Chengming Zhang

University of Science and Technology of China

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i-10 index

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Luonan Chen

Chinese Academy of Sciences

Tao Zeng

Yale University

Youquan Deng

Lanzhou Institute of Chemical Physics

Feng Shi

Lanzhou Institute of Chemical Physics

Xinjiang Cui

Chinese Academy of Sciences

Kazuyuki Aihara

The University of Tokyo

Chuanchao Zhang

Houston Methodist

Xuelan Gu

Unilever (China)

Xiangtian Yu

Shanghai Sixth People's Hospital

Jing Ge

Renji Hospital

Cooperative Institutions

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Center for Excellence in Molecular Cell Science

Wuhan University

Lanzhou Institute of Chemical Physics

Unilever (China)

Shanghai Jiao Tong University

ShanghaiTech University

Shanxi Medical University

Second Hospital of Shanxi Medical University

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Research progress and hotspots on macrophages in osteoarthritis: A bibliometric analysis from 2009 to 2022

Medicine (2023)

Yang Liu Peidong Liu Chengming Zhang Meng-Rou Liu Guishan Wang

Macrophages in the synovium, as immune cells, can be polarized into different phenotypes to play an anti-inflammatory role in the treatment of osteoarthritis. In this study, bibliometric methods were used to search the relevant literature to find valuable research directions for researchers and provide new targets for osteoarthritis prevention and early treatment.Studies about the application of macrophages in the treatment of osteoarthritis were searched through the Web of Science core database from 2009 to 2022. Microsoft Excel 2019, VOSviewer, CiteSpace, R software, and 2 online websites were used to analyze the research status and predict the future development of the trend in research on macrophages in osteoarthritis.The number of publications identified with the search strategy was 1304. China and the United States ranked first in the number of publications. Shanghai Jiao Tong University ranked first in the world with 37 papers. Osteoarthritis and Cartilage was the journal with the most publications, and "exosomes," "stem cells," "macrophage polarization," "regeneration," and "innate immunity" may remain the research hotspots and frontiers in the future.The findings from the global trend analysis indicate that research on macrophages in the treatment of osteoarthritis is gradually deepening, and the number of studies is increasing. Exosomes may become a research trend and hotspot in the future.

10.1097/md.0000000000034642

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Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker

Genes (2020)

Jing Ge Chenxi Song Chengming Zhang Xiaoping Liu Jingzhou Chen

Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as coronary atherosclerosis. Based on the l-DNB methodology, by using the metabolomics data of plasma of patients with coronary atherosclerosis at different stages, we accurately detected the early-warning signals of each patient. Moreover, we also discovered a group of dynamic network biomarkers (DNBs) which play key roles in driving the progression of the disease. Our study provides a new insight into the individualized early diagnosis of coronary atherosclerosis and may contribute to the development of personalized medicine.

Coronary atherosclerosis

Tipping point (physics)

Personalized Medicine

10.3390/genes11060676

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Citations (8)

Active Pd/Fe(OH) catalyst preparation for nitrobenzene hydrogenation by tracing aqueous phase chlorine concentrations in the washing step of catalyst precursors

Tetrahedron (2014)

Chengming Zhang Xinjiang Cui Youquan Deng Feng Shi

Nitrobenzene

Aqueous two-phase system

10.1016/j.tet.2014.02.057

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Citations (9)

Contrastively generative self-expression model for single-cell and spatial multimodal data

Briefings in Bioinformatics (2023)

Chengming Zhang Yiwen Yang Shijie Tang Kazuyuki Aihara Chuanchao Zhang

Advances in single-cell multi-omics technology provide an unprecedented opportunity to fully understand cellular heterogeneity. However, integrating omics data from multiple modalities is challenging due to the individual characteristics of each measurement. Here, to solve such a problem, we propose a contrastive and generative deep self-expression model, called single-cell multimodal self-expressive integration (scMSI), which integrates the heterogeneous multimodal data into a unified manifold space. Specifically, scMSI first learns each omics-specific latent representation and self-expression relationship to consider the characteristics of different omics data by deep self-expressive generative model. Then, scMSI combines these omics-specific self-expression relations through contrastive learning. In such a way, scMSI provides a paradigm to integrate multiple omics data even with weak relation, which effectively achieves the representation learning and data integration into a unified framework. We demonstrate that scMSI provides a cohesive solution for a variety of analysis tasks, such as integration analysis, data denoising, batch correction and spatial domain detection. We have applied scMSI on various single-cell and spatial multimodal datasets to validate its high effectiveness and robustness in diverse data types and application scenarios.

Generative model

Robustness

Expression (computer science)

Discriminative model

10.1093/bib/bbad265

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Citations (2)

ChemInform Abstract: Active Pd/Fe(OH)x Catalyst Preparation for Nitrobenzene Hydrogenation by Tracing Aqueous Phase Chlorine Concentrations in the Washing Step of Catalyst Precursors.

ChemInform (2014)

Chengming Zhang Xinjiang Cui Youquan Deng Feng Shi

Abstract The catalyst is recycled by simple centrifugation, but its reuse proceeds with decreased activity.

