Influence of Climate and Socio-Economic Factors on the Spatio-Temporal Variability of Soil Organic Matter: A Case Study of Central Heilongjiang Province, China

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression （GWR） model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigation has expanded. The regions with positive regression coefficient of fertilizer use have shrinked. The positive regression coefficient of mulch film consumption has significantly increased. The regression coefficient of pesticide consumption was mainly positive in the west of the study area, while it was negative to the east. Generally, GWR model is capable to investigate the influence of both climatic and socio-economic factors, avoided the insufficiency of other research based on the single perspective of climatic or socio-economic factors. Therefore, we can conclude that GWR model could provide methodological support for global change research and serve as basic reference for cultivated land quality improvement and agricultural decision making.

Spatial Heterogeneity Association of HIV Incidence with Socio-economic Factors in Zimbabwe

This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males,unemployed females,percentage of poor households i.e.,poverty prevalence,night lights index,literacy rate,household food security,and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios(LLR),global Moran’s I,local indicator of spatial association-LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression(GWPR)and semi-parametric GWPR(s-GWPR)were used to determine the spatial association between HIV incidence and socio-economic factors.HIV incidence(number of cases per 1000)ranged from 0.6(Buhera district)to 13.30(Mangwe district).Spatial clustering of HIV incidence was observed(Global Moran’s I=-0.150;Z score 3.038;p-value 0.002).Significant clusters of HIV were observed at district level.HIV incidence and its association with socio-economic factors varied across the districts except percentage of females unemployed.Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.

Analysis of the Incidence of Hepatitis B and Hepatitis C and Association with Socio-Economic Factors in Various Regions in China

The incidence of liver cancer in China accounts for more than half of the world, and the majority of them is caused by hepatitis B and hepatitis C. China is known as a great contributor to hepatitis. The Chinese government has implemented a series of preventive measures to solve this problem, especially the policy of free hepatitis B vaccination for newborn babies and effectively reduced the incidence of hepatitis. The incidence of infectious diseases is often related to socio-economic factors. Therefore, we used data on the incidence of hepatitis B and C and socioeconomic factors to analyze and find out the relationship among them in various regions. There were high incidence areas and low incidence areas in China, and the high incidence area of hepatitis B was also the high incidence area of hepatitis C. Especially in Xinjiang, the highest incidence of hepatitis B and hepatitis C was observed at the same time. The incidence of hepatitis B and hepatitis C was more affected by regional economic factors. The economic factors in low incidence areas of hepatitis were better than those in high incidence areas. There was a negative correlation between economic factors and the incidence of hepatitis. In conclusion, in economically developed areas, the government has invested more money and resources in public health and people’s health awareness in comparison to underdeveloped areas. In the future, various preventive strategies should be carried out according to the background of different regions.

The Association of Stress with the Socio-Economic Factors of Individuals That Attended the Taxpayers’ Appreciation Week 2018, Kampala Uganda

Introduction: Work-related stress has increased in nine European Union (EU) countries in the last ten years. Eighty (80%) percent of the general population in European countries believes that work-related stress will rise in the coming five years. Objective: The purpose of this study was to determine the association between the various levels of stress with the socio-economic elements among individuals that participated in Uganda’s tax payer’s appreciation week in the year 2018 held in Kampala. Methodology: This study applied a cross-sectional study design that unified quantitative research methods and a convenience sampling method were used in this study to gather the information from the 390 respondents. Data were examined using SPSS version 20;univariate and bivariate analysis were done to measure the association between stress and the participant’s socio-economic factors. Results: Respondents who were employed recorded the majority with a percentage of 60%, while the unemployed recorded the minority with a percentage of 40%. Respondents who were employed were more likely to experience low stress as compared to those who were unemployed, under the category of moderate stress, respondents who were employed were more likely to be moderately stressed as compared to their unemployed counterparts, as for the category of high stress, unemployed respondents were more likely to be highly stressed than those that were employed and this was not statistically significant (X2 =2.374;p-value = 0.305). Conclusion: The results from this research indicated that there was no significant association between the socioeconomic factors of the respondents with stress levels. Recommendations: More community sensitization and awareness should be carried out to educate individuals about stress and its impacts on health.

