Spatial-temporal Bayesian accelerated failure time models for survival endpoints with applications to prostate cancer registry data.

Prostate cancer is the most common cancer after non-melanoma skin cancer and the second leading cause of cancer deaths in US men. Its incidence and mortality rates vary substantially across geographical regions and over time, with large disparities by race, geographic regions (i.e., Appalachia), among others. The widely used Cox proportional hazards model is usually not applicable in such scenarios owing to the violation of the proportional hazards assumption. In this paper, we fit Bayesian accelerated failure time models for the analysis of prostate cancer survival and take dependent spatial structures and temporal information into account by incorporating random effects with multivariate conditional autoregressive priors. In particular, we relax the proportional hazards assumption, consider flexible frailty structures in space and time, and also explore strategies for handling the temporal variable. The parameter estimation and inference are based on a Monte Carlo Markov chain technique under a Bayesian framework. The deviance information criterion is used to check goodness of fit and to select the best candidate model. Extensive simulations are performed to examine and compare the performances of models in different contexts. Finally, we illustrate our approach by using the 2004-2014 Pennsylvania Prostate Cancer Registry data to explore spatial-temporal heterogeneity in overall survival and identify significant risk factors.

Prognostic Value of Segmental Strain After ST-Elevation Myocardial Infarction: Insights From the EARLY Assessment of MYOcardial Tissue Characteristics by Cardiac Magnetic Resonance (EARLY-MYO-CMR) Study.

BACKGROUND: The prognostic value of left ventricular segmental strain (SS) in ST-elevation myocardial infarction (STEMI) remains unclear. HYPOTHESIS: To assess the prognostic value and application of SS. STUDY TYPE: Retrospective analysis of a prospective registry. POPULATION: Five hundred and forty-four patients after STEMI (500 in Cohort 1, 44 in Cohort 2). FIELD STRENGTH/SEQUENCE: 3 T, balanced steady-state free precession, gradient echo, and gradient echo contrast-enhanced images. ASSESSMENT: Participants underwent cardiac MR during the acute phase after STEMI. Infarct-related artery (IRA) strain was determined based on SS obtained from cine images. The primary endpoint was the composite of major adverse cardiovascular events (MACEs) after 8 years of follow-up. In Cohort 2, SS stability was assessed by MR twice within 8 days. Contrast and non-contrast risk models based on SS were established, leading to the development of an algorithm. STATISTICAL TEST: Student's t-test, Mann-Whitney U-test, Cox and logistic regression, Kaplan-Meier analysis, net reclassification index (NRI). P < 0.05 was considered significant. RESULTS: During a median follow-up of 5.2 years, 83 patients from Cohort 1 experienced a MACE. Among SS, IRA peak circumferential strain (IRA-CS) was an independent factor for MACEs (adjusted hazard ratio 1.099), providing incremental prognostic value (NRI 0.180, P = 0.10). Patients with worse IRA-CS (>-8.64%) demonstrated a heightened susceptibility to MACE. Additionally, IRA-CS was significantly associated with microvascular obstruction (MVO) (adjusted odds ratio 1.084) and infarct size (r = 0.395). IRA-CS showed comparable prognostic effectiveness to global peak circumferential strain (NRI 0.100, P = 0.39), also counterbalancing contrast and non-contrast risk models (NRI 0.205, P = 0.05). In Cohort 2, IRA-CS demonstrated stability between two time points (P = 0.10). Based on risk models incorporating IRA-CS, algorithm "HJKL" was preliminarily proposed for stratification. DATA CONCLUSIONS: IRA-CS is an important prognostic factor, and an algorithm based on it is proposed for stratification. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Association Between Social Vulnerability and SARS-CoV-2 Seroprevalence in Specimens Collected From Commercial Laboratories, United States, September 2021-February 2022.

