1.Research on erythrocyte-liposome drug delivery system for targeted therapy of lung metastatic triple-negative breast cancer
Xiang LI ; Xunyi YOU ; Xiaocheng LI ; Hong WANG ; Rui ZHONG ; Jiaxin LIU ; Limin CHEN ; Ye CAO
Chinese Journal of Blood Transfusion 2026;39(2):180-187
Objective: To prepare the erythrocyte-liposome drug delivery system to enhance the therapeutic effect of drugs on tumors and inhibit tumor metastasis. Methods: This study prepared and characterized paclitaxel (PTX)-plerixafor (AMD3100) liposomes (Lips), developed the erythrocyte-liposome drug delivery system, and evaluated its targeting efficiency and therapeutic efficacy through a series of in vitro cellular and in vivo animal experiments. Results: The particle size of PTX-AMD-Lips was (186.4±0.83) nm. Drug encapsulation efficiency of PTX-AMD-Lips was (75.50±5.27)% for PTX and (88.31±2.45)% for AMD. The Binding efficiency between RBC and liposomes in the drug delivery system was (69.93±2.55)%. Vitro cellular experiments revealed that PTX-AMD-Lips significantly inhibited tumor cell migration. In vivo animal experiments, the erythrocyte-liposome drug delivery system significantly increased drug accumulation in the lungs. At the experimental endpoint, the quantitative fluorescence signal of tumor size measured (4.04±0.44)×10
for the PTX-Lips group, and (5.14±3.40)×10
for the RBC-PTX-AMD-Lips group. Conclusion: The erythrocyte-liposome drug delivery system could enhance the lung-specific targeting capability of liposomes, kill tumor cells and suppress further metastasis effectively.
2.Diagnostic Techniques and Risk Prediction for Cardiovascular-kidney-metabolic (CKM) Syndrome
Song HOU ; Lin-Shan ZHANG ; Xiu-Qin HONG ; Chi ZHANG ; Ying LIU ; Cai-Li ZHANG ; Yan ZHU ; Hai-Jun LIN ; Fu ZHANG ; Yu-Xiang YANG
Progress in Biochemistry and Biophysics 2025;52(10):2585-2601
Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.
3.Rapid health technology assessment of insulin icodec for the treatment of type 2 diabetes mellitus
Jie LI ; Hong LI ; Guanji CHEN ; Xiaoyan CHANG ; Xiang YANG ; Zhitao JIANG
China Pharmacy 2025;36(22):2856-2861
OBJECTIVE To comprehensively evaluate the efficacy, safety and cost-effectiveness of insulin icodec in treating type 2 diabetes mellitus (T2DM), providing evidence-based guidance for new drug selection in hospital and clinical medication decision-making. METHODS PubMed, Cochrane Library, Embase, CNKI, Wanfang, VIP and foreign health technology assessment (HTA) websites were searched by using rapid health technology assessment from inception to 15 July 2025 for systematic reviews/meta-analyses, pharmacoeconomic studies, and HTA reports on insulin icodec in the treatment of T2DM. After data extraction and quality assessment, the findings of the included studies were analyzed descriptively. RESULTS Ten systematic reviews/meta-analyses and three pharmacoeconomic studies were included. Among them, 4 systematic reviews/meta-analyses were of high quality; the overall quality of the 3 pharmacoeconomic studies was relatively good. Regarding efficacy, insulin icodec was superior to once-daily basal insulin in reducing glycated hemoglobin (HbA1c) and in achieving the target of HbA1c<7% (P<0.05). No significant differences were observed between icodec insulin and comparators in lowering fasting plasma glucose (P>0.05). For safety, insulin icodec did not increase the incidence of any adverse events (AEs), serious AEs, clinically significant hypoglycemia (random glucose<3 mmol/L), injection-site reactions, or allergic reactions, compared with once-daily basal insulin overall (P> 0.05); however, insulin icodec was associated with a significant increase in body weight (P<0.05). Domestic economic evaluations indicated that insulin icodec was more cost-effective than insulin glargine and insulin degludec when its annual costs were in the range of 784.90-1 145.96 and 597.66-736.34 US dollars, respectively. CONCLUSIONS Insulin icodec demonstrates favorable efficacy and safety profiles in the treatment of T2DM; however, attention should be paid to the risk of weight gain. Under China’s healthcare system, insulin icodec demonstrates greater economic value only when the patient’s weekly required basal insulin dose falls within a specific range,and clinical practice requires individualization.
4.The Singapore Green Plan 2030: occupational health hazards in the Singapore green economy.
Wei Xiang LIM ; Mei Ling Licia TAN ; Tzu Li Sylvia TEO ; Wee Hoe GAN ; Shiu Hong Joshua WONG
Singapore medical journal 2025;66(4):181-189
The Singapore Green Plan 2030 was released by the Singapore government to set targets for sustainability by 2030. The adoption of novel technologies, processes and substances creates new jobs, and such developments bring about new challenges and risks for both employers and workers. Beyond emerging hazards, traditional hazards still remain, but they may take on new forms through new work processes. This review aims to provide an overview of the potential occupational health issues we may encounter or anticipate in these key sectors: solar energy, waste management and recycling, green buildings, electric vehicles and battery recycling, and sustainable fuels. While existing Occupational Safety and Health regulations in Singapore serve as a foundation, there may be gaps in addressing the specific hazards and risks associated with green jobs. In this review, we propose and outline possible approaches to the protection of worker safety and health.
