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1.
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。  相似文献   
2.
《Clinical neurophysiology》2021,132(6):1312-1320
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.  相似文献   
3.
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.  相似文献   
4.
AimSkin tears are traumatic wounds characterised by separation of the skin layers. Severity evaluation is important in the management of skin tears. To support the assessment and management of skin tears, this study aimed to develop an algorithm to estimate a category of the Skin Tear Audit Research classification system (STAR classification) using digital images via machine learning. This was achieved by introducing shape features representing complicated shape of the skin tears.MethodsA skin tear image was separated into small segments, and features of each segment were estimated. The segments were then classified into different classes by machine learning algorithms, namely support vector machine and random forest. Their performance in classifying wound segments and STAR categories was evaluated with 31 images using the leave-one-out cross validation.ResultsSupport vector machine showed an accuracy of 74% and 69% in classifying wound segments and STAR categories, respectively. The corresponding accuracy using random forest were 71% and 63%.ConclusionMachine learning algorithms revealed capable of classifying categories of skin tears. This could offer the potential to aid nurses in their management of skin tears, even if they are not specialised in wound care.  相似文献   
5.
《Vaccine》2021,39(14):1933-1942
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.  相似文献   
6.
《Vaccine》2022,40(6):934-944
Respiratory Syncytial Virus (RSV) remains a leading cause of severe respiratory disease for which no licensed vaccine is available. We have previously described the derivation of an RSV Fusion protein (F) stabilized in its prefusion conformation (preF) as vaccine immunogen and demonstrated superior immunogenicity in naive mice of preF versus wild type RSV F protein, both as protein and when expressed from an Ad26 vaccine vector. Here we address the question if there are qualitative differences between the two vaccine platforms for induction of protective immunity. In naïve mice, both Ad26.RSV.preF and preF protein induced humoral responses, whereas cellular responses were only elicited by Ad26.RSV.preF. In RSV pre-exposed mice, a single dose of either vaccine induced cellular responses and strong humoral responses. Ad26-induced RSV-specific cellular immune responses were detected systemically and locally in the lungs. Both vaccines showed protective efficacy in the cotton rat model, but Ad26.RSV.preF conferred protection at lower virus neutralizing titers in comparison to RSV preF protein. Factors that may contribute to the protective capacity of Ad26.RSV.preF elicited immunity are the induced IgG2a antibodies that are able to engage Fcγ receptors mediating Antibody Dependent Cellular Cytotoxicity (ADCC), and the induction of systemic and lung resident RSV specific CD8 + T cells. These data demonstrate qualitative improvement of immune responses elicited by an adenoviral vector based vaccine encoding the RSV preF antigen compared to the subunit vaccine in small animal models which may inform RSV vaccine development.  相似文献   
7.
8.
传统的脉诊信息收集和辩证具有明显的主观特性,影响证候的规范化和标准化。本文提出一种融合了微控制器技术、传感器技术、数字信号处理技术、人工智能等技术的数字化脉诊仪,采用数字化信号表示中医脉诊的信息,针对采集到的脉象信息使用机器学习的有关算法进行脉象的识别和分类,该系统对提升中医临床诊疗的客观性和准确性具有重要的借鉴和参考意义。  相似文献   
9.
The estimation of the postmortem interval (PMI) is always a key issue in forensic science. Although many attempts based on metabolomics approaches have been proven to be feasible and accurate for PMI estimation, there have been no reports regarding the determination of the PMI in acute dichlorvos (DDVP) poisoning. In this study, all rats were killed by acute DDVP poisoning at a dose three fold the oral LD50 (240 mg/kg). Gas chromatography-mass spectrometry (GC/MS) was applied to investigate the metabolic profiling of blood samples at various times after death up to 72 h. A total of 39 metabolites were found to be associated with PMI, and the combinations of various numbers of metabolites were used to establish support vector regression (SVR) models to investigate the PMI. The SVR model constructed by 23 metabolites had a minimum mean squared error (MSE) of 5.49 h for the training set. Then, the SVR model was validated by prediction set with an MSE of 10.33 h, suggesting good predictive ability of the model for investigating the PMI. The findings demonstrated the great potential of GC/MS-based metabolomics combined with the SVR model in determining the PMI of DDVP poisoned rats and provided an experimental basis for the application of this approach in investigating the PMI of other toxicants.  相似文献   
10.
目的:通过分子克隆构建KPNA2过表达载体,探究其对骨肉瘤细胞143B生长的影响。方法:利用Trizol法提取Hela细胞总RNA,而后通过PCR反应扩增KPNA2基因,将扩增产物克隆至表达载体pcDNA3.1+构建KPNA2过表达质粒。通过qPCR实验和Western blot实验检测KPNA2过表达载体转染143B细胞后的表达效率。利用CCK-8、平板克隆形成实验检测143B细胞的增殖状况,利用流式细胞术检测143B细胞的周期分布。结果:qPCR实验和Western blot实验均表明KPNA2过表达质粒转染后,143B细胞内KPNA2表达水平显著上调。CCK-8、平板克隆形成实验结果证实KPNA2上调能够促进143B细胞增殖。流式细胞术结果表明过表达KPNA2能够加快143B细胞周期进程。结论:KPNA2能够促进骨肉瘤细胞系143B生长,为骨肉瘤早期诊断和靶向治疗提供实验依据和理论基础。  相似文献   
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