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Background There is evidence that long non-coding RNA (lncRNA) is related to genetic stability. However, the complex biological functions of these lncRNAs are unclear. Method TCGA - KIRC lncRNAs expression matrix and somatic mutation information data were obtained from TCGA database. “GSVA” package was applied to evaluate the genomic related pathway in each samples. GO and KEGG analysis were performed to show the biological function of lncRNAs-mRNAs. “Survival” package was applied to determine the prognostic significance of lncRNAs. Multivariate Cox proportional hazard regression analysis was applied to conduct lncRNA prognosis model. Results In the present study, we applied computational biology to identify genome-related long noncoding RNA and identified 26 novel genomic instability-associated lncRNAs in clear cell renal cell carcinoma. We identified a genome instability-derived six lncRNA-based gene signature that significantly divided clear renal cell samples into high- and low-risk groups. We validated it in test cohorts. To further elucidate the role of the six lncRNAs in the model’s genome stability, we performed a gene set variation analysis (GSVA) on the matrix. We performed Pearson correlation analysis between the GSVA scores of genomic stability-related pathways and lncRNA. It was determined that LINC00460 and LINC01234 could be used as critical factors in this study. They may influence the genome stability of clear cell carcinoma by participating in mediating critical targets in the base excision repair pathway, the DNA replication pathway, homologous recombination, mismatch repair pathway, and the P53 signaling pathway. Conclusion subsections These data suggest that LINC00460 and LINC01234 are crucial for the stability of the clear cell renal cell carcinoma genome.

Mental health issues (e.g., social exclusion, depression, anxiety, and burnout) became highly prevalent in the global eSport industry. Likewise, the eSport trend in China also dramatically increased, while the attitudes and behaviours of the players also impacted their intentions to utilize video gaming. As China became the epicentre of the online video gaming industry, especially MOBA, it primarily influenced young athletes to adopt video gaming strategies for training purposes. Still, preventive measures are needed for video gaming addictions by athletes to improve their overall eSport performance. To conduct this study, self-administered questionnaires were distributed to 400 athletes aged 18–27 years; the response rate was adequate after screening, out of which 345 were finalized for the data analysis. The results indicate that metaverse-based digital healthcare significantly impacts eSport performance. Moreover, mental health significantly mediated the relationship between metaverse-based digital health and eSport performance. In addition, the digital personality also significantly moderated the relationship between metaverse-based digital healthcare and eSport performance. This research holds tremendous significance both from theoretical and practical perspectives. The study adds valuable insights to the growing body of literature regarding eSport gaming and mental health. The beneficial and constructive intuitions regarding eSport from a psychological perspective can be gained from this study, along with its pros and cons on the mental health of young Chinese athletes.

Purpose. To improve immunotherapy efficacy for melanoma, a coexpression network and key genes of M2 macrophages in melanoma were explored. A prognostic risk assessment model was established for M2-related coexpressed genes, and the role of M2 macrophages in the immune microenvironment of melanoma was elucidated. Method. We obtained mRNA data from melanoma and peritumor tissue samples from The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM). Then, we used CIBERSORT to calculate the proportion of M2 macrophage cells. A coexpression module most related to M2 macrophages in TCGA-SKCM was determined by analyzing the weighted gene coexpression network, and a coexpression network was established. After survival analysis, factors with significant results were incorporated into a Cox regression analysis to establish a model. The model’s essential genes were analyzed using functional enrichment, GSEA, and subgroup and total carcinoma. Finally, external datasets GSE65904 and GSE78220 were used to verify the prognostic risk model. Results. The yellow-green module was the coexpression module most related to M2 macrophages in TCGA-SKCM; NOTCH3, DBN1, KDELC2, and STAB1 were identified as the essential genes that promoted the infiltration of M2 macrophages in melanoma. These genes are concentrated in antigen treatment and presentation, chemokine, cytokine, the T cell receptor pathway, and the IFN-γ pathway. These factors were analyzed for survival, and factors with significant results were included in a Cox regression analysis. According to the methods, a model related to M2-TAM coexpressed gene was established, and the formula was risk score=0.25∗NOTCH3+0.008∗ DBN1−0.031∗KDELC2−0.032∗STAB1. The new model was used to perform subgroup evaluation and external queue validation. The results showed good prognostic ability. Conclusion. We proposed a Cox proportional hazards regression model associated with coexpression genes of melanoma M2 macrophages that may provide a measurement method for generating prognosis scores in patients with melanoma. Four genes coexpressed with M2 macrophages were associated with high levels of infiltration of M2 macrophages. Our findings may provide significant candidate biomarkers for the treatment and monitoring of melanoma.

