The burden of cardiovascular disease attributable to high fasting plasma glucose：Findings from the global burden of disease study 2019.

AIM: High fasting plasma glucose (HFPG) is a key risk factor for cardiovascular disease (CVD). Few studies have evaluated the CVD burden attributable to HFPG globally. It is urgent to investigate the current epidemiological pattern and past trends of CVD attributable to HFPG. METHODS: We used the Global Burden of Disease Study (GBD) 2019 to describe the CVD burden attributable to HFPG in 2019 and evaluate temporal trends between 1990 and 2019. RESULTS: Global Disability-Adjusted Life Years (DALYs) cases and death cases of HFPG-related CVD were approximately 72,591,163 and 3,763,298 in 2019, with an increase of 107.4 % and 114.6 % compared with 1990, respectively. Despite the increases, the age-standardized DALYs rate (ASDAR) and age-standardized death rate (ASDR) of HFPG-related CVD contributed to 895.2 per 100,000 people and 48.4 per 100,000 people in 2019, with an estimated annual percentage change (EAPC) of -0.22 and -0.31, respectively, from 1990. The highest ASDAR and ASDR of HFPG-related CVD were in 2019 observed in the low-middle SDI (Socio-demographic Index) and middle-SDI regions. Low SDI and some low-middle SDI regions showed an increase in ASDAR and ASDR of HFPG-related CVD from 1990 to 2019. Males are more affected by HFPG-related CVD than females across all years. The CVD burden attributable to HFPG in the elderly are higher than those in the young in 2019. The main causes of the global CVD burden attributable to HFPG in 2019 were ischemic heart disease, stroke, and peripheral arterial disease. CONCLUSION: The CVD burden attributable to HFPG remains a serious public health challenge threatening human health worldwide. It is necessary to develop more targeted and specific strategies to reduce CVD burden attributable to HFPG, especially in males, elderly, and lower SDI regions.

Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis.

Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods that aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes in three simulation scenarios and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in Root Mean Squared Error (RMSE) of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.

Metagenomic analysis of a thermophilic bacterial consortium and its use in the bioremediation of a petroleum-contaminated soil.

Biodegradation is difficult at high temperatures due to the limited capacity of microorganisms to survive and function outside their optimum temperature range. Here, a thermophilic petroleum-degrading consortium was enriched from compost at a temperature of 55 °C. 16S rDNA and metagenomic techniques were used to analyze the composition of the consortium and the mechanisms of degradation. The consortium degraded 17000 mg total petroleum hydrocarbons (TPHs) L-1 with a degradation efficiency of 81.5% in 14 days. The consortium utilized a range of substrates such as n-hexadecane, n-docosane, naphthalene and pyrene and grew well over a wide range of pH (4-10) and salinity (0-90 g L-1). The hydrocarbon-degrading extremophilic consortium contained, inter alia, (relative abundance >1%) Caldibacillus, Geobacillus, Mycolicibacterium, Bacillus, Chelatococcus, and Aeribacillus spp. Metagenomic analysis was conducted to discover the degradation and environmental tolerance functional genes of the consortium. Two alkane hydroxylase genes, alkB and ladA, were found. A microcosm study shows that the consortium promoted the bioremediation of soil TPHs. The results indicate that the consortium may be a good candidate for the high-temperature bioremediation of petroleum-contaminated soils.

Research note: Preparation and stability of egg white fluidic gel induced by ultrasonic pretreatment.

Ultrasound-induced egg white fluidic gels (UEFG) were prepared through ultrasonic pretreatment followed by subsequent heating. The optimal preparation parameters for UEFG were: ultrasonic power density between 0.2 to 0.8 W/mL, ultrasonic treatment time surpassing 150 s, heating temperature within 70 to 76°C, and heating time under 16 min. The prepared UEFG is a milky white solution with a viscosity lower than that of fresh egg white, and displayed a particle size distribution primarily between 100 and 1,200 nm. Stability assessments conducted over 28 d at 4°C revealed that UEFG remained stable at pH 6-10, with exceptional stability from pH 8 to 10, while it is less stable in highly acidic (pH 2-4) or basic environments (pH 12). The UEFG also showed commendable stability in the presence of salt and sucrose solutions. We report a simple and novel method for preparing UEFG with good flowability after heating treatment. The UEFG has broad applications in the food industry, such as precooked egg white powder, high protein beverages, composite dairy products, etc.

