Personalized starting age of gastric cancer screening based on individuals' risk profiles: a population-based prospective study.

BACKGROUND: The current recommended starting age for gastric cancer (GC) lacks unified guideline and individualized criteria. We aimed to determine risk-stratified starting age for GC screening in China based on individuals' risk profiles, and develop an online calculator for clinical application. METHODS: In this multi-center population-based prospective study, we divided participants enrolled during 2015-2017 (n = 59,771, aged 40-69) into screened and unscreened groups and observed them for primary endpoints-GC occurrence, all-cause and GC-specific deaths. The median follow-up was 6.07 years. To determine the reference starting age, the effectiveness of GC screening was assessed by age-groups after propensity-score-matching. Further, we categorized the calculated individual risk scores (using well-established risk factors) by quantiles. Subsequently, we used age-specific 10-year cumulative risk curves to estimate the risk-stratified starting age-when the individual's risk level matches reference starting age risk threshold. RESULTS: During follow-up, 475 GC cases, 182 GC deaths and 1,860 all-cause deaths occurred. All-cause and GC-specific mortality decreased among screened individuals aged ≥45 and 50-59 years, respectively. Thus, the average population (reference) starting age was set as 50 years. The 10-year cumulative risk of GC in average population aged 50 was 1.147%. We stratified the starting age using eight risk factors, and categorized participants as low-, medium-, and high-risk individuals, whose risk-stratified starting age was 58, 50, and 46, respectively. CONCLUSION: While high-risk individuals warrant 3-5 years earlier GC screening than average population (age 50), low-risk individuals can tolerate delayed screening. Our online, personalized starting-age calculator will help risk-adapted GC screening (https://web.consultech.com.cn/gastric/#/).

The relationship between physical activity and procrastination behavior among Chinese university students: a chain mediated effect of body self-esteem and overall self-esteem.

Objective: This study aimed to explore the relationship between physical activity and procrastination behavior among college students and the serial mediating roles of body self-esteem and overall self-esteem. Methods: A cross-sectional survey was conducted involving 1,018 college students. The Physical Activity Rating Scale, the College Students' Physical Self-perception Profile, the Self-Esteem Scale, and the Chinese Procrastination Scale were utilized. Serial mediating effect analysis and Bootstrap analysis were applied to the data. Results: (1) Individuals engaging in high levels of physical activity demonstrated significantly lower levels of procrastination behavior compared to those with moderate or low levels of physical activity (Partial η2 = 0.01, F = 2.762, p < 0.01). (2) Physical activity was positively correlated with body self-esteem (r = 0.37, p < 0.01) and overall self-esteem (r = 0.29, p < 0.01), and negatively correlated with procrastination behavior (r = -0.14, p < 0.01). body self-esteem was positively correlated with overall self-esteem (r = 0.11, p < 0.01) and negatively correlated with procrastination behavior (r = -0.13, p < 0.01). Overall self-esteem also showed a significant negative correlation with procrastination behavior (r = -0.26, p < 0.01). (3) Mediation effect analysis indicated that body self-esteem and overall self-esteem played partial mediating roles in the relationship between physical activity and procrastination behavior among college students. The mediating effects were composed of three pathways: "Physical Activity → body self-esteem → Procrastination Behavior," "Physical Activity → Overall Self-Esteem → Procrastination Behavior," and "Physical Activity → body self-esteem → Overall Self-Esteem → Procrastination Behavior," with the effect sizes accounting for 27.70, 12.26, and 7.28% of the total effect, respectively. Conclusion: The findings of this study lead to several key conclusions regarding the relationship between physical activity, self-esteem, and procrastination behavior among college students. Firstly, engagement in moderate levels of physical activity is more effective in reducing procrastination behavior among college students. Secondly, participation in high volumes of physical activity is associated with increased levels of both body self-esteem and overall self-esteem. Lastly, physical activity not only directly impacts procrastination behavior but also indirectly influences it by enhancing body self-esteem and overall self-esteem, thereby further reducing the individual's level of procrastination. These conclusions suggest that physical activity plays a multifaceted role in mitigating procrastination behavior in college students. By promoting self-esteem, physical activity can foster a positive psychological state that is conducive to proactive behavior and academic success. The study's findings underscore the importance of integrating physical activity into college students' daily routines as a strategy to combat procrastination and enhance self-esteem.

