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Harnessing innate immune pathways for therapeutic advancement in cancer

Signal Transduction and Targeted Therapy 2024年第4期9卷 1506-1564页

作者： ankang hu Li Sun Hao Lin Yuheng Liao hui Yang Ying Mao Department of Neurosurgery Huashan HospitalFudan UniversityShanghaiP.R.China Institute for Translational Brain Research Shanghai Medical CollegeFudan University ShanghaiPR.China National Center for Neurological Disorders Huashan HospitalShanghai Medical CollegeFudan UniversityShanghaiP.R.China Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration Shanghai Clinical Medical Center of NeurosurgeryNeurosurgical Institute of Fudan UniversityHuashan HospitalShanghai Medical CollegeFudan UniversityShanghaiP.R.China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science and MOE Frontiers Center for Brain Science Institutes of Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiP.R.China Shanghai Key Laboratory of Medical Epigenetics International Co-laboratory of Medical Epigenetics and Metabolism(Ministry of Science and Technology)and Key Laboratory of Metabolism and Molecular Medicine(Ministry of Education)and Molecular and Cell Biology LabInstitutes of Biomedical SciencesShanghai Medical College of Fudan UniversityShanghaiP.R.China

The innate immune pathway is receiving increasing attention in cancer therapy.This pathway is ubiquitous across various cell types,not only in innate immune cells but also in adaptive immune cells,tumor cells,and stromal cells.Agonists targeting the innate immune pathway have shown profound changes in the tumor microenvironment(TME)and improved tumor prognosis in preclinical studies.However,to date,the clinical success of drugs targeting the innate immune pathway remains limited.Interestingly,recent studies have shown that activation of the innate immune pathway can paradoxically promote tumor progression.The uncertainty surrounding the therapeutic effectiveness of targeted drugs for the innate immune pathway is a critical issue that needs immediate investigation.In this review,we observe that the role of the innate immune pathway demonstrates heterogeneity,linked to the tumor development stage,pathway status,and specific cell types.We propose that within the TME,the innate immune pathway exhibits multidimensional diversity.This diversity is fundamentally rooted in cellular heterogeneity and is manifested as a variety of signaling networks.The pro-tumor effect of innate immune pathway activation essentially reflects the suppression of classical pathways and the activation of potential pro-tumor alternative pathways.Refining our understanding of the tumor's innate immune pathway network and employing appropriate targeting strategies can enhance our ability to harness the anti-tumor potential of the innate immune pathway and ultimately bridge the gap from preclinical to clinicalapplication.

关键词： drugs therapeutic innate

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Projection-Specific Heterogeneity of the Axon Initial Segment of Pyramidal Neurons in the Prelimbic Cortex

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Neuroscience Bulletin 2023年第7期39卷 1050-1068页

作者： ankang hu Rui Zhao Baihui Ren Yang Li Jiangteng Lu Yilin Tai The State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science and the Institutes of Brain ScienceFudan UniversityShanghai 200032China School of Clinical Medicine Fudan UniversityShanghai 200032China Center for Brain Science of Shanghai Children’s Medical Center Shanghai Jiao Tong University School of MedicineShanghai 200127China Department of Anatomy and Physiology Shanghai Jiao Tong University School of MedicineShanghai 200025China Shanghai Research Center for Brain Science and Brain-Inspired Intelligence Shanghai 201210China

The axon initial segment(AIS)is a highly specialized axonal compartment where the action potential is initiated.The heterogeneity of AISs has been suggested to occur between interneurons and pyramidal neurons(PyNs),which likely contributes to their unique spiking properties.However,whether the various characteristics of AISs can be linked to specific PyN subtypes remains unknown.Here,we report that in the prelimbic cortex(PL)of the mouse,two types of PyNs with axon projections either to the contralateral PL or to the ipsilateral basal lateral amygdala,possess distinct AIS properties reflected by morphology,ion channel expression,action potential initiation,and axo-axonic synaptic inputs from chandelier cells.Furthermore,projection-specific AIS diversity is more prominent in the superficial layer than in the deep layer.Thus,our study reveals the cortical layer-and axon projection-specific heterogeneity of PyN AISs,which may endow the spiking of various PyN types with exquisite modulation.

