Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

基于GS1 Digital Link的Web编码构建与案例应用

为探索GS1 Digital Link技术在产品物流中的应用潜力,分析研究了GS1系统和GS1 Digital Link的基本结构、编码特点以及技术优势,充分利用GS1 Digital Link技术可以为产品从源头到零售整个物流过程提供相关对象的Web地址编码的特点,以鲜活大闸蟹物流过程为例,构建了基于GS1 Digital Link的鲜活大闸蟹Web编码,为实现产品营销与追溯提供了标准化、动态化、多样化的编码数据支撑。

Recombinant chitinase-3-like protein 1 alleviates learning and memory impairments via M2 microglia polarization in postoperative cognitive dysfunction mice

Postoperative cognitive dysfunction is a seve re complication of the central nervous system that occurs after anesthesia and surgery,and has received attention for its high incidence and effect on the quality of life of patients.To date,there are no viable treatment options for postoperative cognitive dysfunction.The identification of postoperative cognitive dysfunction hub genes could provide new research directions and therapeutic targets for future research.To identify the signaling mechanisms contributing to postoperative cognitive dysfunction,we first conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the Gene Expression Omnibus GSE95426 dataset,which consists of mRNAs and long non-coding RNAs differentially expressed in mouse hippocampus3 days after tibial fracture.The dataset was enriched in genes associated with the biological process"regulation of immune cells,"of which Chill was identified as a hub gene.Therefore,we investigated the contribution of chitinase-3-like protein 1 protein expression changes to postoperative cognitive dysfunction in the mouse model of tibial fractu re surgery.Mice were intraperitoneally injected with vehicle or recombinant chitinase-3-like protein 124 hours post-surgery,and the injection groups were compared with untreated control mice for learning and memory capacities using the Y-maze and fear conditioning tests.In addition,protein expression levels of proinflammatory factors(interleukin-1βand inducible nitric oxide synthase),M2-type macrophage markers(CD206 and arginase-1),and cognition-related proteins(brain-derived neurotropic factor and phosphorylated NMDA receptor subunit NR2B)were measured in hippocampus by western blotting.Treatment with recombinant chitinase-3-like protein 1 prevented surgery-induced cognitive impairment,downregulated interleukin-1βand nducible nitric oxide synthase expression,and upregulated CD206,arginase-1,pNR2B,and brain-derived neurotropic factor expression compared with vehicle treatment.Intraperitoneal administration of the specific ERK inhibitor PD98059 diminished the effects of recombinant chitinase-3-like protein 1.Collectively,our findings suggest that recombinant chitinase-3-like protein 1 ameliorates surgery-induced cognitive decline by attenuating neuroinflammation via M2 microglial polarization in the hippocampus.Therefore,recombinant chitinase-3-like protein1 may have therapeutic potential fo r postoperative cognitive dysfunction.

EfficientNetB1 Deep Learning Model for Microscopic Lung Cancer Lesion Detection and Classification Using Histopathological Images

Cancer poses a significant threat due to its aggressive nature,potential for widespread metastasis,and inherent heterogeneity,which often leads to resistance to chemotherapy.Lung cancer ranks among the most prevalent forms of cancer worldwide,affecting individuals of all genders.Timely and accurate lung cancer detection is critical for improving cancer patients’treatment outcomes and survival rates.Screening examinations for lung cancer detection,however,frequently fall short of detecting small polyps and cancers.To address these limitations,computer-aided techniques for lung cancer detection prove to be invaluable resources for both healthcare practitioners and patients alike.This research implements an enhanced EfficientNetB1 deep learning model for accurate detection and classification using histopathological images.The proposed technique accurately classifies the histopathological images into three distinct classes:(1)no cancer(benign),(2)adenocarcinomas,and(3)squamous cell carcinomas.We evaluated the performance of the proposed technique using the histopathological(LC25000)lung dataset.The preprocessing steps,such as image resizing and augmentation,are followed by loading a pretrained model and applying transfer learning.The dataset is then split into training and validation sets,with fine-tuning and retraining performed on the training dataset.The model’s performance is evaluated on the validation dataset,and the results of lung cancer detection and classification into three classes are obtained.The study’s findings show that an enhanced model achieves exceptional classification accuracy of 99.8%.

