基于CEEMDAN-VMD-TCN-lightGBM模型的水质预测研究

针对目前水质预测模型中因为数据本身的复杂性、在信号处理过程中存在的噪声干扰以及分解深度不够导致单一分解难以全面捕捉信号非线性特征的问题,提出了一种基于二次分解的水质预测模型。该模型采用完全自适应噪声集合经验模态分解(CEEMDAN)对原始数据进行分解,再利用变分模态分解(VMD)对熵值最高的模态分量进行二次分解,最终将处理后的时间序列输入到TCN-lightGBM多特征预测模型中。同时,采用麻雀算法(SSA)对预测模型进行优化。以山东省玉符河水质为例,本模型的均方根误差(RMSE)是0.1053,平均绝对误差(MAE)是0.0815,决定系数(R2)是0.9471,与GRU、LSTM、LightGBM、TCN等当下较为流行的模型的预测指标进行比较。结果显示,在R2上本模型提升了53.04%、70.41%、66.07%、65.20%等,在RMSE上减少了62.76%、65.50%、64.93%、64.80%等,在MAE上降低了62.76%、66.24%、63.80%、65.24%等。由此可知,基于CEEMDAN-VMD-TCN-lightGBM的模型具有更好的预测性能、泛化能力和捕捉信号非线性特征的能力。

基于颗粒流GBM模型的花岗岩热力损伤特性研究

【目的】为了研究花岗岩在热力耦合作用下的裂纹扩展规律及损伤特征,揭示岩石细观结构演化对其力学行为的影响,【方法】基于颗粒流GBM算法,建立了非均质花岗岩热力耦合数值模型,研究20℃及高温(200℃、400℃、600℃和800℃)处理后花岗岩细观裂纹演化规律及力学行为。【结果】结果显示,热致裂纹数量随热处理温度升高显著增加,且所有热处理温度下,花岗岩模型中热致裂纹均以矿物晶界的拉伸裂纹为主;当热处理温度超过400℃后,石英和长石矿物内部开始萌生大量晶内拉伸与晶内剪切裂纹。【结论】结果表明:热致裂纹的萌生、扩展和贯通导致花岗岩的力学性质劣化,随着热处理温度升高,花岗岩峰值强度和弹性模量减小,而峰值应变增加;当温度大于600℃时,热致裂纹开始主导花岗岩试件的最终破坏模式,同时应力-应变曲线峰后阶段开始由脆性向延性转变;热致裂纹随热处理温度的升高而显著增加,导致花岗岩在单轴加载的早期阶段产生了更多的声发射事件。此外,轴向应力引起花岗岩试件内部的应力重分布,应力集中区域产生更多应力诱导裂纹,并最终引起失稳破坏。

沉默RPARP-AS1对GBM U251细胞增殖、迁移和凋亡的影响

目的探究沉默长链非编码RNA RPARP-AS1对胶质母细胞瘤(GBM)U251细胞增殖、迁移和凋亡的影响。方法选取80例GBM组织与癌旁组织。将GBM细胞株U251细胞随机分为Control组、小干扰RNA阴性对照(si-NC)组、si-RPARP-AS1组、si-RPARP-AS1+抑制剂(inhibitor)NC组、si-RPARP-AS1+miR-339-5p inhibitor组。qRT-PCR检测组织和细胞RPARP-AS1、miR-339-5p和鼠双微体基因2(MDM2)mRNA的表达。CCK-8检测各组细胞增殖能力。Transwell检测各组U251细胞迁移和侵袭能力。流式细胞术检测细胞凋亡率。Western blotting检测B细胞淋巴瘤-2(Bcl-2)、Bcl-2相关X蛋白(Bax)、E-钙黏蛋白(E-cadherin)、N-钙黏蛋白(N-cadherin)和MDM2蛋白的表达。双荧光素酶报告基因实验分别验证RPARP-AS1和miR-339-5p、miR-339-5p和MDM2的关系。结果与癌旁组织相比,GBM组织RPARP-AS1、MDM2 mRNA高表达,miR-339-5p低表达(P<0.05)。与Control组、si-NC组相比,si-RPARP-AS1组U251细胞RPARP-AS1、MDM2 mRNA和Bcl-2、N-cadherin、MDM2蛋白表达以及细胞增殖、迁移、侵袭能力显著降低(P<0.05),miR-339-5p、Bax、E-cadherin蛋白表达以及细胞凋亡率显著升高(P<0.05)。与si-RPARP-AS1组、si-RPARP-AS1+inhibitor NC组比较,si-RPARP-AS1+miR-339-5p inhibitor组细胞MDM2 mRNA和Bcl-2、N-cadherin、MDM2蛋白表达以及细胞增殖、迁移、侵袭能力显著升高(P<0.05),miR-339-5p、Bax、E-cadherin蛋白表达以及细胞凋亡率显著降低(P<0.05)。RPARP-AS1靶向负调控miR-339-5p表达,miR-339-5p靶向负调控MDM2表达。结论沉默RPARP-AS1对GBM U251细胞增殖、迁移和侵袭具有抑制作用,对细胞凋亡具有促进作用,可能与通过上调miR-339-5p,抑制MDM2表达有关。

