Objective:To explore the effect of microRNA-101 on apoptosis of condylar cartilage cells and the specific mechanism of molecular biology. Methods: IL-1 was used to stimulate and establish the model of apoptosis of condylar cartilage cells. The expression change of miR-101 in control group was compared with that in IL-1 stimulation group by qRT-PCR. Overexpression and down-regulation models of miR-101 were established by transfecting Mimics and Inhibitor and verified by qRT-PCR. Flow cytometry was used to detect the effect of miR-101 overexpression and down-regulation on apoptosis. Target gene of miR-101 was analyzed and calculated through bioinformatics. Western blot and Luciferase report assay were used to detect whether Sox9 could become the target gene of miR-101. Results:qRT-PCR results showed that IL-1 stimulation could cause the increase of miR-101 expression. After the transfection of rabbit condylar cartilage cells by Mimics and Inhibitor, qRT-PCR results confirmed the significant effect of miR-101 overexpression and down-regulation. It was confirmed by flow cytometry that overexpression of miR-101 could promote the apoptosis of condylar cartilage cells, and down-regulation of miR-101 could reduce the apoptosis. It was confirmed by Western blot and Luciferase report assay that Sox9 was the target gene of miR-101, and miR-101 inhibited SOX9 expression through complementary pairing with 3’UTR of Sox9 mRNA. Conclusions:miR-101 can promote the apoptosis of condylar cartilage cells through inhibiting the protein level of target gene SOX9.

Objective:To investigate the effects of different lipid-lowering regimens on blood lipids, endothelial function and safety in patients with unstable angina.Methods:Patients who admitted to Henan Provincial People's Hospital for unstable angina from September 2018 to May 2019 were randomly (random number) divided into the conventional treatment group, intensive statin group and intensive lipid-lowering group. Follow-up was performed at 1, 3, and 6 months after treatment according to the predetermined lipid-lowering regimen. Assessments included lipid profile, liver function, muscle enzymes, hypersensitive C-reactive protein (hs-CRP), endothelial function (reactive hyperemia index, RHI), ischemic events, myalgia, and discontinuation. The differences of the follow-up indicators among the three groups were analyzed.Results:A total of 375 patients were enrolled and randomly divided into three groups, 125 patients in each group. There were no significant differences in demographic data and medication among the three groups. At the 1st month, the low density lipoprotein cholesterin (LDL-C) compliance rate of the intensive statin group was significantly higher than those in the conventional treatment group ( χ2=3.939, P=0.047) and the intensive lipid-lowering group ( χ2=4.63, P=0.031). At the 3rd month, the reductions of LDL-C in the intensive statin group and the intensive lipid-lowering group were significantly better than that in the conventional treatment group( P<0.01). At the 6th month, the reduction rate of LDL-C in the intensive lipid-lowering group was higher than that in the intensive statin group ( q=4.332, P<0.01). At the 1st month, the improvement of hs-CRP and RHI in the intensive statin group was significantly better than that in the conventional treatment group( q=4.133, P<0.05). From the 3rd month of treatment, the incidence of cardiovascular events in the intensive statin group and the intensive lipid-lowering group showed a tendency to decrease compared with the conventional treatment group, but no statistically significant difference was found. At the 6th months of treatment, the withdrawal rates were significantly higher in the intensive statin group and the intensive lipid-lowering group than that in the conventional treatment group (χ 2=4.488, P=0.03 and χ2=5.039, P=0.02). There were no significant differences in the ratio of liver enzyme and muscle enzyme elevation and the incidence of myalgia among the three groups (all P>0.05). Conclusions:Intensive statin therapy can make LDL-C reach the standard in patients with unstable angina pectoris as soon as possible, significantly improve inflammation indicators and endothelial function, and has good safety.

Objective To evaluate the quantity and quality of graphs and tables in medical literature.Methods We conducted a retrospective survey of 750 randomly selected original research articles,from 2011-2015 issues of 5 academic medical journals by using a stratified random sampling method.Paper characteristics,application status,quantity and quality of graphs and tables were analyzed.Results More than 48％ of original research articles contained at least 1 table or graph.The highest frequency of using table and graph was in clinical research.The number of tables and the number of articles with tables were both significantly decreased during 2011-2015 (P=0.034).The most common errors in tables were the inconsistent decimal number and the presentation of numeric data without right alignment.Only 12％ of the articles contained at least 1 graph.Ofthe 175 graphs,bar chart with intervals predominated.Compared with other domains,the completeness of graphs was excellence.Conclusions The result expression in medical research is still dominated by tables.And the quality of graphs is much better than tables.

