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Abstract Prostate cancer (PCa), with high heterogeneity and poor prognosis, is one of the most common malignant tumors in men. Circular RNAs (circRNAs) have been identified in tumor progression and resistance to medication in numerous studies. However, the role of circ_0001047 in PCa is unclear. In this research, we found that circ_0001047 had low expression in PCa cells and tissues and was negatively correlated with testosterone secretion in vivo. Overexpression of circ_0001047 inhibited the proliferation, migration, invasion, and anti-apoptotic abilities of human PCa cells in vitro. Mechanistically, circ_0001047 promoted the expression of FKBP5 through sponge adsorption of miR-122-5p and then inhibited the proliferation, anti-apoptotic migration, and invasion abilities of PCa cells. In addition, overexpression of circ_0001047 enhanced the sensitivity of PCa cells to abiraterone by inhibiting AKT phosphorylation activation through upregulation of FKBP5/PHLPP1. This study revealed a novel mechanism by which circ_0001047 regulates PCa progression and treatment sensitivity via the miR-122-5p/FKBP5/PHLPP1/AKT axis. These findings deepen our comprehension of the molecular mechanisms in latent PCa progression and treatment resistance. Graphical Abstract

Abstract In March 2023, our pediatric intensive care unit (PICU) retrospectively examined six cases of pediatric necrotizing tracheobronchitis (NTB), focusing on co-infections with influenza A virus (IAV) and Staphylococcus aureus (S. aureus). This study aimed to elucidate NTB’s clinical characteristics, diagnostics, and therapeutic approaches. Diagnostics included symptom assessment, microbiological testing that confirmed all patients were positive for IAV H1N1 with a predominant S. aureus co-infection, and bronchoscopy. The patients predominantly exhibited fever, cough, and dyspnea. Laboratory analysis revealed decreased lymphocyte counts and elevated infection markers like C-reactive protein and procalcitonin. Chest computed tomography (CT) scans detected tracheobronchial obstructions in half of the cases, while bronchoscopy showed severe mucosal congestion, edema, necrosis, and purulent-hemorrhagic exudates. Treatments encompassed comprehensive strategies like oxygen therapy, intubation, bronchoscopic interventions, thoracentesis, oseltamivir, and a regimen of antibiotics. Our findings suggested potential correlations between clinical markers, notably lymphocyte count and procalcitonin, and clinical interventions such as the number of rescues and intensive care unit (ICU) duration. This research highlights the importance of early detection and the role of bronchoscopy and specific markers in assessing NTB, advocating for continued research in larger cohorts to better understand its clinical trajectory and refine treatment approaches for this challenging pediatric disease.

Abstract. Over the past decade, mitochondrial dysfunction has been investigated as a key contributor to acute and chronic kidney disease. However, the precise molecular mechanisms linking mitochondrial damage to kidney disease remain elusive. The recent insights into the cyclic guanosine monophosphate-adenosine monophosphate (GMP-AMP) synthetase (cGAS)-stimulator of interferon gene (STING) signaling pathway have revealed its involvement in many renal diseases. One of these findings is that mitochondrial DNA (mtDNA) induces inflammatory responses via the cGAS-STING pathway. Herein, we provide an overview of the mechanisms underlying mtDNA release following mitochondrial damage, focusing specifically on the association between mtDNA release-activated cGAS-STING signaling and the development of kidney diseases. Furthermore, we summarize the latest findings of cGAS-STING signaling pathway in cell, with a particular emphasis on its downstream signaling related to kidney diseases. This review intends to enhance our understanding of the intricate relationship among the cGAS-STING pathway, kidney diseases, and mitochondrial dysfunction.

Urbanization in China has led to land-use changes resulting in landscape fragmentation, natural habitats loss and ecological connectivity decline. Aiming to support sustainable landscape planning, we proposed an integrated method for ecological structure assessment and optimization including morphological spatial pattern analysis (MSPA), minimal cumulative resistance (MCR) model and circuit theory to assess landscape fragmentation and ecological connectivity change at regional scale. A modified connectivity index is also proposed by employing the index of relative quality of ecological patches and corridors. We applied the combined methods to Jiangsu province in eastern China for multi-temporal landscape analysis and optimization. The results showed that the combined analysis revealed both fragmentation trend of ecological patches and ecological connectivity reduction with regard to all the species as a whole in the study area from 2000 to 2018. While, the trend has been slowed down to a certain extent lately, which is related to a series of ecological protection policies implemented in the study area, including ecological redlines policy, national park construction and returning marginal farmland into forest or grassland. Furthermore, suggestions for improving the ecological network in the study area were proposed. We proposed to improve the ecological network by fostering twenty-five potential ecological sources, maintaining twenty-five pinch points, restoring eleven dredging corridors and planning fifty-three stepping stones. Overall, we argue that the combined method can reveal both structural connectivity and functional connectivity, and the time series analysis can provide dynamics situation for better understanding and planning landscape process. It can also provide planners with a valuable strategic tool that advances the practical utility of landscape ecology techniques for spatial planning, and the combined application of the method helps to reduce some of the limitations of each individual method.