IKIP downregulates THBS1/FAK signaling to suppress migration and invasion by glioblastoma cells

Background:Inhibitor of NF-κB kinase-interacting protein(IKIP)is known to promote proliferation of glioblastoma(GBM)cells,but how it affects migration and invasion by those cells is unclear.Methods:We compared levels of IKIP between glioma tissues and normal brain tissue in clinical samples and public databases.We examined the effects of IKIP overexpression and knockdown on the migration and invasion of GBM using transwell and wound healing assays,and we compared the transcriptomes under these different conditions to identify the molecular mechanisms involved.Results:Based on data from our clinical samples and from public databases,IKIP was overexpressed in GBM tumors,and its expression level correlated inversely with survival.IKIP overexpression in GBM cells inhibited migration and invasion in transwell and wound healing assays,whereas IKIP knockdown exerted the opposite effects.IKIP overexpression in GBM cells that were injected into mouse brain promoted tumor growth but inhibited tumor invasion of surrounding tissue.The effects of IKIP were associated with downregulation of THBS1 mRNA and concomitant inhibition of THBS1/FAK signaling.Conclusions:IKIP inhibits THBS1/FAK signaling to suppress migration and invasion of GBM cells.

GRIK1 promotes glioblastoma malignancy and is a novel prognostic factor of poor prognosis

Primary tumors of the central nervous system(CNS)are classified into over 100 different histological types.The most common type of glioma is derived from astrocytes,and the most invasive glioblastoma(WHO IV)accounts for over 57%of these tumors.Glioblastoma(GBM)is the most common and fatal tumor of the CNS,with strong growth and invasion capabilities,which makes complete surgical resection almost impossible.Despite various treatment methods such as surgery,radiotherapy,and chemotherapy,glioma is still an incurable disease,and the median survival time of patients with GBM is shorter than 15 months.Thus,molecular mechanisms of GBM characteristic invasive growth need to be clarified to improve the poor prognosis.Glutamate ionotropic receptor kainate type subunit 1(GRIK1)is essential for brain function and is involved in many mental and neurological diseases.However,GRIK1’s pathogenic roles and mechanisms in GBM are still unknown.Single-nuclear RNA sequencing of primary and recurrent GBM samples revealed that GRIK1 expression was noticeably higher in the recurrent samples.Moreover,immunohistochemical staining of an array of GBM samples showed that high levels of GRIK1 correlated with poor prognosis of GBM,consistent with The Cancer Genome Atlas database.Knockdown of GRIK1 retarded GBM cells growth,migration,and invasion.Taken together,these findings show that GRIK1 is a unique and important component in the development of GBM and may be considered as a biomarker for the diagnosis and therapy in individuals with GBM.

Comprehensive understanding of glioblastoma molecular phenotypes:classification,characteristics,and transition

Among central nervous system-associated malignancies,glioblastoma(GBM)is the most common and has the highest mortality rate.The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide.In precision medicine,research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity,as well as the refractory nature of GBM toward therapy.Deep understanding of the different molecular expression patterns of GBM subtypes is critical.Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes.The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors.These subtypes also exhibit high plasticity in their regulatory pathways,oncogene expression,tumor microenvironment alterations,and differential responses to standard therapy.Herein,we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype.Furthermore,we review the mesenchymal transition mechanisms of GBM under various regulators.

