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.

An intelligent quantification system for fetal heart rhythm assessment: A multicenter prospective study.

BACKGROUND: The motion relationship and time intervals of the pulsed-wave Doppler (PWD) spectrum are essential for diagnosing fetal arrhythmia. However, few technologies currently are available to automatically calculate fetal cardiac time intervals (CTIs). OBJECTIVE: The purpose of this study was to develop a fetal heart rhythm intelligent quantification system (HR-IQS) for the automatic extraction of CTIs and establish the normal reference range for fetal CTIs. METHODS: A total of 6498 PWD spectrums of 2630 fetuses over the junction between the left ventricular inflow and outflow tracts were recorded across 14 centers. E, A, and V waves were manually labeled by 3 experienced fetal cardiologists, with 17 CTIs extracted. Five-fold cross-validation was performed for training and testing of the deep learning model. Agreement between the manual and HR-IQS-based values was evaluated using the intraclass correlation coefficient and Spearman's rank correlation coefficient. The Jarque-Bera test was applied to evaluate the normality of CTIs' distributions, and the normal reference range of 17 CTIs was established with quantile regression. Arrhythmia subset was compared with the non-arrhythmia subset using the Mann-Whitney U test. RESULTS: Significant positive correlation (P <.001) and moderate-to-excellent consistency (P <.001) between the manual and HR-IQS automated measurements of CTIs was found. The distribution of CTIs was non-normal (P <.001). The normal range (2.5th to 97.5th percentiles) was successfully established for the 17 CTIs. CONCLUSIONS: Using our HR-IQS is feasible for the automated calculation of CTIs in practice and thus could provide a promising tool for the assessment of fetal rhythm and function.

A retrospective analysis of the incidence of postoperative delirium and the importance of database selection for its definition.

BACKGROUND: Postoperative delirium (POD) is a common complication after major surgery, resulting in various adverse reactions. However, incidence and risk factors associated with POD after shoulder arthroplasty (SA) have not been well studied using a large-scale national database. METHODS: A retrospective database analysis was performed based on the Nationwide Inpatient Sample (NIS) from 2005 to 2014, the largest fully paid hospital care database in the United States. Patients undergoing SA were included. The patient's demographics, comorbidities, length of stay (LOS), total costs, type of insurance, type of hospital, in-hospital mortality, and medical and surgical perioperative complications were assessed. RESULTS: A total of 115,147 SA patients were obtained from the NIS database. The general incidence of delirium after SA was 0.89%, peaking in 2010. Patients with delirium after SA had more comorbidities, prolonged LOS, increased hospitalization costs, and higher in-hospital mortality (P < 0.0001). These patients were associated with medical complications during hospitalization, including acute renal failure, acute myocardial infarction, pneumonia, pulmonary embolism, stroke, urinary tract infection, sepsis, continuous invasive mechanical ventilation, blood transfusion, and overall perioperative complications. Risk factors associated with POD include advanced age, neurological disease, depression, psychosis, fluid and electrolyte disturbances, and renal failure. Protective factors include elective hospital admissions and private insurance. CONCLUSION: The incidence of delirium after SA is relatively low. Delirium after SA was associated with increased comorbidities, LOS, overall costs, Medicare coverage, mortality, and perioperative complications. Studying risk factors for POD can help ensure appropriate management and mitigate its consequences. Meanwhile, we found some limitations of this type of research and the need to establish a country-based POD database, including further clearly defining the diagnostic criteria for POD, investigating risk factors and continuing to collect data after discharge (30 days or more), so as to further improve patient preoperative optimization and management.

Role of climate fund raising under fiscal balance on climate change mitigation: an analysis from Pareto optimality.

