Invasive assessment of coronary microvascular dysfunction and cardiovascular outcomes across the full spectrum of CHD: a meta-analysis.

INTRODUCTION AND OBJECTIVES: Coronary microvascular dysfunction (CMD) is highly prevalent and is recognized as an important clinical entity in patients with coronary heart disease (CHD). Nevertheless, the association of CMD with adverse cardiovascular events in the spectrum of CHD has not been systemically quantified. METHODS: We searched electronic databases for studies on patients with CHD in whom coronary microvascular function was measured invasively, and clinical events were recorded. The primary endpoint was major adverse cardiac events (MACE), and the secondary endpoint was all-cause death. Estimates of effect were calculated using a random-effects model from published risk ratios. RESULTS: We included 27 studies with 11 404 patients. Patients with CMD assessed by invasive methods had a higher risk of MACE (RR, 2.18; 95%CI, 1.80-2.64; P<.01) and all-cause death (RR, 1.88; 95%CI, 1.55-2.27; P<.01) than those without CMD. There was no significant difference in the impact of CMD on MACE (interaction P value=.95) among different invasive measurement modalities. The magnitude of risk of CMD assessed by invasive measurements for MACE was greater in acute coronary syndrome patients (RR, 2.84, 95%CI, 2.26-3.57; P<.01) than in chronic coronary syndrome patients (RR, 1.77, 95%CI, 1.44-2.18; P<.01) (interaction P value<.01). CONCLUSIONS: CMD based on invasive measurements was associated with a high incidence of MACE and all-cause death in patients with CHD. The magnitude of risk for cardiovascular events in CMD as assessed by invasive measurements was similar among different methods but varied among CHD populations.

Assessment of coastal eco-environmental sustainable development under multiple pressures: A case study of Jiaozhou Bay, China.

The increasing demand for economic development in the coastal zone is exerting greater pressure on the eco-environment in this region. Therefore, it is imperative to conduct comprehensive research on the sustainable development of the eco-environment in coastal areas. Grounded in sustainable development theory and Integrated Coastal Zone Management (ICZM), this study assessed sustainable development of Jiaozhou Bay (JZB), China over the period from 2015 to 2019 under multiple pressures applying the Driver-Pressure-State-Impact-Response (DPSIR) framework. Subsequently, a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis was employed to propose specific countermeasures and recommendations. In terms of weight within the criterion layer, Response (R) and Pressure (P) were assigned higher weights. The comprehensive assessment value Z in the target layer indicated a slight decrease in 2016 followed by a gradual increase that eventually led to stabilization. The comprehensive assessment values of the indicators varied depending on different conditions, implying that higher values would contribute to sustainable development of the eco-environment. Based on a SWOT analysis, strategies for Qingdao were derived from a combination of research findings and future development policy. These strategies include preventing and controlling land and sea pollution, governing reclamation activities, optimizing industrial structure, and strengthening public opinion guidance. This study highlights the application of quantitative and qualitative analysis methods in ICZM, providing specific recommendations based on policy analysis for achieving sustainable development in JZB's eco-environment under multiple pressures.

A longevity level-oriented wellness target area identification method: a case study of Yunnan Province, China.

Background: Aging, as a global demographic issue, is characterized by its rapid growth, which drives an increase in people's healthcare awareness. The emergence of wellness bases caters to this market demand. Therefore, the identification of potential areas suitable for wellness activities and the construction of wellness bases, referred to as Wellness Target Areas (WTAs), becomes a crucial first step. Currently, commonly used identification methods are mostly based on traditional statistical approaches, which are often complex, cumbersome, and subject to potential risks of subjective assumptions, affecting the reliability of WTAs identification results. Longevity level serves as a comprehensive indicator reflecting the natural and socio-economic environment of a region, making it the most indicative of the regional wellness environment status. Methods: This study proposes using longevity level as the benchmark for WTAs identification to simplify the identification process and reduce the impact of subjective bias on the results. The study focuses on 129 county-level units in Yunnan Province. Firstly, the Geodetector (GD) is utilized to explore the complex interaction between the longevity level and the geographical environment to determine regional wellness factors. Secondly, using ArcGIS and geographical weighted regression (GWR), the study investigates the role of different wellness factors, ultimately classifying and grading the WTAs. Results: The longevity level in Yunnan Province exhibits a pattern of multi-point clustering, forming three major longevity regions. Factors that significantly influence longevity level include annual average precipitation, sunshine duration, PM2.5 content, per capita disposable income, density of tourist attractions, and distance from residential areas to hospitals. Based on the degree of longevity and the contribution rate of influencing factors, Yunnan Province's WTAs are classified into three levels and two types (natural and comprehensive). Conclusion: Our study aims to establish a connection between longevity level and the selection of wellness bases, exploring regional wellness factors through the relationship between longevity phenomena and geographical environment, identifying potential construction areas for wellness bases (i.e., WTAs), providing new insights for the precise selection of wellness bases, effectively enhancing the scientificity of site selection, promoting population health, and contributing to the global aging process with better health.

Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin.

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Evaluation of the coordinated development level in the coastal eco-environmental complex system: A case study of Jiaozhou Bay, China.

Given the exponential population growth and remarkable socio-economic advancements, coastal areas face increasingly complex challenges in eco-environmental management due to anthropogenic pressures. With the current emphasis on high-quality economic development, there is an urgent need to establish and evaluate a comprehensive indicator system to ensure the sustainable development of the coastal eco-environment and to meet evolving management demands. Research on the coordinated development level of coastal eco-environmental complex system, based on the concept of land-sea coordination, plays a pivotal role in promoting the resolution of eco-environmental issues in coastal areas, achieving sustainable socio-economic development in these regions. In this study, we construct an indicator system for the eco-environmental complex system in Jiaozhou Bay (JZB) coastal zone, China, comprising six sub-systems and thirty indicators. The comprehensive development level and coupling coordination degree model (CCDM) are employed in this study to analyze the indicator system in 1980-2020, aiming to elucidate the processes involved in the improvements in this complex system. The findings indicate: (i) the system's comprehensive development level evaluation and coupling coordination degree (CCD) exhibit a two-stage pattern: a declining trend in 1980-2005, followed by a rising trend in 2005-2020. (ii) despite improvements, the comprehensive development level and the CCD of the system in 2020 still hold potential for further enhancement compared to 1980; and (iii) policymaking and changes in anthropogenic pressures in coastal areas are the primary factors influencing the performance of the system. In the future, policymaking can reduce anthropogenic pressures on the coastal eco-environment, improve the comprehensive development level and CCD of the complex system, and encourage a commitment to sustainable development.

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers.

Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A total of 417 patients with essential hypertension (EH), including 214 males and 203 females aged 31-80 years, were enrolled in this study; of these, 161 (38.6%) were diagnosed with LVH. Based on variables demonstrating significant disparities between the LVH and Non-LVH groups, three multivariate stepwise logistic regression models were constructed for risk assessment: the "Clinical characteristics" model, the "Biomarkers" model (each based on their respective variables), and the "Clinical characteristics + Biomarkers" model, which amalgamated both sets of variables. The results revealed that the "Clinical characteristics + Biomarkers" model surpassed the baseline models in performance (AUC values of the "Clinical characteristics + Biomarkers" model, the "Biomarkers" model, and the "Clinical characteristics" model were .83, .75, and .74, respectively; P < .0001 for both comparisons). The optimized model suggested that being female (OR: 4.26, P <.001), being overweight (OR: 1.88, p = .02) or obese (OR: 2.36, p = .02), duration of hypertension (OR: 1.04, P = .04), grade III hypertension (OR: 2.12, P < .001), and sST2 (log-transformed, OR: 1.14, P < .001) were risk factors, while eGFR acted as a protective factor (OR: .98, P = .01). These findings suggest that the integration of clinical characteristics and biomarkers can enhance the performance of LVH risk assessment.

Characterization of research trends and prospects on hepatic echinococcosis over the past forty years: a bibliometric analysis.

BACKGROUND: The distribution of hepatic echinococcosis (HE) is extensive, significantly impacting public health and economic development. Therefore, analyzing global collaboration networks and tracking developmental trends over the past four decades are crucial. This study aimed to demonstrate collaboration in the field of HE and explore key topics and future directions. MATERIALS AND METHODS: Bibliometric analyses were conducted using CiteSpace, Bibliometrix package of R, and VOSviewer software on HE-related studies from the Web of Science Core Collection published before 1 August 2023. RESULTS: This study identified 2605 records published in 196 journals by 9860 authors from 2607 institutes in 90 countries. Publications significantly notably increased in 2021. Developing countries like Turkey and China made notable contributions, while developed countries like the USA had higher average citation rates. The largest nodes in every cluster of the collaboration network were Hacettepe University, Tehran University, Xinjiang Medical University, Salford University, and the University of Pavia, and the top-producing authors were Wen H, Vuitton DA, Gottstein B, and Craig PS. Keyword co-occurrence analysis suggested that surgical techniques and novel drugs targeting combined immune checkpoints are the main therapeutic approaches in the future. CONCLUSION: Although developing countries had significantly contributed to publications on HE, the citation rate for individual articles from developed countries was significantly higher. Additionally, advancements in surgical techniques and novel drugs targeting combined immune checkpoints may emerge as the next research focus and developmental direction.

