Background::Carotid intima-media thickness (IMT) and diameter, stiffness, and wave reflections, are independent and important clinical biomarkers and risk predictors for cardiovascular diseases. The purpose of the present study was to establish nationwide reference values of carotid properties for healthy Chinese adults and to explore potential clinical determinants.Methods::A total of 3053 healthy Han Chinese adults (1922 women) aged 18-79 years were enrolled at 28 collaborating tertiary centers throughout China between April 2021 and July 2022. The real-time tracking of common carotid artery walls was achieved by the radio frequency (RF) ultrasound system. The IMT, diameter, compliance coefficient, β stiffness, local pulse wave velocity (PWV), local systolic blood pressure, augmented pressure (AP), and augmentation index (AIx) were then automatically measured and reported. Data were stratified by age groups and sex. The relationships between age and carotid property parameters were analyzed by Jonckheere-Terpstra test and simple linear regressions. The major clinical determinants of carotid properties were identified by Pearson’s correlation, multiple linear regression, and analyses of covariance.Results::All the parameters of carotid properties demonstrated significantly age-related trajectories. Women showed thinner IMT, smaller carotid diameter, larger AP, and AIx than men. The β stiffness and PWV were significantly higher in men than women before forties, but the differences reversed after that. The increase rate of carotid IMT (5.5 &mu;m/year in women and 5.8 &mu;m/year in men) and diameter (0.03 mm/year in both men and women) were similar between men and women. For the stiffness and wave reflections, women showed significantly larger age-related variations than men as demonstrated by steeper regression slopes (all P for age by sex interaction <0.05). The blood pressures, body mass index (BMI), and triglyceride levels were identified as major clinical determinants of carotid properties with adjustment of age and sex. Conclusions::The age- and sex-specific reference values of carotid properties measured by RF ultrasound for healthy Chinese adults were established. The blood pressures, BMI, and triglyceride levels should be considered for clinical application of corresponding reference values.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To explore the application value of qualitative characteristics and quantitative parameters of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of pancreatic ductal adenocarcinoma (PDAC) and non-PDAC presenting as pancreatic solid focal lesions.Methods:A retrospective analysis was conducted on 64 cases of PDAC(the PDAC group) and 52 cases of non-PDAC(the non-PDAC group) who underwent CEUS examination at Tianjin Medical University Cancer Institute and Hospital from July 2022 to June 2023. Clinical characteristics, two-dimensional ultrasound features, CEUS qualitative characteristic, and quantitative parameters were compared between the two groups. ROC curves were plotted, and the Delong test was used to evaluate the diagnostic performance of qualitative and quantitative analyses in distinguishing PDAC from non-PDAC. Binary logistic regression analysis was employed to assess the independent predictors of PDAC.Results:①There were significant differences in serum CA19-9, lesion size, boundary, the main pancreatic duct (MPD) diameter, degree of enhancement and enhancement pattern between the PDAC group and the non-PDAC group (all P<0.05). ②The relative peak intensity (rPE), and relative wash-in and wash-out area under the curve (rWiWoAUC) were lower in the PDAC group than the non-PDAC group, with statistically significant differences(all P<0.001). ③The areas under the curve (AUC) for diagnosing PDAC using enhancement pattern, venous phase(VP) enhancement degree, rPE, and rWiWoAUC were 0.698, 0.707, 0.863, and 0.867, respectively. The AUCs of quantitative parameters were superior to those of qualitative characteristics, with statistically significant differences ( P<0.05). Using CEUS mode B, low VP enhancement, rPE<72.44, and rWiWoAUC<86.59 as cut-off values, the accuracies for diagnosing PDAC were 0.698, 0.741, 0.828, and 0.802, respectively. ④Serum CA19-9, lesion size, MPD diameter, rPE, and rWiWoAUC were independent predictors of PDAC (all P<0.05). Conclusions:CEUS qualitative and quantitative analyses are helpful in the differential diagnosis of PDAC and non-PDAC, with rPE and rWiWoAUC being useful indicators for diagnosing PDAC.

