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Multi-omics joint analysis revealed the metabolic profile of retroperitoneal liposarcoma

《医学前沿（英文）》 doi: 10.1007/s11684-023-1020-z

摘要： Retroperitoneal liposarcoma (RLPS) is the main subtype of retroperitoneal soft sarcoma (RSTS) and has a poor prognosis and few treatment options, except for surgery. The proteomic and metabolic profiles of RLPS have remained unclear. The aim of our study was to reveal the metabolic profile of RLPS. Here, we performed proteomic analysis (n = 10), metabolomic analysis (n = 51), and lipidomic analysis (n = 50) of retroperitoneal dedifferentiated liposarcoma (RDDLPS) and retroperitoneal well-differentiated liposarcoma (RWDLPS) tissue and paired adjacent adipose tissue obtained during surgery. Data analysis mainly revealed that glycolysis, purine metabolism, pyrimidine metabolism and phospholipid formation were upregulated in both RDDLPS and RWDLPS tissue compared with the adjacent adipose tissue, whereas the tricarboxylic acid (TCA) cycle, lipid absorption and synthesis, fatty acid degradation and biosynthesis, as well as glycine, serine, and threonine metabolism were downregulated. Of particular importance, the glycolytic inhibitor 2-deoxy-D-glucose and pentose phosphate pathway (PPP) inhibitor RRX-001 significantly promoted the antitumor effects of the MDM2 inhibitor RG7112 and CDK4 inhibitor abemaciclib. Our study not only describes the metabolic profiles of RDDLPS and RWDLPS, but also offers potential therapeutic targets and strategies for RLPS.

关键词： RLPS     proteomics     metabolomics     lipidomics     metabolism    

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作物表型组大数据技术及装备发展研究

温维亮,郭新宇 ,张颖,顾生浩,赵春江

《中国工程科学》 2023年 第25卷 第4期   页码 227-238 doi: 10.15302/J-SSCAE-2023.04.015

摘要： Dealing with multi-source and multi-scale information in plant phenomics: The ontology-driven Phenotypingcomponents and genetic architecture of maize stem vascular bundles using high-throughput phenotypic analysisZEAMAP, a comprehensive database adapted to the maize multi-omics era [J]‍.LettuceGDB: The community database for lettuce genetics and omics [J]‍.Multi-source data fusion improves time-series phenotype accuracy in maize under a field high-throughput

关键词： 作物表型组学；表型大数据；表型技术及装备；多组学    

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人工智能加速GPCR配体的发现 Review

陈伟, 宋驰, 冷梁, 张三印, 陈士林

《工程（英文）》 2024年 第32卷 第1期   页码 19-29 doi: 10.1016/j.eng.2023.09.011

摘要：

G蛋白偶联受体（GPCR）在多种生理过程中发挥着关键作用，是新药发现的重要靶标。然而，传统的GPCR配体发现方法需要投入大量的时间和资源。人工智能方法的出现为GPCR配体的识别和优化提供了有利的工具，改变了GPCR配体发现的研究方式。本文从数据资源、数据描述、模型设计等方面介绍了如何利用人工智能方法构建GPCR配体发现模型，并分析了人工智能方法在GPCR药物领域的应用；提出了一种基于人工智能方法整合多组学数据的GPCR配体筛选策略；探讨了人工智能方法在GPCR研究领域面临的挑战和未来发展方向。人工智能方法与多学科的交叉融合将提高GPCR配体发现的效率。

关键词： G蛋白偶联受体     配体     人工智能     多组学     药物发现    

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促进肝癌致癌活性和细胞代谢的新型介质——miR-516a-3p