Modelling Impacts of Socio-Economic Factors on Temporal Diffusion of PV-Based Communal Grids

Impacts of socio-economic factors on temporal diffusions of solar electricity microgeneration systems in a rural developing community are modelled and simulated using an agent-based model (ABM). ABMs seek to capture the overall macro-effects of different micro-decisions in a virtual world;they model individual entities within a complex system and the rules that govern them to capture the overall effects of their interactions. Results showed that falling PV costs coupled with generally increasing grid electricity costs would lead to increased uptake of PV systems in such communities. On the other hand, high lending rates in most developing nations would stifle use of credit facilities in purchases of PV systems and thus diminishing their uptakes. Results also showed that introduction of favourable government policies in forms of subsidies would strongly stimulate PV installations in such communities. Social acceptance is important for diffusion of any new technology into a given market and more so with solar systems;results show that neighbourhood influence plays major roles in PV diffusions with many households installing PV systems if their neighbours within a given sensing radius do the same. Results also showed that requiring a certain percentage of neighbours to have installed PV before a household considered doing the same could have negative effects on PV installations as decisions to install PV are influenced by many independent and dependent factors and not by neighbourhood threshold alone.

Dietary and socio-economic factors in relation to Helicobacter pylori re-infection

AIM:To examine if dietary and socio-economic factors contribute to Helicobacter pylori(H pylori)re-infection. METHODS:The population of patients consisted of subjects in whom H pylori infection had been successfully treated in the past.Patients were divided into two groups:Ⅰ-examined group(111 persons with H pylori re-infection)andⅡ-control group(175 persons who had not been re-infected).The respondents were interviewed retrospectively on their dietary habits and socio-economic factors. RESULTS:A statistically significant lower frequency of fermented dairy products(P<0.0001),vegetables (P=0.02),and fruit(P=0.008)consumption was noted among patients with H pylori re-infection as compared to those who had not been re-infected. CONCLUSION:High dietary intake of probiotic bacteria,mainly Lactobacillus,and antioxidants,mainly vitamin C(contained in fruit and vegetables),might decrease the risk of H pylori re-infection.

Relationship Between Built Environment, Socio-economic Factors and Carbon Emissions from Shopping Trip in Shenyang City, China

Promoting active travel behavior and decreasing transport-related carbon dioxide(CO_2) emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO_2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO_2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated CO_2 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was significant spatial autocorrelation with CO_2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO_2 emissions per trip were negatively correlated with several built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socio-economic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.

Impacts of socio-economic factors on sediment yield in the Upper Yangtze River

In recent years, the role of human activities in changing sediment yield has become more apparent for the construction of hydraulic engineering and water conservation projections in the Upper Yangtze River, but it has not been evaluated at the macro scale. Taking Sichuan Province and Chongqing City as an example, this paper studies the relationship between socio-economic factors and sediment yield in the Upper Yangtze River based on section data in 1989 and 2007. The results show that sediment yield is significantly correlated with population density and cultivated area, in which the former appears to be more closely related to sediment yield. Moreover, in the relation of sediment yield vs. population density, a critical value of population density exists, below which the sediment yield increases with the increase of population density and over which the sediment yield increases with the decrease of population density. The phenomenon essentially reflects the influence of natural factors, such as topography, precipitation and soil property, and some human activities on sediment yield. The region with a higher population density than critical value is located in the east of the study area and is characterized by plains, hills and low mountains, whereas the opposite is located in the west and characterized by middle and high mountains. In the eastern region, more people live on the lands with a low slope where regional soil erosion is slight; therefore, sediment yield is negatively related with population density. In contrast, in the western region, the population tends to aggregate in the areas with abundant soil and water resources which usually lead to a higher intensity of natural erosion, and in turn, high-intensity agricultural practices in these areas may further strengthen local soil erosion. It is also found that population tends to move from the areas with bad environment and high sediment yield to the areas with more comfortable environment and less sediment yield. The natural factors have greater influence on sediment yield of western region than that of eastern region. Generally, the natural factors play a dominant role on sediment yield in the Upper Yangtze River.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Biological factors driving colorectal cancer metastasis

