Semaphorin 7A as a potential immune regulator and promising therapeutic target in rheumatoid arthritis

Abstract Background Semaphorin 7A (Sema7A) is expressed by several different classes of lymphoid and myeloid cells and is a potent immunomodulator. We examined the role of Sema7A in modulating cellular immune responses and to provide experimental data validating the therapeutic potential of Sema7A in rheumatoid arthritis (RA). Methods Soluble Sema7A (sSema7A) levels in the serum and synovial fluid from patients with RA or osteoarthritis, as well as cytokine secretions, were analyzed with an enzyme-linked immunosorbent assay. The cell surface levels and transcripts of Sema7A were evaluated in T cells and monocytes from patients with RA. The effect of Sema7A on the functions of primary T cells isolated from the peripheral blood of healthy donors was observed. Detection of the activation of the signal mediator focal adhesion kinase was performed by Western blotting. Shedding of sSema7A was evaluated in monocytes. The introduction of anti-Sema7A antibody to mice with collagen-induced arthritis (CIA) was observed in vivo. Results Upregulation of sSema7A levels in both the serum and synovial fluid of patients with RA was correlated with disease activity markers. sSema7A markedly increased Th1/Th17 cytokine secretion and induced evident upregulation of T-bet and retinoic acid receptor-related orphan nuclear receptor \u3b3t levels in T cells. Cell surface Sema7A was cleaved by a disintegrin and metalloprotease 17 (ADAM17) in monocytes. Interleukin-6 and tumor necrosis factor-\u3b1 stimulated ADAM17 secretion in synovial macrophages. Blocking of \u3b21-integrin abrogated the Sema7A-mediated cytokine secretion. Treatment with an anti-Sema7A antibody significantly attenuated CIA. Conclusions These findings indicate that Sema7A as a potent activator of T cells and monocytes in the immune response contributes to the inflammation and progression of RA, suggesting its therapeutic potential in the treatment of RA

Bearing fault diagnosis and degradation analysis based on improved empirical mode decomposition and maximum correlated kurtosis deconvolution

Detecting periodic impulse signal (PIS) is the core of bearing fault diagnosis. Earlier fault detected, earlier maintenance actions can be implemented. On the other hand, remaining useful life (RUL) prediction provides important information when the maintenance should be conducted. However, good degradation features are the prerequisite for effective RUL prediction. Therefore, this paper mainly concerns earlier fault detection and degradation feature extraction for bearing. Maximum correlated kurtosis deconvolution (MCKD) can enhance PIS produced by bearing fault. Whereas, it only achieve good effect when bearing has severe fault. On the contrary, PIS produced by bearing weak fault is always masked by heavy noise and cannot be enhanced by MCKD. In order to resolve this problem, a revised empirical mode decomposition (EMD) algorithm is used to denoise bearing fault signal before MCKD processing. In revised EMD algorithm, a new recovering algorithm is used to resolve mode mixing problem existed in traditional EMD and it is superior to ensemble EMD. For degradation analysis, correlated kurtosis (CK) value is used as degradation indicator to reflect health condition of bearing. Except of theory analysis, simulated bearing fault data, injected bearing fault data, real bearing fault data and bearing degradation data are used to verify the proposed method. Simulated bearing fault data is used to explain the existed problems. Then, injected bearing fault data and real bearing fault data are used to demonstrate the effectiveness of proposed method for fault diagnosis. Finally, bearing degradation data is used to verify the degradation feature CK extracted based on proposed method. All these case studies show the effectiveness of proposed fault diagnosis and degradation tracking method

Quantitative real time PCR assay for detecting BK virus in serum, plasma and urine.

PosterBK is a non-enveloped virus in the Polyomavirus family, closely related to SV40 and JC virus. Primary infection with BK generally occurs during childhood without specific symptoms, and is widespread in the population, with approximately 80% of adults infected globally. The virus remains latent in the urogenital tract, but can become transplant patients,reactivated. Asymptomatic reactivation and sporadic shedding of BK virus in urine can happen spontaneously in immunocompetant patients