OBJECTIVE: We conducted a national US study of SARS-CoV-2 seroprevalence by Social Vulnerability Index (SVI) that included pediatric data and compared the Delta and Omicron periods during the COVID-19 pandemic. The objective of the current study was to assess the association between SVI and seroprevalence of infection-induced SARS-CoV-2 antibodies by period (Delta vs Omicron) and age group. METHODS: We used results of infection-induced SARS-CoV-2 antibody assays of clinical sera specimens (N = 406 469) from 50 US states from September 2021 through February 2022 to estimate seroprevalence overall and by county SVI tercile. Bivariate analyses and multilevel logistic regression models assessed the association of seropositivity with SVI and its themes by age group (0-17, ≥18 y) and period (Delta: September-November 2021; Omicron: December 2021-February 2022). RESULTS: Aggregate infection-induced SARS-CoV-2 antibody seroprevalence increased at all 3 SVI levels; it ranged from 25.8% to 33.5% in September 2021 and from 53.1% to 63.5% in February 2022. Of the 4 SVI themes, socioeconomic status had the strongest association with seroprevalence. During the Delta period, we found significantly more infections per reported case among people living in a county with high SVI (odds ratio [OR] = 2.76; 95% CI, 2.31-3.21) than in a county with low SVI (OR = 1.65; 95% CI, 1.33-1.97); we found no significant difference during the Omicron period. Otherwise, findings were consistent across subanalyses by age group and period. CONCLUSIONS: Among both children and adults, and during both the Delta and Omicron periods, counties with high SVI had significantly higher SARS-CoV-2 antibody seroprevalence than counties with low SVI did. These disparities reinforce SVI's value in identifying communities that need tailored prevention efforts during public health emergencies and resources to recover from their effects.

Global, regional, and national burdens of early onset pancreatic cancer in adolescents and adults aged 15-49 years from 1990 to 2019 based on the Global Burden of Disease Study 2019: a cross-sectional study.

BACKGROUND: Early-onset pancreatic cancer (EOPC) in younger populations (age ≤50 years) is likely to be a more aggressive phenotype characterized by poor differentiation. The emerging analysis of the global burden of EOPC is limited and outdated. AIM: To systematically investigate the burden and trend of EOPC based on global populations. METHODS: In this systematic analysis based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, the authors present the number of cases, age-standardized rates (ASRs) per 100 000 population, and risk factors for 204 countries and territories. The average annual percentage changes (AAPCs) for the incidence, mortality, and disability-adjusted life-years (DALYs) of EOPC were calculated using joinpoint regression analysis. RESULTS: According to the GBD 2019 estimates, there were 36 852 new cases of EOPC and 32 004 related deaths. East Asia had the highest number of cases, with 11 401 incidences and 10 149 deaths. The ASRs were 0.94 per 100 000 individuals for incidence and 0.81 per 100 000 for mortality. From 1990 to 2019, the age-standardized incidence increased by 46.9%, mortality increased by 44.6%, and DALYs increased by 41.9% globally. In trend analysis, the global incidence (AAPC, 1.26), mortality (AAPC, 1.24), and DALYs (AAPC, 1.25) of EOPC showed an increasing pattern. The ASRs of incidence, mortality, and DALYs of EOPC in Africa, America, and Asia exhibited a continuous upward trend, while the trend in Europe was fluctuating. Asian males exhibited the fastest growth in incidence (AAPC, 2.15) and mortality (AAPC, 2.13), whereas males in the Americas experienced the slowest increase in new cases (AAPC, 0.72) and deaths (AAPC, 0.67). A certain proportion of EOPC DALYs were attributable to known risk factors: tobacco smoking (13.3%), high BMI, 5.6%, and high fasting plasma glucose 3.2%. Integrating the socio-demographic index (SDI), ASRs of incidence and mortality initially increased with rising SDI, reaching a peak in central Europe (1.5 per 100 000

Domains of Excellence: A CDC Framework for Developing High-Quality, Impact-Driven Public Health Science Publications.

