A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

BACKGROUND: The rapid advance in large-scale SNP-chip technologies offers us great opportunities in elucidating the genetic basis of complex diseases. Methods for large-scale interactions analysis have been under development from several sources. Due to several difficult issues (e.g., sparseness of data in high dimensions and low replication or validation rate), development of fast, powerful and robust methods for detecting various forms of gene-gene interactions continues to be a challenging task. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we have developed an evolution-based method to search for genome-wide epistasis in a case-control design. From an evolutionary perspective, we view that human diseases originate from ancient mutations and consider that the underlying genetic variants play a role in differentiating human population into the healthy and the diseased. Based on this concept, traditional evolutionary measure, fixation index (Fst) for two unlinked loci, which measures the genetic distance between populations, should be able to reveal the responsible genetic interplays for disease traits. To validate our proposal, we first investigated the theoretical distribution of Fst by using extensive simulations. Then, we explored its power for detecting gene-gene interactions via SNP markers, and compared it with the conventional Pearson Chi-square test, mutual information based test and linkage disequilibrium based test under several disease models. The proposed evolution-based method outperformed these compared methods in dominant and additive models, no matter what the disease allele frequencies were. However, its performance was relatively poor in a recessive model. Finally, we applied the proposed evolution-based method to analysis of a published dataset. Our results showed that the P value of the Fst -based statistic is smaller than those obtained by the LD-based statistic or Poisson regression models. CONCLUSIONS/SIGNIFICANCE: With rapidly growing large-scale genetic association studies, the proposed evolution-based method can be a promising tool in the identification of epistatic effects

In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlying complex physical events such as crack propagation and pores formation. However, due to the noisy environment and intricate signal content, acoustic-based monitoring in LDED has received little attention. This paper proposes a novel acoustic-based in-situ defect detection strategy in LDED. The key contribution of this study is to develop an in-situ acoustic signal denoising, feature extraction, and sound classification pipeline that incorporates convolutional neural networks (CNN) for online defect prediction. Microscope images are used to identify locations of the cracks and keyhole pores within a part. The defect locations are spatiotemporally registered with acoustic signal. Various acoustic features corresponding to defect-free regions, cracks, and keyhole pores are extracted and analysed in time-domain, frequency-domain, and time-frequency representations. The CNN model is trained to predict defect occurrences using the Mel-Frequency Cepstral Coefficients (MFCCs) of the lasermaterial interaction sound. The CNN model is compared to various classic machine learning models trained on the denoised acoustic dataset and raw acoustic dataset. The validation results shows that the CNN model trained on the denoised dataset outperforms others with the highest overall accuracy (89%), keyhole pore prediction accuracy (93%), and AUC-ROC score (98%). Furthermore, the trained CNN model can be deployed into an in-house developed software platform for online quality monitoring. The proposed strategy is the first study to use acoustic signals with deep learning for insitu defect detection in LDED process.Comment: 36 Pages, 16 Figures, accepted at journal Additive Manufacturin

Naringenin suppresses BEAS-2B-derived extracellular vesicular cargoes disorder caused by cigarette smoke extract thereby inhibiting M1 macrophage polarization

Extracellular vesicles (EVs)-mediated epithelium-macrophage crosstalk has been proved to maintain lung homeostasis in cigarette smoke-induced lung diseases such as chronic obstructive pulmonary disease (COPD). In our previous study, we found that EVs derived from cigarette smoke extract (CSE) treated BEAS-2B promoted M1 macrophage polarization, which probably accelerated the development of inflammatory responses. Naringenin has been proved to suppress M1 macrophage polarization, but whether naringenin regulates macrophage polarization mediated by EVs has not been reported. In this study, we firstly found that EVs derived from naringenin and CSE co-treated BEAS-2B significantly inhibited the expression of CD86 and CD80 and the secretion of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1β, inducible nitric oxide synthase (iNOS), and IL-12 in macrophage induced by EVs derived from CSE-treated BEAS-2B. Further research revealed that naringenin downregulated BEAS-2B-derived EVs miR-21-3p which targeted phosphatase and tensin homolog deleted on chromosome ten/protein kinase B (PTEN/AKT) cascade in macrophages and then suppressed M1 macrophage polarization. Subsequent proteomics suggested that naringenin decreased BEAS-2B-derived EVs poly ADP-ribose polymerase (PARP)1 expression thereby suppressing M1 macrophage polarization probably. Our study provides novel pharmacological references for the mechanism of naringenin in the treatment of cigarette smoke-induced lung inflammatory diseases

Boosting the performance of single-atom catalysts via external electric field polarization