An Underwater Source Location Privacy Protection Scheme Based on Game Theory in a Multi-Attacker Cooperation Scenario.

Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This paper addresses the aforementioned limitations by proposing an underwater source location privacy protection scheme based on game theory under the scenario of multiple cooperating attackers (SLP-MACGT). First, a transformation method of a virtual coordinate system is proposed to conceal the real position of nodes to a certain extent. Second, through using the relay node selection strategy, the diversity of transmission paths is increased, passive attacks by adversaries are resisted, and the privacy of source nodes is protected. Additionally, a secure data transmission technique utilizing fountain codes is employed to resist active attacks by adversaries, ensuring data integrity and enhancing data transmission stability. Finally, Nash equilibrium could be achieved after the multi-round evolutionary game theory of source node and multiple attackers adopting their respective strategies. Simulation experiments and performance evaluation verify the effectiveness and reliability of SLP-MACGT regarding aspects of the packet forwarding success rate, security time, delay and energy consumption: the packet delivery rate average increases by 30%, security time is extended by at least 85%, and the delay is reduced by at least 90% compared with SSLP, PP-LSPP, and MRGSLP.

GSH-Responsive Liposomes with Heat Shock Protein Regulatory Ability for Efficient Photodynamic/Photothermal Combined Therapy of Tumors.

Phototherapy, represented by photodynamic therapy (PDT) and photothermal therapy (PTT), has great potential in tumor treatment. However, the presence of antioxidant glutathione (GSH) and the heat shock proteins (HSPs) expression caused by high temperature can weaken the effects of PDT and PTT. Here, a multifunctional nanocomplex BT&GA@CL is constructed to realize enhanced synergistic PDT/PTT. Cinnamaldehyde liposomes (CLs) formed by cinnamaldehyde dimer self-assembly were loaded with in gambogic acid (GA) and an aggregation-induced emission molecule BT to obtain BT&GA@CL. As a drug carrier, CL can consume glutathione (GSH) and release drugs responsively. The released BT aggregates can simultaneously act as both a photothermal agent and photosensitizer to achieve PDT and PTT under 660 nm laser irradiation. Specifically, GA as an HSP90 inhibitor can attenuate PTT-induced HSP90 protein expression, thereby weakening the tolerance of tumor cells to high temperatures and enhancing PTT. Such a multifunctional nanocomplex simultaneously modulates the content of GSH and HSP90 in tumor cells, thus enhancing both PDT and PTT, ultimately achieving the goal of efficient combined tumor suppression.

Vacancy-Defect Ternary Topological Insulators Bi2Se2Te Encapsulated in Mesoporous Carbon Spheres for High Performance Sodium Ion Batteries and Hybrid Capacitors.

Ternary topological insulators have attracted worldwide attention because of their broad application prospects in fields such as magnetism, optics, electronics, and quantum computing. However, their potential and electrochemical mechanisms in sodium ion batteries (SIBs) and hybrid capacitors (SIHCs) have not been fully studied. Herein, a composite material comprising vacancy-defects ternary topological insulator Bi2Se2Te encapsulated in mesoporous carbon spheres (Bi2Se2Te@C) is designed. Bi2Se2Te with ample vacancy-defects has a wide interlayer spacing to enable frequent insertion/extraction of Na+ and boost reaction kinetics within the electrode. Meanwhile, the Bi2Se2Te@C with optimized yolk-shell structure can buffer the volume variation without breaking the outer protective carbon shell, ensuring structural stability and integrity. As expected, the Bi2Se2Te@C electrode delivers high reversible capacity and excellent rate capability in half SIB cells. Various electrochemical analyses and theoretical calculations manifest that Bi2Se2Te@C anode confirms the synergistic effect of ternary chalcogenide systems and suitable void space yolk-shell structure. Consequently, the full cells of SIB and SIHC coupled with Bi2Se2Te@C anode exhibit good performance and high energy/power density, indicating its widespread practical applications. This design is expected to offer a reliable strategy for further exploring advanced topological insulators in Na+-based storage systems.

