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Marzec-Schmidt, K., Ghosheh, N., Stahlschmidt, S. R., Küppers-Munther, B., Synnergren, J. & Ulfenborg, B. (2023). Artificial intelligence supports automated characterization of differentiated human pluripotent stem cells. Stem Cells, 41(9), 850-861, Article ID sxad049.
Open this publication in new window or tab >>Artificial intelligence supports automated characterization of differentiated human pluripotent stem cells
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2023 (English)In: Stem Cells, ISSN 1066-5099, E-ISSN 1549-4918, Vol. 41, no 9, p. 850-861, article id sxad049Article in journal (Refereed) Published
Abstract [en]

Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy images to e.g., distinguish between pluripotent stem cells and differentiated cell types derived from stem cells. In this work, we investigated the possibility of using a deep learning model to predict the differentiation stage of pluripotent stem cells undergoing differentiation towards hepatocytes, based on morphological features of cell cultures. We were able to achieve close to perfect classification of images from early and late time points during differentiation, and this aligned very well with the experimental validation of cell identity and function. Our results suggest that deep learning models can distinguish between different cell morphologies, and provide alternative means of semi-automated functional characterization of stem cell cultures.

Place, publisher, year, edition, pages
Oxford University Press, 2023
Keywords
artificial intelligence, cell differentiation, computer-assisted, hepatocytes, image analysis, pluripotent stem cells, quality control
National Category
Bioinformatics (Computational Biology) Cell and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-23064 (URN)10.1093/stmcls/sxad049 (DOI)001025294200001 ()37357747 (PubMedID)2-s2.0-85171393798 (Scopus ID)
Funder
Knowledge Foundation, 20170302Knowledge Foundation, 20200014University of Skövde
Note

CC BY 4.0

Corresponding author: Benjamin Ulfenborg, PhD, Department of Biology and Bioinformatics, School of Bioscience, University of Skövde, SE-541 28, Sweden. Email: benjamin.ulfenborg@his.se

This work was supported by the Swedish Knowledge Foundation (grant numbers 20170302 and 20200014), the Systems Biology Research Center, University of Skövde, Sweden and Takara Bio Europe, Gothenburg, Sweden.

Available from: 2023-07-31 Created: 2023-07-31 Last updated: 2023-12-19Bibliographically approved
Sjölin, J., Jonsson, M., Orback, C., Oldfors, A., Jeppsson, A., Synnergren, J., . . . Vukusic, K. (2023). Expression of Stem Cell Niche-Related Biomarkers at the Base of the Human Tricuspid Valve. Stem Cells and Development, 32(5-6), 140-151
Open this publication in new window or tab >>Expression of Stem Cell Niche-Related Biomarkers at the Base of the Human Tricuspid Valve
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2023 (English)In: Stem Cells and Development, ISSN 1547-3287, E-ISSN 1557-8534, Vol. 32, no 5-6, p. 140-151Article in journal (Refereed) Published
Abstract [en]

Stem cell niches have been thoroughly investigated in tissue with high regenerative capacity but not in tissues where cell turnover is slow, such as the human heart. The left AtrioVentricular junction (AVj), the base of the mitral valve, has previously been proposed as a niche region for cardiac progenitors in the adult human heart. In the present study, we explore the right side of the human heart, the base of the tricuspid valve, to investigate the potential of this region as a progenitor niche. Paired biopsies from explanted human hearts were collected from multi-organ donors (N = 12). The lateral side of the AVj, right atria (RA), and right ventricle (RV) were compared for the expression of stem cell niche-related biomarkers using RNA sequencing. Gene expression data indicated upregulation of genes related to embryonic development and extracellular matrix (ECM) composition in the proposed niche region, that is, the AVj. In addition, immunohistochemistry showed high expression of the fetal cardiac markers MDR1, SSEA4, and WT1 within the same region. Nuclear expression of HIF1α was detected suggesting hypoxia. Rare cells were found with the co-staining of the proliferation marker PCNA and Ki67 with cardiomyocyte nuclei marker PCM1 and cardiac Troponin T (cTnT), indicating proliferation of small cardiomyocytes. WT1+/cTnT+ and SSEA4+/cTnT+ cells were also found, suggesting cardiomyocyte-specific progenitors. The expression of the stem cell markers gradually decreased with distance from the tricuspid valve. No expression of these markers was observed in the RV tissue. In summary, the base of the tricuspid valve is an ECM-rich region containing cells with expression of several stem cell niche-associated markers. Co-expression of stem cell markers with cTnT indicates cardiomyocyte-specific progenitors. We previously reported similar data from the base of the mitral valve and thus propose that human adult cardiomyocyte progenitors reside around both atrioventricular valves.

