Abstract:Pathological diagnosis is the gold standard of tumor diagnosis and the cornerstone of clinical treatment. Artificial intelligence (AI) has made significant progress in detecting tumor tissues and tumor cells, which contributes to accurately, efficiently and quantitatively identifying tumor cells and/or tumor characteristics, leading to improved efficiency of pathologists and making up for the shortage of pathologists. The premise of pathological AI is efficient and accurate labeling, which is to outline the tumor cells of various types and different degrees of differentiation. To promote the standardization and data quality control of labeling, experts of oncology, pathology, electronic information science and other fields jointly discussed the pathological data set construction and data quality control for solid tumor, and thus an expert group was formed for a future expert consensus. Our group is dedicated to the construction of the AI-based standardized pathological data set for solid tumor. This paper introduces the primary opinions reached by our group in the process of tumor cell labeling from multiple aspects, including specimen source, labeling team, labeling rules, labeling process, quality control, and solutions for difficult cases.

Abstract:Basal cell carcinoma (BCC) is one of the most common skin tumors. Dermatologists can make a preliminary diagnosis according to the location and characteristic appearance of the lesions, make a probable diagnosis through analyzing the images by dermoscopy and other non-invasive examination methods, and make a final definite diagnosis by combining histopathology with clinical data. In recent years, with the development of artificial intelligence (AI), it is available to use machine vision for automatic image recognition and analysis. Computer-aided diagnosis system can establish artificial neural network by deep learning great clinical, dermoscopic and histopathological picture data to assist professional physicians to make analysis and judgment on difficult diseases. This is helpful for early diagnosis of skin tumor, elevation the diagnosis capability of junior doctors, and workload reduction of pathologists. Here we reviewed the research progresses of diagnosis and treatment of BCC in AI field at home and abroad.

Abstract:Since the advent of artificial intelligence (AI), remarkable achievements have been made in many research fields and industries, which greatly promote the development of medical ultrasound imaging, which is highly dependent on machine manipulation and massive data analysis. At present, the development of AI in the field of ultrasound medicine is a new focus of the cross-research of medical-industrial integration. More and more medical ultrasound experts, mathematicians and computer scientists are working together to promote the integration of ultrasound medicine and AI, so as to improve the accuracy of ultrasound diagnosis, reduce misdiagnosis rate, shorten reporting time and meet the growing clinical needs. In this review, we summarized the advances on ultrasound medicine in the field of AI, and the opportunities and challenges in the development of ultrasound medicine in China in the era of AI.

Abstract:Objective To construct a gastroscopic image recognition model based on transfer learning and to explore its diagnostic value for gastric cancer. Methods The clear white-light gastroscopic images from 2 001 gastric cancer patients, 2 119 gastric ulcer patients and 2 168 chronic gastritis patients were collected. All these images were divided into training set image group (1 851 gastric cancer, 1 969 gastric ulcer, and 2 018 chronic gastritis) and testing set image group (150 gastric cancer, 150 gastric ulcer, and 150 chronic gastritis). Champion models VGG19, ResNet50 and Inception-V3 in ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) competition were used as pre-trained models. These models were revised for model training. The training set images were assigned to train the above 3 models, and the testing set images were assigned to validate the models. The whole training process was divided into 2 steps (pre-training and finetuning). Results It was found that ResNet50 ranked No.1 in terms of testing accuracy. Its diagnostic accuracy for gastric cancer, gastric ulcer and chronic gastritis reached 93%, 92% and 88%, respectively. Conclusion Based on transfer learning, the gastroscopic image recognition software model constructed by ResNet50 model can more accurately differentiate gastric cancer from benign gastric diseases (gastric ulcer and chronic gastritis).