Objective: To evaluate the protective effect of Yiqi Qingre Xiaozheng formula (YQQRXZF) via the regulation of autophagy in diabetic nephropathy (DN) mice induced by injection of streptozotocin (STZ) after high fat diet (HFD). Methods: The composition of YQQRXZF was analyzed by high performance liquid chromatography-electrospray ionization/mass spectrometry (HPLC-ESI/MSn). The DN model was induced by intraperitoneally injection of 50 mg/kg STZ within 5 days, followed by HFD feeding for 8 weeks in C57BL/6J mice. Mice were randomly separated into DN group, YQQRXZF group, irbesartan group, and control group. Blood glucose was calculated, and body weight was measured every 2 weeks. An enzyme-linked immunosorbent assay was used to measure the urinary albumin-to-creatinine ratio (uACR) before and after treatment, and the serum concentrations of total cholesterol (TC), low-density lipoprotein (LDL), triglycerides (TG), high-density lipoprotein (HDL), blood urea nitrogen (BUN), and serum creatinine (Scr) were measured. In addition, hematoxylin-eosin (H&E) staining, periodic acid-Schiff (PAS) staining, Masson's trichrome staining, and transmission electron microscopy (TEM) were used to observe pathological changes in renal tissue. Autophagy levels were determined by immunofluorescence staining. Results: In this study, 21 dominant chemical constituents were identified in YQQRXZF. The treatment group reduced uACR in a more significant way than the DN group (P = .018). The treatment group reduced TC, TG, and LDL concentrations after YQQRXFF treatment (P = .021, P = .014 and P = .026, respectively). H&E, PAS, and Masson staining showed that pathological damage to mice kidneys improved, the volume of renal glomeruli was reduced, and glomerular sclerosis and fibrosis were reduced. Immunofluorescence analysis revealed that expressions of LC3-Ⅱprotein increased in the treatment group (P = .013). In contrast, the protein expressions of P62 were reduced after treatment (P = .025). Conclusion: YQQRXZF effectively attenuates kidney injury in DN mice, probably by regulating autophagy.

Diabetic kidney disease (DKD) stands as the predominant cause of chronic kidney disease (CKD) on a global scale, with its incidence witnessing a consistent annual rise, thereby imposing a substantial burden on public health. The pathogenesis of DKD is primarily rooted in metabolic disorders and inflammation. Recent years have seen a surge in studies highlighting the regulatory impact of energy metabolism on innate immunity, forging a significant area of research interest. Within this context, fibroblast growth factor 21 (FGF21), recognized as an energy metabolism regulator, assumes a pivotal role. Beyond its role in maintaining glucose and lipid metabolism homeostasis, FGF21 exerts regulatory influence on innate immunity, concurrently inhibiting inflammation and fibrosis. Serving as a nexus between energy metabolism and innate immunity, FGF21 has evolved into a therapeutic target for diabetes, nonalcoholic steatohepatitis, and cardiovascular diseases. While the relationship between FGF21 and DKD has garnered increased attention in recent studies, a comprehensive exploration of this association has yet to be systematically addressed. This paper seeks to fill this gap by summarizing the mechanisms through which FGF21 operates in DKD, encompassing facets of energy metabolism and innate immunity. Additionally, we aim to assess the diagnostic and prognostic value of FGF21 in DKD and explore its potential role as a treatment modality for the condition.

The CCT gene family is present in plants and is involved in biological processes such as flowering, circadian rhythm regulation, plant growth and development, and stress resistance. We identified 87, 62, 46, and 40 CCTs at the whole-genome level in B. napus, B. rapa, B. oleracea, and A. thaliana, respectively. The CCTs can be classified into five groups based on evolutionary relationships, and each of these groups can be further subdivided into three subfamilies (COL, CMF, and PRR) based on function. Our analysis of chromosome localization, gene structure, collinearity, cis-acting elements, and expression patterns in B. napus revealed that the distribution of the 87 BnaCCTs on the chromosomes of B. napus was uneven. Analysis of gene structure and conserved motifs revealed that, with the exception of a few genes that may have lost structural domains, the majority of genes within the same group exhibited similar structures and conserved domains. The gene collinearity analysis identified 72 orthologous genes, indicating gene duplication and expansion during the evolution of BnaCCTs. Analysis of cis-acting elements identified several elements related to abiotic and biotic stress, plant hormone response, and plant growth and development in the promoter regions of BnaCCTs. Expression pattern and protein interaction network analysis showed that BnaCCTs are differentially expressed in various tissues and under stress conditions. The PRR subfamily genes have the highest number of interacting proteins, indicating their significant role in the growth, development, and response to abiotic stress of B. napus.