Place, publisher, year, edition, pages
Mary Ann Liebert, 2023
Keywords
atrioventricular junction, cardiomyocyte proliferation, heart, hypoxia, stem cell niche
National Category
Cell and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-22317 (URN)10.1089/scd.2022.0253 (DOI)000920897800001 ()36565027 (PubMedID)2-s2.0-85149422996 (Scopus ID)
Funder
Knowledge Foundation, 20160294
Note

CC BY 4.0

E-mail: kristina.vukusic@gu.se

This work was supported by grants from foundation of Mats Kleberg as well as from Konrad and Helfrid Johansson and the University of Skövde through grants from the Knowledge foundation (20160294).

Available from: 2023-03-02 Created: 2023-03-02 Last updated: 2023-05-03Bibliographically approved
Nawaz, M., Heydarkhan-Hagvall, S., Tangruksa, B., González-King Garibotti, H., Jing, Y., Maugeri, M., . . . Valadi, H. (2023). Lipid Nanoparticles Deliver the Therapeutic VEGFA mRNA In Vitro and In Vivo and Transform Extracellular Vesicles for Their Functional Extensions. Advanced Science, 10(12), Article ID 2206187.
Open this publication in new window or tab >>Lipid Nanoparticles Deliver the Therapeutic VEGFA mRNA In Vitro and In Vivo and Transform Extracellular Vesicles for Their Functional Extensions
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2023 (English)In: Advanced Science, E-ISSN 2198-3844, Vol. 10, no 12, article id 2206187Article in journal (Refereed) Published
Abstract [en]

Lipid nanoparticles (LNPs) are currently used to transport functional mRNAs, such as COVID-19 mRNA vaccines. The delivery of angiogenic molecules, such as therapeutic VEGF-A mRNA, to ischemic tissues for producing new blood vessels is an emerging strategy for the treatment of cardiovascular diseases. Here, the authors deliver VEGF-A mRNA via LNPs and study stoichiometric quantification of their uptake kinetics and how the transport of exogenous LNP-mRNAs between cells is functionally extended by cells’ own vehicles called extracellular vesicles (EVs). The results show that cellular uptake of LNPs and their mRNA molecules occurs quickly, and that the translation of exogenously delivered mRNA begins immediately. Following the VEGF-A mRNA delivery to cells via LNPs, a fraction of internalized VEGF-A mRNA is secreted via EVs. The overexpressed VEGF-A mRNA is detected in EVs secreted from three different cell types. Additionally, RNA-Seq analysis reveals that as cells’ response to LNP-VEGF-A mRNA treatment, several overexpressed proangiogenic transcripts are packaged into EVs. EVs are further deployed to deliver VEGF-A mRNA in vitro and in vivo. Upon equal amount of VEGF-A mRNA delivery via three EV types or LNPs in vitro, EVs from cardiac progenitor cells are the most efficient in promoting angiogenesis per amount of VEGF-A protein produced. Intravenous administration of luciferase mRNA shows that EVs could distribute translatable mRNA to different organs with the highest amounts of luciferase detected in the liver. Direct injections of VEGF-A mRNA (via EVs or LNPs) into mice heart result in locally produced VEGF-A protein without spillover to liver and circulation. In addition, EVs from cardiac progenitor cells cause minimal production of inflammatory cytokines in cardiac tissue compared with all other treatment types. Collectively, the data demonstrate that LNPs transform EVs as functional extensions to distribute therapeutic mRNA between cells, where EVs deliver this mRNA differently than LNPs. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2023
Keywords
Blood vessels, Cells, Cytology, Direct injection, Diseases, Heart, Mammals, Molecular biology, Molecules, Nanoparticles, Tissue, Copy number, Endocytose, Extracellular, Extracellular vesicle, In-vivo, Lipid nanoparticle-mRNA, Lipid nanoparticles, Luciferase mRNA, MRNA copy number, Uptake, VEGF-A mRNA, Proteins, endocytosis, extracellular vesicles, in vivo, LNP-mRNA
National Category
Cell Biology Biochemistry and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-22310 (URN)10.1002/advs.202206187 (DOI)000935087200001 ()36806740 (PubMedID)2-s2.0-85148415624 (Scopus ID)
Funder
Science for Life Laboratory, SciLifeLabKnut and Alice Wallenberg FoundationSwedish Research Council, 2020-01316Swedish Foundation for Strategic ResearchVinnova, 2017-02960Knowledge Foundation, 20160330
Note

CC BY 4.0

© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.

