Search

Objective The construction of regional integration places higher demands on the integrated development of multi-level rail transit networks in the region. Following the trend of four-network integration, it is crucial to fully consider passenger flow demand and optimize city railway transportation organization oriented by passenger flow demand. Method Starting from the context of four-network integration and the functional positioning of city railway within these networks particularly in Yangtze River Delta region, the connotation of rail transit interoperation is clarified. The current transportation organization challenges faced by city railway are elaborated from three aspects: the total passenger transport capacity demand, the market share of city railway, and the matching of transportation capacity supply and passenger transport demand. Oriented by passenger flow demand, recommendations for optimizing city railway transportation organization are proposed from the three strategic, tactical, and operational levels. Result & Conclusion The three main constraining factors on current city railway transportation organization are identified as the disparity between route planning/construction and passenger transport demand, unclear competitive advantages of city railway compared to other transportation modes, and the lack of train timetable adjustment mechanism and method oriented by passenger flow. From strategic level perspective, strengthening top-level design is proposed to form an integrated transportation organization system. From the tactical level perspective, transforming competition into collaboration and leveraging the network effects of multimodal rail transit are suggested. From the operational level perspective, prioritizing people and implementing diverse train operation organization modes is recommended.

Mesenchymal stem cells (MSCs) can reduce inflammation, restore renal injury and maintain immune homeostasis by paracrine various cytokines and regulating immune cells. In preclinical studies, it has been proved that mesenchymal stem cells have obvious therapeutic effects on acute kidney injury, diabetic nephropathy, lupus nephritis and various glomerular diseases in animal models. In clinical studies, mesenchymal stem cells have also been shown to be safe and partially effective. Mesenchymal stem cell therapy has revealed a new model of biotherapy in kidney diseases.

The pathogenesis of ulcerative colitis (UC) is unclear. House dust mite (HDM) is associated with immune inflammation in the body. This study is designed to identify the association between HDM and UC clinical symptoms. UC patients (n = 86) and non-UC control (NC) subjects (n = 64) were recruited. Colon lavage fluids (CLF) were collected from HDM skin prick test positive patients during colonoscopy, and analyzed by immunological approaches. HDM was detected in fecal samples, which was positively correlated with UC clinical symptoms. HDM-specific eosinophils and Th2 cells were detected in CLF, which could be specifically activated by exposing to HDM in the culture. Direct exposure to HDM induced eosinophil activation in the colon of UC patients. UC patients displayed elevated levels of Th2 cytokines in the serum. UC clinical symptom scores were positively correlated with serum levels of Th2 cytokines. HDM was detected in UC patients’ stools, which was positively correlated with UC clinical symptoms. Direct exposure to HDM could trigger eosinophilic activation of the colon.

Abstract No fully validated risk-stratification strategies have been established in China where colonoscopies resources are limited. We aimed to develop and validate a fecal immunochemical test (FIT)-based risk-stratification model for colorectal neoplasia (CN); 10,164 individuals were recruited from 175 centers nationwide and were randomly allocated to the derivation (n = 6776) or validation cohort (n = 3388). Multivariate logistic analyses were performed to develop the National Colorectal Polyp Care (NCPC) score, which formed the risk-stratification model along with FIT. The NCPC score was developed from eight independent predicting factors and divided into three levels: low risk (LR 0–14), intermediate risk (IR 15–17), and high risk (HR 18–28). Individuals with IR or HR of NCPC score or FIT+ were classified as increased-risk individuals in the risk-stratification model and were recommended for colonoscopy. The IR/HR of NCPC score showed a higher prevalence of CNs (21.8%/32.8% vs. 11.0%, P

With the rapid development of poultry industry and the highly intensive production management, there are an increasing number of stress factors in poultry production. Excessive stress will affect their growth and development, immune function, and induce immunosuppression, susceptibility to a variety of diseases, and even death. In recent years, increasing interest has focused on natural components extracted from plants, among which plant polysaccharides have been highlighted because of their various biological activities. Plant polysaccharides are natural immunomodulators that can promote the growth of immune organs, activate immune cells and the complement system, and release cytokines. As a green feed additive, plant polysaccharides can not only relieve stress and enhance the immunity and disease resistance of poultry, but also regulate the balance of intestinal microorganisms and effectively alleviate all kinds of stress faced by poultry. This paper reviews the immunomodulatory effects and molecular mechanisms of different plant polysaccharides (Atractylodes macrocephala Koidz polysaccharide, Astragalus polysaccharides, Taishan Pinus massoniana pollen polysaccharide, and alfalfa polysaccharide) in poultry. Current research results reveal that plant polysaccharides have potential uses as therapeutic agents for poultry immune abnormalities and related diseases.

