Metabolic dysfunction-associated fatty liver disease （MAFLD） is one of the most prevalent chronic liver diseases worldwide， and currently there is still a lack of effective therapies. Bacteriophages are an important component of gut microbiota， and recent studies have shown that bacteriophages play a pivotal role in the pathological progression of MAFLD by reshaping microbiota structure， modulating intestinal barrier function， and regulating gut-liver axis signaling. Studies have also shown that there is a reduction in the diversity of bacteriophages in MAFLD patients， and the abundance of specific bacteriophages is closely associated with disease severity. The underlying mechanisms of bacteriophages involve the regulation of intestinal barrier， targeted clearance of pathogenic bacteria， promotion of the colonization of probiotic bacteria， and modulation of immune responses and the release of inflammatory cytokines. Animal models and preclinical trials have shown that targeted bacteriophage intervention strategies are expected to alleviate liver inflammation， improve steatosis， and ameliorate metabolic disorders. However， there are still challenges such as drug resistance of bacteriophage， the complexity of host-bacteriophage interactions， and safety issues in clinical translation. This article systematically elaborates on the regulatory mechanisms of bacteriophages in MAFLD and their application prospects in treatment， in order to provide a theoretical reference for future research and the development of bacteriophage-based therapies in this field.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

Traditional Chinese medicine （TCM） clinical trials face challenges such as low participant compliance， insufficient geographical coverage， and cost-effectiveness imbalances. Decentralized clinical trials （DCT）， enabled by digital technology for remote data collection and monitoring， offer a new direction for TCM clinical trial research. This article systematically reviews three novel clinical trial design models. Combining the holistic concept and indivi-dualized treatment characteristics of TCM， it analyzes the challenges currently faced in TCM DCT practice， including the digitization and standardization of TCM theory， data security， privacy protection and patient engagement difficu-lties， insufficient ethical review and regulatory system adaptation， inadequate personnel training， and a shortage of interdisciplinary talent. Addressing these challenges， the article proposes methodological recommendations for DCT implementation that align with the principles of TCM diagnosis and treatment. These recommendations include promoting the intelligentization and standardization of TCM practices， constructing a full-chain data security and privacy protection system， improving the ethical framework and clarifying regulatory responsibilities， and cultivating and building interdisciplinary talent and capabilities， which provide theoretical and technical references for establishing standardized DCT practices in TCM.

OBJECTIVE To investigate the ameliorative effect and mechanism of Euphorbia hirta L.-derived exosome-like nanovesicles（Eh-ENVs） on acetaminophen （APAP）-induced liver injury based on the nuclear factor erythroid 2 related factor 2 （Nrf2）/heme oxygenase-1 （HO-1）/NAD（P）H：quinone oxidoreductase 1 （NQO1） pathway. METHODS The safety of Eh-ENVs was evaluated by examining their effects on the viability of RAW264.7 and AML12 cells， as well as serum liver and kidney function indicators and histopathology of liver， lung， and other tissues in normal mice. A lipopolysaccharide （1 μg/mL）-induced RAW264.7 cell inflammation model was constructed to investigate the effects of 10 and 20 μg/mL Eh-ENVs on the mRNA expression of inflammatory factors and reactive oxygen species （ROS） level in model cells， and the uptake efficiency of Eh-ENVs by RAW264.7 cells was also examined. An APAP-induced liver injury mouse model was established to investigate the effects of 4 mg/kg Eh-ENVs on serum liver function indicators， liver histopathology， mRNA expression of inflammatory factors， malondialdehyde （MDA） level， superoxide dismutase （SOD） level， and mRNA and protein expressions related to the Nrf2/HO-1/NQO1 pathway in liver tissue of model mice. RESULTS In vitro results showed that Eh-ENVs had no inhibitory effect on the proliferation of RAW264.7 and AML12 cells；Eh-ENVs could be efficiently taken up by RAW264.7 cells and significantly reduced the mRNA expression of interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and ROS level in cells （ P ＜0.05）. In vivo results showed that 4 mg/kg Eh-ENVs had no obvious toxic side effects on normal mice，could significantly decrease the serum alanine transaminase （ALT） and aspartate transaminase （AST） levels in model mice （ P ＜0.05），upregulated/increased the mRNA expressions of IL-10， as well as the mRNA and protein expressions of Nrf2， HO-1， and NQO1， and SOD level in liver tissue （ P ＜0.05）， and down-regulated/decreased the mRNA expression of TNF-α， IL-1β and MDA level in liver tissue （ P ＜0.05）. CONCLUSIONS Eh-ENVs may activate the Nrf2/HO-1/NQO1 pathway to inhibit inflammatory response and alleviate oxidative stress， thereby improving APAP-induced liver injury.

