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Li D, Chen Y, Yang B, Li W, Xu Y, Wang X, Teng Y, Luo Y, Liu C, Shi J, Guo X, Liu Y, Lv Q, Fan H. BREAKING NEW GROUND: STANDARDIZING RAT MODELS FOR CRUSH SYNDROME INVESTIGATIONS. Shock 2024; 61:274-282. [PMID: 38010288 DOI: 10.1097/shk.0000000000002280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
ABSTRACT Crush syndrome (CS), alternatively termed traumatic rhabdomyolysis, is a paramount posttraumatic complication. Given the infeasibility of conducting direct simulation research in humans, the role of animal models is pivotal. Regrettably, the dearth of standardized animal models persists. The objective of this study was to construct a repeatable standardized rat CS models and, based on this, simulate specific clinical scenarios. Methods: Using a self-developed multichannel intelligent small-animal crush injury platform, we applied a force of 5 kg to the hind limbs of 8-week-old rats (280-300 g), subjecting them to a continuous 12 h compression to establish the CS model. Continuous monitoring was conducted for both the lower limbs and the overall body status. After decompression, biochemical samples were collected at 3, 6, 12, and 24 h. In addition, we created a CS model after resection of the left kidney (UNx-CS), which was conceptualized to simulate a more challenging clinical scenario to investigate the physiological and pathological responses rats with renal insufficiency combined with crush injury. The results were compared with those of the normal CS model group. Results : Our experiments confirm the stability of the crush injury platform. We defined the standardized conditions for modeling and successfully established rats CS model in bulk. After 12 h of compression, only 40% of the rats in the CS group survived for 24 h. Systemically, there was clear evidence of insufficient perfusion, reflecting the progression of CS from localized to generalized. The injured limbs displayed swelling, localized perfusion deficits, and severe pathological alterations. Significant changes were observed in blood biochemical markers: aspartate transaminase, lactate dehydrogenase, K+, creatine kinase, creatinine, and blood urea nitrogen levels rose rapidly after decompression and were significantly higher than the sham group. The kidney demonstrated characteristic pathological changes consistent with established CS diagnostic criteria. Although the UNx-CS rat model did not exhibit significant biochemical differences and pathological scores when compared with the standard CS model, it did yield intriguing results with regard to kidney morphology. The UNx-CS group manifested a higher incidence of cortical and medullary protein casts compared with the NC-CS group. Conclusion: We developed and iteratively refined a novel digital platform, addressing the multiple uncontrollable variables that plagued prior models. This study validated the stability of the platform, defined the standardized conditions for modeling and successfully established the CS model with good repeatability in bulk. In addition, our innovative approach to model a clinically challenging scenario, the UNx-CS rat model. This offers an opportunity to delve deeper into understanding the combined effects of preexisting renal compromise and traumatic injury. In summary, the development of a standardized, reproducible CS model in rats represents a significant milestone in the study of Crush syndrome. This study is of paramount significance as it advances the standardization of the CS model, laying a solid foundation for subsequent studies in related domains, especially in CS-AKI.
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Suciu I, Pamies D, Peruzzo R, Wirtz PH, Smirnova L, Pallocca G, Hauck C, Cronin MTD, Hengstler JG, Brunner T, Hartung T, Amelio I, Leist M. G × E interactions as a basis for toxicological uncertainty. Arch Toxicol 2023; 97:2035-2049. [PMID: 37258688 PMCID: PMC10256652 DOI: 10.1007/s00204-023-03500-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 04/17/2023] [Indexed: 06/02/2023]
Abstract
To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).
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Affiliation(s)
- Ilinca Suciu
- In Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany
| | - David Pamies
- Department of Biological Sciences, University of Lausanne, 1005, Lausanne, Switzerland
| | - Roberta Peruzzo
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, 94720, USA
| | - Petra H Wirtz
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78457, Constance, Germany
- Biological Work and Health Psychology, Department of Psychology, University of Konstanz, 78457, Constance, Germany
| | - Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | | | - Christof Hauck
- Department of Cell Biology, University of Konstanz, 78457, Constance, Germany
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK
| | - Jan G Hengstler
- Leibniz Research Centre for Working Environment and Human Factors, Technical University Dortmund, 44139, Dortmund, Germany
| | - Thomas Brunner
- Biochemical Pharmacology, Department of Biology, University of Konstanz, 78457, Constance, Germany
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CAAT Europe, University of Konstanz, 78457, Constance, Germany
| | - Ivano Amelio
- Division for Systems Toxicology, Department of Biology, University of Konstanz, 78457, Constance, Germany
| | - Marcel Leist
- In Vitro Toxicology and Biomedicine, Department Inaugurated By the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78457, Constance, Germany.
