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Abstract Underwater friction stir welding (UFSW) achieves reliable joining between dissimilar materials and meets the welding demand for function and properties in lightweight structures of modern engineering. A defect monitoring method based on Variational Mode Decomposition optimized by Beluga Whale Optimization and Hilbert–Huang Transform (BWO–VMD–HHT) is proposed to solve the unclear feature of AE signal in UFSW due to the aqueous medium. UFSW experiments on Al alloy and carbon fiber reinforced thermoplastic (CFRTP) are carried out with AE signals measured. The time–frequency domain features of AE signals are extracted by BWO–VMD–HHT. The experimental results show that the main frequency of the AE signal is 22.5 kHz, and surface crack defects, shallow hole defects, and deep hole defects are accompanied by the transfer phenomena of different frequency components. Then, the feature vectors are built by frequency components in the BWO–VMD–HHT spectrum and reduced by principal component analysis, including 22.5 kHz, 24 kHz, 20.6 kHz, 18.4 kHz, 17.3 kHz, and 15.6 kHz. The feature vectors are divided into the train and test sets, and the welding defect prediction model (ResNet18-attention) is built by ResNet18 and trained by feature vectors. In the test set, the ResNet18-attention is compared with the BP, SVM, and RBF. Test results show that the precision of models has improved by at least 10%, which are trained by BWO–VMD–HHT features vector. Also, ResNet18-attention has achieved an average precision of 0.906 and recognizes the category of weld defect accurately, and this method can be applied to the defect monitoring of UFSW.

Abstract Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces “GENESO,” a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called “Symmetrical Occlusion (SO)”. It collaborates with the baseline LSTM network, mimicking the “gain of function” and “loss of function” of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

Abstract Background The role of lifestyle factors and their relative contributions to the development and mortality of cardio-renal-metabolic multimorbidity (CRMM) remains unclear. Methods A study was conducted with 357,554 UK Biobank participants. CRMM was defined as the coexistence of two or three cardio-renal-metabolic diseases (CRMDs), including cardiovascular disease (CVD), type 2 diabetes (T2D) and chronic kidney disease (CKD). The prospective study examined the associations of individual and combined lifestyle scores (diet, alcohol consumption, smoking, physical activity, sedentary behavior, sleep duration and social connection) with longitudinal progression from healthy to first cardio-renal-metabolic disease (FCRMD), then to CRMM, and ultimately to death, using a multistate model. Subsequently, quantile G-computation was employed to assess the relative contribution of each lifestyle factor. Results During a median follow-up of 13.62 years, lifestyle played crucial role in all transitions from healthy to FCRMD, then to CRMM, and ultimately to death. The hazard ratios (95% CIs) per score increase were 0.91 (0.90, 0.91) and 0.90 (0.89, 0.91) for healthy to FCRMD, and for FCRMD to CRMM, and 0.84 (0.83, 0.86), 0.87 (0.86, 0.89), and 0.90 (0.88, 0.93) for mortality risk from healthy, FCRMD, and CRMM, respectively. Among the seven factors, smoking status contributed to high proportions for the whole disease progression, accounting for 19.88–38.10%. High-risk diet contributed the largest proportion to the risk of transition from FCRMD to CRMM, with 22.53%. Less-frequent social connection contributed the largest proportion to the risk of transition from FCRMD to death, with 28.81%. When we further consider the disease-specific transitions, we find that lifestyle scores had slightly stronger associations with development to T2D than to CVD or CKD. Conclusions Our study indicates that a healthy lifestyle may have a protective effect throughout the longitudinal progression of CRMM, informing more effective management and treatment. Smoking status, diet, and social connection played pivotal roles in specific disease transitions.

Abstract Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the ‘hotspots’, which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where ‘hotspots’ are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10−14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

Abstract Background The link between nonalcoholic fatty liver disease and type 2 diabetes has not been fully established. We investigated the temporal relationship between nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D), quantitatively assessed the impact, and evaluated the related mediation effect. Methods This study involved participants from the China Multi-Ethnic Cohort Study and the UK Biobank. We performed cross-lagged path analysis to compare the relative magnitude of the effects between NAFLD and T2D using two-period biochemical data. Hepatic steatosis and fasting blood glucose elevation (FBG) represented NAFLD and T2D respectively. We fitted two separate Cox proportional-hazards models to evaluate the influence of hepatic steatosis on T2D. Furthermore, we applied the difference method to assess mediation effects. Results In cross-lagged path analyses, the path coefficients from baseline hepatic steatosis to first repeat FBG (β CMEC = 0.068, β UK−Biobank = 0.033) were significantly greater than the path coefficients from baseline FBG to first repeat hepatic steatosis (β CMEC = 0.027, β UK−Biobank = -0.01). Individuals with hepatic steatosis have a risk of T2D that is roughly three times higher than those without the condition (HR = 3.478 [3.314, 3.650]). Hepatic steatosis mediated approximately 69.514% of the total effect between obesity and follow-up T2D. Conclusions Our findings contribute to determining the sequential relationship between NAFLD and T2D in the causal pathway, highlighting that the dominant pathway in the relationship between these two early stages of diseases was the one from hepatic steatosis to fasting blood glucose elevation. Individuals having NAFLD face a significantly increased risk of T2D and require long-term monitoring of their glucose status as well.

Abstract In the realm of video salient object detection (VSOD), the majority of research has traditionally been centered on third‐person perspective videos. However, this focus overlooks the unique requirements of certain first‐person tasks, such as autonomous driving or robot vision. To bridge this gap, a novel dataset and a camera‐based VSOD model, CaMSD, specifically designed for egocentric videos, is introduced. First, the SalEgo dataset, comprising 17,400 fully annotated frames for video salient object detection, is presented. Second, a computational model that incorporates a camera movement module is proposed, designed to emulate the patterns observed when humans view videos. Additionally, to achieve precise segmentation of a single salient object during switches between salient objects, as opposed to simultaneously segmenting two objects, a saliency enhancement module based on the Squeeze and Excitation Block is incorporated. Experimental results show that the approach outperforms other state‐of‐the‐art methods in egocentric video salient object detection tasks. Dataset and codes can be found at https://github.com/hzhang1999/SalEgo.

Ossification of the sacrotuberous ligament is a rare occurrence in soft tissue, with only 15 cases reported in the past few decades. We reported two cases of bilateral ossification in sacrotuberous ligaments and provided a concise review of the literature on this pathology. Clinical data, radiographic outcomes, and diagnostic and treatment details were obtained. This study aimed to summarize this disease's characteristics and investigate its pathogenesis through a review of literature from the last thirty years. This condition is often incidentally confirmed in elderly males via imagiological examination or gross anatomy and presents a low morbidity rate. Its pathogenesis may be related to stress concentration, excessive intake of element ions, injury repair, and improper operative technique. The majority of patients may not exhibit any clinical symptoms or signs and typically do not require medical interventions. It may be complicated with pudendal nerve entrapment syndrome. The long‐term effects of surgical resection and the most effective treatment approach remain areas for further research.