Since there is little progress being made in multinational climate discussions, climate finance is at a crossroads as lenders must come up with new plans for the "Future of Environment Funds." The mission of effectively and efficiently distributing money to support the shift to low-carbon, climate-resilient economies has been given to climate finance organizations. Due to its purpose to contribute to a paradigm shift, the Green Climate Fund (GCF) is anticipated to help the most vulnerable populations adapt to and mitigate climate change. This research alters the premise of the Baumol and Oates public externality model to make it more appropriate for global climate governance analysis. This research then deduces the special pricing conditions to persuade the market to comply with Pareto optimality criteria by contrasting the Pareto optimality model of global climate governance and the market equilibrium model. The rules and potential approaches that must be followed for raising capital and allocating GCFs are then determined by taking into account global Pareto optimality and fiscal balance. The study finds that when each country assumes that the GCF aims to achieve Pareto optimality in climate governance globally and its own fiscal balance, the equilibrium results of the international climate game will not achieve both the financial balance of the GCF and global Pareto optimality simultaneously. The GCF may successfully finance non-bankable components of bigger "almost bankable projects," according to our empirical analysis of the GCF portfolio structure and strategy in this research. This lends credence to an alternative interpretation of the GCF.

SCC-UEFAS, an urban-ecological-feature based assessment system for sponge city construction.

An effective sponge city construction evaluation system plays a crucial role in evaluating sponge city construction schemes. The construction of a sponge city evaluation system still faces challenges related to incomplete index selection and unscientific weight division. Limited studies have focused on the comprehensive assessment of sponge city construction in the early stages. This study constructed a scientific assessment indicator system and a quantitative indicator weight at all levels by literature review and statistical analysis methods from an objective perspective. To demonstrate how to utilize our evaluation methods, three construction schemes randomly generated by MATLAB were evaluated under evaluation states of constant weight and variable weight, respectively. Scheme 3 had the highest score of 0.638 under the constant weight assessment, but it cannot practically be the final construction scheme due to the imbalance between indicators. Compared to the constant weight assessment, a variable weight assessment can effectively balance the states of the evaluation index with changes in the decision variable. Among the three schemes, Scheme 2 is the best choice with a value of 0.0355 under variable weight evaluation due to punishment and incentives in the variable weight method. The concept of "punishing" a disadvantageous indicator and "motivating" an advantageous indicator increases the relative advantages of the indices, ultimately affecting the assessment results of schemes and leading to a more balanced state. This study provides reasonable analysis and decision-making mechanisms to support decision-making and guide the scientific selection of a construction scheme.

Noninvasive embryo evaluation and selection by time-lapse monitoring vs. conventional morphologic assessment in women undergoing in vitro fertilization/intracytoplasmic sperm injection: a single-center randomized controlled study.

OBJECTIVE: To determine whether time-lapse monitoring (TLM) for cleavage-stage embryo selection improves reproductive outcomes in comparison with conventional morphological assessment (CMA) selection. DESIGN: Prospective randomized controlled trial. SETTING: Single academic center. PATIENTS: We randomly assigned 139 women who were undergoing their first in vitro fertilization or intracytoplasmic sperm injection cycle to undergo either fresh embryo transfer or first frozen embryo transfer (FET). Only 1 cleavage-stage embryo was transferred to each participant. INTERVENTIONS: The patients were randomly assigned to either the CMA or the TLM group. In the CMA group, day 2 and day 3 embryos were observed. A good-quality cleavage-stage embryo was selected for transfer or freezing in both groups. MAIN OUTCOME MEASURES: The primary and secondary outcomes were the clinical pregnancy rate (CPR) and the live birth rate (LBR), respectively, after the first embryo transfer (fresh embryo transfer or FET). RESULTS: The CPR and LBR were significantly lower in the TLM group than in the CMA group (CPR: 49.18% vs. 70.42%; relative risk, 0.70; 95% confidence interval [CI], 0.52-0.94; LBR: 45.90% vs. 64.79%; relative risk, 0.71; 95% CI, 0.51-0.98). The CPR with fresh embryo transfer or FET did not significantly differ between the TLM and the CMA groups (fresh embryo transfer: 44.44% vs. 70.0%, relative risk, 0.63, 95% CI, 0.39-1.03; FET: 52.94% vs. 70.73%, relative risk, 0.75, 95% CI, 0.52-1.09). There was a significant difference in the LBR with fresh embryo transfer between the TLM and the CMA groups (40.74% vs. 66.67%; relative risk, 0.61; 95% CI, 0.36-1.03). The LBRs with FET were similar in the TLM and the CMA groups (50.0% vs. 63.41%; relative risk, 0.79; 95% CI, 0.52-1.19). The rates of early spontaneous abortion and ectopic pregnancy did not differ between the TLM and the CMA groups. CONCLUSIONS: Elective single cleavage-stage embryo transfer with TLM-based selection did not have any advantages over CMA when day 2 and day 3 embryo morphology was combined in young women with a good ovarian reserve. Because of these results, we conclude that TLM remains an investigational procedure for in vitro fertilization practice. CLINICAL TRIAL REGISTRATION NUMBER: ChiCTR1900021981.