Abstract:Objective To propose a learning model based on least square support vector machine (LSSVM) algorithm to improve the accuracy and efficiency for predicting clinical blood pressure data of traditional Chinese medicine (TCM). Methods The LSSVM learning model was used to predict the clinical blood pressure of TCM. By replacing the inequality constraints of support vector machine with LSSVM equality constraints, the quadratic programming problem was transformed into a linear equation solution problem to reduce computational complexity and speed up algorithm convergence. The clinical pulse diagram parameters and blood pressure data of 320 patients were collected. Three hundred of them were used as training samples, the remaining 20 samples were used as test data. The LSSVM learning model was used to predict blood pressure data according to the pulse diagram parameters of the patients. Results Experimental results showed that the LSSVM learning model had high prediction accuracy for blood pressure data. The LSSVM learning model based on polynomial kernel function had better learning and prediction abilities than the LSSVM learning model based on radial basis kernel function. The mean prediction errors of systolic blood pressure, diastolic blood pressure and mean arterial pressure obtained by the LSSVM learning model based on polynomial kernel function were 7.88%, 8.40% and 6.67%, respectively, which were lower than those obtained by the LSSVM learning model based on radial basis kernel function (7.95%, 9.70% and 7.48%, respectively). Conclusion The LSSVM learning model proposed in this experiment can be used to predict the blood pressure data of patients only by the clinical pulse diagram parameters, and is a good reference for clinical diagnosis of TCM.

Abstract:Objective To propose a conditional random field (CRF) model based on the new word segmentation method Re-entity, and to compare with bi-directional long short-term memory neural network (BiLSTM)-CRF and Lattice-long short-term memory neural network (LSTM). Methods After analyzing the existing entity recognition methods, we proposed CRF method based on Re-entity, BiLSTM-CRF and Lattice-LSTM for the China Conference on Knowledge Graph and Semantic Computing in 2018 (CCKS2018) task one:Chinese clinical named entity recognition, and trained character vector sets at different parameter levels based on different corpora. The comparative experiments on model performance were carried out in the different neural network models for each methods. Finally, the comparative study was carried out based on different input lengths such as the sentence level and the text level. Results Re-entity method can improve the performance of CRF model. Lattice-LSTM model based on sentence level achieved a strict F1-measure of 89.75% on this task, which was higher than the highest F1-measure (89.25%) on the task one of CCKS2018. Conclusion The CRF model based on Re-entity can effectively improve the recognition rate of traditional Chinese medicines in electronic medical records by using normalized Chinese clinical drug. Re-entity method can improve the error accumulation caused by word segmentation in data preprocessing. Lattice structure can better combine the latent semantic information of characters and word sequences. At the same time, sentence-level input can effectively improve the recognition accuracy of neural network models.

Abstract:Objective To propose a point and line (PL)-simultaneous localization and mapping (SLAM) algorithm and to compare it with oriented FAST and rotated BRIEF (ORB)-SLAM2, so as to improve the global localization accuracy and real-time performance of SLAM algorithm for medical service robots. Methods The PL-SLAM algorithm added line features based on point feature in the process of feature extraction, and carried out mapping and global localization in the complex medical environment according to the point and line features after fusion. The public datasets (EuRoc and KITTI) were used to compare the PL-SLAM and ORB-SLAM2 algorithms, and the comprehensive performance of autonomous navigation of the medical service robots was tested. Results Compared with the ORB-SLAM2 algorithm, PL-SLAM algorithm extracted more point and line features in weak texture scenario, and effectively enhanced the global localization accuracy and real-time performance. The rotation error of the PL-SLAM algorithm decreased by 42.2% and the runtime increased by 55.9%. Conclusion PL-SLAM algorithm can effectively improve global localization accuracy and the real-time performance of medical service robots.

