A novel prognostic gene signature,nomogram and immune landscape based on tanshinone IIA drug targets for hepatocellular carcinoma:Comprehensive bioinformatics analysis and in vitro experiments

Tanshinone IIA,one of the main ingredients of Danshen,is used to treat hepatocellular carcinoma(HCC).However,potential targets of the molecule in the therapy of HCC are unknown.Methods:In this study,we collected the tanshinone IIA targets from public databases for investigation.We screened differentially expressed genes(DEGs)across HCC and normal tissues using mRNA expression profiles from The Cancer Genome Atlas(TCGA).Univariate Cox regression analysis and least absolute shrinkage and selection operator(LASSO)Cox regression models were used to identify and construct the prognostic gene signature.Results:Finally,we discovered common genes across tanshinone IIA targets and HCC DEGs.We reported Fatty acid binding protein-6(FABP6),Polo-like Kinase 1(PLK1),deoxythymidylate kinase(DTYMK),Uridine Cytidine Kinase 2(UCK2),Enhancer of Zeste Homolog 2(EZH2),and Cytochrome P4502C9(CYP2C9)as components of a gene signature.The six-gene signature’s prognostic ability was evaluated using the Kaplan-Meier curve,time-dependent receiver operating characteristic(ROC),multivariate Cox regression analysis,and the nomogram.The mRNA level and protein expression of UCK2 were experimentally validated after treatment with different concentrations of tanshinone IIA in HEPG2 cells.CIBERSORTx,TIMER2.0,and GEPIA2 tools were employed to explore the relationship between the prognostic signature and immune cell infiltration.Conclusion:We established a six-gene signature as a reliable model with significant therapeutic possibility for prognosis and overall survival estimation in HCC patients,which might also benefit medical decision-making for appropriate treatment.

Software Defect Prediction Method Based on Stable Learning

The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor.In previous software defect prediction studies,transfer learning was effective in solving the problem of inconsistent project data distribution.However,target projects often lack sufficient data,which affects the performance of the transfer learning model.In addition,the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model.To address these problems,this article propose a software defect prediction method based on stable learning(SDP-SL)that combines code visualization techniques and residual networks.This method first transforms code files into code images using code visualization techniques and then constructs a defect prediction model based on these code images.During the model training process,target project data are not required as prior knowledge.Following the principles of stable learning,this paper dynamically adjusted the weights of source project samples to eliminate dependencies between features,thereby capturing the“invariance mechanism”within the data.This approach explores the genuine relationship between code defect features and labels,thereby enhancing defect prediction performance.To evaluate the performance of SDP-SL,this article conducted comparative experiments on 10 open-source projects in the PROMISE dataset.The experimental results demonstrated that in terms of the F-measure,the proposed SDP-SL method outperformed other within-project defect prediction methods by 2.11%-44.03%.In cross-project defect prediction,the SDP-SL method provided an improvement of 5.89%-25.46% in prediction performance compared to other cross-project defect prediction methods.Therefore,SDP-SL can effectively enhance within-and cross-project defect predictions.

网络舆论中隐性词汇的情感意涵研究

网络舆论研究大多关注显性情感,对隐性情感的分析较为缺乏。本研究使用加权词向量方法和双向长短时记忆网络(Bi-LSTM)方法进行情感多分类研究,进一步挖掘网络舆论中隐性词汇的情感意涵。研究首先以词频-逆文档频率(TF-IDF)理论思想为基础计算词向量的情感权重,然后对词向量进行情感加权,并将加权后的词向量输入Bi-LSTM模型进行特征计算,最后使用Softmax函数完成情感的多分类预测。同时通过回溯的方式,对情感权重值较高的代表性词汇(隐性词汇)进行情感意涵分析。结果表明,该方法不仅能够有效提升多类情感判别的准确率,还可以通过这些代表性词汇加深对隐性词汇中情感意涵的认识和把握,这对于我国这一具有自我审查文化传统的社会及其舆论的把握具有重要意义。

年支正五行、六气及其正化对化的天文学背景探讨

年支正五行、六气及其正化对化是中医学的理论基础。二十八宿背景下的木星12年周期视运动和火星2年周期视运动对地和人体影响每年都不同,应有不同的12年支气。木星视运动可看成p类木公转运动和J绕p的类日视运动的复合运动。年支正五行的天文学背景是二十八宿背景下的木星类公转运动和火星。火星使年支分阴阳,木星类公转运动的本征五行是年支正五行的基础,参、角、箕、心、璧等宿的突出亮度在夜晚对地、对人体的影响是辰戌丑未属土的关键机制。方位相对的年支类日视运动、年支阴阳相同,但类日视运动所叠加的类木公转方向相反且所处方位的星宿不同。先哲们依经验把子午、丑未、寅申、卯酉、辰戌、巳亥6类年支气五行特性相同部分分别归于少阴君火、太阴湿土、少阳相火、阳明燥金、太阳寒水、厥阴风木,类间差别用正化对化区分。这样,6对年支类日视运动及火星阴阳就是六气五行的天文学背景,年支正五行就是六气正化对化的实质,二十八宿背景下的木星类公转运动和火星就是六气正化对化的天文学背景。每一年支对应的"气",既具有司天、在泉的五行特性,同时又具有正五行的特性。运气加临的气就是这种"气",平气应由岁运与年支正五行、司天、在泉后3种力量综合较量中评定。《素问》及后世医家把年支正五行、司天、在泉三者单列分别与岁运评定平气是错误的。

The effects of microRNA-34a regulating Notch-1/NF-κB signaling pathway on lipopolysaccharide-induced human umbilical vein endothelial cells

