[Clinical features of children with coronavirus disease 2019 in different age groups during the epidemic of Omicron variant]. / æ–°åž‹å† çŠ¶ç— æ¯’Omicronå˜å¼‚æ ªæµè¡ŒæœŸé—´ä¸åŒå¹´é¾„å„¿ç«¥æ„ŸæŸ“çš„ä¸´åºŠç‰¹å¾åˆ†æž.

OBJECTIVES: To study the differences in the clinical features of children with coronavirus disease 2019 (COVID-19) in different age groups during the epidemic of Omicron variant. METHODS: A retrospective analysis was performed on the clinical data of 211 children with COVID-19 who were admitted to the Department of General Pediatrics, Zhongshan People's Hospital, from December 9, 2022 to January 8, 2023. According to their age, they were divided into 4 groups: 1 month-<1 year (n=84), 1-<3 years group (n=64), 3-<5 years (n=29), and ≥5 years (n=34). The above groups were compared in terms of general status, clinical features, ancillary examination results, treatment, and outcome. RESULTS: The children aged <3 years accounted for 70.1% (148/211) of all hospitalized children with COVID-19, and the 3-<5 years group and the ≥5 years group had a significantly higher proportion of children with underlying diseases than the 1 month-<1 year group and the 1-<3 years group (P<0.05). Compared with the other three groups, the 1 month-<1 year group had significantly higher incidence rates of dyspnea, nasal congestion/nasal discharge, diarrhea and significantly lower incidence rates of convulsion and nervous system involvement (P<0.05). Moreover, compared with the other three groups, the 1 month-<1 year group had significantly higher incidence rates of increases in bile acid and creatine kinase isoenzyme and significantly lower incidence rates of decreased platelet count, increased neutrophil percentage, and decreased lymphocyte percentage (P<0.05). The 1 month-<1 year group had a significantly higher incidence rate of mild COVID-19 than the 1-<3 years group and a significantly lower incidence rate of severe/critical COVID-19 than the other three groups (P<0.05). Compared with the other three groups, the 1 month-<1 year group had a significantly higher proportion of children receiving oxygen inhalation therapy (P<0.05). CONCLUSIONS: Children with COVID-19 in different age groups have different clinical features during the epidemic of Omicron variant, especially between the children aged 1 month to <1 year and those aged ≥1 year.

Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis.

Background: IgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN. Methods: GSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN. Result: A total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN. Conclusion: We screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.

A study of forensic genetics: ITO index distribution and kinship judgment between two individuals.

According to Mendel's law of genetic separation, there must be a certain blood relationship between members of the same family, and two individuals with blood relations must have the following three situations, that is, there are two homologous genes (I denotes), one homologous gene (T denotes), and no homologous genes (O denotes), which is the ITO index for calculating the blood relationship between two individuals. The AGGU Expressmarker 22 kit, ABI 3500 genetic analyzer, and GeneMapper ID-X v1.5 software were used to statistically analyze the ITO index of the gene locus of 5 kinds of samples, 28 pairs of monozygotic twins (MT), 4,000 pairs of parent-offspring (PO), 392 pairs of full sibling (FS), 138 pairs of half-siblings (HS) (including grandchildren, uncles, and nephews) and 3,500 pairs of unrelated individuals (UI). Observing the median distribution of ITO index found that from MT, PO, FS, HS to UI, the more distant the kinship, the smaller the ITO index. Full sibling index (FSI)/half-sibling index (HSI) ≥ 1 can be used as the FS discriminant standard, FSI/HSI < 1 can be used as the HS discriminant standard. According to the distance of kinship, from the direction of MT, PO, FS, HS, and UI, the proportion of the maximum ITO index of the same type of sample in the true kinship index item showed a decreasing trend. ITO index is an important statistical means to identify the kinship between two individuals, according to which the ITO index can accurately determine the kinship between individuals, which has high application value. MT index is not 0 to identify relatives as MT, PO index is an important indicator to distinguish between relatives as PO and FS. The critical values of ITO index discriminant values for UI and HS need to be further studied.

Competitive binding of transcription factors underlies flexibility of T peripheral helper cells and T follicular helper cells in SLE.

OBJECTIVE: Peripheral helper T (Tph) cells interact with B cells and promote immune responses at sites of ectopic lymphoid structures (ELSs). To assess the characteristics of Tph cells, we investigated the phenotype of T helper (Th) cells in patients with SLE and the underlying competitive binding mechanisms using cytokine-mediated signal transducer and activator of transcription (STAT) factors. METHODS: Peripheral blood mononuclear cells from SLE patients and healthy controls were analysed for phenotypic identification. Serum cytokine levels were detected using Luminex assays. In vitro culture was performed to assess cytokine-induced conversion of phenotypes and transcriptional regulation using flow cytometry and PCR. Chromatin immunoprecipitation was used to evaluate STAT binding and histone modifications. RESULTS: CXCR5-PD-1+Tph-like cells were increased in SLE patients and showed strong association with disease activity and renal involvement. Serum IFN-α levels were increased and associated with Tph frequency. IFN-α promoted the differentiation of IL-10-producing CXCR5-PD-1+Tph-like cells, increased the responsiveness of IL-2 and induced the conversion of Tfh-like cells to Tph-like cells. STAT5 gained a competitive advantage and bound to the BCL6 locus at the expense of STAT1, accompanied by suppression of H3K4me3. Finally, anti-IFNAR1 decreased the differentiation of Tph-like cells, thereby suppressing the generation of CD38highCD27highplasmablasts. CONCLUSION: Tph cells might be crucial makers to effectively reflect disease activity level in SLE patients. The finding that synergy of IFN-α and IL-2 increases Tph cells through competitive transcriptional regulation could be one of the mechanisms responsible for pathological formation of ELSs and helpful for selection of individualized therapeutic approaches for SLE.