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Article ; Online: Enrichment of SARS-CoV-2 Entry Factors and Interacting Intracellular Genes in Tissue and Circulating Immune Cells.

Devaprasad, Abhinandan / Pandit, Aridaman

2021 Volume 13, Issue 9

Abstract: SARS-CoV-2 uses ACE2 and TMPRSS2 to gain entry into the cell. However, recent studies have shown that SARS-CoV-2 may use additional host factors that are required for the viral lifecycle. Here we used publicly available datasets, CoV-associated genes, ... ...

Abstract	SARS-CoV-2 uses ACE2 and TMPRSS2 to gain entry into the cell. However, recent studies have shown that SARS-CoV-2 may use additional host factors that are required for the viral lifecycle. Here we used publicly available datasets, CoV-associated genes, and machine learning algorithms to explore the SARS-CoV-2 interaction landscape in different tissues. We found that in general a small fraction of cells express ACE2 in the different tissues, including nasal, bronchi, and lungs. We show that a small fraction of immune cells (including T cells, macrophages, dendritic cells) found in tissues also express ACE2. We show that healthy circulating immune cells do not express ACE2 and TMPRSS2. However, a small fraction of circulating immune cells (including dendritic cells, monocytes, T cells) in the PBMC of COVID-19 patients express ACE2 and TMPRSS2. Additionally, we found that a large spectrum of cells (in tissues and circulation) in both healthy and COVID-19-positive patients were significantly enriched for SARS-CoV-2 factors, such as those associated with RHOA and RAB GTPases, mRNA translation proteins, COPI- and COPII-mediated transport, and integrins. Thus, we propose that further research is needed to explore if SARS-CoV-2 can directly infect tissue and circulating immune cells to better understand the virus' mechanism of action.
MeSH term(s)	COVID-19/blood ; COVID-19/etiology ; Dendritic Cells/immunology ; Dendritic Cells/metabolism ; Disease Susceptibility ; Gene Expression Profiling ; Gene Expression Regulation ; High-Throughput Nucleotide Sequencing ; Host-Pathogen Interactions/genetics ; Host-Pathogen Interactions/immunology ; Humans ; Immune System/immunology ; Immune System/metabolism ; Immunity, Innate ; Macrophages/immunology ; Macrophages/metabolism ; SARS-CoV-2/physiology ; Single-Cell Analysis ; Virus Internalization
Language	English
Publishing date	2021-09-02
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v13091757
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Enrichment of SARS-CoV-2 Entry Factors and Interacting Intracellular Genes in Tissue and Circulating Immune Cells

Devaprasad, Abhinandan / Pandit, Aridaman

Viruses. 2021 Sept. 02, v. 13, no. 9

2021

Abstract	SARS-CoV-2 uses ACE2 and TMPRSS2 to gain entry into the cell. However, recent studies have shown that SARS-CoV-2 may use additional host factors that are required for the viral lifecycle. Here we used publicly available datasets, CoV-associated genes, and machine learning algorithms to explore the SARS-CoV-2 interaction landscape in different tissues. We found that in general a small fraction of cells express ACE2 in the different tissues, including nasal, bronchi, and lungs. We show that a small fraction of immune cells (including T cells, macrophages, dendritic cells) found in tissues also express ACE2. We show that healthy circulating immune cells do not express ACE2 and TMPRSS2. However, a small fraction of circulating immune cells (including dendritic cells, monocytes, T cells) in the PBMC of COVID-19 patients express ACE2 and TMPRSS2. Additionally, we found that a large spectrum of cells (in tissues and circulation) in both healthy and COVID-19-positive patients were significantly enriched for SARS-CoV-2 factors, such as those associated with RHOA and RAB GTPases, mRNA translation proteins, COPI- and COPII-mediated transport, and integrins. Thus, we propose that further research is needed to explore if SARS-CoV-2 can directly infect tissue and circulating immune cells to better understand the virus’ mechanism of action.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; data collection ; guanosinetriphosphatase ; integrins ; macrophages ; mechanism of action ; monocytes ; nose ; viruses
Language	English
Dates of publication	2021-0902
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2516098-9
ISSN	1999-4915
ISSN	1999-4915
DOI	10.3390/v13091757
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Integration of

