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.

Hepatocellular carcinoma(HCC), the third leading cause of cancer-related death worldwide, is characterized by high mortality and recurrence rates. Common treatments include hepatectomy, liver transplantation, ablation therapy, interventional therapy, radiotherapy, systemic therapy, and traditional Chinese medicine(TCM). While exhibiting specific advantages, these approaches are associated with varying degrees of adverse effects. To alleviate patients' suffering and burdens, it is crucial to explore additional treatments and elucidate the pathogenesis of HCC, laying a foundation for the development of new TCM-based drugs. With emerging research on gut microbiota, it has been revealed that microbiota plays a vital role in the development of HCC by influencing intestinal barrier function, microbial metabolites, and immune regulation. TCM, with its multi-component, multi-target, and multi-pathway characteristics, has been increasingly recognized as a vital therapeutic treatment for HCC, particularly in patients at intermediate or advanced stages, by prolonging survival and improving quality of life. Recent global studies demonstrate that TCM exerts anti-HCC effects by modulating gut microbiota, restoring intestinal barrier function, regulating microbial composition and its metabolites, suppressing inflammation, and enhancing immune responses, thereby inhibiting the malignant phenotype of HCC. This review aims to elucidate the mechanisms by which gut microbiota contributes to the development and progression of HCC and highlight the regulatory effects of TCM, addressing the current gap in systematic understanding of the "TCM-gut microbiota-HCC" axis. The findings provide theoretical support for integrating TCM with western medicine in HCC treatment and promote the transition from basic research to precision clinical therapy through microbiota-targeted drug development and TCM-based interventions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Carcinoma, Hepatocellular/microbiology* ; Liver Neoplasms/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

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]

Objective To study the ability of radial basis function neural network(RBFNN)with different implementations for electrical impedance tomography(EIT)under real brain shapes,to evaluate the advantages and disadvantages of different approaches,and to provide a reference for the selection of practical imaging methods.Methods COMSOL Multiphysics was used to establish a multilayer 2D model with real structure based on brain CT and an EIT simulation dataset.The effects of the exact RBFNN,the orthogonal least squares-based RBFNN(OLS RBFNN)and the K-Means-based BRFNN(K-Means RBFNN)on the image reconstruction result were explored with the dataset constructed.The root mean square error(RMSE)and image correlation coefficient(ICC)were adopted to evaluate the imaging results.Results EIT could be completed with all the three RBFNNs without noise,and the exact RBFNN had the best results with average ICC and RMSE of 0.784 and 0.467,respectively,in the test set.The OLS RBFNN had the best imaging results at a hidden node of 50,with an average ICC and RMSE of 0.788 and 0.462,respectively.The K-Means RBFNN achieved the best imaging results at noise levels of 30,40,50,60,70 and 80 dB with stable ICC and RMSE and high robustness.Conclusion All the three RBFNNs can be used for brain EIT image reconstruction with their own advantages and disadvantages,and the RBFNN has to be selected for EIT reconstruc-tion based on considerations on actual conditions.[Chinese Medical Equipment Journal,2024,45(10):1-6]

Objective:To investigate the popularization of non-iodized salt among residents in water-borne high iodine areas and the iodine nutrition status of key populations in Shandong Province.Methods:In 2021, monitoring was conducted on a county-by-county basis in 47 counties (cities, districts, hereinafter referred to as counties) in 9 cities of Shandong Province, in accordance with the newly designated high iodine areas in the "Definition of Water Source High Iodine Areas and High Iodine Disease Areas" (GB/T 19380-2016) and historical high iodine areas. In each monitoring county, administrative villages with a median water iodine level greater than 100 μg/L were sorted by water iodine value, and a systematic sampling method was used to select 5 administrative villages as monitoring sites to investigate the water improvement situation and the iodine level of residents' drinking water. Totally 40 non boarding students aged 8 to 10 from one primary school and 20 pregnant women were selected in each village location to collect household edible salt samples and random urine samples for testing salt iodine and urine iodine levels, and the B-ultrasound method was used for thyroid examination in children.Results:A total of 364 high iodine administrative villages had been monitored, all of which had completed water improvement with a water improvement rate of 100.0%. The median iodine content in residential drinking water was 20.3 μg/L, ranging from 0.1 to 869.1 μg/L; and 11 464 edible salt samples were collected from residents' homes, with a non-iodized salt rate of 82.7% (9 481/11 464). A total of 9 197 urine samples from children and 2 335 urine samples from pregnant women were tested, with median urinary iodine levels of 219.0 and 139.0 μg/L, respectively. A total of 9 197 children were examined for thyroid, with 262 cases detected and a goiter rate of 2.8%.Conclusions:The rate of non-iodized salt in high iodine areas of Shandong Province still needs to be improved. Children's iodine nutrition is above the appropriate level, while pregnant women are at an iodine deficiency level.

