Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

Behaviour of sand–clay mixtures for road pavement subgrade

Materials forming sand grains and colluvial soil deposits have a distinct structure, consisting of a composite matrix of coarse and fine soil grains. The influence of sand grains content on the behaviour of sand–clay mixtures was investigated by a series of intensive laboratory experiments. The California bearing ratio (CBR), unconfined compression strength (UCS) and compaction tests were carried out on various contents of sand and clay mixtures. The sand–clay mixtures were prepared with sand contents of 0, 10, 20, 30, 40, and 50% by weight. The laboratory tests on these mixtures have indicated that their behaviour will depend on the relative concentration of the sand and clay samples. The results of the tests showed a decrease in the UCS, and an increase the CBR values with an increase in the amount of sand. An increase in dry unit weight and a decrease in respective moisture content by an increase in the amount of sand were observed in the compaction tests.     

Genetic programming-based attenuation relationship: An application of recent earthquakes in turkey

This study investigates an application of genetic programming (GP) for the prediction of peak ground acceleration (PGA) using strong-ground-motion data from Turkey. The input variables in the developed GP model are the average shear-wave velocity, earthquake source to site distance and earthquake magnitude, and the output is the PGA values. The proposed GP model is based on the most reliable database compiled for earthquakes in Turkey. The results show that the consistency between the observed PGA values and the predicted ones by the GP model yields relatively high correlation coefficients (R²=0.75). The proposed model is also compared with an existing attenuation relationship and found to be more accurate.     

Generalized Regression Neural Networks and Feed Forward Neural Networks for prediction of scour depth around bridge piers

In this study, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN) approaches are used to predict the scour depth around circular bridge piers. Hundred and sixty five data collected from various experimental studies, are used to predict equilibrium scour depth. The model consisting of the combination of dimensional data involving the input variables is constructed. The performance of the models in training and testing sets are compared with observations. Then, the model is also tested by Multiple Linear Regression (MLR) and empirical formula. The results of all approaches are compared in order to get more reliable comparison. The results indicated that GRNN can be applied successfully for prediction of scour depth around circular bridge piers.     

Transferrin-Decorated Niosomes with Integrated InP/ZnS Quantum Dots and Magnetic Iron Oxide Nanoparticles: Dual Targeting and Imaging of Glioma

The development of multifunctional nanoscale systems that can mediate efficient tumor targeting, together with high cellular internalization, is crucial for the diagnosis of glioma. The combination of imaging agents into one platform provides dual imaging and allows further surface modification with targeting ligands for specific glioma detection. Herein, transferrin (Tf)-decorated niosomes with integrated magnetic iron oxide nanoparticles (MIONs) and quantum dots (QDs) were formulated (PEGNIO/QDs/MIONs/Tf) for efficient imaging of glioma, supported by magnetic and active targeting. Transmission electron microscopy confirmed the complete co-encapsulation of MIONs and QDs in the niosomes. Flow cytometry analysis demonstrated enhanced cellular uptake of the niosomal formulation by glioma cells. In vitro imaging studies showed that PEGNIO/QDs/MIONs/Tf produces an obvious negative-contrast enhancement effect on glioma cells by magnetic resonance imaging (MRI) and also improved fluorescence intensity under fluorescence microscopy. This novel platform represents the first niosome-based system which combines magnetic nanoparticles and QDs, and has application potential in dual-targeted imaging of glioma.     

Investigation of drag reduction performance of half NACA 0009 and 0012 airfoils placed over a trailer on the flow around truck-trailer

Journal of Mechanical Science and Technology - The drag reduction performance of a half airfoil attached to a trailer and the roof fairing at different positions was experimentally investigated in...     

Quality assessment of surface and groundwater in Solaklı Basin (Trabzon, Turkey)

The paper reports a study of the surface and ground water in Solakl? Basin, Trabzon, from an assessment of 33 sampling points. Many of the parameters analysed are only marginally acceptable as potable water, even though the samples were collected during the wet season. The highest concentrations of contaminants were found downstream of the centres of population. The results indicate regular monitoring is required and some measures should be taken to protect the limited resources.     

Application of an adaptive neuro-fuzzy inference system for classification of Behcet disease using the fast Fourier transform method

Abstract: In this study, ophthalmic arterial Doppler signals were obtained from 200 subjects, 100 of whom suffered from ocular Behcet disease while the rest were healthy subjects. An adaptive neuro-fuzzy inference system (ANFIS) was used to detect the presence of ocular Behcet disease. Spectral analysis of the ophthalmic arterial Doppler signals was performed by the fast Fourier transform method for determining the ANFIS inputs. The ANFIS was trained with a training set and tested with a testing set. All these data sets were obtained from ophthalmic arteries of healthy subjects and subjects suffering from ocular Behcet disease. Performance indicators and statistical measures were used for evaluating the ANFIS. The correct classification rate was 94% for healthy subjects and 90% for unhealthy subjects suffering from ocular Behcet disease. The classification results showed that the ANFIS was effective at detecting ophthalmic arterial Doppler signals from subjects with Behcet disease.     

Chemical changes of three native Turkish hazelnut varieties (Corylus avellana L.) during fruit development

Three native hazelnut varieties from Turkey, namely, Tombul, Palaz, and Badem, were examined for their proximate composition, minerals, and fatty acid profiles, as well as polyphenol oxidase (PPO), peroxidase (POD), and lipase activities during fruit development stages (early stage: ES, middle stage: MS, and harvest stage: HS). Proximate composition varied considerably (dry weight basis) from ES to MS. Fat was the predominant component at all stages and showed increasing trends. Six essential minerals (calcium, iron, magnesium, phosphorus, potassium, and zinc) were analysed (dry weight basis). Consuming recommended daily amount of 42.5 g hazelnut at HS supplies 23.3–25.0% of phosphorus, 11.6–18.1% of magnesium, 7.0–18.9% of iron, 4.9–8.9% of zinc, 5.1–5.7% of calcium, and 5.1–5.3% of potassium for recommended dietary allowances or adequate intake for adults. Significant (P < 0.05) decreasing trends were found in all mineral contents from early development to maturity, with some exceptions. Sixteen fatty acids were identified, among which 18:1ω9 was by far the most predominant one, followed by 18:2ω6, 16:0, and 18:0. As expected, total monounsaturated fatty acids constituted the main group of fatty acids ranging from 75.51 to 81.07% in Tombul, from 78.21 to 82.71% in Palaz, and from 73.69 to 81.65% in Badem through the maturation stages. In contrast, total polyunsaturated fatty acids showed decreasing trends from ES to HS. No significant changes (P > 0.05) were observed in total saturated fatty acids at different maturation stages. Tombul variety had the lowest PPO activity compared to those of Palaz and Badem. Badem showed highest POD activity compared to Tombul and Palaz at three stages of maturation and significant decreases (P < 0.05) in all hazelnut samples were observed in POD activity from ES to HS. No lipase activity was detected in any hazelnut samples at ES and MS, except in Badem at MS. In contrast, lipase activity was detected in all hazelnut samples at HS. These results suggest that some proximate compositions, minerals, and fatty acids gave good indications during fruit development stages, whereas enzymatic activities of PPO, POD, and lipase behaved differently among varieties and fruit development stages.