Abstract Relative permeability (RP) curves which provide fundamental insights into porous media flow behavior serve as critical parameters in reservoir engineering and numerical simulation studies. However, obtaining accurate RP curves remains a challenge due to expensive experimental costs, core contamination, measurement errors, and other factors. To address this issue, an innovative approach using deep learning strategy is proposed for the prediction of rock sample RP curves directly from mercury injection capillary pressure (MICP) measurements which include the mercury injection curve, mercury withdrawal curve, and pore size distribution. To capture the distinct characteristics of different rock samples' MICP curves effectively, the Gramian Angular Field (GAF) based graph transformation method is introduced for mapping the curves into richly informative image forms. Subsequently, these 2D images are combined into three-channel red, green, blue (RGB) images and fed into a Convolutional Long Short-Term Memory (ConvLSTM) model within our established self-supervised learning framework. Simultaneously the dependencies and evolutionary sequences among image samples are captured through the limited MICP-RP samples and self-supervised learning framework. After that, a highly generalized RP curve calculation proxy framework based on deep learning called RPCDL is constructed by the autonomously generated nearly infinite training samples. The remarkable performance of the proposed method is verified with the experimental data from rock samples in the X oilfield. When applied to 37 small-sample data spaces for the prediction of 10 test samples, the average relative error is 3.6%, which demonstrates the effectiveness of our approach in mapping MICP experimental results to corresponding RP curves. Moreover, the comparison study against traditional CNN and LSTM illustrated the great performance of the RPCDL method in the prediction of both S o and S w lines in oil–water RP curves. To this end, this method offers an intelligent and robust means for efficiently estimating RP curves in various reservoir engineering scenarios without costly experiments.

Abstract We previously showed that MYC promoted Burkitt lymphoma (BL) growth by inhibiting the tumor suppressor miR-150, resulting in release of miR-150 targets MYB and ZDHHC11. The ZDHHC11 gene encodes three different transcripts including a mRNA (pcZDHHC11), a linear long non-coding RNA (lncZDHHC11) and a circular RNA (circZDHHC11). All transcripts contain the same region with 18 miR-150 binding sites. Here we studied the relevance of circZDHHC11, including this miR-150 binding site region, for growth of BL cells. CircZDHHC11 was mainly present in the cytoplasmic fraction in BL cells and its localization was not altered upon miR-150 overexpression. Knockdown of circZDHHC11 caused a strong inhibition of BL growth without affecting the expression levels of MYC, MYB, miR-150 and other genes. Overexpression of circZDHHC11 neither affected cell growth, nor rescued the phenotype induced by miR-150 overexpression. Genomic deletion of the miR-150 binding site region did not affect growth, nor did it change the effect of circZDHHC11 knockdown. This indicated that the miR-150 binding site region is dispensable for the growth promoting role of circZDHHC11. To conclude, our results show that circZDHHC11 is a crucial factor supporting BL cell growth independent of its ability to sponge miR-150.

Abstract Background Despite the importance of medication adherence in treatment effectiveness, little is known about the association between medication non-adherence and self-inflicted violence behaviors. We aimed to assess whether medication non-adherence increased the risk of self-inflicted violence behaviors among schizophrenics in communities (hypothesis 1) and whether the dose–response relationship existed (hypothesis 2). Methods This 12-year cohort study in western China recruited 292,667 community-dwelling schizophrenics. The proportion of regular medication (PRM) was calculated by dividing the time of “regular adherence” by the total time of antipsychotic treatment during follow-up period as an indicator of medication adherence. For hypothesis 1, medication adherence was designated as a binary variable with a threshold of 0.8 (PRM); for hypothesis 2, medication adherence was specified as five-category and continuous variables, respectively. Inverse probability weighting and mixed effects Cox proportional hazards models were conducted for confounders control and survival analyses. Results One hundred eighty-five thousand eight hundred participants were eligible for the final analyses, with a mean age of 47.49 years (SD 14.55 years), of whom 53.6% were female. For hypothesis 1, the medication non-adherence group (PRM

Abstract Background Chimeric antigen receptor natural killer (CAR-NK) cells represent a promising advancement in CAR cell therapy, addressing limitations observed in CAR-T cell therapy. However, our prior study revealed challenges in CAR-NK cells targeting CD19 antigens, as they failed to eliminate CD19+ Raji cells in NSG tumor-bearing mice, noting down-regulation or loss of CD19 antigen expression in some Raji cells. In response, this study aims to enhance CD19 CAR-NK cell efficacy and mitigate the risk of tumor recurrence due to target antigen escape by developing CD19 and CD20 (CD19/CD20) dual-targeted CAR-NK cells. Methods Initially, mRNA encoding anti-CD19 CARs (FMC63 scFv-CD8α-4-1BB-CD3ζ) and anti-CD20 CARs (LEU16 scFv-CD8α-4-1BB-CD3ζ) was constructed via in vitro transcription. Subsequently, CD19/CD20 dual-targeted CAR-NK cells were generated through simultaneous electrotransfection of CD19/CD20 CAR mRNA into umbilical cord blood-derived NK cells (UCB-NK). Results Following co-electroporation, the percentage of dual-CAR expression on NK cells was 86.4% ± 1.83%, as determined by flow cytometry. CAR expression was detectable at 8 h post-electric transfer, peaked at 24 h, and remained detectable at 96 h. CD19/CD20 dual-targeted CAR-NK cells exhibited increased specific cytotoxicity against acute lymphoblastic leukemia (ALL) cell lines (BALL-1: CD19+CD20+, REH: CD19+CD20−, Jurkat: CD19−CD20−) compared to UCB-NK, CD19 CAR-NK, and CD20 CAR-NK cells. Moreover, CD19/CD20 dual-targeted CAR-NK cells released elevated levels of perforin, IFN-γ, and IL-15. Multiple activation markers such as CD69 and cytotoxic substances were highly expressed. Conclusions The creation of CD19/CD20 dual-targeted CAR-NK cells addressed the risk of tumor escape due to antigen heterogeneity in ALL, offering efficient and safe 'off-the-shelf' cell products. These cells demonstrate efficacy in targeting CD20 and/or CD19 antigens in ALL, laying an experimental foundation for their application in ALL treatment.

