Explore the vast range of titles available.

With over 2 million new cases annually, stroke is associated with the highest disability-adjusted life-years lost of any disease in China. The burden is expected to increase further as a result of population ageing, an ongoing high prevalence of risk factors (eg, hypertension), and inadequate management. Despite improved access to overall health services, the availability of specialist stroke care is variable across the country, and especially uneven in rural areas. In-hospital outcomes have improved because of a greater availability of reperfusion therapies and supportive care, but adherence to secondary prevention strategies and long-term care are inadequate. Thrombolysis and stroke units are accepted as standards of care across the world, including in China, but bleeding-risk concerns and organisational challenges hamper widespread adoption of this care in China. Despite little supporting evidence, Chinese herbal products and neuroprotective drugs are widely used, and the increased availability of neuroimaging techniques also results in overdiagnosis and overtreatment of so-called silent stroke. Future efforts should focus on providing more balanced availability of specialised stroke services across the country, enhancing evidence-based practice, and encouraging greater translational research to improve outcome of patients with stroke.

CircRNAs are a novel class of RNA molecules with a unique closed continuous loop structure. CircRNAs are abundant in eukaryotic cells, have unique stability and tissue specificity, and can play a biological regulatory role at various levels, such as transcriptional and posttranscriptional levels. Numerous studies have indicated that circRNAs serve a crucial purpose in cancer biology. CircRNAs regulate tumor behavioral phenotypes such as proliferation and migration through various molecular mechanisms, such as miRNA sponging, transcriptional regulation, and protein interaction. Recently, several reports have demonstrated that they are also deeply involved in resistance to anticancer drugs, from traditional chemotherapeutic drugs to targeted and immunotherapeutic drugs. This review is the first to summarize the latest research on circRNAs in anticancer drug resistance based on drug classification and to discuss their potential clinical applications.

In this paper, a range-based cooperative localization method is proposed for multiple platforms of various structures. The localization system of an independent platform might degrade or fail due to various reasons such as GPS signal-loss, inertial measurement unit (IMU) accumulative errors, or emergency reboot. It is a promising approach to solve this problem by using information from neighboring platforms, thus forming a cooperative localization network that can improve the navigational robustness of each platform. Typical ranging-based ultra-wideband (UWB) cooperative localization systems require at least three auxiliary nodes to estimate the pose of the target node, which is often hard to meet especially in outdoor environment. In this work, we propose a novel IMU/UWB-based cooperative localization solution, which requires a minimum number of auxiliary nodes that is down to 1. An Adaptive Ant Colony Optimization Particle Filter (AACOPF) algorithm is customized to integrate the dead reckoning (DR) system and auxiliary nodes information with no prior information required, resulting in accurate pose estimation, while to our knowledge the azimuth have not been estimated in cooperative localization for the insufficient observation of the system. We have given the condition when azimuth and localization are solvable by analysis and by experiment. The feasibility of the proposed approach is evaluated through two filed experiments: car-to-trolley and car-to-pedestrian cooperative localization. The comparison results also demonstrate that ACOPF-based integration is better than other filter-based methods such as Extended Kalman Filter (EKF) and traditional Particle Filter (PF).

Deep learning has been widely used in remote sensing image segmentation, while a lack of training data remains a significant issue. The few-shot segmentation of remote sensing images refers to the segmenting of novel classes with a few annotated samples. Although the few-shot segmentation of remote sensing images method based on meta-learning can get rid of the dependence on large data training, the generalization ability of the model is still low. This work presents a few-shot segmentation of remote sensing images with a self-supervised background learner to boost the generalization capacity for unseen categories to handle this challenge. The methodology in this paper is divided into two main modules: a meta learner and a background learner. The background learner supervises the feature extractor to learning latent categories in the image background. The meta learner expands on the classic metric learning framework by optimizing feature representation through contrastive learning between target classes and latent classes acquired from the background learner. Experiments on the Vaihingen dataset and the Zurich Summer dataset show that our model has satisfactory in-domain and cross-domain transferring abilities. In addition, broad experimental evaluations on PASCAL-5i and COCO-20i demonstrate that our model outperforms the prior works of few-shot segmentation. Our approach surpassed previous methods by 1.1% with ResNet-101 in a 1-way 5-shot setting.

