KEYWORDSCOVID-19; SARS-CoV-2; Multidisciplinary therapeutic approachThe novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic threatening global public health. In the current paper, we describe our successful treatment of three COVID-19 pneumonia patients cases including severe cases and cases with mortality risk factors. One 32-year-old male COVID-19 patient was diagnosed with severe COVID-19 pneumonia and moderate ARDS. The second COVID-19 pneumonia patient had a history of diabetes and chronic bronchitis. The third case of COVID-19 pneumonia was an 82-year old female patient. All three cases had severe COVID pneumonia and therefore were aggressively managed with a multidisciplinary and personalized therapeutic approach that included nutritional support, antiviral pharmacotherapy, active control of comorbidities, prevention of complication development and psychological intervention. Our experience highlights the importance of the use of a multidisciplinary therapeutic approach that tailors to the specific condition of the patient in achieving a favorable clinical outcome.
In organic solar cells (OSCs), fluorine (F) substitution of conjugated polymers has a variety of effects on molecular properties and device performance. In this work, three conjugated polymers, namely PBDT-4F-BTs, PBDT-8F-FBTs, and PBDT-10F-FBTs, with 4, 8 and 10 fluorine atoms in the backbone were prepared and characterized. The conjugated polymers PBDT-4F-BTs, PBDT-8F-FBTs and PBDT-10F-FBTs showed the same highest occupied molecular orbital (HOMO) energy levels of À 5.58 eV, which did not decrease with the increasing number of F atoms in each repeat unit of polymers. As the number of fluorine atoms in each repeat unit of polymers in the backbone increases from 4 to 10, the dielectric constant (ε r ) increases from 4.5 to 6.2 at 1 kHz. The bimolecular compounding was suppressed by introducing F into the polymer backbone and influenced the device compounding kinetics of OSCs from the blend films of polymers paired with the phenyl-C 71 -butyric-acid-methyl ester (PC 71 BM). Thereby the fill factor (FF) and power conversion efficiency (PCE) of the OSCs devices have been improved, the fluorine atoms in each repeat unit of polymers backbone increased from 4 to 10, FF increased from 48.7 % to 70.0 %, and the corresponding PCE increased from 3.43 % to 6.46 %.
Background: MiR-541 acts as a tumor suppressor in some cancers. However, the role of miR-541 in regulating the chemosensitivity to cancer cells is still unclear. The aim of this study is to explore the effect of miR-541 on chemoresistance of pancreatic cancer (PCa) cells to gemcitabine-induced apoptosis.Methods: Gemcitabine-resistant Panc-1 and Capan-2 PCa cell lines (Panc-1/R and Capan-2/R) were established through long term exposure to gemcitabine. Effect of miR-541 on changing the sensitivity of Panc-1/R and Capan-2/R to gemcitabine-induced cytotoxicity was evaluated by MTT assays. Regulation of miR-541 on HAX-1 was confirmed by bioinformatics, western blot analysis and luciferase reporter assays. Cell apoptosis and mitochondrial membrane potential (MMP) was measured by flow cytometry analysis.Results: Comparison with Panc-1 and Capan-2, downregulation of miR-541 was observed in Panc-1/R and Capan-2/R cells. Overexpression of miR-541 was found to increase the cytotoxicity of gemcitabine to Panc-1/R and Capan-2/R cells. However, transfection with HAX-1 plasmid can abolish the effect of miR-541 on gemcitabine-induced cytotoxicity against Panc-1/R and Capan-2/R.Conclusion: Downregulation of miR-541 is responsible for development of gemcitabine resistance in PCa. Overexpression of miR-541 may represent a potential strategy to reverse the chemoresistance of PCa.
In modern complicated and changing manufacturing environments, unforeseen dynamic events such as machine breakdown or unexpected job arrival make required production resources unpredictable. The scheduling scheme is desired to maintain high stability in dynamic manufacturing environments. To cope with the classic disturbance of machine breakdown, a robust pro-active scheduling scheme is proposed by inserting the repair time into a disjunctive graph for reinforcement learning (IRDRL) in this paper. Firstly, a new mathematical model is developed to predict the machine fault which is assumed to be determined by service time and bearing load. Secondly, a disjunctive graph with breakdown information is designed to express the dynamic scheduling status. Then, an online scheduling framework is built based on the well-trained model through the proximal policy optimization (PPO) algorithm. Finally, compared with the classical methods such as the right-shift strategy and static model of reinforcement learning (RL), the proposed robust pro-active scheduling scheme is verified with high robustness, stability, and short running time.
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