High stress hyperglycemia ratio predicts adverse clinical outcome in patients with coronary three-vessel disease: a large-scale cohort study.

BACKGROUND: Coronary three-vessel disease (CTVD) accounts for one-third of the overall incidence of coronary artery disease, with heightened mortality rates compared to single-vessel lesions, including common trunk lesions. Dysregulated glucose metabolism exacerbates atherosclerosis and increases cardiovascular risk. The stress hyperglycemia ratio (SHR) is proposed as an indicator of glucose metabolism status but its association with cardiovascular outcomes in CTVD patients undergoing percutaneous coronary intervention (PCI) remains unclear. METHODS: 10,532 CTVD patients undergoing PCI were consecutively enrolled. SHR was calculated using the formula: admission blood glucose (mmol/L)/[1.59×HbA1c (%)-2.59]. Patients were divided into two groups (SHR Low and SHR High) according to the optimal cutoff value of SHR. Multivariable Cox regression models were used to assess the relationship between SHR and long-term prognosis. The primary endpoint was cardiovascular (CV) events, composing of cardiac death and non-fatal myocardial infarction (MI). RESULTS: During the median follow-up time of 3 years, a total of 279 cases (2.6%) of CV events were recorded. Multivariable Cox analyses showed that high SHR was associated with a significantly higher risk of CV events [Hazard Ratio (HR) 1.99, 95% Confidence interval (CI) 1.58-2.52, P < 0.001). This association remained consistent in patients with (HR 1.50, 95% CI 1.08-2.10, P = 0.016) and without diabetes (HR 1.97, 95% CI 1.42-2.72, P < 0.001). Additionally, adding SHR to the base model of traditional risk factors led to a significant improvement in the C-index, net reclassification and integrated discrimination. CONCLUSIONS: SHR was a significant predictor for adverse CV outcomes in CTVD patients with or without diabetes, which suggested that it could aid in the risk stratification in this particular population regardless of glucose metabolism status.

cVAN: A Novel Sleep Staging Method Via Cross-View Alignment Network.

Sleep staging is imperative for evaluating sleep quality and diagnosing sleep disorders. Extant sleep staging methods with fusing multiple data-views of physiological signals have achieved promising results. However, they remain neglectful of the relationship among different data-views at different feature scales with view position-alignment. To address this, we propose a novel cross-view alignment network, termed cVAN, utilising scale-aware attention for sleep stages classification. Specifically, cVAN principally incorporates two sub-networks of a residual- like network which learn spectral information from time-frequency images and a transformer- like network which learns corresponding temporal information. The prime advantage of cVAN is to adaptively align the learned feature scales among the different data-views of physiological signals with a scale-aware attention by reorganizing feature maps. Extensive experiments on three public sleep datasets demonstrate that cVAN can achieve a new state-of-the-art result, which is superior to existing counterparts. The source code for cVAN is accessible at the URL (https://github.com/Fibonaccirabbit/cVAN).

Mixed effects of ambient air pollutants on oocyte-related outcomes: A novel insight from women undergoing assisted reproductive technology.

Air pollution is widely acknowledged as a significant risk factor for human health, especially reproductive health. Nevertheless, many studies have disregarded the potentially mixed effects of air pollutants on reproductive outcomes. We performed a retrospective cohort study involving 8048 women with 9445 cycles undergoing In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) in China, from 2017 to 2021. A land-use random forest model was applied to estimate daily residential exposure to air pollutants, including sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and fine particulate matter (PM2.5). Individual and joint associations between air pollutants and oocyte-related outcomes of ART were evaluated. In 90 days prior to oocyte pick-up to oocyte pick-up (period A), NO2, O3 and CO was negatively associated with total oocyte yield. In the 90 days prior to oocyte pick-up to start of gonadotropin medication (Gn start, period B), there was a negative dose-dependent association of exposure to five air pollutants with total oocyte yield and mature oocyte yield. In Qgcomp analysis, increasing the multiple air pollutants mixtures by one quartile was related to reducing the number of oocyte pick-ups by -2.00 % (95 %CI: -2.78 %, -1.22 %) in period A, -2.62 % (95 %CI: -3.40 %, -1.84 %) in period B, and -0.98 % (95 %CI: -1.75 %, -0.21 %) in period C. During period B, a 1-unit increase in the WQS index of multiple air pollutants exposure was associated with fewer number of total oocyte (-1.27 %, 95 %CI: -2.16 %, -0.36 %) and mature oocyte (-1.42 %, 95 %CI: -2.41 %, -0.43 %). O3 and NO2 were major contributors with adverse effects on the mixed associations. Additionally, period B appears to be the susceptible window. Our study implies that exposure to air pollution adversely affects oocyte-related outcomes, which raises concerns about the potential adverse impact of air pollution on women's reproductive health.

