1.Prognostic Utility of the Albumin-to-Alkaline Phosphatase Ratio in Head and Neck Cancer: A Systematic Review and Meta-Analysis
Yun-Ting WANG ; Adarsh KUDVA ; Yen-Ting LU ; Liang-Tseng KUO ; Chia-Hsuan LAI ; Yuan-Hsiung TSAI ; Chun-Ta LIAO ; Ku-Hao FANG ; Chung-Jan KANG ; Ethan I. HUANG ; Cheng-Ming HSU ; Geng-He CHANG ; Ming-Shao TSAI ; Yao-Te TSAI
Clinical and Experimental Otorhinolaryngology 2026;19(1):45-54
Objectives:
. The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC.
Methods:
. A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients.
Results:
. Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected.
Conclusion
. Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.
2.Epidemiological Characteristics and infection sources of cholera in China from 2005 to 2024
Fengfeng LIU ; Yang SONG ; Yao YI ; Jingyun ZHANG ; Siping HUANG ; Jie ZHANG ; Weili LIANG ; Liping WANG ; Yanping ZHANG ; Biao KAN ; Zhaorui CHANG
Chinese Journal of Preventive Medicine 2025;59(6):877-883
Objective:To analyze the epidemiological characteristics and infection sources of cholera in China from 2005 to 2024.Methods:A total of 2 066 cholera cases were included in the study, which were obtained from the China Disease Control and Prevention Information System (CDPCIS) of China CDC. The information on cholera clusters was downloaded from the National Public Health Emergency Event Surveillance System (PHEESS) of China CDC. A total of 128 cholera clusters were included and analyzed in this study. The epidemiological characteristics and infection sources of cholera were analyzed. The Jointpoint model was applied to analyze the incidence trend, and annual percentage change (APC) was also quantified.Results:From 2005 to 2024, a total of 2 066 cholera cases were reported, with an average of 103 cases reported annually. Specifically, the incidence showed a marked downward trend from 2004 to 2015 ( APC=-26.78%, P=0.006). During 2015-2024, the disease remained at low endemic levels, with an average of 18 reported cases annually ( APC=-2.68%, P=0.807). Cholera peak season was from May to October. A total of 24 provinces reported cholera cases, which were mainly distributed in Zhejiang, Fujian, Beijing, Jiangsu, Anhui, Guangdong, and Hainan provinces, accounting for 78.03% of the total cases. Pathogen surveillance indicated an alternating prevalence of Vibrio cholerae serogroups O1 and O139 among laboratory-confirmed cases between 2005 and 2024. There was a disparity in the dominant serogroup of Vibrio cholerae by region. The results from 128 cholera clusters indicated that cholera outbreaks frequently occurred in rural banquets (64.84%), followed by regular restaurants (13.28%). Among these, 63 clusters (49.22%) with identified infection sources indicated that foodborne transmission (95.24%) was the primary mode of cholera transmission, which mainly through seafood and aquatic products, such as soft-shelled turtles, shrimp and shellfish. The characteristics of cholera clusters caused by Vibrio cholerae serogroups O1 and O139 showed statistically significant differences in scale, attack rate, place of residence, setting, and infection source ( P<0.05). Conclusion:Cholera incidence has remained consistently low since 2015 in China, mainly in sporadic cases. Rural gatherings (e.g., wedding banquets) are the main settings for cholera clusters. The main infection sources are predominantly caused by cross-contamination due to improper processing practices of aquatic products, such as soft-shelled turtles.
3.Interpretation of the Standard Establishment Approach and Compilation Rationale for Metallic Pharmaceutical Packaging Standard Development in the 2025 Edition of the Pharmacopeia of the People's Republic of China
Fangfang ZHANG ; Rong CAI ; Wanling LAN ; Lei CHEN ; Lin YAO ; Hao DING ; Weiyi LU ; Yaju ZHOU ; Fenglan ZHANG ; Yuan LIU ; Kai XU ; Liang CHANG ; Yan LIU ; Feifei JIA ; Ying LI ; Yan JIANG ; Dandan WANG ; Shengli WU ; Yong SHEN ; Xiangwei XU ; Yanggege LYU
Herald of Medicine 2025;44(11):1745-1751
To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.
