Objective To establish a zebrafish model of thrombosis induced by three kinds of inducers and observe the anti?thrombotic effect of a Chinese traditional medicine, Guanxinning tablet ( GXN) . Methods The zebrafish models of thrombosis was induced by using 1?5μmol/L phenyl hydrazine, 80μmol/L arachidonic acid and 5 mg/L ponatinib, re?spectively, and were treated with various concentration of GXN, clopidogrel or asprin. The thrombus in the tail vein was observed under microscope, Erythrocytes in the zebrafish heart were stained with o?dianisidine and the erythrocyte staining intensity was assessed with a NIS?Elements DTM image analyzer, and the anti?thrombolic effect of GXN was calculated. Results Venous thrombus was significantly increased and the staining intensities of erythrocytes in the heart were signifi?cantly decreased after induction by phenyl hydrazine, arachidonic acid or Ponatinib ( P <0?001 ) , respectively. At the same time, GXN showed an incresing anti?thrombolic effect in the zebrafish models (P<0?001) in a dose?effect manner, with a IC50 of GXN of 44?32 mg/L,138?5 mg/L and 459?5 mg/L, respectively. Conclusions The zebrafish models of thrombosis are successfully established by phenyl hydrazine, arachidonic acid or Ponatinib, respectively, by different for?mation mechanisms. GXN has been shown to have an anti?thrombosis effect, probably, by multiple target effects.

Objective:Through the bibliometrics analysis and visual analysis of Chinese and English literature related to pneumoconiosis through CiteSpace, to understand the research situation, research trend and hotspots of pneumoconiosis, so as to provide reference for further research.Methods:In August 2022, CNKI (China National Knowledge Infrastructure) data baseand Web of Science core collection database were used as data sources for literature retrieval. Cite Space.5.8.R3c software was used to analyze the cooperation between authors and institutions, keyword co-occurrence analysis, keyword clustering analysis and keyword emergence analysis.Results:A total of 4726 Chinese literature and 2490 English literature related to pneumoconiosis were included; The annual publication volume of Chinese literature shows a fluctuating downward trend, while the annual publication volume of English literature shows a fluctuating upward trend. The Institute of Labor Health and Occupational Disease of the Chinese Academy of Preventive Medical Sciences and the Institute of Occupational Health and Poisoning Control of the Chinese Center for Disease Control and Prevention have the highest publication volume (55 articles) in the institutional cooperation network; The National Institute for Occupational Safety and Health (NIOSH) in the United States has the highest publication volume (153 articles) in the institutional collaboration network. The results of keyword co-occurrence, clustering, and prominence analysis show that Chinese literature focuses more on clinical research on pneumoconiosis, while English literature focuses more on experimental research related to the pathogenesis of pneumoconiosis.Conclusion:In the related field of pneumoconiosis research, the experimental research and clinical research on the pathogenesis are the main research hotspots.

Objective:Through the bibliometrics analysis and visual analysis of Chinese and English literature related to pneumoconiosis through CiteSpace, to understand the research situation, research trend and hotspots of pneumoconiosis, so as to provide reference for further research.Methods:In August 2022, CNKI (China National Knowledge Infrastructure) data baseand Web of Science core collection database were used as data sources for literature retrieval. Cite Space.5.8.R3c software was used to analyze the cooperation between authors and institutions, keyword co-occurrence analysis, keyword clustering analysis and keyword emergence analysis.Results:A total of 4726 Chinese literature and 2490 English literature related to pneumoconiosis were included; The annual publication volume of Chinese literature shows a fluctuating downward trend, while the annual publication volume of English literature shows a fluctuating upward trend. The Institute of Labor Health and Occupational Disease of the Chinese Academy of Preventive Medical Sciences and the Institute of Occupational Health and Poisoning Control of the Chinese Center for Disease Control and Prevention have the highest publication volume (55 articles) in the institutional cooperation network; The National Institute for Occupational Safety and Health (NIOSH) in the United States has the highest publication volume (153 articles) in the institutional collaboration network. The results of keyword co-occurrence, clustering, and prominence analysis show that Chinese literature focuses more on clinical research on pneumoconiosis, while English literature focuses more on experimental research related to the pathogenesis of pneumoconiosis.Conclusion:In the related field of pneumoconiosis research, the experimental research and clinical research on the pathogenesis are the main research hotspots.

