Background: Human respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection and hospitalization, especially in children. Highly mutagenic nature and antigenic diversity enable the RSV to successfully survive in human population. We conducted a molecular epidemiological study during 2017–2021 to investigate the prevalence and genetic characteristics of RSV. Methods: A total of 6499 nasopharyngeal (NP) swabs were collected from hospitalized children at Department of Pediatrics, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, Guangdong, China. All NP swab specimens were preliminary screened for common respiratory viruses and then tested for RSV using specific PCR assays. Partial G genes of RSV were amplified for phylogenetic analysis and genetic characterization. Results: The overall detection rate for common respiratory viruses was 16.12% (1048/6499). Among those, 405 specimens (6.20%, 405/6499) were found positive for RSV. The monthly distribution of RSV and other respiratory viruses was variable, and the highest incidence was recorded in Autumn and Winter. Based on the sequencing of hypervariable region of G gene, 93 RSV sequences were sub-grouped into RSV-A (56, 60.2%) and RSV-B (37, 39.8%). There was no coinfection of RSV-A and RSV-B in the tested samples. Phylogenetic analysis revealed that RSV-A and RSV-B strains belonged to ON1 and BA9 genotypes respectively, indicating predominance of these genotypes in Guangzhou. Several substitutions were observed which may likely change the antigenicity and pathogenicity of RSV. Multiple glycosylation sites were noticed, demonstrating high selection pressure on these genotypes. Conclusion: This study illustrated useful information about epidemiology, genetic characteristics, and circulating genotypes of RSV in Guangzhou China. Regular monitoring of the circulating strains of RSV in different parts of China could assist in the development of more effective vaccines and preventive measures.

Background: Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic synovitis and joint destruction. To systematically investigate the regulatory relationship between key ferroptosis genes and gut metabolites in RA, this study employed an integrative multi-omics approach combined with machine learning algorithms and single-cell transcriptomic data, identifying and validating GPX3 and MYC as potential critical ferroptosis regulators in RA.Methods and results: First, 16 candidate genes were obtained by intersecting WGCNA, differential expression analysis results, and targets related to ferroptosis and gut microbiota. Following cross-validation with machine learning approaches including LASSO, SVM, and RFE-RF, GPX3 and MYC were ultimately identified as crucial genes. GSVA and GSEA analyses revealed that high expression of GPX3 and MYC was enriched in interferon response and TNFA signaling pathways, while their low expression was associated with fatty acid metabolism and oxidative phosphorylation pathways. Further single-cell RNA sequencing analysis demonstrated that MYC was expressed in multiple immune cell types, particularly in CD4+ T cells and NK cells. Ferroptosis scoring for CD8+ T cells and subsequent cell communication analysis revealed stronger interactions between CD8+ T cells with higher ferroptosis scores and other immune cells through IFN-II and CCL signaling, further intensifying the activation of the inflammatory microenvironment. Additionally, molecular docking analysis of GPX3 and MYC with the gut metabolites Diosgenin and Differentiation-inducing factor 3 (DIF-3) respectively showed that the GPX3-Diosgenin complex had the lowest binding energy, and a 100 ns molecular dynamics simulation was performed on this complex. Results showed good stability of the complex across indicators such as RMSD, RMSF, SASA, and radius of gyration, suggesting that Diosgenin may intervene in ferroptosis and inflammatory injury in RA by binding to and modulating GPX3 function.Conclusion: This study elucidated the multifaceted mechanisms of GPX3 and MYC in RA pathogenesis and preliminarily validated the potential role of gut metabolites in mediating ferroptosis regulation, offering novel theoretical foundations and potential strategies for diagnostic biomarker screening and targeted therapy in RA.

