ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Aim To investigate the regulatory role and mechanism of resveratrol in inhibiting autophagy and promoting apoptosis in choroidal melanoma cells. Methods Choroidal melanoma cells (MUM2B) were divided into control and experimental groups, and treated with different concentrations of resveratrol (0, 10, 20,40,60,80 μmol ·L

Objective To investigate the effects of palmatine on migration,invasion and epithelial mesenchymal transformation(EMT)in human oral cancer KB cells.Methods KB cells were divided into control group and palmatine-L,-M,-H groups,cultured with 0,4,8 and 16 μmol·L-1 palmatine.After incubation for 48 h,scratch assay was used to detect migration;Traswell assay was used to detect invasion;matrix metalloproteinase 2(MMP-2),MMP-9 and fibronectin(FN)contents were detected by enzyme-linked immunosorbent assay;the expression of Vimentin,N-cadherin and E-cadherin mRNA were detected by real-time quantitative polymerase chain reaction;the expression of Vimentin,N-cadherin,E-cadherin,Wnt3 and β-catenin protein were detected by Western blot.Results Cell mobility in control group and palmatine-L,-M,-H groups were(69.27±8.62)％,(52.94±4.49)％,(45.22±5.05)％and(37.63±4.88)％;the number of transmembrane cells were 197.33±20.26,125.33±12.01,97.00±9.17 and 62.67±7.51;the content of MMP-2 were(2.93±0.21),(1.49±0.13),(1.16±0.15)and(0.95±0.09)ng·mL-1;the content of MMP-9 were(3.51±0.36),(2.37±0.23),(2.06±0.35)and(1.72±0.16)ng·mL-1;the content of FN were(41.28±4.02),(24.03±3.17),(20.67±2.63)and(13.82±2.19)ng·mL-1;the above indexes in palmatine-L,-M,-H groups were compared with the control group,and the differences were statistically significant(P＜0.05,P＜0.01).The mRNA and protein expressions of Vimentin,N-cadherin and E-cadherin,and the expressions of Wnt3 and β-catenin protein in palmatine-L,-M,-H groups were statistically significant compared with those in control group(P＜0.05,P＜0.01).Conclusion Palmatine can inhibit the migration,invasion and EMT of human oral cancer KB cells,and its mechanism is related to the regulation of Wnt/β-catenin signaling pathway.

AIM To establish a quantitative analysis of multi-components by single-marker(QAMS)method for the simultaneous content determination of gastrodin,parishin E,syringin,parishin B,parishin C,ferulic acid,parishin A,buddleoside,harpagoside and cinnamic acid in Tianma Toufengling Capsules.METHODS The analysis was performed on a 30℃thermostatic GL Science InertsilTM ODS-3 column(150 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelengths were set at 220,280 nm.Syringin was used as an internal standard to calculate the relative correction factors of the other nine constituents,after which the content determination was made.RESULTS Ten constituents showed good linear relationships within their own ranges(r≥0.999 7),whose average recoveries were 98.53%-102.22%with the RSDs of 1.26%-2.68%.The result obtained by QAMS approximated those obtained by external standard method.CONCLUSION This accurate and specific method can be used for the quality control of Tianma Toufengling Capsules.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

The current status of exoskeletons was introduced in enhancing individual soldier's battlefield rescue capabilities,promoting the integrated use of battlefield rescue equipment,protecting medical personnel on the battlefield and assisting injured soldiers in rehabilitation training.The challenges of exoskeletons faced in human-machine interaction,power supply endurance,heavy overall structure,restricted movement and high cost were analyzed when applied to medical service support,and some suggestions were proposed accordingly including enhancing technology research and development,integrated application,communication and cooperation and personnel training.References were provided for the application of exoskeletons in China's medical service support.[Chinese Medical Equipment Journal,2024,45(3):71-75]

