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Abstract It is challenging to match the mutual interactions between implant and host because the biomaterials usually cannot actively adjust their performance to the changing microenvironment. Surface potential is one of the critical factors affecting the bioactivity of biomaterials, but it is difficult to be directly controlled in vivo. Magnetic stimulation has attracted much attention due to its deep penetrability, good reliability, and convenient operability. Here, titanium dioxide (TiO2) nanotubes and Terfenol‐D/P(VDF‐TrFE) composite film are prepared by anodic oxidation and solution casting methods on opposite sides of a titanium sheet, respectively. Terfenol‐D magnetostrictive microparticles deform under a magnetic field, generating surface potential on the P(VDF‐TrFE) piezoelectric matrix through magneto‐electric coupling. Correspondingly, equal opposite charges are induced on the surface of TiO2 nanotubes. Stem cells cultured on TiO2 nanotubes show that cell adhesion, proliferation, and differentiation abilities can be regulated by magnetic strength, which correlates with the absorption of charged proteins. Therefore, a cascade coupling of magnetic, mechanical, electric, biochemical, and cellular effects is established. This work demonstrates the feasibility of regulating the bioactivity of biomaterials in vivo through a magnetic field.

Inflammasome molecules make up a family of receptors that typically function to initiate a proinflammatory response upon infection by microbial pathogens. Dysregulation of inflammasome activity has been linked to unwanted chronic inflammation, which has also been implicated in certain autoimmune diseases such as multiple sclerosis, rheumatoid arthritis, type 1 diabetes, systemic lupus erythematosus, and related animal models. Classical inflammasome activation-dependent events have intrinsic and extrinsic effects on both innate and adaptive immune effectors, as well as resident cells in the target tissue, which all can contribute to an autoimmune response. Recently, inflammasome molecules have also been found to regulate the differentiation and function of immune effector cells independent of classical inflammasome-activated inflammation. These alternative functions for inflammasome molecules shape the nature of the adaptive immune response, that in turn can either promote or suppress the progression of autoimmunity. In this review we will summarize the roles of inflammasome molecules in regulating self-tolerance and the development of autoimmunity.

Purpose: Increasing evidence has elucidated the significance of lipid metabolism in predicting therapeutic efficacy. Obviously, a systematic analysis of lipid metabolism characterizations of gastric cancer (GC) needs to be reported.Experimental design: Based on two proposed computational algorithms (TCGA-STAD and GSE84437), the lipid metabolism characterization of 367 GC patients and its systematic relationship with genomic characteristics, clinicopathologic features, and clinical outcomes of GC were analyzed in our study. Differentially expressed genes (DEGs) were identified based on the lipid metabolism cluster. At the same time, we applied single-factor Cox regression and random forest to screen signature genes to construct a prognostic model, namely, the lipid metabolism score (LMscore). Next, we deeply explored the predictive value of the LMscore for GC. To verify the specific changes in lipid metabolism, a total of 90 serum, 30 tumor, and non-tumor adjacent tissues from GC patients, were included for pseudotargeted metabolomics analysis via SCIEX triple quad 5500 LC-MS/MS system.Results: Five lipid metabolism signature genes were identified from a total of 3,104 DEGs. The LMscore could be a prognosticator for survival in different clinicopathological GC cohorts. As well, the LMscore was identified as a predictive biomarker for responses to immunotherapy and chemotherapeutic drugs. Additionally, significant changes in sphingolipid metabolism and sphingolipid molecules were discovered in cancer tissue from GC patients by pseudotargeted metabolomics.Conclusion: In conclusion, multivariate analysis revealed that the LMscore was an independent prognostic biomarker of patient survival and therapeutic responses in GC. Depicting a comprehensive landscape of the characteristics of lipid metabolism may help to provide insights into the pathogenesis of GC, interpret the responses of gastric tumors to therapies, and achieve a better outcome in the treatment of GC. In addition, significant alterations of sphingolipid metabolism and increased levels of sphingolipids, in particular, sphingosine (d16:1) and ceramide, were discovered in GC tissue by lipidome pseudotargeted metabolomics, and most of the sphingolipid molecules have the potential to be diagnostic biomarkers for GC.

Immunotherapies are needed in the clinic that effectively suppress β cell autoimmunity and reestablish long-term self-tolerance in type 1 diabetes. We previously demonstrated that nondepleting anti-CD4 (αCD4) and αCD8α antibodies establish rapid and indefinite remission in recent-onset diabetic NOD mice. Diabetes reversal by coreceptor therapy (CoRT) is induced by suppression of pathogenic effector T cells (Teffs) and the selective egress of T cells from the pancreatic lymph nodes and islets that remain free of infiltration in the long term. Here, we defined CoRT-induced events regulating early Teff function and pancreatic residency, and long-term tolerance. TCR-driven gene expression controlling autoreactive Teff expansion and proinflammatory activity was suppressed by CoRT, and islet T cell egress was dependent on sphingosine-1 phosphate. In both murine and human T cells, CoRT upregulated the Foxo1 transcriptional axis, which in turn was required for suppression and efficient pancreatic egress of Teffs. Interestingly, long-term tolerance induced in late-preclinical NOD mice was marked by reseeding of the pancreas by a reduced CD8+ Teff pool exhibiting an exhausted phenotype. Notably, PD-1 blockade, which rescues exhausted Teffs, resulted in diabetes onset in protected animals. These findings demonstrate that CoRT has distinct intrinsic effects on Teffs that impact events early in induction and later in maintenance of self-tolerance.