芮韬, 张学优, 冯时, 黄海涛, 詹少伟, 谢海洋, 周琳, 郑树森, 凌琪

《工程（英文）》 2022年 第16卷 第9期   页码 162-175 doi: 10.1016/j.eng.2021.07.020

摘要：

肝细胞肝癌（HCC）是目前最致命的恶性肿瘤之一。根据先前的研究，19 号染色体miRNA簇（C19MC）与肝癌患者的肿瘤高负荷和不良预后相关。目前的研究旨在探讨miR-516a-3p 在HCC 中的作用。miR-516a-3p 是一种由C19MC 4 个致癌前体miRNA（即mir-516a-1、mir-516a-2、mir-516b-1 和mir-516b-2）所共同剪接而成的相同的成熟体miRNA。在肝癌队列中，与瘤旁组织相比，miR-516a-3p 在肝癌组织中显著高表达。肿瘤miR-516a-3p 的高表达与肝癌高肿瘤负荷相关，可以区分高HCC复发率和死亡率，并独立预测肝癌的不良预后。进一步通过体外实验发现miR-516a-3p 增强了肝癌细胞的增殖、迁移和侵袭性，并通过体内实验验证miR-516a-3p 促进了肿瘤的增殖和远处转移能力。在肝癌细胞中，miR-516a-3p 可以通过外泌体进行递送，并增加受体肝癌细胞的致癌活性。此外，为探索miR-516a-3p 致癌的潜在机制，本研究进行了全面的转录组学、蛋白质组学和代谢组学分析。多组学DIABLO分析显示，蛋白质组学和代谢组学数据之间具有密切的相关性和较强的聚类一致性。进一步证实了6 种基因的mRNA（即LMBR1、CHST9、RBM3、SLC7A6、PTGFRN和NOL12）是miR-516a-3p 的直接靶点，并在miR-516a-3p 介导的代谢调节中发挥核心作用。综合多组学和共富集途径分析表明，miR-516a-3p 可以调节肝癌细胞的代谢途径，特别是嘌呤代谢和嘧啶代谢。总之，本研究发现，miR-516a-3p 可以通过调节细胞代谢和外泌体递送系统
影响相邻细胞，促进肝癌细胞的肿瘤恶性进展。因此，miR-516a-3p可作为肝癌治疗的新分子靶点。

 

关键词： 肝细胞肝癌     miRNA簇     外泌体     多组学    

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Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient

《医学前沿（英文）》 2022年 第16卷 第4期   页码 596-609 doi: 10.1007/s11684-021-0868-z

摘要： Sialic acid binding Ig-like lectin 10 (Siglec10) is a member of innate immune checkpoints that inhibits the activation of immune cells through the interaction with its ligand CD24 on tumor cells. Here, by analyzing public databases containing 64 517 patients of 33 cancer types, we found that the expression of Siglec10 was altered in 18 types of cancers and was associated with the clinical outcomes of 11 cancer types. In particular, Siglec10 was upregulated in patients with kidney renal clear cell carcinoma (KIRC) and was inversely associated with the prognosis of the patients. In 131 KIRC patients of our settings, Siglec10 was elevated in the tumor tissues of 83 (63.4%) patients compared with that in their counterpart normal kidney tissues. Moreover, higher level of Siglec10 was associated with advanced disease (stages III and IV) and worse prognosis. Silencing of CD24 in KIRC cells significantly increased the number of Siglec10-expressing macrophages phagocytosing KIRC cells. In addition, luciferase activity assays suggested that Siglec10 was a potential target of the transcription factors c-FOS and GATA1, which were identified by data mining. These results demonstrate that Siglec10 may have important oncogenic functions in KIRC, and represents a novel target for the development of immunotherapies.

关键词： innate immune checkpoint     Siglec10     kidney renal clear cell carcinoma    

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A study on specialist or special disease clinics based on big data

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《医学前沿（英文）》 2014年 第8卷 第3期   页码 376-381 doi: 10.1007/s11684-014-0356-9

摘要：

Correlation analysis and processing of massive medical information can be implemented through big data technology to find the relevance of different factors in the life cycle of a disease and to provide the basis for scientific research and clinical practice. This paper explores the concept of constructing a big medical data platform and introduces the clinical model construction. Medical data can be collected and consolidated by distributed computing technology. Through analysis technology, such as artificial neural network and grey model, a medical model can be built. Big data analysis, such as Hadoop, can be used to construct early prediction and intervention models as well as clinical decision-making model for specialist and special disease clinics. It establishes a new model for common clinical research for specialist and special disease clinics.

关键词： big data     correlation analysis     medical information     integration     data analysis     clinical model    

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Scientific computation of big data in real-world clinical research

null

《医学前沿（英文）》 2014年 第8卷 第3期   页码 310-315 doi: 10.1007/s11684-014-0358-7

摘要：

The advent of the big data era creates both opportunities and challenges for traditional Chinese medicine (TCM). This study describes the origin, concept, connotation, and value of studies regarding the scientific computation of TCM. It also discusses the integration of science, technology, and medicine under the guidance of the paradigm of real-world, clinical scientific research. TCM clinical diagnosis, treatment, and knowledge were traditionally limited to literature and sensation levels; however, primary methods are used to convert them into statistics, such as the methods of feature subset optimizing, multi-label learning, and complex networks based on complexity, intelligence, data, and computing sciences. Furthermore, these methods are applied in the modeling and analysis of the various complex relationships in individualized clinical diagnosis and treatment, as well as in decision-making related to such diagnosis and treatment. Thus, these methods strongly support the real-world clinical research paradigm of TCM.

