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Abstract Cerebral cavernous malformations (CCMs) are hemorrhagic vascular disorders with varied clinical and radiological presentations, occurring sporadically due to MAP3K3 or PIK3CA mutations or through inherited germline mutations of CCM genes. This study aimed to clarify the clinical, genetic, and pathological features of CCMs using a multicenter cohort across three Chinese centers. We analyzed 290 surgical specimens from symptomatic CCM patients, utilizing whole-exome sequencing, droplet digital PCR, and targeted panel sequencing, alongside immunohistology to examine genotypic and phenotypic differences. Among 290 cases, 201 had somatic MAP3K3, PIK3CA, or germline CCM mutations, each associated with distinct clinical parameters: hemorrhage risk (P

Ion exchange selective electrodialysis(ISED) is a water treatment technique that uses ion exchange resin filling to improve the efficiency of ion separation by electrodialysis under specific conditions. With relatively high energy efficiency and no need for resin acid-base regeneration, ISED has been now used in ultra-pure water preparation and specific wastewater treatment in the electric power, pharmaceutical,automotive and other industries. While distinguishing between ion exchange electrodialysis(IXED) and ISED, this paper comprehensively summarized and discussed the theory, mechanism and model of ion movement and separation of target ions in IXED and ISED processes. On this basis, the development status of IXED and ISED process structures and technologies was summarized, and the research progress of ISED technology in the direction of ion separation and recovery in groundwater and industrial wastewater was discussed and analyzed. Finally, the future development direction of selective salt separation by ISED technology was prospected from three aspects of resin,membrane material and operation mode.

BackgroundWe aimed to evaluate the seroprevalence of SARS-CoV-2 and investigate the trajectories of protective immunity and associated risk factors in eastern China between March and November 2023 after the easing of COVID-19 restrictions.Materials and methodsWe conducted repeated population-based seroepidemiologic studies using a multistage, population-stratified, cluster random sampling method. We measured neutralizing antibodies (nAbs) using a fluorescence immunoassay. We calculated both overall and stratified seroprevalence. The latent class growth mixed model (LCGMM) was used to analyze the dynamic trajectories of antibodies, and a multinomial logistic regression model was used to identify factors associated with different antibody trajectory patterns.ResultsA total of 6,147 participants were included at baseline, with a median age of 53.61 years. Both observed and adjusted seroprevalence remained high and stable throughout the study period. The LCGMM identified four distinct antibody trajectories: 75.22% of participants had a high and stable antibody trajectory, while nearly 8% of them exhibited an increase, decline, or low-stable antibody trajectory. Younger participants, women, those fully vaccinated, and individuals with a history of previous infection were more likely to have high and stable antibody trajectories.ConclusionThe majority of the population maintained sustained protective immunity after the outbreak, following the easing of COVID-19 restrictions across the country.

The identification of conservation priority for ecosystem services (ESs) holds paramount importance in harmonizing environmental sustainability with human well-being and bolstering sustainable resource management. However, the utilization of a singular evaluation indicator and the employment of ambiguous methods for delineating conservation priorities have resulted in deviations in the decision-making processes. This study focused on the Danjiangkou Reservoir Area (DRA), the originating point and primary water source for the middle route of the South-to-North Water Transfer Project, and employed the InVEST model to quantify five key ESs, including carbon storage (CS), habitat quality (HQ), water yield (WY), water purification (WP), and soil conservation (SC) for the period spanning from 2000 to 2020 to simulate seven pending priority scenarios by utilizing the ordered weighting algorithm (OWA). Additionally, it incorporated the analytic hierarchy process (AHP) to formulate an evaluation indicator system that combines spatial distribution rationality, conservation efficiency, degree of trade-off, and policy compliance to quantify the scores for each pending scenario, thereby facilitating the determination of the optimal conservation priority. The results indicate a gradual temporal decline in these ESs. Spatially, CS, HQ, WP, and SC show strong synergies, while WY exhibits significant trade-offs with them. The optimal conservation priority, with a total area of 0.35 × 104 km2 and primarily located in the high mountainous and hilly regions in the southern and central parts of DRA, is covered by forest and grass land. It exhibits both high conservation efficiency and spatial distribution rationality, which are based on the policy compliance and effectively coordinates relationships among various ESs. This study offers new insights into the quantification and visualization of the identification of optimal conservation priority. The outcomes serve as a reference for informing the protection and management strategies of water source areas and regions with a high supply of ESs.

Mapping water bodies from remotely sensed imagery is crucial for understanding hydrological and biogeochemical processes. The identification of water extent is mainly dependent on optical and synthetic aperture radar (SAR) images. However, the use of remote sensing for water body mapping is often undermined by the mixed pixel dilemma inherent to traditional hard classification approaches. At the same time, the presence of clouds in optical imagery and speckle noise in SAR imagery, coupled with the difficulty in differentiating between water-like surfaces and actual water bodies, significantly compromise the accuracy of water body identification. This paper proposes a DEEP feature collaborative convolutional neural network (CNN) for Water Super-Resolution Mapping based on Optical and SAR images (DeepOSWSRM), which collaboratively leverages Sentinel-1 and Sentinel-2 imagery to address the challenges of missing data and mixed pixels. The Sentinel-1 image provides complementary water distribution information for the cloudy areas of the Sentinel-2 image, while the Sentinel-2 image enhances the perception capabilities for small water bodies in the Sentinel-1 image. Using PlanetScope imagery as the true reference data, the effectiveness of the proposed method was assessed through two experimental scenarios: one utilizing synthetic coarse-resolution imagery degraded from Sentinel-1 and Sentinel-2 data and another using actual Sentinel-1 and Sentinel-2 data, encompassing both simulated and real cloud conditions. A comparative analysis was conducted against three state-of-the-art CNN-based water mapping methods and two CNN SRM methods. The findings demonstrate that the proposed DeepOSWSRM method successfully produces accurate, fine-resolution water body maps, with its performance mainly benefiting from the fusion of SAR and optical images.

Small water bodies, such as ponds, are widely distributed in agricultural watersheds. They not only serve agricultural irrigation and drainage but also play a crucial role in reducing nitrogen and phosphorus in agricultural non-point source pollution and improving river water quality. However, the linkage between river water quality and the spatial distribution pattern of small water bodies is still unclear. In this study, an agricultural watershed, consisting of nine sub-watersheds and over 1800 ponds was selected, to evaluate the impact of small water body distribution on river water quality. Despite ponds account for less than 0.6 % of the sub-watershed area, they largely determine water quality variations. Specifically, sub-watersheds with lower connectivity among ponds and shorter distances between ponds and farmland exhibited better water quality. These two indicators alone explain more than 87 % variations of nutrient concentrations among the sub-watersheds. This indicates that dispersed ponds that are located close to farmlands serve as important sinks for pollutants in agricultural watersheds. In this study, we emphasize the importance of location of small water bodies in maintaining river water quality, which can provide crucial information for future agricultural watershed land use planning and the development of optimized strategies for water quality improvement.