Fast Specimen Boundary Tracking and Local Imaging with Scanning Probe Microscopy

An efficient and adaptive boundary tracking method is developed to confine area of interest for high-efficiency local scanning. By using a boundary point determination criterion, the scanning tip is steered with a sinusoidal waveform while estimating azimuth angle and radius ratio of each boundary point to accurately track the boundary of targets. A local scan region and path are subsequently planned based on the prior knowledge of boundary tracking to reduce the scan time. Boundary tracking and local scanning methods have great potential not only for fast dimension measurement but also for sample surface topography and physical characterization, with only scanning region of interest. The performance of the proposed methods was verified by using the alternate current mode scanning ion-conductance microscopy, tapping, and PeakForce modulation atomic force microscopy. Experimental results of single/multitarget boundary tracking and local scanning of target structures with complex boundaries demonstrate the flexibility and validity of the proposed method

Evapotranspiration and its components over a rainfed spring maize cropland under plastic film on the Loess Plateau, China

Aim of study: To determine seasonal variations in evapotranspiration (ET) and its components; and ascertain the key factors controlling ET and its components in a rainfed spring maize field under plastic film.Area of study: Shouyang County in Shanxi Province on the eastern Loess Plateau, ChinaMaterial and methods: Eddy covariance system combined with micro-lysimeters and meteorological observing instruments were used in the field. The manual method was used to measure the green leaf area index (GLAI) during the growing season.Main results: In 2015 and 2016, the growing season ET accounted for 80% and 79% of annual ET, respectively. Soil evaporation (E) accounted for 36% and 33% of the growing season ET in 2015 and 2016, respectively. The daily crop coefficient increased with increasing GLAI until a threshold of ~3 m2 m−2 in the canopy-increasing stage, and decreased linearly with decreasing GLAI in the canopy-decreasing stage. At equivalent GLAI, daily basal crop coefficient and soil water evaporation coefficient were generally higher in the canopy-increasing and -decreasing stages, respectively. During the growing season, the most important factor controlling daily ET, T, and E was net radiation (Rn), followed by GLAI for daily ET and T, and soil water content at 10-cm depth for daily E; during the non-growing season, daily ET was mainly controlled by Rn.Research highlights: The daily crop coefficient and its components reacted differently to GLAI in the canopy-increasing and -decreasing stages

Van der Waals coefficients beyond the classical shell model

Van der Waals (vdW) coefficients can be accurately generated and understood by modelling the dynamic multipole polarizability of each interacting object. Accurate static polarizabilities are the key to accurate dynamic polarizabilities and vdW coefficients. In this work, we present and study in detail a hollow-sphere model for the dynamic multipole polarizability proposed recently by two of the present authors (JT and JPP) to simulate the vdW coefficients for inhomogeneous systems that allow for a cavity. The inputs to this model are the accurate static multipole polarizabilities and the electron density. A simplification of the full hollow-sphere model, the single-frequency approximation (SFA), circumvents the need for a detailed electron density and for a double numerical integration over space. We find that the hollow-sphere model in SFA is not only accurate for nanoclusters and cage molecules (e.g., fullerenes) but also yields vdW coefficients among atoms, fullerenes, and small clusters in good agreement with expensive time-dependent density functional calculations. However, the classical shell model (CSM), which inputs the static dipole polarizabilities and estimates the static higher-order multipole polarizabilities therefrom, is accurate for the higher-order vdW coefficients only when the interacting objects are large. For the lowest-order vdW coefficient C6, SFA and CSM are exactly the same. The higher-order (C8 and C10) terms of the vdW expansion can be almost as important as the C6 term in molecular crystals. Application to a variety of clusters shows that there is strong non-additivity of the long-range vdW interactions between nanoclusters

Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data

Time-Series Forecasting based on Cumulative Data (TSFCD) is a crucial problem in decision-making across various industrial scenarios. However, existing time-series forecasting methods often overlook two important characteristics of cumulative data, namely monotonicity and irregularity, which limit their practical applicability. To address this limitation, we propose a principled approach called Monotonic neural Ordinary Differential Equation (MODE) within the framework of neural ordinary differential equations. By leveraging MODE, we are able to effectively capture and represent the monotonicity and irregularity in practical cumulative data. Through extensive experiments conducted in a bonus allocation scenario, we demonstrate that MODE outperforms state-of-the-art methods, showcasing its ability to handle both monotonicity and irregularity in cumulative data and delivering superior forecasting performance.Comment: Accepted as CIKM'23 Applied Research Trac