Objective: To investigate the distribution of fimA and kgp genotypes as well as the common genotype combination of Porphyromonas gingivalis (Pg) in infected root canals of primary apical periodontitis for virulent isolates screening in future. Methods: Thirty-four samples harboring Pg were selected from infected root canals of primary apical periodontitis from patients of the Department of Endodontics, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine from June 2013 to September 2015. FimA type-specific primers were used to amplify the samples, revealing the distribution of various fimA genotypes. The genotypes of kgp were obtained by using Mse Ⅰ restriction endonuclease. The prevalence of each genotype and common genotype combinations were then calculated. Pearson's chi-squared test was performed to analyze the correlation between genotype combinations and clinical symptoms and major signs of apical periodontitis. In addition, the bioflim architectures between Pg isolates with different fimA and kgp genotype combinations were observed compared using confocal laser scanning microscope. Results: Among the 34 Pg-positive samples, fimA Ⅱ was the most prevalent genotype [47% (16/34)] followed by fimA Ⅰ [26% (9/34)], while fimA Ⅴ was detected in only one sample. The prevalence of kgp Ⅰ [56% (19/34)] was slightly higher than that of kgp Ⅱ [44% (15/34)]. Both fimA Ⅱ+kgp Ⅰ and fimAⅡ+kgp Ⅱ were the most prevalent genotype combinations [24% (8/34) each]. No significant correlation was found between specific genotype combination and such major clinical manifestations as gingival swelling and sinus tract of dental origin (P>0.05). Three Pg isolates with different genotype combinations were acquired. Isolate A (fimAⅠ+kgpⅠ) formed densest biofilm, while the biofilm of isolate C (fimAⅤ+kgp Ⅰ) was much looser. The biofilm feature of isolate B (fimAⅢ+kgp Ⅱ) fell in between A and C. Conclusions Pg with fimA Ⅱ was most frequently detected in infected root canals of primary apical periodontitis. The prevalence of Pg with kgp Ⅰ was slightly higher than that with kgp Ⅱ, and fimAⅡ+kgp Ⅰ as well as fimA Ⅱ+kgp Ⅱ were the commonest genotype combinations. According to the comparison of Pg biofilms formed by clinical isolates, it might be possible that different genotype combinations may lead to distinct biofilm architectures.

Objective: To evaluate the effect of 3D-printed oval root canal preparation by using small field-of-view cone beam CT (CBCT) combined with computer-aided technologies. Methods: An extracted tooth with a suitable single oval canal was selected by small field-of-view CBCT scanning. Three-dimensional (3D)-printed resin teeth were obtained based on the CBCT data after data conversion and processing. 50 general dentists were selected to prepare the oval root canal of the resin teeth with X-Gold rotary Ni-Ti instruments. Small field-of-view CBCT was applied to scan the oval root canals before and after preparation. Then, computer-aided technologies were used to calculate and compare these CBCT data, analyzing the effects of oval root canal cleaning as well as the root canal deviation by 3D reconstruction and rendering of the images. Results : Among the 50 cases, the mean unprepared area of the oval root canal wall was（56.20 ± 11.91）% and the mean maximum deviation distance of the root canal was（0.140 ± 0.041）mm. There was no correlation between root canal cleanliness and deviation (r=0.18, P=0.212). Conclusion Combined with small field-of-view CBCT and computer-aided technology, we can effectively quantitatively evaluate the root canal preparation effect.

A fundamental challenge that arises in biomedicine is the need to characterize compounds in a relevant cellular context in order to reveal potential on-target or off-target effects. Recently, the fast accumulation of gene transcriptional profiling data provides us an unprecedented opportunity to explore the protein targets of chemical compounds from the perspective of cell transcriptomics and RNA biology. Here, we propose a novel Siamese spectral-based graph convolutional network (SSGCN) model for inferring the protein targets of chemical compounds from gene transcriptional profiles. Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets, and the biological networks under different experiment conditions further complicate the situation, the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles. On a benchmark set and a large time-split validation dataset, the model achieved higher target inference accuracy as compared to previous methods such as Connectivity Map. Further experimental validations of prediction results highlight the practical usefulness of SSGCN in either inferring the interacting targets of compound, or reversely, in finding novel inhibitors of a given target of interest.
Drug Delivery Systems ; Proteins ; Transcriptome

Digital guided therapy (DGT) has been advocated as a contemporary computer-aided technique for treating endodontic diseases in recent decades. The concept of DGT for endodontic diseases is categorized into static guided endodontics (SGE), necessitating a meticulously designed template, and dynamic guided endodontics (DGE), which utilizes an optical triangulation tracking system. Based on cone-beam computed tomography (CBCT) images superimposed with or without oral scan (OS) data, a virtual template is crafted through software and subsequently translated into a 3-dimensional (3D) printing for SGE, while the system guides the drilling path with a real-time navigation in DGE. DGT was reported to resolve a series of challenging endodontic cases, including teeth with pulp obliteration, teeth with anatomical abnormalities, teeth requiring retreatment, posterior teeth needing endodontic microsurgery, and tooth autotransplantation. Case reports and basic researches all demonstrate that DGT stand as a precise, time-saving, and minimally invasive approach in contrast to conventional freehand method. This expert consensus mainly introduces the case selection, general workflow, evaluation, and impact factor of DGT, which could provide an alternative working strategy in endodontic treatment.
Humans ; Consensus ; Endodontics/methods* ; Tooth ; Printing, Three-Dimensional ; Dental Care ; Cone-Beam Computed Tomography ; Root Canal Therapy