Polydopamine Synergizes with Quercetin Nanosystem to Reshape the Perifollicular Microenvironment for Accelerating Hair Regrowth in Androgenetic Alopecia.

Accumulated reactive oxygen species (ROS) and their resultant vascular dysfunction in androgenic alopecia (AGA) hinder hair follicle survival and cause permanent hair loss. However, safe and effective strategies to rescue hair follicle viability to enhance AGA therapeutic efficiency remain challenging. Herein, we fabricated a quercetin-encapsulated (Que) and polydopamine-integrated (PDA@QLipo) nanosystem that can reshape the perifollicular microenvironment to initial hair follicle regeneration for AGA treatment. Both the ROS scavenging and angiogenesis promotion abilities of PDA@QLipo were demonstrated. In vivo assays revealed that PDA@QLipo administrated with roller-microneedles successfully rejuvenated the "poor" perifollicular microenvironment, thereby promoting cell proliferation, accelerating hair follicle renewal, and facilitating hair follicle recovery. Moreover, PDA@QLipo achieved a higher hair regeneration coverage of 92.5% in the AGA mouse model than minoxidil (87.8%), even when dosed less frequently. The nanosystem creates a regenerative microenvironment by scavenging ROS and augmenting neovascularity for hair regrowth, presenting a promising approach for AGA clinical treatment.

Risk Factors Asscociated with Hypokalemia during Postanesthesia Recovery and Its Impact on Outcomes in Gynecological Patients: A Propensity Score Matching Study.

OBJECTIVE: This study aimed to explore the risk factors and outcomes of hypokalemia during the recovery period from anesthesia in the gynecological population. METHODS: This retrospective cohort study included 208 patients who underwent gynecological surgery at our institution between January 2021 and March 2022. Data were collected for each patient, including demographics, disease status, surgical data, and clinical information. Preoperative bowel preparation, postoperative gastrointestinal function, and electrolyte levels were compared between the two groups using propensity score matching (PSM). RESULTS: The incidence of hypokalemia (serum potassium level <3.5 mmol/L) during the recovery period from anesthesia was approximately 43.75%. After PSM, oral laxative use (96.4% vs. 82.4%, P=0.005), the number of general enemas (P=0.014), and the rate of ≥2 general enemas (92.9% vs. 77.8%, P=0.004) were identified as risk factors for hypokalemia, which was accompanied by decreased PaCO2 and hypocalcemia. There were no significant differences in postoperative gastrointestinal outcomes, such as the time to first flatus or feces, the I-FEED score (a scoring system was created to evaluate impaired postoperative gastrointestinal function), or postoperative recovery outcomes, between the hypokalemia group and the normal serum potassium group. CONCLUSION: Hypokalemia during postanesthesia recovery period occurred in 43.75% of gynecological patients, which resulted from preoperative mechanical bowel preparation; however, it did not directly affect clinical outcomes, including postoperative gastrointestinal function, postoperative complications, and length of hospital stay.

Assessment of nomogram model for the prediction of esophageal variceal hemorrhage in hepatitis B-induced hepatic cirrhosis.

BACKGROUND: Esophageal variceal (EV) hemorrhage is a life-threatening consequence of portal hypertension in hepatitis B virus (HBV) -induced cirrhotic patients. Screening upper endoscopy and endoscopic variceal ligation to find EVs for treatment have complications, contraindications, and high costs. We sought to identify the nomogram models (NMs) as alternative predictions for the risk of EV hemorrhage. METHODS: In this case-control study, we retrospectively analyzed 241 HBV-induced liver cirrhotic patients treated for EVs at the Second People's Hospital of Fuyang City, China from January 2021 to April 2023. We applied univariate analysis and multivariate logistic regression to assess the accuracy of various NMs in EV hemorrhage. The area under the curve (AUC) and calibration curves of the receiver's operating characteristics were used to evaluate the predictive accuracy of the nomogram. Decision curve analysis (DCA) was used to determine the clinically relevant of nomograms. RESULTS: In the prediction group, multivariate logistic regression analysis identified platelet distribution and spleen length as independent risk factors for EVs. We applied NMs as the independent risk factors to predict EVs risk. The NMs fit well with the calibration curve and have good discrimination ability. The AUC and DCA demonstrated that NMs with a good net benefit. The above results were validated in the validation cohort. CONCLUSION: Our non-invasive NMs based on the platelet distribution width and spleen length may be used to predict EV hemorrhage in HBV-induced cirrhotic patients. NMs can help clinicians to increase diagnostic performance leading to improved treatment measures.

