[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。

ObjectiveHistorically documented Zhejiang Atractylodis Macrocephalae Rhizoma（Baizhu） possesses premium characteristics such as phoenix-like head and crane-like neck， pronounced sweetness， and fragrant aroma. However， its current market circulation is low， and the processed products with Zhejiang-style characteristics are at the risk of being lost. This study aims to preserve the ancient Zhejiang-style processing techniques and evaluate them using modern scientific methods. MethodsMultidimensional intelligent sensory evaluation was used to digitally characterize the "quality-structure" of the external appearance of nine-steamed and nine-processed Baizhu medicinal materials（intermediate processed products） and the "odor-taste" of the internal quality of its decoction pieces（slices）， and the appearance parameters were digitally characterized by colorimeter， texture analyzer， electronic nose and electronic tongue， the chemical composition was analyzed via ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）. Then， cluster analysis on the differences in odor between the medicinal materials（intermediate processed products） and decoction pieces（slices） of nine-steamed and nine-processed Baizhu was conducted， as well as the differences in taste between water-soluble and alcohol-soluble extracts of the decoction pieces（slices）， and the correlation analysis of chroma value-alcohol-soluble extract content-component response value. ResultsThe nine-steamed and nine-processed Baizhu had a dark brown to black epidermis， a brownish-yellow to brownish-gray cross-section， a slightly tough texture， a faint odor， and a slightly sweet， bitter and pungent taste. Texture analyzer measurements revealed minimal adhesion and maximum recovery in the middle section of the characteristic processed Baizhu， consistent with the processing endpoint of thorough steaming and cooking. The head section showed the highest internal hardness， elasticity and chewiness， indicating a denser texture in this area. The electronic nose sensor could clearly distinguish the difference between the medicinal materials and its decoction pieces， with a more significant clustering effect at 60 ℃ for 30 minutes compared to ambient temperature headspace for 2 hours， highlighting the significant impact of the baking degree before slicing on the quality. The electronic tongue taste signal map clearly distinguished the differences between water-soluble and alcohol-soluble extracts of nine-steamed and nine-processed Baizhu decoction pieces， and the addition of auxiliary materials during processing could enhance its alcohol-soluble extract content. A total of 82 chemical components were identified in the characteristic processed Baizhu. After processing， the contents of 58 components increased， while 24 components decreased. Correlation analysis revealed significant negative correlations（P<0.01） between ethanol-soluble extract content and colorimetric values of brightness（L^*）， yellow-bule value（b^*）， and total color difference（E^*_ab）. E^*_ab showed marked negative correlations（P<0.05） with the response values of isochlorogenic acid A and C. ConclusionThis study establishes a modern intelligent sensory evaluation model for multidimensional holographic characterization of nine-steamed and nine-processed Baizhu， clarifying the correlation between increased isochlorogenic acid content and the visual color appearance after different steaming cycles， as well as its intrinsic alcohol-soluble extracts. This provides a reference for quality evaluation and processing standards of the Zhejiang-style characteristic processed products.

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.

ObjectiveTo observe the therapeutic effect of Erchentang on depression in obese mice and explore the therapeutic mechanism. MethodsC57BL/6J mice were randomized into the control， model， metformin （0.65 g·kg^-1）， and low-， medium-， and high-dose （3.35， 6.7， and 13.4 g·kg^-1， respectively） Erchentang groups. Gavage was initiated simultaneously with modeling and continued for 28 days. The therapeutic effects of Erchentang were evaluated through behavioral tests， liver and brain indices， liver function， lipid indicators， and histopathological changes in the liver and brain tissue. RNA-seq technology was used to conduct transcriptomic analysis of mouse liver tissue， and differentially expressed genes were screened and subjected to Kyoto Encyclopedia of Genes and Genomes （KEGG） analysis. Key genes were further verified by Western blot and Real-time polymerase chain reaction（Real-time PCR）. ResultsBehavioral tests， liver function， lipid indicators， and histopathological changes in the liver and brain tissue all demonstrated that Erchentang had therapeutic effects on depression in obese mice. KEGG pathway enrichment analysis of transcriptomic data indicated that Erchentang treated depression in obese mice mainly through the peroxisome proliferator-activated receptor （PPAR） signaling pathway. Western blot and Real-time PCR results showed that compared with the model group， the low-， medium-， and high-dose Erchentang groups exhibited downregulated expression of fatty acid-binding protein （FABP） 1 （P<0.01） and upregulated expression of acyl-CoA oxidase （ACOX） 1， PPARα， cholesterol 7α-hydroxylase （CYP7A） 1， and phosphoenolpyruvate carboxy kinase （PCK） 1 （P<0.05） in the liver tissue. ConclusionErchentang exerts therapeutic effects on obesity-associated depression by regulating the PPAR signaling pathway and the expression of related genes FABP1， ACOX1， PPARα， CYP7A1， and PCK1.