Abstract:Objective To explore the role of metabolic detoxification enzyme activity and knockdown resistance (kdr) gene mutations in the pyrethroid resistance of Aedes (Ae.) albopictus. Methods From Aug. to Sep. in 2017, the Ae. albopictus samples were collected in Qianfoshan Park, Jinan City, Shandong Province (JN), Shangmaojiabu, Hangzhou City, Zhejiang Province (HZ), Baoshan Sixth Village, Baoshan District, Shanghai (BS), Gongqing Forest Park, Yangpu District, Shanghai (YP), and Meilan District Residential Area, Haikou City, Hainan Province (HK). The above five field populations were all resistant to insecticide. The activities of metabolic detoxification enzymes (glutathione-S transferase[GST] and mixed function oxidase[MFO]) were detected and compared with the Ae. albopictus susceptible strain (JS). The contribution rates of activity changes of GST and MFO and kdr mutations (I1532 and F1534) in the resistance formation were analyzed by the classification and regression trees (CART). Results The baseline enzyme activities of GST and MFO in Ae. albopictus JS were both significantly higher than those in the BS and HK resistant populations (both P<0.01). There were no significant difference in the activities of GST and MFO between the BS population unexposed and exposed to deltamethrin (P>0.05). After exposure to permethrin of BS population, the activities of GST and MFO were significantly increased (P<0.05, P<0.01). After exposure to deltamethrin, the GST activity was not significantly changed in the HK population (P>0.05), while the MFO activity was significantly increased (P<0.01). However, after exposure to permethrin in the HK population, there were no significant changes in the GST and MFO activities (both P>0.05). In the 5 field resistant populations exposed to deltamethrin and permethrin, the changes of GST and MFO activities were irregular compared with baseline of Ae. albopictus JS strain. CART analysis showed that in the resistance formation of Ae. albopictus against deltamethrin, the contribution rates of GST activity and kdr F1534 mutation were the greatest, followed by MFO activity, and the kdr I1532 mutation was the smallest. In the resistance formation of Ae. albopictus against permethrin, the kdr F1534 mutation had the highest contribution rate, followed by the GST and MFO activities, and the kdr I1532 mutation had no contribution. Conclusion The activity levels of metabolic detoxification enzymes (GST and MFO) are not suitable as single markers for detecting the resistance of Ae. albopictus to pyrethroids. The activity changes of metabolic detoxification enzymes and kdr mutations may be two synergistic mechanisms in the resistance formation of Ae. albopictus to pyrethroid insecticides.

Abstract:Objective To explore the mechanism and biological significance of differentiation of myeloid-derived suppressor cells (MDSCs) mediated by cancer-associated fibroblasts (CAFs) in the pancreatic ductal adenocarcinoma (PDAC), so as to provide theoretical and experimental basis for revealing the roles of CAFs and MDSCs in promoting the progression of pancreatic cancer by remodeling the pancreatic cancer microenvironment. Methods We isolated and purified primary CAFs from PDAC tumor tissues, and screened the up-regulated cytokines in CAFs by quantitative real-time PCR and enzyme-like immunosorbent assay. The human foreskin fibroblasts (HFFs) were used as controls. Human peripheral blood mononuclear cells (PBMCs) were cultured with supernatant of CAFs and HFFs, respectively. The differentiation of PBMCs was observed and the mechanisms of the above cytokines in regulating the differentiation and recruitment of MDSCs were studied. Results The biomarkers (α-smooth muscle actin[α-SMA] and fibroblast activation protein a[FAPa]) were detected in the isolated primary CAFs, but not found in the HFFs. The expression levels of interleukin 6 (IL-6), stromal cell-derived factor 1 (SDF-1) and monocyte chemotactic protein 1 (MCP-1) in the culture supernatant were significantly gradually increased in the CAFs than those in the HFFs (all P<0.01). Compared with culture supernatant of HFFs, the culture supernatant of CAFs promoted more PBMCs to differentiate into CD13-high expression neutrophil-like MDSCs (CD13^hi-nMDSCs; P<0.01). IL-6 human recombinant protein alone in the co-culture system could induce the differentiation of PBMCs into CD13^hi-nMDSCs (P<0.01). SDF-1 or MCP-1 human recombinant protein alone could not induce the increase of CD13^hi-nMDSCs subpopulation. IL-6 neutralizing antibody or signal transducer and activator of transcription 3 (STAT3) blocker FLLL32 could significantly inhibit the differentiation induced by the culture supernatant of CAFs (P<0.05). Conclusion CAFs can promote the differentiation of PBMCs into CD13^hi-nMDSCs via the IL-6/STAT3 pathway.