CONTEXT: The Centers for Disease Control and Prevention (CDC) has a long history of using high-quality science to drive public health action that has improved the health, safety, and well-being of people in the United States and globally. To ensure scientific quality, manuscripts authored by CDC staff are required to undergo an internal review and approval process known as clearance. During 2022, CDC launched a scientific clearance transformation initiative to improve the efficiency of the clearance process while ensuring scientific quality. PROGRAM: As part of the scientific clearance transformation initiative, a group of senior scientists across CDC developed a framework called the Domains of Excellence for High-Quality Publications (DOE framework). The framework includes 7 areas ("domains") that authors can consider for developing high-quality and impactful scientific manuscripts: Clarity, Scientific Rigor, Public Health Relevance, Policy Content, Ethical Standards, Collaboration, and Health Equity. Each domain includes multiple quality elements, highlighting specific key considerations within. IMPLEMENTATION: CDC scientists are expected to use the DOE framework when conceptualizing, developing, revising, and reviewing scientific products to support collaboration and to ensure the quality and impact of their scientific manuscripts. DISCUSSION: The DOE framework sets expectations for a consistent standard for scientific manuscripts across CDC and promotes collaboration among authors, partners, and other subject matter experts. Many aspects have broad applicability to the public health field at large and might be relevant for others developing high-quality manuscripts in public health science. The framework can serve as a useful reference document for CDC authors and others in the public health community as they prepare scientific manuscripts for publication and dissemination.

Comprehensive multicomponent characterization and quality assessment of Xiaoyao Wan by UPLC-Q-Orbitrap-MS, HS-SPME-GC-MS and HS-GC-IMS.

Xiaoyao Wan (XYW) is a prescription medicine of traditional Chinese medicine (TCM) with the effects of "soothing the liver and relieving depression," and "strengthening spleen and nourishing blood". XYW has been widely concerned in the treatment of depression and has become one of the commonly used classic formulas in clinical practice. However, the pharmacodynamic substance basis and the quality control studies of XYW are hitherto quite limited. Here, we aim to fully utilize an advanced ultra - performance liquid chromatography-quadrupole - Orbitrap mass spectrometry (UPLC-Q-Orbitrap-MS), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technique to deep characterization of the pharmacological substance basis and quantitatively evaluate the quality of XYW. Firstly, 299 compounds were identified or tentatively characterized, including 198 non-volatile organic compounds (n-VOCs) and 101 volatile organic compounds (VOCs). Secondly, principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to analyze quality differences in XYW at different manufacturers. Thirdly, a parallel reaction monitoring (PRM) method was established and validated to quantify the fourteen major effective substances in different manufacturers of XYW, which were chosen as the benchmarked substances to evaluate the quality of XYW. In conclusion, this study shows that the strategy provides a useful method for quality control of TCM and offers a practical workflow for exploring the quality consistency of TCM.

Cost-of-illness of gastroenteritis caused by rotavirus in Chinese children less than 5 years.

Acute gastroenteritis (AGE) caused by rotavirus (RV) remains a public health issue in China. To accelerate the mass rotavirus vaccination, it is important to inform the policy maker, and the public of the economic burden caused by rotavirus infection. A meta-analysis was conducted applying standardized algorithms. Articles published before January 1, 2023, in English and Chinese were searched through PubMed, CNKI, and WanFang Data. Studies with cost analysis of RV AGE were included. A random-effects model was applied to synthesize the total cost of RV AGE from the societal perspective. A prospective survey aimed to measure the cost of RV AGE was conducted in 2021 and 2022 in Shaoxing city, Zhejiang province, that can represent the developed region. The cost data was applied as deviation indicator, in comparison with the pooled estimate generated from meta-analysis. Totally 286 articles were identified, and eventually 12 studies were included. The pooled total social cost of RV AGE was US$282.1 (95%CI: US$213.4-350.7). The pooled private cost of RV AGE was US$206.4 (95%CI: US$155.2-257.5). RV AGE hospitalized and RV AGE incurred in developed regions caused remarkable higher burden (US$631.2 [95%CI: US$512.6-749.8], and US$333.6 [95%CI: US$234.1-433.2] respectively), compared to RV AGE treated at outpatient, and incurred in less developed regions. Our study demonstrates that RV AGE causes a significant economic burden in China. Given the promising effectiveness and highly cost-effective, introduction of rotavirus vaccines in national immunization programs could substantially reduce the economic burden in China.