Idiopathic pulmonary fibrosis (IPF) is a progressive pulmonary disease that leads to interstitial inflammation, lung damage, and eventually life-threatening complications. Among various pathologic factors, Smad4 is a pivotal molecule involved in the progression and exacerbation of IPF. It mediates nuclear transfer of Smad2/Smad3 complexes and initiates the transcription of fibrosis-promoting genes. Thus, the inhibition of Smad4 expression in pulmonary fibroblasts by small interfering RNAs (siRNAs) might be a promising therapeutic strategy for IPF. Herein, we engineered exosome membranes (EM) by cationic lipid (i.e., DOTAP) to load siRNAs against Smad4 (DOTAP/siSmad4@EM), and investigated their specific delivery to pulmonary fibroblasts for treating IPF in a mouse model via pulmonary administration. As reference nanoscaffolds, undecorated DOTAP/siSmad4 complexes (lipoplexes, consisting of cationic lipid DOTAP and siRNAs) and siSmad4-loaded lipid nanoparticles (DOTAP/siSmad4@lipo, consisting of lipoplexes fused with DPPCChol liposomes) were also prepared. The results showed that DOTAP/siSmad4@EM exhibited a higher cellular uptake and gene silencing efficacies in mouse pulmonary fibroblasts (viz., MLg2908) as compared to the two reference nanoscaffolds. Furthermore, the outcomes of the in vivo experiments illustrated that DOTAP/siSmad4@EM could significantly down-regulate the Smad4 expression with augmented anti-fibrosis efficiency. Additionally, the DOTAP/siSmad4@EM conferred excellent biocompatibility with low cytokine levels in bronchoalveolar lavage fluid and proinflammatory responses in the pulmonary area. Taken together, the outcomes of our investigation imply that specific inhibition of Smad4 expression in pulmonary fibroblasts by pulmonary administrated DOTAP/siSmad4@EM is a promising therapeutic strategy for IPF, which could safely and effectively deliver siRNA drugs to the targeted site of action.

IntroductionDandelion is widely used in clinical practice due to its beneficial effects. Polyphenolic compounds are considered the main anti-inflammatory active ingredient of dandelion, but the gene expression patterns of polyphenolic compounds in different dandelion tissues are still unclear.MethodsIn this study, we combined a nontargeted metabolome, PacBio Iso-seq transcriptome, and Illumina RNA-seq transcriptome to investigate the relationship between polyphenols and gene expression in roots, flowers, and leaves of flowering dandelion plants.ResultsEighty-eight flavonoids and twenty-five phenolic acids were identified, and 64 candidate genes involved in flavonoid biosynthesis and 63 candidate genes involved in chicoric acid biosynthesis were identified. Most flavonoid and chicoric acid-related genes demonstrated the highest content in flowers. RNA-seq analysis revealed that genes involved in polyphenol biosynthesis pathways, such as CHS, CHI, F3H, F3’H, FLS, HQT, and CAS, which are crucial for the accumulation of flavonoids and chicoric acid, were upregulated in flowers.DiscussionThe combination of transcriptomic and metabolomic data can help us better understand the biosynthetic pathways of polyphenols in dandelion. These results provide abundant genetic resources for further studying the regulatory mechanism of dandelion polyphenol biosynthesis.

Ultrasound-guided radiofrequency ablation (RFA) emerges as a minimally invasive strategy for papillary thyroid microcarcinoma (PTMC), offering advantages over traditional surgical approaches. RFA employs high-frequency electric currents under precise ultrasound guidance to ablate cancerous tissue. Clinical trials consistently demonstrate RFA’s efficacy in tumor control and patient-reported outcomes. However, long-term studies are essential to validate its durability and monitor for potential complications. Collaborative efforts among various medical disciplines ensure procedural accuracy and comprehensive postoperative care. Technological innovations, such as enhanced ultrasound imaging and temperature control, promise to refine RFA’s precision and effectiveness. Nevertheless, challenges persist, including the need for standardized protocols and comparative studies with traditional treatments. Future research should focus on long-term outcomes, patient selection criteria, and optimization of procedural techniques to solidify RFA’s role in PTMC management. RFA presents a promising avenue for PTMC treatment, warranting further investigation and refinement in clinical practice.

In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.

Abstract Background Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including “change-score analysis”, “concurrent change-change analysis” and “lagged change-change analysis”. Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection and comparison of these approaches from a causal inference perspective is lacking. We intend to explicitly elucidate and compare the underlying causal model, causal estimand and interpretation of these approaches, intuitively illustrate it with directed acyclic graph (DAG), and further clarify strengths and limitations of the recommended concurrent change-change analysis through simulations. Methods Causal model and DAG are deployed to clarify the causal estimand and interpretation of each approach theoretically. Monte Carlo simulation is used to explore the performance of distinct approaches under different extents of time-invariant heterogeneity and the performance of concurrent change-change analysis when its causal identification assumptions are violated. Results Concurrent change-change analysis targets the contemporaneous effect of exposure on outcome (measured at the same survey wave), which is more relevant and plausible in studying the associations of diet and intermediate biomarkers in prospective studies, while change-score analysis and lagged change-change analysis target the effect of exposure on outcome after one-period timespan (typically several years). Concurrent change-change analysis always yields unbiased estimates even with severe unobserved time-invariant confounding, while the other two approaches are always biased even without time-invariant heterogeneity. However, concurrent change-change analysis produces almost linearly increasing estimation bias with violation of its causal identification assumptions becoming more serious. Conclusions Concurrent change-change analysis might be the most superior method in studying the diet and intermediate biomarkers in prospective studies, which targets the most plausible estimand and circumvents the bias from unobserved individual heterogeneity. Importantly, careful examination of the vital identification assumptions behind it should be underscored before applying this promising method.

Abstract Objective Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM. Methods This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM. Results We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure). Conclusions Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA’s importance in reducing SIIM for all people, especially those living in high-level air pollution regions.

Abstract Background The prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) has been rising rapidly in western China. Diet acts as an effective therapy for MAFLD. However, there has been scarce research on the association between a posteriori diet patterns (DPs) and MAFLD in this region. Method We identified three a posteriori DPs which were “Sichuan Basin pattern” characterized by a high intake of fish/seafood, poultry, fresh fruit and vegetables, indicating a balanced and modern DP; the “Yunnan–Guizhou Plateau dietary pattern” characterized mainly by a high intake of animal oil and salt, indicating an agricultural and poor DP; and the “Qinghai–Tibet Plateau dietary pattern” characterized by a high intake of coarse grains, wheat products, tubers and tea, respectively, indicating a high-altitude DP. Then, we performed marginal structural models that combined logistic regression and inverse probability exposure weighting (IPEW) to examine the associations between MAFLD and these a posteriori DPs. Result We found the “Yunnan–Guizhou Plateau dietary pattern” revealed stronger positive association (OR = 1.50, 95% CI 1.40–1.60) with MAFLD than that of the “Qinghai–Tibet Plateau dietary pattern” (OR = 1.21, 95% CI 1.14–1.30). In contrast, the “Sichuan Basin dietary pattern” showed no significant association with MAFLD. In the further stratified analysis, we found those above associations were stronger in ethnic minorities and rural residents than their counterparts. Conclusion Our study implied the unfavourable effects of “Yunnan–Guizhou Plateau dietary pattern” on MAFLD and provided evidence that reducing the intake of oil and sodium may be optimal for MAFLD control in the multi-ethnic region in western China.