Objective To investigate the central nervous system (CNS) primary melanocytic tumors (melanocytic tumors) and improve the understanding of melanocytic tumors. Methods and Results Since January 2012 to October 2019, 7 cases of melanocytic tumors were collected in Guangdong 999 Brain Hospital. Five patients underwent surgical resection and 2 patients underwent tissue biopsy. MRI showed high signal in T1WI, low signal in T2WI, and high signal in FLAIR. Tumor cell assumed a variety of shapes, including oval and polygonal, melanin⁃containing macrophages from benign to atypical. Results of immunohistochemistry showed that Melan⁃A and S⁃100 protion were consistently positive, and HMB⁃45 was negative, scattered or strongly positive. Four patients were diagnosed with meningeal melanocytoma, one with meningeal melanoma, one with diffuse meningeal melanocytosis, and one with meningeal melanomatosis. Four cases of melanocytoma underwent total or major resection, and of 3 cases received postoperative radiotherapy. The 2 cases who received radiotherapy were in good condition after follow⁃up of 56 and 116 months. The one case did not receive radiotherapy stay alive for 20 months. One meningeal melanomatosis patient received postoperative chemoradiotherapy, with a total survival time of 15 months. One patient with diffuse melanocytosis had a total survival time of 13 months. One meningealmelanocytosis patient improved after 7 months received chemoradiotherapy. Conclusions CNS primary melanocytic tumors are rare. Meningeal melanocytoma is common in the elderly, while diffuse meningeal melanocytosis is common in children. The expression patterns of melanin markers Melan ⁃A, S ⁃100 are consistently expressed, and HMB ⁃ 45 which helps to identify the benign and malignant tumors. The prognosis of tumour is still unclear. Melanocytoma has the best prognosis and benefits from radiotherapy.

Functional materials with high viscosity and solid materials have received more and more attentions in flexible pressure sensors, which are inadequate in the most used molding method. Herein, laser direct writing (LDW) method is proposed to fabricate flexible piezoresistive sensors with microstructures on PDMS/ MWCNTs composites with an 8% MWCNTs mass fraction. By controlling laser energy, microstructures with different geometries can be obtained, which significantly impacts the performances of the sensors. Subsequently, curved microcones with excellent performance are fabricated under parameters of f = 40 kHz and v = 150 mm·s-1. The sensor exhibits continuous multi-linear sensitivity, ultrahigh original sensitivity of 21.80 % kPa-1, wide detection range of over 20 kPa, response/recovery time of ~100 ms and good cycle stability for more than 1000 times. Besides, obvious resistance variation can be observed when tiny pressure (a peanut of 30 Pa) is applied. Finally, the flexible piezoresistive sensor can be applied for LED brightness controlling, pulse detection and voice recognition.

Text detection is widely applied in the automatic driving and cross-modal image retrieval fields. This technique is also an important pre-procedure in optical character-based text recognition tasks. At present, text detection in complex natural scenes remains a challenging topic. Because text distribution and orientation are varied in different scenes and domains, there is still room for improvement in existing computer vision-based text detection methods. To complicate matters, natural scene texts, such as those in guideposts and shop signs, always contain words in different languages. Even characters are missing from some natural scene texts. These circumstances present more difficulties for feature extraction and feature description, thereby weakening the detectability of existing computer vision and image processing methods. In this context, text detection applications in natural scenes were summarized in this paper, the classical and newly presented techniques were reviewed, and the research progress and status were analyzed. First, the definitions of natural scene text detection and associated concepts were provided based on an analysis of the main characteristics of this problem. In addition, the classic natural scene text detection technologies, such as connected component analysis-based methods and sliding detection window-based methods, were introduced comprehensively. These methods were also compared and discussed. Furthermore, common deep learning models for scene text detection of the past decade were also reviewed. We divided these models into two main categories: region proposal-based models and segmentation-based models. Accordingly, the typical detection and semantic segmentation frameworks, including Faster R-CNN, SSD, Mask R-CNN, FCN, and FCIS, were integrated in the deep learning methods reviewed in this section. Moreover, hybrid algorithms that use region proposal ideas and segmentation strategies were also analyzed. As a supplement, several end-to-end text recognition strategies that can automatically identify characters in natural scenes were elucidated. Finally, possible research directions and prospects in this field were analyzed and discussed.

Mathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba). The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter. The model was established using data collected from dedicated field experiments performed in 2016–2018. Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha−1 and 0.19, and R2 values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively. Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively. In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age. The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI. The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R2≥0.856, RMSE≤0.68 t ha−1) and local accuracies (mean R2≥0.43, RMSE≤0.70 t ha−1). Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R2 of 0.891 and RMSE of 0.591 t ha−1, and local mean R2 of 0.57 and RMSE of 0.66 t ha−1, respectively. The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees.

A rapid and accurate detection of carbapenemase-producing Gram-negative bacteria (CPGNB) has an immediate demand in the clinic. Here, we developed and validated a method for rapid detection of CPGNB using Blue-Carba combined with deep learning (designated as AI-Blue-Carba). The optimum bacterial suspension concentration and detection wavelength were determined using a Multimode Plate Reader and integrated with deep learning modeling. We examined 160 carbapenemase-producing and non-carbapenemase-producing bacteria using the Blue-Carba test and a series of time and optical density values were obtained to build and validate the machine models. Subsequently, a simplified model was re-evaluated by descending the dataset from 13 time points to 2 time points. The best suitable bacterial concentration was determined to be 1.5 optical density (OD) and the optimum detection wavelength for AI-Blue-Carba was set as 615 nm. Among the 2 models (LRM and LSTM), the LSTM model generated the higher ROC-AUC value. Moreover, the simplified LSTM model trained by short time points (0–15 min) did not impair the accuracy of LSTM model. Compared with the traditional Blue-Carba, the AI-Blue-Carba method has a sensitivity of 95.3% and a specificity of 95.7% at 15 min, which is a rapid and accurate method to detect CPGNB.

Recently synthesized Kagome compounds AV _3 Sb _5 attract great attention due to the unusual coexistence of the topology, charge density wave, and superconductivity. In this work, based on the band structures for CsV _3 Sb _5 in the pristine phase, we construct an effective six-band model for the low-energy processes; utilizing the random phase approximation on the effective six-band model, we show that the $E_{1u}$ ( p wave) pairing dominates in the region of $0\lt U\lt0.32$ eV, the $A_{2g}$ ( I wave) in the region of $0.32\lt U\lt0.75$ eV and the $E_{2g}$ ( d wave) in the region of $0.75\lt U\lt1$ eV. Considering that the correlation in AV _3 Sb _5 is weak or intermediate, these results suggest that pairing symmetry is $A_{2g}$ ( I -wave) in the CsV _3 Sb _5 , which can explain some recent experiments about pairing symmetry.

Background/Aims: Activated hepatic stellate cells (HSCs) are the major source of extracellular matrix (ECM). Therefore inhibiting HSC activation is considered as an effective strategy to inhibit the process of liver fibrosis. This study aimed to investigate the underlying mechanism of methyl helicterate (MH) isolated from Helicteres angustifolia on the activation of HSCs. Methods: HSC-T6 cells were treated with various concentration of MH and autophagy was inhibited by 3-Methyl adenine (3-MA) or RNA interference. Cell viability was observed by MTT assay and cell colony assay. Cell cycle and apoptosis were analyzed using flow cytometry. Autophagic vacuoles were observed by transmission electron microscopy and monodansyl cadaverine (MDC) staining. Moreover, autophagy-related genes and proteins were detected using real-time PCR and Western blot assays, respectively. Results: MH significantly inhibited HSC activation, as evidenced by the inhibition of cell viability, colony formation and the expression of α-SMA and collagen I. MH caused cell cycle arrest in G2/M phase. Moreover, MH significantly induced apoptosis through regulating the mitochondria-dependent pathway and the activity of caspases. MH treatment significantly increased lysosomes and autophagosomes, and enhanced the formation of autophagic vacuoles and autophagic flux. Interestingly, inhibiting autophagy by 3-MA or RNA interference abolished the ability of MH in inhibiting HSC activation. On the other hand, induction of autophagy promoted MH-induced HSC apoptosis. Further study showed that MH-induced HSC apoptosis and autophagy was mediated by the JNK and PI3K/Akt/mTOR pathways. Conclusion: Our results demonstrate that MH-induced HSC apoptosis and autophagy may be one of the important mechanisms for its anti-fibrosis effect.