Abstract The search for high‐performance resistive random‐access memory (RRAM) devices is essential to pave the way for highly efficient non‐Von Neumann computing architecture. Here, it is reported on an alloying approach using atomic layer deposition for a Zn‐doped HfOx‐based resistive random‐access memory (HfZnO RRAM), with improved performance. As compared with HfOx RRAM, the HfZnO RRAM exhibits reduced switching voltages (>20%) and switching energy (>3×), as well as better uniformity both in voltages and resistance states. Furthermore, the HfZnO RRAM exhibits stable retention exceeding 10 years, as well as write/erase endurance exceeding 105 cycles. In addition, excellent linearity and repeatability of conductance tuning can be achieved using the constant voltage pulse scheme, achieving ≈90% accuracy in a simulated multi‐layer perceptron network for the recognition of modified national institute of standards and technology database handwriting. The HfZnO RRAM is also characterized down to the temperature of 4 K, showing functionality and the elucidation of its carrier conduction mechanism. Hence, a potential pathway for doped‐RRAM to be used in a wide range of temperatures including quantum computing and deep‐space exploration is shown.

Lobular capillary hemangioma (LCH), previously known as pyogenic granuloma, is a benign vascular lesion commonly found within the oral and nasal cavities. However, it is rarely encountered within the trachea, especially in pediatric patients, where it manifests as hemoptysis, cough, and wheeze, and is frequently misdiagnosed as bronchitis or asthma. There is limited literature on the presentation, behavior, and management of tracheal LCH. Herein, we describe a rare case of tracheal LCH in an 11-year-old boy with a history of hemoptysis, which was successfully managed with arterial embolization followed by electrocautery loop snaring via flexible bronchoscopy. No complications occurred during and after the procedure. A review of the relevant literature is also provided. Our case is unique, given the therapeutic strategy utilized for pediatric tracheal LCH, and reminds physicians to be aware of tracheal LCH in the differential diagnosis for hemoptysis.

Reconciling carbon emissions and GDP development is a challenge for most Chinese cities in the sustainable development process. Taking the Yangtze River Delta of China as an example, this study calculated carbon-emission inventories for five typical years and assigned anthropogenic carbon emissions to land-use types. A multi-objective particle swarm algorithm was used to consider three functions of land-use allocation: maximizing GDP, minimizing carbon emissions, and maximizing suitability. Thereafter, the technique for order of preference by similarity to ideal solution (TOPSIS) method was combined to find the optimal solution for carbon emission and economic development trade-offs. It is observed that Jiangsu has the largest carbon emissions in the Yangtze River Delta region; energy consumption is the main source of the carbon emissions, and industrial land is the most carbon intensive region. The land-use allocation obtained by multi-objective optimization with the TOPSIS evaluation method increases GDP and reduces carbon emissions, which is worthy of reference for land planners. Land use optimization from the perspective of balancing carbon emissions and economic development can provide a useful reference for the rational use of land resources and socio-economic sustainable development.

Abstract Background IgA nephropathy is the most common glomerular disease and is a common cause of progression to end-stage renal disease in patients with kidney diseases. Proteinuria levels are critical for the prognosis of patients with IgA nephropathy, but many patients are still unable to effectively control their proteinuria levels after receiving RAAS blockers. Antimalarial drugs have shown good efficacy in the treatment of kidney disease in previous studies; however, there have been no strictly designed randomized controlled trials to confirm the clinical efficacy of artesunate for treating IgA nephropathy patients. Therefore, we designed this clinical trial to compare the effect of artesunate versus placebo in patients with IgA nephropathy. Methods This study is a randomized, double-blind, three-group-parallel, placebo-controlled clinical trial. One hundred and twenty eligible IgA nephropathy patients at risk of progression will be randomly divided into the artesunate 100-mg group, artesunate 50-mg group, and placebo group. Changes in proteinuria and renal function will be measured 6 months after the intervention. The levels of Gd-IgA1 and anti-Gd-IgA1 in the patient’s blood will also be tested to explore the possible immune mechanisms. Discussion Clinical evidence supporting artesunate treatment of IgA nephropathy is currently lacking, and we expect that the results of this trial will provide high-quality clinical evidence for artesunate as a treatment option for IgA nephropathy in the future. Trial registration Chinese Clinical Trial Registry ChiCTR2000038104 . Registered on 10 September 2020