Background The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. Methods and Results A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1‐km2 grid were derived based on satellite‐ and ground‐based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P

Abstract Metabolic syndrome (MetS) is characterized by metabolic dysfunctions and could predict future risk for cardiovascular diseases (CVDs). However, the traditionally defined dichotomous MetS neither reflected MetS severity nor considered demographic variations. Here we develop a continuous, age-sex-ethnicity-specific MetS score based on continuous measures of the five metabolic dysfunctions (waist circumference [WC], triglycerides [TG], high-density lipoprotein cholesterol [HDL-C], mean arterial pressure [MAP], and fasting blood glucose [FBG]). We find that the weights of metabolic dysfunctions in the score vary across age-sex-ethnicity-specific subgroups, with higher weights for TG, HDL-C, and WC. Each unit increase in the score is associated with increased risks for hyperlipidemia, diabetes, and hypertension, and elevated levels of HbA1c, cholesterol, body mass index, and serum uric acid. The score shows high sensitivity and accuracy for detecting CVD-related risk factors and is validated in different geographical regions. Our study would advance early identification of CVD risks and, more broadly, preventive medicine and sustainable development goals.

Abstract Objective Little is known about the magnitude of the relation of ambient fine particulate matter (PM2.5) constituents with hyperuricemia and serum uric acid (SUA) levels. Therefore, we aimed to assess the associations and to identify the most hazardous constituent. Methods This study included 72,840 participants from the China Multi-Ethnic Cohort. Annual average concentrations of PM2.5 mass and its major 7 constituents were matched to individuals by residential address. SUA levels exceeding 7.0 mg/dL (417 μmol/L) for men and 6.0 mg/dL (357 μmol/L) for women were considered to be hyperuricemia. Multiple logistic and linear regressions were performed on the association of single exposure to PM2.5 constituents with hyperuricemia and SUA, separately. The weighted quantile sum method was applied to examine the joint effect of PM2.5 constituents on hyperuricemia/SUA. Results Significant positive associations were discovered between PM2.5 constituents and SUA/hyperuricemia. For example, the odds ratio (95% confidence interval) of hyperuricemia for per standard deviation increase of PM2.5 mass, black carbon, organic matter, ammonium, and nitrate concentrations were 1.22 (1.12–1.32), 1.17 (1.08–1.27), 1.20 (1.10–1.31), 1.21 (1.11–1.31), and 1.28 (1.18–1.40), respectively. The joint exposure to PM2.5 constituents was significantly positively correlated with hyperuricemia (1.09, 1.05–1.14) and SUA (1.05, 1.03–1.06). And the weight of nitrate was the largest (0.668 for hyperuricemia, 0.586 for SUA). Conclusions Our findings suggest that long-term exposure to PM2.5 constituents is associated with increased SUA levels and a higher risk of hyperuricemia. In particular, nitrate seems to be the main contributor. This study may help prevent hyperuricemia by promoting the introduction of precise preventive measures. Graphical Abstract

Due to its good mechanical robustness and field control capacity, the DC-excited Vernier reluctance machine (DC-VRM) is a promising candidate for electrical vehicle propulsion. However, the conventional design of this machine suffers from large excitation copper loss and leading to low efficiency, due to an identical distribution of DC excitation coils at the stator side. This paper proposes a novel efficiency-enhanced DC-VRM. The key technology is based on the flux modulation mechanism to reduce DC field coils and mitigate DC copper loss while keeping the excitation ability and power density not sacrificed. In this paper, the machine configuration and operation principle are introduced. A combination of the magneto-static finite element and the analytical method is used to quantitatively analyze the contribution of different harmonics on the phase EMF under two different DC layouts. The feasibility of the proposed topology is further verified by a transient finite element analysis, which proves that, with the same design parameters, the proposed design achieves higher back EMF and output torque per DC copper loss. Therefore, this new topology enhances efficiency and can be a more promising non-PM machine for EVs.

High-entropy oxides (HEOs) have received significant attention because of their tunable mechanical properties and wide range of functional applications. However, the conventional method used for sintering HEOs requires prolonged processing time, which results in excessive grain growth, thereby compromising their performance. Here, an ultrafast high-temperature sintering (UHS) strategy was adopted, and rock-salt composite (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)O was selected as model materials. Experimental parameters were tuned to illustrate the influence of applied current and soaking time on the densification process and resulting grain size. Additionally, the electrochemical performance of UHS-synthesized microparticles as anode materials in lithium-ion batteries was investigated. The results show that the ultrafast heating rate results in fine grains with a diameter of ~6–8 μm and density of 95%, which are much smaller and similar to those obtained using the conventional sintering method (25 μm and 96%). Moreover, the high surface area and reactivity of the microparticles, as well as their sluggish diffusion effect and structural stability, contribute to outstanding performance with high capacity (336 mA·h/g at 1 A/g) and ultralong cyclability (1000 cycles). This novel technique offers valuable insights into the densification process of HEOs and other materials and can thus broaden their application range.

Based on the current situation of emergency recovery equipment of offshore oil spill and the difficulties of offshore heavy oil spill recovery, this paper introduced multiple types of oil spill recovery equipment according to the differences in working principles. The configuration of oil spill recovery equipment in the emergency equipment warehouse of national, local government and oil spill emergency professional company was statistically analyzed. This paper focused on the problems of the existing oil spill recovery equipment in the process of heavy oil leakage disposal, such as the lack of targeted structural design, the lack of heavy oil pumping and transmission capacity, and the lack of pressure bearing capacity of the oil pipeline. Finally, the new oil skimmer and pumping system designed by overseas oil spill emergency equipment manufacturers were introduced to solve the difficult problem of heavy oil recovery, which could provide technical reference for the research of offshore heavy oil recovery equipment in China.

Abstract Doubly salient electromagnetic machine (DSEM) can constitute a competitive rugged starter generator (SG) system. But under the traditional startup control method, the field current is set to the rated value regardless of speed or load torque conditions, and the phase currents are controlled with standard angle commutation, bringing in large power loss as well as non‐negligible torque ripple. To overcome these shortcomings, based on the established DSEM power loss calculation model, a currents distribution strategy is proposed according to the obtained quantitative relationship between DSEM power loss and field current under multiple speed and load torque conditions. Then, to identify the load torque for practical implementation, a novel torque observer is designed based on back propagation (BP) neural network algorithm. Afterwards, to further improve the startup torque performance, currents distribution with advanced angle commutation (AAC) strategy is put forward, where the optimal advanced angle is selected from a 3‐D lookup table to achieve the minimal commutation torque ripple. Under the proposed control strategies, DSEM power loss as well as the output torque ripple are desired to be decreased, the simulation and experimental results on a 12/8‐pole DSEM prototype verify the correctness and feasibility of the proposed strategies under multiple operating conditions.

