Syncope is a clinical symptom for many kinds of diseases.The reasons for some syncope are still not clear even after a comprehensive and systematic examination,known as unexplained syncope.The clinical data of one patient with recurrent syncope,who had received the implanted loop recorder (ILR) in Xiangya Hospital,Central South University,were retrospectively analyzed.The instrument recorded the first syncope at a time of recurrence for the sustained ventricular tachycardia in 704 days after ILR.The patient was thus diagnosed as arrhythmic syncope and received an operation with implantable cardioverter defibrillator.The ILR is a new type of examination device for patients suffering from syncope with suspected cardiac rhythm due to its long monitoring time,low infection rate and high safety.It possesses high clinical value in the diagnosis of patients with arrhythmic syncope.

Objective:To evaluate the efficacy and safety of dienogest (DNG) in the treatment of refractory endometriosis-associated pain (REAP).Methods:In this study, REAP was defined according to the following criteria: (1) the pain duration was ≥12 months and visual analogue scale (VAS)≥60 mm; (2) the previous treatments with over two medicines like oral contraceptives and levonorgestrel-releasing intrauterine system failed to achieve satisfactory relief of pain, with VAS reduction less than 50%; with gonadotropin-releasing hormone agonist or mifepristone, the pain could be controlled temporarily, but it recurred after discontinuation of medicines; (3) the pain could not be relieved by surgery or even repeated surgeries. In the present study, 48 patients with REAP were treated with DNG 2 mg/day orally and the clinical outcomes were retrospectively analyzed. The VAS scores, levels of CA 125, estradiol, FSH, LH and changes in the size of endometriotic lesions before and after treatment were compared respectively. The side effects were also analyzed. Results:The average duration of DNG treatment was (20.1±12.8) months. After 3 months of medication, the VAS score was significantly reduced from (77.9±15.8) mm to (20.8±10.7) mm ( P<0.01), and CA 125 level was significantly reduced from (95±139) kU/L to (38±45) kU/L ( P<0.05). The effects were maintained with continuation of DNG treatment. Endometriotic lesions tended to shrink, after 12 months of DNG treatment, the size of ovarian endometriomas was reduced significantly from (3.1±1.0) cm to (1.9±1.2) cm ( P<0.05). The mean level of estradiol was maintained at 124.82-221.04 pmol/L and levels of FSH and LH did not change significantly during the treatment. The major side effect was irregular bleeding (75%, 36/48). Conclusions:DNG could effectively relieve REAP and is a well-tolerated therapy. It may supply an alternative option for patients with REAP.

Objective:To construct a chronic obstructive pulmonary disease (COPD) assessment test (CAT) score prediction model based on a deep network fused with air data, and to explore its significance.Methods:From February 2015 to December 2017, the outdoor environmental monitoring air data near the residential area of the patients with COPD from the Respiratory Outpatient Clinics of Peking University Third Hospital, Peking University People′s Hospital and Beijing Jishuitan Hospital were collected and the daily air pollution exposure of patients was calculated. The daily CAT scores were recorded continuously. The CAT score of the patients in the next week was predicted by fusing the time series algorithm and neural network to establish a model, and the prediction accuracy of the model was compared with that of the long short-term memory model (LSTM), the LSTM-attention model and the autoregressive integrated moving average model (ARIMA).Results:A total of 47 patients with COPD were enrolled and followed up for an average of 381.60 days. The LSTM-convolutional neural networks (CNN)-autoregression (AR) model was constructed by using the collected air data and CAT score, and the root mean square error of the model was 0.85, and the mean absolute error was 0.71. Compared with LSTM, LSTM-attention and ARIMA, the average prediction accuracy was improved by 21.69%.Conclusion:Based on the air data in the environment of COPD patients, the fusion deep network model can predict the CAT score of COPD patients more accurately.

Objective:To explore the application effect and evaluation of virtual reality technology in oral implant therapy training.Methods:In November 2018, one adult patient (female, 36 years old) with missing right mandibular first molar was treated in the Department of Implantology, School and Hospital of Stomatology, Fujian Medical University. The three-dimensional virtual models of mandible and implant surgery tools were established, and the virtual reality software (Unity 3D 5.5.1) was imported. Combined with the virtual reality head mounted display, a virtual reality training system simulating the dental implant treatment process was independently developed. Ten refresher doctors and 20 graduate students in Department of Implantology, School and Hospital of Stomatology, Fujian Medical University from September 2018 to December 2019 were recruited as the experimental objects (no clinical experience was found). According to the level and seniority of doctors, they were randomly divided into virtual training group and conventional training control group, which made the two groups comparable, with 15 in each group. Subjective scores (including anatomical structure, surgical field of vision, cavity preparation, implant placement and process mastery) were given after the corresponding training in the two groups, and the virtual reality training system was used to test. The mesial and distal direction, buccolingual direction, depth and angle deviation of implants before and after the training were analyzed, and the differences between the two groups were compared.Results:The subjective scores of five dimensions in the virtual training group were significantly higher than those in the conventional training control group ( P<0.05). In the virtual training group, the mesial and distal, buccolingual, depth and angle deviation of implants were (0.73±0.33), (0.78±0.41), (0.61±0.32) mm and 6.66°±3.87°. All of them were significantly lower than those in the control group [(0.85±0.32), (1.12±0.38), (0.89±0.24) mm and 9.68°±3.74°] ( P<0.05). Conclusions:The self-developed virtual reality system of oral implant has good application effect, good operability and predictability. It can be effectively carried out in implant education and training, and it can strengthen skills of doctors, and is conducive to the practical operation.

Objective: To investigate the effect of activation of the stimulator of interferon genes(STING) pathway on macrophage polarization function and its role in T-cell response. Methods: Mouse macrophage RAW264.7 cells were used.STING signaling related proteins in RAW264.7 macrophage treated with STING agonist diABZI were analyzed by Western blot,including TANK-binding kinase-1(TBK1),interferon regulatory factor-3(IRF3),STING,p-TBK1,p-IRF3,p-STING.The polarization of macrophage RAW264.7 cells treated with diABZI was analyzed by flow cytometry.Co-culture of diABZI-treated RAW264.7 macrophage and T cells was applied to evaluate the change of T cell response. Results: STING signaling related proteins were upregulated in macrophage RAW264.7 cells treated with diABZI for 3 hours.The expression of CD86 was upregulated on the surface of macrophages after 12 hours of diABZI treatment,and the CD86/CD206 ratio was elevated,which presented the M1 polarization phenotype.When coculturing diABZI-treated macrophage RAW264.7 cells with T cells,the cytokine secretion ability of T cells including CD4+T and CD8+T cells was enhanced and the expression of CD107a in CD8+T cells was upregulated. Conclusion STING signaling induces M1 polarization of macrophages which enhance the function of T cells,especially CD8+T cell immune response.