关键词： Axon initial segment Pyramidal neurons Heterogeneity Chandelier cell

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基于深度学习的螺旋桨水动力性能快速预报方法

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上海交通大学学报 2024年第2期58卷 188-200页

作者：高楠胡安康侯立勋常欣大连海事大学船舶与海洋工程学院辽宁大连116026

为实现螺旋桨水动力性能的快速、精确预报,基于改进的残差连接神经网络建立了一套螺旋桨水动力性能预报模型.残差连接方式大幅提高了模型深度,结合Inception结构从不同尺度同时提取数据特征,利用深度可分离式卷积减少模型参数,基于螺旋... 详细信息

为实现螺旋桨水动力性能的快速、精确预报,基于改进的残差连接神经网络建立了一套螺旋桨水动力性能预报模型.残差连接方式大幅提高了模型深度,结合Inception结构从不同尺度同时提取数据特征,利用深度可分离式卷积减少模型参数,基于螺旋桨几何参数和模型试验结果构建训练深度神经网络所需的样本空间;提出一种改进的群体天牛须算法对模型的初始权重与阈值进行优化,进一步提高其预报精度.研究结果表明:改进的群体天牛须算法显著提高预报模型的精度并解决了过拟合问题,预报结果与试验值吻合良好,对数据集外螺旋桨的预测性能与CFD法基本一致.模型的普适性极佳且计算周期极短、效率高,满足实时、准确预报螺旋桨敞水性能的要求.

关键词：螺旋桨水动力性能残差神经网络 Inception结构改进的群体天牛须搜索算法

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重离子相对生物效应的双尺度模拟方法比较研究

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原子能科学技术 2024年第4期58卷 896-902页

作者：胡子仪邱睿陈宜正胡安康武祯张辉李君利清华大学工程物理系北京100084 清华大学粒子与辐射成像教育部重点实验室北京100084 同方威视技术股份有限公司北京100084 斯坦福大学放射肿瘤系美国斯坦福94305

重离子放射治疗是一种重要的癌症治疗手段,准确评估重离子的辐射生物效应对于提高粒子放疗的精细化水平具有重要意义。本研究基于双尺度剂量学方法和蒙特卡罗模拟,从宏观和微观两个尺度对^(12)C离子的相对生物效应(RBE)进行对比分析。... 详细信息

重离子放射治疗是一种重要的癌症治疗手段,准确评估重离子的辐射生物效应对于提高粒子放疗的精细化水平具有重要意义。本研究基于双尺度剂量学方法和蒙特卡罗模拟,从宏观和微观两个尺度对^(12)C离子的相对生物效应(RBE)进行对比分析。本研究采用宏观的细胞存活线性平方模型(LQ)和微观的微剂量动力学模型(MKM)计算两个尺度的^(12)C离子RBE在体内的分布。蒙特卡罗模拟290 MeV/u的展宽^(12)C离子束在水模型内的宏观剂量及传能线密度(LET)分布,进而计算宏观^(12)C离子RBE。同时统计不同位置处体素内的粒子谱信息,并作为二次源项进行微剂量线能谱的模拟,进而计算微观尺度的^(12)C离子RBE。结果显示,10%细胞存活分数对应的物理剂量水平下,坪区两个尺度^(12)C离子RBE计算结果差异为16%,在布拉格峰处差异为25%。本研究提出了一种计算相同照射情况下宏观和微观两种尺度重离子RBE的模拟方法,并为重离子RBE模型的改进和临床应用提供参考。

关键词：重离子放疗相对生物效应双尺度剂量学双尺度蒙特卡罗模拟

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山东、广西地区新型鹅细小病毒全基因组扩增及遗传进化分析

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中国家禽 2024年第6期46卷 44-55页

作者：乔丹丹刘婷隽陈全刚李德宝周婕董淑红胡安康徐州医科大学实验动物中心江苏徐州221004 徐州生物工程职业技术学院动物工程学院江苏徐州221006

为监测新型鹅细小病毒(Novel goose parvovirus,NGPV)的流行和变异情况,研究采集了山东和广西部分地区的鸭短喙综合征病料进行病原检测、全基因组扩增及序列比对分析。结果显示:共分离两株NGPV,山东分离株命名为SD202304,广西分离株命名... 详细信息

为监测新型鹅细小病毒(Novel goose parvovirus,NGPV)的流行和变异情况,研究采集了山东和广西部分地区的鸭短喙综合征病料进行病原检测、全基因组扩增及序列比对分析。结果显示:共分离两株NGPV,山东分离株命名为SD202304,广西分离株命名为GX202304,两株病毒与2021年NGPV分离株HNXY21亲缘关系最近,全基因组序列相似性为99.1%;GX202304株末端重复序列(Inverted terminal repeat,ITR)有一段未见报道的51 bp基因插入;VP3编码氨基酸序列比对显示,在第290位GX202304株和SD202304株有一个苏氨酸到丙氨酸的突变,这是NGPV近年来发生的新变异位点。研究表明,从山东、广西地区分离到的两株NGPV存在51 bp新的基因插入片段和VP3新的突变位点,结果为我国NGPV感染的防控提供科学依据。

