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Sartipy, Peter
Publications (10 of 31) Show all publications
Toto, R. D., Goldenberg, R., Chertow, G. M., Cain, V., Stefánsson, B. V., Sjöström, C. D. & Sartipy, P. (2019). Correction of hypomagnesemia by dapagliflozin in patients with type 2 diabetes: A post hoc analysis of 10 randomized, placebo-controlled trials. Journal of diabetes and its complications, 33(10), Article ID 107402.
Open this publication in new window or tab >>Correction of hypomagnesemia by dapagliflozin in patients with type 2 diabetes: A post hoc analysis of 10 randomized, placebo-controlled trials
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2019 (English)In: Journal of diabetes and its complications, ISSN 1056-8727, E-ISSN 1873-460X, Vol. 33, no 10, article id 107402Article in journal (Refereed) Published
Abstract [en]

Aims: Hypomagnesemia (serum magnesium [Mg] <0.74 mmol/L [<1.8 mg/dL]) is commonly observed in patients with type 2 diabetes (T2D). This study investigated the effect of treatment with dapagliflozin 10 mg on Mg concentrations in patients with T2D. Methods: In this post hoc analysis, we used pooled data from 10 placebo-controlled studies of dapagliflozin over 24 weeks of treatment in patients with T2D. We evaluated the change in Mg in patients receiving dapagliflozin vs. placebo overall, and in subgroups with baseline hypomagnesemia and normal/hypermagnesemia (≥0.74 mmol/L [≥1.8 mg/dL]). We determined the proportion of patients with baseline hypomagnesemia who achieved Mg ≥0.74 mmol/L (≥1.8 mg/dL). Results: A total of 4398 patients with T2D were included. The mean change from baseline to week 24 in Mg was significantly larger with dapagliflozin vs. placebo; difference, 0.06 mmol/L (95% confidence interval [CI]: 0.05, 0.06). The proportion of patients with Mg within the population reference range after 24 weeks of treatment was significantly higher with dapagliflozin vs. placebo; difference, 47.8% (95% CI: 41.4, 53.9). The proportion of patients displaying hypermagnesemia did not increase with dapagliflozin treatment. Conclusions: Treatment with dapagliflozin 10 mg resulted in correction of Mg concentrations in patients with T2D and hypomagnesemia. 

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Dapagliflozin, Hypomagnesemia, Post hoc analysis, Randomized controlled trials, SGLT2 inhibitor, Type 2 diabetes
National Category
Endocrinology and Diabetes
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-17521 (URN)10.1016/j.jdiacomp.2019.06.007 (DOI)000488886900007 ()31375422 (PubMedID)2-s2.0-85069912043 (Scopus ID)
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-10-18Bibliographically approved
Granéli, C., Hicks, R., Brolén, G., Synnergren, J. & Sartipy, P. (2019). Diabetic Cardiomyopathy Modelling Using Induced Pluripotent Stem Cell Derived Cardiomyocytes: Recent Advances and Emerging Models. Stem Cell Reviews, 15(1), 13-22
Open this publication in new window or tab >>Diabetic Cardiomyopathy Modelling Using Induced Pluripotent Stem Cell Derived Cardiomyocytes: Recent Advances and Emerging Models
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2019 (English)In: Stem Cell Reviews, ISSN 1550-8943, E-ISSN 1558-6804, Vol. 15, no 1, p. 13-22Article in journal (Refereed) Published
Abstract [en]

The global burden of diabetes has drastically increased over the past decades and in 2017 approximately 4 million deaths were caused by diabetes and cardiovascular complications. Diabetic cardiomyopathy is a common complication of diabetes with early manifestations of diastolic dysfunction and left ventricular hypertrophy with subsequent progression to systolic dysfunction and ultimately heart failure. An in vitro model accurately recapitulating key processes of diabetic cardiomyopathy would provide a useful tool for investigations of underlying disease mechanisms to further our understanding of the disease and thereby potentially advance treatment strategies for patients. With their proliferative capacity and differentiation potential, human induced pluripotent stem cells (iPSCs) represent an appealing cell source for such a model system and cardiomyocytes derived from induced pluripotent stem cells have been used to establish other cardiovascular related disease models. Here we review recently made advances and discuss challenges still to be overcome with regard to diabetic cardiomyopathy models, with a special focus on iPSC-based systems. Recent publications as well as preliminary data presented here demonstrate the feasibility of generating cardiomyocytes with a diabetic phenotype, displaying insulin resistance, impaired calcium handling and hypertrophy. However, capturing the full metabolic- and functional phenotype of the diabetic cardiomyocyte remains to be accomplished. 