Characteristics and risk assessment of chilling injury on Morchella esculenta in Western Sichuan Plateau, China.

The development of precise climate risk zoning for chilling injury of Morchella esculenta can provide scientific basis for agricultural cultivation planning, dynamic assessment of chilling injury, and disaster prevention strategies. Based on meteorological data from 17 counties (cities) that located below the altitude of 3000 m in the Western Sichuan Plateau from 2011 to 2020, we analyzed the critical meteorological conditions for M. esculenta disasters in typical years. With the average yearly cold accumulation and cold injury frequency during the first day when the temperature remained stable between 5 ℃ and 10 ℃ during mushroom emergence as zoning indicators, we established a geographical spatial distribution model of the cold injury index, and then divided the risk level of M. esculenta cold injury in the Western Sichuan Plateau, evaluated the risk of cold injury. The results showed that the temperature index for chilling injury risk of M. esculenta in the study area was the daily minimum temperature ≤2.0 ℃. The daily average temperature <6.0 ℃ would cause slow growth or the cessation of growth, which was set as a warning indicator for chilling injury risk. Along the Dadu River and Minjiang River basins, the frequency of chilling injury on M. esculenta increased from south to north. Wenchuan, Maoxian, and Lixian had the fewest overall chilling injuries during the study period, whereas Jiulong, Yajiang, and Batang had the most. The duration for cold injury was mainly 1-3 d, followed by 4-5 d, and rarely for >5 d. The frequency of chilling injury lasting for more than 5 d in Xiangcheng, Batang, Jiulong, Yajiang, and Xiaojin was more than that lasting for 4-5 d. The annual average days of chilling injury of was 3.0-27.4 d, the daily average minimum temperature was -0.84-1.36 ℃, the extreme lowest temperature was -5.8-0.1 ℃, and the average accumulated cold was 0.16-9.64 ℃·d during the period of chilling injury. With the increases of elevation and latitude, the average days of chilling injury and the average accumulated cold increased. The largest duration of chilling injury was 3-20 d, the maximum accumulated cold was 0.44-13.34 ℃·d. The risk of chilling injury to M. esculenta increased from south to north and from low elevation to high elevation. The suitable planting areas were distributed in strips and branches along the direction of mountains and rivers, mainly in the flat areas of low mountains and valleys below the altitude of 2200 m, including Kangding, Luding, Danba, Wenchuan, Lixian, Maoxian, Jiuzhaigou, and Songpan.

Methane emission and influencing factors of China's oil and natural gas sector in 2020-2060: A source level analysis.

The Chinese oil and gas industry requires targeted policies to reduce methane emissions. To achieve this goal, it is necessary to predict future methane emission trends and analyze the factors that influence them. However, changing economic development patterns, insufficient analysis of various factors influencing emissions, and inadequate resolution of methane emission inventories have made these goals difficult to achieve. Accordingly, this study aims to expand the methane emission estimation method to compile source-level emission inventories for future emissions, analyze the factors influencing them, and form a mechanistic understanding of the methane emissions from the local oil and gas industry. The research results indicate that methane emissions deriving from this industry will increase rapidly before 2030, after which they will decline slowly in all scenarios. The production and utilization processes in the natural gas supply chain, i.e., compressors and liquid unloading, include the main sources of methane emissions. Emissions are affected significantly by total production and consumption. Change in the overall supply and demand of natural gas affects change in methane emissions more significantly than adopting new technologies and strengthening facility maintenance, i.e., the overall supply and demand of natural gas are the dominant factors in controlling methane emissions. This study suggests that controlling the total demand for oil and gas should be at the core of the methane emission control policy for the local oil and gas industry. Moreover, equipment maintenance and emission reduction technologies should be used more effectively to reduce total emissions.

Environmental cadmium exposure alters the internal microbiota and metabolome of Sprague-Dawley rats.

