摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-肿瘤学的新研究-膀胱癌是一篇报道的主题。根据NewsRx记者在加拿大沃特卢的新闻报道，研究表明：“细胞外小泡(EV)分子表型为癌症诊断提供了巨大的机会。然而，大多数相关研究都采用基于Berkel的单峰分析来实现癌症诊断，这种分析假阳性率高，准确率低。”新闻记者引用了Wat Erloo大学的研究，“在此，我们报道了一个多光谱3D DNA机器结合多模式机器学习(ML)算法高精度诊断膀胱癌的多模式平台(BCa)。该DNA机器是使用磁性微粒(MNPs)构建的，该磁性微粒(MNPs)具有特异性识别目标的适配子，即，摘要:膀胱Cer源尿EVs(uEVs)上的5个蛋白标记物,与DNA稳定的银纳米簇(DNA/AgNCs)和g-四链体/氯化血红素复合物杂交形成检测模块,确保了荧光(FL)、电感耦合等离子体质谱(ICPMS)、电泳质谱(ICPMS)等多光谱检测蛋白标记物。用紫外-可见吸收光谱(Abs)对所获得的数据进行单峰或多峰ML诊断BCa比较分析性能。结果表明，3D DNA机对UEV的检出限为9.2×10个单位mL，线性范围为4×10~5×10个单位mL，多模式数据融合模型的准确度为95.0%，精密度为93.1%。平均召回率为93.2%，三种单峰模型召回率均不超过91%。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Bladder Can cer is the subject of a report. According to news reporting originating in Water loo, Canada, by NewsRx journalists, research stated, "Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. How ever, the majority of the associated studies adopted biomarker-based unimodal an alysis to achieve cancer diagnosis, which has high false positives and low preci sion." The news reporters obtained a quote from the research from the University of Wat erloo, "Herein, we report a multimodal platform for the high-precision diagnosis of bladder cancer (BCa) through a multispectral 3D DNA machine in combination w ith a multimodal machine learning (ML) algorithm. The DNA machine was constructe d using magnetic microparticles (MNPs) functionalized with aptamers that specifi cally identify the target of interest, i.e., five protein markers on bladder-can cer-derived urinary EVs (uEVs). The aptamers were hybridized with DNA-stabilized silver nanoclusters (DNA/AgNCs) and a G-quadruplex/hemin complex to form a sens ing module. Such a DNA machine ensured multispectral detection of protein marker s by fluorescence (FL), inductively coupled plasma mass spectrometry (ICPMS), a nd UV-vis absorption (Abs). The obtained data sets then underwent uni- or multim odal ML for BCa diagnosis to compare the analytical performance. In this study, urine samples were obtained from our prospective cohort ( = 45). Our analytical results showed that the 3D DNA machine provided a detection limit of 9.2 x 10 pa rticles mL with a linear range of 4 x 10 to 5 x 10 particles mL for uEVs. Moreov er, the multimodal data fusion model exhibited an accuracy of 95.0% , a precision of 93.1%, and a recall rate of 93.2% on average, while those of the three types of unimodal models were no more than 91 %."
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