Objective To analyze the antimicrobial susceptibility,molecular types,serotypes,virulence factors and resistance mechanisms of Streptococcus agalactiae(S.agalactiae)isolated from pregnant women with ad-vanced maternal age in Tangshan City,and provide basic data for the treatment,prevention and control of S.aga-lactiae infection.Methods 42 strains of S.agalactiae isolated from pregnant women with advanced maternal age in North China University of Science and Technology Affiliated Hospital as well as Tangshan Maternal and Child Health Hospital were collected.Detection of antimicrobial susceptibility and whole genome sequencing of 13 antimi-crobial agents were performed.Results The percentage of tetracycline,erythromycin,levofloxacin,and chloram-phenicol concurrently resistant strains was 7.1％,35.7％of the strains presented multidrug resistance to erythro-mycin,clindamycin,and levofloxacin.The carriage rates of resistance genes ermB and tetM were 66.7％and 47.6％,respectively.29 strains(69.0％)exhibited mutations in both gyrA and parC fluoroquinolone resistance determi-nants.42 strains of S.agalactiae belonged to 4 serotypes,namely ⅠB(35.7％),Ⅲ(33.3％),Ⅴ(26.2％),andⅠA(4.8％);and 11 sequence types(STs),with the highest proportion being ST10(35.7％)and ST19(31.0％);as well as 6 clonal complexes(CCs),among which CC19(42.9％)and CC12(35.7％)had the highest proportion.All S.agalactiae carried virulence factor-encoding genes of cfb,cylE,and pavA.Conclusion The molecular types and serotypes of S.agalactiae carried by pregnant women with advanced maternal age in Tangshan City pre-sent polymorphism,with obvious multidrug resistance,and carry multiple types of drug resistance genes and viru-lence genes.

Objective To compare and analyze the clinical outcomes of the ortho-bridge system(OBS)and the proximal humeral internal locking system(PHILOS)for the treatment of humeral surgical neck fractures(HSNF)in the elderly.Methods A retrospective analysis was conducted on the clinical data of 80 elderly patients with HSNF admitted to our hospital.Patients were divided into the two groups based on different surgical methods,among which 30 patients treated with OBS were included into the OBS group and 50 patients treated with PHILOS were included into the PHILOS group.The operation indicators,postoperative recovery indicators,serum bone metabolism indexes[osteocalcin(OCN),N-terminal propeptide of type Ⅰ precollagen(PINP)and alkaline phosphatase(ALP)],callus score,shoulder joint function scores[Constant-Murley scale(CMS)score and Neer score],and incidence of complications of the two groups were compared.Results The operation time in the OBS group was longer than that in the PHILOS group,and the fracture healing time was shorter than that in the PHILOS group(P＜0.05).The levels of serum OCN,PINP,and ALP 1 month and 3 months after surgery in the OBS group were higher than those in the PHILOS group(P＜0.05).The callus scores 1 month,2 months,and 3 months after surgery in the OBS group were higher than those in the PHILOS group(P＜0.05).The CMS and Neer scores 1 month and 3 months after surgery in the OBS group were higher than those in the PHILOS group(P＜0.05).The incisions of patients in the two groups recovered well after surgery,achieving gradeⅠ healing without complications such as wound infection or nonunion.Conclusion Compared with PHILOS,the application of OBS in the treatment of elderly patients with HSNF has a better short-term clinical outcome,and can promote fracture healing.