3 mM, and 6 mM sodium lactate treatments significantly reduced the yellowness values of the breast muscle. As the dose of sodium lactate increased, the shear force value of the breast meat exhibited linear and quadratic increments, while the drip loss decreased linearly. Intraperitoneal injection of 3 mM sodium lactate also significantly reduced the pH24h of broiler breast muscle. In addition, an increased dose of lactate injections up-regulated the glycolytic pathway responsible for endogenous lactate production in the breast muscle by upregulating the expression of phosphofructokinase, pyruvate kinase and lactate dehydrogenase A. In conclusion, intraperitoneal injection of sodium lactate at 3 mM directly increased breast muscle lactate levels, providing a valuable method for establishing a high-level lactate model in poultry.

BackgroundGlioma is the predominant malignant brain tumor that lacks effective treatment options due to its shielding by the blood-brain barrier (BBB). Astrocytes play a role in the development of glioma, yet the diverse cellular composition of astrocytoma has not been thoroughly researched.MethodsWe examined the internal diversity of seven distinct astrocytoma subgroups through single-cell RNA sequencing (scRNA-seq), pinpointed crucial subgroups using CytoTRACE, monocle2 pseudotime analysis, and slingshot pseudotime analysis, employed various techniques to identify critical subgroups, and delved into cellular communication analysis. Then, we combined the clinical information of GBM patients and used bulk RNA sequencing (bulk RNA-seq) to analyze the prognostic impact of the relevant molecules on GBM patients, and we performed in vitro experiments for validation.ResultsThe analysis of the current study revealed that C0 IGFBP7+ Glioma cells were a noteworthy subpopulation of astrocytoma, influencing the differentiation and progression of astrocytoma. A predictive model was developed to categorize patients into high- and low-scoring groups based on the IGFBP7 Risk Score (IGRS), with survival analysis revealing a poorer prognosis for the high-IGRS group. Analysis of immune cell infiltration, identification of genes with differential expression, various enrichment analyses, assessment of copy number variations, and evaluation of drug susceptibility were conducted, all of which highlighted their significant influence on the prognosis of astrocytoma.ConclusionThis research enhances comprehension of the diverse cell composition of astrocytoma, delves into the various factors impacting the prognosis of astrocytoma, and offers fresh perspectives on treating glioma.

BackgroundMultiple studies suggest a potential connection between the gut microbiome and asthma. Our objective is to use advanced genetic and metagenomic techniques to elucidate the causal relationships and underlying mechanisms between gut microbiota and asthma.MethodsThe study utilized comprehensive Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) analyses to examine the relationship between 119 gut microbiota genera and asthma, using publicly accessible genome-wide association studies (GWAS). The meta-analysis synthesized summary effect estimates obtained from LDSC, forward MR, and reverse MR. The MiBioGen collaboration, involving 18,340 individuals, identified genetic variations associated with gut bacteria. Asthma data were collected from the UK Biobank, FinnGen, and GERA, encompassing a total of 82,060 cases and 641,049 controls.ResultsLDSC analysis revealed significant negative genetic correlations between asthma and RuminococcaceaeUCG004 (Rg = −0.55, p = 7.66 × 10−5) and Subdoligranulum (Rg = −0.35, p = 3.61 × 10−4). Forward MR analysis suggested associations between Butyricicoccus (OR = 0.92, p = 0.01), Turicibacter (OR = 0.95, p = 0.025), Butyrivibrio (OR = 0.98, p = 0.047), and reduced asthma risk. Conversely, Coprococcus2 (OR = 1.10, p = 0.035) and Roseburia (OR = 1.07, p = 0.039) were associated with increased risk. Reverse MR analysis indicated significant associations between genetically predicted asthma and Eubacteriumxylanophilumgroup (Beta = −0.08, p = 9.25 × 10−7), LachnospiraceaeNK4A136group (Beta = −0.05, p = 1.26 × 10−4), and Eisenbergiella (Beta = 0.06, p = 0.015, Rg_P = 0.043).ConclusionThe findings underscore significant genetic correlations and causal relationships between specific gut microbiota and asthma. These insights highlight the potential of gut microbiota as both markers and modulators of asthma risk, offering new avenues for targeted therapeutic strategies.