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.

[摘 要] 目的：制备低亲和力的CD117 CAR-T细胞，探讨其对急性髓系白血病（AML）细胞Kasumi-1的体外杀伤效应。方法：调取CD117低亲和力抗体巴佐利单抗（barzolvolimab）和Fab-79D VH和VL序列，设计VH-(G4S)3-VL结构的单链抗体，分别构建带4-1BB共刺激分子的经典二代CAR分子，经基因合成后分别亚克隆至pMFG逆转录病毒载体，获得CD117-79D CAR和CD117-0159 CAR质粒。将两种CAR质粒分别包装制备逆转录病毒，检测其滴度合格后转导活化后的T细胞，构建CD117-79D CAR-T和CD117-0159 CAR-T细胞，采用流式细胞术检测两种CAR-T细胞的阳性率。将未转导T细胞与两种CAR-T细胞分别与CD117+ Kasumi-1细胞共培养，通过流式细胞术检测Kasumi-1细胞凋亡率，以评估两种CAR-T细胞的抗肿瘤活性。结果：成功构建CD117-79D CAR-T和CD117-0159 CAR-T细胞，其阳性率分别为（59.4 ± 2.6）%、（62.5 ± 1.2）%。未转导T细胞、CD117-79D CAR-T和CD117-0159 CAR-T细胞体外培养均能稳定增殖，且三者的增殖能力均无显著差异（均P > 0.05）。体外杀伤Kasumi-1细胞结果显示，不同效靶比条件下，CD117-79D CAR-T和 CD117-0159 CAR-T细胞较未转导T细胞展现出显著增强的杀伤能力（P < 0.05或P < 0.01），但两种CAR-T细胞的杀伤效率无显著差异（P > 0.05）。结论：成功构建低亲和力的CD117-79 CAR-T和CD117-0159 CAR-T细胞，体外实验证实其可有效杀伤CD117+ Kasumi-1细胞，为AML的靶向治疗提供了实验依据。

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Background Fatigue among distribution network live-line workers in complex operational environments has become increasingly severe and requires widespread attention. Objective To investigate the positive rates of fatigue and associated influencing factors of live-line power distribution workers, and to make a reasonable strategy to reduce the fatigue of front-line workers. Methods Power supply companies in Guangdong, Guangxi, and Yunnan provinces were selected by cluster sampling in 2023, and all front-line live-line workers in the selected companies were recruited. The questionnaire used in this study consisted of two parts: one was the Fatigue Scale-14 (FS-14) for investigating fatigue status and the other was for associated influencing factors. A FS-14 score greater than 3 points was defined as fatigue. \begin{document}$ {\chi }^{2} $\end{document} test and logistic regression were employed to analyze the factors affecting fatigue. Results A total of 1341 questionnaires were distributed, and 1217 valid questionnaires were recovered, with a valid response rate of 90.75%. The average fatigue score of the participants was (6.84±3.79) points, and a total of 1054 participants scored over 3, resulting a fatigue positive rate of 86.6%. The logistic regression model showed that working under extreme weather (OR=2.03, 95%CI: 1.38, 2.98), overtime 2-3 times a week (OR=5.24, 95%CI: 1.28, 21.40), overtime everyday (OR=6.95, 95%CI: 1.71, 28.27), frequent wrist rotation (OR=1.95, 95%CI: 1.08, 3.51), and leaning back slightly (OR=2.94, 95%CI: 1.19, 7.28) associated with higher positive rates of fatigue. Conclusion The high positive rate of fatigue among live-line power distribution workers suggests severe fatigue issues. Extreme weather conditions, working overtime frequency, and maintaining wrist rotation and backward bending postures during work are main factors affecting their fatigue.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.