Devaprasad, Abhinandan / Radstake, Timothy R D J / Pandit, Aridaman

Frontiers in immunology

2021 Volume 12, Page(s) 669400

Abstract: Objective: Development and progression of immune-mediated inflammatory diseases (IMIDs) involve intricate dysregulation of the disease-associated genes (DAGs) and their expressing immune cells. Identifying the crucial disease-associated cells (DACs) in ... ...

Abstract	Objective: Development and progression of immune-mediated inflammatory diseases (IMIDs) involve intricate dysregulation of the disease-associated genes (DAGs) and their expressing immune cells. Identifying the crucial disease-associated cells (DACs) in IMIDs has been challenging due to the underlying complex molecular mechanism. Methods: Using transcriptome profiles of 40 different immune cells, unsupervised machine learning, and disease-gene networks, we constructed the Disease-gene IMmune cell Expression (DIME) network and identified top DACs and DAGs of 12 phenotypically different IMIDs. We compared the DIME networks of IMIDs to identify common pathways between them. We used the common pathways and publicly available drug-gene network to identify promising drug repurposing targets. Results: We found CD4 Conclusions: Existing methods are inadequate in capturing the intricate involvement of the crucial genes and cell types essential to IMIDs. Our approach identified the key DACs, DAGs, common mechanisms between IMIDs, and proposed potential drug repurposing targets using the DIME network. To extend our method to other diseases, we built the DIME tool (https://bitbucket.org/systemsimmunology/dime/) to help scientists uncover the etiology of complex and rare diseases to further drug development by better-determining drug targets, thereby mitigating the risk of failure in late clinical development.
MeSH term(s)	Computational Biology ; Databases, Genetic ; Drug Repositioning ; Gene Expression Profiling ; Gene Regulatory Networks ; Humans ; Immune System/drug effects ; Immune System/immunology ; Immune System/metabolism ; Immune System Diseases/drug therapy ; Immune System Diseases/genetics ; Immune System Diseases/immunology ; Immune System Diseases/metabolism ; Inflammation/drug therapy ; Inflammation/genetics ; Inflammation/immunology ; Inflammation/metabolism ; Signal Transduction ; Transcriptome ; Unsupervised Machine Learning
Language	English
Publishing date	2021-05-24
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2021.669400
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Article ; Online: Enrichment of SARS-CoV-2 entry factors and interacting intracellular genes in peripheral immune cells

Devaprasad, Abhinandan / Pandit, Aridaman

bioRxiv

Abstract	SARS-CoV-2 uses ACE2 and TMPRSS2 to gain entry into the cell. However, recent studies have shown that SARS-CoV-2 may use additional host factors that are required for the viral lifecycle. Here we used publicly available datasets, CoV associated genes and machine learning algorithms to explore the SARS-CoV-2 interaction landscape in different tissues. We find that in general a small fraction of cells expresses ACE2 in the different tissues including nasal, bronchi and lungs. We show that a small fraction of immune cells (including T-cells, macrophages, dendritic cells) found in tissues also express ACE2. We show that healthy circulating immune cells do not express ACE2 and TMPRSS2. However, a small fraction of circulating immune cells (including dendritic cells, monocytes, T-cells) in the PBMC of COVID-19 patients express ACE2 and TMPRSS2. Additionally, we found that a large spectrum of cells (in circulation and periphery) in both healthy and COVID-19 positive patients were significantly enriched for SARS-CoV-2 factors. Thus, we propose that further research is needed to explore if SARS-CoV-2 can directly infect peripheral immune cells to better understand the virus9 mechanism of action.
Keywords	covid19
Language	English
Publishing date	2021-03-29
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2021.03.29.437515
Database	COVID19

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Article ; Online: CXCL4 Links Inflammation and Fibrosis by Reprogramming Monocyte-Derived Dendritic Cells

Silva-Cardoso, Sandra C / Tao, Weiyang / Angiolilli, Chiara / Lopes, Ana P / Bekker, Cornelis P J / Devaprasad, Abhinandan / Giovannone, Barbara / van Laar, Jaap / Cossu, Marta / Marut, Wioleta / Hack, Erik / de Boer, Rob J / Boes, Marianne / Radstake, Timothy R D J / Pandit, Aridaman

Frontiers in immunology

2020 Volume 11, Page(s) 2149

Abstract: Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis ... ...

