脂质纳米粒-mRNA递送系统及其在嵌合抗原受体T细胞治疗中的应用

尽管嵌合抗原受体（CAR）T细胞治疗在血液系统恶性肿瘤患者中取得了显著的临床疗效，但需要进一步优化。脂质纳米粒（LNP）-信使核糖核酸（mRNA）递送系统作为一种非病毒性基因载体运用于CAR-T细胞治疗研究中，一方面通过LNP将密封蛋白-6 mRNA靶向递送至抗原提呈细胞，从而实现抗原提呈细胞辅助性增强密封蛋白-6靶向的CAR-T细胞的功能，以进一步诱导对实体瘤的清除；另一方面，通过LNP将成纤维细胞激活蛋白（FAP）CARmRNA靶向递送至T细胞，实现体内FAP靶向的CAR-T细胞的制备，以通过阻断心脏纤维化过程达到治疗急性心肌损伤的目的。在CAR-T细胞研究和治疗中，LNP-mRNA递送系统具有不与细胞基因组整合、价格便宜、毒副作用小及可修饰等优点，亦存在蛋白瞬时表达导致调控细胞功能的持久性不足及制备等方面的技术局限性。本文综述了LNP-mRNA递送系统及其在CAR-T细胞治疗中的应用研究。     

371名大学生微信朋友圈人格、自我呈现策略与情绪表达的关系

目的 探究大学生微信朋友圈人格、自我呈现策略和情绪表达间的关系。方法 采用社交网络自我呈现策略问卷、艾森克人格问卷简式量表、伯克利情绪表达问卷,对随机抽取的371名大学生进行调查。结果 ⑴外倾型人格总分与真实自我呈现策略总分呈正相关(r=0.170,P=0.001),与正性情绪表达呈正相关(r=0.166,P=0.001),与情绪表达强度呈正相关(r=0.184,P=0.001),真实自我呈现策略与正性情绪表达呈正相关(r=0.239,P=0.001)。⑵真实自我呈现策略在外倾型人格与正性情绪表达的关系中存在部分中介效应。结论 371名大学生的外倾型人格、真实自我呈现策略与正性情绪表达关系密切,真实自我呈现策略在外倾型人格与正性情绪表达的关系中存在部分中介效应。     

外周血单个核细胞内人类免疫缺陷病毒DNA和RNA定量对病毒转录活性的区分

目的基于人类免疫缺陷病毒Ⅰ型(HIV-1)感染者外周血单个核细胞(PBMCs)中HIV-1总DNA和RNA定量检测结果对感染细胞内病毒的转录活性进行区分。方法采集2017年10月至2018年12月于哈尔滨医科大学附属第四医院感染科就诊的HIV-1感染者血液样本,分离PBMCs细胞,采用PCR荧光探针法对PBMCs细胞内HIV-1总DNA和RNA进行定量检测,并计算两者比值(Ratio)。根据Ratio值筛选出HIV-1转录活跃组样本和相对非活跃组样本,另外选择健康人PBMCs样本作为对照组。对3组样本进行基因转录组表达谱检测以及人口特征差异性检验,并对基因表达谱检测结果进行主成分分析以验证对3组样本病毒转录活性区分的准确性。结果从60例感染HIV-1患者的PBMCs样本中筛选出HIV-1转录活跃组样本(10例)和相对非活跃组样本(11例),另外选择6例健康人PBMCs样本作为对照组。其中转录活跃组样本Ratio值为165.2~738.93,平均为(339.27±189.68);相对非活跃组Ratio值为4.67~42.39,平均为(17.65±11.78)。转录活跃组和相对非活跃组样本间的CD4+T细胞计数(P=0.049)和Ratio值(P<0.001)差异均具有统计学意义;3组样本年龄(P=0.989)和性别(P=0.650)分布差异无统计学意义。对3组样本的PBMCs基因表达谱主成分分析结果显示:对照组与HIV-1感染者(包括转录活跃组和相对非活跃组)间区分明显。转录活跃组和相对非活跃组间有部分样本重合,同时结果也显示当HIV-1感染者的CD4+T淋巴细胞计数与健康人无显著差异时,其细胞内的基因表达与健康人接近。结论基于HIV-1总DNA和RNA定量检测结果及两者间比值可以较好地区分PBMCs内病毒转录活性。HIV-1感染细胞内部病毒的不同转录激活状况可导致其基因表达谱的异质性。     

基于基因表达谱相似性的四物汤重定位及抗乳腺癌有效成分群辨识＊

目的 发现四物汤的新药理作用并辨识其有效成分群。方法 于GEO和Cmap数据库获取四物汤和1309个小分子药物的基因表达谱，计算差异表达基因及四物汤与1309个小分子药物的基因表达谱间的相似性，相似性较高的小分子药物的药理作用为四物汤的新药理作用。相似性较高的小分子药物的靶点作为四物汤发挥新药理作用的靶标，利用分子对接技术辨识四物汤的有效成分群。结果 四物汤具有抗乳腺癌的作用，其有效成分群为荭草苷、芍药苷和半乳糖醛酸等，并通过文献调研验证了辨识结果的可靠性。结论 本研究将为扩大四物汤的临床应用范围及质量控制奠定基础，为乳腺癌的治疗提供新方法。     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms

PurposeMachine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction algorithms for activity class prediction from hip-based raw acceleration data.MethodsThe hip-based raw acceleration data collected from 27 participants was split into training (70 %) and validation (30 %) subsets. A total of 206 time- (TD) and frequencydomain (FD) features were extracted from 6-second non-overlapping windows of the signal. Feature selection was done using seven filter-based, two wrapper-based, and one embedded algorithm, and classification was performed with artificial neural network (ANN), support vector machine (SVM), and random forest (RF). For every combination between the feature selection method and the classifiers, the most appropriate feature subsets were found and used for model training within the training set. These models were then validated with the left-out validation set.ResultsThe appropriate number of features for the ANN, SVM, and RF ranged from 20 to 45. Overall, the accuracy of all the three classifiers was higher when trained with feature subsets generated using filter-based methods compared with when they were trained with wrapper-based methods (range: 78.1 %–88 % vs. 66 %–83.5 %). TD features that reflect how signals vary around the mean, how they differ with one another, and how much and how often they change were more frequently selected via the feature selection methods.ConclusionsA subset of TD features from raw accelerometry could be sufficient for ML-based activity classification if properly selected from different axes.     

Cancer Cell-Specific Major Histocompatibility Complex II Expression as a Determinant of the Immune Infiltrate Organization and Function in the NSCLC Tumor Microenvironment

IntroductionIn patients with NSCLC, the prognostic significance of the tumor microenvironment (TME) immune composition has been revealed using single- or dual-marker staining on sequential tissue sections. Although these studies reveal that relative abundance and localization of immune cells are important parameters, deeper analyses of the NSCLC TME are necessary to refine the potential application of these findings to clinical care. Currently, the complex spatial relationships between cells of the NSCLC TME and potential drivers contributing to its immunologic composition remain unknown.MethodsWe used multispectral quantitative imaging on the lung adenocarcinoma TME in 153 patients with resected tumors. On a single slide per patient, we evaluated the TME with markers for CD3, CD8, CD14, CD19, major histocompatibility complex II (MHCII), cytokeratin, and 4′,6-diamidino-2-phenylindole (DAPI). Image analysis, including tissue segmentation, phenotyping, and spatial localization, was performed.ResultsSpecimens wherein greater than or equal to 5% of lung cancer cells expressed MHCII (MHCII^hi TME) had increased levels of CD4⁺ and CD8⁺ T cells and CD14⁺ cell infiltration. In the MHCII^hi TME, the immune infiltrate was closer to cancer cells and expressed an activated phenotype. Morphologic image analysis revealed cancer cells in the MHCII^hi TME more frequently interfaced with CD4⁺ and CD8⁺ T cells. Patients with an MHCII^hi TME experienced improved overall survival (p = 0.046).ConclusionsLung cancer cell-specific expression of MHCII associates with levels of immune cell infiltration, spatial localization, and activation status within the TME. This suggests that cancer cell-specific expression of MHCII may represent a biomarker for the immune system’s recognition and activation against the tumor.     

Efficacy of recombinant Marek’s disease virus vectored vaccines with computationally optimized broadly reactive antigen (COBRA) hemagglutinin insert against genetically diverse H5 high pathogenicity avian influenza viruses

The genetic and antigenic drift associated with the high pathogenicity avian influenza (HPAI) viruses of Goose/Guangdong (Gs/GD) lineage and the emergence of vaccine-resistant field viruses underscores the need for a broadly protective H5 influenza A vaccine. Here, we tested experimental vector herpesvirus of turkey (vHVT)-H5 vaccines containing either wild-type clade 2.3.4.4A-derived H5 inserts or computationally optimized broadly reactive antigen (COBRA) inserts with challenge by homologous and genetically divergent H5 HPAI Gs/GD lineage viruses in chickens. Direct assessment of protection was confirmed for all the tested constructs, which provided clinical protection against the homologous and heterologous H5 HPAI Gs/GD challenge viruses and significantly decreased oropharyngeal shedding titers compared to the sham vaccine. The cross reactivity was assessed by hemagglutinin inhibition (HI) and focus reduction assay against a panel of phylogenetically and antigenically diverse H5 strains. The COBRA-derived H5 inserts elicited antibody responses against antigenically diverse strains, while the wild-type-derived H5 vaccines elicited protection mostly against close antigenically related clades 2.3.4.4A and 2.3.4.4D viruses. In conclusion, the HVT vector, a widely used replicating vaccine platform in poultry, with H5 insert provides clinical protection and significant reduction of viral shedding against homologous and heterologous challenge. In addition, the COBRA-derived inserts have the potential to be used against antigenically distinct co-circulating viruses and future drift variants.