Cadmium (Cd) is a toxic element that can negatively affect both humans and animals. It enters the human and animal bodies through the respiratory and digestive tracts, following which it tends to accumulate in different organs, thereby seriously affecting human and animal health, as well as hampering social and economic development. Cd exposure can alter the composition of intestinal microbiota. In addition, it can damage the peripheral organs by causing the translocation of intestinal microbiota. However, the relationship between translocation-induced changes in the composition of microbiome in the blood and metabolic changes remains unclear. In the present study, we investigated the effects of Cd exposure on microbiota and serum metabolism in rats by omics analysis. The results demonstrated that Cd exposure disrupted the balance between the blood and intestinal flora in Sprague-Dawley (SD) rats, with a significant increase in gut microbiota (Clostridia_UCG_014, NK4A214_group) and blood microbiome (Corynebacterium, Muribaculaceae). However, Cd exposure caused the translocation of Corynebacterium and Muribaculaceae from the gut into the blood. In addition, Cd exposure was associated with the up-regulation of serum indoxyl sulfate, phenyl sulfate, and p-cresol sulfate; down-regulation of δ-tocopherol and L-glutamine; and changes in blood microbiome and metabolites. In conclusion, we identified novel metabolic biomarkers for Cd toxicity, which will also expand our understanding of the role of blood microbiome in Cd-induced injury.

Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices.

In 2016, the city of Shanghai increased the minimum down payment rate requirement for purchasing various types of properties. We study the treatment effect of this major policy change on Shanghai's housing market by employing panel data from March 2009 to December 2021. Since the observed data are either in the form of no treatment or under the treatment but before and after the outbreak of COVID-19, we use the panel data approach suggested by Hsiao et al. (J Appl Econ, 27(5):705-740, 2012) to estimate the treatment effects and a time-series approach to disentangle the treatment effects and the effects of the pandemic. The results suggest that the average treatment effect on the housing price index of Shanghai over 36 months after the treatment is -8.17%. For time periods after the outbreak of the pandemic, we find no significant impact of the pandemic on the real estate price indices between 2020 and 2021.

Research on Mechanisms of Chinese Medicines in Prevention and Treatment of Postoperative Adhesion.

Postoperative adhesion (PA) is currently one of the most unpleasant complications following surgical procedures. Researchers have developed several new strategies to alleviate the formation of PA to a great extent, but so far, no single measure or treatment can meet the expectations and requirements of clinical patients needing complete PA prevention. Chinese medicine (CM) has been widely used for thousands of years based on its remarkable efficacy and indispensable advantages CM treatments are gradually being accepted by modern medicine. Therefore, this review summarizes the formating process of PA and the efficacy and action mechanism of CM treatments, including their pharmacological effects, therapeutic mechanisms and advantages in PA prevention. We aim to improve the understanding of clinicians and researchers on CM prevention in the development of PA and promote the in-depth development and industrialization process of related drugs.

Automatic block-wise genotype-phenotype association detection based on hidden Markov model.

BACKGROUND: For detecting genotype-phenotype association from case-control single nucleotide polymorphism (SNP) data, one class of methods relies on testing each genomic variant site individually. However, this approach ignores the tendency for associated variant sites to be spatially clustered instead of uniformly distributed along the genome. Therefore, a more recent class of methods looks for blocks of influential variant sites. Unfortunately, existing such methods either assume prior knowledge of the blocks, or rely on ad hoc moving windows. A principled method is needed to automatically detect genomic variant blocks which are associated with the phenotype. RESULTS: In this paper, we introduce an automatic block-wise Genome-Wide Association Study (GWAS) method based on Hidden Markov model. Using case-control SNP data as input, our method detects the number of blocks associated with the phenotype and the locations of the blocks. Correspondingly, the minor allele of each variate site will be classified as having negative influence, no influence or positive influence on the phenotype. We evaluated our method using both datasets simulated from our model and datasets from a block model different from ours, and compared the performance with other methods. These included both simple methods based on the Fisher's exact test, applied site-by-site, as well as more complex methods built into the recent Zoom-Focus Algorithm. Across all simulations, our method consistently outperformed the comparisons. CONCLUSIONS: With its demonstrated better performance, we expect our algorithm for detecting influential variant sites may help find more accurate signals across a wide range of case-control GWAS.