Incidence and cost of haemolytic uraemic syndrome in urban China: a national population-based analysis.

BACKGROUND: Haemolytic uraemic syndrome (HUS) is a severe syndrome that causes a substantial burden for patients and their families and is the leading cause of acute kidney injury in children. However, data on the epidemiology and disease burden of HUS in Asia, including China, are limited. We aimed to estimate the incidence and cost of HUS in China.  METHODS: Data about HUS from 2012 to 2016 were extracted from the Urban Employee Basic Medical Insurance (UEBMI) and Urban Resident Basic Medical Insurance (URBMI) databases. All cases were identified by ICD code and Chinese diagnostic terms. The 2016 national incidence rates were estimated and stratified by sex, age and season. The associated medical costs were also calculated. RESULTS: The crude incidence of HUS was 0.66 per 100,000 person-years (95% CI: 0.35 to 1.06), and the standardized incidence was 0.57 (0.19 to 1.18). The incidence of HUS in males was slightly higher than that in females. The age group with the highest incidence of HUS was patients < 1 year old (5.08, 95% CI: 0.23 to 24.87), and the season with the highest incidence was autumn, followed by winter. The average cost of HUS was 2.15 thousand US dollars per patient, which was higher than the national average cost for all inpatients in the same period. CONCLUSIONS: This is the first population-based study on the incidence of HUS in urban China. The age and seasonal distributions of HUS in urban China are different from those in most developed countries, suggesting a difference in aetiology.

Association of insurance status with chronic kidney disease stage at diagnosis in children.

BACKGROUND: Whether medical insurance impacts the timely diagnosis in chronic kidney disease (CKD) children is unknown. We aim to examine the extent to which insurance is associated with access to timely diagnosis and different stages of CKD among a large population of children in China. METHODS: A retrospective, cross-sectional study based on China's national hospitalized record database was carried out. Children aged 0-17 years diagnosed as CKD stages 1-5 between June 1, 2013, and December 31, 2018, were included. A diagnosis of advanced CKD stage (CKD stage 4 or 5) was the primary outcome. Multivariable logistic regression model adjusted for age, sex, cross-regional hospitalization, year of diagnosis, and cause of CKD was used to assess the association between insurance status and the stage of CKD when diagnosed. RESULTS: A total of 10,256 children (median [interquartile range, IQR] age, 12.4 [7.9, 15.4] years) were included. There were 4716 (46.0%) uninsured children in the included population. The insurance coverage was highest in children 13-17 years old (60.9%). The hospitalized charge was highest in stage 5 uninsured children (median [IQR], ¥13,000.89 [7640.63, 24,585.00]). More uninsured children are diagnosed in CKD stage 4 or 5 (48.1%) than insured children (47.5%). Uninsured children had higher odds (odds ratio [OR] 1.20, [95% CI, 1.08-1.32]) of receiving a diagnosis of CKD stage 4 or 5 compared with insured children. CONCLUSIONS: Lack of medical insurance was associated with a more advanced stage of CKD when diagnosed in hospitalized children. A higher resolution version of the Graphical abstract is available as Supplementary information.

Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies.

Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.

Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery.

BACKGROUND: Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The "Corrie" DHI consists of a smartphone application, smartwatch, and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring, and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard of care in reducing 30-day readmissions among AMI patients in comparison to standard of care alone. METHODS: A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars, and effectiveness was measured in quality-adjusted life-years (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty. RESULTS: The DHI reduced costs and increased QALYs on average, dominating standard of care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2750 per patient, use of the DHI leads to a cost-savings of $7274 per patient compared with standard of care alone. CONCLUSIONS: Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based health care can reduce hospital readmissions and associated costs.

Analytical validation of the Percepta genomic sequencing classifier; an RNA next generation sequencing assay for the assessment of Lung Cancer risk of suspicious pulmonary nodules.

BACKGROUND: Bronchoscopy is a common procedure used for evaluation of suspicious lung nodules, but the low diagnostic sensitivity of bronchoscopy often results in inconclusive results and delays in treatment. Percepta Genomic Sequencing Classifier (GSC) was developed to assist with patient management in cases where bronchoscopy is inconclusive. Studies have shown that exposure to tobacco smoke alters gene expression in airway epithelial cells in a way that indicates an increased risk of developing lung cancer. Percepta GSC leverages this idea of a molecular "field of injury" from smoking and was developed using RNA sequencing data generated from lung bronchial brushings of the upper airway. A Percepta GSC score is calculated from an ensemble of machine learning algorithms utilizing clinical and genomic features and is used to refine a patient's risk stratification. METHODS: The objective of the analysis described and reported here is to validate the analytical performance of Percepta GSC. Analytical performance studies characterized the sensitivity of Percepta GSC test results to input RNA quantity, the potentially interfering agents of blood and genomic DNA, and the reproducibility of test results within and between processing runs and between laboratories. RESULTS: Varying the amount of input RNA into the assay across a nominal range had no significant impact on Percepta GSC classifier results. Bronchial brushing RNA contaminated with up to 10% genomic DNA by nucleic acid mass also showed no significant difference on classifier results. The addition of blood RNA, a potential contaminant in the bronchial brushing sample, caused no change to classifier results at up to 11% contamination by RNA proportion. Percepta GSC scores were reproducible between runs, within runs, and between laboratories, varying within less than 4% of the total score range (standard deviation of 0.169 for scores on 4.57 scale). CONCLUSIONS: The analytical sensitivity, analytical specificity, and reproducibility of Percepta GSC laboratory results were successfully demonstrated under conditions of expected day to day variation in testing. Percepta GSC test results are analytically robust and suitable for routine clinical use.

Target Controllability in Multilayer Networks via Minimum-Cost Maximum-Flow Method.

In this article, to maximize the dimension of controllable subspace, we consider target controllability problem with maximum covered nodes set in multiplex networks. We call such an issue as maximum-cost target controllability problem. Likewise, minimum-cost target controllability problem is also introduced which is to find minimum covered node set and driver node set. To address these two issues, we first transform them into a minimum-cost maximum-flow problem based on graph theory. Then an algorithm named target minimum-cost maximum-flow (TMM) is proposed. It is shown that the proposed TMM ensures the target nodes in multiplex networks to be controlled with the minimum number of inputs as well as the maximum (minimum) number of covered nodes. Simulation results on Erdos-Rényi (ER-ER) networks, scale-free (SF-SF) networks, and real-life networks illustrate satisfactory performance of the TMM.

Early blood pressure assessment after acute myocardial infarction: Insights using digital health technology.

