The aim of this study was to analyze the clinical data, discharge rate, and fatality rate of COVID‐19 patients for clinical help. The clinical data of COVID‐19 patients from December 2019 to February ...2020 were retrieved from four databases. We statistically analyzed the clinical symptoms and laboratory results of COVID‐19 patients and explained the discharge rate and fatality rate with a single‐arm meta‐analysis. The available data of 1994 patients in 10 literatures were included in our study. The main clinical symptoms of COVID‐19 patients were fever (88.5%), cough (68.6%), myalgia or fatigue (35.8%), expectoration (28.2%), and dyspnea (21.9%). Minor symptoms include headache or dizziness (12.1%), diarrhea (4.8%), nausea and vomiting (3.9%). The results of the laboratory showed that the lymphocytopenia (64.5%), increase of C‐reactive protein (44.3%), increase of lactic dehydrogenase (28.3%), and leukocytopenia (29.4%) were more common. The results of single‐arm meta‐analysis showed that the male took a larger percentage in the gender distribution of COVID‐19 patients 60% (95% CI 0.54, 0.65), the discharge rate of COVID‐19 patients was 52% (95% CI 0.34,0.70), and the fatality rate was 5% (95% CI 0.01,0.11).
Research Highlights
Our study explored the clinical and epidemiological characteristics of COVID‐19 patients, and proposed the need to focus on other systemic symptoms such as the gastrointestinal tract firstly, which could be of use for clinical work.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Existing control techniques for rehabilitation robots commonly ignore robot dynamics by assuming a perfect inner control loop or are limited to rigid-joint robots. The dynamic stability of ...compliantly-actuated rehabilitation robots, consisting of the dynamics of both robot and compliant actuator, is not theoretically grounded. This paper presents an iterative learning impedance controller for rehabilitation robots driven by series elastic actuators (SEAs), where the control objective is specified as a desired impedance model. The desired impedance model is achieved in an iterative manner, which suits the repeating nature of patients’ task through therapeutic process and also guarantees the transient performance of robot. The stability of the overall system is rigorously proved with Lyapunov methods by taking into account both the robot and actuator dynamics. Experimental results are presented to illustrate the performance of the proposed iterative control scheme.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Although great achievements have been made in the synthesis of giant lanthanide clusters, novel structural models are still scarce. Herein, we report a giant lanthanide cluster Dy76, constructed from ...Dy3(μ3‐OH)4 and Dy5(μ4‐O)(μ3‐OH)8 building blocks. As the largest known Dy cluster, the structure of Dy76 can be seen as arising from the fusion of two Dy48 clusters; these clusters can be isolated under various synthetic conditions and were characterized by single‐crystal X‐ray diffraction. This new, fused structural model of the pillar motif has not been found in Ln clusters. Furthermore, the successful conversion of Dy76 back into Dy48 in a retrosynthetic manner supports the proposed fusion formation mechanism of Dy76. Electrospray ionization mass spectrometry (ESI‐MS) analysis suggests that the metal cluster skeleton of Dy76 shows good stability in various solvents. This work not only reveals a new structural type of Ln clusters but also provides insight into the novel fusion assembly process.
We go together: Two dysprosium clusters with 48 and 76 metal atoms, respectively, were generated under solvothermal conditions by using 3‐furancarboxylic acid. The bi‐nanopillar Dy76 was formed by the fusion of two Dy48 nanopillars.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Nitrogen‐doped carbon nanofiber webs (CNFWs) with high surface areas are successfully prepared by carbonization‐activation of polypyrrole nanofiber webs with KOH. The as‐obtained CNFWs exhibit a ...superhigh reversible capacity of 943 mAh g−1 at a current density of 2 A g−1 even after 600 cycles, which is ascribed to the novel porous nanostructure and high‐level nitrogen doping.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background/Aims: Programmed death ligand1(PD-L1) plays a role in the development and progression of non-small cell lung cancer (NSCLC). This study aimed to identify miRNA(s) that are responsible for ...regulation of expression of PD-L1 in NSCLC, and to investigate the role of PD-L1 in regulation of the cell cycle in NSCLC. Methods: We predicted the target miRNA of PD-L1, which was miR-140, using the online tools TargetScan and miBase. In NSCLC cells obtained from clinical specimens, in addition to A549 and NCI-H1650 cell cultures, western blots were used to detect the level of expression of proteins, while real-time PCR was used to determine the level of expression of PD-L1, miR-140, cyclin E, and β-actin. Transfection with miR-140 mimics, miR-140 inhibitors, and PD-L1 siRNA were conducted using commercial kits. To determine whether miR-140 directly binds PD-L1, a luciferase reporter gene with wild type or mutated PD-L1 was used. Cell viability was measured with the MTT assay, and PI staining was used for cell cycle analysis. Results: We found low expression of miR-140 and high expression of PD-L1 and cyclin E in NSCLC cells. Over-expression of miR-140 suppressed the expression of PD-L1 by directly binding its 3’ UTR, and was also associated with decreased expression of cyclin E and inhibition of cellular proliferation in A549 and NCI-H1650 cells. Inhibition of PD-L1, in the absence of manipulations to miR-140, also decreased the expression of cyclin E. Conclusion: We conclude that miR-140 directly suppresses PD-L1 and inhibits the miR-140/PD-L1/cyclin E pathway in NSCLC.