- CAAT Europe, University of Konstanz, 78457, Constance, Germany.
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Zong W, Rahman T, Zhu L, Zeng X, Zhang Y, Zou J, Liu S, Ren Z, Li JJ, Sibille E, Lee AV, Oesterreich S, Ma T, Tseng GC. Transcriptomic congruence analysis for evaluating model organisms. Proc Natl Acad Sci U S A 2023; 120:e2202584120. [PMID: 36730203 PMCID: PMC9963430 DOI: 10.1073/pnas.2202584120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 11/17/2022] [Indexed: 02/03/2023] Open
Abstract
Model organisms are instrumental substitutes for human studies to expedite basic, translational, and clinical research. Despite their indispensable role in mechanistic investigation and drug development, molecular congruence of animal models to humans has long been questioned and debated. Little effort has been made for an objective quantification and mechanistic exploration of a model organism's resemblance to humans in terms of molecular response under disease or drug treatment. We hereby propose a framework, namely Congruence Analysis for Model Organisms (CAMO), for transcriptomic response analysis by developing threshold-free differential expression analysis, quantitative concordance/discordance scores incorporating data variabilities, pathway-centric downstream investigation, knowledge retrieval by text mining, and topological gene module detection for hypothesis generation. Instead of a genome-wide vague and dichotomous answer of "poorly" or "greatly" mimicking humans, CAMO assists researchers to numerically quantify congruence, to dissect true cross-species differences from unwanted biological or cohort variabilities, and to visually identify molecular mechanisms and pathway subnetworks that are best or least mimicked by model organisms, which altogether provides foundations for hypothesis generation and subsequent translational decisions.
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Affiliation(s)
- Wei Zong
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA15261
| | - Tanbin Rahman
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX77030
| | - Li Zhu
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA15261
| | - Xiangrui Zeng
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA02129
| | - Yingjin Zhang
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA15261
| | - Jian Zou
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA15261
| | - Song Liu
- Department of Computer Science and Technology, Qilu University of Technology, Jinan, Shandong 250353, China
| | - Zhao Ren
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA15261
| | - Jingyi Jessica Li
- Department of Statistics, University of California, Los Angeles, CA90095
| | - Etienne Sibille
- Campbell Family Mental Health Research Institute at the Centre for Addiction and Mental Health, Toronto, ONM5S 2S1, Canada
| | - Adrian V. Lee
- Department of Pharmacology and Chemical Biology, University of Pittsburgh Medical Center Hillman Cancer Center University of Pittsburgh, Pittsburgh, PA15261
- Magee-Womens Research Institute, University of Pittsburgh Medical Center, Pittsburgh, PA15123
| | - Steffi Oesterreich
- Department of Pharmacology and Chemical Biology, University of Pittsburgh Medical Center Hillman Cancer Center University of Pittsburgh, Pittsburgh, PA15261
- Magee-Womens Research Institute, University of Pittsburgh Medical Center, Pittsburgh, PA15123
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD20742
| | - George C. Tseng
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA15261
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA15261
- Department of Computational and System, Biology, University of Pittsburgh, Pittsburgh, PA15261
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Lu Y, Boswell M, Boswell W, Salinas RY, Savage M, Reyes J, Walter S, Marks R, Gonzalez T, Medrano G, Warren WC, Schartl M, Walter RB. Global assessment of organ specific basal gene expression over a diurnal cycle with analyses of gene copies exhibiting cyclic expression patterns. BMC Genomics 2020; 21:787. [PMID: 33176680 PMCID: PMC7659085 DOI: 10.1186/s12864-020-07202-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 10/28/2020] [Indexed: 11/25/2022] Open
Abstract
Background Studying functional divergences between paralogs that originated from genome duplication is a significant topic in investigating molecular evolution. Genes that exhibit basal level cyclic expression patterns including circadian and light responsive genes are important physiological regulators. Temporal shifts in basal gene expression patterns are important factors to be considered when studying genetic functions. However, adequate efforts have not been applied to studying basal gene expression variation on a global scale to establish transcriptional activity baselines for each organ. Furthermore, the investigation of cyclic expression pattern comparisons between genome duplication created paralogs, and potential functional divergence between them has been neglected. To address these questions, we utilized a teleost fish species, Xiphophorus maculatus, and profiled gene expression within 9 organs at 3-h intervals throughout a 24-h diurnal period. Results Our results showed 1.3–21.9% of genes in different organs exhibited cyclic expression patterns, with eye showing the highest fraction of cycling genes while gonads yielded the lowest. A majority of the duplicated gene pairs exhibited divergences in their basal level expression patterns wherein only one paralog exhibited an oscillating expression pattern, or both paralogs exhibit oscillating expression patterns, but each gene duplicate showed a different peak expression time, and/or in different organs. Conclusions These observations suggest cyclic genes experienced significant sub-, neo-, or non-functionalization following the teleost genome duplication event. In addition, we developed a customized, web-accessible, gene expression browser to facilitate data mining and data visualization for the scientific community.