China holds the top position globally in apple production and consumption. Detecting diseases during the planting process is crucial for increasing yields and promoting the rapid development of the apple industry. This study proposes a lightweight algorithm for apple leaf disease detection in natural environments, which is conducive to application on mobile and embedded devices. Our approach modifies the YOLOv8n framework to improve accuracy and efficiency. Key improvements include replacing conventional Conv layers with GhostConv and parts of the C2f structure with C3Ghost, reducing the model’s parameter count, and enhancing performance. Additionally, we integrate a Global attention mechanism (GAM) to improve lesion detection by more accurately identifying affected areas. An improved Bi-Directional Feature Pyramid Network (BiFPN) is also incorporated for better feature fusion, enabling more effective detection of small lesions in complex environments. Experimental results show a 32.9% reduction in computational complexity and a 39.7% reduction in model size to 3.8 M, with performance metrics improving by 3.4% to a mAP@0.5 of 86.9%. Comparisons with popular models like YOLOv7-Tiny, YOLOv6, YOLOv5s, and YOLOv3-Tiny demonstrate that our YOLOv8n–GGi model offers superior detection accuracy, the smallest size, and the best overall performance for identifying critical apple diseases. It can serve as a guide for implementing real-time crop disease detection on mobile and embedded devices.

Excessive ammonia nitrogen can potentially compromise the safety of drinking water. Therefore, developing a rapid and simple detection method for ammonia nitrogen in drinking water is of great importance. Nickel–copper hydroxides exhibit strong catalytic capabilities and are widely applied in ammonia nitrogen oxidation. In this study, a self-supported electrode made of nickel–copper carbonate hydroxide was synthesized on a carbon cloth collector via a straightforward one-step hydrothermal method for rapid ammonia nitrogen detection in water. It exhibits sensitivities of 3.9 μA μM−1 cm−2 and 3.13 μA μM−1 cm−2 within linear ranges of 1 μM to 100 μM and 100 μM to 400 μM, respectively, using a simple and rapid i-t method. The detection limit is as low as 0.62 μM, highlighting its excellent anti-interference properties against various anions and cations. The methodology’s simplicity and effectiveness suggest broad applicability in water quality monitoring and environmental protection, particularly due to its significant cost-effectiveness.

In the realm of electrochemical nitrite detection, the potent oxidizing nature of nitrite typically necessitates operation at high detection potentials. However, this study introduces a novel approach to address this challenge by developing a highly sensitive electrochemical sensor with a low reduction detection potential. Specifically, a copper metal nanosheet/carbon paper sensitive electrode (Cu/CP) was fabricated using a one-step electrodeposition method, leveraging the catalytic reduction properties of copper’s high occupancy d-orbital. The Cu/CP sensor exhibited remarkable performance in nitrite detection, featuring a low detection potential of −0.05 V vs. Hg/HgO, a wide linear range of 10~1000 μM, an impressive detection limit of 0.079 μM (S/N = 3), and a high sensitivity of 2140 μA mM−1cm−2. These findings underscore the efficacy of electrochemical nitrite detection through catalytic reduction as a means to reduce the operational voltage of the sensor. By showcasing the successful implementation of this strategy, this work sets a valuable precedent for the advancement of electrochemical low-potential nitrite detection methodologies.

DOX/TPOR4@CB[7]4 was synthesized via self-assembly, and its physicochemical properties and ability to generate reactive oxygen species (ROS) were evaluated. The impact of photodynamic therapy on SH-SY5Y cells was assessed using the MTT assay, while flow cytometry analysis was employed to detect cell apoptosis. Confocal laser scanning microscopy was utilized to observe the intracellular distribution of DOX/TPOR4@CB[7]4 in SH-SY5Y cells. Additionally, fluorescence imaging of DOX/TPOR4@CB[7]4 in nude mice bearing SH-SY5Y tumors and examination of the combined effects of photodynamic and chemical therapies were conducted. The incorporation of CB[7] significantly enhanced the optical properties of DOX/TPOR4@CB[7]4, resulting in increased ROS production and pronounced toxicity towards SH-SY5Y cells. Moreover, both the apoptotic and mortality rates exhibited significant elevation. In vivo experiments demonstrated that tumor growth inhibition was most prominent in the DOX/TPOR4@CB[7]4 group. π–π interactions facilitated the binding between DOX and photosensitizer TPOR, with TPOR’s naphthalene hydrophilic groups encapsulated within CB[7]’s cavity through host–guest interactions with CB[7]. Therefore, CB[7] can serve as a nanocarrier to enhance the combined application of chemical therapy and photodynamic therapy, thereby significantly improving treatment efficacy against neuroblastoma tumors.

Kirsten rats sarcoma viral oncogene (KRAS), the first discovered human oncogene, has long been recognized as “undruggable”. KRAS mutations frequently occur in multiple human cancers including non-small cell lung cancer(NSCLC), colorectal cancer(CRC) and pancreatic ductal adenocarcinoma(PDAC), functioning as a “molecule switch” determining the activation of various oncogenic signaling pathways. Except for its intrinsic pro-tumorigenic role, KRAS alteration also exhibits an unique immune signature characterized by elevated PD-L1 level and high tumor mutational burden(TMB). KRAS mutation shape an immune suppressive microenvironment by impeding effective T cells infiltration and recruiting suppressive immune cells including myeloid-derived suppressor cells(MDSCs), regulatory T cells(Tregs), cancer associated fibroblasts(CAFs). In immune checkpoint inhibitor(ICI) era, NSCLC patients with mutated KRAS tend to be more responsive to ICI than patients with intact KRAS. The hallmark for KRAS mutation is the existence of multiple kinds of co-mutations. Different types of co-alterations have distinct tumor microenvironment(TME) signatures and responses to ICI. TP53 co-mutation possess a “hot” TME and achieve higher response to immunotherapy while other loss of function mutation correlated with a “colder” TME and a poor outcome to ICI-based therapy. The groundbreaking discovery of KRAS G12C inhibitors significantly improved outcomes for this KRAS subtype even though efficacy was limited to NSCLC patients. KRAS G12C inhibitors also restore the suppressive TME, creating an opportunity for combinations with ICI. However, an inevitable challenge to KRAS inhibitors is drug resistance. Promising combination strategies such as combination with SHP2 is an approach deserve further exploration because of their immune modulatory effect.