Summary Background MicroRNAs (miRNAs) can be used as prognostic biomarkers in many types of cancer. We aimed to identify miRNAs that were prognostic in patients with nasopharyngeal carcinoma. Methods ...We retrospectively analysed miRNA expression profiles in 312 paraffin-embedded specimens of nasopharyngeal carcinoma from Sun Yat-sen University Cancer Center (Guangzhou, China) and 18 specimens of non-cancer nasopharyngitis. Using an 873 probe microarray, we assessed associations between miRNA signatures and clinical outcome in a randomly selected 156 samples (training set) and validated findings in the remaining 156 samples (internal validation set). We confirmed the miRNAs signature using quantitative RT-PCR analysis in 156 samples from a second randomisation of the 312 samples, and validated the miRNA signature in 153 samples from the West China Hospital of Sichuan University in Chengdu, China (independent set). We used the Kaplan-Meier method and log-rank tests to estimate correlations of the miRNA signature with disease-free survival (DFS), distant metastasis-free survival (DMFS), and overall survival. Findings 41 miRNAs were differentially expressed between nasopharyngeal carcinoma and non-cancer nasopharyngitis tissues. A signature of five miRNAs, each significantly associated with DFS, was identified in the training set. We calculated a risk score from the signature and classified patients as high risk or low risk. Compared with patients with low-risk scores, patients with high risk scores in the training set had shorter DFS (hazard ratio HR 2·73, 95% CI 1·46–5·11; p=0·0019), DMFS (3·48, 1·57–7·75; p=0·0020), and overall survival (2·48, 1·24–4·96; p=0·010). We noted equivalent findings in the internal validation set for DFS (2·47, 1·32–4·61; p=0·0052), DMFS (2·28, 1·09–4·80; p=0·030), and overall survival (2·87, 1·38–5·96; p=0·0051) and in the independent set for DFS (3·16, 1·65–6·04; p=0·0011), DMFS (2·39, 1·05–5·42; p=0·037), and overall survival (3·07, 1·34–7·01; p=0·0082). The five-miRNA signature was an independent prognostic factor. A combination of this signature and TNM stage had better prognostic value than did TNM stage alone in the training set (area under receiver operating characteristics 0·68 95% CI 0·60–0·76 vs 0·60 0·52–0·67; p=0·013), the internal validation set (0·70 0·61–0·78 vs 0·61 0·54–0·68; p=0·012), and the independent set (0·70 0·62–0·78 vs 0·63 0·56–0·69; p=0·032). Interpretation Identification of patients with the five-miRNA signature might add prognostic value to the TNM staging system and inform treatment decisions for patients at high risk of progression. Funding Science Foundation of Chinese Ministry of Health, National Natural Science Foundation of China, Pearl River Scholar Funded Scheme, Guangdong Key Scientific and Technological Innovation Program, Guangdong Natural Science Foundation, Fundamental Research Funds for the Central Universities.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Previous studies suggest that gut microbiota is associated with neuropsychiatric disorders, such as Parkinson's disease, amyotrophic lateral sclerosis, and depression. However, whether the ...composition and diversity of gut microbiota is altered in patients with Alzheimer's disease (AD) remains largely unknown. In the present study, we collected fecal samples from 43 AD patients and 43 age- and gender-matched cognitively normal controls. 16S ribosomal RNA sequencing technique was used to analyze the microbiota composition in feces. The composition of gut microbiota was different between the two groups. Several bacteria taxa in AD patients were different from those in controls at taxonomic levels, such as Bacteroides, Actinobacteria, Ruminococcus, Lachnospiraceae, and Selenomonadales. Our findings suggest that gut microbiota is altered in AD patients and may be involved in the pathogenesis of AD.
Hepatocellular carcinoma (HCC) is a male‐dominant cancer, and androgen receptor (AR) has been linked to the pathogenesis of HCC. However, AR expression and its precise role in HCC remain ...controversial. Moreover, previous antiandrogen and anti‐AR clinical trials in HCC failed to demonstrate clinical benefits. In this study, we found that AR is overexpressed in the nucleus of approximately 37% of HCC tumors, which is significantly associated with advanced disease stage and poor survival. AR overexpression in HCC cells markedly alters AR‐dependent transcriptome, stimulates oncogenic growth, and determines therapeutic response to enzalutamide, a second generation of AR antagonist. However, AR inhibition evokes feedback activation of AKT‐mTOR (mechanistic target of rapamycin) signaling, a central regulator for cell growth and survival. On the other hand, mTOR promotes nuclear AR protein expression by restraining ubiquitin‐dependent AR degradation and enhancing AR nuclear localization, providing a mechanistic explanation for nuclear AR overexpression in HCC. Finally, cotargeting AR and mTOR shows significant synergistic anti‐HCC activity and decreases tumor burden by inducing apoptosis in vivo. Conclusion: Nuclear AR overexpression is associated with the progression and prognosis of HCC. However, enzalutamide alone has limited therapeutic utility attributed to feedback activation of the AKT‐mTOR pathway. Moreover, mTOR drives nuclear AR overexpression. Cotargeting AR and mTOR is a promising therapeutic strategy for HCC. (Hepatology 2018;67:2271‐2286).
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Porphyrins have planar and conjugated structures, good optical properties, and other special functional properties. Owing to these excellent properties, in recent years, porphyrins and their ...analogues have emerged as a multifunctional platform for chemical sensors. The rich chemistry of these molecules offers many possibilities for metal ions detection. This review mainly discusses two types of molecular porphyrin and porphyrin composite sensors for metal ions detection, because porphyrins can be functionalized to improve their functional properties, which can introduce more chemical and functional sites. According to the different application materials, the section of porphyrin composite sensors is divided into five sub-categories: (1) porphyrin film, (2) porphyrin metal complex, (3) metal-organic frameworks, (4) graphene materials, and (5) other materials, respectively.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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