Abstract:Objective To explore the effect of tissue kallikrein 1 (KLK1) on mitochondrial function after cardiac ischemia/reperfusion (I/R) injury and its mechanism. Methods After KLK1 overexpression by KLK1 recombinant adenovirus infection, the cardiac I/R rat model was established by ligation of left anterior descending coronary artery and reperfusion. The cardiac infarction area and the apoptosis of cardiomyocytes were detected. The mitochondria were isolated from injured myocardial tissues, and mitochondrial functions (mitochondrial superoxide production, membrane potential and ATP production) determined. The neonatal rat cardiomyocytes were isolated and infected with KLK1 recombinant adenovirus to achieve KLK1 overexpression, and then hypoxia/reoxygenation (H/R) cell model was established. The H/R cells were treated with the media containing bradykinin receptor type 1 (B1R) antagonist R715 or bradykinin receptor type 2 (B2R) antagonist HOE140. The cell viability was determined with MTT assay, and the mitochondrial functions were observed. Results In I/R rats, KLK1 overexpression could alleviate the cardiac injury, and decrease infarction area and cell apoptosis (all P<0.01) in cardiac ischemic risk area; moreover, KLK1 overexpression could improve mitochondrial dysfunction, decrease mitochondrial peroxide production, and increase mitochondrial membrane potential and ATP production (all P<0.01). In vitro cardiomyocyte model, KLK1 overexpression could also attenuate cardiomyocyte injury (P<0.01) and mitochondrial dysfunction (P<0.05, P<0.01), which could be inhibited by B2R antagonist HOE140. Conclusion KLK1 mitigates mitochondrial dysfunction after cardiac I/R injury, which may be an important mechanism of its cardioprotective effect.

Abstract:Objective To explore the effect of Neiyi recipe on the reproductive ability of mice with endometriosis (EM) and its mechanisms. Methods The EM mouse model was established and divided into Neiyi recipe group (n=26), gestrinone group (n=25), EM model group (n=26), and sham operation group (n=24). After 15 days of continuous drug intervention, 6 proestrous mice were randomly selected from each group for histomorphological observation. The remaining mice were mated at the ratio of male to female of 4︰1 for 15 days. The pregnancy, endometriosis, pelvic adhesions and follicular development were observed and recorded in the 4 groups. The histomorphology of the liver, kidney and spleen of the mice were observed in each group. The concentrations of IL-2, IL-6 and IL-10 in peritoneal fluid of the mice were detected by enzyme-linked immunosorbent assay. Results The pregnancy rate, volume of lesions and pelvic adhesion of the mice were significantly improved in the Neiyi recipe group compared with the gestrinone group and the EM model group(P<0.05, P<0.01). The ovarian histomorphological observation showed that the follicular development of the mice was better in the Neiyi recipe group than that in the gestrinone group and the EM model group. The mice in the Neiyi recipe group had significantly better outcome in improving follicular development compared with the gestrinone group (P<0.05). Compared with the sham operation group, the levels of IL-2 and IL-6 in the peritoneal fluid of the mice were significantly increased in the EM model group (all P<0.01), and the level of IL-10 was significantly decreased (P<0.05). Compared with the EM model group, the levels of IL-2 in the peritoneal fluid of the mice were significantly decreased in the Neiyi recipe group and the gestrinone group (P<0.01), the level of IL-6 in the peritoneal fluid of the mice was significantly decreased in the gestrinone group (P<0.05) and the level of IL-10 was significantly increased (P<0.01). The pregnancy rate of the mice was not improved in the gestrinone group, and the body mass and the wet mass of liver and kidney were significantly decreased after drug treatment (all P<0.05), while the mice in the Neiyi recipe group showed no obvious damages of the liver, spleen or kidney. Conclusion Neiyi recipe can improve the pelvic microenvironment, promote follicular development and improve the reproductive ability of EM mice by inhibiting the growth of EM lesions and reducing pelvic adhesion, with no serious adverse effects and with good safety.

