Objective:Using high-throughput transcriptome sequencing technology to study the differentially expressed genes (DEGs) and related regulatory signaling pathways involved in H1N1 influenza virus infection in primary human retinal pigment epithelial (RPE) cells.Methods:Primary human RPE cells were infected with H1N1 influenza virus for 2 h or 12 h, respectively. Taking H1N1 uninfected cells as a control group, total RNA was extracted, a library was constructed, and transcriptome sequencing was performed. DEGs were screened by DESeq2 software, and DEGs were analyzed by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway.Results:Compared with the control group, a total of 1830 DEGs were identified in the 2 h H1N1 influenza virus infection group, and 2847 DEGs were identified in the 12 h infection group; 1213 DEGs were identified in the H1N1 influenza virus infection kinetics process (2 h: 12 h). The GO functional annotation analysis of DEGs in the H1N1 influenza virus infection group for 12 h showed that DEGs widely exist in a variety of cellular components and participate in various biological processes such as cellular processes, biological regulation, and metabolic processes. KEGG pathway enrichment analysis showed that DEGs were mainly enriched in the PI3K-Akt signaling pathway, MAPK signaling pathway, cancer MicroRNAs, and cytokine-cytokine receptor interactions in the 2 h H1N1 influenza virus infection group; in the 12 h H1N1 influenza virus infection group, DEGs were mainly enriched in PI3K-Akt signaling pathway, cancer MicroRNAs, AGE-RAGE signaling pathway and immune-inflammatory pathways; during the kinetics of H1N1 influenza virus infection (2 h: 12 h), DEGs were mainly enriched in cytokine-cytokine receptor interaction, TGF-β signaling pathway.Conclusions:Infection with H1N1 influenza virus leads to significant changes in the transcriptome of RPE cells. These data provide scientific reference for elucidating the molecular mechanism of eye infection by respiratory viruses such as influenza virus.

Objective:To investigate the risk factors for proximal junctional kyphosis (PJK) in adult spinal deformity patients with concomitant osteoporosis undergoing long-segment spinal fusion surgery.Methods:A retrospective analysis was conducted on 76 adults spinal deformity patients with osteoporosis who underwent long-segment spinal fusion surgery at the Department of Orthopaedics, Beijing Chaoyang Hospital, between June 2013 and December 2019. The cohort included 19 males and 57 females, with a mean age of 66.26±6.10 years (range, 54-78 years). Patients were categorized into two groups based on the occurrence of PJK within a 2-year postoperative follow-up: the PJK group (21 cases) and the non-PJK group (55 cases). Comparative analyses were performed on baseline characteristics, surgical details, preoperative and postoperative spinal-pelvic parameters, Hounsfield Units (HU) of the vertebral bodies, and paraspinal muscle morphology between the groups. Spinal-pelvic parameters included the main Cobb angle, lumbar lordosis (LL), lumbosacral lordosis (LSL), sagittal vertical axis (SVA), T 1 pelvic angle (TPA), pelvic tilt (PT), sacral slope (SS), and pelvic incidence (PI). Preoperative CT was used to measure HU values at the upper instrumented vertebra (UIV), UIV+1, and UIV+2. Paraspinal muscle morphology, including the relative functional cross-sectional area (rFCSA) and functional muscle-fat index (FMFI) at the L 4 lower endplate level, was assessed using preoperative MRI. Optimal cutoff values for HU and paraspinal muscle parameters were determined using receiver operating characteristic curve analysis. Multivariable logistic regression was employed to identify independent risk factors for PJK. Results:Significant differences were observed between the PJK and non-PJK groups in preoperative PT (17.60°±8.39° vs. 24.12°±9.37°), postoperative LL (35.61°±10.62° vs. 42.22°±13.11°), LSL (30.24°±10.10° vs. 35.87°±11.12°), and SVA (37.82°±20.46° vs. 21.37°±17.35°). The differences were statistically significant ( P<0.05). The HU values of UIV (113.62±17.25 vs. 133.94±16.61), UIV+1 (123.14±16.03 vs. 138.27±13.69), and UIV+2 (121.00±15.91 vs. 134.47±15.53) were significantly lower in the PJK group ( P<0.05). Optimal cutoff values for HU at UIV, UIV+1, and UIV+2 were identified as 120.72, 127.51, and 121.50, respectively. Significant differences were also found in rFCSA (156.87±48.06 vs. 204.87±50.16) and FMFI (0.31±0.10 vs. 0.23±0.09). The differences were statistically significant( P<0.05), with optimal cutoff values of 175.43 for rFCSA and 0.24 for FMFI. Multivariable logistic regression analysis indicated that postoperative SVA [ OR=1.049, 95% CI (1.003, 1.097), P=0.037], HU of UIV [ OR=0.938, 95% CI (0.887, 0.991), P=0.024], and rFCSA of paraspinal muscles [ OR=0.883, 95% CI (0.792, 0.983), P=0.023] were independent risk factors for PJK. Conclusion:Reduced HU values of the UIV, decreased rFCSA of lumbar paraspinal muscles, and inadequate sagittal alignment correction are independent risk factors for PJK in adult spinal deformity patients with osteoporosis undergoing long-segment spinal fusion surgery.

The aim of this study was to identify novel prognostic mRNA and microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) using methods in systems biology. Differentially expressed mRNAs, miRNAs, and long non-coding RNAs (lncRNAs) were compared between HCC tumor tissues and normal liver tissues in The Cancer Genome Atlas (TCGA) database. Subsequently, a prognosis-associated mRNA co-expression network, an mRNA–miRNA reg-ulatory network, and an mRNA–miRNA–lncRNA regulatory network were constructed to identify prognostic biomarkers for HCC through Cox survival analysis. Seven prognosis-associated mRNA co-expression modules were obtained by analyzing these differentially expressed mRNAs. An expression module including 120 mRNAs was significantly corre-lated with HCC patient survival. Combined with patient survival data, several mRNAs and miRNAs, including CHST4, SLC22A8, STC2, hsa-miR-326, and hsa-miR-21 were identified from the network to predict HCC patient prognosis. Clinical significance was investigated using tissue microarray analysis of samples from 258 patients with HCC. Functional annotation of hsa-miR-326 and hsa-miR-21-5p indicated specific associations with several cancer-related pathways. The present study provides a bioinformatics method for biomarker screening, leading to the identification of an integrated mRNA–miRNA–lncRNA regulatory network and their co-expression patterns in relation to predicting HCC patient survival.