Ecosystem services (ES), which serve as the link between human activities and natural ecosystems, are crucial for maintaining ecological balance and supporting economic development. The Ecosystem Services Value (ESV) is an indicator used to quantifying ecosystem services. Accurately estimating the dynamics of ESV and the threshold effects of influencing factors is of great importance for the sustainable development of the region. This study constructs an ESV valuation model based on the equivalent factor method, incorporating construction land, and corrects the initial valuation results in three dimensions. By constructing a random forest model and integrating partial dependence analysis, Elevation, Evapotranspiration, Normalized Difference Vegetation Index, and the proportion of built-up land area were identified as significant factors in determining ecologically vulnerable areas within the study region. The results show that: (1) The total ESV in Henan along the Yellow River in 2000, 2005, 2010, 2015, and 2020 was 204.612 billion yuan, 249.775 billion yuan, 239.100 billion yuan, 234.868 billion yuan and 202.767 billion yuan, respectively. The overall trend of change is first growth and then decline, with spatial features remaining relatively stable, and ESV polarization becoming more pronounced. (2) The spatial clustering characteristics of ESV in Henan along the Yellow River are remarkable, and the cold and hot spot areas show a bidirectional expansion trend. The cold spot areas expand substantially around the construction land, whilethe hot spot areas show a small expansion around the western mountain areas and the vegetation areas along the Yellow River, but the overall growth is slower. (3) The main factors affecting ESV include three natural factors and one anthropogenic factor, namely evapotranspiration (ET), the proportion of built-up land area (POB), normalized vegetation index (NDVI) and elevation (ELEV). ESV is at a high level when ELEV>718 m, ET0.7, and POB

Mixed pixels often hinder accurate cropland mapping from remote sensing images with coarse spatial resolution. Image spatial super-resolution reconstruction technology is widely applied to address this issue, typically transforming coarse-resolution remote sensing images into fine spatial resolution images, which are then used to generate fine-resolution land cover maps using classification techniques. Deep learning has been widely used for image spatial super-resolution reconstruction; however, collecting training samples is often difficult for cropland mapping. Given that the quality of spatial super-resolution reconstruction directly impacts classification accuracy, this study aims to assess the impact of different types of training samples on image spatial super-resolution reconstruction and cropland mapping results by employing a Residual Channel Attention Network (RCAN) model combined with a spatial attention mechanism. Four types of samples were used for spatial super-resolution reconstruction model training, namely fine-resolution images and their corresponding coarse-resolution images, including original Sentinel-2 and degraded Sentinel-2 images, original GF-2 and degraded GF-2 images, histogram-matched GF-2 and degraded GF-2 images, and registered original GF-2 and Sentinel-2 images. The results indicate that the samples acquired by the histogram-matched GF-2 and degraded GF-2 images can resolve spectral band mismatches when simulating training samples from fine spatial resolution imagery, while the other three methods have limitations in their inability to fully address spectral and spatial mismatches. The histogram-matched method yielded the best image quality with PSNR, SSIM, and QNR values of 42.2813, 0.9778, and 0.9872, respectively, and produced the best mapping results, achieving an overall accuracy of 0.9306. By assessing the impact of training samples on image spatial super-resolution reconstruction and classification, this study addresses data limitations and contributes to improving the accuracy of cropland mapping, which is crucial for agricultural management and decision-making.

Abstract BackgroundSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that was first identified in mainland China in 2009 and has been reported in Zhejiang Province, China, since 2011. However, few studies have focused on the association between ticks, host animals, and SFTS. ObjectiveIn this study, we analyzed the influence of meteorological and environmental factors as well as the influence of ticks and host animals on SFTS. This can serve as a foundational basis for the development of strategic policies aimed at the prevention and control of SFTS. MethodsData on SFTS incidence, tick density, cattle density, and meteorological and environmental factors were collected and analyzed using a maximum entropy–based model. ResultsAs of December 2019, 463 laboratory-confirmed SFTS cases were reported in Zhejiang Province. We found that the density of ticks, precipitation in the wettest month, average temperature, elevation, and the normalized difference vegetation index were significantly associated with SFTS spatial distribution. The niche model fitted accurately with good performance in predicting the potential risk areas of SFTS (the average test area under the receiver operating characteristic curve for the replicate runs was 0.803 and the SD was 0.013). The risk of SFTS occurrence increased with an increase in tick density, and the response curve indicated that the risk was greater than 0.5 when tick density exceeded 1.4. The risk of SFTS occurrence decreased with increased precipitation in the wettest month, and the risk was less than 0.5 when precipitation exceeded 224.4 mm. The relationship between elevation and SFTS occurrence showed a reverse V shape, and the risk peaked at approximately 400 m. ConclusionsTick density, precipitation, and elevation were dominant influencing factors for SFTS, and comprehensive intervention measures should be adjusted according to these factors to reduce SFTS incidence in Zhejiang Province.

Background: Chikungunya is emerging and reemerging word-widely in the past decades. It is non-endemic in Zhejiang Province, Southeast China. Aedes albopictus, one of major vectors of chikungunya, is widely-distribution in Zhejiang, and autochthonous transmission is possible after introducing chikungunya virus. Methods: Retrospectively collected the epidemiological, clinical and genetic data of chikungunya and conducted the descriptive analysis and gene sequence analysis. Results: From 2008 to 2022, 29 chikungunya cases, including 26 overseas imported and 3 local cases, were reported and no cases died of chikungunya. More than half of the imported cases (53.85%) were from Southeast Asia. Seasonal peak of the imported cases was noted between August and September, and 42.31% cases onset in those 2 months. Eight prefecture-level cities and 16 counties reported cases during the study period, with Jinghua (27.59%) and Hangzhou (24.14%) reporting the largest number of cases. The 3 local cases were all reported in Qujiang, Quzhou in 2017. For imported cases, the male-female gender ratio was 2.71:1, 20–30 years old cases (46.15%) and commercial service (42.31%) accounted for the highest proportion. Clinically, fever (100%), fatigue (94.44%), arthralgia (79.17%), headache (71.43%) and erythra (65.22%) were the most common reported symptoms. Eight whole-genome sequences were obtained and belonged to East/Central/South African (ECSA) or Asian genotype. Conclusions: With the change of immigration policy, the surveillance of chikungunya should be strengthened and the ability of the case discovery and diagnosis should be improved in Zhejiang in the post-COVID-19 era.

Objective: To estimate the potential causal impact of Enterovirus A71 (EV71) vaccination program on the reduction of EV71-infected hand, foot, and mouth disease (HFMD) in Zhejiang Province. Methods: We utilized the longitudinal surveillance dataset of HFMD and EV71 vaccination in Zhejiang Province during 2010–2019. We estimated vaccine efficacy using a Bayesian structured time series (BSTS) model, and employed a negative control outcome (NCO) model to detect unmeasured confounding and reveal potential causal association. Results: We estimated that 20,132 EV71 cases (95% CI: 16,733, 23,532) were prevented by vaccination program during 2017–2019, corresponding to a reduction of 29% (95% CI: 24%, 34%). The effectiveness of vaccination increased annually, with reductions of 11% (95% CI: 6%, 16%) in 2017 and 66% (95% CI: 61%, 71%) in 2019. Children under 5 years old obtained greater benefits compared to those over 5 years. Cities with higher vaccination coverage experienced a sharper EV71 reduction compared to those with lower coverage. The NCO model detected no confounding factors in the association between vaccination and EV71 cases reduction. Conclusions: This study suggested a potential causal effect of the EV71 vaccination, highlighting the importance of achieving higher vaccine coverage to control the HFMD.

Objective: To investigate the effect of Enterovirus A71 (EV71) vaccination on the transmissibility of different enterovirus serotypes of hand, foot, and mouth disease (HFMD) in Zhejiang, China. Methods: Daily surveillance data of HFMD and EV71 vaccination from August 2016 to December 2019 were collected. Epidemic periods for each HFMD type were defined, and the time-varying effective reproduction number (Rt) was estimated, which could provide more direct evidence of disease epidemics than case number. General additive models (GAMs) were employed to analyze associations between EV71 vaccination quantity and rate and HFMD transmissibility. The epidemic prevention threshold, represented by required vaccination numbers and rates, was also estimated. Results: Vaccinating every 100,000 children ≤ 5 years could lead to a decrease in the Rt of EV71-associated HFMD by 14.44% (95%CI: 6.76%, 21.42%). Additionally, a positive correlation was observed between vaccinations among children ≤ 5 years old (per 100,000) and the increased transmissibility of other HFMD types (caused by enteroviruses other than EV71 and CA16) at 1.82% (95%CI: 0.80%, 2.84%). It was estimated that an additional 362,381 vaccinations, corresponding to increased vaccine coverage to 54.51% among children ≤ 5 years could effectively prevent EV71 epidemics in Zhejiang. Conclusions: Our findings highlight the importance of enhancing EV71 vaccine coverage for controlling the epidemic of EV71-HFMD and assisting government officials in developing strategies to prevent HFMD.