Sorption of Iodine on Biochar Derived from the Processing of Urban Sludge and Garden Waste at Different Pyrolysis Temperatures.

The United Nations proposed the Sustainable Development Goals with the aim to make human settlements in cities resilient and sustainable. The excessive discharge of urban waste including sludge and garden waste can pollute groundwater and lead to the emission of greenhouse gases (e.g., CH4). The proper recycling of urban waste is essential for responsible consumption and production, reducing environmental pollution and addressing climate change issues. This study aimed to prepare biochar with high adsorption amounts of iodine using urban sludge and peach wood from garden waste. The study was conducted to examine the variations in the mass ratio between urban sludge and peach wood (2/1, 1/1, and 1/2) as well as pyrolysis temperatures (300 °C, 500 °C, and 700 °C) on the carbon yield and adsorption capacities of biochar. Scanning electron microscopy, Brunauer-Emmett-Teller analysis, Fourier transform infrared spectrometry, powder X-ray diffraction, and elemental analysis were used to characterize the biochar produced at different pyrolysis temperatures and mass ratios. The results indicate that the carbon yield of biochar was found to be the highest (>60%) at a pyrolysis temperature of 300 °C across different pyrolysis temperatures. The absorbed amounts of iodine in the aqueous solution ranged from 86 to 223 mg g-1 at a mass ratio of 1:1 between urban sludge and peach wood, which were comparably higher than those observed in other mass ratios. This study advances water treatment by offering a cost-effective method by using biochar derived from the processing of urban sludge and garden waste.

Facile, green and scalable synthesis of single-layer manganese dioxide nanosheets and its application for GSH and cTnI colorimetric detection.

Manganese dioxide (MnO2) nanosheets possess unique physical and chemical properties, making them widely applicable in various fields, such as chemistry and biomedicine. Although MnO2 nanosheets are produced using bottom-up wet chemistry synthesis methods, their scale is below the gram level and requires a long processing time, restricting their effective scale-up from laboratory to market. We report a facile, green and scalable synthesis of MnO2 nanosheets by mixing Shiranui mandarin orange juice and KMnO4 for 30 minutes. We produced more than one gram (1.095) of MnO2 nanosheets with a 0.65 nm mean thickness and a 50 nm mean lateral size. Furthermore, we established a visual colorimetric biosensing strategy based on MnO2 nanosheets for the assay of glutathione (GSH) and cardiac troponin I (cTnI), offering high sensitivity and feasibility in clinical samples. For GSH, the limit of detection was 0.08 nM, and for cTnI, it was 0.70 pg mL-1. Meanwhile, the strategy can be used for real-time analysis by applying a smartphone-enabled biosensing strategy, which can provide point-of-care testing in remote areas.

Research progress of Ganoderma lucidum polysaccharide in prevention and treatment of Atherosclerosis.

Atherosclerosis (AS) is a chronic inflammatory disease resulting from dysregulated lipid metabolism, constituting the pathophysiological foundation of cardiovascular and cerebrovascular diseases. AS has a high incidence rate and mortality rate worldwide. As such, traditional Chinese medicine (TCM) has been widely used recently due to its stable therapeutic effect and high safety. Ganoderma lucidum polysaccharides (GLP) are the main active ingredients of Ganoderma lucidum, a Chinese herbal medicine. Research has also shown that GLP has anti-inflammatory and antioxidant properties, regulates gut microbiota, improves blood glucose and lipid levels, and inhibits obesity. Most of the current research on GLP anti-AS is focused on animal models. Thus, its clinical application remains to be discovered. In this review, we combine relevant research results and start with the pathogenesis and risk factors of GLP on AS, proving that GLP can prevent and treat AS, providing a scientific basis and reference for the future prevention and treatment of AS with GLP.

Plant-based fascia tissues: Exploring materials and techniques for realistic simulation.

The growing demand for sustainable and ethical food options has led to significant advancements in plant-based meat substitutes (PBMS). PBMS have made considerable progress in simulating the taste, texture, and sensory properties of animal meat. Connective tissue is a fundamental component of animal meat that significantly influences tenderness, texture, and sensory properties. However, the imitation of realistic connective tissues has received relatively less attention in the PBMS industry. The current work focuses on exploring materials and techniques for the replication of plant-based connective tissues (PBCT). By understanding the structural and functional characteristics of animal connective tissues (ACT), it is possible to replicate these characteristics in PBCT. Hydrogels, with their ability to simulate certain properties of ACT, present a viable material for the creation of PBCT. To achieve the desired simulation, their mechanical and structural properties need to be enhanced by using several materials and several physical techniques.

Preparation of Perilla frutescens L. essential oil hydrogel beads and preservation application research in strawberry.

Perilla frutescens L. essential oil (PLEO) has antibacterial and antioxidant properties, which can effectively maintain the quality of fruits and extend their shelf life. In this study, sodium alginate and chitosan were used as wall materials, and PLEO microcapsule powder was used as the core materials to prepare PLEO hydrogel beads. The best results were obtained by using 2%w/v sodium alginate and 1.5%w/v chitosan as wall materials, with a core-to-wall ratio of 2:1 and homogenized for 15 min producing PLEO hydrogel beads with encapsulation efficiency of 82.61 %. For strawberries preservation, PLEO hydrogel beads preservation group had a better effect after 5 d of storage, showing a lower decay rate (15.71 %), better maintaining the hardness of 1.75 kg/cm2, and a weight loss of 3.29 %. Furthermore, organic acids and total phenols were retained more in this group, the number of microorganisms was significantly reduced, and sensory qualities were improved, especially taste and color. This study provides important insights into the application of natural preservatives in the food industry and promotes sustainable practices in food preservation.

A single-bridge interleaved three-level LLC resonant converter with current sharing capability for fuel cell system.

This paper propose a wide gain single-bridge interleaved three-level LLC resonant converter with current sharing capability. This novel converter offers numerous advantages, including low cost, low current ripple, reduced voltage and current stress, widely gain range, high efficiency, good current sharing capability and versatile application scalability. Utilizing the three-level inverter + full-wave rectifier LLC converter as a representative case, the paper conducts an in-depth analysis and research on the proposed method. Finality, a 600 W experimental prototype was constructed and tested. Experimental results reveal that the proposed converter exhibits lower current ripple and a broader gain range. Moreover, the converter shows good current sharing capability (with a resonant element tolerance of 10%, the current error between the two phases does not exceed 12%) and high efficiency (peaking at 95.8%).

Early detection of gray blight in tea leaves and rapid screening of resistance varieties by hyperspectral imaging technology.