E-mail: hadi.valadi@gu.se

The authors acknowledge the support from the National Genomics Infrastructure in Stockholm funded by Science for Life (SciLife) Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. Moreover, the authors acknowledge Mr. Mario Soriano Navarro at the Responsable Servicio Microscopía Electrónica, Valencia Spain, for technical assistance. This work was supported by grants from the Swedish Foundation of Strategic Research (Stiftelsen för strategisk forskning: SSF) in the Industrial Research Centre, FoRmulaEx - Nucleotide Functional Drug Delivery (Grant ID: IRC15-0065), the Swedish research council (VR, Grant ID: 2020-01316), and the Swedish governmental agency for innovation systems (VINNOVA, Grant ID: 2017-02960). This research was also funded by the Systems Biology Research Centre at the University of Skövde under grants from the Knowledge Foundation (Grant ID: 20160330).

Available from: 2023-03-02 Created: 2023-03-02 Last updated: 2023-05-03Bibliographically approved
Österberg, K., Bogestål, Y., Jenndahl, L., Gustafsson-Hedberg, T., Synnergren, J., Holmgren, G., . . . Håkansson, J. (2023). Personalized tissue-engineered veins – long term safety, functionality and cellular transcriptome analysis in large animals. Biomaterials Science, 11(11), 3860-3877
Open this publication in new window or tab >>Personalized tissue-engineered veins – long term safety, functionality and cellular transcriptome analysis in large animals
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2023 (English)In: Biomaterials Science, ISSN 2047-4830, E-ISSN 2047-4849, Vol. 11, no 11, p. 3860-3877Article in journal (Refereed) Published
Abstract [en]

Tissue engineering is a promising methodology to produce advanced therapy medicinal products (ATMPs). We have developed personalized tissue engineered veins (P-TEV) as an alternative to autologous or synthetic vascular grafts utilized in reconstructive vein surgery. Our hypothesis is that individualization through reconditioning of a decellularized allogenic graft with autologous blood will prime the tissue for efficient recellularization, protect the graft from thrombosis, and decrease the risk of rejection. In this study, P-TEVs were transplanted to vena cava in pig, and the analysis of three veins after six months, six veins after 12 months and one vein after 14 months showed that all P-TEVs were fully patent, and the tissue was well recellularized and revascularized. To confirm that the ATMP product had the expected characteristics one year after transplantation, gene expression profiling of cells from P-TEV and native vena cava were analyzed and compared by qPCR and sequencing. The qPCR and bioinformatics analysis confirmed that the cells from the P-TEV were highly similar to the native cells, and we therefore conclude that P-TEV is functional and safe in large animals and have high potential for use as a clinical transplant graft.

Place, publisher, year, edition, pages
Royal Society of Chemistry, 2023
National Category
Cell and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-22436 (URN)10.1039/d2bm02011d (DOI)000972824700001 ()37078624 (PubMedID)2-s2.0-85160870522 (Scopus ID)
Funder
Vinnova, 2017-02130Knowledge Foundation, #2016-0330, #2020-0014
Note

CC BY 3.0

First published 13 Apr 2023

Joakim.hakansson@ri.se

This study was supported by Vinnova project CAMP (contract no. 2017-02130), a common call by VINNOVA and Vetenskapsrådet: Biologcal pharmaseuticals (Dnr 2017-02983), by University of Skövde under grants from the Swedish Knowledge Foundation [#2016-0330, #2020-0014] and Västra Götalandsregionen (consultant check). The company VERIGRAFT AB holds a patent on peripheral whole blood perfusion of decellularized tissues and did also finance the project. We want to acknowledge the staff at the Department of Experimental Biomedicine at Gothenburg University. The swine studies in Spain were conducted by the ICTS ‘NANBIOSIS’, specifically Units 21, 22, and 24 of the CCMIJU. Graphical Abstract image created with BioRender.com.