Proteogenomic insights into early-onset endometrioid endometrial carcinoma: predictors for fertility-sparing therapy response.

Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10Q144K mutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.

The structure, self-assembly and dynamics of lipid nanodiscs revealed by computational approaches.

Nanodisc technology is increasingly being used in structural, biochemical and biophysical studies of membrane proteins. The computational approaches have revealed many important features of nanodisc assembly, structures and dynamics. Therefore, we reviewed the application of computational approaches, especially molecular modeling and molecular dyncamics (MD) simulations, to characterize nanodiscs, including the structural models, assembly and disassembly, protocols for modeling, structural properties and dynamics, and protein-lipid interactions in nanodiscs. More amazing computational studies about nanodiscs are looked forward to in the future.

Learning Graph Attentions via Replicator Dynamics.

Graph Attention (GA) which aims to learn the attention coefficients for graph edges has achieved impressive performance in GNNs on many graph learning tasks. However, existing GAs are usually learned based on edges' (or connected nodes') features which fail to fully capture the rich structural information of edges. Some recent research attempts to incorporate the structural information into GA learning but how to fully exploit them in GA learning is still a challenging problem. To address this challenge, in this work, we propose to leverage a new Replicator Dynamics model for graph attention learning, termed Graph Replicator Attention (GRA). The core of GRA is our derivation of replicator dynamics based sparse attention diffusion which can explicitly learn context-aware and sparse preserved graph attentions via a simple self-supervised way. Moreover, GRA can be theoretically explained from an energy minimization model. This provides a more theoretical justification for the proposed GRA method. Experiments on several graph learning tasks demonstrate the effectiveness and advantages of the proposed GRA method on ten benchmark datasets.

Evaluation of Blue Honeysuckle Berries (Lonicera caerulea L.) Dried at Different Temperatures: Basic Quality, Sensory Attributes, Bioactive Compounds, and In Vitro Antioxidant Activity.

This study aims to comprehensively investigate the effects of hot-air dehydration on the quality of blue honeysuckle berries (Lonicera caerulea L.). The results demonstrated that drying with hot air at 40-65 °C for 7-72 h resulted in blue honeysuckle berries with a moisture content of 0.21-1.10 g H2O/g dry weight. Generally, low to medium temperatures (40-55 °C) showed a better effect on the quality than high temperatures (60-65 °C). Specifically, drying at 40 °C exclusively resulted in better retention of cuticular wax, the best sensory appearance, and the highest total phenolic content. Drying at 45 °C and 50 °C resulted in the highest antioxidant capacity and the optimal sensory flavor. Drying at 55 °C led to the highest soluble solid/acid ratio, ascorbic acid concentration, total flavonoid, and total anthocyanin. The work introduces an innovative raw berry product and provides a comprehensive practical and theoretical framework for convective dehydration of blue honeysuckle berries.

The application value of metagenomic next-generation sequencing technology in the diagnosis and treatment of neonatal infectious meningitis - a single center retrospective case-control study.

