An improved key-phase-free blade tip-timing technique for nonstationary test conditions and its application on large-scale centrifugal compressor blades

7partially_openopenHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, ZhixiongHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, Zhixion

The cadmium–mercaptoacetic acid complex contributes to the genotoxicity of mercaptoacetic acid-coated CdSe-core quantum dots

Quantum dots (QDs) have many potential clinical and biological applications because of their advantages over traditional fluorescent dyes. However, the genotoxicity potential of QDs still remains unclear. In this paper, a plasmid-based system was designed to explore the genotoxic mechanism of QDs by detecting changes in DNA configuration and biological activities. The direct chemicobiological interactions between DNA and mercaptoacetic acid-coated CdSecore QDs (MAA–QDs) were investigated. After incubation with different concentrations of MAA–QDs (0.043, 0.13, 0.4, 1.2, and 3.6 μmol/L) in the dark, the DNA conversion of the covalently closed circular (CCC) DNA to the open circular (OC) DNA was significantly enhanced (from 13.9% ± 2.2% to 59.9% ± 12.8%) while the residual transformation activity of plasmid DNA was greatly decreased (from 80.7% ± 12.8% to 13.6% ± 0.8%), which indicated that the damages to the DNA structure and biological activities induced by MAA–QDs were concentration-dependent. The electrospray ionization mass spectrometry data suggested that the observed genotoxicity might be correlated with the cadmium–mercaptoacetic acid complex (Cd–MAA) that is formed in the solution of MAA–QDs. Circular dichroism spectroscopy and transformation assay results indicated that the Cd–MAA complex might interact with DNA through the groove-binding mode and prefer binding to DNA fragments with high adenine and thymine content. Furthermore, the plasmid transformation assay could be used as an effective method to evaluate the genotoxicities of nanoparticles

SiO2 nanoparticles induce cytotoxicity and protein expression alteration in HaCaT cells

<p>Abstract</p> <p>Background</p> <p>Nanometer silicon dioxide (nano-SiO₂) has a wide variety of applications in material sciences, engineering and medicine; however, the potential cell biological and proteomic effects of nano-SiO₂exposure and the toxic mechanisms remain far from clear.</p> <p>Results</p> <p>Here, we evaluated the effects of amorphous nano-SiO₂(15-nm, 30-nm SiO₂). on cellular viability, cell cycle, apoptosis and protein expression in HaCaT cells by using biochemical and morphological analysis, two-dimensional differential gel electrophoresis (2D-DIGE) as well as mass spectrometry (MS). We found that the cellular viability of HaCaT cells was significantly decreased in a dose-dependent manner after the treatment of nano-SiO₂and micro-sized SiO₂particles. The IC₅₀value (50% concentration of inhibition) was associated with the size of SiO₂particles. Exposure to nano-SiO₂and micro-sized SiO₂particles also induced apoptosis in HaCaT cells in a dose-dependent manner. Furthermore, the smaller SiO₂particle size was, the higher apoptotic rate the cells underwent. The proteomic analysis revealed that 16 differentially expressed proteins were induced by SiO₂exposure, and that the expression levels of the differentially expressed proteins were associated with the particle size. The 16 proteins were identified by MALDI-TOF-TOF-MS analysis and could be classified into 5 categories according to their functions. They include oxidative stress-associated proteins; cytoskeleton-associated proteins; molecular chaperones; energy metabolism-associated proteins; apoptosis and tumor-associated proteins.</p> <p>Conclusions</p> <p>These results showed that nano-SiO₂exposure exerted toxic effects and altered protein expression in HaCaT cells. The data indicated the alterations of the proteins, such as the proteins associated with oxidative stress and apoptosis, could be involved in the toxic mechanisms of nano-SiO₂exposure.</p

Machine learning classification models for fetal skeletal development performance prediction using maternal bone metabolic proteins in goats

Background: In developing countries, maternal undernutrition is the major intrauterine environmental factor contributing to fetal development and adverse pregnancy outcomes. Maternal nutrition restriction (MNR) in gestation has proven to impact overall growth, bone development, and proliferation and metabolism of mesenchymal stem cells in offspring. However, the efficient method for elucidation of fetal bone development performance through maternal bone metabolic biochemical markers remains elusive. Methods: We adapted goats to elucidate fetal bone development state with maternal serum bone metabolic proteins under malnutrition conditions in mid- and late-gestation stages. We used the experimental data to create 72 datasets by mixing different input features such as one-hot encoding of experimental conditions, metabolic original data, experimental-centered features and experimental condition probabilities. Seven Machine Learning methods have been used to predict six fetal bone parameters (weight, length, and diameter of femur/humerus). Results: The results indicated that MNR influences fetal bone development (femur and humerus) and fetal bone metabolic protein levels (C-terminal telopeptides of collagen I, CTx, in middle-gestation and N-terminal telopeptides of collagen I, NTx, in late-gestation), and maternal bone metabolites (low bone alkaline phosphatase, BALP, in middle-gestation and high BALP in late-gestation). The results show the importance of experimental conditions (ECs) encoding by mixing the information with the serum metabolic data. The best classification models obtained for femur weight (Fw) and length (FI), and humerus weight (Hw) are Support Vector Machines classifiers with the leave-one-out cross-validation accuracy of 1. The rest of the accuracies are 0.98, 0.946 and 0.696 for the diameter of femur (Fd), diameter and length of humerus (Hd, Hl), respectively. With the feature importance analysis, the moving averages mixed ECs are generally more important for the majority of the models. The moving average of parathyroid hormone (PTH) within nutritional conditions (MA-PTH-experim) is important for Fd, Hd and Hl prediction models but its removal for enhancing the Fw, Fl and Hw model performance. Further, using one feature models, it is possible to obtain even more accurate models compared with the feature importance analysis models. In conclusion, the machine learning is an efficient method to confirm the important role of PTH and BALP mixed with nutritional conditions for fetal bone growth performance of goats. All the Python scripts including results and comments are available into an open repository at https://gitlab.com/muntisa/goat-bones-machine-learning

