High prevalence of hyperuricemia and the association with metabolic syndrome in the rural areas of Southwestern China: A structural equation modeling based on the Zhuang minority cohort.

BACKGROUND AND AIMS: The prevalence of hyperuricemia (HUA) and metabolic syndrome (MetS) in the Zhuang minority had not been examined. We aimed to determine the prevalence of HUA and MetS, and explore the interrelationship among the serum uric acid to creatinine (SUA/Cr) ratio, MetS, and its components. METHODS AND RESULTS: A cross-sectional study was conducted with structured questionnaire and physical examination based on the Zhuang minority cohort. A Structural Equation Model was performed to examine the hypothesis link between the SUA/Cr ratio, MetS, and its components. 10,902 aged 35-74 years Zhuang minority adults were included. The total prevalence of HUA and MetS was 17.5% and 23.7%, respectively. The SUA/Cr ratio had a positive effect on MetS (the standardized coefficient ßr was 0.311 in males and 0.401 in females). The SUA/Cr ratio was positively associated with obesity (ßr = 0.215), dyslipidemia (ßr = 0.177), and high blood pressure (ßr = 0.034) in males and was positively associated with obesity (ßr = 0.303), dyslipidemia (ßr = 0.162), and hyperglycemia (ßr = 0.036) in females. CONCLUSIONS: The prevalence of HUA in the aged 35-74 years Zhuang minority adults was high while the prevalence of MetS was relatively low. As HUA is an earlier-onset metabolic disorder and the SUA/Cr ratio had a positive effect on MetS and its components, the prevention measures of MetS should be strengthened. And the SUA/Cr ratio can be used as an early warning sign to implement the intervention measures of MetS.

HA-FPN: Hierarchical Attention Feature Pyramid Network for Object Detection.

The goals of object detection are to accurately detect and locate objects of various sizes in digital images. Multi-scale processing technology can improve the detection accuracy of the detector. Feature pyramid networks (FPNs) have been proven to be effective in extracting multi-scaled features. However, most existing object detection methods recognize objects in isolation, without considering contextual information between objects. Moreover, for the sake of computational efficiency, a significant reduction in the channel dimension may lead to the loss of semantic information. This study explores the utilization of attention mechanisms to augment the representational power and efficiency of features, ultimately improving the accuracy and efficiency of object detection. The study proposed a novel hierarchical attention feature pyramid network (HA-FPN), which comprises two key components: transformer feature pyramid networks (TFPNs) and channel attention modules (CAMs). In TFPNs, multi-scaled convolutional features are embedded as tokens and self-attention is applied to across both the intra- and inter-scales to capture contextual information between the tokens. CAMs are employed to select the channels with rich channel information to alleviate massive channel information losses. By introducing contextual information and attention mechanisms, the HA-FPN significantly improves the accuracy of bounding box detection, leading to more precise identification and localization of target objects. Extensive experiments conducted on the challenging MS COCO dataset demonstrate that the proposed HA-FPN outperforms existing multi-object detection models, while incurring minimal computational overhead.

Application of a ß-cyclodextrin/graphene oxide-modified fiber for solid-phase microextraction of six fragrance allergens in personal products.

A new ß-cyclodextrin/graphene oxide hybrid material prepared via a chemical covalent interaction and layer-to-layer assembly was developed as a sorbent for the solid-phase microextraction of fragrance allergens. As a result of its ultra-large surface area, large delocalized π-electron system and abundant hydroxyls, the ß-cyclodextrin/graphene oxide-coated fiber could be used to extract particular compounds via strong π-π interactions, van der Waals forces and hydrogen bonding interactions. ß-Cyclodextrin with a hydrophobic interior cavity and hydrophilic peripheral face was conducive in extracting the fragrances with hydrophobic and hydrophilic groups. Under the optimized extraction and desorption conditions, the ß-cyclodextrin/graphene oxide-coated fiber showed acceptable extraction efficiency for hydrophilic and hydrogen-bonding-donating alcohols. Compared with other methods based on different coating fibers, the proposed fiber obtained wide linear ranges for fragrances with correlation coefficients ranging from 0.9921 to 0.9970, and low limits of detection in the range of 0.050-0.150 µg L(-1). The obtained results indicated that the newly developed fiber was a selective, feasible and cost-effective microextraction medium and could be successfully applied for the determination of several fragrances in personal products.

Histidine-modified organic-silica hybrid monolithic column for mixed-mode per aqueous and ion-exchange capillary electrochromatography.