Abstract:Objective To explore the efficacy of interventional therapy for central venous stenosis in maintenance hemodialysis patients. Methods The general clinical data of the maintenance hemodialysis patients with central venous stenosis, who received interventional therapy in Changzheng Hospital of Naval Medical University (Second Military Medical University) from Jan. 2014 to Mar. 2018, were retrospectively analyzed, and the patency of vascular access of interventional therapy were followed up. Results A total of 82 maintenance hemodialysis patients with central venous stenosis were enrolled. Six-eight patients (82.93%) had a history of temporary central venous catheterization. Among the 82 patients, 13 (15.85%) had double lesions of central vein and 69 (84.15%) had single lesion; and 5 (6.10%) had mild lesions, 17 (20.73%) had moderate lesions, 35 (42.68%) had severe lesions and 25 (30.49%) had complete occlusion. Of the 82 patients, 57 were treated by percutaneous transluminal angioplasty and 9 by percutaneous transluminal stenting. The followup period ranged from 12 to 62 months after operation. The patency rate of vascular access was 75.76% (50/66) at 6 months postoperatively and 68.18% (45/66) at 12 months postoperatively. The overall patency rate of vascular access was 59.09% (39/66). Conclusion Central venous stenosis of the maintenance hemodialysis patients can affect the life of vascular access. For the patients with symptoms that can not be alleviated, active intervention is recommended. Intervention therapy is safe and effective for the patients with central venous stenosis. Meanwhile, the central venous catheterization shall be avoided if possible to reduce central venous stenosis in the patients with chronic kidney disease.

Abstract:Objective To explore the expression of C-type lectin domain 1 member B (CLEC1B) in hepatocellular carcinoma (HCC) tissues and its relationship with the clinicopathological characteristics and prognosis of HCC patients. Methods HCC tissue microarray data (GSE49515, GSE115018) were retrieved from Gene Expression Omnibus (GEO) database to analyze the differential expression of genes between cancer tissues and normal control tissues. HCC transcriptome datasets were screened from The Cancer Genome Atlas (TCGA) database to analyze the differential expression of CLEC1B in HCC tissues. Gene Set Enrichment Analysis (GSEA) was used to search for the signaling pathways related to CLEC1B in HCC. The cancer tissues and corresponding paracancerous tissues were collected from 37 HCC patients. The expression of CLEC1B mRNA was detected by quantitative real-time PCR, the expression of CLEC1B protein was detected by Western blotting. χ² test was performed to analyze the relationship between CLEC1B expression and clinicopathological characteristics of HCC patients. Kaplan-Meier method and log-rank test were performed to analyze the relationship between CLEC1B mRNA expression and prognosis of HCC patients. The blood samples were collected from 37 HCC patients and 37 healthy volunteers. The concentration of CLEC1B in plasma was measured by enzyme-linked immunosorbent assay. The diagnostic value of CLEC1B for HCC was evaluated by receiver operating characteristic (ROC) curve. Results The expression of CLEC1B was low in HCC cancer tissues, and the low expression of CLEC1B in HCC tissues was associated with tumor hemorrhage (P<0.01). The concentration of CLEC1B in plasma could be used as a biomarker for the diagnosis of HCC. The best diagnostic efficiency of CLEC1B was obtained by using 62.44 ng/mL as cut-off value (the area under the ROC curve was 0.966, the sensitivity was 92.7%, and the specificity was 91.3%). The HCC patients with high CLEC1B expression had a longer overall survival than those with low CLEC1B expression, and the difference was significant (P<0.01). In HCC, CLEC1B gene showed a consistent trend of differential expression with ATM and Rad3-related pathway (ATR pathway), cell cycle pathway, DNA repair pathway and myc signaling pathway. Conclusion The low expression of CLEC1B in HCC is related to tumor hemorrhage, and the prognosis of HCC patients with low expression of CLEC1B is poor.