关键词： big data     real world     clinical research     Chinese medicine     medical computing    

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Clinical research of traditional Chinese medicine in big data era

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《医学前沿（英文）》 2014年 第8卷 第3期   页码 321-327 doi: 10.1007/s11684-014-0370-y

摘要：

With the advent of big data era, our thinking, technology and methodology are being transformed. Data-intensive scientific discovery based on big data, named “The Fourth Paradigm,” has become a new paradigm of scientific research. Along with the development and application of the Internet information technology in the field of healthcare, individual health records, clinical data of diagnosis and treatment, and genomic data have been accumulated dramatically, which generates big data in medical field for clinical research and assessment. With the support of big data, the defects and weakness may be overcome in the methodology of the conventional clinical evaluation based on sampling. Our research target shifts from the “causality inference” to “correlativity analysis.” This not only facilitates the evaluation of individualized treatment, disease prediction, prevention and prognosis, but also is suitable for the practice of preventive healthcare and symptom pattern differentiation for treatment in terms of traditional Chinese medicine (TCM), and for the post-marketing evaluation of Chinese patent medicines. To conduct clinical studies involved in big data in TCM domain, top level design is needed and should be performed orderly. The fundamental construction and innovation studies should be strengthened in the sections of data platform creation, data analysis technology and big-data professionals fostering and training.

关键词： big data     traditional Chinese medicine     clinical evaluation     evidence based medicine    

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Clinical data quality problems and countermeasure for real world study

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《医学前沿（英文）》 2014年 第8卷 第3期   页码 352-357 doi: 10.1007/s11684-014-0351-1

摘要：

Real world study (RWS) has become a hotspot for clinical research. Data quality plays a vital role in research achievement and other clinical research fields. In this paper, the common quality problems in the RWS of traditional Chinese medicine are discussed, and a countermeasure is proposed.

关键词： real world study     traditional Chinese medicine     clinical and research information sharing system     data quality problem     data quality control    

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多组学导向的链霉菌1647产生的奥米克欣的发现——一组抗甲型流感病毒和冠状病毒HCoV-229E的活性类四肽化合物 Article

孙红敏, 李星星, 陈明华, 钟鸣, 李怡华, 王琨, 杜郁, 甄心, 高荣梅, 巫晔翔, 侍媛媛, 余利岩, 车永胜, 李玉环, 蒋建东, 洪斌, 司书毅

《工程（英文）》 2022年 第16卷 第9期   页码 176-186 doi: 10.1016/j.eng.2021.05.010

摘要：

微生物具有产生抗病毒抗生素以保护细胞存活的机制。链霉菌（Streptomyces sp.）1647 是20 世纪70 年代从中国南方土壤中分离的一株链霉菌，其发酵液显示优良的抗甲型流感病毒（IAV）活性，但其抗病毒活性成分始终没有得到有效的分离和结构鉴定。本研究综合利用多组学研究策略，从这株链霉菌中成功分离得到抗病毒活性成分。利用抗生素及次级代谢产物分析软件（antiSMASH）分析该菌株的基因组序列信息，发现其中可能含有38 个次级代谢产物生物合成基因簇（BGC）。经过生物活性导向的比较转录组学分析，初步锁定三个可能的目标抗病毒活性化合物的生物合成基因簇。通过生物信息学分析及对基因簇36 中调节基因和生物合成基因的遗传操作，确定了基因簇36 为抗病毒活性化合物的生物合成基因簇。对野生株和不同重组菌株发酵产物进行基于生物活性导向的质谱数据分子网络分析，初步确定了抗病毒成分是一组化学结构类似物。最后通过高分辨质谱和二维核磁共振波谱分析，确定了抗病毒活性成分为包括18 个含有脲基的类四肽结构，取名奥米克欣（omicsynin）A1~A6、奥米克欣B1~B6 和奥米克欣C1~C6，其中11 个（奥米克欣A1、奥米克欣A2、奥米克欣A6、奥米克欣B1~B3、奥米克欣B5、奥米克欣B6、奥米克欣C1、奥米克欣C2 和奥米克欣C6）是新结构化合物。奥米克欣B1~B4 显示出优良的抗甲型流感病毒活性，其50%抑制浓度（IC50）在1 μmol·L−1左右，选择指数（SI）为100~300。奥米克欣B1~B4 同时显示出对人冠状病毒HCoV-229E的显著抑制活性。综上，通过综合利用多组学技术与数据分析，从链霉菌1647 发酵产物中发现了一组新型的具有抗病毒活性的类四肽化合物，说明微生物次级代谢产物是新型抗病毒抗生素的宝贵资源。