BACKGROUND: Gray blight (GB) is a significant disease of tea leaves, posing a severe threat to both the yield and quality. In this study, the process of leaf infection by a pathogenic isolate of the GB disease (DDZ-6) was simulated. Hyperspectral images of normal leaves, infected leaves without symptoms, and infected leaves with mild and moderate symptoms were collected. Combining convolution neural network (CNN), long short-term memory (LSTM), and support vector machine (SVM) algorithms, the early detection model of GB disease, and the rapid screening model of resistant varieties were established. The generality of this method was verified by collecting datasets under field conditions. RESULTS: The visible red-light band demonstrated a pronounced responsiveness to GB disease, with three sensitive bands identified through rigorous screening processes utilizing uninformative variable elimination (UVE), competitive adaptive reweighted sampling (CARS), and the successive projections algorithm (SPA). The 693, 727, and 766 nm bands emerged as highly sensitive indicators of GB. Under ideal conditions, the CARS-LSTM model excelled in early detection of GB, achieving an accuracy of 92.6%. However, under field conditions, the combination of 693 and 727 nm bands integrated with a CNN provided the most effective early detection model, attaining an accuracy of 87.8%. For screening tea varieties resistant to GB, the SPA-LSTM model excelled, achieving an accuracy of 82.9%. CONCLUSION: This study provides a core algorithm for a GB disease instrument with detection capabilities, which is of great importance for the early prevention of GB disease in tea plantations. © 2024 Society of Chemical Industry.

Concept-based Lesion Aware Transformer for Interpretable Retinal Disease Diagnosis.

Existing deep learning methods have achieved remarkable results in diagnosing retinal diseases, showcasing the potential of advanced AI in ophthalmology. However, the black-box nature of these methods obscures the decision-making process, compromising their trustworthiness and acceptability. Inspired by the concept-based approaches and recognizing the intrinsic correlation between retinal lesions and diseases, we regard retinal lesions as concepts and propose an inherently interpretable framework designed to enhance both the performance and explainability of diagnostic models. Leveraging the transformer architecture, known for its proficiency in capturing long-range dependencies, our model can effectively identify lesion features. By integrating with image-level annotations, it achieves the alignment of lesion concepts with human cognition under the guidance of a retinal foundation model. Furthermore, to attain interpretability without losing lesion-specific information, our method employs a classifier built on a cross-attention mechanism for disease diagnosis and explanation, where explanations are grounded in the contributions of human-understandable lesion concepts and their visual localization. Notably, due to the structure and inherent interpretability of our model, clinicians can implement concept-level interventions to correct the diagnostic errors by simply adjusting erroneous lesion predictions. Experiments conducted on four fundus image datasets demonstrate that our method achieves favorable performance against state-of-the-art methods while providing faithful explanations and enabling conceptlevel interventions. Our code is publicly available at https://github.com/Sorades/CLAT.

Association of genetic variations of 3'-UTR in clopidogrel pharmacokinetic-relevant genes with clopidogrel response in Han Chinese patients with coronary artery disease.

Dual antiplatelet therapy with aspirin and clopidogrel has reduced ischemic vascular events significantly. Genetic influence, especially those in clopidogrel pharmacokinetic-relevant genes partially accounts for interindividual pharmacodynamic variability of clopidogrel. However, most studies have concentrated on the genetic variations in introns, exons, or promoters of the candidate genes, and the association between genetic variations in 3'-UTR in clopidogrel pharmacokinetic-relevant genes and clopidogrel response is unknown. In our study, ten different algorithms were applied to pick potential miRNAs targeting the clopidogrel pharmacokinetic-relevant genes. Furthermore, the correlation between miRNA expression profiles and mRNA expression of corresponding clopidogrel pharmacokinetic-relevant genes was analyzed. Through comprehensive analysis, including bioinformatics prediction and correlation analysis of miRNA and mRNA expression profiles, miR-218-5p and miR-506-5p were supposed to regulate the expression of PON1 via binding with its 3'-UTR. Moreover, PON1 rs854551 and rs854552 were located in miRNA recognizing sequences and may serve as potential miRSNPs possibly affecting PON1 expression. The rs854552 polymorphism was genotyped and platelet reactivity index (PRI) indicative of clopidogrel response was measured in 341 Chinese coronary artery disease (CAD) patients 24 h after administration of 300 mg clopidogrel. Our results showed that PON1 rs854552 had a significant influence on PRI in CAD patients, especially in patients with CYP2C19 extensive metabolic phenotype. In conclusion, PON1 rs854552 polymorphisms may affect clopidogrel response. Bioinformatics prediction followed by functional validation could aid in decoding the contribution of unexplained variations in the 3'-UTR in drug-metabolizing enzymes on clopidogrel response.

