Multinomial logit model(MLM) has been proposed as the most frequently regression model for multi-category response. To deal with correlated data, in this paper we propose G-LASSO/G-SCAD/G-MCP ...penalized MLM to exert class discovery and class prediction for high-dimensional multi-category classification problems. Firstly, we develop a group coordinate descent(GCD) algorithm to simultaneously complete group selection and group estimation, and prove the convergence to the proposed GCD algorithm under mild conditions. Secondly, we apply the training set and group estimations to obtain class probability estimators, choose the Bayes classifier to identify class index information, and introduce the testing set and a few measures to assess multi-category prediction performance. Simulations show that the proposed methods outperform LASSO/SCAD/MCP penalized MLM, 3 deep learning methods and 3 machine learning methods in terms of Kappa, PDI(polytomous discrimination index), Optimal or Average Accuracy. Finally, we combine group penalized MLM with 58 technical indicators to predict up trends, sideways trends and down trends for stock returns, and show that the proposed methods outperform the other 9 methods in terms of Accuracy, PDI, Kappa and HUM. Therefore, the proposed method can not only accommodate the correlation information, but also improve multi-category prediction performance by shrinking group coefficients.
Circular RNAs (circRNAs) have critical roles in various types of diseases, including preeclampsia (PE). Circ_0005714 function in PE was explored in this study.
Reverse transcription-quantitative ...polymerase chain reaction (RT-qPCR) was performed for level analysis of circ_0005714, micoRNA-223-3p (miR-223-3p), and a disintegrin and metalloproteinase 9 (ADAM9). Cell Counting Kit-8 (CCK-8) and colony formation assays were used for cell viability and colony formation detection. Cell proliferation was determined by EdU assay. The determination of migration and invasion was conducted by wound healing assay and transwell assay. Tube formation assay was applied to assess angiopoiesis. Target binding analysis was performed by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. Western blot was used for protein examination.
Circ_0005714 was highly expressed in PE placenta tissues. The expression promotion of circ_0005714 reduced proliferation, migration, invasion, and angiopoiesis in trophoblast cells. Furthermore, circ_0005714 acted as a molecular sponge for miR-223-3p and the effects of circ_0005714 on trophoblast cells were achieved by sponging miR-223-3p. Moreover, miR-223-3p could target ADAM9 and knockdown of ADAM9 reversed cell progression inhibition induced by miR-223-3p inhibitor. In addition, circ_0005714 upregulated the ADAM9 expression and inactivated the Wnt/β-catenin pathway through targeting miR-223-3p.
All results manifested that circ_0005714 retarded the progression of PE by mediating the miR-223-3p/ADAM9 signal network.
Myeloid-derived suppressor cells (MDSCs) play a key role in maintaining maternal-fetal tolerance for a successful pregnancy, but the role of MDSCs in abnormal pregnancy caused by Toxoplasma gondii ...infection is unknown. Herein, we revealed a distinct mechanism by which T-cell immunoglobulin domain and mucin domain containing protein-3 (Tim-3), an immune checkpoint receptor that balances maternal-fetal tolerance during pregnancy, contributes to the immunosuppressive function of MDSCs during T. gondii infection. The expression of Tim-3 in decidual MDSCs was significantly downregulated following T. gondii infection. The proportion of monocytic MDSCs population, the inhibitory effect of MDSCs on T-cell proliferation, the levels of STAT3 phosphorylation, and the expression of functional molecules (Arg-1 and IL-10) in MDSCs were all decreased in T. gondii-infected pregnant Tim-3 gene knockout (Tim-3KO) mice compared with infected pregnant WT mice. After treatment with Tim-3-neutralizing Ab in vitro, the expression levels of Arg-1, IL-10, C/EBPβ, and p-STAT3 were decreased, the interaction between Fyn and Tim-3 or between Fyn and STAT3 was weakened, and the binding ability of C/EBPβ to the promoters of ARG1 and IL10 was decreased in human decidual MDSCs with T. gondii infection, while opposite results were observed following treatment with galectin-9 (a ligand for Tim-3). Inhibitors of Fyn and STAT3 also downregulated the expression of Arg-1 and IL-10 in decidual MDSCs and exacerbated adverse pregnancy outcomes caused by T. gondii infection in mice. Therefore, our studies discovered that the decrease of Tim-3 after T. gondii infection could downregulate the functional molecules of Arg-1 and IL-10 expression in decidual MDSCs through the Fyn-STAT3-C/EBPβ signaling pathway and weaken their immunosuppressive function, which eventually contribute to the development of adverse pregnancy outcomes.
Convolutional Sparse Coding for RGB+NIR Imaging Xuemei Hu; Heide, Felix; Qionghai Dai ...
IEEE transactions on image processing,
2018-April, 2018-Apr, 2018-4-00, 20180401, Letnik:
27, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Emerging sensor designs increasingly rely on novel color filter arrays (CFAs) to sample the incident spectrum in unconventional ways. In particular, capturing a near-infrared (NIR) channel along with ...conventional RGB color is an exciting new imaging modality. RGB+NIR sensing has broad applications in computational photography, such as low-light denoising, it has applications in computer vision, such as facial recognition and tracking, and it paves the way toward low-cost single-sensor RGB and depth imaging using structured illumination. However, cost-effective commercial CFAs suffer from severe spectral cross talk. This cross talk represents a major challenge in high-quality RGB+NIR imaging, rendering existing spatially multiplexed sensor designs impractical. In this work, we introduce a new approach to RGB+NIR image reconstruction using learned convolutional sparse priors. We demonstrate high-quality color and NIR imaging for challenging scenes, even including high-frequency structured NIR illumination. The effectiveness of the proposed method is validated on a large data set of experimental captures, and simulated benchmark results which demonstrate that this work achieves unprecedented reconstruction quality.
