Differentiation of definitive endoderm from human induced pluripotent stem cells on hMSCs feeder in a defined medium

Background: The Definitive Endoderm (DE) differentiation using the undefined media and non-human feeders can cause contaminations in the generated cells for therapeutic applications. Therefore, generating safer and more appropriate DE cells is needed. This study compared five different methods to establish an appropriate method for inducing an efficient DE differentiation from Human Induced Pluripotent Stem Cells (hiPSCs) on an appropriate feeder in a more defined medium. Methods: Human Induced Pluripotent Stem Cells (hiPSCs) were cultured on inactivated feeders. Passaged hiPSCs, without feeder, were incubated for three days with Activin-A and different endodermal differentiation media including 1-FBS, 2-B27, 3- ITS and albumin fraction-V, 4-B27 and ITS and 5-like the third medium. The feeder cells in the first four methods were Mouse Embryonic Fibroblasts (MEFs) and in the fifth method were human adult bone marrow Mesenchymal Stem Cells (hMSCs). DE markers FOXA2, SOX17 and CXCR4 and also pluripotency marker OCT4 were evaluated using qRT-PCR, as well as FOXA2 by the immunocytochemistry. Results: QRT-PCR analysis showed that after three days, the expression levels of DE and pluripotency markers in the differentiated hiPSCs among all five groups did not have any significant differences. Similarly, the immunocytochemistry analysis demonstrated that the differentiated hiPSCs expressed FOXA2, with no significant differences. Conclusion: Despite this similarity in the results, the third differentiation medium has more defined and cost effective components. Furthermore, hMSC, a human feeder, is safer than MEF. Therefore, the fifth method is preferable among other DE differentiation methods and can serve as a fundamental method helping the development of regenerative medicine. © 2016, Avicenna Journal of Medical Biotechnology. All rights reserved

Application of Different Learning Methods for the Modelling of Microstrip Characteristics

In this paper, the performance of four machine learning regressions like Support Vector Machine (SVM), Least Square-Support Vector Machine (LS-SVM), Gaussian Process Regression (GPR) and Random Forest method (RF) are investigated by means of an illustrative example referring to the characteristic impedance of a microstrip line in terms of electrical and geometrical parameters. The required dataset for training is obtained from a set of parametric electromagnetic simulations. The performance comparison of the four methods is done in the presence and absence of numerical noise and inaccuracies affecting the training samples. The results of our comparison provide a guidance for the proper method selection to model the electromagnetic characteristics of interconnects for high-speed signals: advantages and drawbacks of each of the proposed techniques clearly emerge from this analysis

Overexpression of microRNA-16 declines cellular growth, proliferation and induces apoptosis in human breast cancer cells

MicroRNAs (miRNA) are a large family of small single-stranded RNA molecules found in all multicellular organisms. Early studies have been shown that miRNA are involved in cancer development and progression, and this role can be done by working as an oncogenes and tumor suppressor genes, so manipulation of this molecules can be a promising approach in cancer therapy, and experimental results represented that the modification in breast cancer phenotype is possible by miRNA expression alteration. miR-16, which is located in 13q14 chromosome, plays critical roles as a tumor suppressor by targeting several oncogenes which regulate cell cycle and apoptosis. Hence, in the present study, we investigated whether miR-16 could decline growth and survival of MCF-7 cell line as model of human breast cancer. MCF-7 cell line was infected with lentiviruses containing miR-16 precursor sequence. The effects of ectopic expression of miR-16 on breast cancer phenotype were examined by cell cycle analysis and apoptosis assays. miR-16 cytotoxicity effect was measured by the MTT assay. We showed that the miR-16 overexpression reduces Cyclin D1 and BCL2 at messenger RNA (mRNA) and protein levels in MCF-7 cell line. In addition, this is found that enforced expression of miR-16 decreases cell growth and proliferation and induces apoptosis in MCF-7 cells. In conclusion, our results revealed that upregulation of miR-16 would be a potential approach for breast cancer therapy. © 2015, The Society for In Vitro Biology

Relationship of some risk factors and symptoms in patients with acute coronary syndrome