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Affiliation(s)
- Yuan Lu
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA.
| | - Mikki Boswell
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - William Boswell
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Raquel Ybanez Salinas
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA.,The University of Texas MD Anderson Cancer Center, Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Markita Savage
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Jose Reyes
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Sean Walter
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Rebecca Marks
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Trevor Gonzalez
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Geraldo Medrano
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
| | - Wesley C Warren
- Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Manfred Schartl
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA.,Developmental Biochemistry, Theodor-Boveri-Institute, Biozentrum, University of Würzburg, Würzburg, Germany
| | - Ronald B Walter
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, 419 Centennial Hall, 601 University Drive, San Marcos, TX, 78666, USA
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Comparison of post-traumatic changes in circulating and bone marrow leukocytes between BALB/c and CD-1 mouse strains. PLoS One 2019; 14:e0222594. [PMID: 31527918 PMCID: PMC6748677 DOI: 10.1371/journal.pone.0222594] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 09/03/2019] [Indexed: 11/19/2022] Open
Abstract
This manuscript emerged from a larger third-party funded project investigating a new poly-trauma model and its influence upon secondary sepsis. The present sub-study compared selected leukocyte subpopulations in the circulation and bone marrow after polytrauma in BALB/c versus CD-1 mice. Animals underwent unilateral femur fracture, splenectomy and hemorrhagic shock. We collected blood and bone marrow for flow cytometry analysis at 24h and 48h post-trauma. Circulating granulocytes (Ly6G+CD11+) increased in both strains after trauma. Only in BALB/c mice circulating CD8+ T-lymphocytes decreased within 48h by 30%. Regulatory T-cells (Tregs, CD4+CD25+CD127low) increased in both strains by approx. 32%. Circulating Tregs and lymphocytes (CD11b-Ly6G-MHC-2+) were always at least 1.5-fold higher in BALB/c, while the bone marrow MHC-2 expression decreased in CD-1 mice (p<0.05). Overall, immune responses to polytrauma were similar in both strains. Additionally, BALB/c expressed higher level of circulating regulatory T-cells and MHC-2-positive lymphocytes compared to CD-1 mice.
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Wang K, Xiao J, Liu X, Jiang Z, Zhan Y, Yin T, He L, Zhang F, Xing S, Chen B, Li Y, Zhang F, Kuang Z, Du B, Gu J. AICD: an integrated anti-inflammatory compounds database for drug discovery. Sci Rep 2019; 9:7737. [PMID: 31123286 PMCID: PMC6533287 DOI: 10.1038/s41598-019-44227-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 05/13/2019] [Indexed: 02/06/2023] Open
Abstract
Systemic or local inflammation drives the pathogenesis of various human diseases. Small compounds with anti-inflammatory properties hold great potential for clinical translation. Over recent decades, many compounds have been screened for their action against inflammation-related targets. Databases that integrate the physicochemical properties and bioassay results of these compounds are lacking. We created an “Anti-Inflammatory Compounds Database” (AICD) to deposit compounds with potential anti-inflammation activities. A total of 232 inflammation-related targets were recruited by the AICD. Gene set enrichment analysis showed that these targets were involved in various human diseases. Bioassays of these targets were collected from open-access databases and adopted to extract 79,781 small molecules with information on chemical properties, candidate targets, bioassay models and bioassay results. Principal component analysis demonstrated that these deposited compounds were closely related to US Food and Drug Administration-approved drugs with respect to chemical space and chemical properties. Finally, pathway-based screening for drug combination/multi-target drugs provided a case study for drug discovery using the AICD. The AICD focuses on inflammation-related drug targets and contains substantial candidate compounds with high chemical diversity and good drug-like properties. It could be serviced for the discovery of anti-inflammatory medicines and can be accessed freely at http://956023.ichengyun.net/AICD/index.php.