Background To investigate the clinical characteristics and manifestations of older patients with coronavirus disease 2019 (COVID-19). Methods In this retrospective study, 566 patients with confirmed COVID-19 were enrolled and the clinical characteristics, laboratory findings, complications and outcome data were collected and analyzed. Results Among the 566 patients (median age, 61.5 years) with COVID-19, 267 (47.2%) patients were male and 307 (54.2%) were elderly. Compared with younger patients, older patients had more underlying comorbidities and laboratory abnormalities. A higher rate of acute respiratory distress syndrome (ARDS), acute cardiac injury and heart failure was observed in the older group as compared with younger and middle-aged groups, particularly those oldest-old patients had more multi-organ damage. Older patients with COVID-19 were more likely to suffer from acute cardiac injury in cases with preexistenting cardiovascular diseases, while there was no difference among the three groups when patients had no history of cardiovascular diseases. Older patients presented more severe with the mortality of 18.6%, which was higher than that in younger and middle-aged patients ( P  < 0.05). Multivariable analysis showed that age, lymphopenia, ARDS, acute cardiac injury, heart failure and skeletal muscle injury were associated with death in older patients, while glucocorticoids might be harmful. Conclusions Older patients, especially the oldest-old patients were more likely to exhibit significant systemic inflammation, pulmonary and extrapulmonary organ damage and a higher mortality. Advanced age, lymphopenia, ARDS, acute cardiac injury, heart failure and skeletal muscle injury were independent predictors of death in older patients with COVID-19 and glucocorticoids should be carefully administered in older patients.

Micro-LED display technology is considered to be the next generation of display technology, which has the characteristics of high miniaturization, thin film and integration, as well as the advantages of high brightness, high contrast, fast response speed and long service life. However, in the development of Micro-LED display technology, there are still some technical and cost problems to be solved. This paper focuses on the key technologies involved in Micro-LED display technology, such as chip technology, mass transfer, full-color display, bonding and driving technology, the research history and frontier progress of these technologies are reviewed in detail. For chip epitaxy technology, the wavelength uniformity, current density and defect control are emphasized; for chip process, the two main chip structures and the challenges brought by miniaturization are discussed emphatically; for chip integration, full-color display, backplane bonding and driving, several mainstream technical schemes are summarized in turn. Finally, the chip detection and repair technologies and commercial application are introduced.

Uric acid (UA) is an antioxidant with neuroprotective effects in experimental stroke models. Whether serum UA plays a role in hemorrhagic transformation (HT) remains unclear. We aimed to explore the association between serum UA and HT in patients with acute ischemic stroke (AIS). AIS patients within 7 days after stroke onset were consecutively enrolled between January 2016 and October 2017. Patients were categorized into three groups according to serum UA tertiles by sex. HT was detected by follow-up CT or MRI within 7 days after admission. The multivariate logistic analysis was performed to assess the association of serum UA with HT. We included 1230 patients (mean age 64.1 years, 63.5% males) and 133 (10.8%) patients experienced HT. After adjusting confounders, patients in the second and third UA tertiles showed a significant decrease in HT compared with those in the lowest tertile (OR 0.432, 95% CI 0.266–0.702; OR 0.033, 95% CI 0.013–0.086, respectively). Similar results were observed for sex-based subgroups. Males with higher UA had lower risk of HT compared with the lowest UA tertile (OR 0.332, 95% CI 0.170–0.651; OR 0.008, 95% CI 0.001–0.070, respectively). In females, the highest UA tertile was inversely associated with HT (OR 0.148, 95% CI 0.058–0.376). Multiple-adjusted spline regression analyses further confirmed the dose-response relationship between UA levels and HT. Higher serum UA is independently associated with lower HT following stroke. More studies are needed to elucidate the potential neuroprotective mechanism of serum UA and its link to HT.

Background Long noncoding RNAs (lncRNAs) have emerged as important regulators of tumorigenesis and cancer progression. Recently, the lncRNA AGAP2-AS1 was identified as an oncogenic lncRNA in human non-small cell lung cancer (NSCLC) and its elevated expression was linked to NSCLC development and progression. However, the expression pattern and molecular mechanism of AGAP2-AS1 in gastric cancer (GC) have not been characterized. Methods Bioinformatic analysis was performed to determine AGAP2-AS1 expression levels in the GC and normal tissues using gene profiling data from the Gene Expression Omnibus. Quantitative real-time polymerase chain reaction was used to validate AGAP2-AS1 expression in the GC tissues/cell lines compared with that in the adjacent nontumorous tissues/normal epithelial cells. Loss- and gain-of-function approaches were performed to investigate the effect of AGAP2-AS1 on GC cell phenotypes. The effect of AGAP2-AS1 on cell proliferation was evaluated by MTT, colony formation, flow cytometry, and in vivo tumor formation assays. The effects of AGAP2-AS1 on cell migration and invasion were examined using Transwell assays. Chromatin immunoprecipitation, luciferase reporter assays, RNA pull-down, and RNA immunoprecipitation were used to investigate the factors involved in AGAP2-AS1 dysregulation and the mechanism of action of AGAP2-AS1 in the GC cells. Results AGAP2-AS1 was highly expressed in the GC tissues and cell lines, and patients with higher AGAP2-AS1 expression had a poorer prognosis and shorter overall survival. Furthermore, knockdown of AGAP2-AS1 significantly inhibited GC cell proliferation, migration, and invasion in vitro and tumor growth in vivo. AGAP2-AS1 overexpression promoted cell growth and invasion. In addition, the transcription factor SP1 activated AGAP2-AS1 expression in the GC cells. AGAP2-AS1 functions as an oncogenic lncRNA by interacting with LSD1 and EZH2 and suppressing CDKN1A (P21) and E-cadherin transcription. Conclusions Taken together, these findings imply that AGAP2-AS1 upregulated by SP1 plays an important role in GC development and progression by suppressing P21 and E-cadherin, which suggests that AGAP2-AS1 is a potential diagnostic marker and therapeutic target for GC patients.