Coronavirus disease 2019 (COVID-19) can be screened and diagnosed through the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by real-time reverse transcription polymerase chain reaction. SARS-CoV-2 nucleic acid amplification tests (NAATs) have been rapidly developed and quickly applied to clinical testing during the pandemic. However, studies evaluating the performance of these NAAT assays are limited. We evaluated the performance of four NAATs, which were marked by the Conformité Européenne and widely used in China during the pandemic. Results showed that the analytical sensitivity of the four assays was significantly lower than that claimed by the NAAT manufacturers. The limit of detection (LOD) of Daan, Sansure, and Hybribio NAATs was 3000 copies/mL, whereas the LOD of Bioperfectus NAATs was 4000 copies/mL. The results of the consistency test using 46 samples showed that Daan, Sansure, and Hybribio NAATs could detect the samples with a specificity of 100% (30/30) and a sensitivity of 100% (16 /16), whereas Bioperfectus NAAT detected the samples with a specificity of 100% (30/30) and a sensitivity 81.25% (13/16). The sensitivity of Bioperfectus NAAT was lower than that of the three other NAATs; this finding was consistent with the result that Bioperfectus NAAT had a higher LOD than the three other kinds of NAATs. The four above mentioned reagents presented high specificity; however, for the detection of the samples with low virus concentration, Bioperfectus reagent had the risk of missing detection. Therefore, the LOD should be considered in the selection of SARS-CoV-2 NAATs.

Background: To detect the serum antibodies against respiratory viruses and atypical pathogens in adults with community‐acquired pneumonia (CAP) in Guangzhou City (Guangdong province, China).Methods: A retrospective study was carried out with samples from 685 adults who were admitted with CAP and 108 non‐CAP control patients. Atypical pathogens and respiratory viruses in serum were detected using the Pneumoslide IgM test from Vircell, Spain. All patients were divided into 6 groups according to age: 18‐24, 25‐44, 45‐59, 60‐74, 75‐89, and >90.Results: The total positive rate of CAP was 35.4%, which was highest in the 18‐24 age group (P < .05). The highest positive rate, 17.11%, was observed for Mycoplasma pneumoniae (MP). The mean age of MP‐infected patients was higher than that of the controls (P < .05). The positive rates for influenza B (INFB), Legionella pneumophila (LP1), Coxiella burnetii (COX), influenza A (INFA), parainfluenza virus (PIV), respiratory syncytial virus (RSV), Chlamydophila pneumoniae (CP), and adenovirus (ADV) were 5.56%, 3.07%, 2.63%, 2.34%, 1.90%, 1.61, 0.88%, and 0.29%, respectively. There were 4.37% of patients with CAP having multiple infections. The main symptoms observed in the 685 CAP patients were cough and sputum production, in 78.4% and 67.4%. Fever was followed by 54% of CAP patients. Dyspnea (39.1%), anorexia (36.8%), increased thirst (26.7%), chills (18.7), headache (14.6%), and nausea (13.1%) were also frequently observed in the CAP patients.Conclusions: MP infection was the most common in adult CAP patients in Guangzhou City with the highest positive rate in the 18‐24 age groups.

Acute respiratory tract diseases (ARDs) are predominantly caused by viral infections, with one of their hallmark characteristics being multiple viral co-infections. Such multiple viral infections not only complicate therapeutic interventions but also lead to an increase in mortality rates. Most traditional bioassays, however, are limited to identifying a single type of virus, leading to missed diagnoses in samples with multiple respiratory pathogens. Consequently, there is an urgent need for the development of a detection method that exhibits high sensitivity, allows for constant-temperature operation, is user-friendly, and is capable of simultaneously detecting multiple viral nucleic acid targets. To address this challenge, we developed a novel method for the simultaneous detection of multiple respiratory viral nucleic acids using size-encoded microbeads and rolling circle amplification. Additionally, we designed a microfluidic chip featuring distinct spacer arrays that separate the microbeads into different regions based on their size, thereby generating characteristic signals indicative of varying biomarker levels. Rolling circle amplification significantly enhances the detection sensitivity on the microbeads, achieving a detection limit as low as fmol L⁻¹. In representative clinical samples, both the sensitivity and specificity for distinguishing target viral RNA from other respiratory diseases reached 100%. Importantly, this strategy enables simultaneous and in situ sensitive analysis of four viral nucleic acids. The throughput of pathogen nucleic acid detection can be further enhanced by incorporating additional microbeads of varying sizes and implementing a corresponding microchip design. We anticipate that this strategy holds substantial promise for clinical diagnosis of multiple respiratory viral infections.