Singapore
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Humans
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Occupational Health
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Recycling
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Waste Management
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Solar Energy
;
Occupational Exposure
5.Effects of honey-processed Astragalus on energy metabolism and polarization of RAW264.7 cells
Hong-chang LI ; Ke PEI ; Wang-yang XIE ; Xiang-long MENG ; Zi-han YU ; Wen-ling LI ; Hao CAI
Acta Pharmaceutica Sinica 2025;60(2):459-470
In this study, RAW264.7 cells were employed to investigate the effects of honey-processed
6.International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025).
Sheng-Sheng ZHANG ; Lu-Qing ZHAO ; Xiao-Hua HOU ; Zhao-Xiang BIAN ; Jian-Hua ZHENG ; Hai-He TIAN ; Guan-Hu YANG ; Won-Sook HONG ; Yu-Ying HE ; Li LIU ; Hong SHEN ; Yan-Ping LI ; Sheng XIE ; Jin SHU ; Bin-Fang ZENG ; Jun-Xiang LI ; Zhen LIU ; Zheng-Hua XIAO ; Jing-Dong XIAO ; Pei-Yong ZHENG ; Shao-Gang HUANG ; Sheng-Liang CHEN ; Gui-Jun FEI
Journal of Integrative Medicine 2025;23(5):502-518
Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy*
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Humans
;
Medicine, Chinese Traditional/methods*
;
Practice Guidelines as Topic
;
Drugs, Chinese Herbal/therapeutic use*
7.Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine.
Xin-Ran DU ; Meng-Yi WU ; Mao-Can TAO ; Ying LIN ; Chao-Ying GU ; Min-Feng WU ; Yi CAO ; Da-Can CHEN ; Wei LI ; Hong-Wei WANG ; Ying WANG ; Yi WANG ; Han-Zhi LU ; Xin LIU ; Xiang-Fei SU ; Fu-Lun LI
Journal of Integrative Medicine 2025;23(6):641-653
Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy*
;
Humans
;
Medicine, Chinese Traditional/methods*
;
Integrative Medicine
;
Drugs, Chinese Herbal/therapeutic use*
;
Practice Guidelines as Topic
8.Association between Fish Consumption and Stroke Incidence Across Different Predicted Risk Populations: A Prospective Cohort Study from China.
Hong Yue HU ; Fang Chao LIU ; Ke Yong HUANG ; Chong SHEN ; Jian LIAO ; Jian Xin LI ; Chen Xi YUAN ; Ying LI ; Xue Li YANG ; Ji Chun CHEN ; Jie CAO ; Shu Feng CHEN ; Dong Sheng HU ; Jian Feng HUANG ; Xiang Feng LU ; Dong Feng GU
Biomedical and Environmental Sciences 2025;38(1):15-26
OBJECTIVE:
The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks.
METHODS:
A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI).
RESULTS:
During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43).
CONCLUSION
Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans
;
China/epidemiology*
;
Male
;
Female
;
Stroke/etiology*
;
Middle Aged
;
Prospective Studies
;
Incidence
;
Aged
;
Animals
;
Fishes
;
Risk Factors
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Diet
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Seafood
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Adult
;
Cohort Studies
9.Waist Circumference Status and Distribution in Chinese Adults: China Nutrition and Health Surveillance (2015-2017).
Jing NAN ; Mu Lei CHEN ; Hong Tao YUAN ; Qiu Ye CAO ; Dong Mei YU ; Wei PIAO ; Fu Sheng LI ; Yu Xiang YANG ; Li Yun ZHAO ; Shu Ya CAI
Biomedical and Environmental Sciences 2025;38(6):757-762
10.pLM4ACP: a model for predicting anticancer peptides based on machine learning and protein language models.
Yitong LIU ; Wenxin CHEN ; Juanjuan LI ; Xue CHI ; Xiang MA ; Yanqiong TANG ; Hong LI
Chinese Journal of Biotechnology 2025;41(8):3252-3261
Cancer is a serious global health problem and a major cause of human death. Conventional cancer treatments often run the risk of impairing vital organ functions. Anticancer peptides (ACPs) are considered to be one of the most promising therapeutic agents against common human cancers due to their small sizes, high specificity, and low toxicity. Since ACP recognition is highly limited to the laboratory, expensive, and time-consuming, we proposed pLM4ACP, a model for predicting ACPs based on machine learning and protein language models. In this model, the protein language model ProtT5 was used to extract the features of ACPs, and the extracted features were input into the support vector machine (SVM) classification algorithm for optimization and performance evaluation. The model showcased significantly higher accuracy than other methods, with the overall accuracy of 0.763, F1-score of 0.767, Matthews correlation coefficient of 0.527, and area under the curve of 0.827 on the independent test set. This study constructs an efficient anticancer peptide prediction model based on protein language models, further advancing the application of artificial intelligence in the biomedical field and promoting the development of precision medicine and computational biology.
Machine Learning
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Antineoplastic Agents/chemistry*
;
Humans
;
Peptides/chemistry*
;
Support Vector Machine
;
Algorithms
;
Computational Biology/methods*
;
Neoplasms/drug therapy*

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