Stimulation of oxytocin receptor during early reperfusion period protects the heart against ischemia/reperfusion injury: The role of mitochondrial ATP-sensitive potassium channel, nitric oxide, and prostaglandins

Postconditioning is a simple and safe strategy for cardioprotection and infarct size limitation. Our previous study showed that oxytocin (OT) exerts postconditioning effect on ischemic/reperfused isolated rat heart. The aim of this study was to investigate the involvement of OT receptor, mitochondrial ATP-sensitive potassium channel (mKATP), nitric oxide (NO) and cyclooxygenase (COX) pathways in OT postconditioning. Isolated rat hearts were divided into10 groups and underwent 30 min of regional ischemia followed by 120 min of reperfusion (n =6). In I/R (ischemia/reperfusion) group, ischemia and reperfusion were induced without any treatment. In OT group, oxytocin was perfused 5 min prior to beginning of reperfusion for 25 min. In groups 3-6, atosiban (oxytocin receptor blocker), L-NAME (N-Nitro-L-Arginine Methyl Ester, non-specific nitric oxide synthase inhibitor), 5-HD (5-hydroxydecanoate, mKATP inhibitor) and indomethacin (cyclooxygenase inhibitor) were infused prior to oxytocin administration. In others, the mentioned inhibitors were perfused prior to ischemia without oxytocin infusion. Infarct size, ventricular hemodynamic, coronary effluent, malondialdehyde (MDA) and lactate dehydrogenase (LDH) were measured at the end of reperfusion. OT perfusion significantly reduced infarct size, MDA and LDH in comparison with IR group. Atosiban, 5HD, L-NAME and indomethacin abolished the postconditioning effect of OT. Perfusion of the inhibitors alone prior to ischemia had no effect on infarct size, hemodynamic parameters, coronary effluent and biochemical markers as compared with I/R group. In conclusion, this study indicates that postconditioning effects of OT are mediated by activation of mKATP and production of NO and Prostaglandins (PGs). © 2015 Tehran University of Medical Sciences. All rights reserved

Synthesis, characterization and photo behavior of new poly(amide-imide)/montmorillonite nanocomposite containing N,N'-pyrromellitoyl-bis-L-alanine

Two new samples of poly(amide-imide)-nanocomposites were synthesized by insertion nano silicate particles in poly(amide-imide) (PAI) chains using a convenient solution intercalation technique. PAI as a source of polymer matrix was synthesized by the direct polycondensation reaction of N,N'-pyrromelitoyl-bis-L-alanine with 4,4'-diamino diphenyl ether in the presence of triphenyl phosphite (TPP), CaCl2, pyridine and N-methyl-2-pyrrolidone (NMP). Morphology and structure of the resulting PAI-nanocomposite films with 5 and 10% silicate particles were characterized by FTIR spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM). The effect of clay dispersion and the interaction between clay and polymeric chains on the properties of nanocomposites films were investigated by using UV-Vis spectroscopy, thermogravimetric analysis (TGA) and water uptake measurements.DOI: http://dx.doi.org/10.4314/bcse.v27i3.1

Stakeholders’ impact on the reuse potential of structural elements at the end-of-life of a building: A machine learning approach

The construction industry, and at its core the building sector, is the largest consumer of non-renewable resources, which produces the highest amount of waste and greenhouse gas emissions worldwide. Since most of the embodied energy and CO2 emissions during the construction and demolition phases of a building are related to its structure, measures to extend the service life of these components should be prioritised. This study develops a set of easy-to-understand instructions to facilitate the practitioners in assessing the social sustainability and responsibility of reusing the load-bearing structural components within the building sector. The results derived by developing and then employing advanced machine learning techniques indicate that the most significant social factor is the perception of the regulatory authorities. The second and third ranks among the social reusability factors belong to risks. Since there is a strong correlation between perception and risk, the potential risks associated with reusing structural elements affect the stakeholders’ perception of reuse. The Bayesian network developed in this study unveil the complex and non-linear correlation between variables, which means none of the factors could alone determine the reusability of an element. This paper shows that by using the basics of probability theory and combining them with advanced supervised machine learning techniques, it is possible to develop tools that reliably estimate the social reusability of these elements based on influencing variables. Therefore, the authors propose using the developed approach in this study to promote materials' circularity in different construction industry sub-sectors

Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients.