Comprehensive multicomponent characterization and quality assessment of Shuang-Huang-Lian powder injection using ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry and ultra-high-performance liquid chromatography-quadrupole-Orbitrap-mass spectrometry.

RATIONALE: Shuang-Huang-Lian powder injection (SHLPI) is a well-known modern traditional Chinese medicine formula preparation (TCMFP) widely used to treat acute upper respiratory infections. However, SHLPI is extracted from pure Chinese medicine and administered through an injection, and many adverse reactions have been reported clinically. Therefore, it is necessary to characterize in depth the chemical composition of SHLPI and quantitatively analyze its potential allergenic components. METHODS: In this study, the samples were analyzed using ion mobility ultra-high-performance liquid chromatography-quadrupole time-of-flight-mass spectrometry (UHPLC-QTOF-MS) combined with a self-built database. Furthermore, the parallel reaction monitoring (PRM) model of ultra-high-performance liquid chromatography-quadrupole-Orbitrap-mass spectrometry (UHPLC-Q-Orbitrap-MS) was used to successfully quantify 10 representative bioactive components. RESULTS: Using this strategy 90 compounds were identified, the fragmentation pathways of five representative compounds in the five main components of SHLPI were summarized, and 10 components (neochlorogenic acid, chlorogenic acid, sweroside, forsythiaside A, luteoloside, isochlorogenic acid B, isochlorogenic acid C, baicalin, phillyrin, and baicalein) were determine as the quality markers of SHLPI based on UPLC-Q-Orbitrap-MS. CONCLUSIONS: This work comprehensively characterized the material basis of SHLPI, summarized the cracking laws of representative substances, and quantitatively analyzed 10 potential allergenic components. Therefore, this study could provide a basis for the quality control of SHLPI and the clinical rational use of drugs to reduce its adverse reactions.

A prognostic nomogram based on risk assessment for invasive micropapillary carcinoma of the breast after surgery.

PURPOSE: Invasive micropapillary carcinoma (IMPC) is one of the rare subtypes of breast cancer. This study aimed to explore a predictive nomogram model for IMPC prognosis. METHODS: A total of 1855 IMPC patients diagnosed after surgery between 2004 and 2014 were identified from the Surveillance, Epidemiology and End Results (SEER) database to build and validate nomogram. A nomogram was created based on univariate and multivariate Cox proportional hazards regression analysis. Receiver operating characteristic (ROC) curves were used to demonstrate the accuracy of the prognostic model. Decision curve analysis (DCA) was performed to evaluate the safety of the model in the range of clinical applications, while calibration curves were used to validate the prediction consistency. RESULTS: Cox regression analysis indicated that age ≥62 at diagnosis, negative ER status, and tumor stage were considered adverse independent factors for overall survival (OS), while patients who were married, white or of other races, received chemotherapy or radiotherapy, had a better postoperative prognosis. The nomogram accurately predicted OS with high internal and external validation consistency index (C index) (0.756 and 0.742, respectively). The areas under the ROC curve (AUCs) of the training group were 0.787, 0.774 and 0.764 for 3, 5 and 10 years, respectively, while those of the validation group were 0.756, 0.766 and 0.762, respectively. The results of both DCA and calibration curves demonstrated the good performance of the model. CONCLUSIONS: A nomogram for IMPC of the breast patients after surgery was developed to estimate 3, 5 and 10 years-OS based on independent risk factors. This model has good accuracy and consistency in predicting prognosis and has clinical application value.

Spatial distribution, ecological risk, and human health assessment of heavy metals in lake surface sections - a case study of Qinghai Lake, China.