Intrinsic and extrinsic aging affect the health of human skin. Extracellular matrix protein degradation, DNA damage and oxidative stress are known to disturb skin architecture and skin homeostasis leading to skin aging. Traditional Chinese Medicine (TCM) delivers a large amount of knowledge regarding the phytotherapeutic power of diverse plants. Panax ginseng, Polygonatum cyrtonema, Epiphyllum oxypetalum, Nelumbo nucifera and Osmanthus fragrans are five plants used in TCM for their protective effect. In this study, several combinations of these TCM plants were explored: first, an in silico analysis was performed to predict their potential to target biological activities in the skin and then, some predictions were verified with in vitro studies to underline the synergistic effect of plant extracts. The results showed a stronger anti-aging activity for the combination with the five plants compared to the combination with Panax ginseng, Polygonatum cyrtonema, Epiphyllum oxypetalum and, compared to Panax ginseng alone.

An oscillating flow past a structure represents a complex, high-dimensional, and nonlinear flow phenomenon, which can lead to the failure of structures due to material fatigue or constraint relaxation. In order to better understand flow-induced vibration (FIV) and coupled flow fields, a numerical simulation of a two-degrees-of-freedom FIV in a cylinder was conducted. Based on the Lagrangian-based dynamic mode decomposition (L-DMD) method, the vorticity field and motion characteristics of a cylinder were decomposed, reconstructed, and predicted. A comparison was made to the traditional Eulerian-based dynamic mode decomposition (E-DMD) method. The research results show that the first-order mode in the stable phase represents the mean flow field, showcasing the slander tail vortex structure during the vortex-shedding period and the average displacement in the in-line direction. The second mode predominantly captures the crossflow displacement, with a frequency of approximately 0.43 Hz, closely matching the corresponding frequency observed in the CFD results. The higher dominant modes mainly capture outward-spreading, smaller-scale vortex structures with detail displacement characteristics. The motion of the cylinder in the in-line direction was accompanied by symmetric vortex structures, while the motion of the cylinder in the crossflow direction was associated with anti-symmetric vortex structures. Additionally, crossflow displacement will cause a symmetrical vortex structure that spreads laterally along the axis behind the cylinder. Finally, when compared with E-DMD, the L-DMD method demonstrates a notable advantage in analyzing the nonlinear characteristics of FIV.

Baroreflex is critical to maintain blood pressure homeostasis, and the quantification of baroreflex regulation function (BRF) can provide guidance for disease diagnosis, treatment, and healthcare. Current quantification of BRF such as baroreflex sensitivity cannot represent BRF systematically. From the perspective of complex systems, we regard that BRF is the emergence result of fluctuate states and interactions in physiological mechanisms. Therefore, the three-layer emergence is studied in this work, which is from physiological mechanisms to physiological indexes and then to BRF. On this basis, since the entropy in statistical physics macroscopically measures the fluctuations of system’s states, in this work, the principle of maximum entropy is adopted, and a new index called PhysioEnt is proposed to quantify the fluctuations of four physiological indexes, i.e., baroreflex sensitivity, heart rate, heart rate variability, and systolic blood pressure, which aims to represent BRF in the resting condition. Further, two datasets with different subjects are analyzed, and some new findings can be obtained, such as the contributions of the physiological interactions among organs/tissues. With measurable indexes, the proposed method is expected to support individualized medicine.

Intervertebral disc (IVD) herniation is a major cause of chronic low back pain and disability. The current nucleus pulposus (NP) discectomy effectively relieves pain symptoms, but the annulus fibrosus (AF) defects are left unrepaired. Tissue engineering approaches show promise in treating AF injury and IVD degeneration; however, the presence of an inflammatory milieu at the injury site hinders the mitochondrial energy metabolism of AF cells, resulting in a lack of AF regeneration. In this study, we fabricated a dynamic self-healing hydrogel loaded with melatonin (an endocrine hormone well-known for its antioxidant and anti-inflammatory properties) and investigate whether melatonin-loaded hydrogel could promote AF defect repair by rescuing the matrix synthesis and energy metabolism of AF cells. The protective effects of melatonin on matrix components (e.g. type I and II collagen and aggrecan) in AF cells were observed in the presence of interleukin (IL)-1β. Additionally, melatonin was found to activate the nuclear factor erythroid 2-related factor signaling pathway, thereby safeguarding the mitochondrial function of AF cells from IL-1β, as evidenced by the increased level of adenosine triphosphate, mitochondrial membrane potential, and respiratory chain factor expression. The incorporation of melatonin into a self-healing hydrogel based on thiolated gelatin and β-cyclodextrin was proposed as a means of promoting AF regeneration. The successful implantation of melatonin-loaded hydrogel has been shown to facilitate in situ regeneration of AF tissue, thereby impeding IVD degeneration by preserving the hydration of nucleus pulposus in a rat box-cut IVD defect model. These findings offer compelling evidence that the development of a melatonin-loaded dynamic self-healing hydrogel can promote the mitochondrial functions of AF cells and represents a promising strategy for IVD regeneration.

BackgroundDiabetic retinopathy (DR) is a leading cause of vision loss worldwide. Recent studies highlighted the crucial impact of circadian rhythms (CR) on normal retinopathy in response to the external light cues. However, the role of circadian rhythms in DR pathogenesis and potential investigational drugs remains unclear.MethodsTo investigate the weather CR affects DR, differential expression analysis was employed to identify differentially expressed genes (DEGs) from the GEO database (GSE160306). Functional enrichment analysis was conducted to identify relevant signaling pathways. LASSO regression was utilized to screen pivotal genes. Weighted gene co-expression network anlaysis (WGCNA) was applied to identify different modules. Additionally, we use the Comparative Toxicogenomics Database (CTD) database to search key genes related to drugs or molecular compounds. The diabetic mouse model received three consecutive intraperitoneal injections of streptozotocin (STZ) during 3 successive days.ResultsWe initially identified six key genes associated with circadian rhythm in DR, including COL6A3, IGFBP2, IGHG4, KLHDC7A, RPL26P30, and MYL6P4. Compared to normal tissue, the expression levels of COL6A3 and IGFB2 were significantly increased in DR model. Furthermore, we identified several signaling pathways, including death domain binding, insulin-like growth factor I binding, and proteasome binding. We also observed that COL6A3 was positively correlated with macrophages (cor=0.628296895, p=9.96E-08) and Th17 cells (cor=0.665120835, p=9.14E-09), while IGFBP2 showed a negatively correlated with Tgd (cor=-0.459953045, p=0.000247284) and Th2 cells (cor=-0.442269719, p=0.000452875). Finally, we identified four drugs associated with key genes: Resveratrol, Vitamin E, Streptozocin, and Sulindac.ConclusionOur findings revealed several key genes related to circadian rhythms and several relevant drugs in DR, providing a novel insight into the mechanism of DR and potential implications for future DR treatment. This study contributes to a better understanding of CR in DR and its implications for future therapeutic interventions.