Digital mapping of soil salinization based on Sentinel-1 and Sentinel-2 data combined with machine learning algorithms

Soil salinization is one of the most important causes of land degradation and desertification,especially in arid and semi-arid areas.The dynamic monitoring of soil salinization is of great significance to land management,agricultural activities,water quality,and sustainable development.The remote sensing images taken by the synthetic aperture radar(SAR)Sentinel-1 and the multispectral satellite Sentinel-2 with high resolution and short revisit period have the potential to monitor the spatial distribution of soil attribute information on a large area;however,there are limited studies on the combination of Sentinel-1 and Sentinel-2 for digital mapping of soil salinization.Therefore,in this study,we used topography indices derived from digital elevation model(DEM),SAR indices generated by Sentinel-1,and vegetation indices generated by Sentinel-2 to map soil salinization in the Ogan-Kuqa River Oasis located in the central and northern Tarim Basin in Xinjiang of China,and evaluated the potential of multi-source sensors to predict soil salinity.Using the soil electrical conductivity(EC)values of 70 ground sampling sites as the target variable and the optimal environmental factors as the predictive variable,we constructed three soil salinity inversion models based on classification and regression tree(CART),random forest(RF),and extreme gradient boosting(XGBoost).Then,we evaluated the prediction ability of different models through the five-fold cross validation.The prediction accuracy of XGBoost model is better than those of CART and RF,and soil salinity predicted by the three models has similar spatial distribution characteristics.Compared with the combination of topography indices and vegetation indices,the addition of SAR indices effectively improves the prediction accuracy of the model.In general,the method of soil salinity prediction based on multi-source sensor combination is better than that based on a single sensor.In addition,SAR indices,vegetation indices,and topography indices are all effective variables for soil salinity prediction.Weighted Difference Vegetation Index(WDVI)is designated as the most important variable in these variables,followed by DEM.The results showed that the high-resolution radar Sentinel-1 and multispectral Sentinel-2 have the potential to develop soil salinity prediction model.

基于Sentinel-1/2改进极化指数和纹理特征的土壤含盐量反演模型

目前Sentinel-1/2协同反演植被土壤含盐量的研究大多是基于Sentinel-2光谱信息和Sentinel-1后向散射系数,没有考虑Sentinel-2光谱信息容易受土壤亮度等信息影响,Sentinel-1后向散射系数容易受土壤粗糙度和水分影响。为进一步提高Sentinel-1/2协同反演植被土壤含盐量的精度,用水云模型对雷达卫星后向散射系数进行校正,消除植被影响;然后协同Sentinel-2纹理特征,基于VIP、OOB、PCA 3种变量筛选和RF、ELM、Cubist 3种机器学习回归模型构建植被土壤含盐量反演模型。研究结果表明:经过水云模型去除植被影响后的雷达后向散射系数及其极化组合指数与土壤含盐量的相关性有一定程度的提高。不同变量选择方法与不同机器学习方法耦合模型在反演土壤含盐量中,OOB变量筛选方法与RF、ELM和Cubist 3种机器学习方法的耦合模型精度最佳,建模集和验证集的R2都在0.750以上,且验证集的RMSE和MAE均最小;其中OOB-Cubist耦合模型精度最高,且R_(v)^(2)/R_(c)^(2)为0.955,具有良好的鲁棒性。研究可为机器学习协同物理模型、光学卫星协同雷达卫星在土壤含盐量反演中的进一步应用提供思路。