关键词： 多组学     抗甲型流感病毒     抗冠状病毒     链霉菌1647     类四肽化合物    

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subsets determine tumor prognosis and molecular characteristics of clear-cell renal cell carcinoma: a multi-centerintegrated analysis of microbiome, metabolome, and transcriptome data

《医学前沿（英文）》 doi: 10.1007/s11684-023-1029-3

摘要： Microbiome subsets determine tumor prognosis and molecular characteristics of clear-cell renal cell carcinoma: a multi-center integrated analysis of microbiome, metabolome, and transcriptome data

关键词： tumor prognosis molecular     Microbiome subsets determine     center analysis microbiome     transcriptome data    

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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

《能源前沿（英文）》 doi: 10.1007/s11708-023-0912-6

摘要： With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energy sources (RESs) has become a trend in the industry. However, the uncertainty of RES poses challenges to the safe and stable operation of DCs and power grids. In this paper, a multi-timescale optimal scheduling model is established for interconnected data centers (IDCs) based on model predictive control (MPC), including day-ahead optimization, intraday rolling optimization, and intraday real-time correction. The day-ahead optimization stage aims at the lowest operating cost, the rolling optimization stage aims at the lowest intraday economic cost, and the real-time correction aims at the lowest power fluctuation, eliminating the impact of prediction errors through coordinated multi-timescale optimization. The simulation results show that the economic loss is reduced by 19.6%, and the power fluctuation is decreased by 15.23%.

关键词： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed power supply     landscape uncertainty    

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Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-022-0692-4

摘要： Axial piston pumps have wide applications in hydraulic systems for power transmission. Their condition monitoring and fault diagnosis are essential in ensuring the safety and reliability of the entire hydraulic system. Vibration and discharge pressure signals are two common signals used for the fault diagnosis of axial piston pumps because of their sensitivity to pump health conditions. However, most of the previous fault diagnosis methods only used vibration or pressure signal, and literatures related to multi-sensor data fusion for the pump fault diagnosis are limited. This paper presents an end-to-end multi-sensor data fusion method for the fault diagnosis of axial piston pumps. The vibration and pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional neural network. Experiments were performed on an axial piston pump to confirm the effectiveness of the proposed method. Results show that the proposed multi-sensor data fusion method greatly improves the fault diagnosis of axial piston pumps in terms of accuracy and robustness and has better diagnostic performance than other existing diagnosis methods.

关键词： axial piston pump     fault diagnosis     convolutional neural network     multi-sensor data fusion    

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Deciphering the pharmacological mechanism of Guan-Jie-Kang in treating rat adjuvant-induced arthritis using omicsanalysis

Hudan Pan, Yanfang Zheng, Zhongqiu Liu, Zhongwen Yuan, Rutong Ren, Hua Zhou, Ying Xie, Liang Liu

《医学前沿（英文）》 2019年 第13卷 第5期   页码 564-574 doi: 10.1007/s11684-018-0676-2

摘要： Traditional Chinese medicine (TCM) formulas have attracted increasing attention worldwide in the past few years for treating complex disease including rheumatoid arthritis. However, their mechanisms are complex and remain unclear. Guan-Jie-Kang (GJK), a prescription modified from “Wu Tou Decoction,” was found to significantly relieve arthritis symptoms in rats with adjuvant-induced arthritis after 30-day treatment, especially in the 24 g/kg/day group. By analyzing 1749 targets related to 358 compounds in the five herbs of GJK, we identified the possible anti-arthritis pathways of GJK, including the calcium signaling and metabolic pathways. Bone damage levels were assessed by micro-computed tomography, and greater bone protective effect was observed with GJK treatment than with methotrexate. Receptor activator of nuclear factor κB ligand (RANKL)–RANK signaling, which is related to calcium signaling, was significantly regulated by GJK. Moreover, a target metabolomics assay of serum was conducted; 17 metabolic biomarkers showed significant correlations with treatment. An integrated pathway analysis revealed that pyruvate metabolism, purine metabolism, and glycolysis metabolism were significantly associated with the effects of GJK in arthritis treatment. Thus, this study establishes a new omics analytical method integrated with bioinformatics analysis for elucidating the multi-pathway mechanisms of TCM.