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Cardiomyocytes, Diabetic cardiomyopathy, Disease modeling, Induced pluripotent stem cells, Insulin resistance
National Category
Cell Biology
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-16413 (URN)10.1007/s12015-018-9858-1 (DOI)000457386100003 ()30343468 (PubMedID)2-s2.0-85055676513 (Scopus ID)
Available from: 2018-11-20 Created: 2018-11-20 Last updated: 2019-02-15Bibliographically approved
Heerspink, H. J. L., Sjöström, C. D., Inzucchi, S. E., Hallow, M. K., Cain, V. A., Rossing, P., . . . Sartipy, P. (2019). Reduction in albuminuria with dapagliflozin cannot be predicted by baseline clinical characteristics or changes in most other risk markers. Diabetes, obesity and metabolism, 21(3), 720-725
Open this publication in new window or tab >>Reduction in albuminuria with dapagliflozin cannot be predicted by baseline clinical characteristics or changes in most other risk markers
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2019 (English)In: Diabetes, obesity and metabolism, ISSN 1462-8902, E-ISSN 1463-1326, Vol. 21, no 3, p. 720-725Article in journal (Refereed) Published
Abstract [en]

The sodium glucose co-transporter-2 inhibitor dapagliflozin has been shown to decrease urinary albumin-to-creatinine ratio (UACR). This effect, however, varies among individual patients. In this study, we assessed the baseline characteristics and concurrent changes in other cardiovascular risk markers that might be associated with UACR response to dapagliflozin. A pooled analysis of 11 phase 3 randomized, controlled clinical trials was performed. UACR change from baseline after 24 weeks treatment with dapagliflozin 10 mg/d in 531 patients with type 2 diabetes and UACR ≥30 mg/g at baseline was determined. UACR response was defined as >30% reduction from baseline at 24 weeks, whereas UACR non-response was defined as ≤30% reduction at 24 weeks. A total of 288 (54%) patients were classified as responders and 243 (46%) as non-responders. At 24 weeks, the UACR-adjusted mean change from baseline was −71.2% and 25.9% in responders and non-responders, respectively. Baseline characteristics were similar between both groups. Changes in HbA1c and body weight were comparable across groups. Responders showed a numerically larger reduction in estimated glomerular filtration rate and systolic blood pressure versus non-responders. UACR reduction to dapagliflozin is an individual characteristic that cannot be predicted by baseline clinical features or changes in metabolic variables. Whether UACR response would improve long-term renal and cardiovascular outcomes remains to be determined. 

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing Inc., 2019
Keywords
albuminuria, dapagliflozin, diabetes, hypertension, sodium glucose co-transporter-2
National Category
Endocrinology and Diabetes
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-16534 (URN)10.1111/dom.13579 (DOI)000458268600032 ()30414240 (PubMedID)2-s2.0-85058234273 (Scopus ID)
Available from: 2018-12-28 Created: 2018-12-28 Last updated: 2019-02-21Bibliographically approved
Fioretto, P., Del Prato, S., Buse, J. B., Goldenberg, R., Giorgino, F., Reyner, D., . . . Sartipy, P. (2018). Efficacy and safety of dapagliflozin in patients with type 2 diabetes and moderate renal impairment (chronic kidney disease stage 3A): The DERIVE Study. Diabetes, obesity and metabolism, 20(11), 2532-2540
Open this publication in new window or tab >>Efficacy and safety of dapagliflozin in patients with type 2 diabetes and moderate renal impairment (chronic kidney disease stage 3A): The DERIVE Study
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2018 (English)In: Diabetes, obesity and metabolism, ISSN 1462-8902, E-ISSN 1463-1326, Vol. 20, no 11, p. 2532-2540Article in journal (Refereed) Published
Abstract [en]