塔里木盆地顺北1号断裂带奥陶系碳酸盐岩储层结构表征及三维地质建模

综合利用地震、测井、岩心以及动态生产资料,对塔里木盆地顺北1号断裂带断控型碳酸盐岩储集体的内部结构进行了层级划分;基于层级划分,通过地震资料属性提取与转换、深度学习、基于目标示性点过程模拟以及离散裂缝网络模拟(DFN)等方法建立了三维地质模型,并以模型进行油气储量和油藏数值模拟,将拟合结果与实际生产数据进行对比。研究结果表明:(1)顺北1号断裂带奥陶系断控型储层按层级由大到小分为走滑断裂影响带、断控体、类洞穴、类洞穴内簇充填和裂缝带共5个层级。(2)走滑断裂影响带受应力差异影响具有分段性,可细分为挤压段、拉分段和平移段;断控体在拉分段发育断裂交会型、单支走滑型,在平移段发育双断裂交错型和两断裂交会型,在挤压段发育双断裂扭曲型和双断裂交会型,共有6种平面组合样式;类洞穴在地震剖面上呈串珠状反射特征;类洞穴内部分为栅体与栅间(基岩),其中栅体又可进一步分为簇(角砾带)、簇间(裂缝带),整体表现为栅状结构,簇的物性更好;裂缝带为类洞穴的主要储集空间,在簇内部比簇间更发育,在一间房组比鹰山组更发育,一间房组和鹰山组均以发育高角度裂缝为主,在两者连接处则以发育水平缝为主。(3)地质模型预测的油气储量与地质分析储量误差为1.75%,模型模拟的生产井地层压力及累产液结果与生产动态吻合度较高,拟合误差小于10%。

PAI-1和FV基因多态性与静脉血栓的临床意义

目的 一种新技术检测静脉血栓相关基因纤溶酶原激活物抑制剂-1(PAI-1)和凝血因子V(FV)基因多态性,分析清远地区人群基因频率分布情况,指导静脉血栓临床药物治疗。方法 提取2020年4月至2021年8月在清远市人民医院行静脉血栓基因检测的2 281例患者DNA,应用数字荧光分子杂交法检测PAI-1和FV基因多态性,并进行Sanger测序加以验证,大数据分析清远市人民医院就诊患者基因型分布频率,评估男、女性和心、脑血管疾病、肿瘤患者PAI-1和FV基因是否突变与发生静脉血栓的风险,指导抗血栓药物使用。结果 数字荧光分子杂交与Sanger测序结果完全符合(100%);大数据发现本地区人群PAI-1基因呈多态性分布(19.33%、50.33%、30.34%),而FV基因型突变极少,多为野生纯合型(99.91%);PAI-1和FV基因型频率和等位基因频率在男、女性和心、脑血管疾病、肿瘤患者人群中差异无统计学意义(P均>0.05);PAI-1基因多态性与疾病进程无明显相关性。结论 PAI-1基因检测对静脉血栓药物应用极具临床意义,可实现精准化个体治疗,但PAI-1基因多态性与其他疾病和性别无关。

视觉设计与数字动态融合在技能大赛与1+X证书考核中的策略探讨

本文探讨了视觉设计与数字动态在技能大赛和1+X等级证书考核中的应用与融合。探讨了技能大赛中视觉设计与数字动态的融合实践,包括深入理解大赛主题、选题与创意构思、技术实现与表现、故事讲述与情感传递,以及团队协作与项目管理等方面。最后,研究了1+X等级证书考核中视觉设计与数字动态的融合策略,涉及系统复习、模拟测试、实践项目准备、时间管理与策略调整,以及心态调整与信心建立等关键环节。

基于GF-1卫星遥感反演排水河沟水体溶存N_(2)O浓度模型对比研究

[目的]探究利用GF-1卫星数据反演水体溶存氧化亚氮(N_(2)O)浓度的可行性,为实现低成本、高效率的水质实时监测提供有效途径。[方法]以宁夏青铜峡灌区第1和第5排水河沟为研究对象,选取与排水河沟水体溶存N_(2)O浓度相关性高的GF-1卫星影像波段反射率和水质参数作为自变量,通过最优子集筛选法确定最优自变量组合,分别构建了多元线性回归、BP神经网络和支持向量机模型,对水体溶存N_(2)O浓度进行预测对比。[结果]水温(T)、溶解性有机碳(DOC)等是影响水体溶存N_(2)O浓度的主要因素,同时近红外(NIR)等卫星波段与水体溶存N_(2)O浓度变化趋势显著相关。当自变量包括T,NIR等7个因素时,模型预测效果最佳。在3种模型中,BP神经网络模型验证结果R^(2)为0.64,具有最高预测精度。[结论]GF-1卫星数据以及水质参数与水体溶存N_(2)O浓度存在复杂的相关性关系,且BP神经网络能够实现利用GF-1卫星数据较高精度地反演水体溶存N_(2)O浓度。