Deciphering bat influenza H18N11 infection dynamics in male Jamaican fruit bats on a single-cell level.

Jamaican fruit bats (Artibeus jamaicensis) naturally harbor a wide range of viruses of human relevance. These infections are typically mild in bats, suggesting unique features of their immune system. To better understand the immune response to viral infections in bats, we infected male Jamaican fruit bats with the bat-derived influenza A virus (IAV) H18N11. Using comparative single-cell RNA sequencing, we generated single-cell atlases of the Jamaican fruit bat intestine and mesentery. Gene expression profiling showed that H18N11 infection resulted in a moderate induction of interferon-stimulated genes and transcriptional activation of immune cells. H18N11 infection was predominant in various leukocytes, including macrophages, B cells, and NK/T cells. Confirming these findings, human leukocytes, particularly macrophages, were also susceptible to H18N11, highlighting the zoonotic potential of this bat-derived IAV. Our study provides insight into a natural virus-host relationship and thus serves as a fundamental resource for future in-depth characterization of bat immunology.

Heatwaves increase road traffic injury morbidity risk and burden in China and its provinces.

Previous studies have demonstrated health impacts of climate change, but evidence on heatwaves' associations with road traffic injury (RTI) is limited. In this study, individual information of RTI cases in May-September during 2006-2021 in China were obtained from the National Injury Surveillance System. Daily maximum temperatures (TMmax) during 2006-2021 were collected from the ERA-5 reanalysis, and the projected daily TMmax during 2020-2099 were obtained from the latest Coupled Model Intercomparison Project Phase 6 Shared Socioeconomic Pathways scenarios (SSPs). We used a time-stratified case-crossover analysis to investigate the association between short-term exposure (lag01 days) to heatwaves (exceeding the 92.5th percentile of daily TMmax for ≥ three consecutive days) and RTI, and to project heatwave-related RTI until 2099 across China. Finally, a total of 1 031 082 RTI cases were included in the analyses. Compared with non-heatwaves, the risks of RTI increased by 3.61 % during heatwaves. Greater associations were found in people aged 15-64 years, in people with transportation occupation, for non-motor traffic vehicle injuries, for severe RTI cases, and in Western China particularly in Qinghai province. We projected substantial increases in attributable fraction (AF) of heatwave-related RTI in the future, particularly in Western and Southwest China. The national average increase in AF (per decade) during 2020s-2090s was 0.036 % for SSP1-2.6 scenario, and 0.267 % for SSP5-8.5 scenario. This study provided evidence on the associations of heatwaves with RTI, and the heatwave-related RTI will substantially increase in the future.

Temporal and spatial trend analysis of all-cause depression burden based on Global Burden of Disease (GBD) 2019 study.

Depression has been reported as one of the most prevalent psychiatric illnesses globally. This study aimed to obtain information on the global burden of depression and its associated spatiotemporal variation, by exploring the correlation between the global burden of depression and the social development index (SDI) and associated risk factors. Using data from the Global Burden of Disease study from 1990 to 2019, we described the prevalence and burden of disease in 204 countries across 21 regions, including sex and age differences and the relationship between the global disease burden and SDI. The age-standardized rate and estimated annual percentage change were used to assess the global burden of depression. Individuals with documented depression globally ranged from 182,183,358 in 1990 to 290,185,742 in 2019, representing an increase of 0.59%. More patients experienced major depressive disorder than dysthymia. The incidence and disability-adjusted life years of depression were the highest in the 60-64 age group and much higher in females than in males, with this trend occurring across all ages. The age-standardized incidence and adjusted life-years-disability rates varied with different SDI levels. Relevant risk factors for depression were identified. National governments must support research to improve prevention and treatment interventions.

Insight into the status of plasma renin and aldosterone measurement: findings from 526 clinical laboratories in China.