Aims: Dapagliflozin is a selective inhibitor of sodium glucose co-transporter 2 (SGLT2). This study assessed the efficacy and safety of dapagliflozin 10 mg vs placebo in patients with type 2 diabetes (T2D) and moderate renal impairment (estimated glomerular filtration rate [eGFR], 45-59 mL/min/1.73 m(2); chronic kidney disease [CKD] stage 3A). Materials and methods: In this double-blind, parallel group, Phase 3 study (NCT02413398, ) patients with inadequately controlled T2D (HbA1c 7.0%-11.0%) were randomized (1:1) to dapagliflozin 10 mg once daily (N = 160) or matching placebo (N = 161) for 24 weeks. Randomization was stratified by pre-enrolment glucose-lowering therapy. The primary endpoint was change from baseline in HbA1c at Week 24. Results: At Week 24, compared with placebo, dapagliflozin significantly decreased HbA1c (difference [95% CI], -0.34% [-0.53, -0.15]; P < 0.001), body weight (difference [95% CI], -1.25 kg [-1.90, -0.59]; P < 0.001), fasting plasma glucose (difference [95% CI], -0.9 mmol/L [-1.5, -0.4]; P = 0.001) and systolic blood pressure (difference [95% CI], -3.1 mmHg [-6.3, 0.0]; P < 0.05). Decreases from baseline in eGFR were greater with dapagliflozin than placebo at Week 24 (-2.49 mL/min/1.73 m(2) [-4.96, -0.02]), however, eGFR returned to baseline levels at Week 27 (3 weeks post-treatment) (0.61 mL/min/1.73 m(2) [-1.59, 2.81]). No increase in adverse events (AEs; 41.9% vs 47.8%) or serious AEs (5.6% vs 8.7%) were reported with dapagliflozin versus placebo. No AEs of bone fractures, amputations or DKA were reported. Conclusions: The findings of this study (NCT02413398, ) support the positive benefit/risk profile of dapagliflozin for the treatment of patients with T2D and CKD 3A.

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing Inc., 2018
National Category
Medical and Health Sciences Endocrinology and Diabetes
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-16379 (URN)10.1111/dom.13413 (DOI)000446558100003 ()29888547 (PubMedID)2-s2.0-85050481073 (Scopus ID)
Note

Authors on behalf of the DERIVE Study Investigators

Available from: 2018-11-09 Created: 2018-11-09 Last updated: 2019-04-29Bibliographically approved
Holmgren, G., Sartipy, P., Andersson, C. X., Lindahl, A. & Synnergren, J. (2018). Expression profiling of human pluripotent stem cell-derived cardiomyocytes exposed to doxorubicin - integration and visualization of multi omics data. Toxicological Sciences, 163(1), 182-195
Open this publication in new window or tab >>Expression profiling of human pluripotent stem cell-derived cardiomyocytes exposed to doxorubicin - integration and visualization of multi omics data
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2018 (English)In: Toxicological Sciences, ISSN 1096-6080, E-ISSN 1096-0929, Vol. 163, no 1, p. 182-195Article in journal (Refereed) Published
Abstract [en]

Anthracyclines, such as doxorubicin, are highly efficient chemotherapeutic agents against a variety of cancers. However, anthracyclines are also among the most cardiotoxic therapeutic drugs presently on the market. Chemotherapeutic-induced cardiomyopathy is one of the leading causes of disease and mortality in cancer survivors. The exact mechanisms responsible for doxorubicin-induced cardiomyopathy are not completely known, but the fact that the cardiotoxicity is dose-dependent and that there is a variation in time-to-onset of toxicity, and gender- and age differences suggests that several mechanisms may be involved.In the present study, we investigated doxorubicin-induced cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes using proteomics. In addition, different sources of omics data (protein, mRNA, and microRNA) from the same experimental setup were further combined and analyzed using newly developed methods to identify differential expression in data of various origin and types. Subsequently, the results were integrated in order to generate a combined visualization of the findings.In our experimental model system, we exposed cardiomyocytes derived from human pluripotent stem cells to doxorubicin for up to two days, followed by a wash-out period of additionally 12 days. Besides an effect on the cell morphology and cardiomyocyte functionality, the data show a strong effect of doxorubicin on all molecular levels investigated. Differential expression patterns that show a linkage between the proteome, transcriptome, and the regulatory microRNA network, were identified. These findings help to increase the understanding of the mechanisms behind anthracycline-induced cardiotoxicity and suggest putative biomarkers for this condition.

