China ; Equipment Safety ; Equipment and Supplies ; Safety Management

During the practice of supervision and management of medical device in different countries, the strict regulatory and needs of the program by the regulations is to be determined by the risk level of the medical equipment. This paper briefly describes the regulatory requirements of the United States to enter the market for high-risk medical device.
Device Approval ; legislation & jurisprudence ; Equipment Safety ; United States

Objective:To investigate the regulation and mechanism of chronic Trichinella spiralis ( Ts) infection on liver immunopathology in mice co-infected with Plasmodium berghei ANKA( PbA). Methods:According to body weight, 64 specific pathogen free female Kunming mice (6 - 8 weeks old, weighting 22 - 25 g) were divided into 4 groups by using random number table method. Control group: uninfected; Ts group: mice were mono-infected with 30 Ts larvae by oral gavage on day 0; PbA group: mice were mono-infected with 1 × 10 6PbA-infected red blood cells in 0.1 ml of phosphate buffer (PBS) administered by intraperitoneal injection on day 121; co-infected ( Ts+PbA) group: mice were infected with 30 Ts larvae by oral gavage and intraperitoneal injected with 1 × 10 6PbA-infected red blood cells in 0.1 ml PBS on day 121 after Ts infection. There were 16 mice in each group, in which 10 mice in each group were monitored for the survival rate. The peripheral red blood cell parasitemia of PbA group and Ts + PbA group were monitored every other day by light microscope examination of Giemsa-stained thin tail-blood smears from day 3 after PbA infection. Mice were sacrificed at day 135 after Ts infection and/or at day 15 after PbA infection, the mouse body weight and liver weight were measured, and the liver index were calculated. Ts-infected mice were monitored by a light microscope examination of diaphragm compression slide. Under a light microscope, the liver pathology and liver fibrosis of mice were observed and compared with hematoxylin-eosin (HE) staining and Sirius red staining, respectively. The F4/80 + Kupffer cells in liver of mice were examined by immunohistochemical staining. Results:After infection with Ts or PbA, Ts larvae cysts were observed in diaphragm tissues and PbA were observed in red blood cells under the light microscope. After PbA infection, there was no significant difference in survival rate between PbA group and Ts+ PbA group ( P > 0.05). Compared with PbA group, the peripheral red blood cell parasitemia was significantly decreased in Ts+ PbA group on days 11 and 15 after PbA infection (%: 27.104 ± 7.623 vs 45.032 ± 9.849, 60.218 ± 2.776 vs 76.778 ± 6.351, P < 0.05), and the liver index and the liver pathology score were significantly decreased in Ts+ PbA group ( P < 0.05). Sirius red staining showed that the positive area of liver fibrosis in Ts+ PbA group was significantly higher than that in PbA group ( P < 0.05). Immunohistochemical staining showed that the average optical density value of F4/80 + Kupffer cells in Ts+ PbA group was significantly higher than that in PbA group ( P < 0.01). Conclusion:Chronic Ts infection may reduce the peripheral red blood cell parasitemia, increase F4/80 + Kupffer cells expression in liver, and attenuate liver pathology in mice co-infected with PbA.

Parasitic diseases still remain the world's greatest health problems and cause huge economic burden in poor areas. The drugs currently used to treat protozoiases and helminthiases have certain defects, and it is urgent to develop more effective therapeutic drugs for these diseases. Berberine is one kind of important anti-inflammatory agents originally derived from Coptis rhizoma. The derivatives of berberine are obtained by modifying the structural site of berberine. In addition to its anti-inflammatory and anti-microbial activities, berberine and its derivatives also have significant anti-parasitic activity. In this paper, we summarized recent progress in the use of berberine and its derivatives against the infections of protozoa ( Leishmania spp ., Trypanosoma spp. , Toxoplasma gondii, Plasmodium falciparum, and Eimeria tenella) and helminths ( Schistosoma mansoni, Schistosoma. japonicum, Echinococcus granulosus, and Toxocara canis), which may providea useful reference for researchers in this field.