Regulation of non-classical immune parameters in immune thrombocytopenic purpura mice by a spleen-invigorating, qi-replenishing and blood-containing formula

AbstractObjectiveThis study investigated the regulatory effect of non-classical immune parameters on immune thrombocytopenic purpura (ITP) mice by a spleen-invigorating, qi-replenishing and blood-containing formula (SQBF).MethodA total of 80 BALB/c mice were randomly divided into four equal groups (20 mice each): control group, model group, prednisone group and spleen-invigorating, qi-replenishing and blood-containing (SQBF) group. Mice in the model group, prednisone group, and SQBF group were administered anti-platelet serum to induce ITP. The dynamic variations of platelet counts in ITP mice were measured with an automatic blood analyzer before modeling and 48 h, and 8, 12 and 15 days following APS injection. Levels of β-endorphin (β-EP), vasoactive intestinal peptide (VIP) and salivary IgA (SIgA) were detected by enzyme-linked immunosorbent assay (ELISA) on 15th day of experiment.ResultsSQBF enhanced peripheral blood platelet counts in ITP mice similar to that of prednisone, and both groups showed a statistically significant response compared with the model group (P < .01). The SQBF significantly decreased β-EP levels compared with the model and prednisone intervention groups (P < .05), significantly increased the levels of VIP and SIgA in ITP mice compared with the model group (P < .05) and had significant protective effects on the thymus of ITP mice compared with the model group (P < .01).ConclusionsThe SQBF had a similar effect to prednisone with regards to enhancing peripheral blood platelet counts in ITP mice. Furthermore, it decreased β-EP levels and increased VIP and SIgA, and protected the thymus. This shows that, on base of the brain-gut axis functions, some non-classical immune vascular active factors or neurotransmitters are also involved in immune responses, and also have relationship with the onset of ITP and bleeding and/or hemostasis. It needs further study to determine whether a change in these active factors is related to immediate hemostasis

Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory

[Abstract] The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R2 of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system.National Natural Science Foundation of China; 31320103917State of California; XDA05020700National Space Science Center (China); 2010T2S13National Space Science Center (China); 2012T1S0009Hunan Provincial People's Government (China); 2013TF3006Xunta de Galicia; GRC2014/04

The First Principle in Late Neoplatonism: A Study of the One's Causality in Proclus and Damascius

One of the main issues that dominates Neoplatonism in late antique philosophy of the 3rd–6th centuries A.D. is the nature of the first principle, called the ‘One’. From Plotinus onward, the principle is characterized as the cause of all things, since it produces the plurality of intelligible Forms, which in turn constitute the world’s rational and material structure. Given this, the tension that faces Neoplatonists is that the One, as the first cause, must transcend all things that are characterized by plurality—yet because it causes plurality, the One must anticipate plurality within itself. This becomes the main mo- tivation for this study’s focus on two late Neoplatonists, Proclus (5th cent. A.D.) and Damascius (late 5th–early 6th cent. A.D.): both attempt to address this tension in two rather different ways. Proclus’ attempted solution is to posit intermediate principles (the ‘henads’) that mirror the One’s nature, as ‘one’, but directly cause plurality. This makes the One only a cause of unity, while its production of plurality is mediated by the henads that it produces. Damascius, while appropriating Proclus’ framework, thinks that this is not enough: if the One is posed as a cause of all things, it must be directly related to plurality, even if its causality is mediated through the henads. Damascius then splits Proclus’ One into two entities: (1) the Ineffable as the first ‘principle’, which is absolutely transcendent and has no causal relation; and (2) the One as the first ‘cause’ of all things, which is only relatively transcendent under the Ineffable. Previous studies that compare Proclus and Damascius tend to focus either on the Ineffable or a skeptical shift in epistemology, but little work has been done on the causal framework which underlies both figures’ positions. Thus, this study proposes to focus on the causal frameworks behind each figure: why and how does Proclus propose to assert that the One is a cause, at the same time that it transcends its final effect? And what leads Damascius to propose a notion of the One’s causality that no longer makes it transcendent in the way that a higher principle, like the Ineffable, is? The present work will answer these questions in two parts. In the first, Proclus’ and Damascius’ notions of causality will be examined, insofar as they apply to all levels of being. In the second part, the One’s causality will be examined for both figures: for Proclus, the One’s causality in itself and the causality of its intermediate principles; for Damascius, the One’s causality, and how the Ineffable is needed to explain the One. The outcome of this study will show that Proclus’ framework results in an inner tension that Damascius is responding to with his notion of the One. While Damascius’ own solution implies its own tension, he at least solves a difficulty in Proclus—and in so doing, partially returns to a notion of the One much like Iamblichus’ and Plotinus’ One

Phase change material heat storage performance in the solar thermal storage structure employing experimental evaluation

One of the most investigated and broadly used mediums in the solar thermal storage systems is using phase change materials. In this research, a comprehensive performance test bench for solar thermal utilization system using a controllable heater to substitute different levels of solar input was established. The test bench is not limited by the weather and equipped with alternative heat storage tanks for different PCMs. The heat storage structure and the performance of paraffin in low temperature system was examined using numerical simulation method. The results showed that the heating power received by PCM was stable at 6–8 kW under the heating condition of 85 °C. At the stage of incompletely melting, the temperature difference between the inside and outside was as high as 31.6, which can reduce the loss of heat to a great extent