OBJECTIVES: Accurate measurements of renin and aldosterone levels play an important role in primary aldosteronism screening, which is of great importance in the management and categorization of hypertension. The objective of this study is to investigate the current status of plasma renin and aldosterone measurements in China, which is achieved by analyzing the results of 526 clinical laboratories nationwide for three pooled fresh plasma samples derived from more than 2,000 patients. METHODS: Renin and aldosterone in three pooled plasma samples were measured four times in 526 laboratories employing various measurement systems. The inter- and intra-laboratory %CV were calculated and compared. To determine the source of the substantial inter-laboratory %CV, laboratories were categorized according to the measurement systems they are using, and both the inter- and intra-measurement-system %CV were calculated and compared. RESULTS: Regarding renin, the majority of laboratories use four primary commercial immunoassays. However, for aldosterone, in addition to commercial immunoassays, laboratory-developed liquid chromatography-tandem mass spectrometry (LC-MS) methods are also used by laboratories. The median values of intra-laboratory %CVs, intra-measurement-system %CVs, inter-laboratory %CVs, and inter-measurement systems %CVs varied between 1.6 and 2.6 %, 4.6 and 14.9 %, 8.3 and 25.7 %, and 10.0 and 34.4 % for renin, respectively. For aldosterone, these values ranged from 1.4 to 2.2 %, 2.5-14.7 %, 9.9-31.0 %, and 10.0-35.5 %, respectively. CONCLUSIONS: The precision within laboratories and measurement systems for plasma renin and aldosterone measurements is satisfactory. However, the comparability between laboratories using different measurement systems remains lacking, indicating the long way to achieve standardization and harmonization for these two analytes.

Piper longum L. ameliorates gout through the MAPK/PI3K-AKT pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Gout, a painful joint disease with a prevalence ranging from 0.86% to 2.2% in China over the past decade. Traditional medicine has long utilized the medicinal and edible Piper longum L. (PL) fruit spikes for treating gout and other joint conditions like rheumatoid arthritis. However, the exact mechanisms behind its effectiveness remain unclear. AIM OF THE STUDY: This study aimed to investigate the potential of alcoholic extracts from PL fruit spikes as a safe and effective treatment for gout. We used a combined network pharmacology and experimental validation approach to evaluate the mechanisms behind the anti-gout properties of PL. MATERIALS AND METHODS: UPLC-Q/TOF-MS analysis determined the major components of PL. Subsequently, network pharmacology analysis predicted potential molecular targets and related signaling pathways for the anti-gout activity of PL. Molecular docking simulations further explored the interactions between PL compounds and proteins and characterized the properties of potential bioactive secondary metabolites. Mouse models of air pouch inflammation and hyperuricemia were further established, and the anti-gout mechanism of PL was confirmed by examining the expression of proteins related to the MAPK and PI3K-AKT pathways in the tissue. RESULTS: Our analysis revealed 220 bioactive secondary metabolites within PL extracts. Network pharmacology and molecular docking results indicated that these metabolites primarily combat gout by modulating the PI3K-AKT and MAPK signaling pathways. In vivo experiments have also proven that PL at a dose of 100 mg/kg can optimally reduce acute inflammation of gout and kidney damage caused by high uric acid. The anti-gout mechanism involves the PI3K-AKT/MAPK signaling pathway and its downstream NF-κB pathway. CONCLUSION: This study provides compelling evidence for PL's therapeutic potential in gout management by modulating key inflammatory pathways. The findings offer a strong foundation for future clinical exploration of PL as a gout treatment option.

Design and rationale of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study: A cluster randomized controlled trial for hypertension management in primary care.

