[摘 要] 目的：探究外周血1型辅助性T细胞（Th1）/Th2/Th17细胞相关细胞因子IL-2、IL-4、IL-6、IL-10、IFN-γ、TNF-α、IL-17A对Ⅲ~Ⅳ期肺鳞状细胞癌（LSCC）患者一线免疫治疗联合化疗疗效和预后的预测价值及其动态变化的意义。方法：回顾性分析2020年1月至2023年12月在内蒙古医科大学附属医院接受一线免疫治疗联合化疗的58例Ⅲ~Ⅳ期LSCC患者的临床资料，采集基线及治疗2、4、6周期后和疾病进展时的外周血，用流式细胞术检测Th1/Th2/Th17细胞分泌的细胞因子水平，用受试者工作特性曲线（ROC）确定各细胞因子基线的最佳截断值，据此将患者分为高、低表达组；根据RECIST 1.1标准，将患者分为客观缓解（ORR）[完全缓解（CR） + 部分缓解（PR）]组、非ORR[（疾病稳定（SD） + 疾病进展（PD）]组、疾病控制（DCR）（CR + PR + SD）组和非DCR（即PD）组；根据PD-L1表达评分将患者分为PD-L1 ≥ 1%组和PD-L1 < 1%或未知组。比较组间疗效的差异；分析临床病理特征与疗效的相关性；用广义估计方程（GEE）评估细胞因子动态变化与疗效的关系；用Kaplan-Meier法绘制生存曲线，Log-Rank检验比较组间差异，COX比例风险回归模型进行单因素及多因素预后分析。结果：IL-2和IFN-γ高表达组患者的客观缓解率（ORR）显著高于低表达组患者（P < 0.001）。IL-2、IFN-γ高表达组和IL-10、TNF-α低表达组患者的疾病控制率（DCR）均显著高于对应低/高表达组（P < 0.001）。PD-L1 ≥ 1%组DCR显著高于PD-L1 < 1%或未知组（P < 0.001）。动态分析显示，在4周期及6周期时，有效组患者血清中IL-6表达水平显著低于无效组（P < 0.05），控制组IL-6表达水平显著低于未控制组（P < 0.001）；治疗前及6周期时有效组IFN-γ表达水平显著高于无效组（P < 0.05），治疗前控制组IFN-γ表达水平显著高于未控制组（P < 0.05）。生存分析显示，IL-2低表达组、IL-10高表达组、TNF-α高表达组和IFN-γ低表达组患者的中位PFS显著缩短（均P < 0.05）。COX多因素分析证实，治疗前IL-2 < 2.45 pg/mL和IL-10 ≥ 3.52 pg/mL 是PFS的独立危险因素。结论：外周血Th1/Th2/Th17细胞相关细胞因子的基线水平及动态变化对Ⅲ~Ⅳ期LSCC患者一线免疫治疗联合化疗的疗效和预后具有预测价值。

OBJECTIVE To promote the application of drones in emergency rescue and related fields， expand “low-altitude+ medical” rescue services， and advance the standardization of “low-altitude+medical” distribution services. METHODS The Consensus on Low-altitude Transport and Delivery Services for Emergency Medicines via Drones （2025 Edition） （hereinafter referred to as the Consensus） was jointly initiated by the Division of Therapeutic Drug Monitoring， Chinese Pharmacological Society and the Expert Committee on Precision Medication of the Guangdong Pharmaceutical Association. Guangzhou Red Cross Hospital served as the leading unit， organizing 53 multidisciplinary experts nationwide to participate in drafting and reviewing. A nominal group technique was employed to discuss and finalize the consensus outline， resulting in a preliminary draft. Delphi method was employed， and 11 external review experts were invited to conduct the evaluation. After the experts’ opinions were analyzed and integrated， the Consensus was finalized. RESULTS & CONCLUSIONS The finalized Consensus includes its purpose， principles， and applicable scenarios， basic requirements， and operational procedures for low-altitude transport and delivery of emergency medications； distribution requirements and precautions for controlled substances， fragile medications， and temperature-sensitive medications； and recommendations for emergency medications supplies suitable for the low-altitude transportation and distribution. The release of this Consensus is expected to provide guidance and support for the standardization of “low-altitude+medical” distribution services and the application of low-altitude economy in the healthcare sector.

