MVMR-FS : Non-parametric feature selection algorithm based on Maximum inter-class Variation and Minimum Redundancy

How to accurately measure the relevance and redundancy of features is an age-old challenge in the field of feature selection. However, existing filter-based feature selection methods cannot directly measure redundancy for continuous data. In addition, most methods rely on manually specifying the number of features, which may introduce errors in the absence of expert knowledge. In this paper, we propose a non-parametric feature selection algorithm based on maximum inter-class variation and minimum redundancy, abbreviated as MVMR-FS. We first introduce supervised and unsupervised kernel density estimation on the features to capture their similarities and differences in inter-class and overall distributions. Subsequently, we present the criteria for maximum inter-class variation and minimum redundancy (MVMR), wherein the inter-class probability distributions are employed to reflect feature relevance and the distances between overall probability distributions are used to quantify redundancy. Finally, we employ an AGA to search for the feature subset that minimizes the MVMR. Compared with ten state-of-the-art methods, MVMR-FS achieves the highest average accuracy and improves the accuracy by 5% to 11%

Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation

Semi-supervised learning has become increasingly popular in medical image segmentation due to its ability to leverage large amounts of unlabeled data to extract additional information. However, most existing semi-supervised segmentation methods only focus on extracting information from unlabeled data, disregarding the potential of labeled data to further improve the performance of the model. In this paper, we propose a novel Correlation Aware Mutual Learning (CAML) framework that leverages labeled data to guide the extraction of information from unlabeled data. Our approach is based on a mutual learning strategy that incorporates two modules: the Cross-sample Mutual Attention Module (CMA) and the Omni-Correlation Consistency Module (OCC). The CMA module establishes dense cross-sample correlations among a group of samples, enabling the transfer of label prior knowledge to unlabeled data. The OCC module constructs omni-correlations between the unlabeled and labeled datasets and regularizes dual models by constraining the omni-correlation matrix of each sub-model to be consistent. Experiments on the Atrial Segmentation Challenge dataset demonstrate that our proposed approach outperforms state-of-the-art methods, highlighting the effectiveness of our framework in medical image segmentation tasks. The codes, pre-trained weights, and data are publicly available.Comment: MICCAI2023 early accepted, camera ready versio

Effect of ursolic acid on obesity-induced insulin resistance in rat liver

Purpose: To determine the expression of protein tyrosine phosphatase-1B (PTP-1B) and insulin receptor substrate-2 (IRS-2) in the liver tissue of obesity-induced insulin-resistant rats.Methods: Insulin resistance (IR) was induced in Wistar rats by placing them on a high fat diet for 6weeks, and ursolic acid (UA) was administered. Metformin served as positive control drug. The rats were divided into 5 groups based on the  treatments given: normal group, positive control group, metformin group, high-dose UA group, and low-dose UA group. The general conditions of the rats were assessed 4 and 8 weeks after the various treatments. Liver glycogen levels were measured, and liver  histological examination carried out after tissue processing and staining with hematoxylin and eosin (H & E). Real-time polymerase chain reaction (RT-PCR) was employed for the determination of hepatic expressions of PTP-1B and IRS-2 mRNAs, while expressions of PTP-1B protein and IRS-2 protein, and  phosphorylation of IRS-2 tyrosine were assayed by Western blotting.Results: Liver glycogen levels were significantly increased in the UA-treated groups (p < 0.05). Moreover, UA provoked reductions in the expression of PTP-1B protein (p < 0.05), but up-regulated the expression of IRS-2 protein (p < 0.05), and enhanced IRS-2 tyrosine phosphorylation (p < 0.05).Conclusion: These results suggest that UA mitigates IR through blockage of PTP-1B expression and up-regulation of the expression of IRS-2 mRNA. Therefore, PTP-1B is a potential target for the treatment of type 2 diabetes.Keywords: Ursolic acid, Insulin resistance, Liver, Protein tyrosine phosphatase-1B, Insulin receptor substrate