Wildfires spread rapidly and cause considerable ecological and socioeconomic losses. Inner Mongolia is among the regions in China that suffer the most from wildfires. A simple, effective model that uses fewer parameters to simulate wildfire spread is crucial for rapid decision-making. This study presents a region-specific technological process that requires a few meteorological parameters and limited grassland vegetation data to predict fire spreading dynamics in Inner Mongolia, based on cellular automata that emphasize the numeric evaluation of both heat sinks and sources. The proposed method considers a case that occurred in 2021 near the East Ujimqin Banner border between China and Mongolia. Three hypothetical grassland wildfires were developed using GIS technology to test and demonstrate the proposed model. The simulation results suggest that the model agrees well with real-world experience and can facilitate real-time decision-making to enhance the effectiveness of firefighting, fire control, and simulation-based training for firefighters.

Objective: To explore the role of endothelial biomarkers in predicting damp-heat syndrome in diabetic kidney disease (DKD). Methods: A total of 183 patients with DKD were divided into 3 groups: the early DKD group, established DKD group, and advanced DKD group. All patients were classified according to traditional Chinese medicine (TCM) syndrome type, and clinical indexes were collected for statistical analysis. Results: A total of 183 DKD patients were included in this study. Fibroblast growth factor 23 (FGF23), chitinase-3-like protein 1 (CHI3L1), endocan, tumor necrosis factor receptor 1 (TNFR1), secretory leukocyte protease inhibitor (SLPI), and vascular endothelial growth factor A (VEGF-A) were increased in advanced DKD. FGF23, CHI3L1, endocan, SLPI, and TNFR1 showed a negative correlation with estimated glomerular filtration rate (eGFR), while they had a positive correlation with 24 h urine protein. After adjusting for age, gender, diabetes duration, body mass index (BMI), hemoglobin, glucose, uric acid, 24 h urine protein, cholesterol, triglyceride, low-density lipoprotein, and hemoglobin A1c (HbA1c), the multiple regression analysis showed that FGF23, endocan, TNFR1, and SLPI significantly correlated with eGFR. Conclusions: FGF23, endocan, TNFR1, and SLPI are elevated in advanced DKD compared with early stage, and they may take part in the pathogenesis and progression of DKD. Our study provides useful biomarkers for predicting the appearance of damp-heat syndrome, including FGF23, endocan, TNFR1, and SLPI.

Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis. We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups. Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts. Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes’ expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy. In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy.

With rapid urbanization, urban functional zones have become important for rational government and resource allocation. Points of interest (POIs), as informative and open-access data, have been widely used in studies of urban functions. However, most existing studies have failed to address unevenly or sparsely distributed POIs. In addition, the spatial adjacency of analysis units has been ignored. Therefore, we propose a new method for identifying urban functional zones based on POI density and marginalized graph autoencoder (MGAE). First, kernel density analysis was utilized to obtain the POI density and spread the effects of POIs to the surroundings, which enhanced the data from unevenly or sparsely distributed POIs considering the barrier effects of main roads and rivers. Second, MGAE performed feature extraction in view of the spatial adjacency to integrate features from the POIs of the surrounding units. Finally, the k-means algorithm was used to cluster units into zones, and semantic recognition was applied to identify the function category of each zone. A case study of Changzhou indicates that this method achieved an overall accuracy of 90.33% with a kappa coefficient of 0.88, which constitutes considerable improvement over that of conventional methods and can improve the performance of urban function identification.

Objective The aim of this study was to investigate the role of prophylactic use of statin in venous thromboembolism (VTE) in patients with primary membranous nephropathy (PMN). Methods A total of 734 patients with PMN were consecutively enrolled in this retrospective study. 564 patients had received statins prescription, while 170 patients did not. Kaplan–Meier methods were used for cumulative incidence plots of thromboembolic events and Cox proportional hazards regression models were used to assess risk factors. Finally, the effects of different potency of statins were evaluated. Results In the cohort, 37 patients (5.0%) experienced VTE. In a univariate Cox proportional hazard model, the hazard ratio (HR) for VTE in statin users versus statin non-users was 0.5 (95% CI 0.3–0.8, p = .03). Multivariable model proportional-hazards analysis corrected for co-medications and risk factors revealed that adjusted HR was 0.4 (95% CI 0.1–0.7, p = .03). According to the type and dose, statin users were assigned into 3 groups: high-intensity group (n = 278), moderate-intensity group (n = 186), and low-intensity group (n = 49). In comparison, incidences of VTEs in the three groups were similar (2.9% vs 4.8% vs 2.0%, p = .45). Conclusions The prophylactic use of statins could effectively decrease the occurrence of VTE in patients with PMN, and the benefits have no difference in different potency of statins.