关键词：新型鹅细小病毒全基因组序列鸭变异

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An integrated bioinformatics analysis and experimental study identified key biomarkers CD300A or CXCL1,pathways and immune infiltration in diabetic nephropathy mice

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BIOCELL 2022年第8期46卷 1989-2002页

作者： WEI LIANG QIANG LUO ZONGWEI ZHANG KEJU YANG ankang YANG QINGJIA CHI huAN hu Division of Nephrology Renmin Hospital of Wuhan UniversityWuhanChina Nephrology and Urology Research Institute of Wuhan University WuhanChina The First College of Clinical Medical Science China Three Gorges UniversityYichangChina Department of Engineering Structure and Mechanics Wuhan University of TechnologyWuhanChina School of Life Science and Engineering Southwest Jiaotong UniversityChengdu610000China

Diabetic nephropathy(DN)is a common microvascular complication that easily leads to end-stage renal disease.It is important to explore the key biomarkers andmolecular mechanisms relevant to diabetic nephropathy(DN).We used highthroughput RNA sequencing to obtain the genes related to DN glomerular tissues and healthy glomerular tissues of mice.Then we used LIMMA to analyze differentially expressed genes(DEGs)between DN and non-diabetic glomerular samples.And we performed KEGG,gene ontology functional(GO)enrichment,and gene set enrichment analysis to reveal the signaling pathway of the disease.The CIBERSORT algorithm based on support vector machine was used to determine the immune infiltration score.Random forest algorithm and Cytoscape obtained hub genes.Finally,we applied co-staining,immunohistochemical staining,RT-qPCR and western blotting to validate the protein and mRNA expression of both hub genes.We obtained 913 DEGs mainly related to inflammatory factors and immunity.GSEA results showed that differential genes were mainly enriched in IL-17 signaling pathway,lipid and atherosclerosis,rheumatoid arthritis,TNF signaling pathway,neutrophil extracellular trap formation,Staphylococcus aureus infection and other pathways.The intersection of the random forest algorithm and Cytoscape revealed both hub genes of CD300A and CXCL1.Experiments have shown that the both key genes of CD300A and CXCL1 shown increased expression in glomerular podocytes,and are related to the inflammation of diabetic nephropathy.And immunohistochemical staining and RT-qPCR further confirmed that the protein and mRNA expression level of CD300A or CXCL1 in glomeruli tissue in DN mice were increased.The expression levels of CD300A and CXCL1 increased significantly under HG(high glucose)stimulation,further confirming that diabetes can lead to increased levels of CD300A and CXCL1 at the cellular level.Through bioinformatics analysis,machine learning algorithms,and experimental research,CD300A and CXCL1 are confirmed as both potential biomarkers in

关键词： Diabetic nephropathy Immune infiltration Machine learning Bioinformatics Biomarkers

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Genetic algorithm-optimized backpropagation neural network establishes a diagnostic prediction model for diabetic nephropathy:Combined machine learning and experimental validation in mice

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BIOCELL 2023年第6期47卷 1253-1263页

作者： WEI LIANG ZONGWEI ZHANG KEJU YANG HONGTU hu QIANG LUO ankang YANG LI CHANG YUANYUAN ZENG Division of Nephrology Renmin Hospital of Wuhan UniversityWuhanChina Nephrology and Urology Research Institute of Wuhan University WuhanChina The First College of Clinical Medical Science Three Gorges UniversityYichangChina School of Life Science and Engineering Southwest Jiaotong UniversityChengduChina

Background:Diabetic nephropathy(DN)is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide.Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN.Kidney biopsy is the gold standard for diagnosing DN;however,its invasive character is its primary limitation.The machine learning approach provides a non-invasive and specific criterion for diagnosing DN,although traditional machine learning algorithms need to be improved to enhance diagnostic performance.Methods:We applied high-throughput RNA sequencing to obtain the genes related to DN tubular tissues and normal tubular tissues of mice.Then machine learning algorithms,random forest,LASSO logistic regression,and principal component analysis were used to identify key genes(CES1G,CYP4A14,NDUFA4,ABCC4,ACE).Then,the genetic algorithm-optimized backpropagation neural network(GA-BPNN)was used to improve the DN diagnostic model.Results:The AUC value of the GA-BPNN model in the training dataset was 0.83,and the AUC value of the model in the validation dataset was 0.81,while the AUC values of the SVM model in the training dataset and external validation dataset were 0.756 and 0.650,respectively.Thus,this GA-BPNN gave better values than the traditional SVM model.This diagnosis model may aim for personalized diagnosis and treatment of patients with DN.Immunohistochemical staining further confirmed that the tissue and cell expression of NADH dehydrogenase(ubiquinone)1 alpha subcomplex,4-like 2(NDUFA4L2)in tubular tissue in DN mice were decreased.Conclusion:The GA-BPNN model has better accuracy than the traditional SVM model and may provide an effective tool for diagnosing DN.