Available from: 2023-04-20 Created: 2023-04-20 Last updated: 2023-07-14Bibliographically approved
Stahlschmidt, S. R., Ulfenborg, B. & Synnergren, J. (2023). Predicting Cancer Stage from Circulating microRNA: A Comparative Analysis of Machine Learning Algorithms. In: Ignacio Rojas; Olga Valenzuela; Fernando Rojas Ruiz; Luis Javier Herrera; Francisco Ortuño (Ed.), Bioinformatics and Biomedical Engineering: 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12–14, 2023, Proceedings, Part I. Paper presented at 10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023 Meloneras 12 July 2023 through 14 July 2023 Code 297199 (pp. 103-115). Cham: Springer
Open this publication in new window or tab >>Predicting Cancer Stage from Circulating microRNA: A Comparative Analysis of Machine Learning Algorithms
2023 (English)In: Bioinformatics and Biomedical Engineering: 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12–14, 2023, Proceedings, Part I / [ed] Ignacio Rojas; Olga Valenzuela; Fernando Rojas Ruiz; Luis Javier Herrera; Francisco Ortuño, Cham: Springer, 2023, p. 103-115Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, serum-based tests for early detection and detection of tissue of origin are being developed. Circulating microRNA has been shown to be a potential source of diagnostic information that can be collected non-invasively. In this study, we investigate circulating microRNAs as predictors of cancer stage. Specifically, we predict whether a sample stems from a patient with early stage (0-II) or late stage cancer (III-IV). We trained five machine learning algorithms on a data set of cancers from twelve different primary sites. The results showed that cancer stage can be predicted from circulating microRNA with a sensitivity of 71.73%, specificity of 79.97%, as well as positive and negative predictive value of 54.81% and 89.29%, respectively. Furthermore, we compared the best pan-cancer model with models specialized on individual cancers and found no statistically significant difference. Finally, in the best performing pan-cancer model 185 microRNAs were significant. Comparing the five most relevant circulating microRNAs in the best performing model with the current literature showed some known associations to various cancers. In conclusion, the study showed the potential of circulating microRNA and machine learning algorithms to predict cancer stage and thus suggests that further research into its potential as a non-invasive clinical test is warranted. 

Place, publisher, year, edition, pages
Cham: Springer, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 13919
Keywords
cancer stage, circulating microRNA, liquid biopsy, machine learning, Clinical research, Diseases, Forecasting, Learning algorithms, RNA, Cancer models, Comparative analyzes, Diagnostics informations, Late stage, Machine learning algorithms, Machine-learning, Potential sources
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-23058 (URN)10.1007/978-3-031-34953-9_8 (DOI)2-s2.0-85164958861 (Scopus ID)978-3-031-34952-2 (ISBN)978-3-031-34953-9 (ISBN)
Conference
10th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2023 Meloneras 12 July 2023 through 14 July 2023 Code 297199
Funder
Knowledge Foundation, 20170302Knowledge Foundation, 20200014Swedish Research Council, 2022–06725
Note

Part of the book sub series: Lecture Notes in Bioinformatics (LNBI) Electronic ISSN 2366-6331 Print ISSN 2366-6323

© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

This work was supported by the University of Skövde, Swede nunder grants from the Knowledge Foundation (20170302, 20200014). The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at Chalmers University of Technology partially funded by the Swedish Research Council through grant agreement no. 2022–06725.

Available from: 2023-07-31 Created: 2023-07-31 Last updated: 2023-12-19Bibliographically approved
Sandstedt, M., Vukusic, K., Johansson, M., Jonsson, M., Magnusson, R., Hultén, L. M., . . . Sandstedt, J. (2023). Regional transcriptomic profiling reveals immune system enrichment in nonfailing atria as well as all chambers of the failing human heart. American Journal of Physiology. Heart and Circulatory Physiology, 325(6), H1430-H1445
Open this publication in new window or tab >>Regional transcriptomic profiling reveals immune system enrichment in nonfailing atria as well as all chambers of the failing human heart
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2023 (English)In: American Journal of Physiology. Heart and Circulatory Physiology, ISSN 0363-6135, E-ISSN 1522-1539, Vol. 325, no 6, p. H1430-H1445Article in journal (Refereed) Published
Abstract [en]