Background: The aim of this study was to estimate the attributable risk for all-cause mortality in hypertensive adults living in Beijing, China. Methods: We conducted a prospective cohort study on the basis of the disease risk prediction model, which included 3006 hypertensive patients aged 50 and over who participated in the annual health examination from thirty-eight community health centers were randomly selected from all 53 community health centers in Dongcheng district of Beijing in China. This cohort study was conducted from January 1, 2013 to June 31, 2018 in these community health centers. Data included age, gender, education level, BMI, smoking and drinking status, renal function, diabetes mellitus (DM), coronary heart disease, levels of blood pressure, use of medications, and blood lipid levels. Results: the follow-up time was 4.90 ± 0.51 years. There were significant survival differences by gender, renal function (eGFR > 90 vs. 60–90 vs. 12 years), coronary heart disease (CHD) (CHD vs. NO CHD). In the multivariate Cox proportional hazard analysis, the prognostic factors of all-cause mortality in hypertensive patients were male [HR 1.662, 95% CI 1.110–2.489, p = 0.014], educational level

Objective: The aim of this study is to investigate the role of prophylactic anticoagulation regimens based on low molecular weight heparin (LMWH) or aspirin in thromboembolic events in patients with primary membranous nephropathy (PMN). Methods: A total of 717 patients with PMN were consecutively enrolled in this retrospective study. The propensity score matching method was utilized to adjust for the selection bias inherent in an analysis of outcomes, which was stratified by the anticoagulation prophylaxis regimen. Results: According to the anticoagulation prophylaxis regimen, patients were assigned into three groups: only LMWH therapy (L + A−, n = 53), only aspirin therapy (L − A+, n = 97), and no therapy of LMWH or aspirin (L − A−, n = 567). After performing 1:1 match, 37 patients were selected in the L + A − group and the L − A− group, respectively, and 94 patients were selected in the L − A+ group and the L − A− group, respectively. It showed that the prophylactic use of LMWH had no protective effects on arterial thromboembolic events (ATEs) (10.8% vs. 21.6%, p = .21) or venous thromboembolic events (VTEs) (8.1% vs. 10.8%, p = .69). The incidence of VTEs in the L − A+ group was lower than the L − A− group (2.1% vs. 10.6%, p = .02), while there were no significant differences in the incidences of ATEs between the L − A+ group and the L − A− group (5.3% vs. 7.4%, p = .55). Conclusions: The prophylactic use of LMWH showed no benefits on the incidence of ATEs or VTEs in patients with PMN. Aspirin effectively decreased the incidence of VTEs, without effects on the occurrence of ATEs.

Background: The mortality prediction scores were widely used in pediatric intensive care units. However, their performances were unclear in Chinese patients and there were also no reports based on large sample sizes in China. This study aims to evaluate the performances of three existing severity assessment scores in predicting PICU mortality and to identify important determinants.Methods: This prospective observational cohort study was carried out in eight multidisciplinary, tertiary-care PICUs of teaching hospitals in China. All eligible patients admitted to the PICUs between Aug 1, 2016, and Jul 31, 2017, were consecutively enrolled, among whom 3,957 were included for analysis. We calculated PCIS, PRISM IV, and PELOD-2 scores based on patient data collected in the first 24 h after PICU admission. The in-hospital mortality was defined as all-cause death within 3 months after admission. The discrimination of mortality was assessed using the area under the receiver-operating characteristics curve (AUC) and calibrated using the Hosmer–Lemeshow goodness-of-fit test.Results: A total of 4,770 eligible patients were recruited (median age 18.2 months, overall mortality rate 4.7%, median length of PICU stay 6 days), and 3,957 participants were included in the analysis. The AUC (95% confidence intervals, CI) were 0.74 (0.71–0.78), 0.76 (0.73–0.80), and 0.80 (0.77–0.83) for PCIS, PRISM IV, and PELOD-2, respectively. The Hosmer–Lemeshow test gave a chi-square of 3.16 for PCIS, 2.16 for PRISM IV and 4.81 for PELOD-2 (p ≥ 0.19). Cox regression identified five predictors from the items of scores better associated with higher death risk, with a C-index of 0.83 (95%CI 0.79–0.86), including higher platelet (HR = 1.85, 95% CI 1.59–2.16), invasive ventilation (HR = 1.40, 1.26–1.55), pupillary light reflex (HR = 1.31, 95% CI 1.22–1.42) scores, lower pH (HR 0.89, 0.84–0.94), and extreme PaO2 (HR 2.60, 95% CI 1.61–4.19 for the 1st quantile vs. 4th quantile) scores.Conclusions: Performances of the three scores in predicting PICU mortality are comparable, and five predictors were identified with better prediction to PICU mortality in Chinese patients.