IntroductionChildren are naturally curious and often have limited self-control, leading them to imitate both safe and dangerous actions. This study aimed to investigate whether dangerous cues could effectively inhibit children’s imitation of hazardous behaviors and to compare the effectiveness of picture cues versus word cues in reducing this imitation.MethodsSeventy-six children were divided into two groups: one group received picture cues, and the other received word cues. Both groups observed an agent grasping an object and were instructed to perform a corresponding keystroke response when a number appeared. A comparable group of adults was also included for reference.ResultsThe results demonstrated that picture cues were significantly more effective than word cues in reducing the children’s tendency to imitate dangerous actions.DiscussionThese findings suggest that picture cues are a more effective method for preventing imitation of risky behaviors in children, which has important implications for improving safety education and accident prevention strategies through the use of visual danger cues.

Abstract The flexible distribution network presents a promising architecture to accommodate highly integrated distributed generators and increasing loads in an efficient and cost-effective way. The distribution network is characterised by flexible interconnections and expansions based on soft open points, which enables it to dispatch power flow over the entire system with enhanced controllability and compatibility. Herein, we propose a multi-resource dynamic coordinated planning method of flexible distribution network that allows allocation strategies to be determined over a long-term planning period. Additionally, we establish a probabilistic framework to address source-load uncertainties, which mitigates the security risks of voltage violations and line overloads. A practical distribution network is adopted for flexible upgrading based on soft open points, and its cost benefits are evaluated and compared with that of traditional planning approaches. By adjusting the acceptable violation probability in chance constraints, a trade-off between investment efficiency and operational security can be realised.

Abstract Background Segmenting liver vessels from contrast-enhanced computed tomography images is essential for diagnosing liver diseases, planning surgeries and delivering radiotherapy. Nevertheless, identifying vessels is a challenging task due to the tiny cross-sectional areas occupied by vessels, which has posed great challenges for vessel segmentation, such as limited features to be learned and difficult to construct high-quality as well as large-volume data. Methods We present an approach that only requires a few labeled vessels but delivers significantly improved results. Our model starts with vessel enhancement by fading out liver intensity and generates candidate vessels by a classifier fed with a large number of image filters. Afterwards, the initial segmentation is refined using Markov random fields. Results In experiments on the well-known dataset 3D-IRCADb, the averaged Dice coefficient is lifted to 0.63, and the mean sensitivity is increased to 0.71. These results are significantly better than those obtained from existing machine-learning approaches and comparable to those generated from deep-learning models. Conclusion Sophisticated integration of a large number of filters is able to pinpoint effective features from liver images that are sufficient to distinguish vessels from other liver tissues under a scarcity of large-volume labeled data. The study can shed light on medical image segmentation, especially for those without sufficient data.

Extreme precipitation is exacerbating the burden of infectious diarrhea in the context of climate change, it is necessary to identify the critical and easy-to-intervene intermediate factors for public health strategies. Water quality may be the most important mediator, while relevant empirical evidence is limited. This study aimed to examine the role of water quality in the process of infectious diarrhea caused by extreme precipitation. Weekly infectious diarrhea cases, meteorological factors and water quality data in Yangtze River Basin in China between October 29, 2007 to February 19, 2017 were obtained. Two-stage statistical models were used to estimate city-specific extreme precipitation, water quality and infectious diarrhea relationships that were pooled to derive regional estimates. A causal mediation analysis was used to assess the mediation effect of water quality. In Yangtze River Basin, extreme precipitation events had a significant impact on infectious diarrhea (Incidence Rate Ratios [IRR]: 1.027, 95% Confidence Interval [CI]: 1.013∼1.041). After extreme precipitation events, the dissolved oxygen (DO) in surface water decreased (-0.123 mg/L, 95%CI: -0.159 mg/L∼-0.086 mg/L), while the un-ionized ammonia (NH(3)-N) increased (0.004 mg/L, 95%CI: 0.001 mg/L∼0.006 mg/L). The combined overall effect of DO and NH(3)-N on infectious diarrhea showed that both low and high concentrations were associated with an increased risk of infectious diarrhea. The causal mediation analysis showed that the mediation proportion of the two water quality indexes (DO and NH(3)-N) is 70.54% (P < 0.001). To reduce the health effects of extreme precipitation, in contrast to current population-oriented health strategies, those that take into account more direct and easy-to-intervene water quality indicators should be encouraged by future policies.