Approximately 20%of colorectal cancer(CRC)patients present with metastasis at diagnosis.Among Stage I-III CRC patients who undergo surgical resection,18%typically suffer from distal metastasis within the first three years following initial treatment.The median survival duration after the diagnosis of metastatic CRC(mCRC)is only 9 mo.mCRC is traditionally considered to be an advanced stage malignancy or is thought to be caused by incomplete resection of tumor tissue,allowing cancer cells to spread from primary to distant organs;however,increa-sing evidence suggests that the mCRC process can begin early in tumor development.CRC patients present with high heterogeneity and diverse cancer phenotypes that are classified on the basis of molecular and morphological alterations.Different genomic and nongenomic events can induce subclone diversity,which leads to cancer and metastasis.Throughout the course of mCRC,metastatic cascades are associated with invasive cancer cell migration through the circulatory system,extravasation,distal seeding,dormancy,and reactivation,with each step requiring specific molecular functions.However,cancer cells presenting neoantigens can be recognized and eliminated by the immune system.In this review,we explain the biological factors that drive CRC metastasis,namely,genomic instability,epigenetic instability,the metastatic cascade,the cancer-immunity cycle,and external lifestyle factors.Despite remarkable progress in CRC research,the role of molecular classification in therapeutic intervention remains unclear.This review shows the driving factors of mCRC which may help in identifying potential candidate biomarkers that can improve the diagnosis and early detection of mCRC cases.

Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China

Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture(hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector(OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that:(1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km^(2). In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak.(2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced.(3) The results of OPGD detection in 2015 show that the influence of each factor is slope(0.2371) > traffic accessibility(0.2098) > population(0.1403) > regional GDP(0.1325) > elevation(0.0987) > poverty alleviation(0). The results of OPGD detection in 2020 show that the influence of each factor is slope(0.2339) > traffic accessibility(0.2198) > population(0.1432) > regional GDP(0.1219) > poverty alleviation(0.0992) > elevation(0.093). Natural geographical factors(slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors(traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decisionmaking basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.

Analysis of the influencing factors and clinical related characteristics of pulmonary tuberculosis in patients with type 2 diabetes mellitus

BACKGROUND In China,the prevalence of type 2 diabetes mellitus(T2DM)among diabetic patients is estimated to be between 90%-95%.Additionally,China is among the 22 countries burdened by a high number of tuberculosis cases,with approximately 4.5 million individuals affected by active tuberculosis.Notably,T2DM poses a significant risk factor for the development of tuberculosis,as evidenced by the increased incidence of T2DM coexisting with pulmonary tuberculosis(T2DMPTB),which has risen from 19.3%to 24.1%.It is evident that these two diseases are intricately interconnected and mutually reinforcing in nature.AIM To elucidate the clinical features of individuals diagnosed with both T2DM and tuberculosis(T2DM-PTB),as well as to investigate the potential risk factors associated with active tuberculosis in patients with T2DM.METHODS T2DM-PTB patients who visited our hospital between January 2020 and January 2023 were selected as the observation group,Simple DM patients presenting to our hospital in the same period were the control group,Controls and case groups were matched 1:2 according to the principle of the same sex,age difference(±3)years and disease duration difference(±5)years,patients were investigated for general demographic characteristics,diabetes-related characteristics,body immune status,lifestyle and behavioral habits,univariate and multivariate analysis of the data using conditional logistic regression,calculate the odds ratio(OR)values and 95%CI of OR values.RESULTS A total of 315 study subjects were included in this study,including 105 subjects in the observation group and 210 subjects in the control group.Comparison of the results of both anthropometric and biochemical measures showed that the constitution index,systolic blood pressure,diastolic blood pressure and lymphocyte count were significantly lower in the case group,while fasting blood glucose and high-density lipoprotein cholesterol levels were significantly higher than those in the control group.The results of univariate analysis showed that poor glucose control,hypoproteinemia,lymphopenia,TB contact history,high infection,smoking and alcohol consumption were positively associated with PTB in T2DM patients;married,history of hypertension,treatment of oral hypoglycemic drugs plus insulin,overweight,obesity and regular exercise were negatively associated with PTB in T2DM patients.Results of multivariate stepwise regression analysis found lymphopenia(OR=17.75,95%CI:3.40-92.74),smoking(OR=12.25,95%CI:2.53-59.37),history of TB contact(OR=6.56,95%CI:1.23-35.03)and poor glycemic control(OR=3.37,95%CI:1.11-10.25)was associated with an increased risk of developing PTB in patients with T2DM,While being overweight(OR=0.23,95%CI:0.08-0.72)and obesity(OR=0.11,95%CI:0.02-0.72)was associated with a reduced risk of developing PTB in patients with T2DM.CONCLUSION T2DM-PTB patients are prone to worse glycemic control,higher infection frequency,and a higher proportion of people smoking,drinking alcohol,and lack of exercise.Lymphopenia,smoking,history of TB exposure,poor glycemic control were independent risk factors for T2DM-PTB,and overweight and obesity were associated with reduced risk of concurrent PTB in patients with T2DM.

Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

Predictive factors and model validation of post-colon polyp surgery Helicobacter pylori infection

BACKGROUND Recently,research has linked Helicobacter pylori(H.pylori)stomach infection to colonic inflammation,mediated by toxin production,potentially impacting colorectal cancer occurrence.AIM To investigate the risk factors for post-colon polyp surgery,H.pylori infection,and its correlation with pathologic type.METHODS Eighty patients who underwent colon polypectomy in our hospital between January 2019 and January 2023 were retrospectively chosen.They were then randomly split into modeling(n=56)and model validation(n=24)sets using R.The modeling cohort was divided into an H.pylori-infected group(n=37)and an H.pylori-uninfected group(n=19).Binary logistic regression analysis was used to analyze the factors influencing the occurrence of H.pylori infection after colon polyp surgery.A roadmap prediction model was established and validated.Finally,the correlation between the different pathological types of colon polyps and the occurrence of H.pylori infection was analyzed after colon polyp surgery.RESULTS Univariate results showed that age,body mass index(BMI),literacy,alcohol consumption,polyp pathology type,high-risk adenomas,and heavy diet were all influential factors in the development of H.pylori infection after intestinal polypectomy.Binary multifactorial logistic regression analysis showed that age,BMI,and type of polyp pathology were independent predictors of the occurrence of H.pylori infection after intestinal polypectomy.The area under the receiver operating characteristic curve was 0.969[95%confidence interval(95%CI):0.928–1.000]and 0.898(95%CI:0.773–1.000)in the modeling and validation sets,respectively.The slope of the calibration curve of the graph was close to 1,and the goodness-of-fit test was P>0.05 in the two sets.The decision analysis curve showed a high rate of return in both sets.The results of the correlation analysis between different pathological types and the occurrence of H.pylori infection after colon polyp surgery showed that hyperplastic polyps,inflammatory polyps,and the occurrence of H.pylori infection were not significantly correlated.In contrast,adenomatous polyps showed a significant positive correlation with the occurrence of H.pylori infection.CONCLUSION Age,BMI,and polyps of the adenomatous type were independent predictors of H.pylori infection after intestinal polypectomy.Moreover,the further constructed column-line graph prediction model of H.pylori infection after intestinal polypectomy showed good predictive ability.

Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

Predictive factors for percutaneous nephrolithotomy bleeding risks

Objective:This study aimed to identify predictive factors for percutaneous nephrolithotomy(PCNL)bleeding risks.With better risk stratification,bleeding in high-risk patient can be anticipated and facilitates early identification.Methods:A prospective observational study of PCNL performed at our institution was done.All adults with radio-opaque renal stones planned for PCNL were included except those with coagulopathy,planned for additional procedures.Factors including gender,co-morbidities,body mass index,stone burden,puncture site,tract dilatation size,operative position,surgeon's seniority,and operative duration were studied using stepwise multivariate regression analysis to identify the predictive factors associated with higher estimated hemoglobin(Hb)deficiency.Results:Overall,4.86%patients(n=7)received packed cells transfusion.The mean estimated Hb deficiency was 1.3(range 0-6.5)g/dL and the median was 1.0 g/dL.Stepwise multivariate regression analysis revealed that absence of hypertension(p=0.024),puncture site(p=0.027),and operative duration(p=0.023)were significantly associated with higher estimated Hb deficiency.However,the effect sizes are rather small with partial eta-squared of 0.037,0.066,and 0.038,respectively.Observed power obtained was 0.621,0.722,and 0.625,respectively.Other factors studied did not correlate with Hb difference.Conclusion:Hypertension,puncture site,and operative duration have significant impact on estimated Hb deficiency during PCNL.However,the effect size is rather small despite adequate study power obtained.Nonetheless,operative position(supine or prone),puncture number,or tract dilatation size did not correlate with Hb difference.The mainstay of reducing bleeding in PCNL is still meticulous operative technique.Our study findings also suggest that PCNL can be safely done by urology trainees under supervision in suitably selected patient,without increasing risk of bleeding.