Objective:To examine the risk factors for neuropathic pain (NP) after a spinal cord injury (SCI).Methods:A total of 115 patients with a SCI were analyzed retrospectively. They were divided into an NP group of 53 and a non-NP group of 62 according to the occurrence of NP. Gender, age, length of stay, occupation, level of education, cause of injury, spinal fracture, degree of SCI, the injury′s plane and complications at admission (diabetes, hypertension, anemia, venous thrombosis, pressure sores, urinary tract infection or hypoproteinemia) were recorded. T-tests and chi-squared tests were used to compare those factors between the two groups, and multivariate logistic regressions were evaluated to identify the risk factors for NP.Results:Twenty-three of the 53 cases of NP (43%) had developed within 1 month of the SCI. Thirty-seven (75%) experienced pain below the plane of the SCI. The main features reported were squeezing (34%) and numbness (26%). The multivariate logistic regression showed that the occurrence of NP was most strongly related to gender (women being particularly at risk) and venous thrombosis at admission.Conclusions:Women are at particular risk of feeling NP after an SCI, and venous thrombosis is an independent risk factor. NP should be diagnosed and treated quickly to reduce the negative impact on patients′ life quality.

Objective:To explore the risk factors for lower extremity deep vein thrombosis (DVT) in patients with a spinal cord injury (SCI).Methods:The medical records of 276 hospitalized SCI patients were analyzed retrospectively. They were divided into a DVT group ( n=63) and a no-DVT group ( n=213). Gender, age, blood type, smoking history, surgical history, the time from SCI to admission, cause of SCI, fracture, SCI segments, American Spinal Cord Injury Association grade and complications were compared between the two groups. Binomial logistic regression was used to isolate the risk factors for lower extremity DVT among such patients. Results:Among 84% of the 63 with a lower extremity DVT, it was a calf muscle venous thrombosis. Anemia, hyponatremia and time from SCI to admission (which ranged from 74 to 195 days) were the most serious DVT risk factors.Conclusions:SCI patients are of high risk for DVT, with anemia and hyponatremia being independent risk factors.

Objective:To explore the risk factors for urinary tract infection (UTI) after a spinal cord injury (SCI).Methods:The medical records of 403 SCI patients were analyzed retrospectively. They were divided into UTI group and no-UTI group according to whether they had a UTI at admission. Gender, age, cause of injury, injury level of the spinal cord, voluntary anal contraction, time from injury to admission, American Spinal Injury Association (ASIA) grade, axillary temperature at admission, complications at admission (diabetes, hypertension, fracture of the pelvis, pressure sores or anemia), white blood cell count and urinary bacteria were compared between the two groups. Binary logistic regression was used to highlight the risk factors for a UTI after an SCI.Results:Of the 354 patients included in the final analysis, 62 (17.51%) had a UTI at admission. The regression showed that UTI after an SCI was closely related to an inability to voluntarily contract the anus, anemia, elevated white blood cell count and a high level of bacteria in the urine.Conclusions:Inability to contract the anus, fever, anemia and an elevated white blood cell count are independent indicators of a UTI after an SCI. A temperature ≥37.3°C is a simple indicator of a concentration of bacteria in the urine ≥1266/μL.

Objective:To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning.Methods:The researchers collected 519 lung pathologic slides from 2016 to 2019, covering various lung tissues, including normal tissues, adenocarcinoma, squamous cell carcinoma and small cell carcinoma, from the Beijing Chest Hospital, the Capital Medical University. The slides were digitized by scanner, and 316 slides were used as training set and 203 as the internal test set. The researchers labeled all the training slides by pathologists and establish a semantic segmentation model based on DeepLab v3 with ResNet-50 to detect lung cancers at the pixel level. To perform transfer learning, the researchers utilized the gastric cancer detection model to initialize the deep neural network parameters. The lung cancer detection convolutional neural network was further trained by fine-tuning of the labeled data. The deep learning model was tested by 203 slides in the internal test set and 1 081 slides obtained from TCIA database, named as the external test set.Results:The model trained with transfer learning showed substantial accuracy advantage against the one trained from scratch for the internal test set [area under curve (AUC) 0.988 vs. 0.971, Kappa 0.852 vs. 0.832]. For the external test set, the transferred model achieved an AUC of 0.968 and Kappa of 0.828, indicating superior generalization ability. By studying the predictions made by the model, the researchers obtained deeper understandings of the deep learning model.Conclusions:The lung cancer histopathological diagnostic system achieves higher accuracy and superior generalization ability. With the development of histopathological AI, the transfer learning can effectively train diagnosis models and shorten the learning period, and improve the model performance.