Objective:To analyze and summarize the key points of design and implementation of new drug clinical trials for ankylosing spondylitis.Methods:The platform for drug clinical trial registration and information published on the official website of center for drug review and evaluation of national medical products administration (CDE) was searched to obtain data and classified statistics was conducted then. The Mean±SD and M ( Q1, Q3) were used for quantitative data for statistical description, and the rate, composition or relative ratio of qualitative data were used for statistical description. Results:A total of 23 clinical trials meeting the requirements were screened, among which 19 were biological products included in nine phase Ⅲ clinical trials. Among the four chemical drugs, two were phase Ⅱ clinical trials. One of the clinical trials on AS adopted the 1966 New York classification criteria, accounting for 4%. Nineteen of the trials adopted the1984 New York classification criteria, accounting for 83%. Three other trials adopted unspecified classification criteria, accounting for 13%. In one of these clinical trials, the age of patients included was older than 16 years old, 9 trials were 18 to 65 years old, 6 were 18 years old but without upper limit. In the definition of active AS, 19 trials took BASDAI≥4 as the cut-off value for active disease, and BASDAI, total back pain, spinal pain and morning stiffness were regarded as active disease in 4.Conclusion:The number of dosestic AS clinical trial projects continnes to rise. The 1984 classification criteria is adopted as the classification criteria in clinical trials. The minimum age in the inclusion criteria is 18 years old, there is no upper limit in age for inclusion. Disease activity can be evaluated by BASDAI score, combined with comprehensive indicators such as night-time back pain, global spinal pain and morning stiffness.

Chemotherapy-induced complications, particularly lethal cardiovascular diseases, pose significant challenges for cancer survivors. The intertwined adverse effects, brought by cancer and its complication, further complicate anticancer therapy and lead to diminished clinical outcomes. Simple supplementation of cardioprotective agents falls short in addressing these challenges. Developing bi-functional co-therapy agents provided another potential solution to consolidate the chemotherapy and reduce cardiac events simultaneously. Drug repurposing was naturally endowed with co-therapeutic potential of two indications, implying a unique chance in the development of bi-functional agents. Herein, we further proposed a novel "trilogy of drug repurposing" strategy that comprises function-based, target-focused, and scaffold-driven repurposing approaches, aiming to systematically elucidate the advantages of repurposed drugs in rationally developing bi-functional agent. Through function-based repurposing, a cardioprotective agent, carvedilol (CAR), was identified as a potential neddylation inhibitor to suppress lung cancer growth. Employing target-focused SAR studies and scaffold-driven drug design, we synthesized 44 CAR derivatives to achieve a balance between anticancer and cardioprotection. Remarkably, optimal derivative 43 displayed promising bi-functional effects, especially in various self-established heart failure mice models with and without tumor-bearing. Collectively, the present study validated the practicability of the "trilogy of drug repurposing" strategy in the development of bi-functional co-therapy agents.

Objective To explore the protective mechanism of baicalin regulating NOD like receptor thermal protein domain associated protein 3(NLRP3)inflammasomes against acne.Methods Compound acne models were prepared by intradermal injection of Propionibacterium acnes into the auricle.Rats were randomly divided into control group(normal rats were given physiological saline by gavage),model group(acne model rats were given physiological saline by gavage),experimental-L,-M,-H groups(acne model rats were given 25,50,and 100 mg·kg-1 of baicalin by gavage),and positive control group(acne model rats were given 3.125 mg·kg-1 of isotretinoin by gavage),with 10 rats in each group.Observe the morphology of rat auricles;enzyme linked immunosorbent assay(ELISA)was used to detect the level of inflammation in serum;hematoxylin-eosin staining was used to detect pathological changes in rat auricle tissue;Western blotting was used to detect the protein expression level in the auricle tissue.Results After drug treatment,the auricular thickness of rats in the control,model,experimental-H and positive control groups were(0.42±0.05),(0.75±0.10),(0.49±0.05)and(0.50±0.05)mm;the serum levels of tumor necrosis factor-α were(20.46±2.13),(62.32±5.47),(23.27±2.26)and(25.41±2.28)pg·mL-1;interleukin-1 β levels were(11.38±1.26),(31.62±2.58),(15.61±1.35)and(16.72±1.38)pg·mL-1;interleukin-6 levels were(10.62±1.02),(25.43±2.51),(13.27±1.15)and(14.01±1.17)pg·mL-1;NLRP3 protein expression levels in auricular tissues were 0.23±0.03,0.81±0.08,0.30±0.04 and 0.32±0.04;and Caspase-1 protein expression levels were 0.31±0.04,0.76±0.08,0.39±0.04 and 0.41±0.04;matrix metalloproteinase-2 protein expression levels were 0.35±0.04,0.86±0.10,0.40±0.05 and 0.42±0.05.Compared with the model group,the above indexes in the experimental-H group were statistically significant(all P＜0.05).Conclusion Baicalin can inhibit the inflammatory response in acne rats,and its mechanism of action may be related to the inhibition of the NLRP3 inflammasome signaling pathway.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.