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ObjectiveRice plays a crucial role in daily diet. The rice industry involves numerous links, from paddy planting to the consumer's table, and the integrity of the quality control data chain directly affects the credibility of rice quality control and traceability information. The process of rice traceability also faces security issues, such as the leakage of privacy information, which need immediate solutions. Additionally, the previous practice of uploading all information onto the blockchain leads to high storage costs and low system efficiency. To address these problems, this study proposed a differential privacy-enhanced blockchain-based quality control model for rice, providing new ideas and solutions to optimize the traditional quality regulation and traceability system.MethodsBy exploring technologies of blockchain, interplanetary file system (IPFS), and incorporating differential privacy techniques, a blockchain-based quality control model for rice with differential privacy enhancement was constructed. Firstly, the data transmission process was designed to cover the whole industry chain of rice, including cultivation, acquisition, processing, warehousing, and sales. Each module stored the relevant data and a unique number from the previous link, forming a reliable information chain and ensuring the continuity of the data chain for quality control. Secondly, to address the issue of large data volume and low efficiency of blockchain storage, the key quality control data of each link in the rice industry chain was stored in the IPFS. Subsequently, the hash value of the stored data was returned and recorded on the blockchain. Lastly, to enhance the traceability of the quality control model information, the sensitive information in the key quality control data related to the cultivation process was presented to users after undergoing differential privacy processing. Individual data was obfuscated to increase the credibility of the quality control information while also protecting the privacy of farmers' cultivation practices. Based on this model, a differential privacy-enhanced blockchain-based quality control system for rice was designed.Results and DiscussionsThe architecture of the differential privacy-enhanced blockchain-based quality control system for rice consisted of the physical layer, transport layer, storage layer, service layer, and application layer. The physical layer included sensor devices and network infrastructure, ensuring data collection from all links of the industry chain. The transport layer handled data transmission and communication, securely uploading collected data to the cloud. The storage layer utilized a combination of traditional databases, IPFS, and blockchain to efficiently store and manage key data on and off the blockchain. The traditional database was used for the management and querying of structured data. IPFS stored the key quality control data in the whole industry chain, while blockchain was employed to store the hash values returned by IPFS. This integrated storage method improved system efficiency, ensured the continuity, reliability, and traceability of quality control data, and provided consumers with reliable information. The service layer was primarily responsible for handling business logic and providing functional services. The implementation of functions in the application layer relied heavily on the design of a series of interfaces within the service layer. Positioned at the top of the system architecture, the application layer was responsible for providing user-centric functionality and interfaces. This encompassed a range of applications such as web applications and mobile applications, aiming to present data and facilitate interactive features to fulfill the requirements of both consumers and businesses. Based on the conducted tests, the average time required for storing data in a single link of the whole industry chain within the system was 1.125 s. The average time consumed for information traceability query was recorded as 0.691 s. Compared to conventional rice quality regulation and traceability systems, the proposed system demonstrated a reduction of 6.64% in the storage time of single-link data and a decrease of 16.44% in the time required to perform information traceability query.ConclusionsThis study proposes a differential privacy-enhanced blockchain-based quality control model for rice. The model ensures the continuity of the quality control data chain by integrating the various links of the whole industry chain of rice. By combining blockchain with IPFS storage, the model addresses the challenges of large data volume and low efficiency of blockchain storage in traditional systems. Furthermore, the model incorporates differential privacy protection to enhance traceability while safeguarding the privacy of individual farmers. This study can provide reference for the design and improvement of rice quality regulation and traceability systems.

Abstract Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.

ObjectiveTo investigate the prevalence of dental caries among preschool children in Chongming District， Shanghai， and to analyze the related factors influencing dental caries in preschool children in Chongming District， in order to provide references and suggestions for the prevention of dental caries in preschool children in Chongming District.MethodsFrom January to April 2022， 939 preschool children from 5 kindergartens in Chongming District of Shanghai were selected as the research objects through random cluster sampling. The dental caries prevalence rate and related risk factors of dental caries in preschool children were studied through oral examinations and questionnaire surveys.ResultsThe prevalence rate of dental caries among the 939 preschool children was 45.69%. The prevalence of dental caries in preschool children was not related to gender but increased with age （P