OBJECTIVE: This retrospective study was conducted to investigate the application value of metagenomics next generation sequencing (mNGS) technology in the diagnosis and treatment of neonatal infectious meningitis. METHODS: From 1 January 2020 to 31 December 2022, 73 newborns suspected of infectious meningitis were hospitalized. After screening by inclusion and exclusion criteria, 69 newborns were subsequently included in the study, containing 27 cases with positive mNGS result and 42 cases with negative mNGS result. Furthermore, according to the diagnosis of meningitis, mNGS positive group and mNGS negative group were further divided into infectious meningitis with mNGS (+) group (n = 27) and infectious meningitis with mNGS (-) group (n = 26), respectively. RESULTS: (1) Compared with cerebrospinal fluid (CSF) culture, mNGS has better diagnostic value [positive predictive value (PPV) = 100.00% (27/27), negative predictive value (NPV) = 38.10% (16/42), agreement rate = 62.32% (43/69), area under the curve (AUC) = 0.750, 95% confidence interval (CI): 0.636-0.864]. (2) There were significant differences in the onset age, age at first CSF test, CSF leukocyte count, CSF glucose, positive rate of CSF culture, blood leukocyte count, procalcitonin (PCT), C-reaction protein (CRP), age at first mNGS test and adjusting anti-infective medication in the comparison between infectious meningitis with mNGS (+) group and infectious meningitis with mNGS (-) group (p < 0.05). (3) mNGS could help improve the cure rate [crude odds ratio (OR) = 3.393, 95%CI: 1.072-10.737; adjusted OR = 15.580, 95%CI: 2.114-114.798]. CONCLUSION: Compared with classic meningitis detection methods, mNGS has better PPV, NPV, agreement rate, and AUC. mNGS could help improve the cure rate.

Urinary Metabolites of Polycyclic Aromatic Hydrocarbons of Rural Population in Northwestern China: Oxidative Stress and Health Risk Assessment.

Polycyclic aromatic hydrocarbon (PAH) exposure is suspected to be linked to oxidative damage. Herein, ten PAH human exposure biomarkers [hydroxylated PAH metabolites (OH-PAHs)] and five oxidative stress biomarkers (OSBs) were detected in urine samples collected from participants living in a rural area (n = 181) in Northwestern China. The median molar concentration of ΣOH-PAHs in urine was 47.0 pmol mL-1. The 2-hydroxynaphthalene (2-OHNap; median: 2.21 ng mL-1) was the dominant OH-PAH. The risk assessment of PAH exposure found that hazard index (HI) values were <1, indicating that the PAH exposure of rural people in Jingyuan would not generate significant cumulative risks. Smokers (median: 0.033) obtained higher HI values than nonsmokers (median: 0.015, p < 0.01), suggesting that smokers face a higher health risk from PAH exposure than nonsmokers. Pearson correlation and multivariate linear regression analysis revealed that ΣOH-PAH concentrations were significant factors in increasing the oxidative damage to deoxyribonucleic acid (DNA) (8-hydroxy-2'-deoxyguanosine, 8-OHdG), ribonucleic acid (RNA) (8-oxo-7,8-dihydroguanine, 8-oxoGua), and protein (o, o'-dityrosine, diY) (p < 0.05). Among all PAH metabolites, only 1-hydroxypyrene (1-OHPyr) could positively affect the expression of all five OSBs (p < 0.05), suggesting that urinary 1-OHPyr might be a reliable biomarker for PAH exposure and a useful indicator for assessing the impacts of PAH exposure on oxidative stress. This study is focused on the relation between PAH exposure and oxidative damage and lays a foundation for the study of the health effect mechanism of PAHs.

Water-assisted oxidative redispersion of Cu particles through formation of Cu hydroxide at room temperature.

Sintering of active metal species often happens during catalytic reactions, which requires redispersion in a reactive atmosphere at elevated temperatures to recover the activity. Herein, we report a simple method to redisperse sintered Cu catalysts via O2-H2O treatment at room temperature. In-situ spectroscopic characterizations reveal that H2O induces the formation of hydroxylated Cu species in humid O2, pushing surface diffusion of Cu atoms at room temperature. Further, surface OH groups formed on most hydroxylable support surfaces such as γ-Al2O3, SiO2, and CeO2 in the humid atmosphere help to pull the mobile Cu species and enhance Cu redispersion. Both pushing and pulling effects of gaseous H2O promote the structural transformation of Cu aggregates into highly dispersed Cu species at room temperature, which exhibit enhanced activity in reverse water gas shift and preferential oxidation of carbon monoxide reactions. These findings highlight the important role of H2O in the dynamic structure evolution of supported metal nanocatalysts and lay the foundation for the regeneration of sintered catalysts under mild conditions.