A novel organic-silica hybrid monolith was prepared through the binding of histidine onto the surface of monolithic matrix for mixed-mode per aqueous and ion-exchange capillary electrochromatography. The imidazolium and amino groups on the surface of the monolithic stationary phase were used to generate an anodic electro-osmotic flow as well as to provide electrostatic interaction sites for the charged compounds at low pH. Typical per aqueous chromatographic behavior was observed in water-rich mobile phases. Various polar and hydrophilic analytes were selected to evaluate the characteristics and chromatographic performance of the obtained monolith. Under per aqueous conditions, the mixed-mode mechanism of hydrophobic and ion-exchange interactions was observed and the resultant monolithic column proved to be very versatile for the efficient separations of these polar and hydrophilic compounds (including amides, nucleosides and nucleotide bases, benzoic acid derivatives, and amino acids) in highly aqueous mobile phases. The successful applications suggested that the histidine-modified organic-silica hybrid monolithic column could offer a wide range of retention behaviors and flexible selectivities toward polar and hydrophilic compounds.

The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19.

Internet search data was a useful tool in the pre-warning of COVID-19. However, the lead time and indicators may change over time and space with the new variants appear and massive nucleic acid testing. Since Omicron appeared in late 2021, we collected the daily number of cases and Baidu Search Index (BSI) of seven search terms from 1 January to 30 April, 2022 in 12 provinces/prefectures to explore the variation in China. Two search peaks of "COVID-19 epidemic", "Novel Coronavirus" and "COVID-19" can be observed. One in January, which showed 3 days lead time in Henan and Tianjin. Another on early March, which occurred 0-28 days ahead of the local epidemic but the lead time had spatial variation. It was 4 weeks in Shanghai, 2 weeks in Henan and 5-8 days in Jilin Province, Jilin and Changchun Prefecture. But it was only 1-3 days in Tianjin, Quanzhou Prefecture, Fujian Province and 0 day in Shenzhen, Shandong Province, Qingdao and Yanbian Prefecture. The BSI was high correlated (rs:0.70-0.93) to the number of cases with consistent epidemiological change trend. The lead time of BSI had spatial and temporal variation and was close related to the strength of nucleic acid testing. The case detection ability should be strengthened when perceiving BSI increase.

High Prevalence of Hyperuricemia and Associated Factors among Zhuang Adults: A Cross-Sectional Study Based on the Ethnic Minority Population Cohort in the Southwestern China.

The highest prevalence of hyperuricemia was found in Zhuang minority adults in two national surveys in China, with only 1% Zhuang study subjects. However, the prevalence of hyperuricemia and the associated factors in Zhuang adults have not been well-addressed. A cross-sectional study was conducted to explore the prevalence of hyperuricemia and the common comorbidities, and the associated factors in Zhuang adults based on the Guangxi Ethnic Minority Population Cohort. Among 11,175 Zhuang adults aged 35-74 years, the age- and sex-standardized prevalence rate was 18.1% for hyperuricemia and 1.1% for gout. The standardized prevalence rate and awareness rate were 31.6% and 32.3%, respectively, for hypertension, and were 5.1% and 48.2%, respectively, for diabetes. High education level, history of coronary heart disease (CHD), hypertension, being a current drinker, high body mass index (BMI), central obesity, hyper-triglyceride (hyper-TG), hyper-total cholesterol (hyper-TC), hypo-high density lipoprotein cholesterol (hypo-HDL-C), and abnormal aspartate aminotransferase (AST) were risk factors, while smoking and diabetes were protective factors of hyperuricemia in males. Older age, being single/divorced, having a high education level, hypertension, drinking tea, high BMI, central obesity, hyper-TG, hyper-TC, hypo-HDL-C, and abnormal alanine aminotransferase (ALT) were risk factors in females. The high prevalence of hyperuricemia but low prevalence of gout and common comorbidities in Zhuang adults may be due to a lag effect of lifestyle changes. Health education and health management should be strengthened to prevent the progression of comorbidities, considering the lag effect and low awareness rate.

GRMT: Generative Reconstruction of Mutation Tree From Scratch Using Single-Cell Sequencing Data.

Single-cell sequencing (SCS) now promises the landscape of genetic diversity at single cell level, and is particularly useful to reconstruct the evolutionary history of tumor. There are multiple types of noise that make the SCS data notoriously error-prone, and significantly complicate tumor tree reconstruction. Existing methods for tumor phylogeny estimation suffer from either high computational intensity or low-resolution indication of clonal architecture, giving a necessity of developing new methods for efficient and accurate reconstruction of tumor trees. We introduce GRMT (Generative Reconstruction of Mutation Tree from scratch), a method for inferring tumor mutation tree from SCS data. GRMT exploits the k-Dollo parsimony model to allow each mutation to be gained once and lost at most k times. Under this constraint on mutation evolution, GRMT searches for mutation tree structures from a perspective of tree generation from scratch, and implements it to an iterative process that gradually increases the tree size by introducing a new mutation per time until a complete tree structure that contains all mutations is obtained. This enables GRMT to efficiently recover the chronological order of mutations and scale well to large datasets. Extensive evaluations on simulated and real datasets suggest GRMT outperforms the state-of-the-arts in multiple performance metrics. The GRMT software is freely available at https://github.com/qasimyu/grmt.