Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a deep neural network (DNN)-based drug–target interaction (DTI) model and drug design specifications is proposed to design a potential multiple-molecule drug for the medical treatment of OSCC before clinical trials. First, we use big database mining to construct the candidate genome-wide genetic and epigenetic network (GWGEN) including a protein–protein interaction network (PPIN) and a gene regulatory network (GRN) for OSCC and non-OSCC. In the next step, real GWGENs are identified for OSCC and non-OSCC by system identification and system order detection methods based on the OSCC and non-OSCC microarray data, respectively. Then, the principal network projection (PNP) method was used to extract core GWGENs of OSCC and non-OSCC from real GWGENs of OSCC and non-OSCC, respectively. Afterward, core signaling pathways were constructed through the annotation of KEGG pathways, and then the carcinogenic mechanism of OSCC was investigated by comparing the core signal pathways and their downstream abnormal cellular functions of OSCC and non-OSCC. Consequently, HES1, TCF, NF-κB and SP1 are identified as significant biomarkers of OSCC. In order to discover multiple molecular drugs for these significant biomarkers (drug targets) of the carcinogenic mechanism of OSCC, we trained a DNN-based drug–target interaction (DTI) model by DTI databases to predict candidate drugs for these significant biomarkers. Finally, drug design specifications such as adequate drug regulation ability, low toxicity and high sensitivity are employed to filter out the appropriate molecular drugs metformin, gefitinib and gallic-acid to combine as a potential multiple-molecule drug for the therapeutic treatment of OSCC.     

Precision Killing of Sinoporphyrin Sodium-Mediated Photodynamic Therapy against Malignant Tumor Cells

Photodynamic therapy (PDT) has significant advantages in the treatment of malignant tumors, such as high efficiency, minimal invasion and less side effects, and it can preserve the integrity and quality of the organs. The power density, irradiation time and photosensitizer (PS) concentration are three main parameters that play important roles in killing tumor cells. However, until now, the underlying relationships among them for PDT outcomes have been unclear. In this study, human malignant glioblastoma U-118MG and melanoma A375 cells were selected, and the product of the power density, irradiation time and PS concentration was defined as the total photodynamic parameter (TPP), in order to investigate the mechanisms of PS sinoporphyrin sodium (DVDMS)-mediated PDT (DVDMS-PDT). The results showed that the survival rates of the U-118MG and A375 cells were negatively correlated with the TPP value in the curve, and the correlation exactly filed an e-exponential function. Moreover, according to the formula, we realized controllable killing effects of the tumor cells by randomly adjusting the three parameters, and we finally verified the accuracy and repeatability of the formula. In conclusion, the establishment and implementation of a newly functional relationship among the PDT parameters are essential for predicting PDT outcomes and providing personalized precise treatment, and they are contributive to the development of PDT dosimetry.     

Estimation of fracture density and orientation from azimuthal elastic impedance difference through singular value decomposition

Accurate estimation of fracture density and orientation is of great significance for seismic character-ization of fractured reservoirs.Here,we propose a novel m...     

简析利用衰减控制修正不规格网格多面函数在绘制降水等值线中的缺陷

本文采用不规则网格多面函数技术,通过增加衰减控制,很好地解决不规则网格多面函数等值线在处理降水等值线趋势一直延续的缺陷.算法一般步骤首先是根据散点划分网格,其次是散点插值到计算网格节点,再次是根据指定的等值线值,检索网格的各边节点.按确定的搜索算法连接等值线.     

浅谈教育建筑综合体-以广州中匮药大学国际楼为例

当前校园规划出现了复杂性导向,在校园规划的发展过程中,建筑单体也出现了混合功能的倾向.该文就此倾向进行剖析,并结合广州中医药大学国际楼实际工程提出教育建筑综合体的设计特点.     

煤矿避难硐室热环境控制范围探讨

基于国内外矿井避难硐室环境控制技术的研究现状,比较了国内外关于避难硐室环境控制条款规定,探讨了环境控制参数的允许范围,并从建设成本及人员安全角度出发,分析了目前针对避难硐室空气品质控制技术和温度控制技术的不足,指出了未来避难硐室环境控制技术的研究方向：①制订合理的环境参数允许范围;②基于矿井压风的CO浓度多种控制技术的协同作用;③CO₂被动化学吸附技术;④多重复合控温技术。

     

我国稀土产业现状及发展趋势(上)

这是一篇矿物加工工程领域的论文。本文以河南某稀土及伴生萤石资源为研究对象,依据工艺矿物学和小型选矿实验所得的研究结果,进行了处理量为60 kg/h的扩大连续实验。通过化学分析、AMICS镜下鉴定等分析手段发现,该原矿样品中主要有用元素REO含量为1.53%,CaF₂含量为18.22%,稀土选别目标矿物为氟碳铈矿和氟碳钙铈矿;采用“稀土、萤石混合浮选-稀土、萤石分离”的工艺对矿石中的稀土、萤石进行回收,实验室小型实验取得了良好指标。在此基础上,对原矿样品进行了扩大连续实验,最终获得了REO品位52.54%、回收率51.15%的稀土精矿和CaF₂品位94.76%、回收率60.80%的萤石精矿,精矿产品指标良好,扩大实验结果较为理想,初步实现了稀土伴生萤石的综合回收利用,有助于为企业生产提供技术支撑,有助于为同类型稀土及共伴生资源矿床的综合开发利用提供依据。     

废弃锂电池电极材料中有价金属的赋存状态

这是一篇冶金工程领域的论文。以废旧磷酸铁锂电池正极粉为对象,开展了以Na₂S₂O₈作为氧化剂,并添加低浓度乙酸作为浸出剂选择性浸锂的研究,考查了Na₂S₂O₈加入量、乙酸浓度、浸出温度、浸出液固比和浸出时间等对锂选择性浸出影响。在乙酸浓度0.3 mol/L、Na₂S₂O₈加入量为理论量的1.1倍,浸出液固比10 mL/g、室温浸出2 h条件下,锂、铁、磷的浸出率分别为98.05%、4.49%和2.46%。     

构造煤的成因—属性分类

为了研究原生煤和构造煤的吸附扩散特性,采用甲烷吸附装置和解吸装置对2种煤样进行了实验。结果表明,构造煤的极限甲烷吸附量是原生煤的1.18倍,并且在相同甲烷吸附压力下构造煤的吸附能力强于原生煤。当甲烷吸附平衡压力为0.74 MPa和2 MPa时,构造煤的固定扩散系数分别是原生煤的7.3倍和4.5倍,表明构造煤的初始气体扩散能力远高于原生煤。2种煤样的时变扩散系数都随着解吸时间的推移先快速降低后趋于稳定。构造煤的扩散衰减系数在0.74 MPa和2 MPa气体平衡压力下分别达到了96.6%和95.8%,远大于原生煤的扩散衰减系数38.1%和45.7%。