慢性间断缺氧通过上调大鼠海马HMGB1和NF-κB损伤学习记忆

目的:探索慢性间断缺氧(CIH)导致大鼠学习记忆功能障碍,以及对海马区高迁移率族蛋白1(HMGB1)和核转录因子-κB(NF-κB)表达的影响。方法:制作CIH大鼠模型,40只SD大鼠分为常氧组(normoxia)、缺氧4周组(CIH4组)、缺氧8周组(CIH8组)和缺氧12周组(CIH12组)。采用Morris水迷宫评估大鼠学习记忆能力,免疫组织化学染色和ELISA法检测大鼠海马区HMGB1和NF-κB的表达。结果:与常氧组相比,CIH12和CIH8组的逃避潜伏期延长,穿越平台次数和平台所在象限停留时间显著缩短,CIH4组的无显著差异。另外,常氧组海马区HMGB1和NF-κB的表达未见明显表达,CIH4组可见少许表达,CIH8组和CIH12组可见明显表达,同时CIH12组的表达显著高于CIH8组。结论:CIH可导致大鼠的学习记忆功能下降,且间断缺氧时间越长对其学习记忆功能的影响越显著。此外,CIH还导致海马区HMGB1和NF-κB的表达水平升高,并且缺氧12周比8周增加更为明显。

1+X证书制度下职业院校数字教材建设的障碍与解决路径

立足1+X证书制度背景,职业院校数字教材建设是推进书证融通、革新教学模式、促进职业教育现代化发展的重要抓手。然而,现阶段职业院校数字教材建设存在编写标准规范难、教材开发团队组建难、教材内容编纂难、教材开发及应用资源整合难、数字教材评价难等问题。对此,建议加速推动职业院校数字教材标准建设,搭建高质量综合性数字教材开发团队,厘清数字教材内容研发关键要素,打造职业院校数字教材资源共享平台,优化数字教材评价体系,力求推动1+X证书制度深度实施,实现职业教育高质量发展。

多目标系统化学习的PD-L1切片分析方法

在肿瘤尤其是如肺鳞癌(lung squamous cell carcinoma,LUSC)的非小细胞肺癌的治疗中,基于程序性死亡受体-配体1(programmed cell death-ligand 1,PD-L1)染色切片的阳性肿瘤细胞比例评分(tumor proportion score,TPS)可为治疗方案的选择提供重要依据。肿瘤细胞(tumor cell,TC)的许多参数对癌症诊断至关重要。虽然可以通过计算分析来预测这些参数,但很少有一个统一的框架可以同时获得细胞的不同病理信息。为此,提出了一种多目标学习框架(multi-objective learning pipeline,MOLP),从LUSC的PD-L1切片中预测TPS、细胞数目、细胞核轮廓和类别。主干网络包括两个分支:一个分支通过细胞分析估算TPS,另一个分支直接通过回归分析估算TPS。MOLP通过最小化两个分支的TPS预测差值来提高其鲁棒性。细胞分析支路可实现细胞核分割、分类和计数,不仅增强了TPS估计的可信度,还使得MOLP能够估计肿瘤细胞的外观参数以用于LUSC诊断。在大规模图像集上的实验结果证明了MOLP的可行性和有效性。MOLP预测的TPS与病理医师的评分呈现出统计学上的显著相关性:平均绝对误差仅为4.97(95%置信区间:-0.56~10.49),皮尔逊相关系数为0.97(p<0.001)。