Digital health literacy and associated factors among internet users from China: a cross-sectional study.

BACKGROUND: As the internet develops and 5G technology becomes increasingly prominent, the internet has become a major source of health-related information. Increasingly, people use the internet to find health-related information, and digital health literacy is now a set of essential capabilities to improve their health in the digital era. However, little is known about the factors that influencing digital health literacy. This study aimed to assess digital health literacy scores and identify its influencing factors among internet users in China. Additionally, this study explored the participant's actual skills using an additional set of performance-based items from the Digital Health Literacy Instrument (DHLI). METHODS: An online cross-sectional study was conducted in August 2022. Participants aged ≥18 years were recruited to complete the survey. Data were collected using the Chinese revised version of the DHLI, the self-reported internet use questionnaire, and the sociodemographic questionnaire. We conducted multivariate linear regression analyses to explore the relationships among the sociodemographic variables, behavior of internet use, and the digital health literacy scores. RESULTS: In total, 702 participants completed the survey. The mean DHLI score was 2.69 ± 0.61. Multivariate linear regression analyses showed that the age groups 35-49 (ß = - 0.08, P = 0.033), 50-64 (ß = - 0.161, P < 0.001), and ≥ 65 (ß = - 0.138, P < 0.001) were negatively associated with DHL scores. However, education level, including bachelor's or associate degree (ß = 0.255, P = 0.002) and master's degree and above (ß = 0.256, P < 0.001), frequency of health-related Internet usage (ß = 0.192, P < 0.001), the number of digital devices used (ß = 0.129, P = 0.001), and OHISB (ß = 0.103, P = 0.006) showed a positive relationship with DHL scores. CONCLUSIONS: The study findings demonstrate that age, educational levels, number of technological devices used, and greater use of the web for health information were independently associated with DHL scores. Healthcare providers should consider providing training programs tailored to specific sociodemographic factors to improve the ability that find and use accurate information online to meet digital health services, which contributes to enhance their self-management and reduce health disparities.

Integrated Fruit Ripeness Assessment System Based on an Artificial Olfactory Sensor and Deep Learning.

Artificial scent screening systems, inspired by the mammalian olfactory system, hold promise for fruit ripeness detection, but their commercialization is limited by low sensitivity or pattern recognition inaccuracy. This study presents a portable fruit ripeness prediction system based on colorimetric sensing combinatorics and deep convolutional neural networks (DCNN) to accurately identify fruit ripeness. Using the gas chromatography-mass spectrometry (GC-MS) method, the study discerned the distinctive gases emitted by mango, peach, and banana across various ripening stages. The colorimetric sensing combinatorics utilized 25 dyes sensitive to fruit volatile gases, generating a distinct scent fingerprint through cross-reactivity to diverse concentrations and varieties of gases. The unique scent fingerprints can be identified using DCNN. After capturing colorimetric sensor image data, the densely connected convolutional network (DenseNet) was employed, achieving an impressive accuracy rate of 97.39% on the validation set and 82.20% on the test set in assessing fruit ripeness. This fruit ripeness prediction system, coupled with a DCNN, successfully addresses the issues of complex pattern recognition and low identification accuracy. Overall, this innovative tool exhibits high accuracy, non-destructiveness, practical applicability, convenience, and low cost, making it worth considering and developing for fruit ripeness detection.

Reliability and validity of the translated Chinese version of comprehensive assessment of acceptance and commitment therapy processes (CompACT-C) in breast cancer survivors.