Background: There is growing evidence indicating a connection between fine particulate matter (PM2.5) and depressive symptoms. Metabolic risk factors are critical determinants of depressive symptoms. However, the mediating role of these factors on the association between PM2.5 and depressive symptoms remains elusive. We aimed to investigate whether and to what extent metabolic risk factors mediated the link between long-term PM2.5 exposure and depressive symptoms. Methods: This study comprised 7794 individuals aged between 30 and 79 years who participated in two waves of the on-site surveys in the China Multi-Ethnic Cohort. Ambient PM2.5 concentrations were assessed utilizing a random forest method based on satellite data. We employed the Patient Health Questionnaire-9 to assess depressive symptoms at wave 2, and the overall as well as three sub-domain symptom scores (emotional, neurovegetative, and neurocognitive symptoms) were calculated. Three metabolic risk factors, including hypertension, diabetes, and dyslipidemia, were considered. Mediation analyses were conducted to assess the indirect effects of PM2.5 on depressive symptoms through metabolic risk factors. Results: We found a positive association between chronic exposure to ambient PM2.5 and overall depressive symptoms as well as the three sub-domains. In mediation analyses, metabolic risk factors partially mediated the associations of PM2.5 on depressive symptoms. The natural indirect effects (RR, 95% CI) of PM2.5 on overall, emotional, neurovegetative, and neurocognitive symptoms mediated through metabolic risk factors were 1.004(1.001, 1.007), 1.004 (1.001, 1.008), 1.004 (1.001, 1.007), and 1.003(0.999, 1.007), respectively. Larger indirect effects were found in elderly participants (mediated proportion, 29.3%), females (13.3%), and people who did not consume alcohol (19.6%). Conclusions: Metabolic risk factors may act as mediators in the relationship between chronic PM2.5 exposure and depression. Treatment of metabolic risk factors may be an opportunity to reduce the burden of depression caused by long-term exposure to PM2.5.

Background: Particulate matter (PM) exposure has been linked with cardiovascular disease (CVD) and metabolic syndrome (MetS), the latter characterized by concurrent multiple metabolic disorders. As a result, the mechanisms assumption from PM to CVD through MetS have emerged, thus requiring further epidemiological evidence. This cohort study aimed to assess whether MetS mediates the associations of PM with CVD risk. Methods: This study included 14,195 participants from the Chengdu cohort of the China Multi-Ethnic Cohort (CMEC) study in 2018. The primary outcome of incident CVD diagnoses was identified using matched hospital records from the Health Information Center of Sichuan Province. Residence-specific levels of PM with aerodynamic diameters of ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5), and ≤ 10 µm (PM10) were estimated by spatiotemporal models. Causal mediation analyses were applied to evaluate the indirect effect of MetS. Results: Increased exposure levels to PM were significantly associated with MetS and CVD. Mediation analyses indicated that the associations between PM exposure and CVD were mediated by MetS, with the proportion of multiple mediations being 19.3%, 12.1%, and 13.5% for PM1, PM2.5, and PM10, respectively. Further moderated mediation analyses suggested that male, overweight individuals, alcohol drinkers, and those suffering from indoor air pollution may experience more significant adverse effects from PM exposure on CVD via MetS than others. Conclusions: Our findings suggest that MetS partially mediates the association between long-term exposure to PM and CVD. These mediation effects appear to be amplified by demographic characteristics and unhealthy lifestyles.

Summary: Background: The biological aging process can be modified through lifestyle interventions to prevent age-related diseases and extend healthspan. However, evidence from population-based studies on whether tea consumption could delay the biological aging process in humans remains limited. Methods: This study included 7931 participants aged 30–79 years from the China Multi-Ethnic Cohort (CMEC) Study and 5998 participants aged 37–73 years from the UK Biobank (UKB) who participated in both the baseline and first follow-up surveys. Tea consumption information was collected through questionnaires. Biological age (BA) acceleration was calculated using clinical biomarkers and anthropometric measurements based on the Klemera Doubal method (KDM). Change-to-change analyses were performed to estimate the associations between changes in tea consumption status and changes in BA acceleration using multiple linear models. Follow-up adjusted for baseline analyses were further conducted to examine the prospective exposure-response relationship between tea consumption and BA acceleration among individuals with constant tea consumption status. Findings: During a median follow-up of 1.98 (1.78, 2.16) years in the CMEC and 4.50 (3.92, 5.00) years in the UKB, tea consumption was consistently associated with attenuated BA acceleration in both cohorts. Transitioning from nondrinking to tea-drinking was associated with decreased BA acceleration (CMEC: β = −0.319, 95% CI: −0.620 to −0.017 years; UKB: β = −0.267, 95% CI: −0.831 to 0.297 years) compared to consistent nondrinking. Even stronger associations were found in consistent tea drinkers. The exposure-response relationship suggested that consuming around 3 cups of tea or 6–8 g of tea leaves per day may offer the most evident anti-aging benefits. Interpretation: Tea consumption was associated with attenuated BA acceleration measured by KDM, especially for consistent tea drinkers with moderate consumption. Our findings highlight the potential role of tea in developing nutrition-oriented anti-aging interventions and guiding healthy aging policies. Funding: National Natural Science Foundation of China (Grant No. 82273740).

Background & Aims: Existing evidence suggests that long-term exposure to ambient fine particulate pollution (PM2.5) may increase metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, there is still limited evidence on the association of PM2.5 constituents with MAFLD. Therefore, this study explores the associations between the five main chemical constituents of PM2.5 and MAFLD to provide more explicit information on the liver exposome. Methods: A total of 76,727 participants derived from the China Multi-Ethnic Cohort, a large-scale epidemic survey in southwest China, were included in this study. Multiple linear regression models were used to estimate the pollutant-specific association with MAFLD. Weighted quantile sum regression was used to evaluate the joint effect of the pollutant-mixture on MAFLD and identify which constituents contribute most to it. Results: Three-year exposure to PM2.5 constituents was associated with a higher MAFLD risk and more severe liver fibrosis. Odds ratios for MAFLD were 1.480, 1.426, 1.294, 1.561, 1.618, and 1.368 per standard deviation increase in PM2.5, black carbon, organic matter, ammonium, sulfate, and nitrate, respectively. Joint exposure to the five major chemical constituents was also positively associated with MAFLD (odds ratio 1.490, 95% CI 1.360–1.632). Nitrate contributed most to the joint effect of the pollutant-mixture. Further stratified analyses indicate that males, current smokers, and individuals with a high-fat diet might be more susceptible to ambient PM2.5 exposure than others. Conclusions: Long-term exposure to PM2.5 and its five major chemical constituents may increase the risk of MAFLD. Nitrate might contribute most to MAFLD, which may provide new clues for liver health. Males, current smokers, and participants with high-fat diets were more susceptible to these associations. Impact and implications: This large-scale epidemiologic study explored the associations between constituents of fine particulate pollution (PM2.5) and metabolic dysfunction-associated fatty liver disease (MAFLD), and further revealed which constituents play a more important role in increasing the risk of MAFLD. In contrast to previous studies that examined the effects of PM2.5 as a whole substance, this study carefully explored the health effects of the individual constituents of PM2.5. These findings could (1) help researchers to identify the specific particles responsible for hepatotoxicity, and (2) indicate possible directions for policymakers to efficiently control ambient air pollution, such as targeting the sources of nitrate pollution.