Single-atom catalysts represent a unique catalytic system with high atomic utilization and tunable reaction pathway. Despite current successes in their optimization and tailoring through structural and synthetic innovations, there is a lack of dynamic modulation approach for the single-atom catalysis. Inspired by the electrostatic interaction within specific natural enzymes, here we show the performance of model single-atom catalysts anchored on two-dimensional atomic crystals can be systematically and efficiently tuned by oriented external electric fields. Superior electrocatalytic performance have been achieved in single-atom catalysts under electrostatic modulations. Theoretical investigations suggest a universal “onsite electrostatic polarization” mechanism, in which electrostatic fields significantly polarize charge distributions at the single-atom sites and alter the kinetics of the rate determining steps, leading to boosted reaction performances. Such field-induced on-site polarization offers a unique strategy for simulating the catalytic processes in natural enzyme systems with quantitative, precise and dynamic external electric fields

Characterization, in Vitro and in Vivo Evaluation of Naringenin-Hydroxypropyl-β-Cyclodextrin Inclusion for Pulmonary Delivery

Naringenin, a flavonoid compound which exists abundantly in Citrus fruits, is proven to possess excellent antitussive and expectorant effects. However, the clinical applications of naringenin are restricted by its poor solubility and low local concentration by oral administration. The aim of the present study is to prepare a naringenin-hydroxypropyl-β-cyclodextrin (naringenin-HPβCD) inclusion as an inhalation solution for pulmonary delivery. The naringenin-HPβCD inclusion was characterized by phase solubility study, XRD, differential scanning calorimetry (DSC), proton nuclear magnetic resonance (1HNMR), and two-dimensional rotating frame Overhauser effect spectroscopy (2D ROESY). The in vitro permeability of the inclusion was evaluated on Calu-3 cells and the pharmacokinetic profile of pulmonary delivery was investigated in Sprague-Dawley (SD) rats. Based on the linear model of phase solubility study, the relationship between naringenin and HPβCD was identified as AL type with a 1:1 stoichiometry. XRD, DSC, and NMR studies indicated that the entire naringenin molecule is encapsulated into the cavity of HPβCD. HPβCD could increase the concentration of naringenin in the epithelium-lining fluid (ELF) of Calu-3 cells and act as a sustained release system for naringenin. The pharmacokinetic profile of naringenin-HPβCD inclusion showed rapid response and higher local concentration by pulmonary delivery. In conclusion, pulmonary delivery of naringenin-HPβCD inclusion is a promising formulation strategy, which could provide a new possibility for the clinical application of naringenin

A Comparative Study of Intensive Litopenaeus vannamei Culture on Four Bottom Substrates Without Water Change

National Science and Technology Supporting Program of the Twelfth Five-Year Plan of China [2011BAD13B10]; Special Fund for Agro-scientific Research in the Public Interest, China [201103034]The effect of four bottom substrates, oyster shell powder (OP), sugarcane bagasse (SB), a mixture of OP and SB (OS) and fresh soil (FS), on the water quality and bacterial and zooplankton density of intensive shrimp (Litopenaeus vannamei) culture tanks without water change and the growth performance of cultured shrimp were compared in this study. At the end of a 110 days culturing trial, the total ammonium-N (TAN) of the water on SB and the nitrite nitrogen (NO2-N) on OS was significantly lower than that on the other substrates (P<0.05), which coincided with the high density of ammonium-and nitrite-oxidizing bacteria in the water on SB and OS, respectively. The concentration of chlorophyll a (Chl a) increased slowly on OP, SB and OS but remained low on FS. The density of total bacteria on OP, SB and OS was one order of magnitude higher than that on FS, and the density of zooplankton on SB and OS was significantly higher than that on FS or OP (P<0.05). The improved water quality and increased density of bacteria and zooplankton on SB and OS may have had a synergistic effect on shrimp culture, improving its growth performance (high survival rate and yield and low feed conversion rate). SB and OS were more effective for improving the growth performance of intensively cultured L. vannamei without water change than OP and FS. To our knowledge, this study presents the first evidence regarding the effect of different bottom substrates on intensive shrimp culture

Error per single-qubit gate below 10−4 in a superconducting qubit

Abstract Implementing arbitrary single-qubit gates with near perfect fidelity is among the most fundamental requirements in gate-based quantum information processing. In this work, we fabricate a transmon qubit with long coherence times and demonstrate single-qubit gates with the average gate error below 10−4, i.e. (7.42 ± 0.04) × 10−5 by randomized benchmarking (RB). To understand the error sources, we experimentally obtain an error budget, consisting of the decoherence errors lower bounded by (4.62 ± 0.04) × 10−5 and the leakage rate per gate of (1.16 ± 0.04) × 10−5. Moreover, we reconstruct the process matrices for the single-qubit gates by the gate set tomography (GST), with which we simulate RB sequences and obtain single-qubit fidelities consistent with experimental results. We also observe non-Markovian behavior in the experiment of long-sequence GST, which may provide guidance for further calibration. The demonstration extends the upper limit that the average fidelity of single-qubit gates can reach in a transmon-qubit system, and thus can be an essential step towards practical and reliable quantum computation in the near future