This study introduced whole-exome sequencing (WES) in prenatal diagnosis of fetal bowel dilatation to improve the detection outcome when karyotype analysis and copy number variation sequencing (CNV-seq) were uninformative in detecting pathogenic variants. The work reviewed 28 cases diagnosed with fetal bowel dilatation and analyzed the results of karyotype analysis, CNV-seq, and WES. Among the 28 cases, the detection rate in cases with low risk of aneuploidy was 11.54% (3/26), which is lower than 100% (2/2) in cases with high risk of aneuploidy. Ten low-risk aneuploidy cases with isolated fetal bowel dilatation had normal genetic testing results, while the remaining 16 cases with other ultrasound abnormalities were detected for genetic variants at a rate of 18.75% (3/16). The detection rate of gene variation was 3.85% (1/26) by CNV-seq and 7.69% (2/26) by WES. This study suggested that WES could reveal more genetic risk in prenatal diagnosis of fetal bowel dilatation and has value in prenatal diagnosis to reduce birth defects.

Abstract Background Nasopharyngeal carcinoma (NPC), especially the nonkeratinizing type, is a malignant tumor primarily occurring in southern China and Southeast Asia. Chemotherapy (CT) and combined radiotherapy (RT) is used to treat NPC. However, the mortality rate is high in recurrent and metastatic NPC. We developed a molecular marker, analyzed its correlation with clinical characteristics, and assessed the prognostic value among NPC patients with or without chemoradiotherapy. Methods A total of 157 NPC patients were included in this study, with 120 undergoing treatment and 37 without treatment. EBER1/2 expression was investigated using in situ hybridization (ISH). Expression of PABPC1, Ki-67, and p53 was detected with immunohistochemistry. The correlations of EBER1/2 and the expression of the three proteins having clinical features and prognosis were evaluated. Results The expression of PABPC1 was associated with age, recurrence, and treatment but not with gender, TNM classification, or the expression of Ki-67, p53, or EBER. High expression of PABPC1 was associated with poor overall survival (OS) and disease-free survival (DFS) and was an independent predictor depending on multivariate analysis. Comparatively, no significant correlation was observed between the expression of p53, Ki-67, and EBER and survival. In this study, 120 patients received treatments and revealed significantly better OS and DFS than the untreated 37 patients. PABPC1 high expression was an independent predictor of shorter OS in the treated (HR = 4.012 (1.238–13.522), 95% CI, p = 0.021) and the untreated groups (HR = 5.473 (1.051–28.508), 95% CI, p = 0.044). However, it was not an independent predictor of shorter DFS in either the treated or the untreated groups. No significant survival difference was observed between patients with docetaxel-based induction chemotherapy (IC) + concurrent chemoradiotherapy (CCRT) and those with paclitaxel-based IC + CCRT. However, when combined with treatment and PABPC1 expression, patients with paclitaxel-added chemoradiotherapy plus PABPC1 low expression had significantly better OS than those who underwent chemoradiotherapy (p = 0.036). Conclusions High expression of PABPC1 is associated with poorer OS and DFS among NPC patients. Patients with PABPC1 having low expression revealed good survival irrespective of the treatment received, indicating that PABPC1 could be a potential biomarker for triaging NPC patients.

Non-intrusive load monitoring (NILM) technology is only based on the current and voltage information of the main entrance of home power supply to obtain the electrical information of indoor electrical equipment. Improving the accuracy of load identification is of great significance to optimize the energy structure, improve the efficiency of power utilization and reduce energy consumption. Firstly, the normalized current signal is decomposed by using variational mode decomposition (VMD), and then the correlation coefficients between each component and the original current signal are calculated. The two components with the largest correlation coefficients are selected as the load characteristics and input into the trained LSTM neural network for identification. The test results of an example show that the recognition rate of this method is up to 99% on public data set PLAID and 96.6% on laboratory data set, which proves the effectiveness of this method.

Freshwater aquaculture in Jianghan Plain plays a key role in the whole industry of China. It was expanding rapidly to meet the fast-growing demand of consumption in these decades. The spatial distribution change of aquaculture in Jianghan Plain has attracted many researchers in recent years and it is worth further investigating. However, the accuracy and the quality of inland aquaculture classification and mapping still have space to be improved. Our study attempts to use Sentinel-1 and Sentinel-2 data to classify aquaculture areas, nonaquaculture water, and nonwater areas. We applied image segmentation and pixel-based feature computation to obtain candidate datasets. Recursive feature elimination (RFE) was used to find the optimal datasets which were then imported into a modified UNet for classification. This workflow was then applied to the annual datasets for better observation of the spatial change of aquaculture areas. In total, 12 indices and features were found most influential and preserved after RFE. The overall classification accuracy reached 96.83%, while the precision and recall of aquaculture areas reached 84.47% and 90.48%, respectively. The combination of object-based and pixel-based image analysis showed its advantage in inland aquaculture classification compared to other studies. Integrated rice–crawfish farming was found a key factor motivating the rapid development of aquaculture. Policies about the fishing ban and ecosystem restoration were also found deeply affecting the spatial change of aquaculture in Jianghan Plain.

Super-resolution mapping (SRM) can effectively predict the spatial distribution of land cover classes within mixed pixels at a higher spatial resolution than the original remotely sensed imagery. The uncertainty of land cover fraction errors within mixed pixels is one of the most important factors affecting SRM accuracy. Studies have shown that SRM methods using deep learning techniques have significantly improved land cover mapping accuracy but have not coped well with spectral–spatial errors. This study proposes an end-to-end SRM model using a spectral–spatial generative adversarial network (SGS) with the direct input of multispectral remotely sensed imagery, which deals with spectral–spatial error. The proposed SGS comprises the following three parts: first, cube-based convolution for spectral unmixing is adopted to generate land cover fraction images. Second, a residual-in-residual dense block fully and jointly considers spectral and spatial information and reduces spectral errors. Third, a relativistic average GAN is designed as a backbone to further improve the super-resolution performance and reduce spectral–spatial errors. SGS was tested in one synthetic and two realistic experiments with multi/hyperspectral remotely sensed imagery as the input, comparing the results with those of hard classification and several classic SRM methods. The results showed that SGS performed well at reducing land cover fraction errors, reconstructing spatial details, removing unpleasant and unrealistic land cover artifacts, and eliminating false recognition.

ObjectiveAedes-borne arboviral diseases were important public health problems in Zhejiang before the coronavirus disease 2019 (COVID-19) pandemic. This study was conducted to investigate the characteristics and change of the epidemiology of Aedes-borne arboviral diseases in the province.MethodsDescriptive analyses were conducted to summarize the epidemiology of Aedes-borne arboviral diseases during 2003–2022.ResultsA total of 3,125 cases, including 1,968 indigenous cases, were reported during 2003–2022. Approximately three-quarters of imported cases were infected from Southeast Asia. The number of annual imported cases increased during 2013–2019 (R2 = 0.801, p = 0.004) and peaked in 2019. When compared with 2003–2012, all prefecture-level cities witnessed an increase in the annual mean incidence of imported cases in 2013–2019 (0.11–0.42 per 100,000 population vs. 0–0.05 per 100,000 population) but a drastic decrease during 2020–2022 (0–0.03 per 100,000 population). The change in geographical distribution was similar, with 33/91 counties during 2003–2012, 86/91 during 2013–2019, and 14/91 during 2020–2022. The annual mean incidence of indigenous cases in 2013–2019 was 7.79 times that in 2003–2012 (0.44 vs. 0.06 per 100,000 population). No indigenous cases were reported between 2020–2022. Geographical extension of indigenous cases was also noted before 2020—from two counties during 2003–2012 to 44 during 2013–2019.ConclusionDengue, chikungunya fever, zika disease, and yellow fever are not endemic in Zhejiang but will be important public health problems for the province in the post-COVID-19 era.

Fibrosis is a common pathological process that must take place for multiple chronic liver diseases to develop into cirrhosis and liver cancer. Liver fibrosis (LF) is regulated by various cytokines and signaling pathways in its occurrence and development. Ferroptosis is an important mode of cell death caused by iron-dependent oxidative damage and is regulated by iron metabolism and lipid peroxidation signaling pathways. In recent years, numerous studies have shown that ferroptosis is closely related to LF. As the main material secreted by the extracellular matrix, hepatic stellate cells (HSCs) are a general concern in the development of LF. Therefore, targeting HSC ferroptosis against LF is crucial. This review describes the current status of treating LF by inducing HSC ferroptosis that would aid studies in better understanding the current knowledge on ferroptosis in HSCs and the future research direction in this field.

Southern China, one of the traditional rice production bases, has experienced significant declines in the area of rice paddy since the beginning of this century. Monitoring the rice cropping area is becoming an urgent need for food security policy decisions. One of the main challenges for mapping rice in this area is the quantity of cloud-free observations that are vulnerable to frequent cloud cover. Another relevant issue that needs to be addressed is determining how to select the appropriate classifier for mapping paddy rice based on the cloud-masked observations. Therefore, this study was organized to quickly find a strategy for rice mapping by evaluating cloud-mask algorithms and machine-learning methods for Sentinel-2 imagery. Specifically, we compared four GEE-embedded cloud-mask algorithms (QA60, S2cloudless, CloudScore, and CDI (Cloud Displacement Index)) and analyzed the appropriateness of widely accepted machine-learning classifiers (random forest, support vector machine, classification and regression tree, gradient tree boost) for cloud-masked imagery. The S2cloudless algorithm had a clear edge over the other three algorithms based on its overall accuracy in evaluation and visual inspection. The findings showed that the algorithm with a combination of S2cloudless and random forest showed the best performance when comparing mapping results with field survey data, referenced rice maps, and statistical yearbooks. In general, the research highlighted the potential of using Sentinel-2 imagery to map paddy rice with multiple combinations of cloud-mask algorithms and machine-learning methods in a cloud-prone area, which has the potential to broaden our rice mapping strategies.

Land salinization considerably limits crop production. Biological improvement of saline and alkaline land is an important way to achieve efficient land use. It is crucial to study the salt tolerance of halophyte resources in order to explore and improve plant resources through biological improvement. Glaux maritima is a mesophyte halophyte with strong salt tolerance. In this study, we conducted research on the salt tolerance mechanism of G. maritima through phenotypic, physiological, and transcriptomic aspects. The results indicate that leaf cross-sections revealed that G. maritima has a salt gland tissue composed of stalk, collecting, and secretory cells, which are trapped in epidermal cells. At the physiological level, the maximum salt tolerance threshold of G. maritima leaves was 600 mM/L. At this concentration, proline content, relative conductivity, and superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) enzyme activities were maximum. At the transcriptional level, transcriptome data of three experimental groups (N0: 0 mM/L, N3: 600 mM/L, and N4: 800 mM/L) were analyzed, and six essential genes related to proline synthesis and five essential genes related to SOD and CAT enzyme activities were identified. Two genes involved in CAT enzyme activity were also found to play an important role in the MAPK signaling pathway. Trend analysis revealed that the MAPK signaling regulation (37 differentially expressed genes (DEGs)), phytohormone regulation (48 DEGs), glutathione metabolism (8 DEGs), flavonoid and flavonoid biosynthesis (2DEGs), and flavonoid biosynthesis (24 DEGs) pathways played important roles in regulating the salt tolerance of G. maritima. These findings provide valuable information for further studies on the functional characteristics of G. maritima in response to abiotic stress and may contribute to salt resistance breeding of fodder crops for cultivation in saline alkali land.

Abstract Background Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area. Methods Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS. Results The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 ℃, weekly highest temperature at 18 ℃relative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09–1.82), 1.32 (95% CI: 1.05–1.66), 2.18 (95% CI: 1.16–4.07), and 1.91 (95% CI: 1.16–2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation. Conclusion Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.

In order to improve the efficiency of the traction system, this paper researches the PWM control strategy of high-frequency SiC traction inverter system from multiple dimensions such as inverter switching frequency optimization, modulation strategy selection and motor control algorithm adaptation. A multi-mode PWM control method for SiC traction inverter is proposed in this paper. At low and medium speeds which below 30% rated speed, the high-frequency characteristics of SiC are fully utilized and the rated switching frequency of the inverter is optimized based on the principle of system loss optimization. During high speeds above 30% rated speed, the current harmonics are optimized modulated to achieve motor current harmonic suppression, while the motor voltage utilization rate can reach 97%. In addition, a new closed loop control method for multimodal stator flux trajectories of traction motors is proposed in order to adapt to the new PWM control method. The proposed PWM control method is compared with the traditional low-frequency PWM control method. Experimental results show that using the proposed algorithm, the total harmonic distortion (THD) of the motor current can be reduced by a maximum of 9.31%, the overall loss of the traction system can be reduced by a maximum of 10.2%, the temperature rise of the motor can be reduced by a maximum of 31 K, and the maximum noise suppression of the motor can reach 10 dB. Effectiveness of the proposed PWM modulation method is demonstrated.

Hemorrhagic fever with renal syndrome (HFRS) is caused by hantaviruses (HVs) and is endemic in Zhejiang Province, China. In this study, we aimed to explore the changing epidemiology of HFRS cases and the dynamics of hantavirus hosts in Zhejiang Province. Joinpoint regression was used to analyze long-term trends in the incidence of HFRS. The comparison of animal density at different stages was conducted using the Mann–Whitney Test. A comparison of HV carriage rates between stages and species was performed using the chi-square test. The incidence of HFRS shows a continuous downward trend. Cases are widely distributed in all counties of Zhejiang Province except Shengsi County. There was a high incidence belt from west to east, with low incidence in the south and north. The HFRS epidemic showed two seasonal peaks in Zhejiang Province, which were winter and summer. It showed a marked increase in the age of the incidence population. A total of 23,073 minibeasts from 21 species were captured. Positive results were detected in the lung tissues of 14 rodent species and 1 shrew species. A total of 80% of the positive results were from striped field mice and brown rats. No difference in HV carriage rates between striped field mice and brown rats was observed (χ2 = 0.258, p = 0.611).

Solar energy, as an environmentally sustainable power source, is gaining increasing popularity worldwide, driving a surge in the number of solar photovoltaic (PV) plants. China, which has a prominent role in this domain, requires continuous updates to its PV plant data for spatiotemporal analyses. However, there remains an absence of a comprehensive and timely dataset of PV plants across China, leaving PV installation dates and other crucial attributes for comprehensive analyses underexplored. This study leverages Sentinel-2 data as a primary source to propose an optimized deep learning approach for PV plant extraction in China. Statistical analyses of PV plant attributes, including its installation date, size, site slope, and site land cover, were implemented from multiple data sources. Comprehensive analyses were conducted to unravel their spatiotemporal development patterns in the 21st century. The results indicate that as of 2023, China boasts 4347 PV plants, collectively spanning 4146 km ^2 , which are predominantly concentrated in Northwest and North China. 2016 and 2017 marked substantial growth in China’s PV plants, while other years exhibited stability. These plants exhibit the distinct spatial characteristics of installing smaller PV plants on flat terrain covered by vegetation or barren land. Over time, a notable trend in the installation of China’s PV plants has been the increasing preference for establishing larger ones in smooth terrain, with a focus on preventing damage to natural resources. The results reveal China’s optimization of PV plant site selection and construction strategies, aligning with global environmental goals and sustainable energy practices.