This research focuses on the challenge of defining the ellipsoidal boundaries of the reachable set (RS) for neutral-type dynamical systems with time delays. A novel analytical approach is proposed, leveraging the development of new Lyapunov functions and matrix inequality techniques. These methods provide powerful tools for determining the ellipsoidal boundaries of the system's RS. A comparative analysis, supported by numerical examples, demonstrates that the approach outlined in this study can accurately identify smaller yet effective RS boundaries compared to existing literature. This precise boundary determination offers significant theoretical support for state estimation and control design in dynamical systems, thereby enhancing their effectiveness and reliability in real-world applications.

Abstract Chemotherapy is an important therapuetic strategy for colorectal cancer (CRC), but chemoresistance severely affects its efficacy, and the underlying mechanism has not been fully elucidated. Increasing evidence suggests that lipid peroxidation imbalance-mediated ferroptosis is closely associated with chemoresistance. Hence, targeting ferroptosis pathways or modulating the tolerance to oxidative stress might be an effective strategy to reverse tumor chemoresistance. HtrA serine protease 1 (HTRA1) was screened out as a CRC progression- and chemoresistance-related gene. It is highly expressed in CRC cells and negatively correlated with the prognosis of CRC patients. Gain- and loss-of-function analyses demonstrated a stimulatory role of HTRA1 on the proliferation of CRC cells. The enrichment analysis of HTRA1-interacting proteins indicated the involvement of ferroptosis in the HTRA1-mediated chemoresistance. Moreover, electron microscope analysis, as well as the ROS and MDA levels in CRC cells also confirmed the effect of HTRA1 on ferroptosis. We also verified that HTRA1 could interact with SLC7A11 through its Kazal structural domain and up-regulate the expression of SLC7A11, which in turn inhibited the ferroptosis and leaded to the chemoresistance of CRC cells to 5-FU/L-OHP. Hence, we propose that HTRA1 may be a potential therapeutic target and a prognostic indicator in CRC.

Abstract Objective Alzheimer's disease (AD) is characterized by the progressive degeneration and damage of neurons in the brain. However, developing an accurate diagnostic assay using blood samples remains a challenge in clinic practice. The aim of this study was to explore senescence‐associated secretory phenotypes (SASPs) in peripheral blood using mass spectrometry based multi‐omics approach and to establish diagnostic assays for AD. Methods This retrospective study included 88 participants, consisting of 29 AD patients and 59 cognitively normal (CN) individuals. Plasma and serum samples were examined using high‐resolution mass spectrometry to identify proteomic and metabolomic profiles. Receiver operating characteristic (ROC) analysis was employed to screen biomarkers with diagnostic potential. K‐nearest neighbors (KNN) algorithm was utilized to construct a multi‐dimensional model for distinguishing AD from CN. Results Proteomics analysis revealed upregulation of five plasma proteins in AD, including RNA helicase aquarius (AQR), zinc finger protein 587B (ZNF587B), C‐reactive protein (CRP), fibronectin (FN1), and serum amyloid A‐1 protein (SAA1), indicating their potential for AD classification. Interestingly, KNN‐based three‐dimensional model, comprising AQR, ZNF587B, and CRP, demonstrated its high accuracy in AD recognition, with evaluation possibilities of 0.941, 1.000, and 1.000 for the training, testing, and validation datasets, respectively. Besides, metabolomics analysis suggested elevated levels of serum phenylacetylglutamine (PAGIn) in AD. Interpretation The multi‐omics outcomes highlighted the significance of the SASPs, specifically AQR, ZNF587B, CRP, and PAGIn, in terms of their potential for diagnosing AD and suggested neuronal aging‐associated pathophysiology.

