[Objective] To analyze the infection status of hepatitis E virus (HEV) among blood donors in Zhengzhou, so as to provide data support for formulating local blood screening strategies. [Methods] Random samples from blood donors from January to December 2022 were tested for HEV RNA using PCR technology. Reactive samples were sequenced for gene analysis, and the donors were followed up. [Results] Among 21 311 samples, 3(0.14‰) were reactive for HEV RNA, all of whom were male. Genetic sequencing results revealed that one strong positive sample was genotype 4, while sequencing failed for the other two due to low viral load. A follow-up of 25 strong positive donors showed that ALT significantly increased on day 7 after donation, anti-HEV IgM and anti-HEV IgG turned positive. On day 21, ALT returned to normal, and on day 35, HEV RNA turned negative. Notably, anti-HEV IgM and anti-HEV IgG persisted until day 482. [Conclusion] There is HEV infection among blood donors in Zhengzhou, and it is necessary to expand the screening scope to comprehensively explore the prevalence and genotype distribution of HEV among blood donors.

OBJECTIVES: To design a deep learning model that balances model complexity and performance to enable its integration into wearable ECG monitoring devices for automated diagnosis of atrial fibrillation. METHODS: This study was performed based on data from 84 patients with atrial fibrillation, 25 patients with atrial fibrillation, and 18 subjects without obvious arrhythmia collected from the publicly available datasets LTAFDB, AFDB, and NSRDB, respectively. A lightweight attention network based on depthwise separable convolution and fusion of channel-spatial information, namely DSC-AttNet, was proposed. Depthwise separable convolution was introduced to replace standard convolution and reduce model parameters and computational complexity to realize high efficiency and light weight of the model. The multilayer hybrid attention mechanism was embedded to compute the attentional weights of the channels and spatial information at different scales to improve the feature expression ability of the model. Ten-fold cross-validation was performed on LTAFDB, and external independent testing was conducted on AFDB and NSRDB datasets. RESULTS: DSC-AttNet achieved a ten-fold average accuracy of 97.33% and a precision of 97.30% on the test set, both of which outperformed the other 4 comparison models as well as the 3 classical models. The accuracy of the model on the external test set reached 92.78%, better than those of the 3 classical models. The number of parameters of DSC-AttNet was 1.01M, and the computational volume was 27.19G, both smaller than the 3 classical models. CONCLUSIONS This proposed method has a smaller complexity, achieves better classification performance, and has a better generalization ability for atrial fibrillation classification.
Atrial Fibrillation/diagnosis* ; Humans ; Electrocardiography ; Deep Learning ; Wearable Electronic Devices ; Neural Networks, Computer

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective:To analyze the risk factors affecting regional lymph node metastasis in salivary gland mucoepidermoid carcinoma (MEC) and to establish a nomogram model for individually predicting lymph node metastasis in salivary gland MEC.Methods:The clinical data of 2 152 patients with salivary gland MEC from 1975 to 2020 were collected from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute. The collected data were divided into training cohort (1 506 cases) and validation cohort (646 cases) according to the ratio of 7∶3. Single-factor regression and multi-factor logistic regression were used to screen factors related to local lymph node metastasis in salivary gland MEC, with constructing of a nomogram. Calibration curve, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC) and decision curve analysis were used to evaluate model performance in the validation cohort and the total cohort. Statistical tests were performed using SPSS (26.0) and R (4.3.0) software.Results:Multivariate logistic regression results showed that M stage [ OR(95% CI):12.360(3.295-46.365), P=0.014], pathological grade Ⅱ、Ⅲ、Ⅳ[ OR(95% CI): 1.956(1.329-2.879), 9.654(6.309-14.772), 9.298(6.072-14.238), P<0.001], T staging T2, T3, T4[ OR(95% CI): 1.706(0.932-3.124), 3.021(1.790-5.096), 3.311(1.925-5.695), P<0.001], and gender [ OR(95% CI):0.759(0.593-0.972), P=0.029] were independent factors affecting local lymph node metastasis in salivary gland MEC. Through verification in the validation cohort and the total cohort, the AUC values were greater than 0.8, and the calibration curve was close to the perfect reference line, proving that the constructed nomogram model had good specificity and sensitivity for predicting local lymph node metastasis in salivary gland MEC. Conclusion:M stage, pathological grade, T stage, and gender are risk factors for predicting regional lymph node metastasis and the established-nomogram has good predictive performance for local lymph node metastasis in salivary gland MEC.

Objective:To investigate the prevalence of adult skeletal fluorosis caused by drinking tea-type endemic fluorosis in Yushu Tibetan Autonomous Prefecture (hereinafter referred to as Yushu Prefecture), Qinghai Province, and provide scientific basis for prevention and control of the disease.Methods:In August 2021, one village was selected as a survey site in six counties (cities) in Yushu Prefecture, including Nangqian, Chindu, Yushu, Zadoi, Qumarlêb, and Zhiduo. Drinking water samples and 10 brick tea samples were collected from each village to determine the fluoride content in water and brick tea; at least 100 permanent residents aged ≥ 25, who had a habit of drinking brick tea and had lived in the local area for more than 5 years, were selected for X-ray imaging to examine the prevalence of adult skeletal fluorosis.Results:A total of 75 samples of residential drinking water were collected, with a fluoride content of (0.21 ± 0.05) mg/L, ranging from 0.11 to 0.34 mg/L; 60 samples of brick tea, with a fluoride content of (626.70 ± 157.27) mg/kg, ranging from 324.00 to 2 102.00 mg/kg. A total of 1 136 adults were examined, and 318 cases of skeletal fluorosis were diagnosed, with a detection rate of 27.99%. Among them, the detection rates of mild, moderate, and severe skeletal fluorosis were 20.95% (238/1 136), 6.07% (69/1 136), and 0.97% (11/1 136), respectively, with mild symptoms being the main. The detection rates of skeletal fluorosis in males and females were 29.09% (121/416) and 27.36% (197/720), respectively, with no statistically significant difference between the gender (χ 2 = 0.39, P = 0.533). Comparison of the skeletal fluorosis in different gender, the differences were statistically significant (χ 2 = 22.31, P < 0.001). The detection rates of skeletal fluorosis in the age groups of 25 - 35, 36 - 45, 46 - 55, 56 - 65, 66 - 75, and ≥76 years old were 6.86% (7/102), 22.37% (51/228), 24.02% (92/383), 37.44% (73/195), 43.48% (70/161), and 37.31% (25/67), respectively. The differences between the groups were statistically significant (χ 2 = 59.84, P < 0.001). Moreover, there was a statistically significant difference in the composition of skeletal fluorosis among different age groups ( H = 37.66, P < 0.001). The Spearman correlation analysis results showed that the severity of adult skeletal fluorosis was positively correlated with age ( r = 0.34, P < 0.001). Conclusions:There is a certain degree of prevalence of adult skeletal fluorosis in Yushu Prefecture. And as age increases, the condition of skeletal fluorosis becomes more severe.

With a global rise in morbidity rates， obesity has become a pressing public health issue. With increased adipocyte number and volume as the main characteristics， obesity is also manifested by metabolic disorders to varying degrees. At the same time， obesity is a risk factor for diabetes， hypertension， stroke， cancer， and cardiovascular diseases， imposing burdens on society and families. Influenced by lifestyle， environment， behavior， and genetics， obesity is caused by the interaction of many factors， and its pathological process is complex， involving inflammation， autophagy， and intestinal dysbiosis. The mitogen-activated protein kinase （MAPK） cascade reaction， a pivotal signaling pathway， plays a crucial role in cellular processes such as proliferation， differentiation， apoptosis， and stress responses. Both Chinese and international studies indicate that the MAPK signaling pathway can effectively regulate obesity through various pathways， including the modulation of adipocyte differentiation and apoptosis， appetite control， and inflammation improvement. Moreover， traditional Chinese medicine （TCM） has demonstrated significant efficacy in preventing and treating obesity， leveraging advantages such as multiple targets， diverse components， and minimal adverse effects. Research indicates that the MAPK signaling pathway is a primary focus of TCM regulation in this context， although a systematic review in this field is currently lacking. Therefore， this paper， by reviewing the latest Chinese and international research， provided a concise overview of the basic structure of the MAPK pathway， with a specific emphasis on recent progress in TCM interventions targeting the MAPK pathway for obesity treatment. The results indicate that regulating adipose tissue formation， differentiation， and thermogenesis， reducing inflammation and oxidative stress levels， and improving insulin sensitivity and metabolic disorders seem to be the main ways for TCM to regulate the MAPK pathway to prevent and treat obesity. However， it is necessary to find more research methods and explore potential mechanisms underlying TCM formulations based on the MAPK pathway for obesity prevention and treatment.