4.The clinical outcomes analysis of drug-coated balloon de novo coronary lesions left with untreated dissection
Zhi-yuan CHENG ; Wen-rui MA ; Zi-lei PAN ; Chang-sheng NAI ; Shang CHANG ; Li LIANG ; Yao-jun ZHANG ; Qian LI
Chinese Journal of Interventional Cardiology 2025;33(10):568-573
Objective To investigate the clinical prognosis of untreated residual coronary artery dissection treated with drug coated balloon(DCB).Methods A retrospective analysis was conducted on the clinical and imaging data of patients with primary coronary artery lesions(2.5-4.0 mm)treated with DCB under angiography guidance at Xuzhou Cancer Hospital,Xuzhou New Health Geriatric Hospital,and Peixian Guotai Hospital from September 2017 to April 2023.According to the observation of coronary artery dissection through angiography,the patients were divided into a dissection group and a non dissection group.The main endpoint of this study was the major adverse cardiovascular event(MACE)during a 12-month follow-up.Results A total of 381 patients were enrolled in the three research centers,with 30 cases(30 lesions)in the dissection group and 351 cases(367 lesions)in the non dissection group.There was no significant difference between the two groups in terms of age,gender,hypertension,hyperlipidemia,diabetes,smoking,previous myocardial infarction,previous percutaneous coronary intervention,coronary artery bypass grafting and other baseline clinical characteristics(all P>0.05).Except for the reference vessel diameter(P=0.049)and DCB pressure(P=0.032),there was no statistically significant difference in the characteristics of coronary angiography lesions between the two groups of patients(both P>0.05).During a 12-month follow-up,there was no statistically significant difference(P>0.05)in the incidence of MACE between the dissection group and the non dissection group after DCB treatment for primary coronary artery lesions in situ.Conclusions Untreated residual dissection after DCB treatment of de novo coronary lesions does not lead to an increase in clinical MACE.
5.Interpretation of the Standard Establishment Approach and Compilation Rationale for Metallic Pharmaceutical Packaging Standard Development in the 2025 Edition of the Pharmacopeia of the People's Republic of China
Fangfang ZHANG ; Rong CAI ; Wanling LAN ; Lei CHEN ; Lin YAO ; Hao DING ; Weiyi LU ; Yaju ZHOU ; Fenglan ZHANG ; Yuan LIU ; Kai XU ; Liang CHANG ; Yan LIU ; Feifei JIA ; Ying LI ; Yan JIANG ; Dandan WANG ; Shengli WU ; Yong SHEN ; Xiangwei XU ; Yanggege LYU
Herald of Medicine 2025;44(11):1745-1751
To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.
6.The clinical outcomes analysis of drug-coated balloon de novo coronary lesions left with untreated dissection
Zhi-yuan CHENG ; Wen-rui MA ; Zi-lei PAN ; Chang-sheng NAI ; Shang CHANG ; Li LIANG ; Yao-jun ZHANG ; Qian LI
Chinese Journal of Interventional Cardiology 2025;33(10):568-573
Objective To investigate the clinical prognosis of untreated residual coronary artery dissection treated with drug coated balloon(DCB).Methods A retrospective analysis was conducted on the clinical and imaging data of patients with primary coronary artery lesions(2.5-4.0 mm)treated with DCB under angiography guidance at Xuzhou Cancer Hospital,Xuzhou New Health Geriatric Hospital,and Peixian Guotai Hospital from September 2017 to April 2023.According to the observation of coronary artery dissection through angiography,the patients were divided into a dissection group and a non dissection group.The main endpoint of this study was the major adverse cardiovascular event(MACE)during a 12-month follow-up.Results A total of 381 patients were enrolled in the three research centers,with 30 cases(30 lesions)in the dissection group and 351 cases(367 lesions)in the non dissection group.There was no significant difference between the two groups in terms of age,gender,hypertension,hyperlipidemia,diabetes,smoking,previous myocardial infarction,previous percutaneous coronary intervention,coronary artery bypass grafting and other baseline clinical characteristics(all P>0.05).Except for the reference vessel diameter(P=0.049)and DCB pressure(P=0.032),there was no statistically significant difference in the characteristics of coronary angiography lesions between the two groups of patients(both P>0.05).During a 12-month follow-up,there was no statistically significant difference(P>0.05)in the incidence of MACE between the dissection group and the non dissection group after DCB treatment for primary coronary artery lesions in situ.Conclusions Untreated residual dissection after DCB treatment of de novo coronary lesions does not lead to an increase in clinical MACE.