The collection of twelve bronze artifacts discovered in Xichuan provides invaluable historical insights into the Warring States period (476 BC to 221 BC) of ancient China. To investigate their fabrication techniques and current state of preservation, a comprehensive analysis was conducted using a metallographic microscope, a scanning electron microscope, and an electron spectrometer to examine the microstructure and elemental composition of the artifacts. The findings revealed that the copper content in these bronze artifacts varied between 41.82% and 87.95%, the tin content ranged from 6.79% to 46.88%, and the lead content was less than 28.96%. The microstructure exhibited an α-solid-solution dendritic-crystal-segregation structure, with a substantial amount of (α + δ) eutectic distributed in an island-like pattern. Lead was dispersed unevenly, appearing as small granules and large ellipsoids. The composition of these weapons aligned with their intended use, adhering to the manufacturing standards of traditional Chinese bronzes. However, their state of preservation was suboptimal, necessitating immediate protective measures. This study contributes physical evidence to the research on early Chinese bronze production and offers scientific guidance for the conservation and restoration of these bronze artifacts.

The flowering of Amorphophallus bulbifer (A. bulbifer) plays an important role in its reproduction. The flowers and leaves of A. bulbifer cannot grow at the same time. However, the physiological and molecular mechanisms involved in flower bud and leaf bud formation are still unclear. In this study, the flower buds and leaf buds of A. bulbifer in the early stage of growth were used as research materials, transcriptome and metabolome analyses were carried out, and the soluble sugar and starch contents of A. bulbifer corms were determined. Transcriptome analysis revealed 5542 differentially expressed genes (DEGs) between flower buds and leaf buds, 3107 of which were upregulated and 2435 of which were downregulated. Enrichment analysis of the KEGG pathway showed that these differential genes were enriched mainly in the plant hormone signal transduction, DNA replication and fatty acid elongation pathways. A total of 5296 significant differentially abundant metabolites were screened out by nontargeted metabolomics analysis. The differentially abundant metabolites were functionally classified in the HMDB, and 118 were successfully matched, including 17 that were highly expressed in flower buds. The differentially abundant metabolites in the flower buds were mainly enriched in pathways such as amino acid metabolism, isoquinoline alkaloid biosynthesis and pyrimidine metabolism. Targeted metabolomics analysis revealed that the contents of ABA, ZT and iPA in flower buds were significantly greater than those in leaf buds, while the opposite trend was observed for IAA. The analysis of soluble sugar and starch contents showed that the starch and soluble sugar contents in flower buds were significantly greater than those in leaf buds. The results of this study showed that flower bud development in A. bulbifer was regulated by amino acids, starch, ABA, ZT, iPA, IAA and other hormones. These findings could lead to valuable genetic resources for further study of A. bulbifer flowering and provide a deeper understanding of the molecular basis of A. bulbifer flowering.

The microstructure and texture evolution of pure nickel sheets during cryorolling and subsequent short-time low-temperature annealing were analyzed by electron backscatter diffraction technique. Results show that the content of typical texture of brass, copper, S, cube, and Goss texture is no significant change during cryorolling with a reduction of 40%. When the reduction reaches 60%, it begins to significantly increase, and when the reduction reaches 80%, it exhibits a copper type texture. However, when the reduction is 20%, the fiber texture of //normal direction (ND) orientation begins to significantly increase, which was mainly caused by dislocation slip during cryorolling. During low temperature and short time annealing, the content of typical textures decreases except S texture, and the grain changes mainly occur in grains other than //ND orientation which is due to the rich substructure and high dislocation density formed in the cryorolling process leading to rapid response to annealing.

Abstract Background Osteoarthritis (OA) is the most prevalent age-related disease in the world. Chondrocytes undergo an age-dependent decline in their proliferation and synthetic capacity, which is the main cause of OA development. However, the intrinsic mechanism of chondrocyte senescence is still unclear. This study aimed to investigate the role of a novel long non-coding RNA (lncRNA), AC006064.4–201 in the regulation of chondrocyte senescence and OA progression and to elucidate the underlying molecular mechanisms. Methods The function of AC006064.4–201 in chondrocytes was assessed using western blotting, quantitative real-time polymerase chain reaction (qRT-PCR), immunofluorescence (IF) and β-galactosidase staining. The interaction between AC006064.4–201 and polypyrimidine tract-binding protein 1 (PTBP1), as well as cyclin-dependent kinase inhibitor 1B (CDKN1B), was evaluated using RPD-MS, fluorescence in situ hybridization (FISH), RNA immunoprecipitation (RIP) and RNA pull-down assays. Mice models were used to investigate the role of AC006064.4–201 in post-traumatic and age-related OA in vivo. Results Our research revealed that AC006064.4–201 was downregulated in senescent and degenerated human cartilage, which could alleviate senescence and regulate metabolism in chondrocytes. Mechanically, AC006064.4–201 directly interacts with PTBP1 and blocks the binding between PTBP1 and CDKN1B mRNA, thereby destabilizing CDKN1B mRNA and decreasing the translation of CDKN1B. The in vivo experiments were consistent with the results of the in vitro experiments. Conclusions The AC006064.4–201/PTBP1/CDKN1B axis plays an important role in OA development and provides new molecular markers for the early diagnosis and treatment of OA in the future. Graphical Abstract Schematic diagram of AC006064.4–201 mechanism. A schematic diagram of the mechanism underlying the effect of AC006064.4–201

Abstract Developing a new technique/method and/or mechanism for separating ionic charges is critical to the fabrication of a high-performance nanogenerator. Inspired by charge migration and/or separation under an electric bias, herein, we demonstrate a reverse process in which the ionic charge gradients within a metal nanoparticle film are used to output electrical energy. The metal nanoparticle core is ‘jammed’ within the film, while the counterion itself is mobile and magnetic; therefore, ionic gradients are created through an external magnetic field. The distribution gradient of magnetic counterions is subsequently transformed into an electric potential within the metal nanoparticle film and into an electron flow in the external circuit. The performance of the nanoparticle nanogenerator is also optimized, and the highest output open-circuit voltage reaches 0.55 V. Finally, we develop a continuum charge-transport model combining Poisson and Nernst‒Planck diffusion equations to simulate the production of electrical energy within metal nanoparticle films.