Rapid reconstitution of ubiquitinated nucleosome using a non-denatured histone octamer ubiquitylation approach.

BACKGROUND: Histone ubiquitination modification is emerging as a critical epigenetic mechanism involved in a range of biological processes. In vitro reconstitution of ubiquitinated nucleosomes is pivotal for elucidating the influence of histone ubiquitination on chromatin dynamics. RESULTS: In this study, we introduce a Non-Denatured Histone Octamer Ubiquitylation (NDHOU) approach for generating ubiquitin or ubiquitin-like modified histone octamers. The method entails the co-expression and purification of histone octamers, followed by their chemical cross-linking to ubiquitin using 1,3-dibromoacetone. We demonstrate that nucleosomes reconstituted with these octamers display a high degree of homogeneity, rendering them highly compatible with in vitro biochemical assays. These ubiquitinated nucleosomes mimic physiological substrates in function and structure. Additionally, we have extended this method to cross-linking various histone octamers and three types of ubiquitin-like proteins. CONCLUSIONS: Overall, our findings offer an efficient strategy for producing ubiquitinated nucleosomes, advancing biochemical and biophysical studies in the field of chromatin biology.

Universal materials model of deep-learning density functional theory Hamiltonian.

Realizing large materials models has emerged as a critical endeavor for materials research in the new era of artificial intelligence, but how to achieve this fantastic and challenging objective remains elusive. Here, we propose a feasible pathway to address this paramount pursuit by developing universal materials models of deep-learning density functional theory Hamiltonian (DeepH), enabling computational modeling of the complicated structure-property relationship of materials in general. By constructing a large materials database and substantially improving the DeepH method, we obtain a universal materials model of DeepH capable of handling diverse elemental compositions and material structures, achieving remarkable accuracy in predicting material properties. We further showcase a promising application of fine-tuning universal materials models for enhancing specific materials models. This work not only demonstrates the concept of DeepH's universal materials model but also lays the groundwork for developing large materials models, opening up significant opportunities for advancing artificial intelligence-driven materials discovery.

Investigation into the fabrication of plant-based simulant connective tissue utilizing algae polysaccharide-derived hydrogel.

Connective tissue is an important component of meat products that provides support to animal muscles. Hydrogels are considered a promising alternative to connective tissues and simulate actual products by adjusting the gel texture and mouthfeel. This study used soybean protein isolate (SPI), corn starch (CS), konjac glucomannan (KGM), and seaweed powder (SP) as raw materials to examine the effect of different added SP and KGM concentrations on the gel texture. The G' of the gel increased five-fold when the SP and KGM concentration was increased from 1 % to 3 %. The results of mechanical property tests showed that with the addition of SP, the gel hardness increased from 316.00 g to 1827.23 g and the tensile strength increased from 0.027 MPa to 0.089 MPa. Sensory evaluation showed that the samples with 2 % SP and KGM presented the highest overall acceptability score and the most significant similarity to real connective tissue. The connective tissue simulants exhibited excellent water-holding capacity (>90 %), significantly increasing their juiciness. SEM indicated that 2 % KGM addition improved gel network structure stability. The results demonstrate the potential of seaweed polysaccharide-derived hydrogels as connective tissue mimics. This provides a new strategy for the preparation of high mechanical strength hydrogels and lays the foundation for structural diversification of plant-based meat.

Causal relationship between gut microbiota and functional outcomes after ischemic stroke: A comprehensive Mendelian randomization study.

