Unraveling the therapeutic mechanisms of myristic acid and luteolin 7-rutinoside in oral cancer: insights from network pharmacology and molecular docking analysis

Background:The compound Luteolin-7-rutinoside(L7R)is a flavone derivative of luteolin,predominantly identified in plant species belonging to the families Asteraceae.Conversely,Myristic acid is characterized by its structure as a 14-carbon,unsaturated fatty acid.In this investigation,we endeavor to elucidate the putative mechanisms underlying the therapeutic effects of Myristic Acid and Luteolin 7-rutinoside in the context of oral cancer treatment,employing network pharmacology coupled with molecular docking methodologies.Methods:The protein targets of Myristic Acid and Luteolin 7-rutinoside were identified through a search on the Swiss Target Database.Subsequently,a compound-target network was constructed using Cytoscape 3.9.1.Targets associated with OC were retrieved from the OMIM and GeneCards databases.The overlap between compound targets and OC-related targets was determined,and the resulting shared targets were subjected to protein-protein interaction(PPI)network analysis using the STRING database.Additionally,gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted on the identified targets.Molecular docking were performed to investigate the interactions between the core target and the active compound.Results:The component target network comprises 103 nodes and 102 edges.Among the proteins in the protein-protein interaction(PPI)network,those with higher degrees are TNF,PPARG,and TP53.Analysis through Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways indicates that the treatment of OC with Myristic Acid and Luteolin 7-rutinoside primarily involves the regulation of miRNA transcription and inflammatory response.The identified signaling pathways include Pathways in cancer,PPAR signaling pathway,EGFR signaling pathway,and TNF signaling pathway.Molecular docking studies reveal that Luteolin 7-rutinoside and Myristic acid exhibit higher affinity towards TNF,PPARG,TP53,and EGFR.Conclusion:This study reveals the potential molecular mechanism of Myristic Acid and Luteolin 7-rutinoside in the treatment of oral cancer,and provides a reference for subsequent basic research.

Attention-Based Residual Dense Shrinkage Network for ECG Denoising

Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac diagnosis.However,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affectsthe subsequent pathological analysis.Therefore,the effective removal of the noise from ECG signals has becomea top priority in cardiac diagnostic research.Aiming at the problem of incomplete signal shape retention andlow signal-to-noise ratio(SNR)after denoising,a novel ECG denoising network,named attention-based residualdense shrinkage network(ARDSN),is proposed in this paper.Firstly,the shallow ECG characteristics are extractedby a shallow feature extraction network(SFEN).Then,the residual dense shrinkage attention block(RDSAB)isused for adaptive noise suppression.Finally,feature fusion representation(FFR)is performed on the hierarchicalfeatures extracted by a series of RDSABs to reconstruct the de-noised ECG signal.Experiments on the MIT-BIHarrhythmia database and MIT-BIH noise stress test database indicate that the proposed scheme can effectively resistthe interference of different sources of noise on the ECG signal.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

Damage Diagnosis of Bleacher Based on an Enhanced Convolutional Neural Network with Training Interference

Bleachers play a crucial role in practical engineering applications, and any damage incurred during their operationposes a significant threat to the safety of both life and property. Consequently, it becomes imperative to conductdamage diagnosis and health monitoring of bleachers. The intricate structure of bleachers, the varied types ofpotential damage, and the presence of similar vibration data in adjacent locations make it challenging to achievesatisfactory diagnosis accuracy through traditional time-frequency analysis methods. Furthermore, field environmentalnoise can adversely impact the accuracy of bleacher damage diagnosis. To enhance the accuracy and antinoisecapabilities of bleacher damage diagnosis, this paper proposes improvements to the existing ConvolutionalNeural Network with Training Interference (TICNN). The result is an advanced Convolutional Neural Networkmodel with superior accuracy and robust anti-noise capabilities, referred to as Enhanced TICNN (ETICNN).ETICNN autonomously extracts optimal damage-sensitive features from the original vibration data. To validatethe superiority of the proposed ETICNN, experiments are conducted using the bleacher model from Qatar Universityas the subject. Comparative studies under identical experimental conditions involve TICNN, Deep ConvolutionalNeural Networks with wide first-layer kernels (WDCNN), and One-Dimensional ConvolutionalNeural Network (1DCNN). The experimental findings demonstrate that the ETICNN model achieves the highestaccuracy, approximately 99%, and exhibits robust classification abilities in both Phases I and II of the damagediagnosis experiments. Simultaneously, the ETICNN model demonstrates strong anti-noise capabilities, outperformingTICNN by 3% to 4% and surpassing other models in performance.