Automatic Identification System (AIS) data have been widely used in many fields, such as collision detection, navigation, and maritime traffic management. Similarity analysis is an important process for most AIS trajectory analysis topics. However, most traditional AIS trajectory similarity analysis methods calculate the distance between trajectory points, which requires complex and time-consuming calculations, often leading to substantial errors when processing AIS trajectory data characterized by substantial differences in length or uneven trajectory points. Therefore, we propose a cell-based similarity analysis method that combines the weight of the direction and k-neighborhood (WDN-SIM). This method quantifies the similarity between trajectories based on the degree of proximity and differences in motion direction. In terms of its effectiveness and efficiency, WDN-SIM outperformed seven traditional methods for trajectory similarity analysis. Particularly, WDN-SIM has a high robustness to noise and can distinguish the similarities between trajectories under complex situations, such as when there are opposing directions of motion, large differences in length, and uneven point distributions.

Pulmonary hypertension (PH) is a vascular disease, and proinflammatory factors are strongly implicated in its pathogenesis, causing right ventricular (RV) hypertrophy and heart failure. Baicalin exhibits potent anti‐inflammation activity. This study aimed to investigate the curative effects of baicalin in an infant rodent model of PH and to further explore the underlying mechanisms. A PH model in infant rats was induced by hypoxia and the resulting rats were administered baicalin in incremental dosages. Invasive hemodynamic methods were used to measure mean pulmonary arterial pressure (mPAP) and RV end‐diastolic pressure (RVEDP). RV hypertrophy was assessed by mass pathology and histology. ELISAs were used to determine concentrations of high‐mobility group box 1 (HMGB1), secretory receptor for advanced glycation end products (sRAGE), interleukin 6 (IL6) and transforming growth factor β (TGFβ1) in bronchoalveolar lavage fluid (BALF). Electrophoretic mobility shift and phosphorylation in nuclear extracts were used to evaluate the activation of peroxisome proliferator‐activated receptor γ (PPARγ). Western blotting was used to detect the expression levels of heme oxygenase 1 (HO1), HMGB1, RAGE, IL6 and TGFβ1 in lung tissue. Baicalin administration significantly attenuated mPAP, RVEDP and RV hypertrophy in infant rats with PH. HMGB1, sRAGE, IL6 and TGFβ1 levels in BALF were also reduced by baicalin treatment. Baicalin activated PPARγ, which promoted expression of HO1. Furthermore, expression levels of HMGB1, RAGE, IL6 and TGFβ1 in lung tissue were dramatically decreased by baicalin in a dosage‐dependent manner. Baicalin showed curative effects in infant rats with PH. Activation of PPARγ that inhibited HMGB1/RAGE inflammatory signaling was involved.

The monitoring and assessment of land use/land cover (LULC) change over large areas are significantly important in numerous research areas, such as natural resource protection, sustainable development, and climate change. However, accurately extracting LULC only using the spectral features of satellite images is difficult owing to landscape heterogeneities over large areas. To improve the accuracy of LULC classification, numerous studies have introduced other auxiliary features to the classification model. The Google Earth Engine (GEE) not only provides powerful computing capabilities, but also provides a large amount of remote sensing data and various auxiliary datasets. However, the different effects of various auxiliary datasets in the GEE on the improvement of the LULC classification accuracy need to be elucidated along with methods that can optimize combinations of auxiliary datasets for pixel- and object-based classification. Herein, we comprehensively analyze the performance of different auxiliary features in improving the accuracy of pixel- and object-based LULC classification models with medium resolution. We select the Yangtze River Delta in China as the study area and Landsat-8 OLI data as the main dataset. Six types of features, including spectral features, remote sensing multi-indices, topographic features, soil features, distance to the water source, and phenological features, are derived from auxiliary open-source datasets in GEE. We then examine the effect of auxiliary datasets on the improvement of the accuracy of seven pixels-based and seven object-based random forest classification models. The results show that regardless of the types of auxiliary features, the overall accuracy of the classification can be improved. The results further show that the object-based classification achieves higher overall accuracy compared to that obtained by the pixel-based classification. The best overall accuracy from the pixel-based (object-based) classification model is 94.20% (96.01%). The topographic features play the most important role in improving the overall accuracy of classification in the pixel- and object-based models comprising all features. Although a higher accuracy is achieved when the object-based method is used with only spectral data, small objects on the ground cannot be monitored. However, combined with many types of auxiliary features, the object-based method can identify small objects while also achieving greater accuracy. Thus, when applying object-based classification models to mid-resolution remote sensing images, different types of auxiliary features are required. Our research results improve the accuracy of LULC classification in the Yangtze River Delta and further provide a benchmark for other regions with large landscape heterogeneity.