关键词： rheumatoid arthritis     traditional Chinese medicine     pharmacological mechanism     metabolism     adjuvant-induced arthritis     omics analysis    

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多组学联用揭示花粉过敏基于肠道菌的新机制 Article

韩珮, 李丽莎, 王子熹, 锡琳, 于航, 丛林, 张正威, 符洁, 彭冉, 潘利斌, 马殊荣, 王学艳, 王洪田, 王向东, 王琰, 孙劲旅, 蒋建东

《工程（英文）》 2022年 第15卷 第8期   页码 115-125 doi: 10.1016/j.eng.2021.03.013

摘要：

由于过敏性疾病在世界范围内流行且尚无治愈方法，因此有必要探讨其病理生理机制。由于过敏性疾病与肠道菌群失调相关，本研究从宿主与微生物的分子层面，结合代谢组学和微生物组学，寻找可能的机制。本研究对SD大鼠注射青蒿花粉提取物以诱导其对花粉的过敏反应，这种过敏反应降低了血液中的缬氨酸、异亮氨酸、天门冬氨酸、谷氨酸、谷氨酰胺、吲哚丙酸和肌醇浓度，并减少了粪便中的短链脂肪酸（SCFA）。来自于瘤胃球菌科（Ruminococcaceae）、毛螺菌科（Lachnospiraceae）和梭状芽孢杆菌（Clostridiales）的几个有益菌属在模型组中表达减少，而幽门螺杆菌Helicobacter 和阿克曼氏菌Akkermansia 仅在模型组中表达。此外，模型组肠道claudin-3 和肝脏脂肪酸结合蛋白表达下调，与代谢变化和细菌有关。本文的研究结果表明，氨基酸及其衍生物（尤其是缬氨酸和色氨酸的还原产物吲哚丙酸）、短链脂肪酸和肠道微生物（特别是幽门螺杆菌Helicobacter 和阿克曼氏菌Akkermansia）的改变可能通过抑制claudin蛋白表达和影响黏液层而破坏肠道屏障功能，进而导致花粉过敏。

关键词： 代谢组学     肠道菌群     花粉过敏     过敏性疾病     肠道屏障功能紊乱    

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标题 作者 时间 类型 操作

Multi-omics joint analysis revealed the metabolic profile of retroperitoneal liposarcoma

期刊论文

作物表型组大数据技术及装备发展研究

温维亮,郭新宇 ,张颖,顾生浩,赵春江

期刊论文

人工智能加速GPCR配体的发现

陈伟, 宋驰, 冷梁, 张三印, 陈士林

期刊论文

促进肝癌致癌活性和细胞代谢的新型介质——miR-516a-3p

芮韬, 张学优, 冯时, 黄海涛, 詹少伟, 谢海洋, 周琳, 郑树森, 凌琪

期刊论文

Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient

期刊论文

A study on specialist or special disease clinics based on big data

null

期刊论文

Scientific computation of big data in real-world clinical research

null

期刊论文

Clinical research of traditional Chinese medicine in big data era

null

期刊论文

Clinical data quality problems and countermeasure for real world study

null

期刊论文

多组学导向的链霉菌1647产生的奥米克欣的发现——一组抗甲型流感病毒和冠状病毒HCoV-229E的活性类四肽化合物

孙红敏, 李星星, 陈明华, 钟鸣, 李怡华, 王琨, 杜郁, 甄心, 高荣梅, 巫晔翔, 侍媛媛, 余利岩, 车永胜, 李玉环, 蒋建东, 洪斌, 司书毅

期刊论文

subsets determine tumor prognosis and molecular characteristics of clear-cell renal cell carcinoma: a multi-centerintegrated analysis of microbiome, metabolome, and transcriptome data

期刊论文

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

期刊论文

Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

期刊论文

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