OBJECTIVE: There is rising interest in digital health in preventive cardiology, particularly for blood pressure (BP) management. In a digital health study of early BP assessment following acute myocardial infarction (AMI), we sought to examine feasibility and the (1) proportion of post-AMI patients with controlled BP and hypotension, and (2) association between prior cardiovascular disease (CVD) and BP post-AMI. METHODS: In this substudy of the parent Myocardial infarction, COmbined-device, Recovery Enhancement (MiCORE) study, type 1 AMI patients were enrolled between October 2017 and April 2019. Participants self-monitored their BP through 30 days after hospital discharge using an FDA-approved wireless BP monitor connected with a smartphone application. Linear mixed-effects models assessed the association between prior CVD and BP trajectory post-discharge, adjusting for antihypertensive medications and a propensity score inclusive of CVD risk factors. RESULTS: Sixty-eight AMI patients (mean age 58 â€‹± â€‹10 years, 75% male, 68% white race, 68% history of hypertension, 24% prior CVD) provided 2638 measurements over 30 days. The percentage of BP control <130/80 â€‹mmHg was 59.6% (95% CI: 54.3-64.9%) and <140/90 â€‹mmHg was 83.7% (95% CI: 80.3-87.2%). The percentage of systolic BP â€‹<90 â€‹mmHg was 1.1% (95% CI: 0.17-2.0%) and the percentage of diastolic BP â€‹<60 â€‹mmHg was 3.9% (95% CI: 2.6-5.2%). Prior CVD was associated with 12.2 â€‹mmHg higher mean daily systolic BP during admission (95% CI: 3.5-20.9 â€‹mmHg), which persisted over follow-up. There was no association between prior CVD and diastolic BP. CONCLUSION: The digital health program was feasible and ~40% of post-AMI patients who engaged in it had uncontrolled BP according to recent guideline cutpoints, while hypotension occurred rarely. The gap in BP control was especially large in patients in whom AMI represented recurrent CVD. These data suggest an opportunity for more aggressive secondary prevention early after MI as care models integrate digital health.

Assessing different anthropometric indices and their optimal cutoffs for prediction of type 2 diabetes and impaired fasting glucose in Asians: The Jinchang Cohort Study.

BACKGROUND: To study the association between anthropometric measurements and the risk of diabetes and impaired fasting glucose (IFG) and compare body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) to determine the best indicator and its optimal cutoffs for predicting type 2 diabetes and IFG. METHODS: A Chinese prospective (2011-2019) cohort named the Jingchang cohort that included 48 001 participants was studied. Using Cox proportional hazard models, hazard ratios (HRs) for incident type 2 diabetes or IFG per 1 SD change in BMI, WC, and WHtR were calculated. Area under the curve (AUC) was compared to identify the best anthropometric variable and its optimal cutoff for predicting diabetes. RESULTS: The association of BMI, WC, and WHtR with type 2 diabetes or IFG risk was positive in the univariate and multivariable-adjusted Cox proportional hazard models. Of all three indexes, the AUC of BMI was largest and that of WC was smallest. The derived cutoff values for BMI, WC, and WHtR were 24.6 kg/m2 , 89.5 cm, and 0.52 in men and 23.4 kg/m2 , 76.5 cm, and 0.47 in women for predicting diabetes, respectively. The derived cutoff values for BMI, WC, and WHtR were 23.4 kg/m2 , 87.5 cm, and 0.50 in men and 22.5 kg/m2 , 76.5 cm, and 0.47 in women for predicting IFG, respectively. [Correction added on 14 April 2020, after first online publication: '0' has been deleted from 'WC,0' in the first sentence.]. CONCLUSIONS: Our derived cutoff points were lower than the values specified in the most current Asian diabetes guidelines. We recommend a cutoff point for BMI in Asians of 23 kg/m2 and for WC a cutoff point of 89 cm in men and 77 cm in women to define high-risk groups for type 2 diabetes; screening should be considered for these populations.

Task-based assessment of a convolutional neural network for segmenting breast lesions for radiomic analysis.