Abstract:Objective To explore the mediating effect of fatigue on the relationship between negative emotion and burnout in military medical university students. Methods By random sampling, depression anxiety stress scale 21 (DASS- 21), multidimensional fatigue questionnaire (MFI-20) and Maslach burnout questionnaire (MBI) were used to investigate the negative emotion, fatigue and burnout of five-year undergraduates of clinical medicine in a military medical university. Pearson product moment correlation and multivariate hierarchical regression were used to analyze the relationships among different variables. Structural equation model was constructed and Bootstrap test was used to analyze the mediating effect.Results A total of 270 questionnaires were distributed, and 250 valid questionnaires were enrolled, with a response rate of 92.6%. The scores of three dimensions (depression, anxiety and stress) of negative emotion were significantly higher than the norm (all P<0.01). The score of physical fatigue was significantly higher than the norm (P<0.01), and the scores of mental fatigue, power loss and activity reduction were significantly lower than the norm (P<0.05, P<0.01). There were no differences between the scores of emotional exhaustion and cynicism and the norm, but the low achievement score was significantly higher than the norm (P<0.01). There were significant correlations between negative emotion, fatigue and burnout in all dimensions (all P<0.01). Multivariate hierarchical regression analysis showed that fatigue could explain 53.3% of variance variation of burnout (F=71.140, P<0.01). Both physical fatigue and mental fatigue had positive predictive effects on burnout (β=0.516, P<0.01; β=0.188, P<0.01). On the basis of fatigue, negative emotion could independently explain 1.9% of variance variation of burnout (F=44.243, P<0.01). Anxiety, depression and stress could explain 33.5% of the variation variance of burnout (F=42.333, P<0.01), and depression and stress had positive predictive effects on burnout (β=0.236, P<0.01; β=0.258, P<0.05). On the basis of negative emotion, fatigue could independently explain 21.7% of variance variation of burnout (F=44.243, P<0.01). Physical fatigue and mental fatigue had positive predictive effects on burnout (β=0.423, P<0.01; β=0.166, P<0.01). Mediation effect models and Bootstrap test results showed that negative emotion could indirectly affect burnout through fatigue (χ²=74.508, df=17, χ²/df=4.383, comparative fit index[CFI]=0.955, incremental fit index[IFI]=0.956, relative fit index[RFI]=0.943, Tucker-Lewis index[TLI]=0.926). The mediating effect of fatigue was 65.3%. Conclusion Fatigue plays a mediating role between negative emotion and burnout. The military medical students with high anxiety, depression and stress need more attention and effective measures should be adopted to avoid the aggravation of their fatigue and burnout.

Abstract:In recent years, scientists have had a deeper understanding of the basic principles of tumor biology and immunology, and immunotherapy for cancer has made great progresses, greatly promoting the development of a series of new immunotherapy drugs for cancer. Cancer immunotherapy aims at eliminating cancer cells by stimulating and coordinating the immune system. However, the promotion and application of cancer immunotherapy are limited because of the uncertain safety and effectiveness of immune regulatory compound delivery. Due to its unique advantages, such as good targeting, less adverse events, and good stability, various nano-targeted delivery systems with different physical and chemical properties have been developed to stimulate the immune system in anti-tumor therapy. In this review, we summed up the research progresses of nanotechnology combined with immunotherapy for cancer in recent years.