PKHD1L1 blocks the malignant behavior of lung adenocarcinoma cells and restricts tumor growth by regulating CBX7

Objective:To explore the role of polycystic kidney and hepatic disease 1-like 1(PKHD1L1)in lung adenocarcinoma(LUAD).Methods:Bioinformatics tools were utilized to examine the clinical profile of PKHD1L1 and chromobox protein homolog 7(CBX7)in LUAD.The Cell Counting Kit-8,colony formation,terminal deoxynucleotidyl transferase dUTP nick end labeling,Transwell,and wound-healing assays were carried out to assess the proliferative,apoptotic,invasive,and migrative capacities of the cells.Furthermore,the interrelation between PKHD1L1 and CBX7 was validated using a co-immunoprecipitation assay.A LUAD mice model was constructed by subcutaneous injection of A549 cells.Finally,immunohistochemical staining was performed to evaluate CBX7 and Ki67 expression.Results:PKHD1L1 was downregulated in LUAD and predicted dismal outcomes in patients with LUAD.PKHD1L1 upregulation repressed the proliferative,invasive,and migrative capabilities of A549 cells and exacerbated the apoptotic rate.Additionally,PKHD1L1 may bind to CBX7 and positively modulate CBX7 expression.CBX7 deletion partly abrogated the effects of PKHD1L1 upregulation on the cellular biological activities in A549 cells.Furthermore,the PKHD1L1/CBX7 axis regulates the Hippo signaling pathway in A549 cells.PKHD1L1 restricted tumor growth in LUAD xenograft mice;this was partly abolished by CBX7 knockdown.Conclusion:PKHD1L1 can hinder LUAD progression by regulating CBX7-mediated Hippo signaling.

Action Mechanism of Components from Gardenia jasminoides on Eye Skin Based on Network Pharmacology

[Objectives]To explore the pharmacological effects of Gardenia jasminoides and its potential benefits on eye skin.[Methods]TCMSP and SymMap databases were used to screen the active components and corresponding targets of G.jasminoides.Human eye skin-related targets were screened,and the active component-target network and protein-protein interaction(PPI)network were established.Gene ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed.[Results]Twenty-six active compounds were screened out from G.jasminoides,and 277 targets were obtained.From the Gencards database,26652 disease targets were retrieved and 205 related gene targets were screened.The active component-action target network of G.jasminoides constructed by Cytoscape software revealed the potential of G.jasminoides to play a role in multiple biological pathways.In addition,PPI-network analysis,GO function analysis and KEGG pathway enrichment analysis revealed that the active components of G.jasminoides mainly regulate the biological processes such as inflammatory response,oxidative stress and apoptosis,involving MAPK,NF-κB and other important signaling pathways.[Conclusions]This study provides a theoretical basis for the eye skin protection of G.jasminoides and an important clue for future drug development.