过表达海马LINGO-1对小鼠学习和记忆能力及海马各亚区Spinophilin+树突棘的影响

目的 脑立体定位注射腺相关病毒特异性过表达海马LINGO-1,探讨其对小鼠空间学习和记忆能力以及海马各亚区体积和Spinophilin+树突棘的影响。方法 将7月龄雄性C57小鼠按照简单随机法分为对照组和LINGO-1过表达组,对照组小鼠海马立体定位注射携带绿色荧光的空载腺相关病毒(adeno-associated virus, AAV),LINGO-1过表达组小鼠海马立体定位注射同时携带绿色荧光和LINGO-1过表达载体的AAV。运用Morris水迷宫评估小鼠的空间学习和记忆能力,荧光定量PCR及免疫荧光染色方法分别检测小鼠海马内LINGO-1基因表达水平和各亚区荧光强度,体视学三维定量小鼠海马各亚区体积及Spinophilin+树突棘总数。结果 对照组和LINGO-1过表达组病毒注射前后体质量差异无统计学意义;LINGO-1过表达诱导小鼠海马LINGO-1的mRNA水平升高、荧光强度增强(P<0.01);与对照组相比,LINGO-1过表达组小鼠在Morris水迷宫实验中的表现明显更差(P<0.05);LINGO-1过表达诱导小鼠海马各亚区体积显著下降(P<0.05,P<0.01),Spinophilin+树突棘密度显著降低(P<0.01,P<0.05),Spinophilin+树突棘数量显著减少(P<0.05)。结论 海马立体定位注射过表达LINGO-1腺相关病毒能够特异性上调小鼠海马内LINGO-1水平,海马LINGO-1的异常高表达可导致小鼠海马体积减小及Spinophilin+树突棘突触丢失,并在一定程度上损伤其空间学习与记忆能力。

基于1+X证书制度的中职“岗课赛证”融通育人模式初探——以中职数字媒体艺术专业群建设为例

基于1+X证书制度的中职“岗课赛证”融通育人模式是开展实践技能培养的有效途径,有利于提高人才培养质量、科学评价中职学校的办学质量、促进产教融合及校企合作育人机制的创新和深度发展。在具体实践中,中职学校可以岗位能力需求为出发点制订发展规划,重新建构专业课程标准和教学内容,以专业课程改革为抓手积极推进“三教”改革,培养高素质技术技能人才,以各赛项为载体,全方位提升学生的职业技能水平,以职业技能等级证书为落脚点构建全新育人机制,实现课证融通。

Physics-embedded machine learning search for Sm-doped PMN-PT piezoelectric ceramics with high performance

Pb(Mg_(1/3)Nb_(2/3))O_(3)–PbTiO_(3)(PMN-PT)piezoelectric ceramics have excellent piezoelectric properties and are used in a wide range of applications.Adjusting the solid solution ratios of PMN/PT and different concentrations of elemental doping are the main methods to modulate their piezoelectric coefficients.The combination of these controllable conditions leads to an exponential increase of possible compositions in ceramics,which makes it not easy to extend the sample data by additional experimental or theoretical calculations.In this paper,a physics-embedded machine learning method is proposed to overcome the difficulties in obtaining piezoelectric coefficients and Curie temperatures of Sm-doped PMN-PT ceramics with different components.In contrast to all-data-driven model,physics-embedded machine learning is able to learn nonlinear variation rules based on small datasets through potential correlation between ferroelectric properties.Based on the model outputs,the positions of morphotropic phase boundary(MPB)with different Sm doping amounts are explored.We also find the components with the best piezoelectric property and comprehensive performance.Moreover,we set up a database according to the obtained results,through which we can quickly find the optimal components of Sm-doped PMN-PT ceramics according to our specific needs.