Qinghai Lake is the largest inland saltwater lake in China, with a drainage area of 29,661 km2. This study sought to conduct an ecological and human health risk assessment of metals and heavy metals, including copper, as well as investigate their concentration, distribution, and source distribution. In terms of seasonal variation, the increases in Fe, Cr, As, Pb, and Hg were relatively large, and the spatial distribution of metals presented a three-level stepped distribution trend, gradually increasing from east to west. By further exploring the source and migration path of pollutants, our study found that the source of metals in the sediments of Qinghai Lake is mainly controlled by five rivers entering the lake. Enrichment factor (EF) calculations indicated that the metal accumulation or enrichment capacity of the three central points in Qinghai Lake Basin was strong. Interestingly, the enrichment capacity of Cu and Zn was the strongest among all metals but occurred at low and medium concentration levels, respectively. The Igeo and [Formula: see text] ecological risk assessment results indicated that the individual metals posed little to no ecological risks to the Qinghai Lake Basin. However, the multi-element environmental risk comprehensive index (RI) indicated that Hg (RI = 147.97) represented a slight ecological hazard, Mn (RI = 181.13) posed moderate ecological hazards, and Zn (RI = 386.66) posed strong ecological hazards. The human health risk assessment results showed that the heavy metals in the surface sediments of Qinghai Lake currently do not pose a threat to human health. This information may facilitate the implementation of more stringent monitoring programs in the aquatic ecosystem by the relevant regulatory authorities.

Urinary Creatinine Concentrations and Its Explanatory Variables in General Chinese Population: Implications for Creatinine Limits and Creatinine Adjustment.

Objective: The study aimed to analyze the applicability of the World Health Organization's exclusionary guidelines for Urinary creatinine (Ucr) in the general Chinese population, and to identify Ucr related factors. Methods: We conduct a cross-sectional study using baseline data from 21,167 participants in the China National Human Biomonitoring Program. Mixed linear models and restricted cubic splines (RCS) were used to analyze the associations between explanatory variables and Ucr concentration. Results: The geometric mean and median concentrations of Ucr in the general Chinese population were 0.90 g/L and 1.01 g/L, respectively. And 9.36% samples were outside 0.3-3.0 g/L, including 7.83% below the lower limit and 1.53% above the upper limit. Middle age, male, obesity, smoking, higher frequency of red meat consumption and chronic kidney disease were associated significantly with higher concentrations of Ucr. Results of the RCS showed Ucr was positively and linearly associated with body mass index, inversely and linearly associated with systolic blood pressure, diastolic blood pressure, triglycerides level, and glomerular filtration rate, and were non-linearly associated with triiodothyronine. Conclusion: The age- and gender-specific cut-off values of Ucr that determine the validity of urine samples in the general Chinese population were recommended. To avoid introducing bias into epidemiologic associations, the potential predictors of Ucr observed in the current study should be considered when using Ucr to adjust for variations in urine dilution.

Use of radiolabeled hyaluronic acid for preclinical assessment of inflammatory injury and acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is accompanied by a dramatic increase in lung hyaluronic acid (HA), leading to a dose-dependent reduction of pulmonary oxygenation. This pattern is associated with severe infections, such as COVID-19, and other important lung injury etiologies. HA actively participates in molecular pathways involved in the cytokine storm of COVID-19-induced ARDS. The objective of this study was to evaluate an imaging approach of radiolabeled HA for assessment of dysregulated HA deposition in mouse models with skin inflammation and lipopolysaccharide (LPS)-induced ARDS using a novel portable intensified Quantum Imaging Detector (iQID) gamma camera system. METHODS: HA of 10 kDa molecular weight (HA10) was radiolabeled with 125I and 99mTc respectively to produce [125I]I-HA10 and [99mTc]Tc-HA10, followed by comparative studies on stability, in vivo biodistribution, and uptake at inflammatory skin sites in mice with 12-O-tetradecanoylphorbol-13-acetate (TPA)-inflamed ears. [99mTc]Tc-HA10 was used for iQID in vivo dynamic imaging of mice with ARDS induced by intratracheal instillation of LPS. RESULTS: [99mTc]Tc-HA10 and [125I]I-HA10 had similar biodistribution and localization at inflammatory sites. [99mTc]Tc-HA10 was shown to be feasible in measuring skin injury and monitoring skin wound healing. [99mTc]Tc-HA10 dynamic pulmonary images yielded good visualization of radioactive uptake in the lungs. There was significantly increased lung uptake and slower lung washout in mice with LPS-induced ARDS than in control mice. Postmortem biodistribution measurement of [99mTc]TcHA10 (%ID/g) was 11.0 ± 3.9 vs. 1.3 ± 0.3 in the ARDS mice (n = 6) and controls (n = 6) (P < 0.001), consistent with upregulated HA expression as determined by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) staining. CONCLUSIONS: [99mTc]Tc-HA10 is promising as a biomarker for evaluating HA dysregulation that contributes to pulmonary injury in ARDS. Rapid iQID imaging of [99mTc]Tc-HA10 clearance from injured lungs may provide a functional template for timely assessment and quantitative monitoring of pulmonary pathophysiology and intervention in ARDS.