ObjectiveTo investigate the intervention effects and mechanisms of the flavonoid hyperoside （Hyp） on lipopolysaccharide （LPS）-induced inflammation in the zebrafish model. MethodsZebrafish larvae were either microinjected with 0.5 g·L^-1 LPS or immersed in 1 g·L^-1 LPS for the modeling of inflammation. The larvae were then treated with Hyp at 25， 50， and 100 mg·L^-1 through immersion for four consecutive days. The inflammatory phenotypes were assessed by analyzing the mortality rate， malformation rate， body length， and yolk sac area ratio. Behavioral tests were conducted to evaluate the inflammatory stress responses， and macrophage migration was observed by fluorescence microscopy. Additionally， the mRNA levels of inflammation-related genes， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， chemokine C-C motif ligand 2 （CCL2）， chemokine C-X3-C motif receptor 1 （CX3CR1）， chemokine C-C motif receptor 2 （CCR2）， and genes associated with the Toll-like receptor 4 （TLR4）/myeloid differentiation factor 88 （MyD88）/nuclear factor-kappa B （NF-κB） signaling pathway， were measured by Real-time quantitative polymerase chain reaction（Real-time PCR）. ResultsCompared with the pure water injection group， the model group exhibited increased mortality， malformation rates and yolk sac area ratio （P0.01）， reduced body length （P0.01）， increased total swimming distance and high-speed swimming duration （P0.01）， and up-regulated mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.01）. Hyp at low， medium and high doses， as well as aspirin， reduced the mortality and malformation rates （P0.05，P0.01）， increased the body length （P0.05，P0.01）， decreased the yolk sac area ratio （P0.01）， reduced the high-speed swimming duration （P0.01）， and down-regulated the mRNA levels of TLR4， MyD88， NF-κB， IL-1β， IL-6， CCL2， CX3CR1， and CCR2 （P0.05，P0.01） compared with the model group. ConclusionHyp may modulate the TLR4/MyD88/NF-κB pathway to ameliorate inflammatory phenotypes and alleviate stress conditions in zebrafish， thereby exerting the anti-inflammatory effect.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective To explore the protective effect and related mechanism of Compound Baimai Powder(CBMP,a compound description of Mongolian medicine)on astrocytes after oxygen glu-cose deprivation and reoxygenation(OGD/R)injury.Methods Astrocyte model of OGD/R injury was subjected to simulate in vitro cerebral ischemia/reperfusion injury.Cultured astrocytes were randomly divided into normal group,OGD/R group,OGD/R+nimodipine group(10 μmol/L),OGD/R+low-and high-dose CBMP groups(25,50 μmol/L).Cell viability and apoptosis were de-tected with CCK-8 assay and flow cytometry,respectively.Western blotting was used to measure the expression levels of the proteins related to the nuclear factor erythroid-2-related factor-2(NRF2)/antioxidant response element and Janus kinase(J AK)/signal transducer and activator of transcription(STAT)signaling pathways.ELISA was employed to examine the levels of inflam-matory factors IL-1β,IL-6,and TNF-α,as well as oxidative stress molecules ROS,GSH,MDA and SOD.Results Compared to the normal group,the OGD/R group showed significant decreases in cell viability,NRF2 protein level,and SOD and GSH activities(P＜0.05,P＜0.01),and obvious increases in p-JAK and p-STAT proteins levels,contents of IL-1β,IL-6 and TNF-α,and ROS and MDA levels(P＜0.05,P＜0.01).High-dose CBMP treatment resulted in notably elevated cell via-bility and NRF2 protein level,while reduced levels of p-JAK[(1.20±0.20)vs(2.50±0.26)]and p-STAT[(1.15±0.25)vs(2.10±0.21)]proteins,IL-6[(30.33±5.20)vs(180.35±18.50)]and TNF-α[(50.12±8.24)vs(160.45±15.20)]when compared to the OGD/R group(P＜0.05,P＜0.01).Conclusion CBMP exerts protective effect on astrocytes against OGD/R injury.

Objective: To establish a prenatal non-invasive method for combined detection of fetal ABO, RhD, and RhCE blood group genotypes based on fluorescence quantitative PCR (FQ-PCR) technology, and to evaluate its clinical value in the early prenatal diagnosis of hemolytic disease of the fetus and newborn (HDFN). Methods: A total of 200 high-risk singleton pregnant women who underwent prenatal examinations in our hospital from January 2022 to December 2024 were prospectively enrolled. They were divided into four groups: the ABO incompatibility group (n=100), the RhD incompatibility group (n=50), the RhCE incompatibility group (n=50), and the control group (n=200). FQ-PCR technology was used to detect cell-free fetal DNA (cff-DNA) in maternal plasma, targeting the ABO system (261delG, 796C>A), exons 5/7 of the RHD gene, and the key loci of RhCE system (C/c, E/e). After delivery, the blood group of newborn was verified by serological testing of umbilical cord blood., and the hemolysis panel tests (direct antiglobulin test, free antibody test, and antibody release test) were performed to evaluate the detection consistency and identify high-risk factors. Results: The detection coincidence rates for ABO, RhD, and RhCE blood groups were 98.0% (98/100), 100.0% (50/50), and 96.0% (48/50), respectively. The incidence of HDFN in the ABO incompatibility group was 69.0% (69/100), which is significantly higher than that in the RhD incompatibility group (10.0%, 5/50) and the RhCE incompatibility group (2.0%, 1/50). Multivariate analysis identified maternal blood type O (OR=3.021), maternal RhD-negative (OR=5.253), and maternal age ≥35 years (OR=1.950) as independent risk factors for HDFN (all P<0.05). Conclusion: Prenatal non-invasive combined detection of multiple blood group antigen genotypes can significantly improve the efficiency of early diagnosis of HDFN and provide accurate early warning for high-risk pregnant women.

Purpose To investigate the diagnostic value of 7T ultra-high field MRI in deep medullary venography.Materials and Methods This prospective controlled study enrolled 47 healthy subjects from the First Affiliated Hospital of Army Medical University from May to August 2022.All participants underwent susceptibility-weighted imaging scans on both 7T and 3T MRI systems on the same day.Subjective image quality was evaluated using a Likert 5-point scale,while deep medullary vein visualization was assessed via a visual quartile grading system.Objective metrics,including signal-to-noise ratio and contrast-to-noise ratio,were used to evaluate venous image quality.Results There were statistically significant differences in subjective Likert 5-point scores between the 7T and 3T MRI group[5(5,5)vs.4(3,4);Z=234.50,P<0.001].Deep medullary vein visual quartile scores also showed significant differences between 7T and 3T MRI[0(0,0)]vs.[1(1,2);Z=47.00,P<0.001].Signal-to-noise ratio in the 7T group(1.50±0.35)was lower than that in the 3T group(5.45±1.83),while contrast-to-noise ratio(7.64±1.70)was higher than that in the 3T group(5.44±2.11),with both differences being statistically significant(t=14.54,-5.68,P<0.001).Conclusion 7T ultra-high field MRI demonstrates superior image quality for deep medullary venography visualization compared to 3T MRI.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.