This study analyzed the mechanical and physiological strategies associated with four features in the branch–stem junction of a tree, namely the U-shaped branch attachment, the branch collar, the branch bark ridge, and the roughened lower stem. Models were established for each stage of tree growth by adding these four features sequentially to a base model, and the finite element method (FEM) was employed to create three-dimensional models of an Acer tree's branch–stem structure for static force analysis. According to the results, the development of the branch collar shifted the point of breakage to the outer part of the collar and, thus, constituted a physiological strategy that prevented decay in the stem. Additionally, the concentration of stress in the branch bark ridge limited the area of tear in the bark following breakage. Finally, the U-shaped branch attachment reduced stress and shifted the point of peak stress toward the branch, while the thickening of the lower stem reduced the overall stress. The development of these features, including the spatial positioning of the branch bark ridge and branch collar, resulted in two breakage points constituting a physical and a physiological strategy that limited damage to the tree and protected the xylem structure. This is the part that has been challenging to decipher in previous discussions of tree-related self-protection mechanisms. [ABSTRACT FROM AUTHOR]

The study was to understand the quality status of main feed ingredients in dairy farm, to provide data support for roughage and TMR daily ration on farms. A total of 311 feed materials and roughage ingredients were analyzed. The results showed that in 2022, the quality of alfalfa and silage was good, the quality stability of Leymus chinensis and oat grass was normal, the TMR production level of low-yield and high-yield cattle was good, and the TMR production level of dry cows and reserve cattle was normal. The study indicates that the test analysis report provided a reference for improving the quality of roughage and TMR for dairy cows in Beijing. [ABSTRACT FROM AUTHOR]

Objective To evaluate the 18F-fluoro-2-deoxy-D-glucose (18F-FDG) PET performance of focal cortical dysplasia (FCD) without MRI abnormalities. Methods A total of 47 cases with FCD underwent standard anterior temporal lobectomy (ATL) and hippocampectomy and were confirmed by postoperative pathological findings. Preoperative MRI showed no obvious abnormalities, and 18F-FDG PET were performed on all of them. Results There were 26 males and 21 females, aged 9-51 years (the mean age was 24.35 years). According to postoperative pathological examinations, there were 33 cases of FCD type Ⅰ (12 cases of type Ⅰa, 8 cases of type Ⅰb and 13 cases of type Ⅰc) and 14 cases of FCD type Ⅱ (10 cases of type Ⅱ a and 4 cases of type Ⅱ b). A total of 45 cases (95.74% ) showed reduced brain metabolism in PET examination, including 37 cases of focal temporal lobe hypometabolism (located in medial temporal lobe, temporal pole and hippocampus, etc.) and 8 cases of multifocal hypometabolism (extensive hypometabolism in anterior and posterior temporal lobe). Conclusions 18F-FDG PET imaging can be taken as an adjunct diagnostic tool in temporal lobe FCD without MRI abnormalities, so it has important referential value in clinical diagnosis. DOI: 10.3969/j.issn.1672-6731.2015.10.011

N parties were involved in the computation of a function,which did not trust each other.Some of them found a coalition and destroy the security of others through collusion.Based on secure multi-party computation and communica-tions channel,to the collusion that could be nested,a trusted coalition-proof protocol model was proposed.The concept of correlated equilibrium was used by the model in game theory for talking place the trusted third party.