PURPOSE: Radiomics allows for powerful data-mining and feature extraction techniques to guide clinical decision making. Image segmentation is a necessary step in such pipelines and different techniques can significantly affect results. We demonstrate that a convolutional neural network (CNN) segmentation method performs comparably to expert manual segmentations in an established radiomics pipeline. METHODS: Using the manual regions of interest (ROIs) of an expert radiologist (R1), a CNN was trained to segment breast lesions from dynamic contrast-enhanced MRI (DCE-MRI). Following network training, we segmented lesions for the testing set of a previously established radiomics pipeline for predicting lymph node metastases using DCE-MRI of breast cancer. Prediction accuracy of CNN segmentations relative to manual segmentations by R1 from the original study, a resident (R2), and another expert radiologist (R3) were determined. We then retrained the CNN and radiomics model using R3's manual segmentations to determine the effects of different expert observers on end-to-end prediction. RESULTS: Using R1's ROIs, the CNN achieved a mean Dice coefficient of 0.71 ± 0.16 in the testing set. When input to our previously published radiomics pipeline, these CNN segmentations achieved comparable prediction performance to R1's manual ROIs, and superior performance to those of the other radiologists. Similar results were seen when training the CNN and radiomics model using R3's ROIs. CONCLUSION: A CNN architecture is able to provide DCE-MRI breast lesion segmentations which are suitable for input to our radiomics model. Moreover, the previously established radiomics model and CNN can be accurately trained end-to-end using ground truth data provided by distinct experts.

Population pharmacokinetics and dosage optimization of tacrolimus in pediatric patients with nephrotic syndrome
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OBJECTIVES: The aims of this study were to investigate the population pharmacokinetic (PPK) characteristics of tacrolimus in Chinese children with nephrotic syndrome and to apply it in clinical practice. MATERIALS AND METHODS: A total of 137 concentrations from 61 patients were collected from routine therapeutic drug monitoring data between 2011 and 2018. Population modeling was performed with the nonlinear mixed-effects model (NONMEM) program, using a one-compartment model with first-order absorption and elimination. The mean population estimate values of clearance (CL/F) and volume of distribution (V/F) were determined. Common demographic and clinical variables were tested for their influence on these parameters. External validation was conducted, and Monte Carlo simulation, based on the final model, was carried out to determine optimal dosage regimen. RESULTS: Age and body weight were the covariates that displayed a significant influence on CL/F and V/F according to the final regression model. Goodness-of-fit plots, bootstrap outcomes, and external validation confirmed the relatively good stability and prediction capability of the model. The interindividual variability of CL/F was 31.10%, and the residual variability was 0.91 ng/mL. Mean prediction error (MPE, %) and Mean absolute prediction error (MAPE, %) were 10.3% and 16.6%, respectively. Monte Carlo simulation based on the final model was carried out to determine optimal dosage regimen. CONCLUSION: A PPK model of tacrolimus in children with nephrotic syndrome was developed. Age and bodyweight could partly explain the interindividual variability in the CL/F and V/F of tacrolimus. The final model could be used to accurately predict tacrolimus individual pharmacokinetic parameters and assist in dosage optimization.
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Minimum Cost Control of Directed Networks With Selectable Control Inputs.

The minimum cost control problem is one of the most important issues in controlling complex networks. Different from the previous works, in this paper, we consider the minimum cost control problem with selectable inputs by adopting the cost function summed over both quadratic terms of system input and system state with a weighting factor. To address such an issue, the orthonormal-constraint-based projected gradient method is proposed to determine the input matrix iteratively. Convergence of the proposed algorithm is established. Extensive simulation results are carried out to show the effectiveness of the proposed algorithm. We also investigate what kinds of nodes are most important for minimizing average control cost in directed stems/circles and small networks through simulation studies. The presented results in this paper bring meaningful physical insights in controlling the directed networks from an energy point of view.

Implementation of a specific urban water management - Sponge City.