Acute coronary syndrome (ACS) is one of the major causes of death in the worldwide. Clinical manifestations are different. So it's necessary to have knowledge about the types of symptoms experienced by patients with ACS. This study was performed to assay the Relationship of some risk factors and symptoms in patients with acute coronary syndrome. This cross-sectional study, were studied 294 patients with acute coronary syndrome at least 24 hours after admission had survived. Data was collected by a questionnaire that included demographic data form and check list of some symptoms and history of risk factors. There was a significant relationship between STEMI with vomiting (OR=1.94) and anxiety (OR=1.83) and UA with vomiting (OR=0.42). Between sex with weakness (OR=2.29) and anxiety (OR=1.82), diabetes with dyspenea (OR=1.8), weakness (OR=1.02) and tinnitus (OR=2.06) and hyperlipidemia with weakness (OR=2.35) and tinnitus (OR=2.49) was available significant difference. The findings of this study indicate that the appearance of symptoms of acute coronary syndrome were different as for ECG changes and risk factors, and more focused on those symptoms that they are common with any other diseases. Since, many of the symptoms of acute coronary syndrome can be potentially dangerous and life threatening, accurate diagnosis and timely action is crucial for the patients

Long Term Factors of Internet Diffusion in Sub-Saharan Africa: A Panel Co- Integration Analysis

Identifying factors that influence the diffusion of the Internet is paramount for researchers as well as policy makers in articulating strategies to improve the availability and subsequent use of the Internet. Most existing empirical studies have focused on this problem by analyzing diffusion data for countries for one fixed year and identified variables affecting the Internet diffusion. These variables, generally, come from the economic, technological, policy, culture, and human capital realms. These results have provided a good “snapshot” of what factors are important towards the diffusion of the Internet and the results tend to vary for studies conducted in different time frames. This paper also addresses, the phenomenon of cross-country dependence – the economic, political, and technological environment of one country affecting other countries- into account in their analyses. This paper, for the first time in the literature, empirically identifies long-term determinants of the Internet diffusion in sub-Saharan African (SSA) countries by considering data for the period 1997-2013. It employs a recently-developed technique named “panel co-integration analysis” to model the diffusion of the internet among the SSA countries. The analysis reveals that in SSA countries, the number of telephones, the level of per capita real gross product and the extent of ruralization (conversely, the degree of urbanization) are the key long-term drivers of the diffusion of the Internet. Finally, the paper concludes with a discussion of policy implications

Stochastic Time-Domain Mapping for Comprehensive Uncertainty Assessment in Eye Diagrams

The eye diagram is one of the most common tools used for quality assessment in high-speed links. This article proposes a method of predicting the shape of the inner eye for a link subject to uncertainties. The approach relies on machine learning regression and is tested on the very challenging example of flexible link for smart textiles. Several sources of uncertainties are taken into account related to both manufacturing tolerances and physical deformation. The resulting model is fast and accurate. It is also extremely versatile: rather than focusing on a specific metric derived from the eye diagram, its aim is to fully reconstruct the inner eye and enable designers to use it as they see fit. This article investigates the features and convergence of three alternative machine learning algorithms, including the single-output support vector machine regression, together with its least squares variant, and the vector-valued kernel ridge regression. The latter method is arguably the most promising, resulting in an accurate, fast and robust tool enabling a complete parametric stochastic map of the eye

Efficacy of aftercare services for people with severe mental disorders in Iran: A randomized controlled trial

Objectives: This study aimed to determine whether after-care services reduced the number of rehospitalizations and length of hospital stay among patients with severe mental disorders. Methods: A total of 120 patients with schizophrenia and schizoaffective or bipolar disorder between the ages of 15 and 65 were recruited from 2010 to 2012 for a randomized controlled trial. The participants were followed up for 20 months after discharge from a university-affiliated hospital in Tehran, Iran. The selection procedure was random sampling. Sixty patients received aftercare services, which included treatment follow-up, family psychoeducation, and patient social skills training, and 60 patients received treatment as usual. Number of hospitalizations and length of hospital stay were primary outcome measures, and severity of psychopathology and severity of illness were secondary outcome measures. The quantitative primary and secondary outcomes measures were compared by using repeated-measures analysis. Results: Three members of the control group did not complete the study. The cumulative number of hospitalizations during the follow-up period was 55 for the control group and 26 for the intervention group. Length of stay was significantly greater in the control group compared with the intervention group (rate ratio=2.38, 95 confidence interval=2.17-2.62). Psychopathology was less severe in the intervention group compared with the control group (p<.001). Conclusions: Aftercare services are efficacious for reducing both the need for rehospitalization and the severity of psychopathology. © 2015, American Psychiatric Association. All rights reserved