Abstract	Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis development in multiple inflammatory and fibrotic diseases. Here, we used monocyte-derived cells as a model system to study the effects of CXCL4 exposure on dendritic cell development by integrating 65 longitudinal and paired whole genome transcriptional and methylation profiles. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters the trajectory of monocyte differentiation, inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key transcriptional regulators including CIITA. Importantly, these pro-inflammatory cells directly trigger a fibrotic cascade by producing extracellular matrix molecules and inducing myofibroblast differentiation. Inhibition of CIITA mimicked CXCL4 in inducing a pro-inflammatory and pro-fibrotic phenotype, validating the relevance of the gene regulatory network. Our study unveils that CXCL4 acts as a key secreted factor driving innate immune training and forming the long-sought link between inflammation and fibrosis.
MeSH term(s)	Cells, Cultured ; Cellular Reprogramming Techniques ; DNA Methylation ; Decision Trees ; Decitabine/pharmacology ; Dendritic Cells/cytology ; Fibroblasts ; Fibrosis/genetics ; Fibrosis/immunology ; Gene Regulatory Networks ; Humans ; Inflammation/genetics ; Inflammation/immunology ; Monocytes/cytology ; Multidimensional Scaling Analysis ; Nuclear Proteins/antagonists & inhibitors ; Nuclear Proteins/physiology ; Platelet Factor 4/physiology ; Poly I-C/pharmacology ; RNA Interference ; RNA, Small Interfering/genetics ; RNA, Small Interfering/pharmacology ; RNA-Seq ; Trans-Activators/antagonists & inhibitors ; Trans-Activators/physiology ; Transcriptome
Chemical Substances	MHC class II transactivator protein ; Nuclear Proteins ; PF4 protein, human ; RNA, Small Interfering ; Trans-Activators ; Platelet Factor 4 (37270-94-3) ; Decitabine (776B62CQ27) ; Poly I-C (O84C90HH2L)
Language	English
Publishing date	2020-09-17
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2020.02149
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Meta-analysis of host response networks identifies a

Sambarey, Awanti / Devaprasad, Abhinandan / Baloni, Priyanka / Mishra, Madhulika / Mohan, Abhilash / Tyagi, Priyanka / Singh, Amit / Akshata, J S / Sultana, Razia / Buggi, Shashidhar / Chandra, Nagasuma

NPJ systems biology and applications

2017 Volume 3, Page(s) 4

Abstract: Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several ... ...

Abstract	Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput
Language	English
Publishing date	2017
Publishing country	England
Document type	Journal Article
ISSN	2056-7189
ISSN	2056-7189
DOI	10.1038/s41540-017-0005-4
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Article ; Online: Meta-analysis of host response networks identifies a common core in tuberculosis

Awanti Sambarey / Abhinandan Devaprasad / Priyanka Baloni / Madhulika Mishra / Abhilash Mohan / Priyanka Tyagi / Amit Singh / JS Akshata / Razia Sultana / Shashidhar Buggi / Nagasuma Chandra

npj Systems Biology and Applications, Vol 3, Iss 1, Pp 1-

2017 Volume 12

Abstract: Tuberculosis: an underlying common-core host response network Patients suffering from tuberculosis (TB) show a high extent of variations in their gene expression patterns. Such heterogeneity poses major road blocks to our understanding of how hosts ... ...

