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The death of coronavirus disease 2019 (COVID-19) is primarily due to from critically ill patients, especially from ARDS complications caused by SARS-CoV-2. Therefore, it is essential to contribute an in-depth understanding of the pathogenesis of the disease and to identify biomarkers for predicting critically ill patients at the molecular level. Immunogenic cell death (ICD), as a specific variant of regulatory cell death driven by stress, can induce adaptive immune responses against cell death antigens in the host. Studies have confirmed that both innate and adaptive immune pathways are involved in the pathogenesis of SARS-CoV-2 infection. However, the role of ICD in the pathogenesis of severe COVID-19 has rarely been explored. In this study, we systematically evaluated the role of ICD-related genes in COVID-19. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis based on ICD differentially expressed genes. The results showed that immune infiltration characteristics were altered in severe and non-severe COVID-19. In addition, we used multiple machine learning methods to screen for five risk genes (KLF5, NSUN7, APH1B, GRB10 and CD4), which are used to predict COVID-19 severity. Finally, we constructed a nomogram to predict the risk of severe COVID-19 based on the classification and recognition model, and validated the model with external data sets. This study provides a valuable direction for the exploration of the pathogenesis and progress of COVID-19, and helps in the early identification of severe cases of COVID-19 to reduce mortality. [ABSTRACT FROM AUTHOR]

The death of coronavirus disease 2019 (COVID-19) is primarily due to from critically ill patients, especially from ARDS complications caused by SARS-CoV-2. Therefore, it is essential to contribute an in-depth understanding of the pathogenesis of the disease and to identify biomarkers for predicting critically ill patients at the molecular level. Immunogenic cell death (ICD), as a specific variant of regulatory cell death driven by stress, can induce adaptive immune responses against cell death antigens in the host. Studies have confirmed that both innate and adaptive immune pathways are involved in the pathogenesis of SARS-CoV-2 infection. However, the role of ICD in the pathogenesis of severe COVID-19 has rarely been explored. In this study, we systematically evaluated the role of ICD-related genes in COVID-19. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis based on ICD differentially expressed genes. The results showed that immune infiltration characteristics were altered in severe and non-severe COVID-19. In addition, we used multiple machine learning methods to screen for five risk genes (KLF5, NSUN7, APH1B, GRB10 and CD4), which are used to predict COVID-19 severity. Finally, we constructed a nomogram to predict the risk of severe COVID-19 based on the classification and recognition model, and validated the model with external data sets. This study provides a valuable direction for the exploration of the pathogenesis and progress of COVID-19, and helps in the early identification of severe cases of COVID-19 to reduce mortality. [ABSTRACT FROM AUTHOR]

Renal cell carcinoma (RCC) accounts for about 2% of cancer diagnoses and deaths worldwide. Recent studies emphasized the critical involvement of microbial populations in RCC from oncogenesis, tumor growth, and response to anticancer therapy. Microorganisms have been shown to be involved in various renal physiological and pathological processes by influencing the immune system function, metabolism of the host and pharmaceutical reactions. These findings have extended our understanding and provided more possibilities for the diagnostic or therapeutic development of microbiota, which could function as screening, prognostic, and predictive biomarkers, or be manipulated to prevent RCC progression, boost anticancer drug efficacy and lessen the side effects of therapy. This review aims to present an overview of the roles of microbiota in RCC, including pertinent mechanisms in microbiota-related carcinogenesis, the potential use of the microbiota as RCC biomarkers, and the possibility of modifying the microbiota for RCC prevention or treatment. According to these scientific findings, the clinical translation of microbiota is expected to improve the diagnosis and treatment of RCC. [ABSTRACT FROM AUTHOR]

In this paper, we generalize the index of impulsive periodic orbits defined in planar systems to n-dimensional impulsive switched systems. The moving Poincaré section is applied, which extends the classical Poincaré section and makes it possible to always preserve the transversal property at the corresponding time t with the help of reparametrization. Further, we combine it with the implicit function theorem and linear approximation to rewrite the original n-dimensional differential equation, which contributes to the definitions of indexes of impulsive periodic orbits of arbitrary finite order m. Based on these indexes, we further obtain sufficient conditions to judge the Zhukovskiǐ quasi-stability, which permits a time lag and focuses on the study of approximate synchronization between orbits with the existence of impulsive switchings. At last, an example of harvesting fishery model with mutual impacts of infection and abrupt harvesting firstly is presented and some sufficient criteria based on model parameters are obtained to illustrate our results. [ABSTRACT FROM AUTHOR]

The combination of ultrasound and microreactors for the synthesis of nanomaterials is becoming increasingly popular, but effectively altering the ultrasonic field at the microscale to control the crystallization process remains a challenge. Herein, we investigated numerically and experimentally the effects of the ultrasonic field on the synthesis of boron-doped carbon nitride supported silver nanoparticles based on our homemade ultrasound-assisted coiled flow inverter microreactor (UCFIR). Specifically, the ultrasound promotes the radial mixing in the coiled flow inverter microreactor, even under low Reynolds number 10, resulting in better control over the crystallization process. The effects of key parameters, such as ultrasonic field distribution and ultrasonic power, on the particle size and size distribution of Ag/B-g-C3N4 have been demonstrated. The results show that when the ultrasound transducer is positioned on the 'abc' sides, the Ag/B-g-C3N4 with small and uniform Ag particles (4.12 ± 1.12 nm) can be obtained. As ultrasound power increased (0–176 W) and residence time decreased (17.5–140 s), the size of silver nanoparticles decreased, and their distribution narrowed. [ABSTRACT FROM AUTHOR]

We construct a two-tensor model with order-3 and present its W-representation. Moreover we derive the compact expressions of correlators from the W-representation and analyze the free energy in large N limit. In addition, we establish the correspondence between two colored Dyck walks in the Fredkin spin chain and tree operators in the ring. Based on the classification Dyck walks, we give the number of tree operators with the given level. Furthermore, we show the entanglement scaling of Fredkin spin chain beyond logarithmic scaling in the ordinary critical systems from the viewpoint of tensor model. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) is a highly aggressive and prevalent brain tumor that poses significant challenges in treatment. SRSF9, an RNA-binding protein, is essential for cellular processes and implicated in cancer progression. Yet, its function and mechanism in GBM need clarification. Methods: Bioinformatics analysis was performed to explore differential expression of SRSF9 in GBM and its prognostic relevance to glioma patients. SRSF9 and CDK1 expression in GBM cell lines and patients’ tissues were quantified by RT-qPCR, Western blot or immunofluorescence assay. The role of SRSF9 in GBM cell proliferation and migration was assessed by MTT, Transwell and colony formation assays. Additionally, transcriptional regulation of CDK1 by SRSF9 was investigated using ChIP-PCR and dual-luciferase assays. Results: The elevated SRSF9 expression correlates to GBM stages and poor survival of glioma patients. Through gain-of-function and loss-of-function strategies, SRSF9 was demonstrated to promote proliferation and migration of GBM cells. Bioinformatics analysis showed that SRSF9 has an impact on cell growth pathways including cell cycle checkpoints and E2F targets. Mechanistically, SRSF9 appears to bind to the promoter of CDK1 gene and increase its transcription level, thus promoting GBM cell proliferation. Conclusions: These findings uncover the cellular function of SRSF9 in GBM and highlight its therapeutic potential for GBM. [ABSTRACT FROM AUTHOR]