Objective:To explore the molecular mechanism of fluoride toxicity to ameloblasts.Methods:Mouse ameloblast cell line (LS8 cells) was taken and divided into control group [0.0 mmol/L sodium fluoride (NaF)] and fluoride exposed group (1.6 mmol/L NaF) according to the final concentration of NaF. Transcriptome sequencing was performed to screen differentially expressed genes (DEGs), and gene ontology (GO) analysis and gene set enrichment analysis (GSEA) were performed on DEGs. The STRING database was used to construct the protein-protein interaction (PPI) network of DEGs, and Cytoscape 3.8.0 software was used to visualize the PPI network to screen key modules and key genes. At the same time, real-time fluorescence quantitative PCR was used to detect the mRNA expression level of key genes, and the key genes were verified by gene expression database (GEO database).Results:Compared with the control group, there were 709 DEGs in the fluoride exposed group, including 223 up-regulated genes and 486 down-regulated genes. The GO analysis of DEGs mainly involved molecular functions such as receptor-ligand activity, cell adhesion molecule binding, structural components of extracellular matrix, cellular components such as collagen of extracellular matrix, receptor complex, membrane raft, biological processes such as external packaging structure organization, extracellular structure organization, and extracellular matrix organization. The GSEA of the whole gene set found that the interleukin-17 (IL-17) signaling pathway, ribosome biogenesis in eukaryotes, and the nuclear factor kappa-B (NF-κB) signaling pathway were activated, while fatty acid degradation, pyruvate metabolism and fatty acid metabolism were inhibited. After constructing PPI network, three key modules and four key genes [typeⅠcollagen α1 (Col1a1), typeⅠcollagen α2 (Col1a2), typeⅤcollagen α1 (Col5a1) and fibrinogen 1 (Fbn1)] were obtained. Compared with the control group, the mRNA expression levels of Col1a1, Col1a2, Col5a1 and Fbn1 in LS8 cells of the fluoride exposed group were significantly decreased ( P < 0.05), which was consistent with the change trend of gene expression in the GEO database. Conclusion:Key genes such as Col1a1, Col1a2, Col5a1, Fbn1, and signaling pathways such as IL-17 and NF-κB, which are screened by bioinformatics method, may be closely related to the toxic effects of fluoride on ameloblasts.

Purpose To explore the diagnostic value of beak sign in fetal annular pancreas by analyzing the ultrasonographic features of fetal annular pancreas.Materials and Methods The ultrasound images and clinical data of 13 cases of fetal annular pancreas diagnosed by prenatal ultrasound in Shandong Provincial Maternal and Child Health Hospital from September 2019 to December 2021 and confirmed by surgery after birth were retrospectively analyzed.The degree of duodenal stenosis at the obstruction site was observed,especially whether the angle formed by the intestinal wall could identify the fetal annular pancreas,and the ultrasonic characteristics were summarized and analyzed.Results A total of 13 fetuses with annular pancreas showed double bubble sign,3 cases showed clamp sign,and 7 cases showed beak sign at the end of duodenal dilatation.All the 13 cases underwent surgical treatment after birth,including 2 cases with duodenal atresia and 1 case with atypical intestinal malrotation.All the children had good prognosis after operation.Conclusion By observing the dilated end of duodenum and the relationship with pancreatic head,prenatal ultrasound combined with beak sign and double bubble sign could improve the diagnostic accuracy of fetal annular pancreas,which has significant value in prenatal diagnosis of fetal annular pancreas.

Objective:To establish autoverification rules for coagulation tests in multicenter cooperative units, in order to reduce workload for manual review of suspected results and shorten turnaround time (TAT) of test reports, while ensure the accuracy of results.Methods:A total of 14 394 blood samples were collected from fourteen hospitals during December 2019 to March 2020. These samples included: Rules Establishment Group 11 230 cases, including 1 182 cases for Delta check rules; Rules Validation Group 3 164 cases, including 487cases for Delta check; Clinical Application Trial Group 77 269 cases. Samples were analyzed for coagulation tests using Sysmex CS series automatic coagulation analyzers, and the clinical information, instrument parameters, test results, clinical diagnosis, medication history of anticoagulant and other relative results such as HCT, TG, TBIL, DBIL were summarized; on the basis of historical data, the 2.5 and 97.5 percentile of all data arranged from low to high were initially accumulated; on the basis of clinical suggestions, critical values and specific drug use as well as relative guidelines, autoverification rules and limits were established.The rules were then input into middleware, in which Stage I/Stage II validation was done. Positive coincidence, negative coincidence, false negative, false positive, autoverification pass rate, passing accuracy (coincidence of autoverification and manual verification) were calculated. Autoverification rules underwent trial application in coagulation results reports.Results:(1) The autoverification algorisms involve 33 rules regarding PT/INR, APTT, FBG, D-dimer, FDP,Delta check, reaction curve and sample abnormalities; (2)Autoverification Establishment Group showed autoverification pass rate was 68.42% (7 684/11 230), the false negative rate was 0%(0/11230), coincidence of autoverification and manual verification was 98.51%(11 063/11 230), in which positive coincidence and negative coincidence were respectively 30.09% (3 379/11 230) and 68.42%(7 684/11 230); Autoverification Validation Group showed autoverification pass rate was 60.37%(1 910/3 164), the false negative rate was 0%(0/11 230), coincidence of autoverification and manual verification was 97.79%(3 094/3 164), in which positive coincidence and negative coincidence were respectively 37.42%(1 184/3 164) and 60.37%(1 910/3 164); (3) Trialed implementation of these autoverification rules on 77 269 coagulation samples showed that the average TAT shortened by 8.5 min-83.1 min.Conclusions:This study established 33 autoverification rules in coagulation tests. Validation showedthese rules could ensure test quality while shortening TAT and lighten manual workload.