In this study, a small-scale simulated fermentation system of fermented grains (Jiupei in Chinese) without pit mud (PM) was used as a control, and the differences in the microbial community and metabolite components between the PM and control groups were compared. The results indicated that PM significantly enhanced the contents of major flavor compounds in Jiupei including butyric acid, caproic acid, ethyl acetate, ethyl butyrate, and ethyl caproate, and reduced the contents of lactic acid and ethyl lactate. For both groups, the relative abundance of Lactobacillus, one of the dominant bacteria in the upper and bottom layers of Jiupei, significantly increased at the initial stage, and showed a slight difference between them at the end of fermentation. The decay period of Lactobacillus in the PM group was about 15 days earlier than that in the control group. At the same time, the relative abundance of Rhodococcus in the control group, and the relative abundance of Kroppenstedtia, Clostridium_sensu_stricto_12, and Acetobacter in the PM group increased. The abundance of most of the enzymes in the Embden-Meyerhof-Parnas (EMP) pathway, as well as that of caproic acid synthase (EC 1.3.1.38, EC 2.3.1.16, EC 6.2.1.1) and butyric acid synthase (EC 2.3.1.9, EC 2.8.3.8) increased during fermentation, and the abundance of these enzymes was significantly higher in the bottom layer of Jiupei than in the upper layer. The abundance of lactate dehydrogenase (EC 1.1.1.27), which uses lactic acid as a substrate, increased in the PM group. These findings reveal the contribution of PM to the microbial communities and metabolite components of Jiupei.

Background and objectives This study aimed to identify predictors of sepsis-associated in-hospital mortality from readily available laboratory biomarkers at onset of illness that include haematological, coagulation, liver and kidney function, blood lipid, cardiac enzymes and arterial blood gas.Methods Children with sepsis were enrolled consecutively in a prospective observational study involving paediatric intensive care units (PICUs) of two hospitals in Beijing, between November 2016 and January 2020. The data on demographics, laboratory examinations during the first 24 hours after PICU admission, complications and outcomes were collected. We screened baseline laboratory indicators using the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, then we constructed a mortality risk model using Cox proportional hazards regression analysis. The ability of risk factors to predict in-hospital mortality was evaluated by receiver operating characteristic (ROC) curves.Results A total of 266 subjects were enrolled including 44 (16.5%) deaths and 222 (83.5%) survivors. Those who died showed a shorter length of hospitalisation, and a higher proportion of mechanical ventilation, complications and organ failure (p

Background Heart failure (HF) is a serious condition with increasing prevalence, high morbidity, and increased mortality. Obesity is an established risk factor for HF. Fluctuation in body mass index (BMI) has shown a higher risk of cardiovascular outcomes. We investigated the association between BMI variability and incident HF. Methods and Results In the UK Biobank, we established a prospective cohort after excluding participants with prevalent HF or cancer at enrollment. A total of 99 368 White participants with ≥3 BMI measures during >2 years preceding enrollment were included, with a median follow‐up of 12.5 years. The within‐participant variability of BMI was evaluated using standardized SD and coefficient of variation. The association of BMI variability with incident HF was assessed using Fine and Gray's competing risk model, adjusting for confounding factors and participant‐specific rate of BMI change. Higher BMI variability measured in both SD and coefficient of variation was significantly associated with higher risk in HF incidence (SD: hazard ratio [HR], 1.05 [95% CI, 1.03–1.08], P

ObjectiveThis study aims to explore the association between outdoor artificial light at night (ALAN) exposure and gestational diabetes mellitus (GDM).MethodsThis study is a retrospective case–control study. According with quantiles, ALAN has been classified into three categories (Q1-Q3). GDM was diagnosed through oral glucose tolerance tests. Conditional logistic regression models were used to evaluate the association between ALAN exposure and GDM risk. The odds ratio (OR) with 95% confidence interval (CI) was used to assess the association. Restricted cubic spline analysis (RCS) was utilized to investigate the no liner association between ALAN and GDM.ResultsA total of 5,720 participants were included, comprising 1,430 individuals with GDM and 4,290 matched controls. Pregnant women exposed to higher levels of ALAN during the first trimester exhibited an elevated risk of GDM compared to those with lower exposure levels (Q2 OR = 1.39, 95% CI 1.20–1.63, p

Background Methods Results Conclusions Using cohort analysis to examine the effects of sleep quality on loneliness among older adults from the life course perspective.The hierarchical age‐period‐cohort growth curve model was used to analyze the data from the 2005–2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS).(1) Loneliness has a ‘U’ curve relationship with age, but with the rate of increase gradually slowing down. (2) There were significant differences in loneliness across birth cohorts, with younger cohorts having higher predicted loneliness than older cohorts at the same age. (3) The influence of different sleep quality on loneliness showed a trend of increasing with age. (4) There were no significant differences in the impact of sleep quality on loneliness in different cohorts.This study has identified heterogeneity in loneliness, emphasising the need for a diversified intervention approach. Sleep quality has a protective effect on loneliness and is easy to assess, making it an important intervention tool. In addition, it is imperative to account for the influences of age and cohort effects when formulating intervention strategies. [ABSTRACT FROM AUTHOR]