Network pharmacology and molecular docking analysis reveal insights into the molecular mechanism of Gualou Qumai Wan in clear cell renal cell carcinoma

Background:To initially clarify the potential therapeutic targets and pharmacological mechanism regarding Gualou Qumai Wan(GQW),a kind of traditional Chinese medicine(TCM),in clear cell renal cell carcinoma(ccRCC)by virtue of the network pharmacology analysis and molecular docking analysis.Methods:The screening of bioactive components and targets of GQW was based on the Traditional Chinese Medicine System Pharmacology(TCMSP)and the UniProt platform served for standardizing their targets.Online Mendelian Inheritance in Man(OMIM),PharmGkb,TTD,DrugBank and GeneCards databases were searched to collect the disease targets of ccRCC.Cytoscape assisted in constructing herb-compound-target(H-C-T)networks.The STRING database was searched for constructing the target protein-protein interaction(PPI)networks,while the R programming language served for analyzing GO functional terms and the KEGG pathways related to potential targets.Analyses of core genes related to survival and tumor microenvironment(TME)were conducted respectively based on the GEPIA2 database and TIMER 2.0 database.Human Protein Atlas(HPA)and The Cancer Genome Atlas(TCGA)helped to obtain core genes’protein expression as well as transcriptome expression level.Autodock Vina software validated the molecular docking regarding GQW components and pivotal targets.Results:The constructed H-C-T networks mainly had 33 compounds and 65 targets.A topological analysis of the PPI network identified that ESR1,AKT1,HIF1A,PTGS2,TP53 and VEGFA serve as core targets in the way GQW affects ccRCC.According to the GO and KEGG pathway enrichment analyses,the effects of GQW are mediated by genes related to hypoxia and oxidative stress as well as the Chemical carcinogenesis-receptor activation and PI3K-Akt signaling pathways.AKT1 shows a close relation to the recruitment of various immune cells and can remarkably affect disease prognosis according to reports.Molecular docking and molecular dynamics simulations showed that diosgenin has higher affinity with core targets.Conclusion:The study makes a comprehensive explanation of the biological activity,potential targets,as well as molecular mechanism regarding GQW against ccRCC,which promisingly assists in revealing the action mechanism of TCM formulae in disease treatment and the respective and scientific basis.

雷公藤内酯醇通过调控miR-142-3p/HSP70通路抑制人乳腺癌MCF-7细胞增殖、侵袭和迁移

目的:探究雷公藤内酯醇(TP)通过miR-142-3p/HSP70信号通路对人乳腺癌MCF-7细胞恶性生物学行为的影响。方法:常规培养MCF-7细胞,将其分为6组:对照组、TP组、miR-142-3p inhibitor组、TP+inhibitor组、miR-142-3p mimic组和TP+mimic组,用转染试剂将相应的核酸或质粒转染MCF-7细胞。qPCR法、EdU细胞增殖实验、Transwell小室实验、细胞划痕实验、WB法分别检测转染后各组MCF-7细胞中miR-142-3p和HSP70 mRNA的表达,MCF-7细胞的增殖、侵袭、迁移能力和HSP70蛋白表达水平。结果:TP或miR-142-3p过表达能显著促进MCF-7细胞中miR-142-3p和HSP70的表达,敲减miR-142-3p则可明显抑制MCF-7细胞中miR-142-3p和HSP70的表达,TP可逆转由敲减miR-142-3p对MCF-7细胞中miR-142-3p和HSP70表达的影响;TP、过表达miR-142-3p均可明显抑制MCF-7细胞的增殖、迁移和侵袭能力(均P<0.05),敲减miR-142-3p则均可促进MCF-7细胞的增殖、迁移和侵袭能力(均P<0.05),TP可逆转由敲减miR-142-3p对MCF-7细胞恶性生物学行为的影响(均P<0.05)。结论:TP可通过调控miR-142-3p/HSP70信号通路,进而抑制MCF-7细胞的增殖、侵袭和迁移能力。