Abstract Drug resistance represents a significant obstacle in cancer treatment, underscoring the need for the discovery of novel therapeutic targets. Ubiquitin-specific proteases (USPs), a subclass of deubiquitinating enzymes, play a pivotal role in protein deubiquitination. As scientific research advances, USPs have been recognized as key regulators of drug resistance across a spectrum of treatment modalities, including chemotherapy, targeted therapy, immunotherapy, and radiotherapy. This comprehensive review examines the complex relationship between USPs and drug resistance mechanisms, focusing on specific treatment strategies and highlighting the influence of USPs on DNA damage repair, apoptosis, characteristics of cancer stem cells, immune evasion, and other crucial biological functions. Additionally, the review highlights the potential clinical significance of USP inhibitors as a means to counter drug resistance in cancer treatment. By inhibiting particular USP, cancer cells can become more susceptible to a variety of anti-cancer drugs. The integration of USP inhibitors with current anti-cancer therapies offers a promising strategy to circumvent drug resistance. Therefore, this review emphasizes the importance of USPs as viable therapeutic targets and offers insight into fruitful directions for future research and drug development. Targeting USPs presents an effective method to combat drug resistance across various cancer types, leading to enhanced treatment strategies and better patient outcomes.

Abstract The emergence of drug-resistant Enterobacteriaceae carrying plasmid-mediated β-lactamase genes has become a significant threat to public health. Organisms in the Enterobacteriaceae family containing New Delhi metallo-β-lactamase‑1 (NDM-1) and its variants, which are capable of hydrolyzing nearly all β-lactam antibacterial agents, including carbapenems, are referred to as superbugs and distributed worldwide. Despite efforts over the past decade, the discovery of an NDM-1 inhibitor that can reach the clinic remains a challenge. Here, we identified oxidized glutathione (GSSG) as a metabolic biomarker for bla NDM-1 using a non-targeted metabolomics approach and demonstrated that GSSG supplementation could restore carbapenem susceptibility in Escherichia coli carrying bla NDM-1 in vitro and in vivo. We showed that exogenous GSSG promotes the bactericidal effects of carbapenems by interfering with intracellular redox homeostasis and inhibiting the expression of NDM-1 in drug-resistant E. coli. This study establishes a metabolomics-based strategy to potentiate metabolism-dependent antibiotic efficacy for the treatment of antibiotic-resistant bacteria.

Abstract This paper investigates the impact of economic policy uncertainty (EPU) on the dividend policy of listed companies, alongside its underlying mechanisms. Based on a panel data compilation from 4421 Chinese listed companies spanning 2007 to 2021, the research demonstrates that EPU significantly increases the cash dividends of listed companies. Our findings resolve endogeneity issues and are robust to different variable definitions. The influence is more significant among smaller, non-state-owned companies, as well as those with lower equity concentration and lower financial constraints. We further find that EPU heightens investors’ demand for dividends, increases agency costs, and reduces business growth opportunities to improve companies’ dividend distribution tendency. Moreover, we find that increasing dividend payout when EPU increases is aligned with shareholders’ wealth maximization objective.