Osteonecrosis of the femoral head(ONFH)is a common orthopedic disease,and hip preservation surgery has high clinical value in the early stages of ONFH,especially for young and middle-aged patients.However,the repair of ONFH is heterogeneous,leading to inter-individual variations in the efficacy of hip preservation.Currently,the existing tissue-engineered scaffolds in the field of hip preservation are uncontrollable after implantation,making it difficult to achieve precise repair.Smart responsive materials have good biocompatibility and self-feedback capability.By combining them with therapeutic drugs to construct stimulus-responsive drug delivery systems,new possibilities are provided for the precise repair of ONFH.This paper reviews the research progress of smart responsive materials at home and abroad.Based on the response principles of various materials and the repair characteristics of ONFH,the application prospects of various smart responsive materials such as reactive oxygen species-responsive,fluid shear stress-responsive,and light/magnetic-responsive materials are discussed and prospected in the field of precise repair for ONFH,providing new ideas for the precise treatment of ONFH.

Respiratory infectious diseases (RID) are the major public health problems threatening the people's lives and health.Infection control (IC) is one of the effective tools to contain the occurrence and spread of RID.We collected the articles and data on IC published since January 1,2018 and summarized the achievements,problems,and challenges of IC from administrative control,management control,environment and engineering control,and personal protection in the medical institutions and public places in China.The efforts for IC vary in different regions and medical institutions of different levels.There are still links to be improved for IC from administrative control,management control,environment and engineering control,and personal protection,especially in community-level medical institutions and public areas.It is urgent to strengthen the implementation of IC policies and conduct IC precisely according to local situations.We proposed the following suggestions.First,the existing IC products and tools should be applied to precisely implement the IC measures;second,modern high technology should be employed to develop efficient and convenient IC products and tools;finally,a digital or intelligent IC platform should be built for monitoring infections,so as to contain the occurrence and spread of RID.
Humans ; COVID-19 ; Infection Control ; Communicable Diseases ; China/epidemiology*

Objective To explore the acute effects of NO₂ on children's respiratory hospitalization risk in Foshan City. Methods The daily average concentrations of six air pollutants such as NO2 and fine particulate matter, and meteorological data including average temperature and relative humidity in Foshan were collected from 2016 to 2019. Data on the daily number of children newly hospitalized for respiratory diseases (ECRH) in Foshan Women and Children Hospital were retrieved. Time series analysis was used to quantitatively evaluate the effect of daily NO2 concentration on the hospitalization risk of children with respiratory diseases. Results From 2016 to 2019, the average ECRH in the hospital was 10. The daily average concentrations of air pollutants NO₂, PM_2.5, PM₁₀, and SO₂ were 42.0 μg/m³, 35.3 μg/m³, 58.1 μg/m³, and 11.4 μg/m³, respectively. The air pressure, daily average temperature and relative humidity of atmosphere were 1008.4 Pa, 23.7℃ and 73.3%, respectively. ECRH was significantly correlated with the daily average concentration of NO2 (r=0.079, P<0.05). After excluding temperature, humidity and other influencing factors, for every 10 μg/m³ increase of NO2 concentration in the single pollutant model, the excess risk of ECHR in the hospital increased by 1.22% (95% CI: 0.06%, 2.40%) and 1.37% (95% CI: 0.23%, 2.53%) in lag0 and Lag1 day, respectively. The strongest effect appeared in lag0:7 with the excess risk increasing by 1.70% (95% CI:0.12%, 3.31%). In the NO₂ + SO₂ + CO + O₃_8h + PM_2.5 and NO₂ + SO₂ + CO + O₃_8h + PM₁₀ multi-pollutant models, significance correlation still existed between the daily average NO₂ concentration and ECHR in lag0, lag1 and lag0:1 to lag0:7. The strongest effect appeared in lag0:1, and the excess risks were 4.06% (95% CI: 1.83%, 6.34%) and 3.95% (95% CI: 1.85%, 6.09%), respectively. Dose-response relationship analysis showed a linear relationship between the daily average NO₂ concentration and ECHR, and the excess risk of new hospitalization gradually increased with the increase of daily average NO₂ concentration. Conclusion There was a significant correlation between NO₂ concentration and hospitalization risk of children with respiratory diseases in Foshan City, which suggests that the government should further strengthen the prevention and control of air pollution.