Abstract	Tuberculosis: an underlying common-core host response network Patients suffering from tuberculosis (TB) show a high extent of variations in their gene expression patterns. Such heterogeneity poses major road blocks to our understanding of how hosts respond to the disease. A number of studies have profiled transcriptomes of human blood samples from TB patients, but a meta-analysis indicates that very few changes are consistently seen. The problem, to a large extent, lies with the way large data is analysed. We have used a genome-wide network approach to characterise the host response and have identified a common-core in the TB response networks of different patients, indicating the presence of unified host response mechanisms. This core network provides a comprehensive view into the most significant regulators of the infection-mediated biological processes across patients from different populations, and it shows partial reversals upon treatment.
Keywords	Biology (General) ; QH301-705.5
Language	English
Publishing date	2017-02-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Disease-Associated MicroRNA Cluster Links Inflammatory Pathways and an Altered Composition of Leukocyte Subsets to Noninfectious Uveitis.

Verhagen, Fleurieke H / Bekker, Cornelis P J / Rossato, Marzia / Hiddingh, Sanne / de Vries, Lieuwe / Devaprasad, Abhinandan / Pandit, Aridaman / Ossewaarde-van Norel, Jeannette / Ten Dam, Ninette / Moret-Pot, Maartje C A / Imhof, Saskia M / de Boer, Joke H / Radstake, Timothy R D J / Kuiper, Jonas J W

Investigative ophthalmology & visual science

2018 Volume 59, Issue 2, Page(s) 878–888

Abstract: Purpose: The cause of noninfectious uveitis (NIU) is poorly understood but is considered to be mediated by a complex interplay between genetic, environmental, and-relatively unexplored-epigenetic factors. MicroRNAs (miRNAs) are noncoding small RNAs that ...

Abstract	Purpose: The cause of noninfectious uveitis (NIU) is poorly understood but is considered to be mediated by a complex interplay between genetic, environmental, and-relatively unexplored-epigenetic factors. MicroRNAs (miRNAs) are noncoding small RNAs that are important epigenetic regulators implicated in pathologic signaling. Therefore, we mapped the circulating miRNA-ome of NIU patients and studied miRNA perturbations within the broader context of the immune system. Methods: We designed a strategy to robustly identify changes in the miRNA profiles of two independent cohorts totaling 54 untreated patients with active and eye-restricted disease and 26 age-matched controls. High-resolution miRNA-ome data were obtained by TaqMan OpenArray technology and subsequent RT-qPCR. Flow cytometry data, and proteomic data spanning the cellular immune system, were used to map the uveitis-miRNA signature to changes in the composition of specific leukocyte subsets in blood. Results: Using stringent selection criteria, we identified and independently validated an miRNA cluster that is associated with NIU. Pathway enrichment analysis for genes targeted by this cluster revealed significant enrichment for the PI3K/Akt, MAPK, FOXO, and VEGF signaling pathways, and photoreceptor development. In addition, unsupervised multidomain analyses linked the presence of the uveitis-associated miRNA cluster to a different composition of leukocyte subsets, more specifically, CD16+CD11c+HLA-DR- cells. Conclusions: Together, this study identified a unique miRNA cluster associated with NIU that was related to changes in leukocyte subsets demonstrating systemic changes in epigenetic regulation underlying NIU.
MeSH term(s)	Adult ; CD11c Antigen/immunology ; Cluster Analysis ; Female ; Flow Cytometry ; Gene Expression Profiling ; HLA-DR Antigens/immunology ; Humans ; Inflammation/genetics ; Lymphocyte Subsets/immunology ; Male ; MicroRNAs/blood ; MicroRNAs/genetics ; Middle Aged ; Real-Time Polymerase Chain Reaction ; Receptors, IgG/immunology ; Transcriptome ; Uveitis/genetics ; Uveitis/immunology
Chemical Substances	CD11c Antigen ; HLA-DR Antigens ; MicroRNAs ; Receptors, IgG
Language	English
Publishing date	2018--01
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	391794-0
ISSN	1552-5783 ; 0146-0404
ISSN (online)	1552-5783
ISSN	0146-0404
DOI	10.1167/iovs.17-23643
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Article ; Online: Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks

Awanti Sambarey / Abhinandan Devaprasad / Abhilash Mohan / Asma Ahmed / Soumya Nayak / Soumya Swaminathan / George D'Souza / Anto Jesuraj / Chirag Dhar / Subash Babu / Annapurna Vyakarnam / Nagasuma Chandra

EBioMedicine, Vol 15, Iss C, Pp 112-

2017 Volume 126

Abstract: Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially ... ...