Large-scale geospatial data have accumulated worldwide in the past decades. However, various data formats often result in a geospatial data sharing problem in the geographical information system community. Despite the various methodologies proposed in the past, geospatial data conversion has always served as a fundamental and efficient way of sharing geospatial data. However, these methodologies are beginning to fail as data increase. This study proposes a parallel spatial data conversion engine (PSCE) with a symmetric mechanism to achieve the efficient sharing of massive geodata by utilizing high-performance computing technology. This engine is designed in an extendable and flexible framework and can customize methods of reading and writing particular spatial data formats. A dynamic task scheduling strategy based on the feature computing index is introduced in the framework to improve load balancing and performance. An experiment is performed to validate the engine framework and performance. In this experiment, geospatial data are stored in the vector spatial data defined in the Chinese Geospatial Data Transfer Format Standard in a parallel file system (Lustre Cluster). Results show that the PSCE has a reliable architecture that can quickly cope with massive spatial datasets.

High-precision information regarding the location, time, and type of land use change is integral to understanding global changes. Time series (TS) analysis of remote sensing images is a powerful method for land use change detection. To address the complexity of sample selection and the salt-and-pepper noise of pixels, we propose a bidirectional segmented detection (BSD) method based on object-level, multivariate TS, that detects the type and time of land use change from Landsat images. In the proposed method, based on the multiresolution segmentation of objects, three dimensions of object-level TS are constructed using the median of the following indices: the normalized difference vegetation index (NDVI), the normalized difference built index (NDBI), and the modified normalized difference water index (MNDWI). Then, BSD with forward and backward detection is performed on the segmented objects to identify the types and times of land use change. Experimental results indicate that the proposed BSD method effectively detects the type and time of land use change with an overall accuracy of 90.49% and a Kappa coefficient of 0.86. It was also observed that the median value of a segmented object is more representative than the commonly used mean value. In addition, compared with traditional methods such as LandTrendr, the proposed method is competitive in terms of time efficiency and accuracy. Thus, the BSD method can promote efficient and accurate land use change detection.

A reaction-based two-photon (TP) ratiometric fluorescence probe Z2 has been developed and successfully applied to detect and image fluoride ion in living cells and tissues. The Z2 probe was designed designed to utilize an ICT mechanism between n-butylnaphthalimide as a fluorophore and tert-butyldiphenylsilane (TBDPS) as a response group. Upon addition of fluoride ion, the Si-O bond in the Z2 would be cleaved, and then a stronger electron-donating group was released. The fluorescent changes at 450 and 540 nm, respectively, made it possible to achieve ratiometric fluorescence detection. The results indicated that the Z2 could ratiometrically detect and image fluoride ion in living cells and tissues in a depth of 250 μm by two-photon microscopy (TPM).

As urbanization has profound effects on global environmental changes, quick and accurate monitoring of the dynamic changes in impervious surfaces is of great significance for environmental protection. The increased spatiotemporal resolution of imagery makes it possible to construct time series to obtain long-time-period and high-accuracy information about impervious surface expansion. In this study, a three-step monitoring method based on time series trajectory segmentation was developed to extract impervious surface expansion using Landsat time series and was applied to the Xinbei District, Changzhou, China, from 2005 to 2017. Firstly, the original time series was segmented and fitted to remove the noise caused by clouds, shadows, and interannual differences, leaving only the trend information. Secondly, the time series trajectory features of impervious surface expansion were described using three phases and four types with nine parameters by analyzing the trajectory characteristics. Thirdly, a multi-level classification method was used to determine the scope of impervious surface expansion, and the expansion time was superimposed to obtain a spatiotemporal distribution map. The proposed method yielded an overall accuracy of 90.58% and a Kappa coefficient of 0.90, demonstrating that Landsat time series remote sensing images could be used effectively in this approach to monitor the spatiotemporal expansion of impervious surfaces.

