Numerical Simulation in Alternating Current Field Measurement (ACFM) Inducer Design

Inducer design plays an important part in Alternating Current Field Measurement (ACFM). It involves influence analysis of some key parameters on the perturbation of the magnetic field above the crack. Experimental analysis methods are time-consuming, high cost and have experimental errors. Finite element method (FEM) can overcome these shortcomings, and is adopted in this paper to aid design of ACFM inducer. Two kinds of ACFM Inducer, twin coil and U-shaped inducer are proposed, and corresponding numerical simulation models are built. In the model for the U-shaped inducer, the inducer comprises a U-shaped core and a current-carrying coil. The specimen is modeled by a plate, and the surface breaking crack in the specimen is modeled by a semi-ellipse [1], as shown in Figure 1. The models are then verified by comparison with experimental data. After that, influence of various parameters, such as core material, core dimensions and inducer lift-off on the perturbed magnetic field above the crack is analyzed in the models and suggested parameters are given based on the influence analysis results. The numerical simulation results provide guidance to design of ACFM inducer

Resveratrol attenuates chronic pulmonary embolism-related endothelial cell injury by modulating oxidative stress, inflammation, and autophagy

Objectives: Due to Pulmonary Artery Endothelial Cell (PAEC) dysfunction, Pulmonary Hypertension (PH) persists even after the Pulmonary Embolism (PE) has been relieved. However, the mechanism behind this remains unclear. Method: Here, the authors incubated Human PAECs (HPAECs) with thrombin to simulate the process of arterial thrombosis. Results: CCK8 results showed a decrease in the viability of HPAECs after thrombin incubation. In addition, the expression of Tissue Factor (TF), Monocyte Chemoattractant Protein 1 (MCP-1), VCAM-1, ICAM-1, cleaved caspase 3, cleaved caspase 9, and Bax protein were all increased after thrombin incubation, while Bcl-2 was decreased. The effects of 3-MA treatment further suggested that autophagy might mediate the partial protective effects of Resveratrol on HPAECs. To observe the effects of Resveratrol in vivo, the authors established a Chronic Thromboembolic Pulmonary Hypertension (CTEPH) model by repeatedly injecting autologous blood clots into a rat's left jugular vein. The results exhibited that Mean Pulmonary Arterial Pressure (mPAP) and vessel Wall Area/Total Area (WA/TA) ratio were both decreased after Resveratrol treatment. Moreover, Resveratrol could reduce the concentration and activity of TF, vWF, P-selectin, and promote these Superoxide Dismutase (SOD) in plasma. Western blot analysis of inflammation, platelet activation, autophagy, and apoptosis-associated proteins in pulmonary artery tissue validated the results in PHAECs. Conclusions: These findings suggested that reduced autophagy, increased oxidative stress, increased platelet activation, and increased inflammation were involved in CTEPH-induced HPAEC dysfunction and the development of PH, while Resveratrol could improve PAEC dysfunction and PH

A Novel SASH1-IQGAP1-E-Cadherin Signal Cascade Mediates Breast Cancer Metastasis

SAM and SH3 domain-containing protein 1 (SASH1) was previously described as a candidate tumor suppressor gene in breast cancer and colon cancer to mediate tumor metastasis and tumor growth. However, the underlying mechanism that SASH1 implements breast cancer metastasis in most solid cancers remains unexplored. In this study, SASH1 was identified to bind to IQ motif-containing GTPase activating protein 1 (IQGAP1). In breast cancer tissues, there was a correlation between the expressions of SASH1 and IQGAP1 (P  0.05). Therefore, it is suggested that SASH1 may form a new signaling cascade with IQGAP1 and E-cadherin to regulate breast cancer metastasis

A Novel P53/POMC/Gas/SASH1 Autoregulatory Feedback Loop and Pathologic Hyperpigmentation

P53-regulated proteins in transcriptional level are associated with many signal transduction pathways and p53 plays a pivotal role in a number of positive and negative autoregulatory feedback loops. Although POMC/α-MSH productions induced by ultraviolet (UV) are directly mediated by p53, p53 is related to UV-independent pathological pigmentation. In the process of identifying the causative gene of dyschromatosis universalis hereditaria (DUH), three mutations encoding amino acid substitutions were found in the gene SAM and SH3 domain containing 1 (SASH1). SASH1 was identified to interact with guanine nucleotide-binding protein subunit-alpha isoforms short (Gαs). However, for about 90 years, the pathological gene and the pathological mechanism of DUH are unclear. Our study indicates that SASH1 is physiologically medicated by p53 upon UV stimulation and a reciprocal SASH-p53 inducement is existed physiologically and pathophysiologically. A novel p53/POMC/α-MSH/Gαs/SASH1 signal cascade regulates SASH1 to foster melanogenesis. SASH1 mutations control a novel p53/POMC/Gαs/SASH1 autoregulatory positive feedback loop to promote pathological hyperpigmentation phenotype in DUH-affected individuals. Our work illustrates a novel p53/POMC/Gαs/SASH1 autoregulatory positive feedback loop that is mediated by SASH1 mutations to foster pathological hyperpigmentation phenotype

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

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

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

The sequencing and de novo assembly of the Larimichthys crocea genome using PacBio and Hi-C technologies.

Larimichthys crocea is an endemic marine fish in East Asia that belongs to Sciaenidae in Perciformes. L. crocea has now been recognized as an "iconic" marine fish species in China because not only is it a popular food fish in China, it is a representative victim of overfishing and still provides high value fish products supported by the modern large-scale mariculture industry. Here, we report a chromosome-level reference genome of L. crocea generated by employing the PacBio single molecule sequencing technique (SMRT) and high-throughput chromosome conformation capture (Hi-C) technologies. The genome sequences were assembled into 1,591 contigs with a total length of 723.86 Mb and a contig N50 length of 2.83 Mb. After chromosome-level scaffolding, 24 scaffolds were constructed with a total length of 668.67 Mb (92.48% of the total length). Genome annotation identified 23,657 protein-coding genes and 7262 ncRNAs. This highly accurate, chromosome-level reference genome of L. crocea provides an essential genome resource to support the development of genome-scale selective breeding and restocking strategies of L. crocea