Objective:To screen key genes that co-regulate immune and mitochondrial energy metabolism through bioinformatics methods and to investigate the relationship between the key genes and immune infiltration.Methods:A total of 671 glioma samples (the tumor group) and 5 non-tumor brain tissue samples (the control group) were collected from the Cancer Genome Atlas (TCGA) database on November 13, 2023. Through a comprehensive search of the GeneCards database and immune-related genes (IRG) and mitochondrial energy metabolism-related genes (MEMRG) in previous published literatures, 76 IRG and MEMRG (IR & MEMRG) were obtained by taking the intersection of IRG and MEMRG after merging and deduplicating. The limma package in R software was used to screen the differentially expressed genes (DEG) between the tumor group and the control group. Then, immune-related & mitochondrial energy metabolism-related differentially expressed genes (IR&MEMRDEG) were obtained by intersecting with IR & MEMRG. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the IR&MEMRDEG through the clusterProfiler package in R software. The STRINGv12.0 online database (https://cn.string-db.org/) was employed to construct a protein interaction network based on IR&MEMRDEG and to identify the top 5 key core genes. Single-sample gene-set enrichment analysis (ssGSEA) was used to determine the relative abundance of immune cell infiltration in all samples, and the immune cell infiltration matrices for both the tumor and the control groups were acquired. The expression differences in infiltration abundance of the immune cells in the tumor group and the control group were analyzing by using the ggplot2 package in R software. The heat map was drawn by utilizing the R software pheatmap package to show self-correlation of immune cells. The correlation between the top 5 key genes in the protein interaction network and immune cells was calculated by using the Spearman algorithm and the R software ggplot2 package.Results:A total of 3 623 DEGs were identified from the TCGA database in both groups, including 1 711 up-regulated genes and 1 912 down-regulated genes. After taking the intersection of DEG and IR&MEMRG, 11 IR&MEMRDEG were obtained including EIF4EBP1, TP53, IDH1, PRCKZ, CD200, GPI, PGM2, PKLR, AK2, ATP4A, and ALDH3B1. GO enrichment analysis results showed that 11 IR&MEMRDEG were mainly enriched in ADP metabolic process, ATP metabolic process, purine nucleoside diphosphate metabolic process, purine ribonucleoside diphosphate metabolic process, and ribonucleoside diphosphate metabolic process at the biological level; in the fibronectin-1 rich granule, secretory granule lumen, cytoplasmic vesiclelumen, vesiclelumen, and nuclear matrix at the cellular component level; in magnesium ion binding, potassium ion binding, and alkali metal ion binding at the molecular functional level. The KEGG enrichment analysis results showed that 11 IR&MEMRDEGs were mainly enriched in glycolysis/gluconeogenesis, carbon metabolism, insulin signaling pathway, pentose phosphate pathway, starch and sucrose metabolism signaling pathways. The protein interaction network analysis from the STRING database revealed that 5 highest scoring core proteins were identified, namely EIF4EBP1, TP53, IDH1, PRKCZ, and AK2.The immune infiltration abundances of 28 immune cells were calculated by using the ssGSEA algorithm. The infiltration abundance of 15 immune cells in the tumor group was higher than that in the control group, and the differences were statistically significant (all P < 0.05). The findings from the immune infiltration analysis indicated a positive correlation among 15 types of immune cells, in which there was a strongest correlation between effector memory CD8 + T cell and myeloid derived suppressor cells. EIF4EBP1, TP53, IDH1, and AK2 exhibited a positive correlation with a large number of immune cells (all P < 0.05), whereas PRKCZ demonstrated a negative correlation with more immune cells (all P < 0.05). Conclusions:PRKCZ, AK2, and EIF4EBP1 have the potential to be the new targets of immunotherapy for gliomas.