Objective To analyze the epidemiological characteristics and disease burden of liver cancer in Guangdong Province in 2020, and to provide a scientific foundation for the development of regionalized prevention and control strategies for liver cancer. Methods According to the cancer registry data of Guangdong Province, the incidence, mortality and age-standardized rate by Chinese standard population in 2020 were calculated to analyze the epidemiological characteristics of liver cancer. The disability adjusted life years (DALYs), year of life loss (YLL), year of lived with disability (YLD), and cause-eliminated life expectancy were used to assess the disease burden of liver cancer. Results In 2020, the crude incidence rate and the age-standardized incidence rate of liver cancer in Guangdong Province were 27.79/100 000 and 20.84/100 000，respectively, and the crude mortality rate and the age-standardized mortality rate of liver cancer were 25.49/100,000 and 17.64/100 000, respectively. The total DALY and DALY rate of liver cancer in Guangdong Province were 515 311 person-years and 513.83/100 000, respectively. After eliminating the causes of death from liver cancer, the life expectancy in Guangdong Province increased from 84.60 years to 84.99 years. All indicators consistently demonstrated that the burden of liver cancer was higher in males than that in females, and the burden of liver cancer was higher in rural areas than that in urban areas. Conclusion Liver cancer in Guangdong Province exhibits a high incidence, mortality and disease burden level in 2020. There are obvious differences of gender, age and region in cancer burden. It is necessary to strengthen liver cancer screening and diagnosis and treatment in men, the elderly and those in rural areas to reduce the burden of liver cancer gradually in Guangdong Province.

BackgroundLow medication compliance among patients with severe mental disorders increases the disease burden on both the patients' families and the society. Medication adherence is influenced by numerous factors. Traditional methods such as Logistic regression struggle to quantify the importance of these factors. By introducing Extreme Gradient Boosting （XGBoost） combined with Shapley Additive Explanations （SHAP）， enables the quantification of the relative contribution weights of each factor， providing support for identifying the core influencing factors. ObjectiveTo explore the influencing factors of medication adherence among patients with severe mental disorders in Zhuhai， aiming to provide references for optimizing patient management strategies. MethodsExtract the data of patients with severe mental disorders who were registered on the mental health system platform in Zhuhai City from January 1， 2023 to March 31， 2025. A total of 9 329 patients were finally included for analysis. Influencing factors were screened using univariate analysis and multivariate logistic regression analysis， and an XGBoost model combined with the SHAP algorithm was constructed to quantify the importance of each influencing factor. ResultsAmong 9 329 patients， 8 446 demonstrated medication adherence， yielding an adherence rate of 90.53%. Multivariable analysis identified several risk factors significantly associated with medication non-adherence， being unmarried （OR=1.237， 95% CI： 1.019–1.502） or divorced （OR=1.389， 95% CI： 1.038–1.832）， a diagnosis of mental retardation with psychiatric disorders （OR=3.025， 95% CI： 2.402–3.796） or paranoid psychosis （OR=5.117， 95% CI： 3.086–8.299）， a disease duration of 2–4 years （OR=1.355， 95% CI： 1.085–1.696）， 4–6 years （OR=2.143， 95% CI： 1.671–2.747）， or >6 years （OR=1.681， 95% CI： 1.365–2.079）， lack of guardian subsidies （OR=1.412， 95% CI： 1.099–1.801）， absence of a disability certificate （OR=1.900， 95% CI： 1.588–2.282）， not being enrolled in care and support groups （OR=1.384， 95% CI： 1.183–1.617） or community services （OR=1.313， 95% CI： 1.042–1.645）， and not cohabiting with a guardian （OR=1.257， 95% CI： 1.048–1.501）. Conversely， the enrollment in special outpatient disease programs （OR=0.716， 95% CI： 0.609–0.842） and a family history of mental illness （OR=0.713， 95% CI： 0.503–0.982） were identified as protective factors. The XGBoost model exhibited robust predictive performance， with a sensitivity of 0.433， specificity of 0.944， accuracy of 0.891， Area Under the Curve （AUC） of 0.837， and F1 value of 0.449. Feature importance ranking indicated that the top three factors were disease duration， diagnosis， and the acquisition of disability certificates. ConclusionPolicy-based support （acquisition of disability certificates， special outpatient disease enrollment） and clinical disease characteristics （disease duration， diagnosis type） are key factors affecting medication adherence among patients with severe mental disorders in Zhuhai City. ［Funded by Zhuhai Medical Research Project （number， 2220009000281）］