7.Epidemiological Characteristics and infection sources of cholera in China from 2005 to 2024
Fengfeng LIU ; Yang SONG ; Yao YI ; Jingyun ZHANG ; Siping HUANG ; Jie ZHANG ; Weili LIANG ; Liping WANG ; Yanping ZHANG ; Biao KAN ; Zhaorui CHANG
Chinese Journal of Preventive Medicine 2025;59(6):877-883
Objective:To analyze the epidemiological characteristics and infection sources of cholera in China from 2005 to 2024.Methods:A total of 2 066 cholera cases were included in the study, which were obtained from the China Disease Control and Prevention Information System (CDPCIS) of China CDC. The information on cholera clusters was downloaded from the National Public Health Emergency Event Surveillance System (PHEESS) of China CDC. A total of 128 cholera clusters were included and analyzed in this study. The epidemiological characteristics and infection sources of cholera were analyzed. The Jointpoint model was applied to analyze the incidence trend, and annual percentage change (APC) was also quantified.Results:From 2005 to 2024, a total of 2 066 cholera cases were reported, with an average of 103 cases reported annually. Specifically, the incidence showed a marked downward trend from 2004 to 2015 ( APC=-26.78%, P=0.006). During 2015-2024, the disease remained at low endemic levels, with an average of 18 reported cases annually ( APC=-2.68%, P=0.807). Cholera peak season was from May to October. A total of 24 provinces reported cholera cases, which were mainly distributed in Zhejiang, Fujian, Beijing, Jiangsu, Anhui, Guangdong, and Hainan provinces, accounting for 78.03% of the total cases. Pathogen surveillance indicated an alternating prevalence of Vibrio cholerae serogroups O1 and O139 among laboratory-confirmed cases between 2005 and 2024. There was a disparity in the dominant serogroup of Vibrio cholerae by region. The results from 128 cholera clusters indicated that cholera outbreaks frequently occurred in rural banquets (64.84%), followed by regular restaurants (13.28%). Among these, 63 clusters (49.22%) with identified infection sources indicated that foodborne transmission (95.24%) was the primary mode of cholera transmission, which mainly through seafood and aquatic products, such as soft-shelled turtles, shrimp and shellfish. The characteristics of cholera clusters caused by Vibrio cholerae serogroups O1 and O139 showed statistically significant differences in scale, attack rate, place of residence, setting, and infection source ( P<0.05). Conclusion:Cholera incidence has remained consistently low since 2015 in China, mainly in sporadic cases. Rural gatherings (e.g., wedding banquets) are the main settings for cholera clusters. The main infection sources are predominantly caused by cross-contamination due to improper processing practices of aquatic products, such as soft-shelled turtles.
8.The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images
Yao-Wen LIANG ; Yu-Ting FANG ; Ting-Chun LIN ; Cheng-Ru YANG ; Chih-Chang CHANG ; Hsuan-Kan CHANG ; Chin-Chu KO ; Tsung-Hsi TU ; Li-Yu FAY ; Jau-Ching WU ; Wen-Cheng HUANG ; Hsiang-Wei HU ; You-Yin CHEN ; Chao-Hung KUO
Neurospine 2024;21(2):665-675
Objective:
This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans.
Methods:
Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness.
Results:
The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements.
Conclusion
Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.
9.The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images
Yao-Wen LIANG ; Yu-Ting FANG ; Ting-Chun LIN ; Cheng-Ru YANG ; Chih-Chang CHANG ; Hsuan-Kan CHANG ; Chin-Chu KO ; Tsung-Hsi TU ; Li-Yu FAY ; Jau-Ching WU ; Wen-Cheng HUANG ; Hsiang-Wei HU ; You-Yin CHEN ; Chao-Hung KUO
Neurospine 2024;21(2):665-675
Objective:
This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans.
Methods:
Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness.
Results:
The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements.
Conclusion
Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.
10.The Quantitative Evaluation of Automatic Segmentation in Lumbar Magnetic Resonance Images
Yao-Wen LIANG ; Yu-Ting FANG ; Ting-Chun LIN ; Cheng-Ru YANG ; Chih-Chang CHANG ; Hsuan-Kan CHANG ; Chin-Chu KO ; Tsung-Hsi TU ; Li-Yu FAY ; Jau-Ching WU ; Wen-Cheng HUANG ; Hsiang-Wei HU ; You-Yin CHEN ; Chao-Hung KUO
Neurospine 2024;21(2):665-675
Objective:
This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans.
Methods:
Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness.
Results:
The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements.
Conclusion
Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

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