Climate change, rapid urbanization and inappropriate urban planning policies in many countries have resulted in urban water-related problems, such as flooding disasters, water pollution and water shortages. To tackle these issues, the specific urban water management strategy known as Sponge City has been implemented in China since 2013. This is a complex method and one involving many challenges. This paper critically assesses the approaches associated with conventional urban water management. The Sponge City concept and its adoption are then scrutinized to comprehensively assess the limitations and opportunities. It emerges that Sponge City has four main principles, these being: urban water resourcing, ecological water management, green infrastructures, and urban permeable pavement. The uncertainties in Sponge City design and planning, and financial insufficiencies are the most serious problems that can risk the failure of the Sponge City concept. While significant barriers exist, the opportunities for implementing a Sponge City are evident. To obtain multi-ecosystem services of Sponge City, it should be implemented at the watershed scales and be flexible, depending on different decision levels or catchment characteristics. It is essential to apply an intelligent decision-making mechanism and consider the need for close cooperation between various agencies with which the central government can work. A suitable sized and harmonious Sponge City, ensuring a good balance between socio-economic development and environmental conservation, is the ideal.

Establishment and value assessment of efficacy prediction model about transurethral prostatectomy.

OBJECTIVES: To establish and to evaluate discriminant models to predict the outcomes of transurethral prostatectomy. METHODS: Clinical data of patients treated with transurethral prostatectomy between January and December 2013 were collected, including medical history, symptoms, biochemical tests, ultrasonography and urodynamics. Surgical efficacy was evaluated at 6-month follow up. Predictive models were constructed by logistic regression. Receiver operating characteristic curve and diagnostic tests were used to test the accuracy of models before the predictive value between models was compared. RESULTS: A total of 182 patients were included, with 73.6% having an effective outcome. History of recurrent urinary tract infection (OR 1.33), score of storage phase (OR 2.58), maximum flow rate (OR 2.11) and detrusor overactivity (OR 3.13) were found to be risk factors. International Prostate Symptom Score (OR 0.13), transitional zone index (OR 0.58), resistive index of prostatic artery (OR 0.46), bladder wall thickness (OR 0.78), ultrasonic estimation of bladder weight (OR 0.28), bladder outlet obstruction index (OR 0.20) and bladder contractility index (OR 0.83) were found to be protective factors. The areas under the curve of models using factors from ultrasonography and urodynamics were 0.792 and 0.829 respectively, with no significant difference being found between them (P = 0.348). CONCLUSIONS: Surgical efficacy of transurethral prostatectomy is positively correlated to severe voiding phase symptoms, outlet obstruction and better detrusor contractility, and negative correlated with urinary infection, severe storage phase symptoms and excessive detrusor contractibility. Ultrasonography might replace urodynamics in selecting patients for whom transurethral prostatectomy is more likely to be beneficial.

Comprehensive assessment of the association of WNK4 polymorphisms with hypertension: evidence from a meta-analysis.

The relationship between with-no-lysine [K] kinase 4 (WNK4) gene polymorphisms and hypertension has been widely investigated, However, the studies yielded contradictory results. To evaluate these inconclusive findings comprehensively, we therefore performed a meta-analysis. Ten articles encompassing 16 independent case-control studies with 6089 hypertensive cases and 4881 normotensive controls were selected for this meta-analysis. Four WNK4 gene polymorphisms were identified (G1155942T, G1156666A, T1155547C, and C6749T). The results showed statistically significant associations of G1155942T polymorphism (allelic genetic model: odds ration or OR = 1.62, 95% confidence interval or CI: 1.11-2.38, P = 0.01; dominant model: OR = 1.85, 95% CI: 1.07-3.19, P = 0.03) and C6749T polymorphism (allele contrast: OR = 2.04, 95% CI: 1.60-2.59, P<0.01; dominant model: OR = 2.04, 95%CI: 1.59-2.62, P<0.01; and homozygous model: OR = 5.01, 95% CI: 1.29-19.54, P = 0.02) with hypertension risk. However, neither C1155547T nor G1156666A was associated significantly with hypertension susceptibility. In conclusion, this meta-analysis suggested that WNK4 G1155942T and C6749T gene polymorphisms may contribute to the susceptibility and development of hypertension. Further well-designed studies with larger sample size are required to elucidate the association of WNK4 gene multiple polymorphisms with hypertension risk.