BACKGROUND: Notch-1/NF-κB signaling plays a key role in the cecal ligation and puncture(CLP)-induced sepsis. This study aims to investigate the intervention effects of microRNA-34a(miR-34a) lentivirus regulating Notch-1/NF-κB signaling pathway on lipopolysaccharide(LPS)-induced human umbilical vein endothelial cells(HUVEC).METHODS: HUVEC were divided into four groups as the following: they were infected with negative control lentivirus(NC group) or miR-34a lentivirus(OE group); LPS(1 g/mL) was added on the third day on the basis of NC group and OE group for 24 hours(NC+LPS group or OE+LPS group). The levels of TNF-α, IL-1β, IL-6, and IL-10 in the cell supernatants, and the mRNA and protein expression of Notch-1 and NF-κB in the HUVEC were evaluated.RESULTS: After 24 hours, the levels of TNF-α, IL-1β, IL-6 in the cell supernatants and the protein expression of NF-κB from NC+LPS group were significantly higher than those of NC group, but IL-10 level and the protein expression of Notch-1 in NC+LPS group were the opposite. After intervention of miR-34a lentivirus, the cell supernatants TNF-α and the protein expression of NF-κB in OE+LPS group after 24 hours markedly decreased compared to NC+LPS group. While the cell supernatants IL-1β and IL-6 and the mRNA expression of NF-κB slightly decreased in OE+LPS group, IL-10 and the mRNA and protein expression of Notch-1 were the opposite.CONCLUSION: miR-34a regulating Notch-1/NF-κB signaling pathway can reduce the HUVEC damage caused by LPS stimulation.

Proximity Chemistry in Living Systems

Enzyme-and catalyst-generated reactive species have been leveraged in the past decade to covalently label biomolecules within a short range of a defined site or space inside cells or at the cell–cell interface.Due to their high spatial resolution,such proximity labeling strategies have been coupled with various bioanalytical techniques for dissecting dynamic and complex biological processes.Here,we review the development of enzyme-and catalyst-triggered proximity chemistry and their applications to identifying protein interaction networks as well as cell–cell communications in living systems.

Differentiating gastric cancer and gastric lymphoma using texture analysis(TA)of positron emission tomography(PET)

Background:Texture analysis(TA)can quantify intra-tumor heterogeneity using standard medical images.The present study aimed to assess the application of positron emission tomography(PET)TA in the differential diagnosis of gastric cancer and gastric lymphoma.Methods:The pre-treatment PET images of 79 patients(45 gastric cancer,34 gastric lymphoma)between January 2013 and February 2018 were retrospectively reviewed.Standard uptake values(SUVs),first-order texture features,and second-order texture features of the grey-level co-occurrence matrix(GLCM)were analyzed.The differences in features among different groups were analyzed by the two-way Mann-Whitney test,and receiver operating characteristic(ROC)analysis was used to estimate the diagnostic efficacy.Results:InertiaGLCM was significantly lower in gastric cancer than that in gastric lymphoma(4975.61 vs.11,425.30,z=-3.238,P=0.001),and it was found to be the most discriminating texture feature in differentiating gastric lymphoma and gastric cancer.The area under the curve(AUC)of inertiaGLCM was higher than the AUCs of SUVmax and SUVmean(0.714 vs.0.649 and 0.666,respectively).SUVmax and SUVmean were significantly lower in low-grade gastric lymphoma than those in high grade gastric lymphoma(3.30 vs.11.80,2.40 vs.7.50,z=-2.792 and-3.007,P=0.005 and 0.003,respectively).SUVs and first-order greylevel intensity features were not significantly different between low-grade gastric lymphoma and gastric cancer.EntropyGLCM12 was significantly lower in low-grade gastric lymphoma than that in gastric cancer(6.95 vs.9.14,z=-2.542,P=0.011)and had an AUC of 0.770 in the ROC analysis of differentiating low-grade gastric lymphoma and gastric cancer.Conclusions:InertiaGLCM and entropyGLCM were the most discriminating features in differentiating gastric lymphoma from gastric cancer and low-grade gastric lymphoma from gastric cancer,respectively.PET TA can improve the differential diagnosis of gastric neoplasms,especially in tumors with similar degrees of fluorodeoxyglucose uptake.

Mechanisms of Pb(Ⅱ) coprecipitation with natrojarosite and its behavior during acid dissolution

Lead(Pb) coprecipitation with jarosite is common in natural and engineered environments,such as acid mine drainage(AMD) sites and hydrometallurgical industry. Despite the high relevance for environmental impact, few studies have examined the exact interaction of Pb with jarosite and the dissolution behavior of each phase. In the present work, we demonstrate that Pb mainly interacts with jarosite in four modes, namely incorporation, occlusion,physically mixing, and chemically mixing. For comparison, the four modes of Pb-bearing natrojarosite were synthesized and characterized separately. Batch dissolution experiments were undertaken on these synthetic Pb-bearing natrojarosites under pH_(2) to simulate the AMD environments. The introduction of Pb decreases the final Fe releasing efficiency of jarosite-type compounds from 18.18% to 3.45%-5.01%, showing a remarkable inhibition of their dissolution. For Pb releasing behavior, PbSO_(4) dissolves in preference to Pb-substituted natrojarosite, i.e.,(Na, Pb)-jarosite, which primarily results in the sharp increase of Pb releasing concentration(> 40 mg/L). PbSO_(4) occlusion by jarosite-type compounds can significantly reduce the release of Pb. The results of this study could provide useful information regarding Fe and Pb cycling in acidic natural and engineered environments.