基于Keap1/Nrf2/HO-1通路探讨虎杖苷对衰老小鼠学习认知障碍的作用机制

目的研究虎杖苷对D-半乳糖致衰老模型小鼠的调节作用。方法将56只ICR小鼠(雌雄各半)分为正常组、模型组、阳性组、虎杖苷低、中、高治疗组,通过每日颈后部皮下注射D-半乳糖(500 mg·kg^(-1))建立衰老模型。造模期间,阳性组灌胃盐酸多奈哌齐片(0.75 mg·kg^(-1)),治疗组灌胃虎杖苷(40、70、100 mg·kg^(-1)),正常组给予等量生理盐水。通过筑巢实验、新型物体识别实验与Morris水迷宫实验评估小鼠学习认知能力;取小鼠心、肝、脾、肾、胸腺计算脏器指数;苏木精-伊红(HE)染色观察小鼠全脑组织病理变化;ELISA检测小鼠血清与全脑组织中T-SOD、MDA、GSH-Px、AchE水平;Western blot检测小鼠海马组织Keap1、Nrf2、HO-1蛋白表达水平。结果较模型组相比,阳性组与虎杖苷低、中、高剂量组小鼠的筑巢能力、对新物体的识别能力与水下寻找站台的能力有所上升;脏器指数增加;大脑皮层与海马组织的神经元损伤明显改善;血清与脑组织中T-SOD、GSH-Px活性升高,MDA、AchE活性下降;海马组织中Nrf2、HO-1蛋白表达水平上升,Keap1蛋白表达水平降低。结论虎杖苷对D-半乳糖致衰老模型小鼠的学习认知障碍具有改善作用,其机制可能与Keap1/Nrf2/HO-1通路有关。

技术赋能民主实践:数字政务平台价值实现的路径研究——以杭州1+X民意互动平台为例

数字技术为民主实践活动提供多种实现路径。数字政务平台通过搭建民主活动的新空间,开拓了民主实践新场域;赋予民主活动参与者新身份,建构民主实践新关系;重塑民主活动的新流程,生成了民主实践新理念。数字政务平台充分发挥技术优势,通过数字化手段,实现可视化的民情搜集、可互动的主体协商、数据支撑公共决策、数媒联动多元监督,是技术赋能民主实践的有益探索。由于平台建设质量参差不齐、信息协调机制不畅、用户与议题范围有限、数字服务与创新能力不高等原因,数字政务平台民主应用潜能有待挖掘、民主实践效能仍需提升,要通过扩大民主实践主体、丰富民主实践形式、拓展民主实践范围、提高民主实践质量、建立健全体制机制等手段,促进民主实践绩效的优化升级。

王浆主蛋白1(MRJP-1)及其对蜜蜂学习记忆影响的研究进展

蜂王浆由蜜蜂幼年工蜂所产,是蜂王及工蜂小幼虫的唯一食物来源,同时也因蜂王浆的丰富营养价值而为人们所熟知。蜂王浆主蛋白(MRJPs)是蜂王浆中最为丰富的水溶性蛋白,其中的MRJP-1除提供营养外,对蜜蜂的个体发育、神经系统发育、行为调控、级型分化等方面均有很好的生理调节作用。文章介绍了MRJP-1的理化特性和在蜜蜂体内的表达情况,并对MRJP-1在蜜蜂学习记忆方面的影响研究作简要概括,以期为王浆主蛋白在蜜蜂认知行为方面的研究提供一些思路和理论支撑。

SERINC1表达在肺癌中的预后作用及与肿瘤免疫浸润的关系

目的本研究旨在探讨血清素转运蛋白1(SERINC1)在肺癌预后中的作用。方法从GEO数据库下载了肺癌的单细胞测序scRNA数据,提取上皮细胞显著表达基因。同时Xena数据库下载TCGA数据,并进行了差异分析。将以上两者差异显著表达基因取交集,得到了上皮细胞差异基因。使用LASSO、随机森林、GBM、XGBoost等多种机器学习算法取交集,得到了FAM107A、SERINC1、MDK、GGCT、AVL9和FEZ16个交集基因。由于SERINC1在肺癌中还未被研究,对SERINC1进行了一系列的临床相关性分析,包括诊断ROC分析、表达分析、富集分析、生存分析、蛋白表达、蛋白互作分析以及免疫浸润分析。结果通过单细胞测序和机器学习筛选出了目标基因SERINC1。ROC分析SERINC1的AUC值高达0.972,显示出很高的诊断效能。K-M曲线显示,SERINC1表达高的患者的预后明显好于表达量低的患者,其HR值为0.71(95%CI:0.63~0.81)和0.48(95%CI:0.39~0.61),这表明基因表达量越高的患者预后更好。免疫浸润分析揭示,SERINC1与多种免疫细胞相关,且与多种T细胞的标志基因集相关。结论SERINC1是肺癌的一个有前景的预后标志物,且与免疫浸润相关。