PRMT7通过调控Notch信号转导通路抑制膀胱癌细胞增殖和迁移

背景与目的:膀胱癌是常见的泌尿系统恶性肿瘤之一,蛋白质精氨酸甲基转移酶7(protein arginine methyltransferase 7,PRMT7)在消化道肿瘤中的作用已有研究报道,但在膀胱癌中的生物学作用及机制尚未明确,本文旨在探究PRMT7对人膀胱癌细胞增殖和迁移能力的影响及其可能的作用机制。方法:体外培养人膀胱癌细胞系5637、T24、RT112、UM-UC-3和输尿管上皮永生化细胞系SV-HUC-1,采用蛋白质印迹法(Western blot)检测PRMT7的表达情况。采用RNA干扰技术沉默PRMT7基因的表达,设立阴性对照组(si-NC)及实验组(siPRMT7#1、siPRMT7#2),采用质粒转染法过表达PRMT7基因,设立阴性对照组(p-PCMV3)及实验组(p-PRMT7)。采用实时荧光定量聚合酶链反应(real-time fluorescence quantitative polymerase chain reaction,RTFQ-PCR)及Western blot验证PRMT7的转染效率,采用细胞计数试剂盒-8(cell counting kit-8,CCK-8)和集落形成实验检测细胞增殖能力,采用transwell实验检测细胞迁移能力,采用Western blot检测增殖和迁移相关靶蛋白Cyclin D1、CDK4和MMP9以及Notch信号转导通路关键蛋白Notch1、HEY1和Hes1的表达情况。使用转染siPRMT7#2的细胞加入Notch信号特异性抑制剂γ-分泌酶抑制剂DAPT,进一步验证PRMT7在膀胱癌中的表达情况。结果:Western blot结果显示,PRMT7在膀胱癌细胞中低表达(P<0.05)。在5637细胞中沉默PTMT7后,细胞增殖和迁移能力显著增强(P<0.05),增殖和迁移相关靶蛋白Cyclin D1、CDK4和MMP9以及Notch信号通路关键蛋白Notch1、HEY1和Hes1的表达明显增加(P<0.05);而在T24细胞中过表达PRMT7后,呈相反的趋势。使用DAPT后,明显逆转了PRMT7在膀胱癌细胞中的表达。结论:PRMT7抑制膀胱癌细胞增殖和迁移,其作用机制与Notch信号转导通路有关。

Study of the roles of caspase-3 and nuclear factor kappa B in myenteric neurons in a P2X7 receptor knockout mouse model of ulcerative colitis