Background
Gestational diabetes mellitus (GDM), characterized by glucose intolerance during pregnancy, poses substantial health risks for both mothers and infants due to the interplay of insulin ...resistance and β-cell dysfunction. Molecular biomarkers, including SNPs, microRNAs (miRNAs), and proteins, have been linked to GDM development during pregnancy. Notably, miRNA-mediated regulation of gene expression holds pivotal roles in metabolic disorders. This study aims to identify diagnostic biomarkers for GDM and establish a diagnostic model.
Methods
Firstly, gene expression data from GDM samples (N = 9) and normal samples (N = 9) were sourced from the Gene Expression Omnibus (GEO) database. Subsequently, the limma package was employed to discern differentially expressed genes (DEGs), with subsequent functional and enrichment analyses executed using the clusterProfiler package. A comprehensive exploration of genes significantly correlated with GDM was undertaken via weighted gene co-expression network analysis (WGCNA). The construction of a protein-protein interaction (PPI) network was facilitated by STRING, while visualization of hub genes was achieved through Cytoscape. Moreover, the miRNA-mRNA network was established using StarBase. Concurrently, immune infiltration significantly correlated with hub genes was identified.
Results
In this study, 209 DEGs between normal and GDM samples were identified, and these genes were associated with collagen containing extracellular matrix heparin binding and axon guidance, etc. Then, 18 modules were identified by WGCNA and the brown module including 212 genes had a significantly negative correlation with GDM (r = −0.66, P = 0.003). Additionally, five low gene expressions (CXCL12, MEF2C, MMP2, SOX17 and THBS2) and two high gene expressions (BMP4 and SFRP5) were identified as GDM related hub genes. Moreover, hub genes regulated by alternations of miRNAs were established and three hub genes (CXCL12, MEF2C and THBS2) were negatively correlated with activated Natural Killer (NK) cells while two hub genes (BMP4 and SFRP5) were positively correlated with activated NK cells.
Conclusions
This study offers novel hub genes that could contribute to the diagnostic approach for GDM, potentially shedding light on the intricate mechanisms underpinning GDM's developmental pathways.
We developed the indirect method for stochastic logistic growth models involving both birth and death rates in the drift and diffusion coefficients, and not only propose two indirect estimators, but ...also construct a likelihood ratio-type indirect statistic for testing hypotheses concerning parameters. Simulations show that the proposed two indirect estimators can correct the discretization bias, and the proposed indirect test possesses very good estimated power and size.
A unique bifocal compound eye visual system found in the now extinct trilobite, Dalmanitina socialis, may enable them to be sensitive to the light-field information and simultaneously perceive both ...close and distant objects in the environment. Here, inspired by the optical structure of their eyes, we demonstrate a nanophotonic light-field camera incorporating a spin-multiplexed bifocal metalens array capable of capturing high-resolution light-field images over a record depth-of-field ranging from centimeter to kilometer scale, simultaneously enabling macro and telephoto modes in a snapshot imaging. By leveraging a multi-scale convolutional neural network-based reconstruction algorithm, optical aberrations induced by the metalens are eliminated, thereby significantly relaxing the design and performance limitations on metasurface optics. The elegant integration of nanophotonic technology with computational photography achieved here is expected to aid development of future high-performance imaging systems.
Fibroblast growth factor 21 (FGF21) acts as an anti‐atherosclerotic agent. However, the specific mechanisms governing this regulatory activity are unclear. Autophagy is a highly conserved cell stress ...response which regulates atherosclerosis (AS) by reducing lipid droplet degradation in foam cells. We sought to assess whether FGF21 could inhibit AS by regulating cholesterol metabolism in foam cells via autophagy and to elucidate the underlying molecular mechanisms. In this study, ApoE−/− mice were fed a high‐fat diet (HFD) with or without FGF21 and FGF21 + 3‐Methyladenine (3MA) for 12 weeks. Our results showed that FGF21 inhibited AS in HFD‐fed ApoE−/− mice, which was reversed by 3MA treatment. Moreover, FGF21 increased plaque RACK1 and autophagy‐related protein (LC3 and beclin‐1) expression in ApoE−/− mice, thus preventing AS. However, these proteins were inhibited by LV‐RACK1 shRNA injection. Foam cell development is a crucial determinant of AS, and cholesterol efflux from foam cells represents an important defensive measure of AS. In this study, foam cells were treated with FGF21 for 24 hours after a pre‐treatment with 3MA, ATG5 siRNA or RACK1 siRNA. Our results indicated that FGF21‐induced autophagy promoted cholesterol efflux to reduce cholesterol accumulation in foam cells by up‐regulating RACK1 expression. Interestingly, immunoprecipitation results showed that RACK1 was able to activate AMPK and interact with ATG5. Taken together, our results indicated that FGF21 induces autophagy to promote cholesterol efflux and reduce cholesterol accumulation in foam cells through RACK1‐mediated AMPK activation and ATG5 interaction. These results provided new insights into the molecular mechanisms of FGF21 in the treatment of AS.
This article introduces the robust indirect technique for the slightly contaminated stochastic logistic population models. Based on discrete sampled data with a fixed unit of time between two ...consecutive observations, we not only construct the robust indirect inference generalized method of moments (GMM) estimator for the model parameters, but also propose a likelihood-ratio-type indirect statistic and a robust indirect GMM saddle-point statistic for testing the parameters of interest. In addition, we develop the robust exponential tilting estimator and the robust exponential tilting test to improve their small sample performances. Finally, their finite-sample properties are studied through Monte Carlo experiments.
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