Combined CT score, blood mononuclear cell count, LDH, and plasma D-dimer for viral pneumonia diagnosis: a retrospective study.

OBJECTIVE: Due to a continued increase in viral pneumonia incidence and resulting high mortality, fast and accurate diagnosis is important for effective management. This investigation examined the significance of blood biomarkers and the CT score in the early diagnosis of viral pneumonia. METHODS: Patients who were hospitalized due to radiologically-confirmed pneumonia and underwent virus antigen rapid test were enrolled. Their clinical information was compared. Blood mononuclear cell count, LDH, and plasma D-dimer were obtained. To evaluate the utility of biomarker levels in differentiating viral pneumonia from other pneumonia, ROC curves were developed to analyze the AUC. The optimal cut-off thresholds, specificity, sensitivity, and predictive values were assessed using the Youden index. The added value of the multi-marker approach was delineated using IDI and Reclassification analyses using NRI; IDI and NRI values were examined with 95% CI. RESULTS: Overall, 1163 inpatients were recruited between January 2017 and January 2021. They were sub-divided into the viral pneumonia (n = 563) and non-viral pneumonia (n = 600) categories. We found that the CT score, blood mononuclear cell count, LDH, and plasma D-dimer were markedly elevated in viral pneumonia patients. At an LDH threshold of 693.595 U/L, an AUC of ROC was 0.805 in differentiating viral pneumonia. The combination of CT score and blood biomarkers had an ROC AUC value of 0.908. CONCLUSIONS: Combining elevated biomarkers with CT assessments outperformed the CT score alone in identifying viral pneumonia. It is crucial to better characterize the significance of biomarkers in combination with CT assessments in the diagnosis of viral pneumonia.

Application of weighted gene co-expression network analysis to identify the hub genes in H1N1.

OBJECTIVE: Identifying the disease-associated interactions between different genes helps us to find novel therapeutic targets and predictive biomarkers. METHODS: Gene expression data GSE82050 from H1N1 and control human samples were acquired from the NCBI GEO database. Highly co-expressed genes were grouped into modules. Through Person's correlation coefficient calculation between the module and clinical phenotype, notable modules were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted, and the hub genes within the module of interest were identified. Also, gene expression data GSE27131 were acquired from the GEO database to verify differential key gene expression analysis. The CIBERSORT was used to evaluate the immune cells infiltration and the GSVA was performed to identify the differentially regulated pathways in H1N1. The receiver operating characteristic (ROC) curves were used to assess the diagnostic values of the hub genes. RESULT: The black module was shown to have the highest correlation with the clinical phenotype, mainly functioning in the signaling pathways such as the mitochondrial inner membrane, DNA conformation change, DNA repair, and cell cycle phase transition. Through analysis of the black module, we found 5 genes that were highly correlated with the H1N1 phenotype. The H1N1 project from GSE27131 confirmed an increased expression of these genes. CONCLUSION: By using the WGCNA we analyzed and predicted the key genes in H1N1. BRCA1, CDC20, MAD2L1, MCM2, and UBE2C were found to be the most relevant genes, which may be therapeutic targets and predictive biomarkers for H1N1 therapy.

HA of H1N1 enhanced the expression of ICAM-1 and IL-6 in HUVECs and pathological injury in the lungs in mice.

OBJECTIVE: Both COVID-19 and influenza are viral respiratory tract infections and the epidemics of viral respiratory tract infections remain highly prevalent with lethal consequences in susceptible individuals. Expression of ICAM-1 on vascular endothelium recruits leukocytes which initiates inflammation. IL-6 induces ICAM-1. Both ICAM-1 and IL-6 can be enhanced in influenza virus infection and COVID-19 patients. Besides initiation of virus entry host cells, whether HA alone, instead of whole virus, of influenza has the effects on expression of ICAM-1 and IL-6 in vascular endothelium with injury in the lungs, remains to be demonstrated. METHODS: RT-qPCR and Western blot as well as histopathologic examination were used to examine mRNA and protein of ICAM-1 and IL-6 as well as pathological injury in the lung tissues, respectively. RESULTS: After incubation of the Human Umbilical Vein Endothelial Cells (HUVECs) with HA of H1N1 for 24 h, the mRNA and protein of ICAM-1 and IL-6 in HUVECs were increased in group of 5 µg/ml concentration with statistical significance (p < 0.05). Pathological injury in lung tissues of the mice was shown 12 h after tail intravenous injection with 100 µl of HA (50 µg/ml and 100 µg/ml in normal saline), including widened alveolar spaces with angiotelectasis in alveolar wall, alveolar luminal and interstitial inflammatory infiltrates, alveolar luminal erythrocyte effusion. CONCLUSIONS: HA alone, instead of whole H1N1 virus, induced more expression of ICAM-1 and IL-6, two molecules involving in pathological and inflammatory responses, in HUVECs and pathological injury in lung tissues of the mice. This knowledge provides a new HA-targeted potential direction for prevention and treatment of disease related to H1N1 infection.

[Epidemiologic study on the relationship between smoking and sleep apnea/hypopnea syndrome].

OBJECTIVE: To investigate how smoking was affecting the prevalence of sleep apnea/ hypopnea syndrome (SAHS) among adults aged over 30 years in Chengde city of Hebei province. METHODS: 1168 subjects, over 30 years of age were derived from a random sample from a community-based population in Shuangqiao district of Chengde city. All subjects responded to a questionnaire at their own houses regarding their habits of snoring and smoking. 1168 subjects (95.2%) answered the questions satisfactorily. RESULTS: (1) Among the smoking groups, the prevalence of snoring was 69.09%, higher than that in the nonsmoking groups 45.07% (P = 0.000). (2) In males, the smoking group had a higher prevalence (69.72%) of snoring than in the nonsmoking group (60.80%, P = 0.033). (3) Females in the smoking group had a higher prevalence of snoring (61.80%) than in the nonsmoking group (39.70%, P = 0.011). (4) The prevalence of snoring in males (60.80%) was significantly higher than that in females (39.70%, P = 0.000). (5) The prevalence (69.72%) of snoring in smoking males was similar to that in smoking females (61.80%, P = 0.336). (6) Data from logistic regression analysis indicated that smoking was one of the factors affecting snoring. (7) According to the degree of snoring, 127 moderate and severe snorers were measured by portable PSG for a whole night and the prevalence of SAHS was estimated. According to the AHI > or = 5 and the ESS > or = 9 cutoff-points, the prevalence rates of SAHS in smoking groups were both significantly higher than that in nonsmoking groups (P < 0.001). CONCLUSION: Smoking and snoring among adults aged over 30 years had correlation in our city.