关键词： Diabetic nephropathy Renal tubule Machine learning Diagnostic model Genetic algorithm

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Adversarial Active Learning for Named Entity Recognition in Cybersecurity

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Computers, Materials & Continua 2021年第1期66卷 407-420页

作者： Tao Li Yongjin hu ankang Ju Zhuoran hu Zhengzhou Institute of Information Science and Technology Zhengzhou450001China College of Letters and Science University of Wisconsin-MadisonMadison53706USA

Owing to the continuous barrage of cyber threats,there is a massive amount of cyber threat intelligence.However,a great deal of cyber threat intelligence come from textual sources.For analysis of cyber threat intelligence,many security analysts rely on cumbersome and time-consuming manual efforts.Cybersecurity knowledge graph plays a significant role in automatics analysis of cyber threat intelligence.As the foundation for constructing cybersecurity knowledge graph,named entity recognition(NER)is required for identifying critical threat-related elements from textual cyber threat intelligence.Recently,deep neural network-based models have attained very good results in NER.However,the performance of these models relies heavily on the amount of labeled data.Since labeled data in cybersecurity is scarce,in this paper,we propose an adversarial active learning framework to effectively select the informative samples for further annotation.In addition,leveraging the long short-term memory(LSTM)network and the bidirectional LSTM(BiLSTM)network,we propose a novel NER model by introducing a dynamic attention mechanism into the BiLSTM-LSTM encoderdecoder.With the selected informative samples annotated,the proposed NER model is retrained.As a result,the performance of the NER model is incrementally enhanced with low labeling cost.Experimental results show the effectiveness of the proposed method.

关键词： Adversarial learning active learning named entity recognition dynamic attention mechanism

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Face Recognition Using Sequence Combinatorics

Face Recognition Using Sequence Combinatorics

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2013年中国智能自动化学术会议

作者： Chunhui Wang ankang hu Fenglei Han College of Shipbuilding Engineering Harbin Engineering University

This paper presents a sequence similarity,called all common subsequences (ACS),for use with support vector machine(SVM) and k-nearest neighbors(kNN) to the face recognition problem.We first decompose face images as row and column sequences.Then use ACS,which compares two sequences by counting the number of occurrence of common subsequences,to measure the similarity of each pair of corresponding sequences in two images and the average of similarity of all pairs of sequences is proposed to be the similarity of two images.Experiments on four public face databases:Caltech,Jaffe,Orl and Yale databases,demonstrate that ACS can achieve higher recognition accuracy than some classic face recognition methods,e.g.2DPCA and 2DLDA.

关键词： All common subsequences（ACS） Face recognition kNN SVM 2DPCA 2DLDA

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建党前后马克思主义文献的译介与传播研究——以陈独秀赞助人身份为线索

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安康学院学报 2024年第2期36卷 31-37页

作者：刘虎皖西学院外国语学院安徽六安237001

建党前后,陈独秀以多重身份鼎力支持马克思主义文献的译介、阐释和传播。作为马克思主义翻译活动的组织者和领导者,陈独秀组织策划了《共产党宣言》等马克思主义经典著作的译介出版活动;作为马克思主义媒体人和出版家,陈独秀构建了以《... 详细信息

建党前后,陈独秀以多重身份鼎力支持马克思主义文献的译介、阐释和传播。作为马克思主义翻译活动的组织者和领导者,陈独秀组织策划了《共产党宣言》等马克思主义经典著作的译介出版活动;作为马克思主义媒体人和出版家,陈独秀构建了以《新青年》为中心的红色舆论阵地以及新青年社和人民出版社等机构,为马克思主义译文提供了理想的刊载平台和发行渠道;作为马克思主义撰稿人、评论家和演说家,陈独秀发表了《马克思学说》《社会改造的方法与信仰》等评论文章或演说,促进了马克思主义的大众化传播。陈独秀鼎力支持的马克思主义文献译介和传播活动为中国共产党的创建和党的早期革命活动提供了丰厚的理论滋养,也为党百余年来的马克思主义编译出版事业打下了良好基础。

关键词：陈独秀赞助人马克思主义经典文献译介传播

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