Efficacy and safety of anlotinib combined with the STUPP regimen in patients with newly diagnosed glioblastoma: a multicenter, single-arm, phase Ⅱ trial

Objective:Glioblastomas are highly vascularized malignant tumors.We determined the efficacy and safety of the anti-angiogenic multi-kinase inhibitor,anlotinib,for a newly diagnosed glioblastoma.Methods:This multicenter,single-arm trial(NCT04119674)enrolled 33 treatment-naïve patients with histologically proven glioblastomas between March 2019 and November 2020.Patients underwent treatment with the standard STUPP regimen[fractionated focal irradiation in daily fractions of 1.8-2 Gy given 5 d/w×6 w(total=54-60 Gy)]or radiotherapy plus continuous daily temozolomide(TMZ)(75 mg/m^(2)of body surface area/d,7 d/w from the first to the last day of radiotherapy),followed by 6 cycles of adjuvant TMZ(150-200 mg/m^(2)×5 d during each 28-d cycle)plus anlotinib(8 mg/d on d 1-14 of each 3-w cycle for 2 cycles during concomitant chemoradiotherapy,8 maximal cycles as adjuvant therapy,followed by maintenance at 8 mg/d.The primary endpoint was progression-free survival(PFS).Secondary endpoints included overall survival(OS)and adverse events(AEs).Results:Thirty-three patients received the planned treatment.The median PFS was 10.9 months(95%CI,9.9-18.7 months)and the 12-month PFS rate was 48.5%.The median OS was 17.4 months(95%CI,14.5-21.1 months)and the 12-month OS rate was 81.8%.The most common AEs included hypertriglyceridemia[58%(n=19)],hypoalbuminemia[46%(n=15)],and hypercholesterolemia[46%(n=15)]during concurrent chemoradiotherapy and leukopenia[73%(n=24)],hypertriglyceridemia[67%(n=22)],and neutropenia[52%(n=17)]during adjuvant therapy.Five patients discontinued treatment due to AEs.HEG1(HR,5.6;95%CI,1.3-23.7;P=0.021)and RP1L1 alterations(HR,11.1;95%CI,2.2-57.2;P=0.004)were associated with a significantly shorter PFS.Conclusions:Anlotinib plus the STUPP regimen has promising anti-tumor activity against glioblastoma and manageable toxicity.HEG1 and RP1L1 alterations might be novel predictive biomarkers of the response to anlotinib.

NUDT5 promotes the growth,metastasis,and Warburg effect of IDH wild-type glioblastoma multiforme cells by upregulating TRIM47

Objective:To explore the regulatory mechanism of NUDT5 in glioblastoma multiforme(GBM).Methods:GEPIA database was used to predict the expressions of NUDT5 and tripartite motif family proteins 47(TRIM47)in GBM patients.RT-qPCR and Western blot analyses were performed to examine NUDT5 expression in GBM cells.LN-229 cell proliferation,migration as well as invasion were estimated by CCK-8,colony formation,wound healing,and Transwell assays following interference with NUDT5.ECAR assay,L-lactic acid kit,glucose detection kit,and ATP detection kit were applied for the detection of glycolysis-related indexes.Co-immunoprecipitation experiment was carried out to verify the relationship between NUDT5 and TRIM47.Results:GEPIA database showed that NUDT5 expression was significantly increased in GBM patients.Inhibiting the expression of NUDT5 in GBM cells significantly suppressed the viability,proliferation,invasion,migration,and glycolysis of GBM cells.Moreover,TRIM47 was highly expressed in GBM cells and interacted with NUDT5.Overexpression of TRIM47 partially reversed the inhibitory effect of NUDT5 downregulation on the proliferation,metastasis,and glycolysis of GBM cells.Conclusions:NUDT5 promotes the growth,metastasis,and Warburg effect of GBM cells by upregulating TRIM47.Both NUDT5 and TRIM47 can be used as targets for GMB treatment.