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Cerebral edema is characterized by fluid accumulation, and the glymphatic system (GS) plays a pivotal role in regulating fluid transport. Using the Tenecteplase system, magnesium salt of salvianolic acid B/ginsenoside Rg1 (SalB/Rg1) was injected intravenously into mice 4.5 h after middle cerebral artery occlusion and once every 24 h for the following 72 h. GS function was assessed by Evans blue imaging, near-infrared fluorescence region II (NIR-II) imaging, and magnetic resonance imaging (MRI). SalB/Rg1 had significant effects on reducing the infarct volume and hemorrhagic transformation score, improving neurobehavioral function, and protecting tissue structure, especially inhibiting cerebral edema. Meanwhile, the influx/efflux drainage of GS was enhanced by SalB/Rg1 according to NIR-II imaging and MRI. SalB/Rg1 inhibited matrix metalloproteinase-9 (MMP-9) activity, reduced cleaved β-dystroglycan (β-DG), and stabilized aquaporin-4 (AQP4) polarity, which was verified by colocalization with CD31. Our findings indicated that SalB/Rg1 treatment enhances GS function and attenuates cerebral edema, accompanying the regulation of the MMP9/β-DG/AQP4 pathway.
Animals ; Ginsenosides/administration & dosage* ; Brain Edema/etiology* ; Male ; Benzofurans/administration & dosage* ; Glymphatic System/diagnostic imaging* ; Mice ; Infarction, Middle Cerebral Artery/drug therapy* ; Aquaporin 4/metabolism* ; Disease Models, Animal ; Mice, Inbred C57BL ; Matrix Metalloproteinase 9/metabolism* ; Neuroprotective Agents/pharmacology* ; Depsides

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

OBJECTIVE: To discuss the development status of meridian diagnosis technology through the patent analysis, so as to obtain the hot spots of patents and provide the ideas for the research and development of new equipment. METHODS: The patent data of meridian diagnosis technology were searched from Chinese Think Tank of Traditional Chinese Medicine. The patent analysis and SWOT method were used to deeply explore the patent application of meridian diagnosis technology. RESULTS: Among 100 patents included, the inventions were mainly in Chinese mainland, and the invention institution was from Chengdu University of TCM. Since 2015, the number of patent application for meridian diagnosis technology was increasing, and up to a peak from 2020 to 2021. The main technological programs cover electrical, temperature and optical detection; and the application functions focus on the precise positioning of acupoints, and the diagnosis of zangfu diseases. CONCLUSION From the perspective of patents, it is suggested that the development of meridian diagnosis technology in China should pay attention to reducing the cost, improving the function, driving the standard formulation, strengthening safety measure, deepening human-machine interaction, exploring biological effect and optimizing the experimental platform. Through continuous innovation and breakthrough, the meridian diagnosis technology can be further matured and widely applied, so as to realize its comprehensive upgrade.
Meridians ; Humans ; Patents as Topic ; Medicine, Chinese Traditional/instrumentation* ; China ; Acupuncture Points

OBJECTIVE: To explore the dose-effect relationship between the number of acupuncture sessions and the efficacy for cervical vertigo (CV). METHODS: Literature regarding randomized controlled trials (RCTs) of acupuncture for CV was retrieved from CNKI, Wanfang, VIP, Web of Science, and PubMed databases from inception to June 28th, 2024. Studies were included if patients were treated solely with acupuncture and the core prescription included Baihui (GV20)-Fengchi (GB20)-neck-jiaji (EX-B2). Outcomes included the evaluation scale for cervical vertigo symptoms and function (ESCV) score and the mean blood flow velocity of vertebrobasilar arteries. The Cochrane risk of bias assessment tool 2.0 was used to evaluate study quality. Dose-effect Meta-regression analysis was performed using the robust-error Meta-regression (REMR) method in Stata 17.0 software. RESULTS: Nineteen RCTs were included with a total of 747 patients in the experimental groups. After 10 sessions of acupuncture, the ESCV score increased to 20.29 (95% CI: 16.77, 23.80), with a pre-post ESCV difference of 4.60 (95% CI: 2.59, 6.60) and an improvement rate of 0.36 (95% CI: 0.26, 0.46). After 20 sessions of acupuncture, the ESCV score increased to 21.55 (95% CI: 18.87, 24.22), with a difference of 5.42 (95% CI: 3.87, 6.97) and an improvement rate of 0.39 (95% CI: 0.31, 0.48). After 10 sessions of acupuncture, the improvement rates for left vertebral artery (LVA), right vertebral artery (RVA), and basilar artery (BA) mean blood flow velocities were 0.08 (95% CI: 0.05, 0.12), 0.09 (95% CI: 0.05, 0.12), and 0.11 (95% CI: 0.06, 0.15), respectively. After 14 sessions of acupuncture, the improvement rates reached their peaks: LVA [0.09 (95% CI: 0.06, 0.12)], RVA [0.10 (95% CI: 0.07, 0.13)], and BA [0.12 (95% CI: 0.07, 0.16)]. CONCLUSION A nonlinear dose-effect relationship existed between the number of acupuncture sessions and the efficacy for CV. Fourteen sessions were recommended as the optimal number of acupuncture treatments.
Humans ; Acupuncture Therapy ; Randomized Controlled Trials as Topic ; Vertigo/physiopathology* ; Treatment Outcome ; Acupuncture Points ; Regression Analysis ; Male ; Female

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.