Abstract	Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially expressed genes, but cannot by itself identify the most influential contributors to the disease phenotype. Here, we describe a computational pipeline that adopts an unbiased approach to identify a biomarker signature. Data from RNA sequencing from whole blood samples of TB patients were integrated with a curated genome-wide molecular interaction network, from which we obtain a comprehensive perspective of variations that occur in the host due to TB. We then implement a sensitive network mining method to shortlist gene candidates that are most central to the disease alterations. We then apply a series of filters that include applicability to multiple publicly available datasets as well as additional validation on independent patient samples, and identify a signature comprising 10 genes — FCGR1A, HK3, RAB13, RBBP8, IFI44L, TIMM10, BCL6, SMARCD3, CYP4F3 and SLPI, that can discriminate between TB and healthy controls as well as distinguish TB from latent tuberculosis and HIV in most cases. The signature has the potential to serve as a diagnostic marker of TB.
Keywords	Tuberculosis ; Biomarkers ; Network biology ; Computational medicine ; Diagnostics ; Medicine ; R ; Medicine (General) ; R5-920
Subject code	006
Language	English
Publishing date	2017-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks.

Sambarey, Awanti / Devaprasad, Abhinandan / Mohan, Abhilash / Ahmed, Asma / Nayak, Soumya / Swaminathan, Soumya / D'Souza, George / Jesuraj, Anto / Dhar, Chirag / Babu, Subash / Vyakarnam, Annapurna / Chandra, Nagasuma

EBioMedicine

2016 Volume 15, Page(s) 112–126

Abstract	Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially expressed genes, but cannot by itself identify the most influential contributors to the disease phenotype. Here, we describe a computational pipeline that adopts an unbiased approach to identify a biomarker signature. Data from RNA sequencing from whole blood samples of TB patients were integrated with a curated genome-wide molecular interaction network, from which we obtain a comprehensive perspective of variations that occur in the host due to TB. We then implement a sensitive network mining method to shortlist gene candidates that are most central to the disease alterations. We then apply a series of filters that include applicability to multiple publicly available datasets as well as additional validation on independent patient samples, and identify a signature comprising 10 genes - FCGR1A, HK3, RAB13, RBBP8, IFI44L, TIMM10, BCL6, SMARCD3, CYP4F3 and SLPI, that can discriminate between TB and healthy controls as well as distinguish TB from latent tuberculosis and HIV in most cases. The signature has the potential to serve as a diagnostic marker of TB.
MeSH term(s)	Adolescent ; Adult ; Biomarkers ; Case-Control Studies ; Cluster Analysis ; Coinfection ; Computational Biology/methods ; Data Mining/methods ; Female ; Gene Expression Profiling ; Gene Regulatory Networks ; HIV Infections/immunology ; HIV Infections/virology ; Host-Pathogen Interactions ; Humans ; Male ; Middle Aged ; Models, Biological ; Mycobacterium tuberculosis ; Prognosis ; Protein Interaction Mapping ; Protein Interaction Maps ; Reproducibility of Results ; Signal Transduction ; Tuberculosis, Pulmonary/blood ; Tuberculosis, Pulmonary/diagnosis ; Tuberculosis, Pulmonary/genetics ; Tuberculosis, Pulmonary/metabolism ; Young Adult
Chemical Substances	Biomarkers
Language	English
Publishing date	2016-12-21
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2851331-9
ISSN	2352-3964
ISSN (online)	2352-3964
DOI	10.1016/j.ebiom.2016.12.009
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