[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。

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

This study reports a new species of Culicoides(Avaritia)isolated from Xunke County, Heilongjiang Province, China. The new species, Culicoides(Avaritia)dongshanensis Liu et Wang, sp. nov., was identified and illustrated based on female adults. Its diagnostic characteristics are as follows: eyes contiguous over a short distance, with short interfacetal hair, antennal ratio(AR)of 1.20, palpal ratio(PR)of 2.16, wing length of 0.83 mm, mandible with 15 teeth, one pale spot in base cell M1, one pale spot in cell M4, two pale spots in cell A, and two unequal spermathecae. Type specimens were deposited at the Center for Disease Control and Prevention of the Northern Theater Command.

Objective To construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

X-ray is usually used to determine anatomy and localization during conventional permanent pacemaker implantation.But X-ray exposure might induce radiation injury to fetus.In this paper,we reported 2 cases successful double cavity permanent pacemaker implantation in pregnant women woman at 13 weeks of gestation under the guidance of transthoracic echocardiography.The postoperative pacing parameters were good,the whole process was finished with zero radiation,and there were complications during pregnancy.Both cases resulted in full-term pregnancies and the natural delivery of healthy newborns.Pacemaker electrodes were in normal position as confirmed by post-delivery X-ray examinations.

Objective:To observe the effects of acupuncture on the motor function of Parkinson disease(PD)model mice and to investigate the neuroprotective effects of acupuncture on PD from the perspective of cellular senescence.Methods:C57BL/6J mice were randomly divided into a normal control(NC)group,a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)group,an acupuncture(ACU)group,and a rasagiline(RAS)group,with 6 mice in each group.Except for the mice in the NC group,all mice were injected intraperitoneally with MPTP[30 mg/(kg·bw)]to establish a PD mouse model.After the models were successfully established,mice in the ACU group received acupuncture at Baihui(GV20)and bilateral Yanglingquan(GB34)for 15 min,once a day for 14 consecutive days.Mice in the RAS group were treated with gavage of rasagiline mesylate[0.5 mg/(kg·bw)],once daily for 14 d.Mouse balance and motor functions were detected using the mouse fatigue rotating rod apparatus.Immunohistochemistry staining was used to detect the number of tyrosine hydroxylase(TH)-positive neurons and the protein expression levels of special AT-rich sequence-binding protein 1(SATB1),p21,and p53 in the substantia nigra(SN)region of the mouse brain in each group.The glutathione peroxidase(GSH-Px)activity of mouse brain SN tissue was detected by enzyme-linked immunosorbent assay.The protein expression levels of interleukin(IL)-6 and senescence-associated β-galactosidase(SA-β-gal)in the SN tissue of mice in each group were detected by Western blotting.The relative expression of SATB1,p21,and p53 mRNA in the SN of each group was detected by real-time quantitative polymerase chain reaction.Results:Compared to the NC group,the overall rod performance(ORP)score,the number of TH-positive neurons,and GSH-Px activity in the SN region were significantly lower in the mice in the MPTP group(P<0.01);compared to the MPTP group,the ORP score,the number of TH-positive neurons,and GSH-Px activity were significantly increased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly increased(P<0.01);compared to the MPTP group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly decreased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the relative expression of SATB1 protein and mRNA in the SN of mice in the MPTP group was significantly decreased(P<0.01);compared to mice in the MPTP group,mice in the ACU group and the RAS group showed significant increases in the relative expression of SATB1 protein and mRNA(P<0.01 or P<0.05).Conclusion:Acupuncture can improve motor function and increase the number of TH-positive neurons in the SN of PD model mice.Its neuroprotective effect may relate to the regulation of the SATB1/p21 signaling pathway and the inhibition of cellular senescence-related biomarker expression in the SN.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.