AIMS: To investigate the association of the genetic predisposition of specific gut microbiotas with the clinical outcome of ischemic stroke. METHODS: We leveraged publicly available genome-wide association study (GWAS) data to perform Mendelian randomization (MR) analysis. The gut microbiota-related GWAS data from 18,340 individuals from the international consortium MiBioGen was used. The summary data for functional outcomes after ischemic stroke was obtained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME) network meta-analysis. The primary outcomes were judged by the modified Rankin Scale (mRS). The principal analyses were conducted using the inverse-variance weighted (IVW) MR method. The Cochran's Q test, weighted median, MR-Egger regression, leave-one-SNP-out analysis, MR-Pleiotropy Residual Sum, and Outlier methods were adopted as sensitivity analyses. Furthermore, we performed bi-directional MR analysis and the MR Steiger directionality test to examine the direction of the causal relations. RESULTS: The results demonstrated that the genetic predisposition of genus Lactococcus, genus Ruminococcaceae NK4A214 group, family Peptostreptococcaceae, and genus Odoribacter was positively associated with favorable functional outcome after ischemic stroke. Genus Collinsella, genus Ruminococcaceae UCG005, genus Akkermansia, genus Eubacterium oxidoreducens group, and family Verrucomicrobiaceae were identified to be associated with worse functional outcomes after ischemic stroke. Our results showed no evidence of heterogeneity, directional pleiotropic effects, or collider bias, and the sensitivity of our analysis was acceptable. CONCLUSION: The genetic predisposition of different gut microbiotas was associated with the clinical outcome of ischemic stroke. Microbiota adjustment was a promising method to improve the clinical outcome of ischemic stroke.

Fetal cerebral arteries in a new ultrasonographic perspective.

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Effect of soybean proteins and peptides on the growth and adhesive ability of Limosilactobacillus Reuteri DSM17938.

Limosilactobacillus reuteri DSM17938 is one of the most pivotal probiotics, whose general beneficial effects on the intestinal microbiota are well recognized. Enhancing their growth and metabolic activity can effectively regulate the equilibrium of intestinal microbiota, leading to improved physical health. A common method to promote the growth of Lactobacillus is the addition of prebiotics. Current research suggests that proteins and their hydrolysates from different sources with potential prebiotic activity can also promote the growth of probiotics. In this study, soybean proteins and peptides were effective in promoting the growth, organic acid secretion, and adhesive properties of Limosilactobacillus reuteri DSM17938 to Caco-2 cells. These results illustrate the feasibility of soybean proteins and peptides as prebiotics, providing theoretical and practical advantages for their application.

Black Ultrathin Single-Crystalline Flakes of CuVP2S6 and CuCrP2S6 for Near-Infrared-Driven Photocatalytic Hydrogen Evolution.

The development of new near-infrared-responsive photocatalysts is a fascinating and challenging approach to acquire high photocatalytic hydrogen evolution (PHE) performance. Herein, near-infrared-responsive black CuVP2S6 and CuCrP2S6 flakes, as well as CuInP2S6 flakes, are designed and constructed for PHE. Atom-resolved scanning transmission electron microscopy images and X-ray absorption fine structure evidence the formation of ultrathin single-crystalline sheet-like structure of CuVP2S6 and CuCrP2S6. The synthetic CuVP2S6 and CuCrP2S6, with a narrow bandgap of ≈1.0 eV, shows the high light-absorption edge exceeding 1100 nm. Moreover, through the femtosecond-resolved transient absorption spectroscopy, CuCrP2S6 displays the efficient charge transfer and long charge lifetime (18318.1 ps), which is nearly 3 and 29 times longer than that of CuVP2S6 and CuInP2S6, respectively. In addition, CuCrP2S6, with the appropriate d-band and p-band, is thermodynamically favorable for the H+ adsorption and H2 desorption by contrast with CuVP2S6 and CuInP2S6. As a result, CuCrP2S6 exhibits high PHE rates of 9.12 and 0.66 mmol h-1 g-1 under simulated sunlight and near-infrared light irradiation, respectively, far exceeding other layered metal phospho-sulfides. This work offers a distinctive perspective for the development of new near-infrared-responsive photocatalysts.