Role of MicroRNA-26b in Glioma Development and Its Mediated Regulation on EphA2

BACKGROUND: MicroRNAs (miRNAs) are short, non-coding RNAs that regulate the expression of multiple target genes. Deregulation of miRNAs is common in human tumorigenesis. Low level expression of miR-26b has been found in glioma cells. However, its underlying mechanism of action has not been determined. METHODOLOGY/PRINCIPAL FINDINGS: Real-time PCR was employed to measure the expression level of miR-26b in glioma patients and cells. The level of miR-26b was inversely correlated with the grade of glioma. Ectopic expression of miR-26b inhibited the proliferation, migration and invasion of human glioma cells. A binding site for miR-26b was identified in the 3'UTR of EphA2. Over-expression of miR-26b in glioma cells repressed the endogenous level of EphA2 protein. Vasculogenic mimicry (VM) experiments were performed to further confirm the effects of miR-26b on the regulation of EphA2, and the results showed that miR-26b inhibited the VM processes which regulated by EphA2. SIGNIFICANCE: This study demonstrated that miR-26b may act as a tumor suppressor in glioma and it directly regulates EphA2 expression. EphA2 is a direct target of miR-26b, and the down-regulation of EphA2 mediated by miR-26b is dependent on the binding of miR-26b to a specific response element of microRNA in the 3'UTR region of EphA2 mRNA

Uygur Autonomous Region Research

Abstract: Related HLA-haploidentical HSCT has been applied more and more recently, but the reconstitution of T lymphocyte subsets and its clinical significance in patients received related HLA-haploidentical non T-cell depleted in vitro high-dose peripheral blood hematopoietic SCT (RHNT-PSCT) are incompletely defined. In the present study of our RHNT-PSCT, we found that in non-aGVHD group, CD3 + T lymphocyte recovered to normal levels gradually between 60 and 90 days, and the recovery of CD4 + T lymphocyte was retarded significantly, CD4 + /CD8 + ratio was apparently inverted. Whereas, the ratio of CD4 + CD25 + Foxp3 + Treg cells was significantly lower in aGVHD group than in healthy control group and non-aGVHD group, and also in grade III-IV aGVHD patients than in grade I-II aGVHD patients. Meanwhile, we observed the level of interleukin-10 (IL-10) gradually increased in serum of patients without aGVHD, but decreased in III-IV aGVHD patients significantly. Spearman correlation analysis showed that serum IL-10 level was negatively correlated with the grade of aGVHD. These results suggest that the reconstitution of peripheral blood T lymphocyte subsets is good, and dynamic detection of Treg cells and serum IL-10 level might predict aGVHD in the early stage after our RHNT-PSCT

Hemagglutinin Gene Variation Rate of H9N2 Avian Influenza Virus by Vaccine Intervention in China

H9N2 subtype avian influenza virus (AIV) is widespread globally, with China being the main epidemic center. Inactivated virus vaccination was adopted as the main prevention method in China. In this study, 22 hemagglutinin (HA) sequences were obtained from all inactivated vaccine strains of H9N2 subtype AIVs in China since its introduction. A phylogenetic analysis of the vaccine sequences and HA sequences of all published H9N2 subtype AIVs was conducted to investigate the relationship between vaccine use and the virus genetic diversity of the virus. We found that during 2002–2006, when fewer vaccines were used, annual genetic differences between the HA sequences were mainly distributed between 0.025 and 0.075 and were mainly caused by point mutations. From 2009 to 2013, more vaccines were used, and the genetic distance between sequences was about 10 times greater than between 2002 and 2006, especially in 2013. In addition to the accumulation of point mutations, insertion mutations may be the main reason for the large genetic differences between sequences from 2009 to 2013. These findings suggest that the use of inactivated vaccines affected point mutations in the HA sequences and that the contribution of high-frequency replacement vaccine strains to the rate of virus evolution is greater than that of low-frequency replacement vaccine strains. The selection pressure of the vaccine antibody plays a certain role in regulating the variation of HA sequences in H9N2 subtype AIV

RNA Sequencing Demonstrates That Circular RNA Regulates Avian Influenza Virus Replication in Human Cells

Circular RNAs (circRNAs) are involved in diverse biological processes. Avian influenza virus (AIV) can cross the species barrier to infect humans. Here, we employed RNA sequencing technology to profile circRNA, microRNA, and mRNA expression in human lung carcinoma cells in response to AIV or human influenza A virus (IAV) infection at viral replication. The analysis revealed that the expression of 475 common circRNAs were significantly regulated. The 381 and 1163 up-regulated circRNAs were induced by AIV at 8 and 16 h, respectively. Subsequently, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses were also conducted for the AIV-specific up-regulated circRNAs. Moreover, the circRNAs were characterized, of which six were verified by quantitative real-time PCR. We further confirmed that expression of the selected circRNAs only increased following AIV infection. Knocking down the selected circRNAs promoted AIV proliferation, and overexpression of three of the candidate circRNAs restricted AIV replication and proliferation. We further analyzed that AIV-specific up-regulated circRNA mechanisms might function through the ceRNA network to affect the “Endocytosis” pathway and the “Cell cycle process”. These data provide the first expression profile of AIV-specific up-regulated circRNAs and shed new light on the pathogenesis of AIV infection. Our findings also suggest that these circRNAs serve an important role in AIV infection

InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting

Long-term time series forecasting (LTSF) provides substantial benefits for numerous real-world applications, whereas places essential demands on the model capacity to capture long-range dependencies. Recent Transformer-based models have significantly improved LTSF performance. It is worth noting that Transformer with the self-attention mechanism was originally proposed to model language sequences whose tokens (i.e., words) are discrete and highly semantic. However, unlike language sequences, most time series are sequential and continuous numeric points. Time steps with temporal redundancy are weakly semantic, and only leveraging time-domain tokens is hard to depict the overall properties of time series (e.g., the overall trend and periodic variations). To address these problems, we propose a novel Transformer-based forecasting model named InParformer with an Interactive Parallel Attention (InPar Attention) mechanism. The InPar Attention is proposed to learn long-range dependencies comprehensively in both frequency and time domains. To improve its learning capacity and efficiency, we further design several mechanisms, including query selection, key-value pair compression, and recombination. Moreover, InParformer is constructed with evolutionary seasonal-trend decomposition modules to enhance intricate temporal pattern extraction. Extensive experiments on six real-world benchmarks show that InParformer outperforms the state-of-the-art forecasting Transformers

Dual-Encoder Transformer for Short-Term Photovoltaic Power Prediction Using Satellite Remote-Sensing Data

The penetration of photovoltaic (PV) energy has gained a significant increase in recent years because of its sustainable and clean characteristics. However, the uncertainty of PV power affected by variable weather poses challenges to an accurate short-term prediction, which is crucial for reliable power system operation. Existing methods focus on coupling satellite images with ground measurements to extract features using deep neural networks. However, a flexible predictive framework capable of handling these two data structures is still not well developed. The spatial and temporal features are merely concatenated and passed to the following layer of a neural network, which is incapable of utilizing the correlation between them. Therefore, we propose a novel dual-encoder transformer (DualET) for short-term PV power prediction. The dual encoders contain wavelet transform and series decomposition blocks to extract informative features from image and sequence data, respectively. Moreover, we propose a cross-domain attention module to learn the correlation between the temporal features and cloud information and modify the attention modules with the spare form and Fourier transform to improve their performance. The experiments on real-world datasets, including PV station data and satellite images, show that our model achieves better results than other models for short-term PV power prediction

Evaluation of Clinical and Immune Responses in Recovered Children with Mild COVID-19

The coronavirus disease 2019 (COVID-19) has spread globally and variants continue to emerge, with children are accounting for a growing share of COVID-19 cases. However, the establishment of immune memory and the long-term health consequences in asymptomatic or mildly symptomatic children after severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We collected clinical data and whole blood samples from discharged children for 6–8 months after symptom onset among 0-to-14-year-old children. Representative inflammation signs returned to normal in all age ranges. The infants and young children (0–4 years old) had lung lesions that persisted for 6–8 months and were less responsive for antigen-specific IgG secretion. In the 5-to-14-year-old group, lung imaging abnormalities gradually recovered, and the IgG-specific antibody response was strongest. In addition, we found a robust IgM+ memory B cell response in all age. Memory T cells specific for the spike or nucleocapsid protein were generated, with no significant difference in IFN-γ response among all ages. Our study highlights that although lung lesions caused by COVID-19 can last for at least 6–8 months in infants and young children, most children have detectable residual neutralizing antibodies and specific cellular immune responses at this stage

Identification of potential resistance mechanisms and therapeutic targets for the relapse of BCMA CAR-T therapy in relapsed/refractory multiple myeloma through single-cell sequencing

Abstract Background BCMA CAR-T is highly effective for relapsed/refractory multiple myeloma(R/R-MM) and significantly improves the survival of patients. However, the short remission time and high relapse rate of MM patients treated with BCMA CAR-T remain bottlenecks that limit long-term survival. The immune microenvironment of the bone marrow (BM) in R/R-MM may be responsible for this. The present study aims to present an in-depth analysis of resistant mechanisms and to explore potential novel therapeutic targets for relapse of BCMA CAR-T treatment via single-cell RNA sequencing (scRNA-seq) of BM plasma cells and immune cells. Methods This study used 10X Genomic scRNA-seq to identify cell populations in R/R-MM CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. Cell Ranger pipeline and CellChat were used to perform detailed analysis. Results We compared the heterogeneity of CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We found that the proportion of monocytes/macrophages increased, while the percentage of T cells decreased at relapse after BCMA CAR-T treatment. We then reclustered and analyzed the alterations in plasma cells, T cells, NK cells, DCs, neutrophils, and monocytes/macrophages in the BM microenvironment before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We show here that the percentage of BCMA positive plasma cells increased at relapse after BCMA CAR-T cell therapy. Other targets such as CD38, CD24, SLAMF7, CD138, and GPRC5D were also found to be expressed in plasma cells of the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Furthermore, exhausted T cells, TIGIT+NK cells, interferon-responsive DCs, and interferon-responsive neutrophils, increased in the R/R-MM patient at relapse after BCMA CAR-T cell treatment. Significantly, the proportion of IL1βhi Mφ, S100A9hi Mφ, interferon-responsive Mφ, CD16hi Mφ, MARCO hi Mφ, and S100A11hi Mφ significantly increased in the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Cell–cell communication analysis indicated that monocytes/macrophages, especially the MIF and APRIL signaling pathway are key players in R/R-MM patient at relapse after BCMA CAR-T cell therapy. Conclusion Taken together, our data extend the understanding of intrinsic and extrinsic relapse of BCMA CAR-T treatment in R/R-MM patient and the potential mechanisms involved in the alterations of antigens and the induced immunosuppressive microenvironment, which may provide a basis for the optimization of BCMA CAR-T strategies. Further studies should be performed to confirm these findings