Abstract Objectives Prior research on the effect of tea consumption on blood pressure (BP) generated inconsistent findings. The objective of this study was to explore the effects of different types of tea consumption on BP. Methods We included 76,673 participants aged 30–79 from the baseline data of the China Multi-Ethnic Cohort (CMEC) study. Binary logistic regression was used to analyze the influences of different types of tea consumption on the risk of hypertensive BP. Moreover, multiple linear regression was used to examine the association between tea drinking and BP. Results Tea consumption was associated with a reduced risk of hypertensive BP by 10% (AOR: 0.90, 95%CI: 0.86–0.94). While dark tea was related to a 1.79–5.31 mmHg reduction in systolic blood pressure (SBP) and a 0.47–1.02 mmHg reduction in diastolic blood pressure (DBP), sweet tea, regardless of the duration, frequency, or amount of consumption, significantly was associated with a reduced SBP by 3.19–7.18 mmHg. Green tea also was associated with a reduced SBP by 1.21–2.98 mmHg. Although scented tea was related to reduced SBP by 1.26-2.48 mmHg, the greatest effect came from the long duration (> 40 years:β=-2.17 mmHg, 95%CI=-3.47 mmHg --0.87 mmHg), low frequency (1–2 d/w: β = -2.48 mmHg, 95%CI=-3.76 mmHg–-1.20 mmHg), and low amount (≤ 2 g/d: β=-2.21 mmHg, 95%CI=-3.01 mmHg–-1.40 mmHg). Additionally, scented tea was correlated to a decrease in DBP at the frequency of 1–2 d/w (β=-0.84 mmHg, 95%CI=-1.65 mmHg–-0.02 mmHg). Drinking black tea only was associated with lowered SBP. The protective effect of black tea on SBP was characterized by the long-duration (> 15 years, -2.63–-5.76 mmHg), high frequency (6–7 d/w, -2.43 mmHg), and medium amount (2.1-4.0 g/d, -3.06 mmHg). Conclusion Tea consumption was associated with lower SBP and a reduced risk of hypertensive BP. The antihypertensive effect varies across types of tea consumed.

PurposePhysical fitness and fundamental motor skills are two important aspects for the healthy development of preschoolers. Despite the growing interest in clarifying their relationship, the scarcity of longitudinal studies prevents us from understanding causality.MethodThis study employed a cross-lagged model with two time points to investigate the bidirectional relationship between these two aspects. A total of 174 preschoolers (54.0% girls) from 3 to 6 years old (M = 3.96 ± 0.47) were surveyed, they were recruited by convenience from two kindergartens in Beijing, China, and their physical fitness (via CNPFDSM-EC) and fundamental motor skills (via TGMD-3) were tracked over a period of 6 months.ResultsThe findings revealed a bidirectional predictive effect. The predictive strength of flexibility was found to be lower than other physical fitness aspects, while locomotor skills demonstrated a higher predictive strength than object control skills.ConclusionThis study indicates that physical fitness and fundamental motor skills mutually enhance each other in young children, and both should be emphasized in preschool sports education.

Background: Exposure to particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) may increase the risk of 10-year atherosclerotic cardiovascular disease (ASCVD) risk. While PM2.5 is comprised of various components, the evidence on the correlation of its components with 10-year ASCVD risk and which component contributes most remains limited. Methods: Data were derived from the baseline assessments of China Multi-Ethnic Cohort (CMEC). In total, 69,722 individuals aged 35–74 years were included into this study. The annual average concentration of PM2.5 and its components (black carbon, ammonium, nitrate, sulfate, organic matter, soil particles, and sea salt) were estimated by satellite remote sensing and chemical transport models. The ASCVD risk of individuals was calculated by the equations from the China-PAR Project (prediction for ASCVD risk in China). The relationship between single exposure to PM2.5 and its components and predicted 10-year ASCVD risk was assessed using the logistic regression model. The effect of joint exposure was estimated, and the most significant contributor was identified using the weighted quantile sum approach. Results: Totally 69,722 participants were included, of which 95.8 % and 4.2 % had low and high 10-year ASCVD risk, respectively. Per standard deviation increases in the 3-year average concentration of PM2.5 mass (odds ratio [OR] 1.23, 95 % confidence interval [CI]: 1.12–1.35), black carbon (1.21, 1.11–1.33), ammonium (1.21, 1.10–1.32), nitrate (1.25, 1.14–1.38), organic matter (1.29, 1.18–1.42), sulfate (1.17, 1.07–1.28), and soil particles (1.15, 1.04–1.26) were related to high 10-year ASCVD risk. The overall effect (1.19, 1.11–1.28) of the PM2.5 components was positively associated with 10-year ASCVD risk, and organic matter had the most contribution to this relationship. Female participants were more significantly impacted by PM2.5, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles compared to others. Conclusion: Long-term exposure to PM2.5 mass, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles were positively associated with high 10-year ASCVD risk, while sea salt exhibited a protective effect. Moreover, the organic matter might take primary responsibility for the relationship between PM2.5 and 10-year ASCVD risk. Females were more susceptible to the adverse effect.

Background: Ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) consists of various toxic constituents. However, the health effect of PM2.5 may differ depending on its constituents, but the joint effect of PM2.5 constituents remains incompletely understood. Objective: Our goal was to evaluate the joint effect of long-term PM2.5 constituent exposures on dyslipidemia and identify the most hazardous chemical constituent. Methods: This study included 67,015 participants from the China Multi-Ethnic Cohort study. The average yearly levels of PM2.5 constituents for all individuals at their residences were assessed through satellite remote sensing and chemical transport modeling. Dyslipidemia was defined as one or more following abnormal blood lipid concentrations: total cholesterol (TC) ≥ 6.22 mmol/L, triglycerides (TG) ≥ 2.26 mmol/L, high-density lipoprotein cholesterol (HDL-C)

Abstract Background Adiposity is widely recognized as one of the risk factors for high blood pressure (BP) and increasing adiposity is associated with elevated BP. However, which measures of adiposity could be most strongly associated with BP in multi-ethnic population remains uncertain, giving rise to implications that population-based adiposity measures could be necessary. Methods 80,000 multi-ethnic adults recruited from 5 provinces across Southwest China during 2018 ~ 2019 were studied. Multiple linear regression was applied to investigate the associations of systolic blood pressure (SBP) with: (1) two measures of general adiposity, body mass index (BMI) and height-adjusted weight; and (2) three measures of central adiposity, waist circumference (WC), hip circumference (HC) and waist hip ratio (WHR). Results Two distinct population-specific patterns were identified, as “BMI to SBP” and “WC to SBP”. 90% of the participants fall into “BMI to SBP” pattern, in which the associations of SBP with BMI were independent of WC, and SBP-WC associations were considerably decreased by adjustment for BMI. And in this pattern, 10 kg/m2 greater BMI was associated with 11.9 mm Hg higher SBP on average. As for the rest population (Han males in Yunnan and Tibetans in Lhasa), they are suited for “WC to SBP” pattern, 10 cm wider WC was associated with 3.4 mm Hg higher SBP. Conclusion Our results indicated that when selecting proper predictors for BP, population-specific adiposity measures are needed, considering ethnicity, sex and residing regions. A better understanding of adiposity and BP may better contribute to the potential clinical practices and developing precision application strategies.

Designing scaled electronic devices for neuromorphic applications remains a challenge. Here, Zhang et al. develop an artificial molecular synapse based on self-assembled peptide molecule monolayer whose conductance can be dynamically modulated and used for waveform recognition.