Electrooptic modes with fast response and high contrast ratio are highly desirable in modern photonics and displays. Ferroelectric liquid crystals (FLCs) are especially promising for fulfilling these demands by employing photoalignment technology in FLC cells. Three electrooptic modes including surface stabilized FLC (SSFLC), deformed helix ferroelectric (DHF) mode, and electrically suppressed helix (ESH) mode are reviewed with the corresponding electrooptic effects like bi- and multi-stable switching, continuous modulation of grayscale or phase, and high contrast switching. The general operation principles FLC electrooptic modes are described, and then the characteristics of each modes for potential applications are summarized. With the advantages of controllable anchoring energy, the photoalignment provides FLC samples with uniform alignment and high contrast ratio. The fast FLCs with a high resolution and high contrast can be used in the next generation display including field sequential color FLC microdisplays, as well as switchable 2D/3D televisions.

Background The international SARS-CoV-2 pandemic has resulted in an urgent need to identify new anti-viral drugs for treatment of COVID-19. The initial step to identifying potential candidates usually involves in vitro screening that includes standard cytotoxicity controls. Under-appreciated is that viable, but stressed or otherwise compromised cells, can also have a reduced capacity to replicate virus. A refinement proposed herein for in vitro drug screening thus includes a simple growth assay to identify drug concentrations that cause cellular stress or “cytomorbidity”, as distinct from cytotoxicity or loss of viability. Methods A simple rapid bioassay is presented for antiviral drug screening using Vero E6 cells and inhibition of SARS-CoV-2 induced cytopathic effects (CPE) measured using crystal violet staining. We use high cell density for cytotoxicity assays, and low cell density for cytomorbidity assays. Results The assay clearly illustrated the anti-viral activity of remdesivir, a drug known to inhibit SARS-CoV-2 replication. In contrast, nitazoxanide, oleuropein, cyclosporine A and ribavirin all showed no ability to inhibit SARS-CoV-2 CPE. Hydroxychloroquine, cyclohexamide, didemnin B, γ-mangostin and linoleic acid were all able to inhibit viral CPE at concentrations that did not induce cytotoxicity. However, these drugs inhibited CPE at concentrations that induced cytomorbidity, indicating non-specific anti-viral activity. Conclusions We describe the methodology for a simple in vitro drug screening assay that identifies potential anti-viral drugs via their ability to inhibit SARS-CoV-2-induced CPE. The additional growth assay illustrated how several drugs display anti-viral activity at concentrations that induce cytomorbidity. For instance, hydroxychloroquine showed anti-viral activity at concentrations that slow cell growth, arguing that its purported in vitro anti-viral activity arises from non-specific impairment of cellular activities. The cytomorbidity assay can therefore rapidly exclude potential false positives.

Granzyme A (GZMA) is a serine protease secreted by cytotoxic lymphocytes, with Gzma -/- mouse studies having informed our understanding of GZMA’s physiological function. We show herein that Gzma -/- mice have a mixed C57BL/6J and C57BL/6N genetic background and retain the full-length nicotinamide nucleotide transhydrogenase ( Nnt ) gene, whereas Nnt is truncated in C57BL/6J mice. Chikungunya viral arthritis was substantially ameliorated in Gzma -/- mice; however, the presence of Nnt and the C57BL/6N background, rather than loss of GZMA expression, was responsible for this phenotype. A new CRISPR active site mutant C57BL/6J Gzma S211A mouse provided the first insights into GZMA’s bioactivity free of background issues, with circulating proteolytically active GZMA promoting immune-stimulating and pro-inflammatory signatures. Remarkably, k-mer mining of the Sequence Read Archive illustrated that ≈27% of Run Accessions and ≈38% of BioProjects listing C57BL/6J as the mouse strain had Nnt sequencing reads inconsistent with a C57BL/6J genetic background. Nnt and C57BL/6N background issues have clearly complicated our understanding of GZMA and may similarly have influenced studies across a broad range of fields.

SARS-CoV-2 uses the human ACE2 (hACE2) receptor for cell attachment and entry, with mouse ACE2 (mACE2) unable to support infection. Herein we describe an ACE2-lentivirus system and illustrate its utility for in vitro and in vivo SARS-CoV-2 infection models. Transduction of non-permissive cell lines with hACE2 imparted replication competence, and transduction with mACE2 containing N30D, N31K, F83Y and H353K substitutions, to match hACE2, rescued SARS-CoV-2 replication. Intrapulmonary hACE2-lentivirus transduction of C57BL/6J mice permitted significant virus replication in lung epithelium. RNA-Seq and histological analyses illustrated that this model involved an acute inflammatory disease followed by resolution and tissue repair, with a transcriptomic profile similar to that seen in COVID-19 patients. hACE2-lentivirus transduction of IFNAR -/- and IL-28RA -/- mouse lungs was used to illustrate that loss of type I or III interferon responses have no significant effect on virus replication. However, their importance in driving inflammatory responses was illustrated by RNA-Seq analyses. We also demonstrate the utility of the hACE2-lentivirus transduction system for vaccine evaluation in C57BL/6J mice. The ACE2-lentivirus system thus has broad application in SARS-CoV-2 research, providing a tool for both mutagenesis studies and mouse model development.