Objective To explore growth pattern of neo-aortic root as well as development of neo-aortic regurgitation after arterial switch operation (ASO) for Taussig-Bing anomaly. Methods From 2002 to 2017, the patients who received ASO, and were discharged alive from Shanghai Children’s Medical Center and followed up for more than 3 years were retrospectively involved in this study. Results A total of 127 patients were enrolled. There were 98 (77.2%) males, the median age at ASO was 73.0 d and the average weight was 4.7 kg. Forty-five (35.4%) children were complicated with mild or mild-to-moderate pulmonary insufficiency (PI) before ASO. The average follow-up time was 7.0 years. During the follow-up, 14 (11.0%) children presented moderate or greater neo-aortic regurgitation (neo-AR). The diameter of neo-aortic annulus and sinus of Valsalva was beyond normal range during the entire follow-up. The average diameter of neo-aortic annulus was 18.0 mm at 5 years and 20.5 mm at 10 years. The average diameter of sinus of Valsalva was 25.9 mm at 5 years and 31.1 mm at 10 years. Neo-AR continued to develop over time. The diameter of children who developed moderate or greater neo-AR was constantly larger than that of children who did not (χ2=18.3, P<0.001). Preoperative mild or mild-to-moderate PI was an independent risk factor for the development of moderate or greater neo-AR during mid-to-long term follow-up (c-HR=3.46, P=0.03). Conclusion The diameters of neo-aortic annulus and sinus of Valsalva of Taussig-Bing children who receive ASO repair continue to expand without normalization. The dilation of annulus correlates with the development of neo-AR. PI before ASO repair increases the risk of neo-AR development.

Objective:To validate the diagnostic performance of the Paris system for reporting urinary cytology (TPS).Methods:A total of 7 046 urine cytology samples from 3 402 patients collected in the Department of Pathology, Beijing Hospital, China from January 2020 to January 2022 were analyzed. 488 patients had a biopsy or resection specimen during the follow-up period of 6 months. The sensitivity, specificity, risk of malignancy (ROM) and risk of high-grade malignancy (ROHM) of the TPS were evaluated using histological diagnosis as the golden standard.Results:Among the 7 046 samples, high-grade urothelial carcinoma (HGUC) accounted for 5.7% (399/7 046), suspicious for high-grade urothelial carcinoma (SHGUC) for 3.2% (227/7 046), atypical urothelial cells (AUC) for 8.4% (593/7 046), and negative for high-grade urothelial carcinoma (NHGUC) for 72.9% (5 139/7 046) including low-grade urothelial neoplasm (LGUN) for 0.8% (59/7 046) and insufficient samples for 9.8% (688/7 046). 488 patients had a bladder biopsy or resection in the follow-up of six months, including 314 males and 174 females, aged 27 to 92 years (average, 66 years). The ROHM of TPS was 94.7% in HGUC, 83.3% in SHGUC, 41.3% in AUC and 18.8% in NHGUC. The sensitivity and specificity of urine cytology were 70.1% (169/241) and 97.0% (162/167), respectively. The negative predictive value of NHGUC was 69.2% (162/234).Conclusions:The study has shown that TPS classification has high sensitivity and specificity, high ROHM for HGUC and SHGUC, and high negative predictive value for NHGUC. The application of TPS reporting system can better interpret the clinical significance of cytology samples, improve the accuracy of urine cytopathology and ensure continuous diagnostic consistency.

Objective:To investigate the importance of cell block and immunohistochemistry in the accurate diagnosis of serous effusion.Methods:A retrospective study was conducted on 3 124 cases of serous effusion from the Department of Pathology, Beijing Hospital from 2018 to 2022, include 2 213 cases of pleural effusion, 768 cases of peritoneal effusion, 143 cases of pericardial effusion. There were 1 699 males (54.4%) and 1 425 females (45.6%), average age 69 years old. Of which 1 292 cases were prepared with cell blocks and examined with immunohistochemical stain.Results:The percentage of malignant diagnosis increased from 64.9% (839/1 292) to 84.0% (1 086/1 292) after cell block preparation, and 1 086 cases were accurately diagnosed with histological type and/or origin of primary tumor. The undetermined diagnosis of suspected malignancy decreased from 13.3% (172/1 292) to 0.1% (1/1 292) and that of atypical hyperplasia from 18.8% (243/1 292) to 0.4% (5/1 292). The negative result for malignancy rate increased from 3.0% (38/1 292) to 15.5% (200/1 292). The differences highlighted above were statistically significant (Pearson′s chi-squared test=12.739, P<0.01). Conclusion:Application of immunohistochemistry based on cell block can significantly improve malignant diagnosis in serous effusion, identify tumor origin and histological type as well as decrease the uncertain diagnosis.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.