Abstract Background The global pandemic of coronavirus disease 2019 (COVID-19) has attracted great public health efforts across the world. Few studies, however, have described the potential impact of these measures on other important infectious diseases. Methods The incidence of 19 major infectious diseases in Zhejiang Province was collected from the National Notifiable Infectious Disease Surveillance System from January 2017 to October 2020. The entire epidemic control phase was divided into three stages. The government deployed the first level response from 24 January to 2 March (the most rigorous measures). When the outbreak of COVID-19 was under control, the response level changed to the second level from 3 to 23 March, and then the third level response was implemented after 24 March. We compared the epidemiological characteristics of 19 major infectious diseases during different periods of the COVID-19 epidemic and previous years. Results A total of 1,814,881 cases of 19 infectious diseases were reported in Zhejiang from January 2017 to October 2020, resulting in an incidence rate of 8088.30 cases per 1,000,000 person-years. After the non-pharmaceutical intervention, the incidence of 19 infectious diseases dropped by 70.84%, from 9436.32 cases per 1,000,000 person-years to 2751.51 cases per 1,000,000 person-years, with the large decrease in the first response period of influenza. However, we observed that the daily incidence of severe fever with thrombocytopenia syndrome (SFTS) and leptospirosis increased slightly (from 1.11 cases per 1,000,000 person-years to 1.82 cases per 1,000,000 person-years for SFTS and 0.30 cases per 1,000,000 person-years to 1.24 cases per 1,000,000 person-years for leptospirosis). There was no significant difference in the distribution of epidemiological characteristic of most infectious diseases before and during the implementation of COVID-19 control measures. Conclusion Our study summarizes the epidemiological characteristics of 19 infectious diseases and indicates that the rigorous control measures for COVID-19 are also effective for majority of infectious diseases.

BackgroundHemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in China. The geographic distribution has went throughout China, among which Zhejiang Province is an important epidemic area. Since 1963, more than 110,000 cases have been reported.MethodsWe collected the meteorological factors and socioeconomic indicators of Zhejiang Province, and constructed the HFRS ecological niche model of Zhejiang Province based on the algorithm of maximum entropy.ResultsModel AUC from 2009 to 2018, is 0.806–0.901. The high incidence of epidemics in Zhejiang Province is mainly concentrated in the eastern, western and central regions of Zhejiang Province. The contribution of digital elevation model ranged from 2009 to 2018 from 4.22 to 26.0%. The contribution of average temperature ranges from 6.26 to 19.65%, Gross Domestic Product contribution from 7.53 to 21.25%, and average land surface temperature contribution with the highest being 16.73% in 2011. In addition, the average contribution of DMSP/OLS, 20-8 precipitation and 8-20 precipitation were all in the range of 9%. All-day precipitation increases with the increase of rainfall, and the effect curve peaks at 1,250 mm, then decreases rapidly, and a small peak appears again at 1,500 mm. Average temperature response curve shows an inverted v-shape, where the incidence peaks at 17.8°C. The response curve of HFRS for GDP and DMSP/OLS shows a positive correlation.ConclusionThe incidence of HFRS in Zhejiang Province peaked in areas where the average temperature was 17.8°C, which reminds that in the areas where temperature is suitable, personal protection should be taken when going out as to avoid contact with rodents. The impact of GDP and DMSP/OLS on HFRS is positively correlated. Most cities have good medical conditions, but we should consider whether there are under-diagnosed cases in economically underdeveloped areas.

ABSTRACT Malaria poses public health threats worldwide. Nigeria accounted for the highest numbers of cases (26.8%) and deaths (31.9%) among countries where malaria is endemic in 2020. Currently, monitoring molecular markers in imported malaria cases provides an efficient means to screen for emerging drug resistance in countries where malaria is endemic, particularly in those where field surveillance is challenging. Here, we investigated 165 Plasmodium falciparum infections imported from Nigeria to Zhejiang Province, China, between 2016 and 2020. Multiple molecular markers in k13, Pfcrt, Pfmdr1, Pfdhfr, and Pfdhps were detected. The prevalences and patterns of mutations were analyzed. Polymorphism of k13 was limited to 5 of 156 (3.21%) isolates. The wild-type CVMNK allele of Pfcrt became predominant (65.36%) compared with the triple mutation CVIET. A low frequency (4.73%) of double mutations (N86Y and Y184F) in Pfmdr1 was observed. The dominant haplotypes of Pfdhfr and Pfdhps were IRNDI (92.41%) and ISGKAA (36.84%), respectively. The newly discovered mutant I431V was identified in 21.71% of isolates. A “fully resistant” combination of Pfdhfr-Pfdhps, IRN-GE, was found in eight (5.67%) samples, which was hardly seen in Nigeria. The current study demonstrated a high frequency of wild-type Pfcrt. Limited polymorphism of Pfmdr1 but a high prevalence of Pfdhfr and Pfdhps mutations was illustrated. Our data so far serve as comprehensive surveillance of molecular markers of the k13, Pfcrt, Pfmdr1, Pfdhfr, and Pfdhps genes. Based on our findings, it has become crucial to evaluate the impact of the emerging fully resistant type of Pfdhfr-Pfdhps as well as its combination with I431V on the efficacy of sulfadoxine-pyrimethamine (SP) in Nigeria. IMPORTANCE Monitoring the current resistance to antimalarial drugs is critical to enable timely action to prevent its spread and limit its impact. The high prevalence of wild-type Pfcrt found in our study is an optimistic signal to reevaluate chloroquine (CQ) sensitivity in Nigeria, which is cost-effective and once played a crucial role in the fight against malaria. Based on the continued emergence of fully resistant Pfdhfr-Pfdhps alleles illustrated in the current investigation, actions are needed in Nigeria, such as national systemic surveillance to monitor their updated epidemiology as well as assessments of their influence on SP efficacy to minimize any public health impact. These findings urge a response to the threat of drug resistance to facilitate appropriate drug policies in the study area.

This study aimed to clarify the role of Orosomucoid 1 (ORM1) in the development and therapy resistance in hepatocellular carcinoma (HCC). The mRNA expression level of ORM1 was analyzed via integrative analysis of Gene Express Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. The protein expression level of ORM1 in our cohort was determined using immunohistochemistry. Correlation analysis was used to investigate the relationship between ORM1 expression and clinical parameters. The Cell Counting Kit-8 assay was used to clarify the role of ORM1 in HCC malignant behaviors, including cell growth and sorafenib sensitivity, in vitro. The results indicated that ORM1 was significantly downregulated in the hepatic cancer cells compared to that in the non-cancerous cells. However, it was upregulated in microvascular invasion samples, especially in the cancer embolus compared to that in the surrounding tumor cells. Though Kaplan-Meier analysis did not show an association of ORM1 expression with the overall survival rates of HCC patients, univariate analysis indicated that ORM1 expression was highly correlated with tumor grade and stage. An in vitro assay also revealed that downregulation of ORM1 led to the suppression of tumor growth and enhancement of sorafenib sensitivity without epithelial-to-mesenchymal transition (EMT) alteration, which was consistent with our bioinformatic analysis. Hence, ORM1 played a key role in HCC tumorigenesis and may serve as a potential target for the development of therapeutics against HCC in the future.

Topography and soil factors are known to play crucial roles in the species composition of plant communities in subtropical evergreen-deciduous broadleaved mixed forests. In this study, we used a systematic quantitative approach to classify plant community types in the subtropical forests of Hubei Province (central China), and then quantified the relative contribution of drivers responsible for variation in species composition and diversity. We classified the subtropical forests in the study area into 12 community types. Of these, species diversity indices of three communities were significantly higher than those of others. In each community type, species richness, abundance, basal area and importance values of evergreen and deciduous species were different. In most community types, deciduous species richness was higher than that of evergreen species. Linear regression analysis showed that the dominant factors that affect species composition in each community type are elevation, slope, aspect, soil nitrogen content, and soil phosphorus content. Furthermore, structural equation modeling analysis showed that the majority of variance in species composition of plant communities can be explained by elevation, aspect, soil water content, litterfall, total nitrogen, and total phosphorus. Thus, the major factors that affect evergreen and deciduous species distribution across the 12 community types in subtropical evergreen-deciduous broadleaved mixed forests include elevation, slope and aspect, soil total nitrogen content, soil total phosphorus content, soil available nitrogen content and soil available phosphorus content.