A review on potential heterocycles for the treatment of glioblastoma targeting receptor tyrosine kinases

Glioblastoma,the most aggressive form of brain tumor,poses significant challenges in terms of treatment success and patient survival.Current treatment modalities for glioblastoma include radiation therapy,surgical intervention,and chemotherapy.Unfortunately,the median survival rate remains dishearteningly low at 12–15 months.One of the major obstacles in treating glioblastoma is the recurrence of tumors,making chemotherapy the primary approach for secondary glioma patients.However,the efficacy of drugs is hampered by the presence of the blood-brain barrier and multidrug resistance mechanisms.Consequently,considerable research efforts have been directed toward understanding the underlying signaling pathways involved in glioma and developing targeted drugs.To tackle glioma,numerous studies have examined kinase-downstream signaling pathways such as RAS-RAF-MEKERK-MPAK.By targeting specific signaling pathways,heterocyclic compounds have demonstrated efficacy in glioma therapeutics.Additionally,key kinases including phosphatidylinositol 3-kinase(PI3K),serine/threonine kinase,cytoplasmic tyrosine kinase(CTK),receptor tyrosine kinase(RTK)and lipid kinase(LK)have been considered for investigation.These pathways play crucial roles in drug effectiveness in glioma treatment.Heterocyclic compounds,encompassing pyrimidine,thiazole,quinazoline,imidazole,indole,acridone,triazine,and other derivatives,have shown promising results in targeting these pathways.As part of this review,we propose exploring novel structures with low toxicity and high potency for glioma treatment.The development of these compounds should strive to overcome multidrug resistance mechanisms and efficiently penetrate the blood-brain barrier.By optimizing the chemical properties and designing compounds with enhanced drug-like characteristics,we can maximize their therapeutic value and minimize adverse effects.Considering the complex nature of glioblastoma,these novel structures should be rigorously tested and evaluated for their efficacy and safety profiles.

Silvestrol alleviates glioblastoma progression through ERK pathway modulation and MANBA and NRG-1 expression

Background:Glioblastoma,a notably malignant tumor within the central nervous system,is distinguished by its aggressive behavior.Silvestrol,a robust inhibitor of the RNA helicase eukaryotic initiation factor 4A(eIF4A),has shown significant potential as an anticancer compound.Yet,the impact of silvestrol on glioblastoma,especially its molecular mechanisms,has not been fully elucidated.Methods:This investigation employed a variety of in vitro assays,such as cell counting kit-8(CCK-8),clonogenic,5-ethynyl-2′-deoxyuridine(EDU),wound healing,and flow cytometry,to evaluate cell cycle progression,apoptosis,cell viability,and migration.Western blot analysis was also performed to study the apoptosis and extracellular regulated kinase(ERK)pathways.After the ERK pathway was inhibited,differentially expressed genes(DEGs)in U87 cells were identified,followed by an analysis of target genes using the gene expression profiling interactive analysis(GEPIA)database.Results:Silvestrol significantly suppressed the proliferation,migration,and colony formation of glioma cells.It caused cell cycle arrest and enhanced apoptosis in these cells.Additionally,silvestrol stimulated the ERK pathway,with these effects being reversible by an ERK phosphorylation inhibitor.Transcriptome combined with GEPIA,GSCA,UALCAN,TIMER database screened 4 potential drug targets of silvestrol:chromosome 1 open reading frame 226(C1ORF226),mannosidase beta A(MANBA),IQ motif and Sec7 domain 2(IQSEC2),neuregulin 1(NRG-1).Among them,C1ORF226 was lower risk gene while MANBA,IQSEC2,and NRG-1 were high-risk genes.Furthermore,silvestrol notably reduced MANBA mRNA levels,which could be reversed by inhibiting ERK phosphorylation.Furthermore,silvestrol markedly decreased NRG-1 protein levels,with an additional reduction observed when the ERK pathway was blocked.Conclusion:Silvestrol’s anti-glioma effects are primarily due to the suppression of MANBA expression via the ERK pathway and possibly by hindering the translation of NRG-1 protein,thus reducing its expression.The downregulation of MANBA and NRG-1 proteins may be crucial in hindering glioma development and progression.These results highlight the intricate relationship between the ERK pathway and gene expression regulation in silvestrol’s therapeutic effectiveness against glioma.