Abstract The relatively short duration of available tide gauge records poses challenges for conducting comprehensive statistical analyses of storm surges in the Western North Pacific. To address this issue, we employ a convolutional neural network model to reconstruct the maximum daily storm surge at 160 tide gauges from 1900 to 2010 in the Western North Pacific. The reconstructed dataset serves multiple purposes. Firstly, it facilitates the identification of regions where notable changes in the storm surges have occurred in the past. Additionally, the dataset enables long-term analyses of the storm surge climate, offering insights into historical patterns and variations. Furthermore, it provides a solid foundation for conducting robust extreme value analyses. To ensure accessibility, the data are publicly available through a repository, allowing for easy access and utilization by the broader scientific community and the general public. Overall, our research contributes to the field of oceanography by providing a dataset that aids in understanding the historical storm surge dynamics in the Western North Pacific region.

Fermented milk is an important application form of probiotics in the food industry, which is rich in nutrition and unique in flavor, and has rapid market development. Compared with Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus and other fermentation strains, probiotics have a lower participation in the main fermentation process, but they have a certain effect on the texture, flavor and post-acidification of fermented milk through synergistic fermentation, affecting the quality of fermented milk. This paper reviews the effects of probiotics on the texture, flavor quality and post-acidification process of fermented milk, and analyzes the mechanisms of probiotics maintaining the texture of fermented milk by metabolism and producing EPS, improving the flavor quality of fermented milk by producing flavor compounds, and affecting the post-acidification process by affecting the growth of commercial starter cultures, and summarizes the relevant technologies to improve the stability of probiotics in fermented milk, in order to provide reference for the development and quality improvement of functional fermented milk.

Recent teaching trends are increasingly integrating diverse multimedia and computer-aided practices to enhance representation and understanding. Leveraging data-focused strategies, these methods are further refined with artificial intelligence and decision-making techniques. To improve data handling in multimedia-based teaching representation, this article introduces an integrated data representation model aided by regression learning (IDR-RL). The proposed model satisfies the data required for different teaching methods/ subjects based on curriculum and student requirements. The data integration from different sources is performed using checksum assessment. The checksum assessment for data provides precise assimilation and content-related data-to-visual representation. In this representation, the checksums are verified for their linearity, wherein the saturation/ threshold factors are identified, and data integration is recommended. This recommendation is performed as the decision-making for preventing paused representation in live teaching sessions. The checksums are used for content coherency and complete data representations to prevent time lags in teaching. The proposed model’s performance is verified through data handling rate, integration ratio, pause time, representation time lag, and failures.

Abstract VEGFR-2 kinase inhibitors are clinically approved drugs that can effectively target cancer angiogenesis. However, such inhibitors have adverse effects such as skin toxicity, gastrointestinal reactions and hepatic impairment. In this study, machine learning and Topomer CoMFA, which is an alignment-dependent, descriptor-based method, were employed to build structural activity relationship models of potentially new VEGFR-2 inhibitors. The prediction ac-curacy of the training and test sets of the 2D-SAR model were 82.4 and 80.1%, respectively, with KNN. Topomer CoMFA approach was then used for 3D-QSAR modeling of VEGFR-2 inhibitors. The coefficient of q2 for cross-validation of the model 1 was greater than 0.5, suggesting that a stable drug activity-prediction model was obtained. Molecular docking was further performed to simulate the interactions between the five most promising compounds and VEGFR-2 target protein and the Total Scores were all greater than 6, indicating that they had a strong hydrogen bond interactions were present. This study successfully used machine learning to obtain five potentially novel VEGFR-2 inhibitors to increase our arsenal of drugs to combat cancer.

Abstract Obstruction and/or reflux compromise during venous emptying can facilitate different pathophysiologies in chronic venous insufficiency (CVI). We present a patient with persistent lower limb CVI edema caused by post-thrombotic syndrome (PTS), who responded well to femoral vein valve therapy via axillary vein bypass after unsuccessful valvuloplasty, and led a normal life. During a 12 month observation period, bridging vessels completely restored original anatomical structures. In a literature study, no similar surgeries were reported, but we show that this operation may be feasible in selected patients.