Fever is one of the most common clinical conditions and is characterized by pyrogenic infection, malignancy, inflammation, and tissue damage, among others. Ellagic acid (EA) can inhibit the expression of related proteins on the pathway by blocking the nuclear factor kappa-B(NF-κB) signaling pathway, inhibit the levels of pro-inflammatory factors interleukin-1β(IL-1β), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α), increase the level of anti-inflammatory factor IL-10, and effectively alleviate inflammatory symptoms. In addition, EA can also reduce the levels of malondialdehyde(MDA) and nitric oxide(NO) in the body, increase the activities of superoxide dismutase (SOD), glutathione (GSH), and catalase(CAT), scavenge oxidative free radicals, inhibit lipid oxidation, and achieve antipyretic and anti-inflammatory effects. The purpose of this study was to establish the relationship between EA and various inflammatory markers, such as TNF-α, IL-6, IL-1β, prostaglandin E2(PGE2), and cyclic adenosine monophosphate(cAMP), and clarify the mechanism of the cyclooxidase-2(COX-2)/NF-κB signaling pathway. Combined with the metabolomics analysis, our study revealed the effects of EA on multiple endogenous biomarkers, reflecting the characteristics of a multi-component, multi-target, and multi-pathway mechanism. Compared to lipopolysaccharide (LPS)- treated animals, subsequent administration of EA significantly lowered the LPS-induced rectal temperature increase (p < 0.05 or p < 0.01), significantly increased serum SOD and GSH levels (p < 0.05 or p < 0.01), and significantly decreased serum MDA, IL-1β, IL-6, and TNF-α levels (p < 0.05 or p < 0.01). In addition, compared to LPS-treated animals, subsequent administration of EA significantly decreased cerebrospinal fluid cAMP and PGE2 levels (p < 0.05 or p < 0.01), significantly decreased cAMP, significantly increased 5-HT levels (p < 0.05 or p < 0.01), and significantly down-regulated p-NF-κB p65 and COX-2 protein levels in the hypothalamus. Subsequent gas chromatography mass spectrometry(GC-MS) metabolite analysis indicated that 12 differential metabolites were detected in serum isolated 4 h after LPS treatment, and 10 differential metabolites were detected in serum collected 7 h after LPS treatment. Next, Pearson correlation analysis was used to systematically characterize the relationship between the identified metabolites and TNF-α, IL-6, MDA, SOD, PGE2, and cAMP. The levels of propionic acid, pyridine, and L-valine were up-regulated by EA, which inhibited the expression of MDA, IL-1β, and TNF-α and increased the activity of GSH. The levels of inositol, urea, and 2-monopalmitin were down-regulated by EA, which inhibited the expression of MDA, IL-1β, and TNF-α, increased the activity of SOD and GSH, reduced the inflammatory response, and alleviated the oxidative stress state. Combined with the results of the metabolic pathway analysis, we suggest that the pathways of the galactose metabolism, synthesis and degradation of ketone bodies, as well as ascorbic acid and aldehyde acid metabolism are closely related to the antipyretic and anti-inflammatory effects of EA. Our study established the relationship between EA and various inflammatory markers, such as TNF-α, IL-6, IL-1β, PGE2, and cAMP, and clarified the mechanism of the COX-2/NF-κB signaling pathway. Combined with the metabolomics analysis, our study revealed the effects of EA on multiple endogenous biomarkers, reflecting the characteristics of a multi-component, multi-target, and multi-pathway mechanism. [ABSTRACT FROM AUTHOR]

Despite the current detectors achieving outstanding performance, detecting small objects remains a challenging problem. The challenge mainly arises from the low quantity and quality of samples as well as the inherent difficulty in localization. Focusing on these problems, we present an approach for small object detection with a scale-adaptive label assignment scheme and a novel quality-driven localization loss (QLL). First, we perform the scale-adaptive label assignment by combining distance-based and Intersection-over-Union (IoU)-based criterion along with a scale discriminator mechanism to obtain larger quantity and higher quality of training samples. Then, we extend an additional branch parallel to the original localization branch, modeling the localization task as predicting Gaussian probability distributions to incorporate localization uncertainty. Finally, we develop QLL by integrating the scale information and IoU to achieve more accurate localization for small objects. Extensive experiment results on two natural images benchmarks demonstrate that our method underscores its superiority over baseline detector in detecting small objects. Moreover, our method performs better than other recent state-of-the-art methods on the large-scale small object detection benchmark SODA-D without bells and whistles. [ABSTRACT FROM AUTHOR]