Cerebral Glioblastoma in Renal Transplant Recipient: A Case Report

Cancers is a leading cause of mortality among transplant recipients. The most common cancers are skin tumors. Glioblastoma is the most frequent brain tumor in adults aged 45 - 70 years. It accounts for 12% - 15% of all intracranial tumors. It is characterized by its rapid development and poor prognosis. We report the case of a cerebral glioblastoma in a kidney transplant recipient. Clinical case: Mr G.R, 44 years old caucasian patient who underwent kidney transplantation. Immunosuppressive treatment included cyclosporine, mycophenolate mofetil and methylprednisolone. Creatinine levels after transplantation remained stable at 11 mg/L (96.8 μmol/l) with an estimated glomerular filtration rate (eGFR) of 77 ml/min/1.73m2 after a 15 years of follow-up. A grade IV right fronto-callossal cerebral glioblastoma was diagnosed in our patient. EBV PCR was negative. Therefore, he underwent 25 sessions of radiotherapy combined with oral chemotherapy using temozolomide. One month later, the patient died due to cerebral edema with subfalcine herniation. Conclusion: This is a case of cerebral glioblastoma in a kidney transplant recipient, a population considered at risk for tumor development due to immunosuppressive treatment. This emphasizes the need for a lifelong surveillance and, more importantly a better balance between graft function preservation and the risks associated with immunosuppressants.

Identification of TMEM159 as a biomarker of glioblastoma progression based on immune characteristics

Background:Glioblastoma multiforme(GBM)is the most general malignancy of the primary central nervous system that is characterized by high aggressiveness and lethality.Transmembrane protein 159(TMEM159)is an endoplasmic reticulum protein that can form oligomers with seipin.The TMEM159-seipin complex decides the site of lipid droplet(LD)formation,and the formation of LDs is a marker of GBM.However,the role of TMEM159 in the progression of GBM has not been investigated to date.Methods:In this study,we examined the genes that may be associated with patient prognosis in GBM by bioinformatics analyses,and identified the key genes that affect the development of GBM using single-cell RNA sequencing technology.The biological functions of TMEM159 in GBM cells were additionally assessed by clone formation and transwell assays as well as using a model of chick embryo chorioallantois membrane(CAM)and western blotting.The association between TMEM159 and epidermal growth factor receptor(EGFR)was finally analyzed in GBM cells.Results:A prognostic model was established and validated for predicting the prognosis.Survival curve analysis showed a critical difference in the prognosis of the high-and low-risk groups predicted by the prognostic model.The results demonstrated that TMEM159 affected the proliferation and invasion of GBM cells.The chick embryo CAM assays demonstrated that the inhibition of TMEM159 expression reduced angiogenesis in the CAM model.Conclusions:The prognostic model achieved good predictive potential for high-risk patients.The findings also revealed that TMEM159 might be an important prognostic factor for GBM,indicating that the protein may be a promising therapeutic target for suppressing the development of GBM.

一种基于随机森林和Light GBM的房产估价模型

针对商品房评估方法中存在数据源单一,考虑影响因素理想化,特征工程过分依赖主观经验等问题,结合随机森林和Light GBM模型,提出了一种RF_LightGBM模型用于房产价值评估。首先,通过随机森林对特征进行重要度排序,将影响房产价格因素较小的特征排除,使用网格搜索算法对模型进行优化,最后将该方法用于房产价值评估。在真实的房价数据集上进行的实验表明,相较于随即森林,XGBoost等传统模型,RF_LightGBM模型的评估精度提高了1.7%,且百分误差在0%~10%以内的评估结果占比88.38%。说明所用模型可以很好地应用于房产价值评估,得到的评估结果更加准确。

Application of Convolutional Neural Networks in Classification of GBM for Enhanced Prognosis

The lethal brain tumor “Glioblastoma” has the propensity to grow over time. To improve patient outcomes, it is essential to classify GBM accurately and promptly in order to provide a focused and individualized treatment plan. Despite this, deep learning methods, particularly Convolutional Neural Networks (CNNs), have demonstrated a high level of accuracy in a myriad of medical image analysis applications as a result of recent technical breakthroughs. The overall aim of the research is to investigate how CNNs can be used to classify GBMs using data from medical imaging, to improve prognosis precision and effectiveness. This research study will demonstrate a suggested methodology that makes use of the CNN architecture and is trained using a database of MRI pictures with this tumor. The constructed model will be assessed based on its overall performance. Extensive experiments and comparisons with conventional machine learning techniques and existing classification methods will also be made. It will be crucial to emphasize the possibility of early and accurate prediction in a clinical workflow because it can have a big impact on treatment planning and patient outcomes. The paramount objective is to not only address the classification challenge but also to outline a clear pathway towards enhancing prognosis precision and treatment effectiveness.