T cell receptor (TCR) signaling influences multiple aspects of CD4+ and CD8+ T cell immunobiology including thymic development, peripheral homeostasis, effector subset differentiation/function, and memory formation. Additional T cell signaling cues triggered by co-stimulatory molecules and cytokines also affect TCR signaling duration, as well as accessory pathways that further shape a T cell response. Type 1 diabetes (T1D) is a T cell-driven autoimmune disease targeting the insulin producing β cells in the pancreas. Evidence indicates that dysregulated TCR signaling events in T1D impact the efficacy of central and peripheral tolerance-inducing mechanisms. In this review, we will discuss how the strength and nature of TCR signaling events influence the development of self-reactive T cells and drive the progression of T1D through effects on T cell gene expression, lineage commitment, and maintenance of pathogenic anti-self T cell effector function.

Type 1 diabetes (T1D) is widely considered to be a T cell driven autoimmune disease resulting in reduced insulin production due to dysfunction/destruction of pancreatic β cells. Currently, there continues to be a need for immunotherapies that selectively reestablish persistent β cell-specific self-tolerance for the prevention and remission of T1D in the clinic. The utilization of monoclonal antibodies (mAb) is one strategy to target specific immune cell populations inducing autoimmune-driven pathology. Several mAb have proven to be clinically safe and exhibit varying degrees of efficacy in modulating autoimmunity, including T1D. Traditionally, mAb therapies have been used to deplete a targeted cell population regardless of antigenic specificity. However, this treatment strategy can prove detrimental resulting in the loss of acquired protective immunity. Nondepleting mAb have also been applied to modulate the function of immune effector cells. Recent studies have begun to define novel mechanisms associated with mAb-based immunotherapy that alter the function of targeted effector cell pools. These results suggest short course mAb therapies may have persistent effects for regaining and maintaining self-tolerance. Furthermore, the flexibility to manipulate mAb properties permits the development of novel strategies to target multiple antigens and/or deliver therapeutic drugs by a single mAb molecule. Here, we discuss current and potential future therapeutic mAb treatment strategies for T1D, and T cell-mediated autoimmunity.

Fibroblast growth factor receptor 1 (FGFR1) has been reported in gastric cancer to be a prognostic factor. However, miR-497-targeted FGFR1 has not been explored in the carcinogenesis of gastric cancer. The present study intended to revalidate the prognostic significance of FGFR1 in patients with gastric cancer, and the mechanism of miR-497-regulated FGFR1 was investigated in gastric cancer cell proliferation and apoptosis. The messenger RNA (mRNA) and protein levels were assayed by RT-qPCR and western blotting, respectively. The targeted genes were predicted by a bioinformatics algorithm and confirmed by a dual luciferase reporter assay. Cell proliferation was analyzed by CCK-8 assay. Annexin V-FITC/PI staining was used to evaluate the apoptosis in AGS and SGC-7901 cells. FGFR1 was frequently up-regulated in gastric cancer tissues and associated with poor overall survival in patients with gastric cancer. Interestingly, FGFR1 loss-of-function resulted in a significant growth inhibition and apoptosis in AGS and SGC-7901 cells. In addition, we found that miR-497 was inhibited in gastric cancer tissues and cell lines, while overexpression of miR-497 could suppress proliferation and induce apoptosis in AGS and SGC-7901 cells. Importantly, bioinformatics analysis and experimental data suggested that FGFR1 was a direct target of miR-497, which could inhibit FGFR1 expression when transfected with miR-497 mimics. Furthermore, we found that overexpression of FGFR1 reversed the growth inhibition and apoptosis of miR-497 mimics in AGS and SGC-7901 cells. These findings suggested that overexpression of miR-497 inhibited proliferation and induced apoptosis in gastric cancer through the suppression of FGFR1.

Type 1 diabetes (T1D) is an autoimmune disease that is generally considered to be T cell-driven. Accordingly, most strategies of immunotherapy for T1D prevention and treatment in the clinic have targeted the T cell compartment. To date, however, immunotherapy has had only limited clinical success. Although certain immunotherapies have promoted a protective effect, efficacy is often short-term and acquired immunity may be impacted. This has led to the consideration of combining different approaches with the goal of achieving a synergistic therapeutic response. In this review, we will discuss the status of various T1D therapeutic strategies tested in the clinic, as well as possible combinatorial approaches to restore β cell tolerance.

Based on the difference between the vibrations of color gradient orientation sequences and color gradient sum sequences of stego images and those of images without hiding message,a novel reliable steganalysis of color images was presented which major in the analysis of these two categories of color gradient sequences,which could distill the differ-ences of the vibrations of them.The Hilbert-Huang transform based characteristic vectors were constructed and the SVM classifier was used to classification.The experimental results have shown that the proposed method realizes the reliable steganalysis of color images with higher correct rate,shorter vectors and lower false positive rate comparing with tradi-tional color image steganalysis algorithms.

Finding the densest subgraph has tremendous potential in computer vision and social network research, among other domains. In computer vision, it can demonstrate essential structures, and in social network research, it aids in identifying closely associated communities. The densest subgraph problem is finding a subgraph with maximum mean density. However, most densest subgraph-finding algorithms are based on edge-weighted graphs, where edge weights can only represent a single value dimension, whereas practical applications involve multiple dimensions. To resolve the challenge, we propose two algorithms for resolving the densest subgraph problem in a vertex-weighted graph. First, we present an exact algorithm that builds upon Goldberg's original algorithm. Through theoretical exploration and analysis, we rigorously verify our proposed algorithm's correctness and confirm that it can efficiently run in polynomial time O(n(n + m)log2n) is its temporal complexity. Our approach can be applied to identify closely related subgroups demonstrating the maximum average density in real-life situations. Additionally, we consistently offer an approximation algorithm that guarantees an accurate approximation ratio of 2. In conclusion, our contributions enrich theoretical foundations for addressing the densest subgraph problem. [ABSTRACT FROM AUTHOR]