The maximum light use efficiency (LUE) (ε0) is a key essential parameter of the LUE model, and its accurate estimation is crucial for quantifying gross primary production (GPP) and better understanding the global carbon budget. Currently, a comprehensive understanding of the potential of seasonal variations of ε0 in GPP estimation across different plant functional types (PFTs) is still lacking. In this study, we used a phenology-based strategy for the estimation of ε0 to find the optimal photosynthetic responses of the parameter in different phenological stages. The start and end of growing season (SOS and EOS) from time series vegetation indices and the camera-derived greenness index were extracted across seven PFT flux sites using the methods of the hybrid generalized additive model (HGAM) and double logistic function (DLF). Optimal extractions of SOS and EOS were evaluated, and the ε0 was estimated from flux site observations during the optimal phenological stages with the light response equation. Coupled with other obligatory parameters of the LUE model, phenology-based GPP (GPPphe-based) was estimated over 21 site-years and compared with vegetation photosynthesis model (VPM)-based GPP (GPPVPM) and eddy covariance-measured GPP (GPPEC). Generally, GPPphe-based basically tracked both the seasonal dynamics and inter-annual variation of GPPEC well, especially at forest, cropland, and wetland flux sites. The R2 between GPPphe-based and GPPEC was stable between 0.85 and 0.95 in forest ecosystems, between 0.75 and 0.85 in cropland ecosystems, and around 0.9 in wetland ecosystems. Furthermore, we found that GPPphe-based was significantly improved compared to GPPVPM in cropland, grassland, and wetland ecosystems, implying that phenology-based ε0 is more appropriate in the GPP estimation of herbaceous plants. In addition, we found that GPPphe-based was significantly improved over GPPVPM in cropland, grassland, and wetland ecosystems, and the R2 between GPPphe-based and GPPEC was improved by up to 0.11 in cropland ecosystems and 0.05 in wetland ecosystems compared to GPPVPM, and RMSE was reduced by up to 5.90 and 2.11 g C m−2 8 day−1, respectively, implying that phenology-based ε0 in herbaceous plants is more appropriate for GPP estimation. This work highlights the potential of phenology-based ε0 in understanding the seasonal variation of vegetation photosynthesis and production.

Dengue imposes a heavy economic burden on families and society. We used surveillance data reported in 2019 to characterize the dengue epidemic in Zhejiang Province, China, which provided guidance for dengue prevention and control. Dengue epidemics mostly occurred in July to October. People aged 30–44 years, males, and commercial service workers were more likely to suffer from dengue. The epidemic areas were mainly in Hangzhou and Wenzhou. Meanwhile, we assessed the economic cost of dengue in the province from both family and organizational perspectives. The direct economic burden of dengue patients was estimated to be USD 405,038.25, and the indirect economic burden was USD 140,364.90, for a total economic burden of USD 543,213.00. The direct economic burden of dengue patients should be reduced by increasing the coverage and reimbursement of health insurance. Additionally, the total annual cost of dengue prevention and control for the government and organizational sectors was estimated to be USD 7075,654.83. Quantifying the dengue burden is critical for developing disease control strategies, allocating public health resources, and setting health policy priorities.

Abstract Since the outbreak of COVID-19 in December 2019 in Wuhan, Zhejiang has become the province with the largest number of cases. The aim of this article is to present Zhejiang province’s experience of establishing an accurate and smart control mechanism for epidemic prevention and control and resumption of work and production using a ‘five-colour epidemic chart’. The number of confirmed cases, proportion of local cases, and occurrence of clustered outbreaks were used as evaluation indicators to calculate the county-level epidemic risk and were assigned different weight coefficients; the absence of cases for 3 and 7 consecutive days was used as the adjustment index. When the first chart was published on February 9, there were 1 very-high-risk, 12 high-risk, and 12 low-risk counties. Under the five-colour chart, Zhejiang began to adopt precise measures to prevent and control the epidemic and resume work and production. By February 24, the low-risk counties had expanded to 82, with no high-risk and very-high-risk counties. The epidemic situation in Zhejiang province has been effectively controlled. The experience of epidemic prevention and control in Zhejiang is worthy to be emulated and learned by other countries and regions.

Abstract This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understanding the extent of the prevalence of modern slavery and exploitative labour. This analysis represents the first of its kind in estimating the spatiotemporal patterns in the Bull’s Trench Kilns across the Brick Belt, as well as its connections with various UN Sustainable Development Goals (SDGs). With a principal focus on Sustainable Development Goal Target 8.7 regarding the effective measures to end modern slavery by 2030, the article provides additional evidence on the intersections that exist between SDG 8.7 and those relating to urbanisation (SDG 11, 12), environmental degradation and pollution (SDG 3, 14, 15), and climate change (SDG 13). Our findings are then used to make a series of pragmatic suggestions for mitigating the most extreme SDG risks associated with brick production in ways that can improve human lives and human freedom.

Micro ribonucleic acids (miRNAs), as a category of post-transcriptional gene inhibitors, have a wide range of biological functions, are involved in many pathological processes, and are attractive therapeutic targets. Considerable evidence in ophthalmology indicates that miRNAs play an important role in diabetic retinopathy (DR), especially in inflammation, oxidative stress, and neurodegeneration. Targeting specific miRNAs for the treatment of DR has attracted much attention. This is a review focusing on the pathophysiological roles of miRNAs in DR, diabetic macular edema, and proliferative DR complex multifactorial retinal diseases, with particular emphasis on how miRNAs regulate complex molecular pathways and underlying pathomechanisms. Moreover, the future development potential and application limitations of therapy that targets specific miRNAs for DR are discussed.

Monitoring the spatio-temporal dynamic changes of reservoir surface water area (RSWA) values is crucial when investigating global water resource reserves. Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed imagery has been extensively used for this purpose, but the coarse spatial resolution limits the accuracy when monitoring the small water area variations of reservoirs. In this paper, we introduce a novel approach for the monitoring of RSWA variation by integrating MODIS and Landsat imagery to overcome this problem. In the proposed method, the sub-pixel water fraction information in the MODIS images is explored based on the C/M ratio model, where C/M represents the ratio between the reflectance of a land pixel and that of a water pixel. By using the series of RSWA values extracted from Landsat images as the reference, the C/M values extracted from MODIS images are used to construct regression functions with the overall RSWA for each MODIS pixel. An RSWA time series is then predicted from the extracted daily C/M values with the use of the regression functions constructed in the study. In a case study of Dale Hollow Reservoir in the United States, the performance of the proposed method was assessed, and the resulting Pearson's correlation coefficient between the predicted RSWA and water level (WL) reached 0.88, which was higher than that of the conventional pixel analysis based method and the spectral unmixing based sub-pixel analysis method, confirming the effectiveness of the proposed method.