Celastrol inhibits inflammatory factors expression in glioblastoma

Background:Glioblastoma is one of the most common primary intracranial tumors of the central nervous system in adults.Although chemotherapy is an important component of glioblastoma treatment,its effectiveness remains unsatisfactory.Due to multiple immunosuppressive mechanisms,glioblastoma immunotherapy has not been effective in treating many patients as a result of the clinical breakthroughs in the field.Therefore,the development of cancer immunotherapy relies on the understanding of how tumors interact with the immune system and the analysis of their molecular determinants.This study identified the key interactions between immune cells in the glioma microenvironment using RNA microarrays and single-cell sequencing.Methods:First,we screened differentially expressed genes in tumor and control samples from GSE29796 and GSE50161 datasets using GEO2R.All differentially expressed genes were used to perform enrichment analysis and construct protein-protein interaction topological analysis to analyze the interaction between proteins.Using single-cell RNA sequencing data from the GSE162631 database,we identified immune cell types within the glioblastoma microenvironment,and validated the hub gene expression in these cells.In addition,based on the GEPIA and TIMER databases,hub genes were investigated and compared with immune infiltration to determine differential expression.Finally,CellChat was used to visualize the gene expression distribution and cell-to-cell communication analysis of the proteins between different types of cells.Results:We found that monocytes/macrophages may communicate with each other in the tumor microenvironment through MIF-(CD74+CXCR4)and MIF-(CD74+CD44).In addition,our study indicated that celastrol has the ability to inhibit inflammatory factors expression by MIF/CD74 signaling pathway in U87 cells.Conclusion:This study improved the effectiveness of cancer immunotherapy strategies and developed new ideas for immunotherapy that can be applied to glioblastoma.

DWI联合DCE-MRI鉴别呈环形强化的脑GBM和感染性病变

目的:探讨MR扩散加权成像(DWI)和3D肝脏容积快速采集(LAVA)序列动态对比增强(DCE)MRI扫描对颅内呈环形强化的胶质母细胞瘤(GBM)和感染性病变的鉴别诊断价值。方法:回顾性搜集2015年9月-2020年9月在本院经病理证实的23例脑GBM和17例颅内感染性病变(脑脓肿11例,结核瘤6例)患者的临床和MRI资料。所有患者在术前2周内行3.0T颅脑MRI扫描,扫描序列包括常规序列、对比增强T_(1)WI、DWI和LAVA序列DCE-MRI扫描。分别使用Firevoxel软件和GE Omni-Kinetics软件在每例患者的表观扩散系数(ADC)图和DCE图像中选取病灶最大层面于病灶内环形强化区域手动勾画ROI,测量并比较两组病变的ADC第一四分位数(ADC-P25)、容积转移常数(K_(trans))、血管外细胞外体积分数(V_(e))、增强曲线下初始面积(IAUGC)、速率常数(K_(ep))、血浆容积分数(V_(p))、达峰时间(TTP)和最大斜率(S_(MAX))测量值的差异。K_(trans)、V_(p)和IAUGC的组间比较采用独立样本t检验,ADC-P25、K_(ep)、V_(p)、TTP和S_(MAX)的组间比较采用Mann-Whitney U检验。对组间差异有统计学意义的参数,绘制其受试者工作曲线(ROC),评估单个参数和多参数联合后对GBM和感染性病变的鉴别诊断效能。将AUC<0.7、0.7~0.9和>0.9分别定义为具有低、中和高度诊断效能。结果:GBM的K_(trans)、IAUGC和S_(MAX)值均显著高于感染性病变,差异均有统计学意义(P=0.004、0.045、0.011),而ADC-P25显著低于感染性病变(P=0.042)。K_(trans)、ADC-P25和S_(MAX)值对两种病变均达到了中度以上的鉴别诊断效能,单一参数诊断效能最佳的是K_(trans),联合ADC-P25、K_(trans)和S_(MAX)三个参数的诊断效能最佳,其ROC曲线下面积、敏感度和特异度分别为0.967、0.900和1.000。结论:DWI和DCE-MRI定量及半定量参数对呈环形强化的GBM和感染性病变均具有一定的鉴别能力,两类参数联合可显著提高鉴别诊断效能。