The different chambers of the human heart demonstrate regional physiological traits and may be differentially affected during pathologic remodeling, resulting in heart failure. Few previous studies have, however, characterized the different chambers at a transcriptomic level. We therefore conducted whole-tissue RNA sequencing and gene set enrichment analysis of biopsies collected from the four chambers of adult failing (n = 8) and nonfailing (n = 11) human hearts. Atria and ventricles demonstrated distinct transcriptional patterns. Compared to nonfailing ventricles, the transcriptional pattern of nonfailing atria was enriched for a large number of gene sets associated with cardiogenesis, the immune system and bone morphogenetic protein (BMP), transforming growth factor beta (TGF beta), MAPK/JNK and Wnt signaling. Differences between failing and nonfailing hearts were also determined. The transcriptional pattern of failing atria was distinct compared to that of nonfailing atria and enriched for gene sets associated with the innate and adaptive immune system, TGF beta/SMAD signaling, and changes in endothelial, smooth muscle cell and cardiomyocyte physiology. Failing ventricles were also enriched for gene sets associated with the immune system. Based on the transcriptomic patterns, upstream regulators associated with heart failure were identified. These included many immune response factors predicted to be similarly activated for all chambers of failing hearts. In summary, the heart chambers demonstrate distinct transcriptional patterns that differ between failing and nonfailing hearts. Immune system signaling may be a hallmark of all four heart chambers in failing hearts, and could constitute a novel therapeutic target.

Place, publisher, year, edition, pages
American Physiological Society, 2023
Keywords
Heart Failure, Immune system, Normal Heart, Transcriptomics, Upstream Regulators
National Category
Developmental Biology Genetics Medical Genetics Bioinformatics and Systems Biology Cell and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-23313 (URN)10.1152/ajpheart.00438.2023 (DOI)37830984 (PubMedID)2-s2.0-85178497083 (Scopus ID)
Funder
Swedish Heart Lung FoundationUniversity of SkövdeKnowledge FoundationSwedish Fund for Research Without Animal Experiments
Note

This study was funded by grants from the Swedish Society of Medicine, the Gothenburg Society of Medicine, the Heart-Lung Foundation, the Emelle Foundation, the foundations of the Sahlgrenska University Hospital, the University of Skövde, the Swedish Knowledge Foundation, the foundation Research Without Animal Experiments, and the Swedish Royal Academy and by ALF research grants from the Sahlgrenska University Hospital.

Available from: 2023-10-16 Created: 2023-10-16 Last updated: 2024-01-02Bibliographically approved
Johansson, M., Tangruksa, B., Heydarkhan-Hagvall, S., Jeppsson, A., Sartipy, P. & Synnergren, J. (2022). Data Mining Identifies CCN2 and THBS1 as Biomarker Candidates for Cardiac Hypertrophy. Life, 12(5), Article ID 726.
Open this publication in new window or tab >>Data Mining Identifies CCN2 and THBS1 as Biomarker Candidates for Cardiac Hypertrophy
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2022 (English)In: Life, E-ISSN 2075-1729, Vol. 12, no 5, article id 726Article in journal (Refereed) Published
Abstract [en]

Cardiac hypertrophy is a condition that may contribute to the development of heart failure. In this study, we compare the gene-expression patterns of our in vitro stem-cell-based cardiac hypertrophy model with the gene expression of biopsies collected from hypertrophic human hearts. Twenty-five differentially expressed genes (DEGs) from both groups were identified and the expression of selected corresponding secreted proteins were validated using ELISA and Western blot. Several biomarkers, including CCN2, THBS1, NPPA, and NPPB, were identified, which showed significant overexpressions in the hypertrophic samples in both the cardiac biopsies and in the endothelin-1-treated cells, both at gene and protein levels. The protein-interaction network analysis revealed CCN2 as a central node among the 25 overlapping DEGs, suggesting that this gene might play an important role in the development of cardiac hypertrophy. GO-enrichment analysis of the 25 DEGs revealed many biological processes associated with cardiac function and the development of cardiac hypertrophy. In conclusion, we identified important similarities between ET-1-stimulated human-stem-cell-derived cardiomyocytes and human hypertrophic cardiac tissue. Novel putative cardiac hypertrophy biomarkers were identified and validated on the protein level, lending support for further investigations to assess their potential for future clinical applications. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
biomarker, cardiac hypertrophy, disease model, endothelin-1, stem cells, transcriptomics
National Category
Cell and Molecular Biology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy) Bioinformatics and Systems Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-21200 (URN)10.3390/life12050726 (DOI)000802500000001 ()35629393 (PubMedID)2-s2.0-85130327246 (Scopus ID)
Funder
Knowledge Foundation, 20160294Knowledge Foundation, 20160330Knowledge Foundation, 20200014AstraZeneca
Note

CC BY 4.0

© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

This research was funded by the Systems Biology Research Centre at the University of Skövde under grants from the Knowledge Foundation (20160294, 20160330, 20200014), Takara Bio Europe, Gothenburg, Sweden, and AstraZeneca R&D, Gothenburg.