Abstract:Pregnant women's health is vulnerable to a variety of environmental and behavioral factors. Air pollution is one of the important environmental factors for pregnant women, and many studies have analyzed its impact on complications during pregnancy. Most of the findings demonstrate that air pollution is associated with the increased incidence of gestational diabetes mellitus (GDM) and hypertensive disorders of pregnancy (HDP). The particles and aerosol contaminants in the air can cause GDM and HDP through inflammation, oxidative stress, and other mechanisms. To control body mass index before pregnancy and supplement trace elements such as folic acid and vitamin D play active roles in preventing complications during pregnancy. In this review, we discussed the effects of various components of air pollutants on complications during pregnancy, hoping to provide references for preventing complications during pregnancy.

Abstract:Warships undergo accelerated motion when attacked by underwater explosion in the naval battles, resulting in severe damage of the warship personnel, which is termed as ship shock injury. The ship shock injury is the main factor that causes the loss of fighting capacity of personnel on warships. A great number of studies on ship shock injury have been made at home and abroad. In this paper, we reviewed and analyzed the history, research methods, injury mechanisms and characteristics, and protection and treatment measures of ship shock injury, pointing out the shortcomings of current research and proposing research direction in future. We hoped this paper can help to deepen the understanding of naval surgeons on ship shock injury and provide a reference for the prevention and treatment of ship shock injury.

Abstract:Objective To investigate the current status of skeletal muscle reduction (abbreviated as sarcopenia), quality of life and mental status of maintenance dialysis (MHD) patients, and to explore the relationship between sarcopenia and the quality of life and mental status. Methods According to the diagnostic criteria developed by the European Working Group on Sarcopenia in Older People, 101 MHD patients treated in our hospital in Dec, 2017 were divided into sarcopenia group (n=51) and non-sarcopenia group (n=50). The body composition was measured by human body composition monitor in all the patients. The quality of life was assessed using the SF-36 scale. The anxiety and depression were assessed with the hospital anxiety and depression scale (HADS). Multivariate linear regression analysis was used to explore the relationship between sarcopenia and the quality of life and mental status of the MHD patients. Results There were significant differences in the age, gender, body mass index (BMI), Charlson comorbidity index, grip strength, walking speed, somatic cell mass, extra-cellular fluid/total body fluid ratio (ECF/TBF), high-sensitivity C-reactive protein (hsCRP), urea clearance index (Kt/V), anxiety, depression, physical function, bodily pain, general health status and mental health between the two groups (P<0.05, P<0.01). While there were no significant differences in the marital status, education, annual income, dialysis age, primary disease, hemoglobin, total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, prealbumin, albumin, serum calcium, blood phosphorus, intact parathyroid hormone, physical role, vitality, social function and emotion role between the two groups (all P>0.05). Multivariate linear regression analysis showed that skeletal muscle mass, marital status and comorbidity were the influencing factors of the quality of life of MHD patients with sarcopenia (all P<0.05), and skeletal muscle mass, BMI and annual income were the influencing factors of mental status of MHD patients with sarcopenia (P<0.05, P<0.01). Conclusion The incidence of sarcopenia is high in MHD patients. Sarcopenia is related to poor quality of life, and anxiety and depressive symptoms, highlighting the importance of early detection and attention to sarcopenia.

Abstract:Objective To report a family with Hailey-Hailey disease (HHD) and to analyze the ATP2C1 gene mutation. Methods The general data of HHD family members were collected for clinical investigation, and the family tree was drawn. ATP2C1 gene was detected by PCR and Sanger direct sequencing in 4 HHD patients of the family, and 3 healthy members in the family and 100 unrelated normal volunteers were taken as controls. Results In the 4 HHD patients, a novel missense mutation (c.472G>A) on the 21^th exon of the ATP2C1 gene was identified, which resulted in a missense mutation of aspartic acid (p.Asp158Asn). But the mutation was not found in the healthy members in the family or the unrelated normal individuals. Conclusion The missense mutation c.472G>A on exon 21 of ATP2C1 gene is a new mutation site, which may be the main cause of HHD.

Abstract: