Study In Hangzhou Research Articles

The Levels of Serum HBV Pre-Genomic RNA and Its Associated Factors Among HBV-Infected Patients: A Retrospective Cohort Study in Hangzhou, Zhejiang, China.

This study aimed to explore serum HBV pre-genomic RNA (pgRNA) levels and its associated factors among HBV-infected patients in the real world. This retrospective cohort study was conducted from May 10, 2023, to January 15, 2024. Univariate logistic analysis for positive serum HBV pgRNA was performed first, and variables with statistical significance were included in a multivariate logistic model. A decreasing trend of serum HBV pgRNA and HBV DNA levels was also detected first by univariate logistic regression and then by multivariate logistic regression. 482 patients were included in our analysis at baseline, and 191 patients were followed up. Multivariate logistic regression revealed that positive HBV DNA (AOR: 2.63, 95% CI: 1.46-4.75, P=0.001), ≥1000hBsAg (AOR: 2.29, 95% CI: 1.08-4.89, P=0.03), positive HBeAg (AOR: 28.26, 95% CI: 15.2-52.55, P<0.001), and ALP (AOR: 1.01, 95% CI: 1.001-1.02, P=0.03) were positively correlated with positive HBV pgRNA at baseline. Two independent multivariate logistic regression models were constructed for the decreasing trend of serum HBV pgRNA and HBV DNA for the 191 follow-up patients. Results showed that the decreasing trend of HBV pgRNA was positively correlated with positive baseline HBV DNA (AOR: 4.60, 95% CI: 1.84-11.51, P=0.001), baseline HBsAg ≥1000 IU/mL (AOR: 8.74, 95% CI: 1.09-70.10, P=0.04), and HDL (AOR: 5.01, 95% CI: 1.28-19.66, P=0.02). The decreasing trend of HBV DNA was positively correlated with positive baseline HBV pgRNA (AOR: 3.80, 95% CI: 2.00-8.83, P<0.001) and AST (AOR: 1.06, 95% CI: 1.03-1.08, P<0.001). Our study revealed that HBV DNA, HBsAg, HBeAg, and ALP were significantly correlated with positive HBV pgRNA at baseline. The baseline HBV DNA, HBsAg, and HDL were significantly correlated with decreasing levels of HBV pgRNA. A decreasing trend of HBV DNA significantly correlated with patients' baseline HBV pgRNA and AST.

Uncovering driving factors and spatiotemporal patterns of urban passenger car CO2 emissions: A case study in Hangzhou, China

While passenger cars offer the convenience of door-to-door travel, they are responsible for a substantial share of urban traffic-related carbon emissions, accounting for 44% of the global transport sector's emissions in 2022. Existing studies have not adequately identified the driving factors and spatiotemporal patterns of Passenger car CO2 Emissions (PCEs). To fill this gap, a comprehensive analytical framework for analysing PCE, encompassing several key components, has been developed. First, the PCE is estimated at a fine-grained level by utilising million-scale GPS trajectory data. Secondly, road network and urban functional features are extracted based on multi-source data, examining their nonlinear impacts on PCE. The driving factors of PCE during peak and off-peak periods are identified based on interpretable factor analysis. Finally, latent space clustering techniques are applied to reveal the spatiotemporal patterns of PCE, verified by significance tests. The effectiveness of this framework is demonstrated via a case study in Hangzhou, China. Notably, during peak hours, the driving factors of PCE are the road network's closeness centrality, service-related Points of Interest (POI) density, and trunk road density. In addition, five distinctive PCE patterns are identified. These findings facilitate the development of targeted and differentiated passenger car traffic management strategies, promoting carbon emission reduction in the transport sector.

Force and Deformation Characteristics of Large-Scale Zoning Excavation in Soft Soil: A Case Study in Hangzhou

The zoning excavation method is fully employed to control the deformation of foundation pits constructed in urban soft soil areas. However, the similarities and differences in forces and deformations between foundation pits excavated by the zonal method and those excavated by the conventional method still need to be further explored. In this study, the deformation was monitored and analyzed by taking the zonal excavation of a foundation pit of the ‘New World’ project in Hangzhou City as the research object. The measured results showed that the pre-built diaphragm wall for the first excavated foundation pit restricted the deformation of the first excavated diaphragm wall. The presence of extensive construction and unloading activities also changed the deformation pattern of the soil. Further, finite element simulations were carried out. The simulation results revealed that excavating the foundation pit first caused displacements in the pre-built diaphragm wall. The displacements transmitted by non-adjacent pits through the pre-built diaphragm wall were small and were concentrated at the junction of the two sub-pits. Adjacent foundation pits caused large displacements of the pre-built diaphragm wall with similar displacement patterns. The results of the study can provide effective guidance for foundation pit excavation in soft soil areas in the future.

Optimizing routing and scheduling of shared autonomous electric taxis considering capacity constrained parking facilities

This paper focuses on routing and scheduling of autonomous electric vehicles to provide reservation-based shared ride services, while a set of parking facilities with limited capacity are used for vehicle intermittent charging. A mixed-integer linear program model is formulated in the form of a vehicle routing problem with satellite facilities (VRPSF), subject to a series of additional time and capacity-related constraints. The objective of the model is to minimize the total operating costs of the system, including those related to vehicle miles traveled and the deployed vehicle fleet size. The number of vehicles inside each parking facility is tracked so as to ensure that the capacity is never exceeded throughout the service horizon. A customized solution method based on an adaptive large neighborhood search algorithm with an explicit treatment of parking facility choices is developed. A series of numerical experiments, consisting of both hypothetical examples and a real-world case study in Hangzhou, China, have been conducted to evaluate the effectiveness and applicability of the proposed model and algorithm. The results demonstrate that ride-sharing services and parking facilities have the potential to significantly reduce the total vehicle energy consumption and operating costs for a shared autonomous electric taxi (SAET) operator in practical scenarios.

The Effects of the Built Environment on the Mental Health of Older Adults: A Case Study in Hangzhou, China.

This study examines the association between the built environment and mental health among older adults by exploring the potential pathways through the perceived built environment, social interaction, and environmental pollution. Research data were collected from 1405 older adults aged 60 years and older in 30 residential neighborhoods of Hangzhou, China, in 2022. The participants' evaluation of the perceived built environment, social interaction, and environmental pollution were assessed. Mental health was measured by the 12-item Short-Form Health Survey. The built environment was measured through an evaluation of density, diversity, design, destination accessibility, distance to transit, and the age-friendly environment. Structural equation models were established based on 300-m, 500-m, and 800-m buffers from the entrance of residential neighborhoods. The propensity score method was employed for sensitivity analysis. With regard to older adult's mental health, there were significant direct effects of the accessibility of health services, shopping services, and bus stops. A robust mediating effect of perceived built environment was displayed on the relationship between land use mix and mental health of older adults. Social interaction exhibited robust mediating effects between the age-friendly environment, the number of bus stops, and mental health of older adults. This study provides empirical experience for related research on the built environment and mental health as well as policy implications for urban planners focusing on community planning.

Riding practices of e-bike riders after the implementation of electric bike management regulations: An observational study in Hangzhou, China

ObjectiveThis study aimed to understand the riding behaviors of electric bike (e-bike) users in Hangzhou after the “Regulations of Zhejiang Province on the Administration of Electric Bicycles”. MethodsThe study consisted of two parts, including a questionnaire survey of local e-bike users in Shangcheng District and Jiande County in Hangzhou City, and a cross-sectional observational study of 16 intersections. ResultsA total of 789 e-bike riders participated in the questionnaire survey, and the riding behavior of 99,407 e-bike users was observed. The main purpose of using e-bike was work and daily life, 46.0% of them used e-bikes more than 5 days a week, and 58.5% used e-bikes for less than 30 min each time. A vast majority (81.7%) of e-bike riders believe that the implementation of Zhejiang Regulations has significantly improved the safety level of e-bike riding in the region. The field survey found that the correct rates of helmet wearing by e-bike riders and passengers were 78.83% and 42.27%. The main violations were invalid/non-helmet wearing (21.17%), followed by carrying passengers and running red lights (7.94% and 4.26%). The rates of invalid/non-helmet wearing and running red lights were significantly higher during non-morning rush hour, weekends, and roads without separate non-motorized vehicle lanes than in other conditions (all P < 0.05). Additionally, sunny days and crossroads were risk factors for passenger-carrying and invalid/non-helmet wearing compared to rainy/cloudy days and T-intersections. ConclusionsThe phenomenon that e-bike users' correct practice lags far behind the awareness of various violations has shown some improvement. To further enhance safety measures for e-bike riders, it is necessary to promote education, improve infrastructure, and strengthen law enforcement, in support of the “Zhejiang Regulations” and behavioral interventions.

Near-surface imaging by joint analysis of traffic-induced Rayleigh and Love waves using 3C dense linear arrays: A case study in Hangzhou, China

As urbanization grows at an unexpectedly rapid pace around the world, the underground space is gradually regarded as a largely undeveloped natural resource. Passive surface wave methods based on short-time traffic-induced noise measurements have been shown to be powerful tools for underground imaging and monitoring in urban areas. The common surface-wave investigations mainly focus on the use of Rayleigh waves in vertical components. We have developed an application of using three-component traffic-induced surface waves to investigate near-surface structures in Hangzhou City, Eastern China. With the deployment of two dense linear arrays along the orthogonal roads, we analyze the temporal and spectral characteristics of the three-component traffic noise. The retrieval of Rayleigh and Love waves using the horizontal components could be biased due to the uneven noise source distribution and errors in the orientation of the horizontal receivers. We use the match-field processing technique to obtain the direction of noise source distribution, and apply polarization analysis to evaluate the misorientation of the horizontal components. Subsequently, high-quality Rayleigh and Love waves are retrieved based on seismic interferometry within 1 h noise recordings. We invert the multicomponent surface waves to determine near-surface shear (S)-wave velocity structures. The joint analysis of Rayleigh and Love waves improves the reliability and stability of the result. Comparisons among the results from the individual inversion of Rayleigh waves, the joint inversion of Rayleigh and Love waves, and the logging data demonstrate that the jointly inverted S-wave velocity profiles provide better correspondence with the logging results, which confirms that the combined use of Rayleigh and Love waves from multicomponent traffic noise can be a more powerful technique for near-surface characterization in urban areas.

Effect of urbanization and urban forests on water quality improvement in the Yangtze River Delta: A case study in Hangzhou, China

In the context of rapid global urbanization, the sustainable development of ecosystems should be considered. Accordingly, the Planetary Boundaries theory posits that reducing the amount of nitrogen and phosphorus pollutants entering bodies of water is necessary as excess levels may harm the aquatic environment and reduce in water quality. Thus, based on the long-term monitoring data of representative urban rivers in the Yangtze River Delta region, we evaluated the nitrogen and phosphorus pollution of water bodies in different urbanization stages and further quantified the effect of urban forests on water quality improvement. The results showed that, with the continuous progression of urbanization, the proportion of impervious surface area increased, along with the levels of nitrogen and phosphorus pollution in water bodies. The critical period of water quality deterioration in urban rivers occurred during the medium urbanization level when the proportion of impervious surface area reached 55–65 %, and the probability of an abrupt increase in total nitrogen (TN) and total phosphorus (TP) concentration exceeded 95 %. However, increasing the area of urban forests during this period reduced TN pollution by 36.64 % and TP pollution by 49.03 %. The results of this study support the expansion of urban forests during the medium urbanization stage to improve water quality. Furthermore, our results provide a reference and theoretical basis for urban forest construction as a key aspect of the sustainable development of the urban ecosystem in the Yangtze River Delta and similar regions around world.

Performance of a Deep Excavation Supported by Diaphragm Walls Combining with Servo Steel Struts: A Case Study in Hangzhou, China, Soft Clay Deposits

Performance of a Deep Excavation Supported by Diaphragm Walls Combining with Servo Steel Struts: A Case Study in Hangzhou, China, Soft Clay Deposits

Integrating LCA, BIM, and Surrounding Trees for Carbon Neutrality in Steel and Concrete Frame Public Structures: A Case Study in Hangzhou

The construction industry is actively working to improve its operations’ sustainability and reduce buildings’ ecological impact on climate change. One approach involves integrating Building Information Modeling (BIM) with Life Cycle Assessment (LCA) to streamline data input, calculate environmental impacts, and optimize output data. This case study focuses on using the One-Click LCA plugin to explore LCA-BIM integration for sustainable construction.The study examines the carbon emissions of steel and concrete frame public structures and assesses the role of surrounding trees in achieving carbon neutrality. Two innovative public buildings in China’s Zhejiang province serve as the case study’s subject. The One-Click LCA plugin in Revit is a quick and user-friendly tool, providing concrete and steel structure results and generating informative graphs for easy comparison.The findings reveal that the A1-A3 material stage during the design phase contributes the most to emissions and biogenic carbon storage. By demonstrating the practical implementation of LCA-BIM integration using the One-Click LCA plugin, this case study contributes to the knowledge base on sustainable construction practices. The results can guide decision-making for architects, engineers, and construction professionals, empowering them to make informed choices that minimize carbon emissions and promote environmentally-friendly design strategies.

An update on the association between ambient short-term air pollution exposure and daily outpatient visits for conjunctivitis: a time-series study in Hangzhou, China.

Air pollution is a major public health problem that can lead to conjunctivitis. This study aimed to explore the associations between air pollutants and outpatient visits for conjunctivitis in Hangzhou, China. This study collected data on 50,772 patients with conjunctivitis and the concentrations of six air pollutants from February 1, 2014, to August 31, 2018. A time series analysis using a generalized additive model (GAM) was conducted. We found that the risk of conjunctivitis was related to the air pollutants PM2.5, PM10, SO2, NO2, and O3, which had concentration hysteresis effects. The risk of conjunctivitis increased by 1.009 (95% confidence interval (CI): 1.003, 1.014), 1.011 (95% CI: 1.008, 1.015), 1.238 (95% CI: 1.186, 1.292), 1.028 (95% CI: 1.019, 1.038), and 1.013 (95% CI: 1.008, 1.017) for every 10µg/m3 increase in PM2.5, PM10, SO2, NO2, and O3 concentrations, respectively. The lag effects of SO2 and NO2 were stronger than those of particulate matter. Females exposed to PM10, PM2.5, SO2, and O3 had a higher risk of conjunctivitis than males, while males exposed to NO2 had a nearly identical risk of conjunctivitis as females. People aged 19-59 were more likely to suffer from conjunctivitis. The risk of conjunctivitis caused by PM10, SO2, and O3 was highest in the transitional season, while the risk caused by NO2 was highest in the winter season. In conclusion, females and middle-aged adults were at higher risk of conjunctivitis. People were more susceptible to conjunctivitis during the transitional season. These findings highlight the importance of atmospheric pollution governance and reference for public health measures.

Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China.

In December 2022, there was a large Omicron epidemic in Hangzhou, China. Many people were diagnosed with Omicron pneumonia with variable symptom severity and outcome. Computed tomography (CT) imaging has been proven to be an important tool for COVID-19 pneumonia screening and quantification. We hypothesized that CT-based machine learning algorithms can predict disease severity and outcome in Omicron pneumonia, and we compared its performance with the pneumonia severity index (PSI)-related clinical and biological features. Our study included 238 patients with the Omicron variant who have been admitted to our hospital in China from 15 December 2022 to 16 January 2023 (the first wave after the dynamic zero-COVID strategy stopped). All patients had a positive real-time polymerase chain reaction (PCR) or lateral flow antigen test for SARS-CoV-2 after vaccination and no previous SARS-CoV-2 infections. We recorded patient baseline information pertaining to demographics, comorbid conditions, vital signs, and available laboratory data. All CT images were processed with a commercial artificial intelligence (AI) algorithm to obtain the volume and percentage of consolidation and infiltration related to Omicron pneumonia. The support vector machine (SVM) model was used to predict the disease severity and outcome. The receiver operating characteristic (ROC) area under the curve (AUC) of the machine learning classifier using PSI-related features was 0.85 (accuracy = 87.40%, p < 0.001) for predicting severity while that using CT-based features was only 0.70 (accuracy = 76.47%, p = 0.014). If combined, the AUC was not increased, showing 0.84 (accuracy = 84.03%, p < 0.001). Trained on outcome prediction, the classifier reached the AUC of 0.85 using PSI-related features (accuracy = 85.29%, p < 0.001), which was higher than using CT-based features (AUC = 0.67, accuracy = 75.21%, p < 0.001). If combined, the integrated model showed a slightly higher AUC of 0.86 (accuracy = 86.13%, p < 0.001). Oxygen saturation, IL-6, and CT infiltration showed great importance in both predicting severity and outcome. Our study provided a comprehensive analysis and comparison between baseline chest CT and clinical assessment in disease severity and outcome prediction in Omicron pneumonia. The predictive model accurately predicts the severity and outcome of Omicron infection. Oxygen saturation, IL-6, and infiltration in chest CT were found to be important biomarkers. This approach has the potential to provide frontline physicians with an objective tool to manage Omicron patients more effectively in time-sensitive, stressful, and potentially resource-constrained environments.

Occurrence, distribution and potential risk to infants of neonicotinoids in breast milk: A case study in Hangzhou, China

The pervasive use of neonicotinoid insecticides (neonics) has led to increasing concerns regarding the potential health risks associated with them. Breast milk is the main food source of infants, and thus, the presence of chemicals in breast milk has a greater impact on infant health. However, there have only been few reports regarding the presence of neonics in breast milk. Herein, eight neonics were detected in breast milk samples using ultraperformance liquid chromatography–mass spectrometry and their Pearson correlation was analyzed. The potential health risks of neonics to infants were assessed using the relative potency factor (RPF) method. The results revealed that neonics were widely detected in the breast milk samples from Hangzhou, with at least one neonics being detected in >94 % of the breast milk samples. The most frequently detected neonics included thiamethoxam (70.8 %) followed by imidacloprid (IMI) (62.0 %) and clothianidin (46.0 %). The residual concentrations of neonics in the breast milk samples ranged from <limit of detection of 501 ng/L, with a maximum IMIRPF value of 4760 ng/L. The analysis of neonics concentrations via Pearson's correlation coefficient revealed statistically significant positive correlations between the concentrations of thiamethoxam, clothianidin, and acetamiprid and between those of clothianidin, acetamiprid, and IMI in the breast milk samples, indicating that these neonics may have the same source. The cumulative intake exposure of infants of different ages ranged from 152.9 to 276.3 ng/kg/day, with the risks within acceptable limits. The findings of this study enable the assessment of the exposure level and health risks of neonics to infants during breastfeeding.

Identification of priority areas for public-access automated external defibrillators (AEDs) in metropolitan areas: A case study in Hangzhou, China

Out-of-hospital cardiac arrest (OHCA) is a major health concern in China. The use of automated external defibrillators (AEDs) has received great attention from Chinese public healthcare departments as a useful intervention to address OHCA, and there is a growing need to place AEDs throughout the urban built environment. However, due to the lack of a publicly available, geocoded dataset of historical OHCA cases, there is not a coherent approach for identifying priority areas for AEDs placement in this country. This study attempts to fill this gap by examining the spatial disparity of OHCA risk in Hangzhou, China, and then proposing a Geographic Information Systems(GIS) based model that incorporates the urban land cover, vulnerable groups, and transportation accessibility to identify priority areas at the hexagon level for future AEDs placement. Results show that: (1) the hexagons with the highest level of OHCA risk (ranked Group 1) are accounting for 9.87%–16.71% and are spatially dispersed. (2) A large high-risk cluster was identified in the western region of the Qiantang district. (3) Nearly one-fifth of the new AEDs are recommended to install in Phase I, more than 60% in Phase II, and the remainder in Phase III. (4) Xiaoshan district requires the most AEDs, while Linping district requires the fewest. Ultimately, these results guide future placement of the AED facilities in the cities, particularly those with no geocoded OHCA historical data.

Study of the Impact of Air Pollution on Convulsions in Children: A Hospital-Based Retrospective Study in Hangzhou, China.

To investigate the relationship between the occurrence of convulsions in children and air pollution in Hangzhou. From January 1, 2018, to December 31, 2020, 775 children admitted with convulsion to the pediatric outpatient clinic of The Affiliated Hospital of Hangzhou Normal University (Hangzhou, China) were enrolled in this study. The clinical data and the corresponding weather data of the day in Hangzhou were collected and analyzed. Also, the monthly etiological classification of convulsions and the monthly average air data of Hangzhou were statistically analyzed. The highest incidence of convulsion was observed in children 1 to 2 years old, and higher in boys than in girls. The top three main causes were febrile seizure, benign infantile convulsion with mild gastroenteritis, and epilepsy. Among the meteorological factors, the increase in the level of 2.5 micron particulate matter (PM 2.5) in the air per month led to an increase in the number of patients with febrile seizure, benign infantile convulsion with mild gastroenteritis, and epilepsy, where the increase of ozone in 8 hours (O3-8h) per month led to a decrease in the number of patients with such conditions. PM2.5, PM10, and SO2 are the main meteorological factors affecting the occurrence of convulsions in children in Hangzhou, and PM2.5 and SO2 are risk factors. The increase in the level of PM2.5 in the air per month could increase occurrence of child convulsions, but the increase of O3-8h per month could decrease occurrence of child convulsions.

Seasonal effects of urban morphology on land surface temperature in a three-dimensional perspective: A case study in Hangzhou, China

Architecture influences the design of urban landscapes and hence plays an important role in the regulation of urban thermal environment. Studies on the correlation between multi-dimensional building morphology and land surface temperature (LST) have been conducted in many cities around the world. However, general conclusions on their relationship have not been drawn, owing to the differences in climatic, social, and economic conditions between cities. Moreover, the multivariate and nonlinearity of the three-dimensional (3D) indicators also require more robust and specific statistical models. In this study, the random forest (RF) regression model was used to quantitatively analyse the seasonal differences in the responses of nine multi-dimensional building indicators to LST. The results show that the building coverage ratio (BCR), high building ratio (HBR), and architecture height standard deviation (AHSD) always had the most substantial influence. Across seasons, the average relative contribution ratios of BCR, HBR, and AHSD were 13.23–33.50%, 11.37–20.06%, and 9.02–24.12%, respectively. In general, 2D indicators tended to have a higher impact in warmer seasons while 3D indicators showed more impact on LST in cooler seasons. According to the marginal effect analysis, the BCR, cubic index (CI), and aggregation index (AI) were the main heating indicators, whereas AHSD and HBR were the main cooling indicators. Overall, our findings contribute to the understanding of the urban heat island phenomenon, which remains an important issue in the context of sustainable landscape and urban planning.

Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China

Land-use/land-cover change (LUCC) is an important factor affecting carbon storage. It is of great practical significance to quantify the relationship between LUCC and carbon storage for regional ecological protection and sustainable socio-economic development. In this study, we proposed an integrated framework based on multiobjective programming (MOP), the patch-level land-use simulation (PLUS) model, and the integrated valuation of ecosystem service and trade-offs (InVEST) model. First, we used the InVEST model to explore the spatial and temporal evolution characteristics of carbon storage in Hangzhou from 2000 to 2020 using land-cover data. Second, we constructed four scenarios of natural development (ND), economic development (ED), ecological protection (EP), and balanced development (BD) using the Markov chain model and MOP, and then simulated the spatial distribution of land cover in 2030 with the PLUS model. Third, the InVEST model was used to predict carbon storage in 2030. Finally, we conducted a spatial correlation of Hangzhou’s carbon storage and delineated carbon storage zoning in Hangzhou. The results showed that: (1) The artificial surfaces grew significantly, while the cultivated land decreased significantly from 2000 to 2020. The overall trend was a decrease in carbon storage, and the changing areas of carbon storage were characterized by local aggregation and sporadic distribution. (2) The areas of artificial surfaces, water bodies, and shrubland will continue to increase up to 2030, while the areas of cultivated land and grassland will continue to decrease. The BD scenario can effectively achieve the multiple objectives of ecological protection and economic development. (3) The carbon storage will continue to decline up to 2030, and the EP scenario will have the highest carbon storage, which will effectively mitigate the carbon storage loss. (4) The spatial distribution of carbon storage in Hangzhou was inextricably linked to the land cover, which was characterized by a high–high concentration and a low–low concentration. The results of the study can provide decision support for the sustainable development of Hangzhou and other cities in the Yangtze River Delta region.

Clinical characteristics and associated factors of pediatric acute disseminated encephalomyelitis patients with MOG antibodies: a retrospective study in Hangzhou, China

BackgroundTo explore the clinical characteristics and related factors of children with acute disseminated encephalomyelitis (ADEM) with positive anti-myelin oligodendrocyte glycoprotein (MOG) antibody.MethodsA retrospective study was conducted and enrolled pediatric ADEM patients who underwent serum MOG antibody detection from May 2017 to August 2020. The patients were divided into two groups: MOG- immunoglobulin G (IgG) positive (n = 35) and MOG-IgG negative (n = 50). We analyzed the clinical characteristics of MOG-IgG-positive ADEM pediatric patients and conducted a comparative analysis between the two groups.ResultsThirty-five patients (21 males and 14 females) in the MOG-IgG-positive group with encephalopathy, multifocal neurological symptoms, and typical magnetic resonance imaging (MRI) abnormalities were enrolled. They usually had a favorable outcome, while some suffered from relapse. Compared to the MOG-IgG-negative group, MOG-IgG-positive ADEM patients had a longer disease duration (median: 10 vs. 6 days), more meningeal involvement (31.4% vs. 8%) and frontal lobe involvement (82.8% vs. 68%), higher relapse rates (14.3% vs. 2%), lower serum tumor necrosis factor (1–12.4 pg/ml, median 1.7 vs. 1–34 pg/ml, median 2.2) and interferon-gamma (1–9.4 pg/ml, median 1.3 vs. 1–64 pg/ml, median 3) (P < 0.05, respectively). Multivariate logistic regression analysis showed that the longer disease duration, meningeal involvement and frontal lobe involvement were the correlated factors of patients with ADEM with MOG antibody (P < 0.05).ConclusionsOur findings provide clinical evidence that MOG-IgG positivity is associated with longer disease duration, meningeal involvement, and frontal lobe involvement.

Investigating the Changes in Urban Green-Space Patterns with Urban Land-Use Changes: A Case Study in Hangzhou, China

Urban green space (e.g., parks, farmland, gardens, etc.) design in different urban functional regions (e.g., residential land, commercial land, etc.) depends on different planning purposes. The changes in urban green spaces are highly related to urban land-use changes (e.g., from residential land to commercial land). However, the investigation of urban green space patterns in response to urban land-use changes has been ignored. This research takes Hangzhou city, a typical example in terms of urbanization, population growth, economic development, and land-use changes, as the study site, aiming to explore the landscape patterns of urban green space changes with different urban land-use changes. The results showed that urban green spaces increased from 2017 to 2021, and the growth was mainly concentrated in the urban core area, indicating that the city has made remarkable achievements in the planning of green spaces. Specifically, the increase in urban green spaces in the first ring belt was mainly related to the old town transformation program in the residential land. The change from the residence parcels to the business parcels determined the increase in green spaces in the second and third ring belts, probably because of the attractiveness of customers. In addition, a large number of open-space parcels have changed to business parcels around the urban periphery, which might be due to the transformation from farmland to impervious surfaces. Combined with the urban land-use and green-space policies, the findings highlighted that a reasonable urban land-use layout can promote the optimization and layout of urban green spaces. The private sector (e.g., shopping malls) can also contribute to the increase in green spaces. The understanding of urban green landscapes with different urban land-use changes can provide references for analyzing and optimizing green space in other cities experiencing rapid urban land-use changes.

Intended and unintended impacts of the comprehensive reform of urban public hospitals: A mixed-method study in Hangzhou, China.

ObjectivesPublic hospital reform is a key area in the Chinese healthcare system reform with the aim of controlling excessive growth of medical expenditures. This study aims to evaluate the impacts of two rounds of urban public hospital reforms respectively starting in 2018 and 2019.MethodA mixed-method method was conducted in Hangzhou. In the quantitative phase, monthly data covering 7 provincial, 12 municipal, and 35 district hospitals from March 2017 to June 2020 was analyzed using a panel-interrupted time-series. Thematic content analysis was conducted using qualitative data collected from 32 in-depth interviews.ResultsQuantitative data showed a considerable reduction in the proportion of drug revenue (provincial hospitals: −4.937%; municipal hospitals: −2.765%; district hospitals: −2.189%) and an increase in the proportion of consumable (provincial hospitals: β2 = 2.025; municipal hospitals: β3 = 0.206) and examinations (provincial hospitals: β2 = 1.354, β3=0.159; municipal hospitals: β2 = 1.179) revenue after the first reform. In post-reform 2, The respective instant decrease and increase in the proportion of consumable (provincial hospitals: −2.395%; municipal hospitals: −0.898%) and medical services (provincial hospitals: 2.115%; municipal hospitals: −2.604%) revenue were observed. Additionally, quantitative and qualitative data indicated inpatient expenditures dropped considerably after the reform. However, insufficient compensation for medical services and increased financial pressure on hospitals were repeatedly mentioned as unintended consequences in qualitative interviews.ConclusionsOverall, the urban public hospital reforms in China created positive effects in adjusting hospital revenue structure and constraining soaring medical expenditures. Unintended consequences remind policymakers to establish rational and dynamic compensation mechanisms for public hospitals.