BACKGROUND The literature indicates that the enteric nervous system is affected in inflammatory bowel diseases(IBDs)and that the P2X7 receptor triggers neuronal death.However,the mechanism by which enteric neurons are lost in IBDs is unknown.AIM To study the role of the caspase-3 and nuclear factor kappa B(NF-κB)pathways in myenteric neurons in a P2X7 receptor knockout(KO)mouse model of IBDs.METHODS Forty male wild-type(WT)C57BL/6 and P2X7 receptor KO mice were euthanized 24 h or 4 d after colitis induction by 2,4,6-trinitrobenzene sulfonic acid(colitis group).Mice in the sham groups were injected with vehicle.The mice were divided into eight groups(n=5):The WT sham 24 h and 4 d groups,the WT colitis 24 h and 4 d groups,the KO sham 24 h and 4 d groups,and the KO colitis 24 h and 4 d groups.The disease activity index(DAI)was analyzed,the distal colon was collected for immunohistochemistry analyses,and immunofluorescence was performed to identify neurons immunoreactive(ir)for calretinin,P2X7 receptor,cleaved caspase-3,total caspase-3,phospho-NF-κB,and total NF-κB.We analyzed the number of calretinin-ir and P2X7 receptor-ir neurons per ganglion,the neuronal profile area(μm^(2)),and corrected total cell fluorescence(CTCF).RESULTS Cells double labeled for calretinin and P2X7 receptor,cleaved caspase-3,total caspase-3,phospho-NF-κB,or total NF-κB were observed in the WT colitis 24 h and 4 d groups.The number of calretinin-ir neurons per ganglion was decreased in the WT colitis 24 h and 4 d groups compared to the WT sham 24 h and 4 d groups,respectively(2.10±0.13 vs 3.33±0.17,P<0.001;2.92±0.12 vs 3.70±0.11,P<0.05),but was not significantly different between the KO groups.The calretinin-ir neuronal profile area was increased in the WT colitis 24 h group compared to the WT sham 24 h group(312.60±7.85 vs 278.41±6.65,P<0.05),and the nuclear profile area was decreased in the WT colitis 4 d group compared to the WT sham 4 d group(104.63±2.49 vs 117.41±1.14,P<0.01).The number of P2X7 receptor-ir neurons per ganglion was decreased in the WT colitis 24 h and 4 d groups compared to the WT sham 24 h and 4 d groups,respectively(19.49±0.35 vs 22.21±0.18,P<0.001;20.35±0.14 vs 22.75±0.51,P<0.001),and no P2X7 receptor-ir neurons were observed in the KO groups.Myenteric neurons showed ultrastructural changes in the WT colitis 24 h and 4 d groups and in the KO colitis 24 h group.The cleaved caspase-3 CTCF was increased in the WT colitis 24 h and 4 d groups compared to the WT sham 24 h and 4 d groups,respectively(485949±14140 vs 371371±16426,P<0.001;480381±11336 vs 378365±4053,P<0.001),but was not significantly different between the KO groups.The total caspase-3 CTCF,phospho-NF-κB CTCF,and total NF-κB CTCF were not significantly different among the groups.The DAI was recovered in the KO groups.Furthermore,we demonstrated that the absence of the P2X7 receptor attenuated inflammatory infiltration,tissue damage,collagen deposition,and the decrease in the number of goblet cells in the distal colon.CONCLUSION Ulcerative colitis affects myenteric neurons in WT mice but has a weaker effect in P2X7 receptor KO mice,and neuronal death may be associated with P2X7 receptor-mediated caspase-3 activation.The P2X7 receptor can be a therapeutic target for IBDs.

基于网络药理学探讨山奈酚-7-O-新橘皮糖苷抗前列腺癌的作用机制

目的 探讨山奈酚-7-O-新橘皮糖苷(kaempferol-7-O-neohesperidoside, K7ON)抗前列腺癌细胞(prostate cancer, PCa)的作用及潜在分子机制。方法 采用CCK-8法检测K7ON对PCa细胞PC3、DU145、C4-2和LNCap增殖的影响;应用细胞划痕实验检测K7ON对DU145细胞迁移能力的影响;SuperPred等数据库获取K7ON和PCa的靶点;从Venny在线平台获取K7ON与PCa的共同靶点,应用String和Cytoscape构建蛋白相互作用(protein-protein interaction, PPI)网络;通过DAVID数据库进行GO和KEGG功能富集分析,构建“药物-靶点-疾病-通路”网络模型。通过流式细胞术检测K7ON对PCa细胞周期的影响;采用Western blot法检测周期相关蛋白Skp2、p27和p21蛋白的表达;应用Sybyl X2.0将Skp2与K7ON进行分子对接。结果 K7ON可显著抑制PCa细胞的增殖和迁移能力。筛选出药物与疾病的交集靶点共34个,其中Skp2、p27等是K7ON治疗PCa的关键靶点,进一步的GO和KEGG功能功能富集表明其机制主要与细胞周期相关。流式细胞术结果表明,K7ON处理可使DU145细胞周期阻滞在S期。与对照组相比,Skp2蛋白表达水平明显下调,p27和p21的蛋白表达水平上调。分子对接结果显示K7ON与受体Skp2具有较好的结合能力。结论 K7ON可抑制PCa细胞的增殖和迁移,使细胞周期阻滞在S期,其机制可能与调控Skp2-p27/p21信号通路相关。

Mechanism of AiTongXiao granule in the treatment of hepatocellular carcinoma based on network pharmacology and rat transplanted liver cancer model

