部分还原氧化石墨烯的制备、 表征及对人宫颈癌HeLa细胞的体外杀伤作用

以氧化石墨烯(GO)为原料, 利用温和方法制备了3种不同还原程度的部分还原氧化石墨烯pRGO₁, pRGO₂和pRGO₃(pRGO_1—3)； 利用傅里叶变换红外光谱(FTIR)、 拉曼光谱(Raman)、 X 射线光电子能谱(XPS)、 紫外-可见光谱(UV-Vis)、 透射电子显微镜(TEM)和 EDS能谱对其结构和形貌进行了表征. 细胞实验结果表明, 无激光照射下pRGO_1—3本身的细胞毒性较低; 近红外(NIR)激光照射下pRGO_1—3通过光热和光毒性双重作用杀伤肿瘤细胞. 实验结果显示了pRGO 在肿瘤光热疗法和光动力疗法领域的应用潜力.     

Isoflavonoids from Astragalus membranaceus Hairy Roots

Chemistry of Natural Compounds -     

Identification of phytocompounds from Houttuynia cordata Thunb. as potential inhibitors for SARS-CoV-2 replication proteins through GC–MS/LC–MS characterization,molecular docking and molecular dynamics simulation

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a massive viral disease outbreak of international concerns. The present study is mainly intended to identify the bioactive phytocompounds from traditional antiviral herb Houttuynia cordata Thunb. as potential inhibitors for three main replication proteins of SARS-CoV-2, namely Main protease (Mpro), Papain-Like protease (PLpro) and ADP ribose phosphatase (ADRP) which control the replication process. A total of 177 phytocompounds were characterized from H. cordata using GC–MS/LC–MS and they were docked against three SARS-CoV-2 proteins (receptors), namely Mpro, PLpro and ADRP using Epic, LigPrep and Glide module of Schrödinger suite 2020-3. During docking studies, phytocompounds (ligand) 6-Hydroxyondansetron (A104) have demonstrated strong binding affinity toward receptors Mpro (PDB ID 6LU7) and PLpro (PDB ID 7JRN) with G-score of???7.274 and???5.672, respectively, while Quercitrin (A166) also showed strong binding affinity toward ADRP (PDB ID 6W02) with G-score -6.788. Molecular Dynamics Simulation (MDS) performed using Desmond module of Schrödinger suite 2020–3 has demonstrated better stability in the ligand–receptor complexes A104-6LU7 and A166-6W02 within 100 ns than the A104-7JRN complex. The ADME-Tox study performed using SwissADMEserver for pharmacokinetics of the selected phytocompounds 6-Hydroxyondansetron (A104) and Quercitrin (A166) demonstrated that 6-Hydroxyondansetron passes all the required drug discovery rules which can potentially inhibit Mpro and PLpro of SARS-CoV-2 without causing toxicity while Quercitrin demonstrated less drug-like properties but also demonstrated as potential inhibitor for ADRP. Present findings confer opportunities for 6-Hydroxyondansetron and Quercitrin to be developed as new therapeutic drug against COVID-19.

Graphic abstract

     

On lower iteration complexity bounds for the convex concave saddle point problems

Mathematical Programming - In this paper, we study the lower iteration complexity bounds for finding the saddle point of a strongly convex and strongly concave saddle point problem: $$\min _x\max...     

Quantum Watermark Algorithm Based on Maximum Pixel Difference and Tent Map

International Journal of Theoretical Physics - A new quantum watermark algorithm is presented by combining maximum pixel difference partitioning with the least significant bit substitution...     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.