Background Cutaneous malignant melanoma (CMM) ranks among the deadliest forms of cancer. Abnormalities in lipid metabolism may have a connection with the risk of CMM progression. Methods Lipid metabolism-related genes were selected in MSigDB. A lipid metabolism-related predictive model was constructed in The Cancer Genome Atlas-skin cutaneous melanoma (TCGA-SKCM) using univariate Cox regression analysis, non-negative matrix factorization (NMF) clustering analysis, Weighted correlation network analysis (WGCNA), least absolute shrinkage and selection operator regression (LASSO) analysis, and outcomes-related genes were identified. The roles of candidate genes in CMM were determined using in vivo and in vitro experiments, and the pathway mechanism of the candidate gene was studied using transcriptomics, proteomics, lipid metabolomics, and other molecular biological methods. Results A predictive model was established, Risk Score = -0.009 * UBE2L6 + 0.033 * PLEKHA5 + 0.024 * LHB + 0.036 * CARM1 + 0.016 * PRXL2B + 0.131 * PLA2G4D. The pleckstrin homology domain-containing A5 (PLEKHA5) was identified as an essential gene and positively correlated with poor outcomes in CMM. Fc receptor-like A (FCRLA) is the downstream gene of PLEKHA5, upregulated in CMM, and tumor necrosis factor alpha (TNFα) is also an essential cytokine that promotes CMM proliferation and metastasis. Lipid metabolomics showed that PLEKHA5 knockdown increased ceramide and sphingosine levels while decreasing cholesterol ester and triglyceride levels in CMM cells, possibly related to disease progression. Conclusion The predictive model of CMM related to lipid metabolism was constructed. TNFα activates the PLEKHA5-FCRLA axis to enhance neutral lipid storage and energy metabolism in CMM cells, promoting malignant behavior.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes Coronavirus Disease 2019 (COVID-19), which can result in severe disease, often characterised by a ‘cytokine storm’ and the associated acute respiratory distress syndrome. However, many infections with SARS-CoV-2 are mild or asymptomatic throughout the course of infection. Although blood biomarkers of severe disease are well studied, less well understood are the inflammatory signatures in lung tissues associated with mild disease or silent infections, wherein infection and inflammation are rapidly resolved leading to sequelae-free recovery. Herein we described RNA-Seq and histological analyses of lungs over time in an omicron BA.1/K18-hACE2 mouse infection model, which displays these latter features. Although robust infection was evident at 2 days post infection (dpi), viral RNA was largely cleared by 10 dpi. Acute inflammatory signatures showed a slightly different pattern of cytokine signatures compared with severe infection models, and where much diminished 30 dpi and absent by 66 dpi. Cellular deconvolution identified significantly increased abundance scores for a number of anti-inflammatory pro-resolution cell types at 5/10 dpi. These included type II innate lymphoid cells, T regulatory cells, and interstitial macrophages. Genes whose expression trended downwards over 2–66 dpi included biomarkers of severe disease and were associated with ‘cytokine storm’ pathways. Genes whose expression trended upward during this period were associated with recovery of ciliated cells, AT2 to AT1 transition, reticular fibroblasts and innate lymphoid cells, indicating a return to homeostasis. Very few differentially expressed host genes were identified at 66 dpi, suggesting near complete recovery. The parallels between mild or subclinical infections in humans and those observed in this BA.1/K18-hACE2 mouse model are discussed with reference to the concept of “protective inflammation”.

Tight sandstone reservoirs generally exhibit poor physical properties and characterization of microscopic pore structure is crucial for evaluating reservoir quality and fluid flow behavior. Fractal dimension provides an effective means to quantify the complexity and heterogeneity of pore structures in such reservoirs. This study investigates tight sandstone reservoirs of the Kongdian Formation in the Nanpi Slope, Cangdong Sag, using cast thin sections, scanning electron microscopy (SEM), high-pressure mercury injection (HPMI), and constant-rate mercury injection (CRMI) experiments. We establish a full-range fractal model to characterize pore-throat distributions and elucidate the correlation between fractal dimensions and reservoir properties, alongside factors influencing pore-structure heterogeneity. Key findings include that (1) pore types are predominantly residual intergranular pores, intergranular dissolution pores, and clay mineral intercrystalline pores, with throats primarily consisting of sheet-like and curved sheet-like types, exhibiting strong pore-structure heterogeneity; (2) full-range fractal dimensions D1, D2 and D4 effectively characterize the heterogeneity of pore structure, where higher D1 and D2 values correlate with increased macro–mega pore and micro-fine throat abundance, respectively, indicating enhanced pore connectivity and superior flow capacity, while elevated D4 reflects greater nano throat complexity, degrading reservoir properties and impeding hydrocarbon flow; (3) compared to conventional methods splicing HPMI and CRMI data at 0.12 μm, the fractal-derived integration point more accurately resolves full-range pore-throat distributions, revealing significant disparities in pore-throat size populations; (4) the fractal dimensions D1, D2, and D4 are collectively governed by clay mineral content, average throat radius, displacement pressure, and tortuosity.