Keywords
Human pluripotent stem cells, cardiomyocytes, doxorubicin, multi-omics data, proteomics, toxicity
National Category
Bioinformatics (Computational Biology)
Research subject
Bioinformatics; INF502 Biomarkers; INF501 Integration of -omics Data
Identifiers
urn:nbn:se:his:diva-14745 (URN)10.1093/toxsci/kfy012 (DOI)000432299900018 ()29385562 (PubMedID)2-s2.0-85046994085 (Scopus ID)
Available from: 2018-02-14 Created: 2018-02-14 Last updated: 2019-02-14Bibliographically approved
Ulfenborg, B., Karlsson, A., Riveiro, M., Améen, C., Åkesson, K., Andersson, C. X., . . . Synnergren, J. (2017). A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells. PLoS ONE, 12(6), Article ID e0179613.
Open this publication in new window or tab >>A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells
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2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 6, article id e0179613Article in journal (Refereed) Published
Abstract [en]

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic-and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

National Category
Bioinformatics and Systems Biology Bioinformatics (Computational Biology)
Research subject
Bioinformatics; Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science; INF501 Integration of -omics Data
Identifiers
urn:nbn:se:his:diva-14015 (URN)10.1371/journal.pone.0179613 (DOI)000404541500020 ()28654683 (PubMedID)2-s2.0-85021324072 (Scopus ID)
Available from: 2017-08-22 Created: 2017-08-22 Last updated: 2018-11-16Bibliographically approved
Ghosheh, N., Küppers-Munther, B., Asplund, A., Edsbagge, J., Ulfenborg, B., Andersson, T. B., . . . Synnergren, J. (2017). Comparative transcriptomics of hepatic differentiation of human pluripotent stem cells and adult human liver tissue. Physiological Genomics, 49(8), 430-446
Open this publication in new window or tab >>Comparative transcriptomics of hepatic differentiation of human pluripotent stem cells and adult human liver tissue
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2017 (English)In: Physiological Genomics, ISSN 1094-8341, E-ISSN 1531-2267, Vol. 49, no 8, p. 430-446Article in journal (Refereed) Published
Abstract [en]

Hepatocytes derived from human pluripotent stem cells (hPSC-HEP) have the potential to replace presently used hepatocyte sources applied in liver disease treatment and models of drug discovery and development. Established hepatocyte differentiation protocols are effective and generate hepatocytes, which recapitulate some key features of their in vivo counterparts. However, generating mature hPSC-HEP remains a challenge. In this study, we applied transcriptomics to investigate the progress of in vitro hepatic differentiation of hPSCs at the developmental stages, definitive endoderm, hepatoblasts, early hPSC-HEP, and mature hPSC-HEP, to identify functional targets that enhance efficient hepatocyte differentiation. Using functional annotation, pathway and protein interaction network analyses, we observed the grouping of differentially expressed genes in specific clusters representing typical developmental stages of hepatic differentiation. In addition, we identified hub proteins and modules that were involved in the cell cycle process at early differentiation stages. We also identified hub proteins that differed in expression levels between hPSC-HEP and the liver tissue controls. Moreover, we identified a module of genes that were expressed at higher levels in the liver tissue samples than in the hPSC-HEP. Considering that hub proteins and modules generally are essential and have important roles in the protein-protein interactions, further investigation of these genes and their regulators may contribute to a better understanding of the differentiation process. This may suggest novel target pathways and molecules for improvement of hPSC-HEP functionality, having the potential to finally bring this technology to a wider use.

Keywords
human pluripotent stem cell, stem cell-derived hepatocytes, liver tissue, differentiation, transcriptomics
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Bioinformatics; INF501 Integration of -omics Data; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-14112 (URN)10.1152/physiolgenomics.00007.2017 (DOI)000407487100004 ()28698227 (PubMedID)2-s2.0-85027420517 (Scopus ID)
Available from: 2017-09-14 Created: 2017-09-14 Last updated: 2018-11-16
Bays, H. E., Sartipy, P., Xu, J., Sjöström, C. D. & Underberg, J. A. (2017). Dapagliflozin in patients with type II diabetes mellitus, with and without elevated triglyceride and reduced high-density lipoprotein cholesterol levels. Journal of Clinical Lipidology, 11(2), 450-458
Open this publication in new window or tab >>Dapagliflozin in patients with type II diabetes mellitus, with and without elevated triglyceride and reduced high-density lipoprotein cholesterol levels
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2017 (English)In: Journal of Clinical Lipidology, ISSN 1933-2874, E-ISSN 1876-4789, Vol. 11, no 2, p. 450-458Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Dapagliflozin is a selective sodium-glucose cotransporter 2 inhibitor that improves glycemic control in patients with type II diabetes mellitus (T2DM) by reducing renal glucose reabsorption.