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Affiliation(s)
- Kun Wang
- Research Center of Integrative Medicine, School of Basic Medical Science, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.,Department of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Jianyong Xiao
- Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Xiaodong Liu
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Hong Kong, 999077, China
| | - Zhuqiao Jiang
- Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Yujuan Zhan
- Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Ting Yin
- Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Lina He
- Department of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Fangyuan Zhang
- Department of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Shangping Xing
- Research Center of Integrative Medicine, School of Basic Medical Science, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Bonan Chen
- Department of Biochemistry, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Yingshi Li
- Department of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Fengxue Zhang
- Research Center of Integrative Medicine, School of Basic Medical Science, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Zaoyuan Kuang
- Research Center of Integrative Medicine, School of Basic Medical Science, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
| | - Biaoyan Du
- Department of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
| | - Jiangyong Gu
- The Second Clinical College, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
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Schosserer M, Banks G, Dogan S, Dungel P, Fernandes A, Marolt Presen D, Matheu A, Osuchowski M, Potter P, Sanfeliu C, Tuna BG, Varela-Nieto I, Bellantuono I. Modelling physical resilience in ageing mice. Mech Ageing Dev 2018; 177:91-102. [PMID: 30290161 PMCID: PMC6445352 DOI: 10.1016/j.mad.2018.10.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Revised: 09/12/2018] [Accepted: 10/01/2018] [Indexed: 02/06/2023]
Abstract
Geroprotectors, a class of drugs targeting multiple deficits occurring with age, necessitate the development of new animal models to test their efficacy. The COST Action MouseAGE is a European network whose aim is to reach consensus on the translational path required for geroprotectors, interventions targeting the biology of ageing. In our previous work we identified frailty and loss of resilience as a potential target for geroprotectors. Frailty is the result of an accumulation of deficits, which occurs with age and reduces the ability to respond to adverse events (physical resilience). Modelling frailty and physical resilience in mice is challenging for many reasons. There is no consensus on the precise definition of frailty and resilience in patients or on how best to measure it. This makes it difficult to evaluate available mouse models. In addition, the characterization of those models is poor. Here we review potential models of physical resilience, focusing on those where there is some evidence that the administration of acute stressors requires integrative responses involving multiple tissues and where aged mice showed a delayed recovery or a worse outcome then young mice in response to the stressor. These models include sepsis, trauma, drug- and radiation exposure, kidney and brain ischemia, exposure to noise, heat and cold shock.
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Affiliation(s)
- Markus Schosserer
- University of Natural Resources and Life Sciences, Vienna, Department of Biotechnology, Vienna, Austria
| | - Gareth Banks
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Campus, Oxfordshire, OX11 0RD, United Kingdom
| | - Soner Dogan
- Department of Medical Biology, School of Medicine, Yeditepe University, Istanbul, Turkey
| | - Peter Dungel
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, AUVA Research Center, Vienna, Austria
| | - Adelaide Fernandes
- Neuron-Glia Biology in Health and Disease, iMed.ULisboa, Research Institute for Medicines, Department of Biochemistry and Human Biology, Faculty of Pharmacy, Universidade de Lisboa, Lisboa, Portugal
| | - Darja Marolt Presen
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, AUVA Research Center, Vienna, Austria
| | - Ander Matheu
- Oncology Department, Biodonostia Research Institute, San Sebastián, Spain
| | - Marcin Osuchowski
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, AUVA Research Center, Vienna, Austria
| | - Paul Potter
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Campus, Oxfordshire, OX11 0RD, United Kingdom
| | - Coral Sanfeliu
- Institute of Biomedical Research of Barcelona (IIBB) CSIC, IDIBAPS, CIBERESP, Barcelona, Spain
| | - Bilge Guvenc Tuna
- Department of Medical Biophysics, School of Medicine, Yeditepe University, Istanbul, Turkey
| | | | - Ilaria Bellantuono
- MRC/Arthritis Research-UK Centre for Integrated Research into Musculoskeletal Ageing (CIMA), Department of Oncology and Metabolism, The Medical School, Beech Hill Road, Sheffield, S10 2RX, United Kingdom.
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Labena AA, Gao YZ, Dong C, Hua HL, Guo FB. Metabolic pathway databases and model repositories. QUANTITATIVE BIOLOGY 2017. [DOI: 10.1007/s40484-017-0108-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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