ObjectivesTo investigate sex difference in global gastric cancer incidence by year, age and socioeconomical status.DesignAn international comparative study.SettingWe obtained the global and national sex-specific incidence of gastric caner by year and age from the Global Burden of Disease Study 2017. The human development index (HDI) in 2017 as an indicator of national socioeconomical status was extracted from the Human Development Report.Main outcome measuresSex-specific incidence of gastric cancer was compared by year and age at the global level. Linear regression analyses were performed to explore socioeconomic-associated sex difference in gastric cancer incidence.ResultsDespite declining incidence of global gastric cancer in both sexes between 1990 and 2017, relative sex difference showed an increasing trend, with male to female ratios of age-standardised incidence rates (ASRs) rising from 1.86 to 2.20. Sex difference was almost negligible under 45 years of age and relative difference maximised in the age range of 65–69 years with male to female ratios of ASRs being 2.74. Both absolute sex difference (standardised β=0.256, p<0.001) and relative difference (standardised β=0.387, p<0.001) in ASRs were positively associated with HDI.ConclusionsThis study revealed that decreasing incidence of global gastric cancer was accompanied by widening sex difference in the past few decades. Men always had higher incidence than women. Greater sex difference was found in older age and in more developed countries. These findings highlight the importance of making sex-sensitive health policy to cope with the global gastric cancer burden.

Introduction: Gastrointestinal stromal tumors (GISTs), with a primary occurrence in the duodenum and proximal jejunum, are rare and treatment is poorly understood. This study aimed to evaluate the main factors influencing the prognosis of GIST resection in this complex anatomical structure. Materials and methods: This retrospective study included 47 patients who underwent surgery for primary GIST of the duodenum (20) and proximal jejunum (27) between 2012 and 2017. Perioperative clinical data as well as relapse and survival information were collected. Results: All patients underwent negative margin resection (R0) of duodenal and proximal jejunum GISTs. Complications occurred more frequently in treatment of duodenal GISTs than proximal jejunum GISTs (p ¼ 0.003). GISTs in D3 (the 3rd portion of duodenum) were related to larger tumor size (p ¼ 0.001), higher probability of severe complication rate (p ¼ 0.042), longer hospital stays (p ¼ 0.023) and fasting time (p ¼ 0.020). More complications were found for patients with digestive reconstruction than limited resection (p ¼ 0.010). Additionally, patients with a tumor mass larger than 5 cm or a mitotic index greater than 5 mitoses/50 HPFs showed poorer therapeutic outcomes. The 1-and 3-year overall survival was 97.9% and 86.1%, respectively and were not influenced by operation type (p ¼ 0.061) or GIST position (p ¼ 0.447). Conclusion: With negative operational margins, limited resection is a safe and feasible procedure for duodenal and proximal jejunum GIST patients and unnecessary digestive reconstruction should be avoided. Considering the severe complication rate, resection for GISTs in D3 should be performed with care.

The Notch signaling pathway has been identified as a therapeutic target for cancers. γ-Secretase inhibitors (GSIs) have been progressively recognized as potential anticancer drugs. The present study aimed to investigate the effects of anti-delta like legend 4 (anti-DLL4) treatment on the anticancer efficacy of GSIs in gastric cancer. SGC-7901-GFP human gastric cancer cells were tested for DLL4 expression by rosette formation test and immunofluorescence, and then were treated with anti-DLL4 antibody N-[N-(3,5-difluorophenacetyl)-L-ananyl]-S-phenylglycine t-butyl ester (DAPT, a type of GSI), or a combination of anti-DLL4 antibody and DAPT. The effects of in vitro treatments on cell apoptosis, cell cycle, and cell invasion were analyzed. For in vivo study, an orthotopic mouse model of gastric cancer was established with green fluorescence expressing SGC-7901. Ultrasound targeted microbubble destruction was used to treat tumor-bearing mice with anti-DLL4 antibody conjugated microbubbles, DAPT, and a combination of the two. Real-time fluorescence imaging was performed to assess tumor cell inhibition in each group. Following in vivo treatments, apoptosis of tumor cells and the expression of apoptosis-related genes BAX, Bcl-2, and P53 were detected by TUNEL and immunohistochemical staining. In vivo combined treatment of anti-DLL4 and DAPT led to a higher rate of cell apoptosis and greater inhibition of cell invasion than that observed with DAPT treatment alone. DAPT and anti-DLL4 combination therapy resulted in decreased cell distribution at G1 phase and increased cell distribution at S phase, compared to the untreated control group (P < .01). In vivo combined therapy with anti-DLL4 and DAPT significantly increased tumor growth inhibition and tumor cell apoptosis when compared to DAPT therapy alone (P < .05). In addition, combined treatment significantly increased expression of BAX and P53 and reduced Bcl-2 expression (P < .05). Conversely, treatment with DAPT alone only increased expression of BAX and P53 (P < .05), suggesting that the reduction of Bcl-2 expression may play an important role in the synergetic antitumor and proapoptosis effects of the combined treatment. Concurrent treatment with anti-DLL4 enhances the antitumor and proapoptotic efficacy of the γ-secretase inhibitor in gastric cancer both in vitro and in vivo.