Purpose: This study aimed to translate and validate a Chinese version of the Comprehensive assessment of Acceptance and Commitment Therapy processes (CompACT-C), a 23-item questionnaire for measuring an individual's level of psychological flexibility among Chinese breast cancer survivors for utilisation of Acceptance and commitment therapy (ACT)-based interventions in breast cancer patients. Methods: Six translators translated the original English version into Chinese according to Brislin's Translation Model. Psychometric properties tests were conducted on the CompACT-C, including internal consistency, test-retest reliability (two-week interval), face validity, content validity, convergent validity with experiential avoidance, and construct validity (confirmatory factor analysis). Results: 308 Chinese breast cancer survivors with mastectomies were conveniently recruited. The translated scale showed satisfactory test-retest reliability (two-week interval, r = 0.53-0.72, p < 0.001), face validity, and content validity (CVI-Scale/CVS-Item = 1.00). According to the confirmatory factor analysis results, the final Chinese version remained the 23 items and three dimensions, with the modification of item six from the dimension of openness to experience to behavioural awareness for better model fitness [structural equation model analysis, χ2 = 559.486, df = 226, NC (χ2/df) = 2.476, RMSEA = 0.069, CFI = 0.834, TLI = 0.815, SRMR = 0.079] and satisfactory internal consistency (Cronbach's α = 0.71), convergent validity with AAQ-2 (r = -0.57, p < 0.001) in these breast cancer patients. Conclusions: The Chinese version of the CompACT showed good reliability and validity among Chinese breast cancer patients. Future research is suggested to confirm its psychometric properties with diverse breast and other cancer groups.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.

Assessment of isthmus filling using two obturation techniques performed by students with different levels of clinical experience.

Background/purpose: Root canal filling is a necessary skill for dental students and an important aspect of endodontic education. This study aimed to evaluate the effect of students' clinical experiences on isthmus filling using different techniques and sealers. Materials and methods: One hundred eight three-dimensional-printed resin replicas of isthmus were divided into six groups and either continuous wave of condensation (CWC) or single-cone obturation (SC) was performed. One of three sealers (AH Plus Jet®, GuttaFlow2, iRoot SP) was used together with a size-fitted gutta-percha master cone. All the obturations were completed by students with three different levels of clinical experience including senior postgraduate students (SPS), junior postgraduate students (JPS), and undergraduate students (US). The percentages of filled areas (PFA) at 2, 4, 6, and 8 mm from the apex were analyzed using a light microscope. Data were analyzed using the Mann-Whitney U test or Kruskal-Wallis 1-way ANOVA with Dunn's tests (α = 0.05). Results: The CWC group exhibited a higher PFA than the SC group (P < 0.05). The PFA was higher in the SPS group than in the JPS group or the US group with CWC (P < 0.05). The three clinical experience groups showed similar PFAs with SC (P > 0.05); however, when using SC with iRoot SP, the PFA was higher than with either of the other two sealers (P < 0.05). Conclusion: CWC was found to be technique-sensitive and required clinical training. With SC, clinical experience did not improve the quality of isthmus filling without additional training. CWC was superior to SC for type IV isthmuses. When using SC, better filling quality was obtained with a bioceramic sealer.

Achieving Accuracy and Economy for Calculating Vertical Detachment Energies of Molecular Anions: A Model Chemistry Composite Methods.

The vertical detachment energy (VDE) is a vital factor for predicting the stability of anions that have important applications in the atom, molecule and cluster science. Due to the synthetic or characterization difficulty of anions, accurate and efficient predictions of VDE independent of laboratory data have always been an appealing task to remedy the experimental deficiencies. Unfortunately, the generally adopted CCSD(T) and electron propagator theory (EPT) methods have respectively been proven to be reliable but very cost-expensive, and cost-effective but sometimes problematic when Koopman's theorem is invalid. Here, we for the first time introduced and benchmarked a series of model chemistry composite methods (e. g., CBS-QB3, G4 and W1BD) on calculating VDE for 57 molecular anions. Notably, CBS-QB3 exceeds the accuracy of CCSD(T) while approaching the economy of EPT. Therefore, we highly recommend the composite method CBS-QB3 to compute VDEs for molecular anions in the attractive "killing two birds with one stone" manner.

Characteristics and End-of-Life Care Pathways of Decedents From a National Cohort of Assisted Living Residents.

