16 research outputs found
Multiway modeling and analysis in stem cell systems biology
<p>Abstract</p> <p>Background</p> <p>Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells.</p> <p>Results</p> <p>We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate.</p> <p>Conclusion</p> <p>Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.</p
Effect of different surface treatments on the shear bond strength of resin cement to zirconia ceramic and metal alloy
Experimental infection of Peste des Petit Ruminant virus and Mannheimia haemolytica A2 in goats: immunolocalisation of Mannheimia haemolytica antigens
Effect of some medium parameters on Brilliant Blue G biosorption by Amberlite resin/Agaricus campestris
Liquid Crystalline Systems for Transdermal Delivery of Celecoxib: In Vitro Drug Release and Skin Permeation Studies
Clinical significance of hepatic steatosis according to coronary plaque morphology: assessment using controlled attenuation parameter
Parameters of Patients with Diabetes Mellitus (TEMD Obesity Study)
Background: Obesity is the main obstacle for metabolic control in patients with type 2 diabetes. Turkey has the highest prevalence of obesity and type 2 diabetes in Europe. The effect of obesity on the metabolic control, and the macro-and microvascular complications of patients are not apparent. Objectives: This nationwide survey aimed to investigate the prevalence of overweight and obesity among patients with type 2 diabetes and to search for the impact of obesity on the metabolic control of these patients. We also investigated the independent associates of obesity in patients with type 2 diabetes. Methods: We consecutively enrolled patients who were under follow-up for at least 1 year in 69 tertiary healthcare units in 37 cities. The demographic, anthropometric, and clinical data including medications were recorded. Patients were excluded if they were pregnant, younger than 18 years, had decompensated liver disease, psychiatric disorders interfering with cognition or compliance, had bariatric surgery, or were undergoing renal replacement therapy. Results: Only 10% of patients with type 2 diabetes (n = 4,648) had normal body mass indexes (BMI), while the others were affected by overweight (31%) or obesity (59%). Women had a significantly higher prevalence of obesity (53.4 vs. 40%) and severe obesity (16.6 vs. 3.3%). Significant associations were present between high BMI levels and lower education levels, intake of insulin, antihypertensives and statins, poor metabolic control, or the presence of microvascular complications. Age, gender, level of education, smoking, and physical inactivity were the independent associates of obesity in patients with type 2 diabetes. Conclusion: The TEMD Obesity Study shows that obesity is a major determinant of the poor metabolic control in patients with type 2 diabetes. These results underline the importance of prevention and management of obesity to improve health care in patients with type 2 diabetes. Also, the results point out the independent sociodemographic and clinical associates of obesity, which should be the prior targets to overcome, in the national fight with obesity. (c) 2019 The Author(s) Published by S. 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Tamer; Cetinkaya Altuntas, Seher] Cukurova Univ, Sch Med, Dept Endocrinol & Metab, Adana, Turkey.[Atmaca, Aysegul; Durmus, Elif Tutku] 19 Mayis Univ, Sch Med, Dept Endocrinol & Metab, Samsun, Turkey.[Mete, Turkan] Univ Hlth Sci, Sch Med, Samsun Training & Res Hosp, Dept Endocrinol & Metab, Samsun, Turkey.[Dikbas, Oguz] Giresun Univ, Sch Med, Dept Endocrinol & Metab, Giresun, Turkey.[Akin, Safak] Recep Tayyip Erdogan Univ, Sch Med, Dept Endocrinol & Metab, Rize, Turkey.[Nuhoglu, Irfan; Ersoz, Halil Onder] Karadeniz Tech Univ, Sch Med, Dept Endocrinol & Metab, Trabzon, Turkey.[Bayraktaroglu, Taner] Bulent Ecevit Univ, Sch Med, Dept Endocrinol & Metab, Zonguldak, Turkey.[Sisman, Pinar] Kars Harakani State Hosp, Dept Endocrinol & Metab, Kars, Turkey.[Sahin, Ibrahim; Cetin, Sedat] Inonu Univ, Sch Med, Dept Endocrinol & Metab, Malatya, Turkey.[Capoglu, Ilyas; Akbas, Emin Murat] Erzincan Univ, Sch Med, Dept Endocrinol & Metab, Erzincan, Turkey.[Ucler, Rifki] Yuzuncu Yil Univ, Sch Med, Dept Endocrinol & Metab, Van, Turkey.[Eren, Mehmet Ali] Harran Univ, Sch Med, Dept Endocrinol & Metab, Sanliurfa, Turkey.[Tuzcu, Alpaslan Kemal; Pekkolay, Zafer] Dicle Univ, Sch Med, Dept Endocrinol & Metab, Diyarbakir, Turkey.[Ozkaya, Mesut] Univ Hlth Sci, Sch Med, Gaziantep Ersin Arslan Res & Training Hosp, Gaziantep, Turkey.[Araz, Mustafa] Gaziantep Univ, Sch Med, Dept Endocrinol & Metab, Gaziantep, Turkey.[Salman, Serpil] Liv Hosp Ulus, Dept Endocrinol & Metab, Istanbul, Turkey.[Dizdar, Oguzhan Sitki] Kayseri Educ & Res Hosp, Dept Internal Med, Kayseri, Turkey.[Gurkan, Eren] Mustafa Kemal Univ, Dept Endocrinol & Metab, Antakya, Turkey.[Kargili Carlioglu, Ayse] Erzurum Reg Educ & Res Hosp, Dept Endocrinol & Metab, Erzurum, Turkey