The relationship between farmers' entrepreneurial behavior and macroeconomics based on the probit regression model and entrepreneurial psychological capital.

At present, the research on the influence mechanism of psychological capital on farmers' entrepreneurial behavior is relatively mature. However, the relationship between farmers' entrepreneurial behavior and macroeconomics by entrepreneurial psychological capital (PsyCap) is still unclear. Based on this, firstly, this work analyzes the entrepreneurial PsyCap in detail. Secondly, the research hypothesis is put forward and a conceptual model is implemented. A questionnaire is designed to analyze the current situation of farmers' entrepreneurial PsyCap and entrepreneurial behavior. Finally, a structural equation model (SEM) is implemented to explore the relationship between farmers' entrepreneurial behavior and macroeconomics. The path test of the SEM is utilized to obtain the following. Macroeconomic growth has a significant positive impact on entrepreneurial behavior. Macroeconomics can affect farmers' entrepreneurial behavior to varying degrees by affecting the four entrepreneurial PsyCap of farmers' subjective cognition, Tenacity, hope and open-mindedness. This indicates that entrepreneurial PsyCap plays an intermediary role between farmers' entrepreneurial behavior and macroeconomics. The purpose of this work is to explore the relationship among farmers' entrepreneurial behavior, macroeconomics, and the role of entrepreneurial PsyCap through empirical analysis, thereby providing a theoretical reference for the subsequent country's optimization of farmers' entrepreneurial strategies.

Price Decision-Making in Dual-Channel Healthcare Services Supply Chain Considering the Channel Acceptance, Price Ceiling, and Public Welfare.

Given that an increasing number of online healthcare channels play an essential role as a supply method in the healthcare service supply chain (HSSC), this paper studies the price decision-making problem for a dual-channel HSSC considering the channel acceptance, price ceiling, and public welfare. In this HSSC, a healthcare institution establishes both a traditional offline channel and an online channel to provide healthcare services for some health conditions. Considering the public welfare of healthcare institutions, we employ a sum formula of economic revenue and patient surplus to describe the total revenue of both healthcare service channels. Based on the Stackelberg game, we develop a decentralized supply chain model to maximize supply chain members' revenue. By employing the Karush-Kuhn-Tucker optimality condition, we derive an analytical expression for the optimal service price, which includes the functions of the public welfare coefficient and channel acceptance. Finally, we conduct extensive numerical analyses under various system parameters to verify the optimal price decision-making strategies. Our analytical results indicate that: (1) the healthcare service price is closely related to the patients' channel acceptance, the public welfare coefficient, and the government price ceiling policy; (2) the public welfare coefficient strongly influences the service price and total revenue, and its increase can decrease the economic revenue of the HSSC; (3) the acceptance of online channels is an essential factor that should be carefully considered in the construction of a dual-channel HSSC. Improving patient acceptance of online channels is conducive to developing and improving a sustainable dual-channel HSSC.