BACKGROUND: Hypertension management in China is suboptimal with high prevalence and low control rate due to various barriers, including lack of self-management awareness of patients and inadequate capacity of physicians. Digital therapeutic interventions including mobile health and computational device algorithms such as clinical decision support systems (CDSS) are scalable with the potential to improve blood pressure (BP) management and strengthen the healthcare system in resource-constrained areas, yet their effectiveness remains to be tested. The aim of this report is to describe the protocol of the Comprehensive intelligent Hypertension managEment SyStem (CHESS) evaluation study assessing the effect of a multifaceted hypertension management system for supporting patients and physicians on BP lowering in primary care settings. MATERIALS AND METHODS: The CHESS evaluation study is a parallel-group, cluster-randomized controlled trial conducted in primary care settings in China. Forty-one primary care sites from 3 counties of China are randomly assigned to either the usual care or the intervention group with the implementation of the CHESS system, more than 1,600 patients aged 35 to 80 years with uncontrolled hypertension and access to a smartphone by themselves or relatives are recruited into the study and followed up for 12 months. In the intervention group, participants receive patient-tailored reminders and alerts via messages or intelligent voice calls triggered by uploaded home blood pressure monitoring data and participants' characteristics, while physicians receive guideline-based prescription instructions according to updated individual data from each visit, and administrators receive auto-renewed feedback of hypertension management performance from the data analysis platform. The multiple components of the CHESS system can work synergistically and have undergone rigorous development and pilot evaluation using a theory-informed approach. The primary outcome is the mean change in 24-hour ambulatory systolic BP from baseline to 12 months. DISCUSSION: The CHESS trial will provide evidence and novel insight into the effectiveness and feasibility of an implementation strategy using a comprehensive digital BP management system for reducing hypertension burden in primary care settings. TRIAL REGISTRATION: https://www. CLINICALTRIALS: gov, NCT05605418.

Mutual Associations of Exposure to Ambient Air Pollutants in the First 1000 Days of Life With Asthma/Wheezing in Children: Prospective Cohort Study in Guangzhou, China.

BACKGROUND: The first 1000 days of life, encompassing pregnancy and the first 2 years after birth, represent a critical period for human health development. Despite this significance, there has been limited research into the associations between mixed exposure to air pollutants during this period and the development of asthma/wheezing in children. Furthermore, the finer sensitivity window of exposure during this crucial developmental phase remains unclear. OBJECTIVE: This study aims to assess the relationships between prenatal and postnatal exposures to various ambient air pollutants (particulate matter 2.5 [PM2.5], carbon monoxide [CO], sulfur dioxide [SO2], nitrogen dioxide [NO2], and ozone [O3]) and the incidence of childhood asthma/wheezing. In addition, we aimed to pinpoint the potential sensitivity window during which air pollution exerts its effects. METHODS: We conducted a prospective birth cohort study wherein pregnant women were recruited during early pregnancy and followed up along with their children. Information regarding maternal and child characteristics was collected through questionnaires during each round of investigation. Diagnosis of asthma/wheezing was obtained from children's medical records. In addition, maternal and child exposures to air pollutants (PM2.5 CO, SO2, NO2, and O3) were evaluated using a spatiotemporal land use regression model. To estimate the mutual associations of exposure to mixed air pollutants with the risk of asthma/wheezing in children, we used the quantile g-computation model. RESULTS: In our study cohort of 3725 children, 392 (10.52%) were diagnosed with asthma/wheezing. After the follow-up period, the mean age of the children was 3.2 (SD 0.8) years, and a total of 14,982 person-years were successfully followed up for all study participants. We found that each quartile increase in exposure to mixed air pollutants (PM2.5, CO, SO2, NO2, and O3) during the second trimester of pregnancy was associated with an adjusted hazard ratio (HR) of 1.24 (95% CI 1.04-1.47). Notably, CO made the largest positive contribution (64.28%) to the mutual effect. After categorizing the exposure according to the embryonic respiratory development stages, we observed that each additional quartile of mixed exposure to air pollutants during the pseudoglandular and canalicular stages was associated with HRs of 1.24 (95% CI 1.03-1.51) and 1.23 (95% CI 1.01-1.51), respectively. Moreover, for the first year and first 2 years after birth, each quartile increment of exposure to mixed air pollutants was associated with HRs of 1.65 (95% CI 1.30-2.10) and 2.53 (95% CI 2.16-2.97), respectively. Notably, SO2 made the largest positive contribution in both phases, accounting for 50.30% and 74.70% of the association, respectively. CONCLUSIONS: Exposure to elevated levels of mixed air pollutants during the first 1000 days of life appears to elevate the risk of childhood asthma/wheezing. Specifically, the second trimester, especially during the pseudoglandular and canalicular stages, and the initial 2 years after birth emerge as crucial susceptibility windows. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-ROC-17013496; https://tinyurl.com/2ctufw8n.

Direct Imaging of Protein Clusters in Metal-Organic Frameworks.

