Bordbar Mohammad Mahdi, Barzegar Hamideh, Tashkhourian Javad, Bordbar Mohammadreza, Hemmateenejad Bahram
Chemistry Department, Shiraz University, Shiraz, Iran.
Pediatric Department, Shiraz University of Medical Sciences, Shiraz, Iran.
Anal Chim Acta. 2021 Jan 2;1141:28-35. doi: 10.1016/j.aca.2020.10.029. Epub 2020 Oct 19.
Volatile organic compounds (VOCs) in blood samples can be used as useful biomarkers to diagnose various human diseases. This study describes the potential of a paper-based sensor array for detecting leukemia using blood VOCs. Blood samples were collected from 59 new leukemia cases and 47 healthy cases as a control group. Each blood sample was divided into two parts; one for a laboratory test and the other was used in our study. Samples were mixed with heparin and then transferred to a sterile container, and a sensor was stacked on its cap. This sensor array contains 16 nanoparticles deposited on a sheet of hydrophobic paper in a 4 × 4 array format. Containers were stored in an oven at 60 °C for 4.5 h. Then, the image of sensors was recorded by a scanner and compared to the image before exposing the blood vapor. The sensor responses were subjected to different multivariate statistical methods to develop models that discriminate between control and leukemia samples. The interaction of nanoparticles with the volatile metabolome of blood caused aggregation and consequently changing in the color of nanoparticles. The color changes resulted in a specific pattern for blood samples with leukemia, which is different from those obtained from healthy specimens. The discrimination analysis was approved by pattern recognition methods such as principal component analysis with 97% accuracy. Among 59 patients, the mean age was 6.02 ± 4.55 years (range 1-16 y). The mean total response was 652.83 ± 117.02. The rock curve showed an accuracy of 96% for classifying patients from the control group. The logistic regression model showed that 93.6% of healthy and 93.2% of patients were classified correctly by using this method. These statistics agree with the classification results obtained by principal component analysis. For every 5000-unit increase in platelet count, the chance of leukemia decreased by 9%. Additionally, the chance of being categorized as a patient decreased by 10% for every 20-unit increase in total response. The electronic nose using VOC's of blood is a non-invasive and inexpensive tool for detecting new cases of leukemia with high sensitivity and specificity. Platelet count is an essential para-clinical parameter determining the total response of the sensors. Follow up studies with a larger sample size are warranted to elucidate its clinical applicability.
血液样本中的挥发性有机化合物（VOCs）可作为诊断各种人类疾病的有用生物标志物。本研究描述了一种基于纸张的传感器阵列利用血液VOCs检测白血病的潜力。从59例新确诊的白血病病例和47例健康对照者中采集血液样本。每个血液样本分为两部分；一部分用于实验室检测，另一部分用于本研究。样本与肝素混合后转移至无菌容器中，传感器堆叠在容器盖上。该传感器阵列包含以4×4阵列形式沉积在一张疏水纸上的16个纳米颗粒。容器在60℃的烤箱中保存4.5小时。然后，用扫描仪记录传感器的图像，并与暴露于血液蒸汽之前的图像进行比较。对传感器响应采用不同的多元统计方法来建立区分对照样本和白血病样本的模型。纳米颗粒与血液挥发性代谢组的相互作用导致聚集，进而使纳米颗粒颜色发生变化。颜色变化为白血病血液样本产生了一种特定模式，这与健康样本的模式不同。通过主成分分析等模式识别方法进行的判别分析准确率达到97%。59例患者中，平均年龄为6.02±4.55岁（范围1 - 16岁）。平均总响应为652.83±117.02。ROC曲线显示将患者与对照组进行分类的准确率为96%。逻辑回归模型显示，使用该方法健康者和患者的正确分类率分别为93.6%和93.2%。这些统计结果与主成分分析得到的分类结果一致。血小板计数每增加5000个单位，患白血病的几率降低9%。此外，总响应每增加20个单位，被归类为患者的几率降低10%。利用血液VOCs的电子鼻是一种用于检测新发病例白血病的非侵入性且廉价的工具，具有高灵敏度和特异性。血小板计数是决定传感器总响应的一个重要临床旁参数。有必要进行更大样本量的后续研究以阐明其临床适用性。
