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In this paper, the problem of the uniform stability for a class of fuzzy fractional‐order genetic regulatory networks with random discrete delays, distributed delays, and parameter uncertainties is studied. Although there is a portion of literature on using fixed point theorems to study the stability of fractional neural networks, most of them required the fractional order to be in 12,1. However, the case of the fractional‐order belonging to (0,12) has not been discussed. To solve it, this work proposes a novel idea of using fixed point theory to study the stability of fuzzy (0,1) order neural networks, the problem of the uniqueness of the solution of the considered genetic regulatory networks is resolved, and a novel sufficient condition to guarantee the uniform stability of above genetic regulatory networks is also derived. Eventually, an example is given to demonstrate that the obtained result is effective. [ABSTRACT FROM AUTHOR]

Background Immunoglobulin A nephropathy (IgAN) is characterized by predominant IgA deposition in the glomerular mesangium. Previous studies have proved that renal-deposited IgA in IgAN came from circulating IgA1-containing complexes (CICs). Methods To explore the composition of CICs in IgAN, we isolated CICs from IgAN patients and healthy controls and then quantitatively analyzed them by mass spectrometry. Meanwhile, the isolated CICs were used to treat human mesangial cells to monitor mesangial cell injury. Using the protein content and injury effects, the key constituent in CICs was identified. Then the circulating levels of identified key constituent–IgA complex were detected in an independent population by an in-house-developed enzyme-linked immunosorbent assay. Results By comparing the proteins of CICs between IgAN patients and controls, we found that 14 proteins showed significantly different levels. Among them, α1-microglobulin content in CICs was associated with not only in vitro mesangial cell proliferation and monocyte chemoattractant protein 1 secretion, but also in vivo estimated glomerular filtration rate (eGFR) levels and tubulointerstitial lesions in IgAN patients. Moreover, we found α1-microglobulin was prone to bind aberrant glycosylated IgA1. Additionally, elevated circulating IgA-α1-microglobulin complex levels were detected in an independent IgAN population and IgA-α1-microglobulin complex levels were correlated with hypertension, eGFR levels and Oxford T- scores in these IgAN patients. Conclusions Our results suggest that the IgA-α1-microglobulin complex is an important constituent in CICs and that circulating IgA-α1-microglobulin complex detection might serve as a potential noninvasive biomarker detection method for IgAN. [ABSTRACT FROM AUTHOR]

The accurate model of the load state for all balls under multidirectional load is very helpful for the design process of ball screws. The contact deformation model of the ball screw without consideration of the stress difference of all balls is inaccurate. In this paper, a novel contact load model of the ball screw is established by considering coupled axial, radial load to study the elastic deformation displacement and position accuracy. The deviation and variation of axial elastic deformation with the dimension errors of all balls are investigated to obtain the influence of load state on the precision sustainability of the ball screw. The position precision including travel deviation and variation by considering load distribution of all balls is studied under the different load conditions. In addition, a new working bench is designed to study the position precision of the ball screw. The experimental study is carried out to obtain the relationship between the position precision and the contact load state of all balls, which is a reference to compensate for the precision loss of the ball screw. [ABSTRACT FROM AUTHOR]

Abstract Background Hepatitis B virus (HBV) is a major cause of liver infection in human. Because of the lack of an appropriate cell culture system for supporting HBV infection efficiently, the cellular and molecular mechanisms of hepadnavirus infection remain incompletely understood. Duck heptatitis B virus (DHBV) can naturally infect primary duck hepatocytes (PDHs) that provide valuable model systems for studying hepadnavirus infection in vitro. In this report, we explored global changes in cellular protein expression in DHBV infected PDHs by two-dimension gel electrophoresis (2-DE) combined with MALDI-TOF/TOF tandem mass spectrometry (MS/MS). Results The effects of hepadnavirus infection on hepatocytes were investigated in DHBV infected PDHs by the 2-DE analysis. Proteomic profile of PDHs infected with DHBV were analyzed at 24, 72 and 120 h post-infection by comparing with uninfected PDHs, and 75 differentially expressed protein spots were revealed by 2-DE analysis. Among the selected protein spots, 51 spots were identified corresponding to 42 proteins by MS/MS analysis; most of them were matched to orthologous proteins of Gallus gallus, Anas platyrhynchos or other avian species, including alpha-enolase, lamin A, aconitase 2, cofilin-2 and annexin A2, etc. The down-regulated expression of beta-actin and annexin A2 was confirmed by Western blot analysis, and potential roles of some differentially expressed proteins in the virus-infected cells have been discussed. Conclusions Differentially expressed proteins of DHBV infected PDHs revealed by 2-DE, are involved in carbohydrate metabolism, amino acid metabolism, stress responses and cytoskeleton processes etc, providing the insight to understanding of interactions between hepadnavirus and hepatocytes and molecular mechanisms of hepadnavirus pathogenesis.

In this work, Ti3C2 MXene, a novel two-dimensional nanosheet, was introduced to waterborne polyurethane (WPU) coatings to prepare a composite coating. First, MAX phase materials were in situ etched by HF acid and further intercalated by water molecules to obtain exfoliated single-layer MXene nanosheet. And then, composite coatings were prepared via solution-blending low addition (0–0.4 wt%) of MXene, self-prepared waterborne polyacrylate emulsion (PAE) and isocyanate hardener, applying on Q235 mild steel. Results of AFM, XRD SEM and SEM–EDS confirm that single-layer MXene nanosheets with large lateral-to-thickness ratio are successfully prepared and achieved homogenous distribution within WPU matrix. With 0.4 wt% MXene incorporated, the WPU/Ti3C2 MXene composite coatings reach a lowest corrosion current of 2.143 × 10–6 A/cm2, a decrease of one order of magnitude compared with blank WPU (1.599 × 10–5 A/cm2) and own an excellent UV-blocking property (almost block the whole UV light). [ABSTRACT FROM AUTHOR]

Purpose: Current approaches to quantification of magnetic particle imaging (MPI) for cell-based therapy are thwarted by the lack of reliable, standardized methods of segmenting the signal from background in images. This calls for the development of artificial intelligence (AI) systems for MPI analysis.Procedures: We utilize a canonical algorithm in the domain of unsupervised machine learning, known as K-means++, to segment the regions of interest (ROI) of images and perform iron quantification analysis using a standard curve model. We generated in vitro, in vivo, and ex vivo data using islets and mouse models and applied the AI algorithm to gain insight into segmentation and iron prediction on these MPI data. In vitro models included imaging the VivoTrax-labeled islets in varying numbers. In vivo mouse models were generated through transplantation of increasing numbers of the labeled islets under the kidney capsule of mice. Ex vivo data were obtained from the MPI images of excised kidney grafts.Results: The K-means++ algorithms segmented the ROI of in vitro phantoms with minimal noise. A linear correlation between the islet numbers and the increasing prediction of total iron value (TIV) in the islets was observed. Segmentation results of the ROI of the in vivo MPI scans showed that with increasing number of transplanted islets, the signal intensity increased with linear trend. Upon segmenting the ROI of ex vivo data, a linear trend was observed in which increasing intensity of the ROI yielded increasing TIV of the islets. Through statistical evaluation of the algorithm performance via intraclass correlation coefficient validation, we observed excellent performance of K-means++-based model on segmentation and quantification analysis of MPI data.Conclusions: We have demonstrated the ability of the K-means++-based model to provide a standardized method of segmentation and quantification of MPI scans in an islet transplantation mouse model. [ABSTRACT FROM AUTHOR]