Protein@metal-organic frameworks (P@MOFs) prepared by coprecipitation of protein, metal ions, and organic ligands represent an effective method for protein stabilization with a wide spectrum of applications. However, the formation mechanism of P@MOFs via the coprecipitation process and the reason why proteins can retain their biological activity in the frameworks with highly concentrated metal ions remain unsettled. Here, by a combined methodology of single molecule localization microscopy and clustering analysis, we discovered that in this process enzyme molecules form clusters with metal ions and organic ligands, contributing to both the nucleation and subsequent crystal growth. We proposed that the clusters played an important role in the retention of overall enzymatic activity by sacrificing protein molecules on the cluster surface. This work offers fresh perspectives on protein behaviors in the formation of P@MOFs, inspiring future endeavors in the design and development of artificial bionanocomposites with high biological activities.

Untargeted metabolomics reveals potential plasma biomarkers for diagnosis of primary aldosteronism using liquid chromatography-mass spectrometry.

Metabolite profiling has the potential to comprehensively bridge phenotypes and complex heterogeneous physiological and pathological states. We performed a metabolomics study using parallel liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis to screen for biomarkers of primary aldosteronism (PA) from a cohort of 111 PA patients and 218 primary hypertension (PH) patients. Hydrophilic interaction chromatography and reversed-phase liquid chromatography separations were employed to obtain a global plasma metabolome of endogenous metabolites. The satisfactory classification between PA and PH patients was obtained using the MVDA model. A total of 35 differential metabolites were screened out and identified. A diagnostic biomarker panel was established using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model and receiver operating characteristic analysis. Joint analysis with clinical indicators, including plasma supine aldosterone level, plasma orthostatic aldosterone level, body mass index, and blood potassium, revealed that the combination of metabolite biomarker panel and plasma supine aldosterone has the best clinical diagnostic efficacy.

Selective Recovery of Battery-Grade Li2CO3 from Spent NCM Cathode Materials Using a One-Step Method of CO2 Carbonation Recovery Without Acids or Bases.

The recovery of spent lithium-ion batteries by traditional acid leaching is limited by serious pollution, complicated technology, and the low purity of Li2CO3. To address the problems of the traditional acid leaching process and increasing demand for decarbonization, a technique for the selective carbonation leaching of Li and the recovery of battery-grade Li2CO3 by a simple concentration precipitation process without acids or bases was developed. The coupling of CO2 and reducing agents could effectively promote the precipitation of MCO3 (M=Ni/Co/Mn) and the selective leaching of Li by decreasing the reducing capability needed for transition metals and decreasing the pH of the solution. The optimal selective leaching process of Li was obtained under 1 MPa CO2 with 20 g/L Na2S2O3 at an L/S ratio of 30 mL/g for 1.5 h. FT-IR, XRD, ICP-MS and other methods were used to reveal the multiphase interfacial reaction mechanism of the carbonation reduction of layered cathode materials, which indicated that the reducing agent Na2S2O3 could promote lattice distortion of the cathode materials and effective separation of Li. In summary, a green and economical method for the selective recovery of battery-grade Li2CO3 using a one-step method of CO2 carbonation recovery in a near-neutral environment was proposed.

Joint effects of heat-humidity compound events on drowning mortality in Southern China.

BACKGROUND: Several previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality. METHODS: The drowning mortality data and meteorological data during the five hottest months (May to September) were collected from 46 cities in Southern China (2013-2018 in Guangdong, Hunan and Zhejiang provinces). Distributed lag non-linear model was first conducted to examine the association between heat-humidity compound events and drowning mortality at city level. Then, meta-analysis was employed to pool the city-specific exposure-response associations. Finally, we analysed the additive interaction of heat and humidity on drowning mortality. RESULTS: Compared with wet-non-hot days, dry-hot days had greater effects (excess rate (ER)=32.34%, 95% CI: 24.64 to 40.50) on drowning mortality than wet-hot days (ER=14.38%, 95%CI: 6.80 to 22.50). During dry-hot days, males (ER=42.40%, 95% CI: 31.92 to 53.72), adolescents aged 0-14 years (ER=45.00%, 95% CI: 21.98 to 72.35) and urban city (ER=36.91%, 95% CI: 23.87 to 51.32) showed higher drowning mortality risk than their counterparts. For wet-hot days, males, adolescents and urban city had higher ERs than their counterparts. Attributable fraction (AF) of drowning attributed to dry-hot days was 23.83% (95% CI: 21.67 to 26.99) which was significantly higher than that for wet-hot days (11.32%, 95% CI: 9.64 to 13.48%). We also observed that high temperature and low humidity had an additive interaction on drowning mortality. CONCLUSION: We found that dry-hot days had greater drowning mortality risk and burden than wet-hot days, and high temperature and low humidity might have synergy on drowning mortality.