Data Availability Statement: This study is based on two trancriptomics datasets, which are available for download at ArrayExpress (https://www.ebi.ac.uk/arrayexpress/, accessed on 4 April 2022) accession numbers: E-MTAB-11030 and E-MEXP-2296.

Acknowledgments :The graphical abstract was created with BioRender software. The networks and functional analyses were generated through the use of IPA (Qiagen Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis, accessed on 1 March 2022)

Available from: 2022-06-02 Created: 2022-06-02 Last updated: 2022-07-12Bibliographically approved
Sandstedt, M., Vukusic, K., Ulfenborg, B., Jonsson, M., Mattsson Hultén, L., Dellgren, G., . . . Sandstedt, J. (2022). Human intracardiac SSEA4+CD34 cells show features of cycling, immature cardiomyocytes and are distinct from Side Population and C-kit+CD45- cells. PLOS ONE, 17(6), Article ID e0269985.
Open this publication in new window or tab >>Human intracardiac SSEA4+CD34 cells show features of cycling, immature cardiomyocytes and are distinct from Side Population and C-kit+CD45- cells
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2022 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 17, no 6, article id e0269985Article in journal (Refereed) Published
Abstract [en]

Cardiomyocyte proliferation has emerged as the main source of new cardiomyocytes in the adult. Progenitor cell populations may on the other hand contribute to the renewal of other cell types, including endothelial and smooth muscle cells. The phenotypes of immature cell populations in the adult human heart have not been extensively explored. We therefore investigated whether SSEA4+CD34- cells might constitute immature cycling cardiomyocytes in the adult failing and non-failing human heart. The phenotypes of Side Population (SP) and C-kit+CD45- progenitor cells were also analyzed. Biopsies from the four heart chambers were obtained from patients with end-stage heart failure as well as organ donors without chronic heart failure. Freshly dissociated cells underwent flow cytometric analysis and sorting. SSEA4+CD34- cells expressed high levels of cardiomyocyte, stem cell and proliferation markers. This pattern resembles that of cycling, immature, cardiomyocytes, which may be important in endogenous cardiac regeneration. SSEA4+CD34- cells isolated from failing hearts tended to express lower levels of cardiomyocyte markers as well as higher levels of stem cell markers. C-kit+CD45- and SP CD45- cells expressed high levels of endothelial and stem cell markers-corresponding to endothelial progenitor cells involved in endothelial renewal.

Place, publisher, year, edition, pages
PLOS, 2022
National Category
Cell and Molecular Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-21252 (URN)10.1371/journal.pone.0269985 (DOI)000843613300105 ()35709180 (PubMedID)2-s2.0-85132081811 (Scopus ID)
Note

CC BY 4.0

Copyright:  © 2022 Sandstedt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was funded by grants from the Swedish Society of Medicine (JS, https://www.sls.se/); The Gothenburg Society of Medicine (MS,JS, https://goteborgslakaresallskap.se/); the Emelle Foundation (MS); the Heart-Lung Foundation (LMH, https://www.hjart-lungfonden.se/); ALF research grant from the Sahlgrenska University Hospital (JS, LMH, https://www.sahlgrenska.se/); grants from the foundations of the Sahlgrenska University Hospital (MS, JS, https://www.sahlgrenska.se/) and University of Skövde (JSy, https://www.his.se), by grants from the Swedish Knowledge Foundation (https://www.kks.se).There was no additional external fundingreceived for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Available from: 2022-06-17 Created: 2022-06-17 Last updated: 2023-08-23Bibliographically approved
Stahlschmidt, S. R., Ulfenborg, B. & Synnergren, J. (2022). Multimodal deep learning for biomedical data fusion: a review. Briefings in Bioinformatics, 23(2), Article ID bbab569.
Open this publication in new window or tab >>Multimodal deep learning for biomedical data fusion: a review
2022 (English)In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 23, no 2, article id bbab569Article, review/survey (Refereed) Published
Abstract [en]

Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. Deep learning (DL)-based data fusion strategies are a popular approach for modeling these nonlinear relationships. Therefore, we review the current state-of-the-art of such methods and propose a detailed taxonomy that facilitates more informed choices of fusion strategies for biomedical applications, as well as research on novel methods. By doing so, we find that deep fusion strategies often outperform unimodal and shallow approaches. Additionally, the proposed subcategories of fusion strategies show different advantages and drawbacks. The review of current methods has shown that, especially for intermediate fusion strategies, joint representation learning is the preferred approach as it effectively models the complex interactions of different levels of biological organization. Finally, we note that gradual fusion, based on prior biological knowledge or on search strategies, is a promising future research path. Similarly, utilizing transfer learning might overcome sample size limitations of multimodal data sets. As these data sets become increasingly available, multimodal DL approaches present the opportunity to train holistic models that can learn the complex regulatory dynamics behind health and disease.

Place, publisher, year, edition, pages
Oxford University Press, 2022
Keywords
data integration, deep neural networks, fusion strategies, multi-omics, multimodal machine learning, representation learning
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-20873 (URN)10.1093/bib/bbab569 (DOI)000804196500091 ()35089332 (PubMedID)2-s2.0-85127534700 (Scopus ID)
Funder
Knowledge Foundation, 20170302Knowledge Foundation, 20200014
Note

CC BY-NC 4.0

Corresponding author: Sören Richard Stahlschmidt. Systems Biology Research Center, University of Skövde, Skövde, Sweden. E-mail: soren.richard.stahlschmidt@his.se

Published: 28 January 2022

This work was supported by the University of Skövde, Sweden under grants from the Knowledge Foundation (20170302, 20200014).

Available from: 2022-01-31 Created: 2022-01-31 Last updated: 2022-06-23Bibliographically approved
Johansson, M., Ulfenborg, B., Andersson, C. X., Heydarkhan-Hagvall, S., Jeppsson, A., Sartipy, P. & Synnergren, J. (2022). Multi-Omics Characterization of a Human Stem Cell-Based Model of Cardiac Hypertrophy. Life, 12(2), Article ID 293.
Open this publication in new window or tab >>Multi-Omics Characterization of a Human Stem Cell-Based Model of Cardiac Hypertrophy
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2022 (English)In: Life, E-ISSN 2075-1729, Vol. 12, no 2, article id 293Article in journal (Refereed) Published
Abstract [en]

Cardiac hypertrophy is an important and independent risk factor for the development of cardiac myopathy that may lead to heart failure. The mechanisms underlying the development of cardiac hypertrophy are yet not well understood. To increase the knowledge about mechanisms and regulatory pathways involved in the progression of cardiac hypertrophy, we have developed a human induced pluripotent stem cell (hiPSC)-based in vitro model of cardiac hypertrophy and performed extensive characterization using a multi-omics approach. In a series of experiments, hiPSC-derived cardiomyocytes were stimulated with Endothelin-1 for 8, 24, 48, and 72 h, and their transcriptome and secreted proteome were analyzed. The transcriptomic data show many enriched canonical pathways related to cardiac hypertrophy already at the earliest time point, e.g., cardiac hypertrophy signaling. An integrated transcriptome–secretome analysis enabled the identification of multimodal biomarkers that may prove highly relevant for monitoring early cardiac hypertrophy progression. Taken together, the results from this study demonstrate that our in vitro model displays a hypertrophic response on both transcriptomic- and secreted-proteomic levels. The results also shed novel insights into the underlying mechanisms of cardiac hypertrophy, and novel putative early cardiac hypertrophy biomarkers have been identified that warrant further investigation to assess their potential clinical relevance.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
cardiac hypertrophy, cardiomyocytes, disease model, endothelin-1, stem cells, transcriptomics, proteomics
National Category
Cell Biology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-20931 (URN)10.3390/life12020293 (DOI)000763058200001 ()35207580 (PubMedID)2-s2.0-85125071986 (Scopus ID)
Funder
Knowledge Foundation, 20160294Knowledge Foundation, 20160330AstraZeneca
Note

CC BY 4.0

Correspondence: markus.johansson@his.se

This article belongs to the Special Issue The Molecular Mechanism of Cardiovascular Disease

This research was funded by the Systems Biology Research Centre at the University of Skövde under grants from the Knowledge Foundation (20160294, 20160330), Takara Bio Europe, Gothenburg, Sweden, and AstraZeneca R&D, Gothenburg.

Available from: 2022-02-22 Created: 2022-02-22 Last updated: 2023-02-21Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4697-0590

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