Disinfection Byproducts and Their Precursors in Drinking Water Sources:Origins,Influencing Factors,and Environmental Insights

Tracing the contamination origins in water sources and identifying the impacts of natural and human processes are essential for ecological safety and public health.However,current analysis approaches are not ideal,as they tend to be laborious,time-consuming,or technically difficult.Disinfection byproducts(DBPs)are a family of well-known secondary pollutants formed by the reactions of chemical disinfectants with DBP precursors during water disinfection treatment.Since DBP precursors have various origins(e.g.,natural,domestic,industrial,and agricultural sources),and since the formation of DBPs from different precursors in the presence of specific disinfectants is distinctive,we argue that DBPs and DBP precursors can serve as alternative indicators to assess the contamination in water sources and identify pollution origins.After providing a retrospective of the origins of DBPs and DBP precursors,as well as the specific formation patterns of DBPs from different precursors,this article presents an overview of the impacts of various natural and anthropogenic factors on DBPs and DBP precursors in drinking water sources.In practice,the DBPs(i.e.,their concentration and speciation)originally present in source water and the DBP precursors determined using DBP formation potential tests—in which water samples are dosed with a stoichiometric excess of specific disinfectants in order to maximize DBP formation under certain reaction conditions—can be considered as alternative metrics.When jointly used with other water quality parameters(e.g.,dissolved organic carbon,dissolved organic nitrogen,fluorescence,and molecular weight distribution)and specific contaminants of emerging concern(e.g.,certain pharmaceuticals and personal care products),DBPs and DBP precursors in drinking water sources can provide a more comprehensive picture of water pollution for better managing water resources and ensuring human health.

Risk factors,prognostic factors,and nomograms for distant metastasis in patients with diagnosed duodenal cancer:A population-based study

BACKGROUND Duodenal cancer is one of the most common subtypes of small intestinal cancer,and distant metastasis(DM)in this type of cancer still leads to poor prognosis.Although nomograms have recently been used in tumor areas,no studies have focused on the diagnostic and prognostic evaluation of DM in patients with primary duodenal cancer.AIM To develop and evaluate nomograms for predicting the risk of DM and person-alized prognosis in patients with duodenal cancer.METHODS Data on duodenal cancer patients diagnosed between 2010 and 2019 were extracted from the Surveillance,Epidemiology,and End Results database.Univariate and multivariate logistic regression analyses were used to identify independent risk factors for DM in patients with duodenal cancer,and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors in duodenal cancer patients with DM.Two novel nomograms were established,and the results were evaluated by receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS A total of 2603 patients with duodenal cancer were included,of whom 457 cases(17.56%)had DM at the time of diagnosis.Logistic analysis revealed independent risk factors for DM in duodenal cancer patients,including gender,grade,tumor size,T stage,and N stage(P<0.05).Univariate and multivariate COX analyses further identified independent prognostic factors for duodenal cancer patients with DM,including age,histological type,T stage,tumor grade,tumor size,bone metastasis,chemotherapy,and surgery(P<0.05).The accuracy of the nomograms was validated in the training set,validation set,and expanded testing set using ROC curves,calibration curves,and DCA curves.The results of Kaplan-Meier survival curves(P<0.001)indicated that both nomograms accurately predicted the occurrence and prognosis of DM in patients with duodenal cancer.CONCLUSION The two nomograms are expected as effective tools for predicting DM risk in duodenal cancer patients and offering personalized prognosis predictions for those with DM,potentially enhancing clinical decision-making.

Survey on Knowledge of Cardiovascular Disease Risk Factors in the Dakar Region

Introduction: Non-communicable diseases constitute a major public health problem, due to their morbi-mortality. The aim was to study knowledge of cardiovascular risk factors among residents of Dakar. Patients and Methods: This was a descriptive cross-sectional study. Our investigations were recruited over a six-month period (October 17, 2021 to March 21, 2022). Results: Two hundred and twenty-six (226) patients were enrolled. The mean age was 45.9 years. The under-40 age group was the most represented with 37.2%. There were 129 men (57.1%), giving a male/female sex ratio of 1.33. The highest level was represented by 159 people (70.4%). Those who responded (heart disease) were in the majority (38.1%). Hypertension was the most common CVD for 101 people (44.7%). One hundred and ninety (190) people (84%) knew the risk factors for CVD. Good knowledge of risk factors concerned 103 people (54.2%). Obesity was the best-known risk factor in 156 cases (69%). The media was the most important source of information for 121 people (53.5%). Hypertensives were the most represented with 8.4%. One hundred and thirty (130) people (57.5%) had previously paid attention to these FDRCVs. Awareness campaigns were the most effective means of communication for 170 cases (75.2%). Sixteen (16) people (35.6%) were taking antihypertensive medication. Walking was the most popular physical activity for 102 people (45%). People with a balanced diet were in the majority, with 174 respondents (77.0%). Conclusion: NCDs are a major cause of morbidity and mortality. It is essential to develop and implement a prevention and management program.