OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

Extracellular vesicles (EVs) are pivotal mediators of intercellular communication within the tumor immune microenvironment (TME). They are broadly categorized into exosomes, microvesicles, and apoptotic bodies based on their distinct biogenesis pathways. Exosomes originate from the endosomal system via multivesicular body fusion, microvesicles bud directly from the plasma membrane, and apoptotic bodies are released during programmed cell death. By shuttling diverse bioactive cargoes—including proteins, lipids, and nucleic acids such as mRNA, miRNA, and DNA—EVs exert dual modulatory effects on tumor initiation, progression, and immune evasion. Importantly, EVs exhibit remarkable compositional heterogeneity that is intrinsically linked to their cellular origin. Tumor-derived EVs (TDEVs) are typically enriched with immunosuppressive molecules like PD-L1, TGF‑β, and miR-21, which promote tumor immune escape and metastasis. In contrast, EVs derived from immune cells, such as dendritic cells or cytotoxic T lymphocytes, often carry immunostimulatory components including antigens, co-stimulatory molecules, and granzymes, thereby potentiating anti-tumor immunity. This review systematically delineates the biogenesis and molecular composition of EVs, with a particular emphasis on their dynamic regulatory functions within the TME. Specifically, we discuss how EVs mediate intricate crosstalk between immune and tumor cells, facilitating signal transfer that reshapes immune surveillance. For instance, TDEVs can induce macrophage polarization toward an M2-like pro-tumor phenotype, while also suppressing natural killer cell cytotoxicity and dendritic cell maturation. The clinical utility of EV-associated biomarkers in liquid biopsy is increasingly recognized. Circulating EVs carry tumor-specific molecular signatures that mirror the genetic and proteomic alterations of primary tumors, enabling non-invasive early diagnosis, molecular subtyping, and real-time monitoring of therapeutic responses. Their natural biocompatibility, low immunogenicity, and intrinsic ability to traverse biological barriers make them ideal candidates for drug delivery systems. This review explores cutting-edge applications, including the use of EVs in immune checkpoint blockade therapy—for instance, engineered EVs displaying anti-PD-1 antibodies or carrying siRNA to silence immunosuppressive genes. Moreover, EV-based tumor vaccines are being developed, leveraging dendritic cell-derived EVs loaded with tumor antigens to elicit potent T cell responses. The feasibility of loading EVs with therapeutic molecules such as chemotherapeutic agents, oncolytic viruses, or CRISPR-Cas9 components is also under active investigation. The advent of engineered EVs has further expanded their therapeutic potential. Through surface modification or cargo encapsulation, EVs can be tailored for targeted delivery and controlled release, enhancing precision immunotherapy. However, several hurdles impede clinical translation. Current isolation and purification methods, such as ultracentrifugation and size-exclusion chromatography, suffer from low yield and purity. Distinguishing EV subpopulations remains technically challenging due to overlapping size and marker expression. Moreover, the lack of standardized protocols for EV production, characterization, and quality control poses significant barriers to regulatory approval and clinical adoption. Looking forward, the convergence of multi-omics technologies with artificial intelligence offers a powerful approach to decipher EV heterogeneity and identify robust diagnostic signatures. Machine learning algorithms can integrate proteomic, transcriptomic, and lipidomic data from large patient cohorts to construct predictive models for cancer diagnosis and prognosis. Concurrently, advances in bioengineering are enabling the design of next-generation EVs with enhanced targeting specificity, on-demand drug release, and reduced off-target effects. Future efforts should also focus on establishing good manufacturing practice (GMP)‑compliant production processes and conducting rigorous preclinical and clinical evaluations. In summary, this review provides a comprehensive overview of EV biology, their multifaceted roles in the TME, and their transformative potential in cancer diagnostics and therapeutics. By addressing current challenges and leveraging emerging technologies, EV-based strategies are poised to revolutionize precision oncology.

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.