OBJECTIVE: The aim was to evaluate the lipid effects of dapagliflozin 10 mg or placebo in patients with T2DM with/without baseline elevated triglyceride and reduced high-density lipoprotein (HDL) cholesterol levels.

METHODS: This was a post hoc analysis of 10 phase 3, placebo-controlled studies of dapagliflozin 10 mg (N = 2237) or placebo (N = 2164) administered for 24 weeks in patients with T2DM. Patients with elevated triglyceride (>= 150 mg/dL [1.69 mmol/L]) and reduced HDL cholesterol levels (<40 mg/dL [1.04 mmol/L] in men; <50 mg/dL [1.29 mmol/L] in women) were included (group A). The reference group (group B) included patients who did not meet the defined lipid criteria.

RESULTS: The effects of dapagliflozin on fasting lipid profiles were generally similar in the 2 lipid groups (ie, groups A and B) and, compared with placebo, were associated with minor increases in non-HDL cholesterol, low-density lipoprotein, and HDL cholesterol levels. The effects on triglyceride levels were inconsistent. The incidence of adverse events (AEs)/serious AEs, and AEs of genital infection, urinary tract infection, volume reduction, renal function, and hypoglycemia were similar in the 2 lipid groups.

CONCLUSION: Patients with T2DM treated with dapagliflozin experienced minor changes in lipid levels; the changes were generally similar in the 2 lipid groups. The clinical significance of these changes in lipids is unclear, especially in view of the positive effects of dapagliflozin on other cardiovascular disease risk factors. 

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Dapagliflozin, Dyslipidemia, Type II diabetes mellitus, SGLT2 inhibitors, Cardiovascular
National Category
Basic Medicine Clinical Medicine
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
urn:nbn:se:his:diva-13728 (URN)10.1016/j.jacl.2017.01.018 (DOI)000402346500018 ()28502502 (PubMedID)2-s2.0-85015260431 (Scopus ID)
Available from: 2017-06-20 Created: 2017-06-20 Last updated: 2019-02-14Bibliographically approved
Sartipy, P., Holmgren, G., Synnergren, J., Andersson, C. & Lindahl, A. (2017). Visual integration of multiple omics data from human pluripotent stem cell-derived cardiomyocytes. In: : . Paper presented at International Society for Stem Cell Research (ISSCR) Annual meeting, Boston 14–17 June 2017 (pp. 13).
Open this publication in new window or tab >>Visual integration of multiple omics data from human pluripotent stem cell-derived cardiomyocytes
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2017 (English)Conference paper, Poster (with or without abstract) (Refereed)
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-14761 (URN)
Conference
International Society for Stem Cell Research (ISSCR) Annual meeting, Boston 14–17 June 2017
Available from: 2018-02-20 Created: 2018-02-20 Last updated: 2018-02-26Bibliographically approved
Synnergren, J., Drowley, L., Plowright, A. T., Brolén, G., Goumans, M.-J., Gittenberger-de Groot, A. C., . . . Wang, Q.-D. (2016). Comparative transcriptomic analysis identifies genes differentially expressed in human epicardial progenitors and hiPSC-derived cardiac progenitors. Physiological Genomics, 48(11), 771-784
Open this publication in new window or tab >>Comparative transcriptomic analysis identifies genes differentially expressed in human epicardial progenitors and hiPSC-derived cardiac progenitors
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2016 (English)In: Physiological Genomics, ISSN 1094-8341, E-ISSN 1531-2267, Vol. 48, no 11, p. 771-784Article in journal (Refereed) Published
Abstract [en]

Comparative transcriptomic analysis identifies genes differentially expressed in human epicardial progenitor cells and hiPSC-derived cardiac progenitor cells: effects of hypoxic vs normoxic culture conditions.

National Category
Medical and Health Sciences Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject
Bioinformatics
Identifiers
urn:nbn:se:his:diva-13045 (URN)10.1152/physiolgenomics.00064.2016 (DOI)000389638800001 ()27591124 (PubMedID)2-s2.0-84994667368 (Scopus ID)
Available from: 2016-10-24 Created: 2016-10-24 Last updated: 2018-07-31Bibliographically approved
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