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MicroRNA (miRNA) studies are experiencing a transition from basic research applications to clinical applications. However, the lack of reliable and sensitive miRNA detection methods has become a bottleneck in the process. Here, we report an absolute quantification method based on the competitive PCR amplification of specific miRNAs and synthetic RNA spike-ins in a single reaction. RNA spike-ins are quantified as dynamic RNA copy number standards and are used to measure selected miRNAs free from the effects of intra-assay variables, including those from individual sample sources. Combined with the size differentiation power of capillary electrophoresis, the content of miRNAs was reproducibly measured, with verifiable detection limits of 10–46 copies over 5-log detection ranges. The direct measurements of miRNAs from 168 human serum samples and their considerable value as a diagnostic for bronchopneumonia and bronchiolitis demonstrate the potential of the assay in clinical applications.

In the field of community detection in complex networks, the most commonly used approach to this problem is the maximization of the benefit function known as “modularity”. In this study, it is found that the path of length two have the similar property as the edge, which is denser within communities and sparser between different communities. In order to take both edge and path of length two into consideration simultaneously, a self-loop is added to each node of the network and a novel benefit function has been defined. To divide the network into two communities, a second eigenvector method is proposed based on maximization of our new benefit function. Experimental results obtained by applying the method to karate club network and dolphin social network show the feasibility of our benefit function and the effectiveness of our algorithm.

Trees can resorb nutrients to preserve and reuse them before leaves fall, which could efficiently adapt to environmental changes. However, the nutrient requirements of trees in different months with seasonal climate changes are often neglected. In this study, we selected plantations of an evergreen broadleaf tree (Castanopsis carlesii (Hemsl.) Hayata) and a coniferous tree (Cunninghamia lanceolate (Lamb.) Hook.) in the subtropics. The monthly dynamics of leaf nitrogen (N) and phosphorus (P) resorption efficiencies and C:N:P stoichiometric ratios were checked along a growing season from April to October 2021. Trees in both plantations exhibited efficient N and P resorption but with significant monthly variations. The N and P resorption efficiencies in the Cunninghamia lanceolata plantation ranged from 34.26% to 56.28% and 41.01% to 54.85%, respectively, and were highest in September. In contrast, N and P resorption efficiencies in the Castanopsis carlesii plantation ranged from 11.25% to 34.23% and 49.22% to 58.72%, respectively, and were highest in July. Compared with the Cunninghamia lanceolata, the C:N of the Castanopsis carlesii plantation was significantly lower, while its C:P was significantly higher in May and September. The Castanopsis carlesii plantation was strongly limited by P (the N:P ratios in mature leaves were higher than 20), whereas the Cunninghamia lanceolata plantation might be limited by both N and P (the N:P ratios in mature leaves were between 10 and 20). In addition, the statistical analyses revealed that temperature and precipitation were significantly associated with N and P resorption efficiencies, but the relationships were controlled by forest types. These findings highlight that efficient resorption of N and P may be beneficial in regulating nutrient limitation and balance in subtropical forest ecosystems. These results contribute to the understanding of N and P utilization strategies of trees and provide a theoretical basis for vegetation management in the subtropics.

In the current nuclear reactor system analysis codes, the interfacial area concentration and void fraction are mainly obtained through empirical relations based on different flow regime maps. In the present research, the data-driven method has been proposed, using four machine learning algorithms (lasso regression, support vector regression, random forest regression and back propagation neural network) in the field of artificial intelligence to predict some important two-phase flow parameters in rectangular channels, and evaluate the performance of different models through multiple metrics. The random forest regression algorithm was found to have the strongest ability to learn from the experimental data in this study. Test results show that the prediction errors of the random forest regression model for interfacial area concentrations and void fractions are all less than 20%, which means the target parameters have been forecasted with good accuracy.