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 evaluate the impact of an integrated management mode of prenatal diagnosis-postnatal treatment for congenital heart disease (CHD) on perioperative and long-term outcomes of the arterial switch operation (ASO), and to analyze the efficacy of ASO in a single center. Methods This retrospective study analyzed the clinical data of 183 children who underwent ASO at Guangdong Provincial People’s Hospital from 2018 to 2024. The cohort included 106 (57.9%) patients of transposition of the great arteries with intact ventricular septum (TGA/IVS), 61 (33.3%) patients of transposition of the great arteries with ventricular septal defect (TGA/VSD), and 16 (8.7%) patients of Taussig-bing anomaly (TBA). Perioperative indicators were compared between 91 patients in the prenatal-postnatal integrated management group (an integrated group) and 92 patients in the traditional management group (a non-integrated group). Long-term survival and reoperation rates were analyzed using Kaplan-Meier curves. Results The overall perioperative mortality rate was 4.9% (9/183), showing a downward trend year by year. The primary cause of perioperative mortality was low cardiac output syndrome (LCOS), which occurred in 12 patients (6.6% incidence) with a mortality rate of 75.0%. The integrated group had a higher proportion of males (89.0% vs. 72.8%, P<0.05) and lower body weight [3.1 (2.7, 3.3) kg vs. 3.3 (3.0, 3.7) kg, P<0.05] compared to the non-integrated group. The age at surgery was significantly earlier in the integrated group [7 (3, 10) d vs. 14 (9, 48) d, P<0.05], and all children in the integrated group underwent ASO within the optimal surgical window (100.0% vs. 82.6%, P<0.05). Intraoperatively, cardiopulmonary bypass time [173 (150, 207) min vs. 186 (159, 237) min, P<0.05] and aortic cross-clamp time [100 (90, 117) min vs. 116 (97, 142) min, P<0.05] were significantly shorter in the integrated group. Although the integrated group had longer postoperative mechanical ventilation time [145 (98, 214) h vs. 116 (77, 147) h, P<0.05] and higher 48-hour maximum vasoactive inotropic score [15 (10, 21) points vs. 12 (8, 16) points, P<0.05], there was no statistically significant difference in the incidence of severe complications (LCOS, necrotizing enterocolitis, extracorporeal membrane oxygenation) or mortality rate (3.3% vs. 6.5%, P=0.51) between the two groups, despite earlier surgical intervention and a higher proportion of critically ill cases in the integrated group. The length of hospital stay in the emergency surgery group was significantly shorter than that in the elective surgery group [20 (15, 28) d vs. 25 (21, 30) d, P<0.05], suggesting that early surgery may be of potential benefit. A total of 163 patients were successfully followed up for a median of 4.7 years, with a 5-year survival rate of 95.1% and a freedom from reintervention survival rate of 95.1%. There were no late deaths, and the most common postoperative complication was pulmonary artery stenosis. Conclusion The integrated management model allowed critically ill children with lower body weights to safely undergo surgery, significantly optimizing the timing of surgery and shortening intraoperative times. The long-term risk of reoperation after ASO is primarily concentrated on pulmonary artery stenosis, necessitating long-term follow-up and monitoring.

With the widespread application of low-dose computed tomography (CT), the detection rate of multiple lung cancers (MLCs) is gradually increasing. The diagnosis and treatment of MLCs have become a major challenge in clinical practice in thoracic surgery and oncology. In April 2025, the Lung Cancer Professional Committee of the China Anti-Cancer Association (CACA) organized multidisciplinary experts from both domestic and international fields to release the first edition of the CACA Expert Consensus on the Diagnosis and Treatment of Multiple Lung Cancers, providing systematic recommendations for the diagnostic system, molecularassessment strategies, and surgical and non-surgical management of MLCs. This article provides a detailed interpretation of the core content of this consensus and, by incorporating the latest research progress in the field, delves into the pathogenesis, precise diagnostic strategies, and individualized treatment pathways for multiple lung cancers, aiming to offer a more comprehensive reference for clinical practice.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveThe controllability changes of structural brain network were explored based on the control and brain network theory in young smokers, this may reveal that the controllability indicators can serve as a powerful factor to predict the sleep status in young smokers. MethodsFifty young smokers and 51 healthy controls from Inner Mongolia University of Science and Technology were enrolled. Diffusion tensor imaging (DTI) was used to construct structural brain network based on fractional anisotropy (FA) weight matrix. According to the control and brain network theory, the average controllability and the modal controllability were calculated. Two-sample t-test was used to compare the differences between the groups and Pearson correlation analysis to examine the correlation between significant average controllability and modal controllability with Fagerström Test of Nicotine Dependence (FTND) in young smokers. The nodes with the controllability score in the top 10% were selected as the super-controllers. Finally, we used BP neural network to predict the Pittsburgh Sleep Quality Index (PSQI) in young smokers. ResultsThe average controllability of dorsolateral superior frontal gyrus, supplementary motor area, lenticular nucleus putamen, and lenticular nucleus pallidum, and the modal controllability of orbital inferior frontal gyrus, supplementary motor area, gyrus rectus, and posterior cingulate gyrus in the young smokers’ group, were all significantly different from those of the healthy controls group (P<0.05). The average controllability of the right supplementary motor area (SMA.R) in the young smokers group was positively correlated with FTND (r=0.393 0, P=0.004 8), while modal controllability was negatively correlated with FTND (r=-0.330 1, P=0.019 2). ConclusionThe controllability of structural brain network in young smokers is abnormal. which may serve as an indicator to predict sleep condition. It may provide the imaging evidence for evaluating the cognitive function impairment in young smokers.

AIM To establish an HPLC-MS/MS method for the simultaneous content determination of dehydrodiisoeugenol,eugenol,costiolactone,dehydrocostiolactone,quercetin,isorhamnetin,luteolin,caffeic acid,gallic acid,protocatechuic acid,ellagic acid and kaempferol in Anshen Buxin Liuwei Pills,and to make chemical pattern recognition.METHODS The analysis was performed on a 35 ℃ thermostatic Shim-pack GST-HP C18 column(2.1 mm × 100 mm,3 μm),with the mobile phase comprising of methanol-water(containing 0.1％formic acid)flowing at 0.25 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive and negative ion scanning with multiple reaction monitoring mode.Subsequently,cluster analysis,principal component analysis and orthogonal partial least square-discriminant analysis were performed.RESULTS Twelve constituents showed good linear relationships within their own ranges(r≥0.999 0),whose average recoveries were 95.38％-105.00％with the RSDs of 1.91％-5.14％.Thirteen batches of samples were clustered into 3 types,ellagic acid,dehydrocodenolactone,dehydrodiisoeugenol,protocatechuic acid,gallic acid,quercetin and kaempferol were taken as potential quality differential markers.CONCLUSION This accurate,sensitive,stable and reproducible method can be used for the quality control and evaluation of Anshen Buxin Liuwei Pills.