BACKGROUND: Assisted living (AL) is an increasingly common, place of care for dying persons. However, it remains unclear to what extent residents are able to age in place or if AL represents an additional transition before death. OBJECTIVES: Examine the sociodemographic characteristics, comorbidities, health care utilization, and end-of-life care pathways of AL residents before death. RESEARCH DESIGN: A national cohort study of fee-for-service Medicare beneficiaries residing in large AL communities (25+ beds) during the month of January 2017 with 3 years of follow-up, using administrative claims data. SUBJECTS: 268,812 AL residents. MEASURES: Sociodemographic characteristics, comorbidities, and health care utilization at the end of life. RESULTS: Between 2017 and 2019, 35.1% of the study cohort died. Decedents were more likely than the overall AL population to be 85 years old or older (76.5% vs. 59.5%), and diagnosed with Alzheimer's disease and related dementia (70.3% vs. 51.6%). Most decedents (96.2%) had some presence in AL during the last year of life, but over 1 in 5 left AL before the last month of life. Among those in AL on day 30 before death, nearly half (46.4%) died in place without any health care transition, while 13.2% had 3 or more transfers before dying. CONCLUSIONS: AL is an important place of care for dying persons, especially for those with dementia. These findings indicate a need to assess existing policies and processes guiding the care of the frail and vulnerable population of dying AL residents.

A noninvasive multianalytical approach establishment for risk assessment and gastric cancer screening.

Effective screening and early detection are critical to improve the prognosis of gastric cancer (GC). Our study aims to explore noninvasive multianalytical biomarkers and construct integrative models for preliminary risk assessment and GC detection. Whole genomewide methylation marker discovery was conducted with CpG tandems target amplification (CTTA) in cfDNA from large asymptomatic screening participants in a high-risk area of GC. The methylation and mutation candidates were validated simultaneously using one plasma from patients at various gastric lesion stages by multiplex profiling with Mutation Capsule Plus (MCP). Helicobacter pylori specific antibodies were detected with a recomLine assay. Integrated models were constructed and validated by the combination of multianalytical biomarkers. A total of 146 and 120 novel methylation markers were found in CpG islands and promoter regions across the genome with CTTA. The methylation markers together with the candidate mutations were validated with MCP and used to establish a 133-methylation-marker panel for risk assessment of suspicious precancerous lesions and GC cases and a 49-methylation-marker panel as well as a 144-amplicon-mutation panel for GC detection. An integrated model comprising both methylation and specific antibody panels performed better for risk assessment than a traditional model (AUC, 0.83 and 0.63, P < .001). A second model for GC detection integrating methylation and mutation panels also outperformed the traditional model (AUC, 0.82 and 0.68, P = .005). Our study established methylation, mutation and H. pylori-specific antibody panels and constructed two integrated models for risk assessment and GC screening. Our findings provide new insights for a more precise GC screening strategy in the future.

High-throughput screening of human mercury exposure based on a low-cost naked eye-recognized biosensing platform.

Whole-cell biosensors could be helpful for in situ disease diagnosis. However, their use in analyzing biological samples has been hindered by unstable responses, low signal enhancement, and growth inhibition in complex media. Here, we offered a solution by building a visual whole-cell biosensor for urinary mercury determination. With deoxyviolacein as the preferred signal for the mercury biosensor for the first time, it enabled the quantitative detection of urinary mercury with a favorable linear range from 1.57 to 100 nM. The biosensor can accurately diagnose urine mercury levels exceeding the biological exposure index with 95.8% accuracy. Thus, our study provided a biosensing platform with great potential to serve as a stable, user-friendly, and high-throughput alternative for the daily monitoring or estimating of urinary mercury.

Protocol guide for food foraging behavior test: Assessment of decision making in rodents.

Food foraging behavior requires higher cognitive function like investing efforts in decision making. Hoarding food for the future consumption in adverse climatic conditions or to avoid predatory threats needs precise perception and potential of decision making to overcome challenges in the time of need. The brain areas and neural circuitry responsible for such cognitive skills are poorly understood. Previously available animal models are trained prior to test, which makes it difficult to understand the true nature of animals, and hoard the food from external source into the cage. The new food foraging behavior test, recently developed and evidenced by Li et al., relies on untrained rats and test the competitive ability and hoarding from source within the test box. It can be used to study decision making potentials and underlying neural bases in laboratory settings. Multiple aspects like food quality/flavor preference, competitive nature can be assessed within the test box and the paradigm is conveniently customizable according the hypothesis. However, a detailed protocol guide, to be followed in the laboratory setting, for food foraging behavior test is not available. Therefore, it is urged to produce an elaborated guide for scientists to conduct food foraging behavior test in convenient and precise manner.

Assessment of soil property in the Guyuan region from Ningxia Province of China and prediction of pepper blight.

