Comparative analysis of clinical and immunological profiles across Omicron BA.5.2 subvariants using next-generation sequencing in a Chinese cohort.

Objective: The Omicron BA.5.2 variant of SARS-CoV-2 has undergone several evolutionary adaptations, leading to multiple subvariants. Rapid and accurate characterization of these subvariants is essential for effective treatment, particularly in critically ill patients. This study leverages Next-Generation Sequencing (NGS) to elucidate the clinical and immunological features across different Omicron BA.5.2 subvariants. Methods: We enrolled 28 patients infected with the Omicron variant, hospitalized in Zhangjiajie People's Hospital, Hunan, China, between January 20, 2023, and March 31, 2023. Throat swabs were collected upon admission for NGS-based identification of Omicron subvariants. Clinical data, including qSOFA scores and key laboratory tests, were collated. A detailed analysis of lymphocyte subsets was conducted to ascertain the extent of immune cell damage and disease severity. Results: Patients were infected with various Omicron subvariants, including BA.5.2.48, BA.5.2.49, BA.5.2.6, BF.7.14, DY.1, DY.2, DY.3, and DY.4. Despite having 43 identical mutation sites, each subvariant exhibited unique marker mutations. Critically ill patients demonstrated significant depletion in total lymphocyte count, T cells, CD4, CD8, B cells, and NK cells (P < 0.05). However, there were no significant differences in clinical and immunological markers across the subvariants. Conclusion: This study reveals that critically ill patients infected with different Omicron BA.5.2 subvariants experience similar levels of cellular immune dysfunction and inflammatory response. Four mutations - ORF1a:K3353R, ORF1a:L3667F, ORF1b:S997P, S:T883I showed correlation with immunological responses although this conclusion suffers from the small sample size. Our findings underscore the utility of NGS in the comprehensive assessment of infectious diseases, contributing to more effective clinical decision-making.

Robust data hiding for JPEG images with invertible neural network.

JPEG compression will cause severe distortion to the shared compressed image, which brings great challenges to extracting messages correctly from the stego image. To address such challenges, we propose a novel end-to-end robust data hiding scheme for JPEG images. The embedding and extracting secret messages on the quantized discrete cosine transform (DCT) coefficients are implemented by the bi-directional process of the invertible neural network (INN), which can provide intrinsic robustness against lossy JPEG compression. We design a JPEG compression attack module to simulate the JPEG compression process, which helps the network automatically learn how to recover the secret message from JPEG compressed image. Experimental results have demonstrated that our method achieves strong robustness against lossy JPEG compression, and also significantly improves the security compared with the existing data hiding methods on the premise of ensuring image quality and high capacity. For example, the detection error of our method against XuNet has been increased by 3.45% over the existing data hiding methods.

CEP55 predicts the poor prognosis and promotes tumorigenesis in endometrial cancer by regulating the Foxo1 signaling.

Endometrial cancer is a common gynecologic cancer, which is relevant to many differentially expressed genes. Centrosomal protein 55 (CEP55) was proved to be aberrantly expressed in several cancers. However, the function of CEP55 in endometrial cancer remains largely uncertain. The differentially expressed genes in endometrial cancer were analyzed by GEO datasets. CEP55 expression and its correlation to aggressive behaviors and diagnosis were analyzed by TCGA and the Human Protein Atlas databases. The association between CEP55 expression and 5-year overall survival in endometrial cancer was predicted using Kaplan-Meier Plotter database. Cell proliferation and apoptosis were determined by western blotting, EdU staining, TUNEL staining, and LDH release. CEP55-related targets were predicted by LinkedOmics and analyzed by KEGG pathway analysis using KOBAS. Foxo1 level was detected by western blotting. CEP55 expression was increased in endometrial cancer. The upregulated CEP55 was associated with tumor invasion, histologic grade, histological type and poor prognosis in endometrial cancer. CEP55 knockdown decreased PCNA and CDK2 levels and inhibited cell proliferation. Moreover, CEP55 downregulation promoted cell apoptosis, LDH release and increased cl-caspase-3/caspase-3 level. CEP55-related targets were enriched in Foxo1 signaling. CEP55 silencing increased the transcription activity of Foxo1. Inhibition of Foxo1 activity reversed the effect of CEP55 knockdown on cell proliferation and apoptosis. In conclusion, CEP55 knockdown repressed cell proliferation and facilitated apoptosis by regulating the Foxo1 signaling in endometrial cancer.