Objective:To investigate the mechanism of action and material basis of AiTongXiao granule in the treatment of hepatocellular carcinoma(HCC)based on network pharmacology and transplanted liver cancer rat model.Methods:TCMSP database was used to screen out effective components and its corresponding potential pharmaceutical targets,and databases including Gene Cards,OMIM,Drugbank and TTD were further used to collect HCC-related drug targets.The intersecting targets were obtained by mapping the drug and disease targets.The component-targets network was constructed and visualized by Cytoscape 3.8.2 software.Protein-protein interaction(PPI)network was built by STRING online platform,and the topological relationship and core targets was analyzed and screened by using CytoNCA software.In addition,Metascape database was used to perform gene ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis of the core targets.At last,rat liver transplanted liver cancer model was established by using Walker-256 cell line and treated by AiTongXiao granule for 15 days.Western blot was used to further compare the expression levels of AKT,pAKT,p53,p-p53,ERK1/2 and ERK1/2 in the tumor between treatment group and the control group.Results:257 active components were obtained from AiTongXiao granule,corresponding to 294 drug targets.Meanwhile,233 of the 7993 HCC disease targets were screened out between AiTongXiao granule drug and HCC disease targets.11 core targets including AKT1,IL6,TP53,MAPK3,TNF,JUN,CASP3,MAPK1,MYC,PTGS2,MMP9 were further obtained by median screening.GO and KEGG analysis results showed that these core targets enriched to HBV,TNF and cancer related pathways.The rat transplanted liver cancer model results indicated significant down regulation for AKT,p-AKT,pERK1/2,and significant up regulation of p-p53 after AiTongXiao granule treatment(P<0.05).Conclusion:AiTongXiao granule could act to multiple cancer related pathways,and AKT,p53 and ERK1/2 were validated to be regulated by ATXF in rat model.The mechanism may be through the regulation of the above signaling pathways to exert anti-liver cancer effect.

A Novel Radial Basis Function Neural Network Approach for ECG Signal Classification

ions in the ECG signal.The cardiologist and medical specialistfind numerous difficulties in the process of traditional approaches.The specified restrictions are eliminated in the proposed classifier.The fundamental aim of this work is tofind the R-R interval.To analyze the blockage,different approaches are implemented,which make the computation as facile with high accuracy.The information are recovered from the MIT-BIH dataset.The retrieved data contain normal and pathological ECG signals.To obtain a noiseless signal,Gaborfilter is employed and to compute the amplitude of the signal,DCT-DOST(Discrete cosine based Discrete orthogonal stock well transform)is implemented.The amplitude is computed to detect the cardiac abnormality.The R peak of the underlying ECG signal is noted and the segment length of the ECG cycle is identified.The Genetic algorithm(GA)retrieves the primary highlights and the classifier integrates the data with the chosen attributes to optimize the identification.In addition,the GA helps in performing hereditary calculations to reduce the problem of multi-target enhancement.Finally,the RBFNN(Radial basis function neural network)is applied,which diminishes the local minima present in the signal.It shows enhancement in characterizing the ordinary and anomalous ECG signals.

Automatic Extraction of Medical Latent Variables from ECG Signals Utilizing a Mutual Information-Based Technique and Capsular Neural Networks for Arrhythmia Detection

From a medical perspective,the 12 leads of the heart in an electrocardiogram(ECG)signal have functional dependencies with each other.Therefore,all these leads report different aspects of an arrhythmia.Their differences lie in the level of highlighting and displaying information about that arrhythmia.For example,although all leads show traces of atrial excitation,this function is more evident in lead II than in any other lead.In this article,a new model was proposed using ECG functional and structural dependencies between heart leads.In the prescreening stage,the ECG signals are segmented from the QRS point so that further analyzes can be performed on these segments in a more detailed manner.The mutual information indices were used to assess the relationship between leads.In order to calculate mutual information,the correlation between the 12 ECG leads has been calculated.The output of this step is a matrix containing all mutual information.Furthermore,to calculate the structural information of ECG signals,a capsule neural network was implemented to aid physicians in the automatic classification of cardiac arrhythmias.The architecture of this capsule neural network has been modified to perform the classification task.In the experimental results section,the proposed model was used to classify arrhythmias in ECG signals from the Chapman dataset.Numerical evaluations showed that this model has a precision of 97.02%,recall of 96.13%,F1-score of 96.57%and accuracy of 97.38%,indicating acceptable performance compared to other state-of-the-art methods.The proposed method shows an average accuracy of 2%superiority over similar works.