BACKGROUND: Within the UK, COVID-19 has contributed towards over 103,000 deaths. Although multiple risk factors for COVID-19 have been identified, using this data to improve clinical care has proven challenging. The main aim of this study is to develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, thus enabling risk-stratification and earlier clinical decision-making. METHODS: Anonymised data consisting of 44 independent predictor variables from 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case-control analysis. Primary outcomes included inpatient mortality, required ventilatory support, and duration of inpatient treatment. Pulmonary embolism sequala was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were then learned and constructed using Bayesian networks. RESULTS: The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and clinical decision-making tools

Quantitative miRNA Expression Analysis Using Fluidigm Microfluidics Dynamic Arrays

MicroRNA (miRNA) is a small non-coding RNA that can regulate gene expression in both plants and animals. Studies showed that miRNAs play a critical role in human cancer by targeting messenger RNAs that are positive or negative regulators of cell proliferation and apoptosis. Here, we evaluated miRNA expression in formalin fixed, paraffin embedded (FFPE) samples and fresh frozen (FF) samples using a high throughput qPCR-based microfluidic dynamic array technology (Fluidigm). We compared the results to hybridization-based microarray platforms using the same samples. We obtained a highly correlated Ct values between multiplex and single-plex RT reactions using standard qPCR assays for miRNA expression. For the same samples, the microfluidic technology (Fluidigm 48.48 dynamic array systems) resulted in a left shift towards lower Ct values compared to those observed by standard TaqMan (ABI 7900HT, mean difference, 3.79). In addition, as little as 10ng total RNA was sufficient to reproducibly detect up to 96 miRNAs at a wide range of expression values using a single 96-multiplexing RT reaction in either FFPE or FF samples. Comparison of miRNAs expression values measured by microfluidic technology with those obtained by other array and Next Generation sequencing platforms showed positive concordance using the same samples but revealed significant differences for a large fraction of miRNA targets. The qPCRarray based microfluidic technology can be used in conjunction with multiplexed RT reactions for miRNA gene expression profiling. This approach is highly reproducible and the results correlate closely with the existing singleplex qPCR platform while achieving much higher throughput at lower sample input and reagent usage. It is a rapid, cost effective, customizable array platform for miRNA expression profiling and validation. However, comparison of miRNA expression using different platforms requires caution and the use of multiple platforms

Multiple Analytical Approaches Reveal Distinct Gene-Environment Interactions in Smokers and Non Smokers in Lung Cancer

Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11–2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25–0.65,p<0.001 and OR = 0.51;95%CI = 0.33–0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33–10.55,p = 0.006), whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15–7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer

Lavender Oil Attenuates Myocardial Ischemia/Reperfusion Injury Through Inhibition of Autophagy and Stimulation of Angiogenesis

Myocardial infarction (MI) is a serious threat to human health that creates millions of death annually. In this study, we went on to examine molecular mechanism of lavender oil that which by give rises to cardioprotection against MI. An MI model was established in male Wistar rats by ligation of the left anterior descending coronary artery (LAD) and lavender oil at 100 mg/kg concentration 1 h after reperfusion was intraperitoneally administrated. ELISA assay was used to evaluate the activities of myocardial injury markers. Western blot and immunohistochemical assays were used to evaluate the expression of beclin-1, LC3II/LC3I ratio, CD34 and vascular endothelial growth factor (VEGF). RT-PCR was applied to investigate the mRNA levels of apoptotic factors. Compared to sham, increased levels of myocardial injury markers, pro-apoptotic and autophagic factors were found in MI rats that were reversed by post-treatment with lavender oil. Likewise, reduced levels of anti-apoptotic factors and VEGF were observed in MI/R group compared to sham that reversed by lavender oil. Collectively, our findings showed the validity of lavender oil as an excellent candidate to create cardioprotection effects against MI/R injury. © 2021, Shiraz University

ELABELA (ELA) Peptide Exerts Cardioprotection Against Myocardial Infarction by Targeting Oxidative Stress and the Improvement of Heart Function

