METHOD: The performances of e-nose technology with different statistical methods to determine the best classifier were conducted and discussed. The gas sensor study has been complemented using solid phase micro-extraction-gas chromatography mass spectrometry. For this purpose, the lung cancer cells (A549 and Calu-3) and control cell lines, breast cancer cell (MCF7) and non-cancerous lung cell (WI38VA13) were cultured in growth medium.
RESULTS: This study successfully provided a list of possible volatile organic compounds that can be specific biomarkers for lung cancer, even at the 24th hour of cell growth. Also, the Linear Discriminant Analysis-based One versus All-Support Vector Machine classifier, is able to produce high performance in distinguishing lung cancer from breast cancer cells and normal lung cells.
CONCLUSION: The findings in this work conclude that the specific VOC released from the cancer cells can act as the odour signature and potentially to be used as non-invasive screening of lung cancer using gas array sensor devices.
OBJECTIVES: This paper focused on how the refractive index based nanobio-sensoring gold platform can produce more efficient, adaptable and more practical detection techniques to observe molecular interactions at high degree of sensitivity. It discusses surface chemistry approach, optimisation of the refractive index of gold platform and manipulation of gold geometry augmenting signal quality.
METHODS: In a normal-incidence reflectivity, r0 can be calculated using the Fresnel equation. Particularly at λ = 470 nm the ratio of r / r0 showed significant amplitude reduction mainly stemmed from the imaginary part of the Au refractive index. Hence, the fraction of reduction, Δr = 1 - r / r0. Experimentally, in a common reference frame reflectivity of a bare gold surface, R0 is compared with the reflectivity of gold surface in the presence of biolayer, R. The reduction rate (%) of reflectivity, ΔR = 1 - R / R0 is denoted as the AR signal. The method therefore enables quantitative measurement of the surface-bound protein by converting ΔR to the thickness, d, and subsequently the protein mass. We discussed four strategies to improve the AR signal by changing the effective refractive index of the biosensing platform. They are; a) Thickness optimisation of Au thin layer, b) Au / Ag bimetallic layer, c) composing alloy or Au composite, and d) Au thinlayer with nano or micro holes.
RESULTS: As the result we successfully 'move' the refractive index, ε of the AR platform (gold only) to ε = -0.948 + 3.455i, a higher sensitivity platform. This was done by composing Au-Ag2O composite with ratio = 1:1. The results were compared to the potential sensitivity improvement of the AR substrate using other that could be done by further tailoring the ε advanced method.
CONCLUSION: We suggested four strategies in order to realize this purpose. It is apparent that sensitivity has been improved through Au/Ag bimetallic layer or Au-Ag2O composite thin layer, This study is an important step towards fabrication of sensitive surface for detection of biomolecular interactions.
MATERIALS AND METHODS: Our search was limited to original papers in the English language from 2010 to 2018 using several databases including Pubmed, Scopus, Google Scholar, Iranmedex, and Scientific Information Database. A manual search of references provided in the included papers was also performed.
RESULTS: Of 101 electronically searched citations, 43 met the inclusion criteria. ELISA is commonly used for qualitative and screening detection, and WB and PCR techniques are used to confirm infection.
CONCLUSION: Among all the reported methods for detection of HTLV-1, only serological and molecular tests are used as the most common technical assays for HTLV-1. The ELISA assay, without a confirmatory test, has several limitations and affect the accuracy of the results. Owing to the prevalence of HTLV-1 and limitations of the current detection methods, further evaluation of the accuracy of these methods is needed. There are new opportunities for applying novel technological advances in microfluidics, biosensors, and lab-on-a-chip systems to perform HTLV-1 diagnostics.