Soil quality is an important determinant of soil-use efficiency in the Loess Plateau. However, there is no in-depth study on the soil quality of the Loess Plateau. The present study compared the quality of the 0-20 cm soil layer (T0-20) and the 20-40 cm soil layer (T20-40) from the Guyuan region located in the Loess Plateau. The analysis revealed that T0-20 had a higher content of total N, total P, available P, and organic matter, and the activities of microbial enzymes, especially ß-grape-glycosidase (ß-GC) and sucrase (SC), than T20-40, indicating that soil quality in T0-20 was better than T20-40. Amplicon sequencing found that Pseudombrophila from Ascomycota was the most abundant microbial species and significantly differed between T0-20 (34.2%) and T20-40 (48.7%). This species and another 19 microbial species, such as Ceratobasidiaceae and Mortierellaceae, determined the diversity of soil microorganism. Further analysis of the phenotype and other parameters of pepper seedlings subjected to P. capsici infection isolated from test soil revealed that decreased organic matter content in deep soil layer is related to happening of pepper blight, and 3 h after infection was the critical time point for infection. The peroxidase (POD) activity increased after P. capsici infection and was positively correlated with infection time, suggesting this enzyme may be an indicator of pepper blight occurrence. These findings provide a theoretical foundation for planning pepper blight management and crop cultivation strategies in the Guyuan region.

Blinding assessment in clinical trials of traditional Chinese medicine: Exploratory principles and protocol.

As one of the key components of clinical trials, blinding, if successfully implemented, can help to mitigate the risks of implementation bias and measurement bias, consequently improving the validity and reliability of the trial results. However, successful blinding in clinical trials of traditional Chinese medicine (TCM) is hard to achieve, and the evaluation of blinding success through blinding assessment lacks established guidelines. Taking into account the challenges associated with blinding in the TCM field, here we present a framework for assessing blinding. Further, this study proposes a blinding assessment protocol for TCM clinical trials, building upon the framework and the existing methods. An assessment report checklist and an approach for evaluating the assessment results are presented based on the proposed protocol. It is anticipated that these improvements to blinding assessment will generate greater awareness among researchers, facilitate the standardization of blinding, and augment the blinding effectiveness. The use of this blinding assessment may further advance the quality and precision of TCM clinical trials and improve the accuracy of the trial results. The blinding assessment protocol will undergo continued optimization and refinement, drawing upon expert consensus and experience derived from clinical trials. Please cite this article as: Wang XC, Liu XY, Shi KL, Meng QG, Yu YF, Wang SY, Wang J, Qu C, Lei C, Yu XP. Blinding assessment in clinical trials of traditional Chinese medicine: Exploratory principles and protocol. J Integr Med. 2023; 21(6): 528-536.

[Spatial and Temporal Distribution Characteristics of Heavy Metals in Main Rivers Sediments and Ecological Risk Assessment in Kaifeng City].

Heavy metal pollution in urban river sediments is an important threat to river ecosystem health. To explore the temporal and spatial distribution characteristics of heavy metals in river sediments of Kaifeng City, the surface sediments of rivers were sampled in 2015 and 2021, respectively, and the contents of Cd, Cr, Cu, Ni, Pb, and Zn in sediments at different periods were compared. The heavy metal pollution in the two periods was evaluated using the indices of geo-accumulation, bio-toxicity risk assessment, and potential ecological risk. The results showed that the content of heavy metals in river sediments of Kaifeng City in 2021 were decreased significantly compared with that in 2015. Cd, Cr, Cu, Ni, Pb, and Zn decreased by 94.42%, 18.4%, 85.7%, 45.19%, 75.61%, and 92.28%, respectively. The heavy metal content in the Huafei River and Huiji River was higher than that in other rivers in both periods. Correlation and principal component analyses showed that the heavy metal pollution sources of river sediments in Kaifeng City were highly similar, and human activities such as industrial layout, road traffic, and land use were the main pollution sources. However, the results showed that the main pollutants were different between the two sampling times. In 2015, Cd, Cr, Pb, and Zn were the main pollutants, and in 2021, Cd, Cu, Pb, and Zn were the main pollutants. The results of the geo-accumulation, bio-toxicity risk assessment, and potential ecological risk indices showed that the temporal and spatial differences in heavy metal pollution in river sediments in Kaifeng City were large. However, the heavy metal pollution of the Huiji River and Huafei River was still serious, with contents in the medium and high pollution levels, especially to Cd. The heavy metal treatment of rivers in Kaifeng City has a long way to go, and it is particularly necessary to strengthen the engineering treatment for key river sections and effectively monitor key pollution elements.