基于GBM的特征选择在心脏病预测中的研究

心脏病患者的人数逐年增多,死亡率居高不下,因此许多学者对基于机器学习的患病人群识别方法进行了研究,但由于心脏病数据的特征过多,构建的模型参数较多,往往导致训练时间过长。因此提出一种利用梯度提升机算法(GBM)对已有的特征选择算法进行改进,在通过减少特征数量实现缩短训练时间的同时,对心脏病患者的预测准确率也得到了提升。首先,采用遗传算法(GA)和基于相关性的特征选择(CFS)进行特征降维,并选出备选特征子集;其次,提出利用GBM实现对模型预测无关特征的筛除;最后,采用支持向量机(SVM)和K近邻算法(KNN)进行准确率预测。实验表明:当预测模型为SVM时,GBM对GA和CFS的综合评价指标的提升分别达到了9.89%和2.2%;当预测模型为KNN时,GBM对GA和CFS的综合评价指标的提升分别达到了7.7%和2.2%,并且GA+GBM在SVM上的表现最好,达到了84.62%,能够有效地提升医疗诊断的效率。

Nanosensitizers for sonodynamic therapy for glioblastoma multiforme: current progress and future perspectives

Glioblastoma multiforme(GBM) is the most common primary malignant brain tumor, and it is associated with poor prognosis. Its characteristics of being highly invasive and undergoing heterogeneous genetic mutation, as well as the presence of the blood–brain barrier(BBB), have reduced the efficacy of GBM treatment. The emergence of a novel therapeutic method, namely, sonodynamic therapy(SDT), provides a promising strategy for eradicating tumors via activated sonosensitizers coupled with low-intensity ultrasound. SDT can provide tumor killing effects for deep-seated tumors, such as brain tumors. However, conventional sonosensitizers cannot effectively reach the tumor region and kill additional tumor cells, especially brain tumor cells. Efforts should be made to develop a method to help therapeutic agents pass through the BBB and accumulate in brain tumors. With the development of novel multifunctional nanosensitizers and newly emerging combination strategies, the killing ability and selectivity of SDT have greatly improved and are accompanied with fewer side effects. In this review, we systematically summarize the findings of previous studies on SDT for GBM, with a focus on recent developments and promising directions for future research.

Development of glioblastoma organoids and their applications in personalized therapy

Glioblastomas(GBMs)are the brain tumors with the highest malignancy and poorest prognoses.GBM is characterized by high heterogeneity and resistance to drug treatment.Organoids are 3-dimensional cultures that are constructed in vitro and comprise cell types highly similar to those in organs or tissues in vivo,thus simulating specific structures and physiological functions of organs.Organoids have been technically developed into an advanced ex vivo disease model used in basic and preclinical research on tumors.Brain organoids,which simulate the brain microenvironment while preserving tumor heterogeneity,have been used to predict patients’therapeutic responses to antitumor drugs,thus enabling a breakthrough in glioma research.GBM organoids provide an effective supplementary model that reflects human tumors’biological characteristics and functions in vitro more directly and accurately than traditional experimental models.Therefore,GBM organoids are widely applicable in disease mechanism research,drug development and screening,and glioma precision treatments.This review focuses on the development of various GBM organoid models and their applications in identifying new individualized therapies against drug-resistant GBM.

Nanomedicine-based combination therapies for overcoming temozolomide resistance in glioblastomas

Glioblastoma(GBM)is the most common malignant brain tumor.Although current treatment strategies,including surgery,chemotherapy,and radiotherapy,have achieved clinical effects and prolonged the survival of patients,the gradual development of resistance against current therapies has led to a high recurrence rate and treatment failure.Mechanisms underlying the development of resistance involve multiple factors,including drug efflux,DNA damage repair,glioma stem cells,and a hypoxic tumor environment,which are usually correlative and promote each other.As many potential therapeutic targets have been discovered,combination therapy that regulates multiple resistance-related molecule pathways is considered an attractive strategy.In recent years,nanomedicine has revolutionized cancer therapies with optimized accumulation,penetration,internalization,and controlled release.Blood-brain barrier(BBB)penetration efficiency is also significantly improved through modifying ligands on nanomedicine and interacting with the receptors or transporters on the BBB.Moreover,different drugs for combination therapy usually process different pharmacokinetics and biodistribution,which can be further optimized with drug delivery systems to maximize the therapeutic efficiency of combination therapies.Herein the current achievements in nanomedicine-based combination therapy for GBM are discussed.This review aimed to provide a broader understanding of resistance mechanisms and nanomedicine-based combination therapies for future research on GBM treatment.