Transcriptional regulation of dendritic cell development and function

Dendritic cells (DCs) are sentinel immune cells that form a critical bridge linking the innate and adaptive immune systems. Extensive research addressing the cellular origin and heterogeneity of the DC network has revealed the essential role played by the spatiotemporal activity of key transcription factors. In response to environmental signals DC mature but it is only following the sensing of environmental signals that DC can induce an antigen specific T cell response. Thus, whilst the coordinate action of transcription factors governs DC differentiation, sensing of environmental signals by DC is instrumental in shaping their functional properties. In this review, we provide an overview that focuses on recent advances in understanding the transcriptional networks that regulate the development of the reported DC subsets, shedding light on the function of different DC subsets. Specifically, we discuss the emerging knowledge on the heterogeneity of cDC2s, the ontogeny of pDCs, and the newly described DC subset, DC3. Additionally, we examine critical transcription factors such as IRF8, PU.1, and E2-2 and their regulatory mechanisms and downstream targets. We highlight the complex interplay between these transcription factors, which shape the DC transcriptome and influence their function in response to environmental stimuli. The information presented in this review provides essential insights into the regulation of DC development and function, which might have implications for developing novel therapeutic strategies for immune-related diseases

Inhibitive effect of triptolide on invasiveness of human fibrosarcoma cells by downregulating matrix metalloproteinase—9 expression

AbstractObjectiveTo explore the molecular mechanisms of antitumor properties of triptolide, a bioactive component isolated from the Chinese herb Tripterygium wolfordii Hook F.MethodsHuman fibrosarcoma HT-1080 cells were treated with different doses of triptolide for 72 h. Then the expression and activity of matrix metalloproteinase (MMP)-2 and -9 were measured and the invasiveness of triptolide-treated HT-1080 cells was compared with that of anti-MMP-9-treated HT-1080 cells.Results18 nmol/L triptolide inhibited the gene expression and activity of MMP-9, but not those of MMP-2, in HT-1080 cells. In addition, both 18 nmol/L triptolide and 3 μg/mL anti-MMP-9 significantly reduced the invasive potential of HT-1080 cells, by about 50% and 35%, respectively, compared with the control. Whereas there was no significant difference between the effect of 18 nmol/L triptolide and that of anti-MMP-9 on invasive potential of HT-1080 cells.ConclusionsThese data suggest that triptolide inhibits tumor cell invasion partly by reducing MMP-9 gene expression and activity

Indirect shared control for cooperative driving between driver and automation in steer-by-wire vehicles

It is widely acknowledged that drivers should remain in the control loop before automated vehicles completely meet real-world operational conditions. This paper presents an ``indirect shared control'' framework for steer-by-wire vehicles, which allows the control authority to be continuously shared between the driver and automation through an weighted-input-summation method. A ``best-response'' driver steering model based on model predictive control (MPC) for indirect shared control is proposed. Unlike any conventional driver model for manual driving, this model assumes that drivers can learn and incorporate the controller strategy into their internal model for predictive path following. The analytic solution to the driver model is provided to enable off-line simulations. A driving-simulator experiment was conducted to demonstrate the advantages of the indirect shared control system in a highway lane-keeping task. The result showed that the proposed indirect shared control method was effective to improve the subjects' lane-keeping performance and reduce steering control effort. The proposed driver steering model was also validated by the experiment data, which produced a smaller prediction error than the conventional MPC driver model

MicroRNA-322 inhibits inflammatory cytokine expression and promotes cell proliferation in LPS-stimulated murine macrophages by targeting NF-κB1 (p50)

Correspondence : Hanchuan Dai ([email protected]) Inflammation is the body's normal self-protection mechanism to eliminate pathogens and resist pathogen invasion. The excessive inflammatory response may lead to inflammatory lesions. The mechanisms accounting for inflammation remain hazy. miRNAs have been proposed to have crucial effects on inflammation. In the present study, we reported that lipopolysaccharide (LPS)-stimulation increased the expression levels of inflammatory cytokines and the cell-cycle progression was suppressed in RAW264.7 cells. Meanwhile, the expression of miR-322 was significantly down-regulated after LPS treatment. Bioinformatics predictions revealed a potential binding site of miR-322 in 3 -UTR of NF-κB1 (p50) and it was further confirmed by luciferase assay. Moreover, both the mRNA and protein levels of NF-κB1 (p50) were down-regulated by miR-322 in RAW264.7 cells. Subsequently, we demonstrated that miR-322 mimics decrease in the expression levels of inflammatory cytokines and cell-cycle repression can be rescued following LPS treatment in RAW264.7 cells. The anti-inflammatory cytokines expression including IL-4 and IL-10 were significantly up-regulated. Furthermore, miR-322 could also promote RAW264.7 cells proliferation. These results demonstrate that miR-322 is a negative regulator of inflammatory response by targeting NF-κB1 (p50)

Molecular characteristics and function of elliptical Kiwifruit

Article describes study analyzing the chemical components of elliptical kiwifruit (Actinidia chinensis Planch) using Fourier transform infrared spectroscopy (FT-IR) and gas chromatography mass spectrometry (GC–MS) technologies