Airborne Light Detection and Ranging (LiDAR) is widely used in digital elevation model (DEM) generation. However, the very large volume of LiDAR datasets brings a great challenge for the traditional serial algorithm. Using parallel computing to accelerate the efficiency of DEM generation from LiDAR points has been a hot topic in parallel geo-computing. Generally, most of the existing parallel algorithms running on high-performance clusters (HPC) were in process-paralleling mode, with a static scheduling strategy. The static strategy would not respond dynamically according to the computation progress, leading to load unbalancing. Additionally, because each process has independent memory space, the cost of dealing with boundary problems increases obviously with the increase in the number of processes. Actually, these two problems can have a significant influence on the efficiency of DEM generation for larger datasets, especially for those of irregular shapes. Thus, to solve these problems, we combined the advantages of process-paralleling with the advantages of thread-paralleling, forming a new idea: using process-paralleling to achieve a flexible schedule and scalable computation, using thread-paralleling inside the process to reduce boundary problems. Therefore, we proposed a hybrid process/thread parallel algorithm for generating DEM from LiDAR points. Firstly, at the process level, we designed a parallel method (PPDB) to accelerate the partitioning of LiDAR points. We also proposed a new dynamic scheduling strategy to achieve better load balancing. Secondly, at the thread level, we designed an asynchronous parallel strategy to hide the cost of LiDAR points’ reading. Lastly, we tested our algorithm with three LiDAR datasets. Experiments showed that our parallel algorithm had no influence on the accuracy of the resultant DEM. At the same time, our algorithm reduced the conversion time from 112,486 s to 2342 s when we used the largest dataset (150 GB). The PPDB was parallelizable and the new dynamic scheduling strategy achieved a better load balancing. Furthermore, the asynchronous parallel strategy reduced the impact of LiDAR points reading. When compared with the traditional process-paralleling algorithm, the hybrid process/thread parallel algorithm improved the conversion efficiency by 30%.

To analyze the clinical effect of extracorporeal membrane oxygenation (ECMO) in children with acute fulminant myocarditis, we retrospectively analyzed the data of five children with acute fulminant myocarditis in the intensive care unit (ICU) at the Affiliated Children's Hospital, Zhejiang University from February 2009 to November 2012. The study group included two boys and three girls ranging in age from 9 to 13 years (median 10 years). Body weight ranged from 25 to 33 kg (mean 29.6 kg). They underwent extracorporeal membrane oxygenation (ECMO) through a venous-arterial ECMO model with an average ECMO supporting time of 89.8 h (40-142 h). Extracorporeal circulation was established in all five children. After treatment with ECMO, the heart rate, blood pressure, and oxygen saturation were greatly improved in the four children who survived. These four children were successfully weaned from ECMO and discharged from hospital machine-free, for a survival rate of 80% (4/5). One child died still dependent on the machine. Cause of death was irrecoverable cardiac function and multiple organ failure. Complications during ECMO included three cases of suture bleeding, one case of acute hemolytic renal failure and suture bleeding, and one case of hyperglycemia. During the follow-up period of 4-50 months, the four surviving children recovered with normal cardiac function and no abnormal functions of other organs. The application of ECMO in acute fulminant myocarditis, even in local centers that experience low incidence of this disease, remains an effective approach. Larger studies to determine optimal timing of placement on ECMO to guide local centers are warranted.

Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI) information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD) always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

Objective: Rare disease. Background: RASopathies involve mutations in genes that encode proteins participating in the RAS-mitogen-activated protein kinase pathway and are a collection of multisystem disorders that clinically overlap. Variants in the SHOC2 gene have been reported in Noonan-like syndrome, which include distinct facial features, short stature, congenital cardiac defects, developmental delays, bleeding disorders, and loose anagen hair. This report is of a 7-yearold girl with the c.4A>G (p.Ser2Gly) variant of the SHOC2 gene, consistent with Noonan-like syndrome, with loose anagen hair, presenting with thrombotic thrombocytopenic purpura and autoimmune hemolytic anemia. Case Report: The child had a medical history of 7 hospitalizations at our institution. At the age of 2 months, she underwent surgical correction for ventricular and atrial septal defects. At the age of 2 years, tonsil and adenoid removal surgery was performed, followed by surgery for otitis media at age 5 years. At 7 years, she was hospitalized for the simultaneous occurrence of thrombotic thrombocytopenic purpura and autoimmune hemolytic anemia. The patient displayed short stature and mild intellectual disability. Notable facial features included sparse hair, mild frontal bossing, and low-set ears. Antinuclear antibody levels demonstrated a significant gradual shift. Through trio whole-exome sequencing, a c.4A>G (p.Ser2Gly) variation in the SHOC2 gene was identified. Conclusions: Given the clinical information and genetic testing results, the patient's condition appeared to closely be a type of RASopathy. This report has highlighted the importance of physical, developmental, and genetic testing in children presenting with dysmorphism, developmental delay, and hematological abnormalities. [ABSTRACT FROM AUTHOR]