Objectives: Avian influenza virus A(H7N9) remains a threat to humans and has great potential to cause a pandemic in the foreseeable future. Antiviral treatment with neuraminidase inhibitors has been recommended to treat patients with H7N9 infection as early as possible, although evidence-based research on their effectiveness for H7N9 infection is lacking. Methods: Data from all laboratory-confirmed cases of H7N9 infection in Zhejiang Province between 2013 and 2017 were retrieved, and time-dependent survival models were used to evaluate the effectiveness of treatment with neuraminidase inhibitors to reduce the risk of mortality. Results: The final optimal model found no significant association (odds ratio 1.29, 95% confidence interval 0.78–2.15) between time to treatment with neuraminidase inhibitors and survival after controlling for age and white blood cell count. Sensitivity analyses with multiple imputation for missing data concurred with the primary analysis. Conclusions: No association was found between treatment with neuraminidase inhibitors and survival in patients with H7N9 infection using various adjusted models and sensitivity analyses of missing data imputations.

Super-resolution mapping (SRM) is an effective technology to solve the problem of mixed pixels because it can be used to generate fine-resolution land cover maps from coarse-resolution remote sensing images. Current methods based on deep neural networks have been successfully applied to SRM, as they can learn complex spatial patterns from training data. However, they lack the ability to learn structural information between adjacent land cover classes, which is vital in the reconstruction of spatial distribution. In this article, an SRM method based on graph convolutional networks (GCNs), named ${\rm{SR}}{{\rm{M}}_{{\rm{GCN}}}}$, is proposed to improve SRM results by capturing structure information on the graph. In ${\rm{SR}}{{\rm{M}}_{{\rm{GCN}}}}$, a supervised inductive learning strategy with mini-graphs as input is considered, which is an extension of the GCN framework. Furthermore, two operations are designed in terms of adjacency matrix construction and an information propagation rule to help reconstruct detailed information of geographical objects. Experiments on three datasets with different spatial resolutions demonstrate the qualitative and quantitative superiority of ${\rm{SR}}{{\rm{M}}_{{\rm{GCN}}}}$ over three other popular SRM methods.

Abstract Background To investigate the clinical efficacy and safety of bone cement combined with radiofrequency ablation (RFA) in the treatment of spinal metastases. Methods The medical records of patients with spinal metastatic tumor admitted to our hospital from January 2016 to December 2018 were retrospectively analyzed. Based on different surgical methods, the patients were divided into groups A (treated with RFA combined with bone cement) and B (treated with bone cement only). Group A included 35 patients with 47 segments of diseased vertebral bodies. Group B consisted of 52 patients with 78 vertebral segments. Pain, quality of life score, vertebra height, bone cement leakage, postoperative tumor recurrence, and complications were assessed 3 days and 1 and 6 months after surgery. Results All the patients had smooth operation without paraplegia, spinal cord injury, and perioperative death. Visual analogue scales (VAS) and Oswestry Disability Index (ODI) scores of the two groups significantly improved 3 days and 1 month after surgery compared with those before surgery (P 0.05). Six months after surgery, the VAS and ODI scores of patients in group A were lower than those in group B, with statistically significant differences (P 0.05). Postoperative bone cement permeability in group A was 6.4%, and postoperative tumor recurrence rate was 11.4%. The permeability of bone cement in group B was 20.5%, and the tumor recurrence rate was 30.8%. The bone cement permeability and tumor recurrence rate in group A were lower than those in group B, with statistically significant differences (P

Objective To analyze the sensitivity and specificity of neuroelectrophysiological monitoring and warning criterion in the spinal cord cavernous malformations surgery. Methods A total of 64 patients with spinal cord cavernous malformation underwent surgical treatment were collected from November 2012 to March 2016. All patients underwent intraoperative monitoring of motor⁃evoked potential (MEP) and somatosensory ⁃ evoked potential (SEP). Multimodal monitoring combined MEP amplitude decreased ≥ 80% with SEP was performed to predict the postoperative neurological function defect of patients. McCormick grade as "gold standard" was used to calculate sensitivity, specificity, positive predictive value and negative predictive value. Results The sensitivity, specificity, positive predictive value and negative predictive value were 75% (15/20), 78.57% (33/42), 62.50% (15/24) and 86.84% (33/38), respectively. Conclusions Intraoperative MEP combined with SEP monitoring can effectively predict the occurrence of new neurological deficits after operation. MEP amplitude reduction ≥ 80% can be used as the operation warning criterion. DOI:10.3969/j.issn.1672⁃6731.2020.11.007

Abstract Background Occlusive atherosclerotic disease of the anterior cerebral circulation is one of the most common causes of anterior circulation ischemia and stroke. Treatment options include medical therapies (including antiplatelet use, blood pressure control, lipid reduction, and lifestyle modification) and extracranial-intracranial bypass surgery (such as superficial temporal artery-middle cerebral artery bypass). However, the optimal treatment remains unclear. The objective of this study will be to compare the efficacy of and extracranial-intracranial bypass surgery with that of other medical therapy in adult patients with occlusive atherosclerotic disease of the anterior cerebral circulation. Methods This is the study protocol for a systematic review. We will search MEDLINE, EMBASE, Web of Science, and the Cochrane Library (from January 1980 onwards). We will include randomized controlled trials, quasi-experimental studies (non-randomized, interrupted time series), and observational studies (e.g., cohort studies and case-control studies), examining the efficacy of extracranial-intracranial bypass surgery compared to other treatments for adult patients with occlusive atherosclerotic disease of anterior cerebral circulation. Two team members will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The primary outcome will include stroke or death. The secondary outcomes will include intracranial hemorrhage, transient ischemic attack, and myocardial infarction. The study methodological quality (or bias) will be appraised using appropriate tools. If feasible, we will conduct random effects meta-analysis. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g., study design, geographical location, or risk of bias). Discussion This review will evaluate the evidence on the efficacy of extracranial-intracranial bypass surgery for adult patients with occlusive atherosclerotic disease of the anterior cerebral circulation. We anticipate that our findings will be of interest to patients, their families, caregivers, healthcare professionals, and in making optimal treatment selection. Implications for future clinical and epidemiological research will be discussed. Systematic review registration PROSPERO CRD42018105513

BackgroundHand-foot-mouth disease (HFMD) is caused by a group of enteroviruses (EVs) and has a high incidence in children; some subtypes had high mortalities in children. The subtypes of HFMD had a different incidence across seasons. Thereby, we suspect that the infection of HFMD is varied by meteorological factors. However, studies examining serotype-specific associations between meteorological factors and HFMD incidence were rare.MethodsWe obtained all HFMD cases that occurred from 1 January 2010 to 31 December 2018 in Zhejiang province from the China Information System for Disease Control and Prevention (CISDCP). Daily meteorological data for Zhejiang province were provided by the China Methodological Data Sharing Service System and linked to HFMD cases based on residential addresses and dates of onset. The associations between meteorological factors and HFMDs were examined using distributed lag non-linear models (DLNMs) for each serotype.ResultsOverall, the incidences of all HFMD cases were increasing in study years, while the number of severe and fatality cases were decreasing. The dominant serotypes varied by study year. The association between temperature and incidence of both CVA16 and EV71 serotypes showed an inverted U shape. The risk ratio for CVA16 was increasing when temperature is 11–25°C, reaching the maximum RR at 18°C and humidity above 77% can promote the occurrence with CVA16, and temperature between 11 and 32°C with the maximum RR at 21°C and relative humidity above 77% are risk conditions of the occurrence of HFMD associated with EV71. For other enteroviruses causing HFMD, temperature above 11°C and humidity above 76% have a risk effect. CVA16, EV71, and all enteroviruses of HFMD have a maximum effect on lag day 0, and temperature is 35, 34, and 33°C respectively, while the enteroviruses of HFMD other than EV71 and CVA16 has a maximum effect when the temperature is 33°C and the lag time is 7 days.ConclusionThis study shows that meteorological factors have an effect on the occurrence of different HFMD serotypes. Local control strategies for public health should be taken in time to prevent and reduce the risk of HFMD while the weather is getting warmer and wetter.