Background Long noncoding RNAs (lncRNAs) are known to regulate tumorigenesis and cancer progression, but their contributions to non-small-cell lung cancer (NSCLC) metastasis remain poorly understood. Our previous and other studies have revealed the involvement of upregulated LINC01234 in regulating gastric cancer and colon cancer cells proliferation, and we aimed to investigate whether LINC01234 overexpression also contribute to cancer cells metastasis in this study. Methods We collect the NSCLC tissues and adjacent non-tumor tissues and analyzed expression levels of LINC01234 by quantitative reverse-transcription PCR. LINC01234 were knocked down by using siRNAs or shRNAs, and overexpressed by transfection with overexpression vector; RNA levels of miRNA were downregulated or upregulated with inhibitors or mimics. Transwell assays were used to evaluate cell migration and invasive ability; in vivo metastasis experiments were performed to investigate the effect of LINC01234 on NSCLC cells metastasis. Luciferase reporter, RIP, and ChIP assays were used to determine the regulation of LINC01234 on its targets. Results LINC01234 expression is increased in NSCLC tissues, and its upregulation is associated with metastasis and shorter survival in NSCLC. Downregulation of LINC01234 impairs cell migration and invasion in vitro, and inhibits cells metastasis in vivo by acting as a competing endogenous RNA for the miR-340-5p and miR-27b-3p. LINC01234 also interacts with the RNA-binding proteins LSD1 and EZH2, leading to histone modification and transcriptional repression of the anti-proliferative genes BTG2. Conclusions Taken together, our findings identify two oncogenic regulatory axes in NSCLC centering on LINC01234: one involving miR-340-5p/miR-27b-3p in the cytoplasm and the second involving EZH2, LSD1, and BTG2 in the nucleus. Our study indicates that these genes may be targeted to reduce or prevent NSCLC metastasis.

Background To analyze the ultrasound imaging and clinical characteristics of fetuses with umbilical artery thrombosis (UAT), explore the potential causes of UAT and construct a prognostic prediction model to guide clinical practice. Methods This was a retrospective cohort study of fetal UAT cases examined at two academic tertiary referral care centers from 2014 to 2020. The basic information of the participants was obtained by interview during follow-up, and data on clinical treatment, delivery conditions, diagnosis and confirmation were obtained through medical records. Probable causes of thrombosis were explored by comparative analysis of the UAT group to the control group and by further regression analysis. Multivariable logistic regression models were used to evaluate risk factors for adverse pregnancy outcomes. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic value of the prognostic prediction model. Results Thirty fetuses with UAT were included in this study. UAT occurred mostly in the third trimester of pregnancy, and there was an obvious predominance of right UAT. An abnormal pregnancy history (53.3%) was the most common comorbidity, followed by gestational diabetes mellitus (GDM) (20.0%). GDM and umbilical cord (UC) abnormalities were found to be independent risk factors for the development of UAT. After comprehensive decision-making, over two-thirds of the patients with UAT received urgent treatment, and less than one-third received expectant management. Surprisingly, there were no significant differences in fetal outcomes between the urgent treatment and expectant management groups. Multivariate logistic regression analysis showed that gestational age (GA) at clinical diagnosis and UC abnormalities were independent risk factors for adverse pregnancy outcomes (OR 0.781, p  = 0.042; OR 16.779, p  = 0.023, respectively). Based on this, we constructed a comprehensive prognostic prediction model. The area under the ROC curve (AUC) was 0.877 (95% CI 0.698–0.970; p  < 0.001), which suggested that the combination of GA and UC abnormalities was a better predictor for fetal outcomes in our setting. Conclusion In summary, maternal GDM and fetal UC abnormalities are independent risk factors for UAT. UAT is more frequently observed on the right side. Moreover, poor clinical outcomes for fetuses with UAT are ascribed mainly to GA and UC abnormalities, which should be comprehensively evaluated to choose the appropriate treatment.