SRSF7对HepG2细胞增殖、迁移和侵袭的影响及其可能机制

目的:探讨富含丝氨酸/精氨酸剪接因子7(SRSF7)对肝细胞癌(HCC)细胞HepG2增殖、迁移和侵袭的影响及其可能机制。方法:通过癌症基因组图谱(TCGA)和Kaplan-Meier Plotter在线分析SRSF7在HCC和癌旁组织中的差异表达及其与患者预后的关系。常规培养HepG2细胞,用转染试剂将SRSF7 RNA敲减序列(siSRSF7#1和siSRSF7#2)、对照序列(NC)、SRSF7过表达载体(hSRSF7-oe)和对照载体(hSRSF7-nc)转染至HepG2细胞中,实验分为NC组、siSRSF7#1组、siSRSF7#2组、NC+hSRSF7-nc组、siSRSF7+hSRSF7-nc组和siSRSF7+hSRSF7-oe组。通过qPCR和WB法检测各组HepG2细胞中SRSF7 mRNA和蛋白的表达,MTS实验、平板克隆形成实验、划痕愈合实验、Transwell小室实验分别检测各组HepG2细胞的增殖、迁移和侵袭的能力。WB法检测各组HepG2细胞中JAK1/STAT3信号通路的相关蛋白的表达。结果:数据库数据分析显示SRSF7 mRNA在HCC组织中呈高表达(P<0.001),SRSF7 mRNA高表达与HCC患者不良预后有关联(P<0.05)。敲减SRSF7后,HepG2细胞的增殖、迁移和侵袭能力均显著下降(均P<0.01)。敲减SRSF7组细胞中JAK1和STAT3磷酸化水平显著降低(均P<0.05),同时过表达SRSF7后,JAK1和STAT3磷酸化水平又明显升高(均P<0.05)。结论:SRSF7在HCC组织中呈高表达,其可能通过调控JAK1/STAT3信号通路促进HepG2细胞的增殖、迁移和侵袭。

基于CNN-Swin Transformer Network的LPI雷达信号识别

针对在低信噪比(SNR)条件下,低截获概率雷达信号调制方式识别准确率低的问题,提出一种基于Transformer和卷积神经网络(CNN)的雷达信号识别方法。首先,引入Swin Transformer模型并在模型前端设计CNN特征提取层构建了CNN+Swin Transformer网络(CSTN),然后利用时频分析获取雷达信号的时频特征,对图像进行预处理后输入CSTN模型进行训练,由网络的底部到顶部不断提取图像更丰富的语义信息,最后通过Softmax分类器对六类不同调制方式信号进行分类识别。仿真实验表明:在SNR为-18 dB时,该方法对六类典型雷达信号的平均识别率达到了94.26%,证明了所提方法的可行性。

Postmortem ^(7)Li NMR analysis for assessing the reversibility of lithium metal electrodes in lithium metal batteries