Age-period-cohort analysis of ischemic stroke deaths attributable to physical inactivity in different income regions.

This study assessed the global and regional burden of IS (ischemic stroke) deaths due to LPA (low physical activity) from 1990 to 2019, analyzed regional, sex, and age differences in ASMR (age-standardized mortality rate), and provided a comprehensive understanding of the impact of age, period, and cohort on low physical activity related ischemic stroke ASMR. We conducted an APC (age-period-cohort) analysis of the global and four World Bank income level regions' IS mortality data attributed to LPA from 1990 to 2019, using the GBD2019 database, and the results showed that the global net drift of the Ischemic stroke age-standardized mortality attributable to low physical activity was - 1.085%[95% CI: - 1.168, - 1.003].The ASMR drop is most pronounced in the high-income zone, with a net drift of - 2.473% [95% CI: - 2.759, - 2.187] across the four income groups. The influence of age on mortality is increasing in the worldwide old population, while the period and cohort effects are decreasing. We also performed a Joinpoint regression analysis, which revealed that the specific time of considerable drop in ASMR of IS in the global LPA population was 2002-2007, with an APC of -2.628%. The specific period of considerable drop in ASMR in high-income regions with the highest variation was 1999-2007, with an APC = - 4.726%. The global burden of public health deaths caused by LPA is diminishing, with the most notable progress observed in high-income regions. However, in low and lower-middle income areas, the situation continues to deteriorate. Within the global elderly population, the effects of age on mortality is increasing, while the effects of period and cohort are diminishing. These trends vary across income levels, highlighting the necessity for enhanced international collaboration to formulate context-specific public health strategies aimed at enhancing cardiovascular health on a global, regional, and national scale.

Research and application of deep learning-based sleep staging: Data, modeling, validation, and clinical practice.

Over the past few decades, researchers have attempted to simplify and accelerate the process of sleep stage classification through various approaches; however, only a few such approaches have gained widespread acceptance. Artificial intelligence technology, particularly deep learning, is promising for earning the trust of the sleep medicine community in automated sleep-staging systems, thus facilitating its application in clinical practice and integration into daily life. We aimed to comprehensively review the latest methods that are applying deep learning for enhancing sleep staging efficiency and accuracy. Starting from the requisite "data" for constructing deep learning algorithms, we elucidated the current landscape of this domain and summarized the fundamental modeling process, encompassing signal selection, data pre-processing, model architecture, classification tasks, and performance metrics. Furthermore, we reviewed the applications of automated sleep staging in scenarios such as sleep-disorder screening, diagnostic procedures, and health monitoring and management. Finally, we conducted an in-depth analysis and discussion of the challenges and future in intelligent sleep staging, particularly focusing on large-scale sleep datasets, interdisciplinary collaborations, and human-computer interactions.

The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China.

The public health burden of increasing extreme weather events has been well documented. However, the influence of meteorological factors on physical activity remains limited. Existing mixture effect methods cannot handle cumulative lag effects. Therefore, we developed quantile g-computation Distributed lag non-linear model (QG-DLNM) by embedding a DLNM into quantile g-computation to allow for the concurrent consideration of both cumulated lag effects and mixture effects. We gathered repeated measurement data from Henan Province in China to investigate both the individual impact of meteorological factor on step counts using a DLNM, and the joint effect using the QG-DLNM. We projected future step counts linked to changes in temperature and relative humidity driven by climate change under three scenarios from the sixth phase of the Coupled Model Intercomparison Project. Our findings indicate there are inversed U-shaped associations for temperature, wind speed, and mixture exposure with step counts, peaking at 11.6 °C in temperature, 2.7 m/s in wind speed, and 30th percentile in mixture exposure. However, there are negative associations between relative humidity and rainfall with step counts. Additionally, relative humidity possesses the highest weights in the joint effect (49% contribution). Compared to 2022s, future step counts are projected to decrease due to temperature changes, while increase due to relative humidity changes. However, when considering both future temperature and humidity changes driven by climate change, the projections indicate a decrease in step counts. Our findings may suggest Chinese physical activity will be negatively influenced by global warming.