Emerging evidence has shown that ELA peptide plays a pivotal role in cardiac development and modulation of vascular and cardiac function. In the current work, we sought to examine the possible therapeutic potential of ELA peptide to reduce I/R injury following MI and elucidate the possible mechanisms by which ELA peptide may ameliorate injury and improve heart function after MI. 5 µg/kg of ELA peptide was administrated intraperitoneally in rats once per day for 4 days after ischemia of heart for 30 min. Male Wistar rats were sacrificed at 24 h and 2 weeks after reperfusion. The infarct size was determined by TTC staining 2 weeks after reperfusion. ELISA was employed to measure serum level of myocardial injury markers such as LDH, CK-MB and Troponin I and oxidative stress markers such as membrane lipid peroxidation (MDA), GSH and SOD activities in the first 24 h. Cardiac function was evaluated using echocardiography prior to MI and 2 weeks after reperfusion. After administration of ELA peptide in MI rats, infarct size, serum levels of LDH, CK-MB, Troponin I and tissue levels of MDA were significantly reduced; GSH and SOD activities were markedly increased (p < 0.05). Likewise, ELA peptide improved cardiac function 2 weeks after MI (p < 0.05). ELA peptide administration for 4 days after MI could reduce injury by targeting oxidative stress and improvement of cardiac function. These findings establish a fundamental foundation for future peptide research and therapy. © 2018 Springer Science+Business Media, LLC, part of Springer Natur

ELABELA (ELA) Peptide Exerts Cardioprotection Against Myocardial Infarction by Targeting Oxidative Stress and the Improvement of Heart Function

Emerging evidence has shown that ELA peptide plays a pivotal role in cardiac development and modulation of vascular and cardiac function. In the current work, we sought to examine the possible therapeutic potential of ELA peptide to reduce I/R injury following MI and elucidate the possible mechanisms by which ELA peptide may ameliorate injury and improve heart function after MI. 5 µg/kg of ELA peptide was administrated intraperitoneally in rats once per day for 4 days after ischemia of heart for 30 min. Male Wistar rats were sacrificed at 24 h and 2 weeks after reperfusion. The infarct size was determined by TTC staining 2 weeks after reperfusion. ELISA was employed to measure serum level of myocardial injury markers such as LDH, CK-MB and Troponin I and oxidative stress markers such as membrane lipid peroxidation (MDA), GSH and SOD activities in the first 24 h. Cardiac function was evaluated using echocardiography prior to MI and 2 weeks after reperfusion. After administration of ELA peptide in MI rats, infarct size, serum levels of LDH, CK-MB, Troponin I and tissue levels of MDA were significantly reduced; GSH and SOD activities were markedly increased (p < 0.05). Likewise, ELA peptide improved cardiac function 2 weeks after MI (p < 0.05). ELA peptide administration for 4 days after MI could reduce injury by targeting oxidative stress and improvement of cardiac function. These findings establish a fundamental foundation for future peptide research and therapy. © 2018, Springer Science+Business Media, LLC, part of Springer Nature

ELABELA (ELA) Peptide Exerts Cardioprotection Against Myocardial Infarction by Targeting Oxidative Stress and the Improvement of Heart Function

Emerging evidence has shown that ELA peptide plays a pivotal role in cardiac development and modulation of vascular and cardiac function. In the current work, we sought to examine the possible therapeutic potential of ELA peptide to reduce I/R injury following MI and elucidate the possible mechanisms by which ELA peptide may ameliorate injury and improve heart function after MI. 5 µg/kg of ELA peptide was administrated intraperitoneally in rats once per day for 4 days after ischemia of heart for 30 min. Male Wistar rats were sacrificed at 24 h and 2 weeks after reperfusion. The infarct size was determined by TTC staining 2 weeks after reperfusion. ELISA was employed to measure serum level of myocardial injury markers such as LDH, CK-MB and Troponin I and oxidative stress markers such as membrane lipid peroxidation (MDA), GSH and SOD activities in the first 24 h. Cardiac function was evaluated using echocardiography prior to MI and 2 weeks after reperfusion. After administration of ELA peptide in MI rats, infarct size, serum levels of LDH, CK-MB, Troponin I and tissue levels of MDA were significantly reduced; GSH and SOD activities were markedly increased (p < 0.05). Likewise, ELA peptide improved cardiac function 2 weeks after MI (p < 0.05). ELA peptide administration for 4 days after MI could reduce injury by targeting oxidative stress and improvement of cardiac function. These findings establish a fundamental foundation for future peptide research and therapy. © 2018 Springer Science+Business Media, LLC, part of Springer Natur