Despite the proficiency of lithium(Li)-7 NMR spectroscopy in delineating the physical and chemical states of Li metal electrodes,challenges in specimen preparation and interpretation impede its progress.In this study,we conducted a comprehensive postmortem analysis utilizing ^(7)Li NMR,employing a stan-dard magic angle spinning probe to examine protective-layer coated Li metal electrodes and LiAg alloy electrodes against bare Li metal electrodes within Li metal batteries(LMBs).Our investigation explores the effects of sample burrs,alignment with the magnetic field,the existence of liquid electrolytes,and precycling on the ^(7)Li NMR signals.Through contrasting NMR spectra before and after cycling,we identi-fied alterations in Li^(0) and Li^(+) signals attributable to the degradation of the Li metal electrode.Our NMR analyses decisively demonstrate the efficacy of the protective layer in mitigating dendrite and solid elec-trolyte interphase formation.Moreover,we noted that Li*ions near the Li metal surface exhibit magnetic susceptibility anisotropy,revealing a novel approach to studying diamagnetic species on Li metal elec-trodes in LMBs.This study provides valuable insights and practical guidelines for characterizing distinct lithium states within LMBs.

抗奥合剂通过p38 MAPK/NF-κB信号通路和ACE2/Ang1-7/Mas轴缓解急性肺损伤研究

目的探讨抗奥合剂(KAHJ)治疗小鼠急性肺损伤(ALI)的作用及机制,为其可能作为缓解新型冠状病毒(COVID-19)感染后症状的药物提供依据。方法采用网络药理学方法预测KAHJ治疗ALI的主要活性成分、潜在靶点和相关信号通路。将C57BL/6J小鼠随机分为对照组、LPS组和LPS+KAHJ组。LPS+KAHJ组小鼠灌胃KAHJ(4.76 g·kg^(-1)·d^(-1),8.8 mL·kg^(-1)·d^(-1)),其余组小鼠灌胃生理盐水(8.8 mL·kg^(-1)·d^(-1))。14 d后,腹腔注射LPS(5 mg·kg^(-1))诱导ALI模型。收集小鼠血清和肺组织,通过组织病理学观察肺组织的病理变化。采用Western blot、qPCR、ELISA和IHC等方法评估KAHJ对ALI的改善作用。结果通过网络药理学筛选出疾病和药物共同的70个核心靶基因,并显示与多个信号通路密切相关,如MAPK、NF-κB、Apoptosis、COVID-19和肾素-血管紧张素系统(Ras)信号通路等。此外,通过实验验证发现KAHJ能改善小鼠ALI后的炎症和细胞凋亡,减少肺损伤和肺水肿,抑制肺纤维化。同时,KAHJ的作用机制与p38 MAPK和NF-κB的磷酸化以及ACE2/Ang1-7/Mas轴的调控也有着密切关系。结论KAHJ可能通过抑制p38 MAPK/NF-κB信号通路和调控ACE2/Ang1-7/Mas轴缓解ALI,为缓解COVID-19感染后症状提供了补充和替代药物。

B7 homolog 3 in pancreatic cancer

Despite advances in cancer treatment,pancreatic cancer(PC)remains a disease with high mortality rates and poor survival outcomes.The B7 homolog 3(B7-H3)checkpoint molecule is overexpressed among many malignant tumors,including PC,with low or absent expression in healthy tissues.By modulating various immunological and nonimmunological molecular mechanisms,B7-H3 may influence the progression of PC.However,the impact of B7-H3 on the survival of patients with PC remains a subject of debate.Still,most available scientific data recognize this molecule as a suppressive factor to antitumor immunity in PC.Furthermore,it has been demonstrated that B7-H3 stimulates the migration,invasion,and metastasis of PC cells,and enhances resistance to chemotherapy.In preclinical models of PC,B7-H3-targeting monoclonal antibodies have exerted profound antitumor effects by increasing natural killer cell-mediated antibodydependent cellular cytotoxicity and delivering radioisotopes and cytotoxic drugs to the tumor site.Finally,PC treatment with B7-H3-targeting antibody-drug conjugates and chimeric antigen receptor T cells is being tested in clinical studies.This review provides a comprehensive analysis of all PC-related studies in the context of B7-H3 and points to deficiencies in the current data that should be overcome by future research.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.