Effects of dietary supplementation of fish oil plus vitamin D3 on gut microbiota and fecal metabolites, and their correlation with nonalcoholic fatty liver disease risk factors: a randomized controlled trial.

We previously reported that fish oil plus vitamin D3 (FO + D) could ameliorate nonalcoholic fatty liver disease (NAFLD). However, it is unclear whether the beneficial effects of FO + D on NAFLD are associated with gut microbiota and fecal metabolites. In this study, we investigated the effects of dietary supplementation of FO + D on gut microbiota and fecal metabolites and their correlation with NAFLD risk factors. Methods: A total of 61 subjects were randomly divided into three groups: FO + D group (2.34 g day-1 of eicosatetraenoic acid (EPA) + docosahexaenoic acid (DHA) + 1680 IU vitamin D3), FO group (2.34 g day-1 of EPA + DHA), and corn oil (CO) group (1.70 g d-1 linoleic acid). Blood and fecal samples were collected at the baseline and day 90. Gut microbiota were analyzed through 16S rRNA PCR analysis, and fecal co-metabolites were determined via untargeted ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Results: The relative abundance of Eubacterium (p = 0.03) and Lactobacillus (p = 0.05) increased, whereas that of Streptococcus (p = 0.02) and Dialister (p = 0.04) decreased in the FO + D group compared with the CO group. Besides, changes in tetracosahexaenoic acid (THA, C24:6 n-3) (p = 0.03) levels were significantly enhanced, whereas 8,9-DiHETrE levels (p < 0.05) were reduced in the FO + D group compared with the CO group. The changes in 1,25-dihydroxyvitamin D3 levels in the fecal samples were inversely associated with insulin resistance, which was determined using the homeostatic model assessment model (HOMA-IR, r = -0.29, p = 0.02), and changes in 8,9-DiHETrE levels were positively associated with adiponectin levels (r = -0.43, p < 0.05). Conclusion: The present results indicate that the beneficial effects of FO + D on NAFLD may be partially attributed to the impact on gut microbiota and fecal metabolites.

Multilayer factors associated with excess all-cause mortality during the omicron and non-omicron waves of the COVID-19 pandemic: time series analysis in 29 countries.

BACKGROUND: The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems. METHODS: Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds. RESULTS: From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI: 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022. CONCLUSION: Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.

Performance of aldosterone-to-renin ratio before washout of antihypertensive drugs in screening of primary aldosteronism.

OBJECTIVE: The aim of this study is to evaluate performance of aldosterone-to-renin ratio (ARR) before washout of antihypertensive drugs as a screening test for primary aldosteronism (PA). METHODS: This retrospective analysis included consecutive patients suspected of having secondary hypertension during a period from January 2017 to May 2022 at authors' institute. For inclusion in the final analysis, ARR must be available prior to as well as after discontinuation of antihypertensives. Patients with ARR ≥2.4(ng/dL)/(µIU/mL) after washout proceeded to confirmatory tests. Diagnosis of PA was established based on positive result of the confirmatory test. Diagnostic accuracy of ARR prior to the washout in predicting PA are shown as sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: The analysis included a total of 1306 patients [median age of 50.2 (41.0-59.0) years, 64.0% male]. Confirmatory tests showed PA in 215(16.5%) patients and essential hypertension (EH) in the remaining 1091(83.5%) patients. In comparison to the second screening test, the first screening test (before washout of antihypertensives) yielded lower plasma aldosterone and higher renin, and consequently lower ARR in both the PA and EH groups. At a cutoff of 0.7(ng/dL)/(µIU/ml), ARR before washout had 96.3% sensitivity, 61.2% specificity, 0.33 PPV and 0.99 NPV. At a lower cutoff of 0.5(ng/dL)/(µIU/ml), the sensitivity, specificity, PPV and NPV are 97.7%, 52.0%, 0.29 and 0.99. CONCLUSIONS: ARR prior to washout of antihypertensives is a sensitive screening test for PA. Washout of antihypertensives could be omitted and further investigation for PA is not warranted if ARR was ≤ 0.7(ng/dL)/(µIU/ml) before washout.