Nitrobenzene

Aqueous two-phase system

10.1002/chin.201503071

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Citations (0)

Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage

Journal of Molecular Cell Biology (2021)

Chengming Zhang Hong Zhang Jing Ge Tingyan Mi Xiao Cui

Skin, as the outmost layer of human body, is frequently exposed to environmental stressors including pollutants and ultraviolet (UV), which could lead to skin disorders. Generally, skin response process to ultraviolet B (UVB) irradiation is a nonlinear dynamic process, with unknown underlying molecular mechanism of critical transition. Here, the landscape dynamic network biomarker (l-DNB) analysis of time series transcriptome data on 3D skin model was conducted to reveal the complicated process of skin response to UV irradiation at both molecular and network levels. The advanced l-DNB analysis approach showed that: (i) there was a tipping point before critical transition state during pigmentation process, validated by 3D skin model; (ii) 13 core DNB genes were identified to detect the tipping point as a network biomarker, supported by computational assessment; (iii) core DNB genes such as COL7A1 and CTNNB1 can effectively predict skin lightening, validated by independent human skin data. Overall, this study provides new insights for skin response to repetitive UVB irradiation, including dynamic pathway pattern, biphasic response, and DNBs for skin lightening change, and enables us to further understand the skin resilience process after external stress.

Tipping point (physics)

Human skin

Reprogramming

Skin Aging

10.1093/jmcb/mjab060

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Citations (20)

Metal‐Organic Frameworks for Electrocatalytic CO2 Reduction: From Catalytic Site Design to Microenvironment Modulation

Angewandte Chemie International Edition (2024)

Chengming Zhang Zhongyuan Lin Long Jiao Hai‐Long Jiang

The electrochemical reduction of CO2 to high‐value carbon‐based chemicals provides a sustainable approach to achieving an artificial carbon cycle. In the decade, metal‐organic frameworks (MOFs), a kind of porous crystalline porous materials featuring well‐defined structures, large surface area, high porosity, diverse components, easy tailorability, and controllable morphology, have attracted considerable research attention, serving as electrocatalysts to drive CO2 reduction. In this review, the reaction mechanisms of electrochemical CO2 reduction and the structure/component advantages of MOFs meeting the requirements of electrocatalysts for CO2 reduction are analyzed. After that, the representative progress for the precise fabrication of MOF‐based electrocatalysts for CO2 reduction, focusing on catalytic site design and microenvironment modulation, are systemically summarized. Furthermore, the emerging applications and promising research for more practical scenarios related to electrochemical CO2 conversion are specifically proposed. Finally, the remaining challenges and future outlook of MOFs for electrochemical CO2 reduction are further discussed.

Carbon fibers

10.1002/anie.202414506

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Citations (2)

Detecting Personalized Determinants During Drug Treatment from Omics Big Data

Current Pharmaceutical Design (2018)

Lu Wang Xiangtian Yu Chengming Zhang Tao Zeng

Targeted therapy is the foundation of personalized medicine in cancer, which is often understood as the right patient using the right drug. Thinking from the viewpoint of determinants during personalized drug treatment, the genetics, epigenetics and metagenomics would provide individual-specific biological elements to characterize the personalized responses for therapy.Such personalized determinants should be not only understood as specific to one person, while they should have certain replicate observations in a group of individuals but not all, which actually provide more credible and reproducible personalized biological features. The requirement of detecting personalized determinants is well supported by novel high-throughput sequencing technologies and newly temporal-spatial experimental protocols, which quickly produce the omics big data.In this mini-review, we would like to give a brief introduction firstly on the advanced drug or drug-like therapy with genetics, epigenetics and metagenomics, respectively, from the viewpoint of personalized determinants; then summarize the computational methods helpful to analyze the corresponding omics data under the consideration of personalized biological context; and particularly focus on metagenomics to discuss current data, method, and opportunity for personalized medicine.Totally, detecting personalized determinants during drug treatment from omics big data will bring the precision medicine or personalized medicine from concept to application. More and more inspiring biotechnologies, data resources, and analytic approaches will benefit All of US in the near future.

Personalized Medicine

Omics

Drug response

10.2174/1381612824666181106102111

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Citations (10)

Correction to ‘Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage’

Journal of Molecular Cell Biology (2022)

Chengming Zhang Hong Zhang Jing Ge Tingyan Mi Xiao Cui

Tipping point (physics)

Reprogramming

10.1093/jmcb/mjac013

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Citations (1)

Chlorine as an Indicator in the Controllable Preparation of Active Nano-Gold Catalyst

Scientific Reports (2013)

Chengming Zhang Lequan Liu Xinjiang Cui Lirong Zheng Youquan Deng

The controllable preparation of nano-gold catalyst maintains a challenge. Except the parameters have been revealed before, here we'd like to show that controllable preparation of active nano-gold catalyst can be achieved using chlorine as an indicator. By tracing the chlorine concentration in the washing step, a series of Au/Fe2O3 catalysts were prepared with co-precipitation method. The applying of these catalysts in CO oxidation and reductive nitrobenzene N-alkylation suggested the active catalysts were prepared from solutions containing ~2 ppm chlorine. The catalytic activity dropped dramatically if the chlorine concentration is >4–6 or ≪1 ppm. Extensive characterizations revealed that the active catalyst was composed by nano-gold on the edge of Fe2O3 particle with 8.92 Au-Au coordination numbers. Although the real role of chlorine in the variation of catalyst structure and activity was still ambiguous, the current results should promote the controllable preparation of active nano-Au catalyst.

Nitrobenzene

10.1038/srep01503

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Citations (16)