Kynurenine pathway (KP) is a major catabolic route of tryptophan, generating a series of bioactive metabolites including kynurenine, kynurenic acid (KA), quinolinic acid, and 3-hydroxykynurenine. Beyond its fundamental role in amino acid metabolism, KP exerts critical regulatory functions in neurodevelopment, synaptic plasticity, and immune modulation. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with onset in early childhood, characterized by persistent deficits in social communication and restricted, repetitive behaviors. Despite extensive research, the etiological mechanisms underlying ASD remain highly complex and incompletely understood, involving genetic, environmental, and immunological factors. Emerging clinical evidence has consistently revealed a significant imbalance in KP metabolites in individuals with ASD, often accompanied by altered ratios of neuroprotective versus neurotoxic byproducts. However, the primary drivers of this metabolic dysregulation and its causative contribution to ASD pathogenesis are not yet fully elucidated. In this review, we systematically review the enzymatic steps of KP and the principal physiological functions of its major metabolites, with particular emphasis on their dual roles in neuroprotection and neurotoxicity. We then analyze the potential pathogenic mechanisms through which KP dysfunction may contribute to ASD, focusing on two interconnected etiological dimensions. First, KP imbalance can promote oxidative stress, which in turn triggers chronic inflammatory responses via microglial activation and release of pro-inflammatory cytokines, thereby disrupting neuronal homeostasis. Second, aberrant KP metabolism affects neurotransmitter systems, particularly glutamatergic and dopaminergic signaling, leading to impaired neural circuit development and synaptic pruning. By integrating current findings on the KP-ASD association, this review offers a comprehensive etiological framework and a clinically relevant paradigm. Furthermore, we highlight that specific KP metabolites, such as the KA/quinolinic acid ratio, hold promise as peripheral biomarkers for early diagnosis and disease stratification. Finally, we discuss the therapeutic potential of targeting KP enzymes or receptors for personalized intervention strategies, while acknowledging the challenges in translating these findings into clinical practice.

BACKGROUND:Pulmonary arterial hypertension is a destructive cardiopulmonary disease for which there is no cure.An association between plasma proteins and pulmonary arterial hypertension has been suggested,but the causal relationship has not been specifically elucidated.OBJECTIVE:To elucidate the causal relationship between plasma proteome and pulmonary arterial hypertension using a two-sample Mendelian randomization method,thereby searching for potential therapeutic targets for pulmonary arterial hypertension.METHODS:Plasma Protein Gene-Wide Association Analysis Statistics for 4 907 Aptamer Measurements in 35 559 Icelanders from the Icelandic Database;Genome-wide association analysis statistics for pulmonary arterial hypertension were obtained from the Finn Gen database,version R9,including 234 cases and 265 626 controls.Analyses were performed using Mendelian randomization and Bayesian co-localization analysis,the findings were examined using sensitivity analyses,and protein-protein interaction network maps were constructed to explore the causal relationship between plasma proteins and pulmonary arterial hypertension.RESULTS AND CONCLUSION:(1)The results of inverse variance weighting,maximum likelihood and Wald ratio methods showed 19 proteins causally associated with pulmonary arterial hypertension(P＜0.05).Among them,10 plasma proteins,including Beta-1,3-N-acetylglucosaminyltransferase manic fringe(odds ratio[OR]=0.12,95％confidence interval[CI]0.02-0.61,P=0.01)and interferon alpha/beta receptor 1(OR=0.45,95％CI 0.24-0.84,P=0.012),might be associated with a reduced risk of pulmonary arterial hypertension.In contrast,nine plasma proteins,such as glucoside xylosyltransferase 1(OR=3.48,95％CI 1.51-8.00,P=0.003)and plasminogen(OR=42.78,95％CI 2.49-734.31,P=0.01),might be associated with an increased risk of pulmonary arterial hypertension.After the false discovery rate was corrected,19 proteins remained significantly associated with pulmonary arterial hypertension.(2)Multiple sensitivity analyses such as the MR-Egger intercept test and leave-one-out method showed no horizontal multiplicity or heterogeneity in the results of the study,indicating the stability of the study's results.(3)Bayesian co-localization analysis showed that six plasma proteins,including plasminogen(PPH4=1.0)and glucoside xylosyltransferase 1(PPH4=0.94),had PPH4＞0.8,suggesting that plasma proteins and the genome-wide association study of pulmonary arterial hypertension had similar causal variance in terms of genetic association.(4)By constructing a protein-protein interaction network map,plasminogen,Annexin A1,fibrinogen gamma chain and matrix metalloproteinase 7 were found to be core proteins.(5)The article used Mendelian randomization analysis to reveal a potential causal association between 4 907 plasma proteins and pulmonary arterial hypertension,suggesting that plasma proteins may be potential therapeutic targets for pulmonary arterial hypertension.The core proteins identified in the study also provide a theoretical basis for further in-depth study of the pathophysiological mechanisms of pulmonary arterial hypertension.Secondly,analyses using the large-scale international databases of Iceland and FinnGen provide new research directions and treatment ideas for pulmonary arterial hypertension in specific populations and environments,as well as ideas and methods that can be used to prevent and treat pulmonary arterial hypertension in China.