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Polymer coated surfaces for the target-agnostic diagnosis of diseases - an artificial nose approach

Polymer coated surfaces for the target-agnostic diagnosis of diseases - an artificial nose approach
用于与目标无关的疾病诊断的聚合物涂层表面——人工鼻方法
批准号:
2767061
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金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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英文摘要
Surface-enhanced Raman spectroscopy (SERS) has emerged in recent years as a very promising technique for sensing applications due to its high sensitivity and multiplex capability.1 In the medical field, this has been applied as both an imaging and diagnosis tool, for diseases ranging from cancer to bacterial infections.1,2,3 Additionally, SERS is also compatible with 'target-agnostic' diagnosis of diseases: in contrast with techniques that rely on the detection of a specific molecules or targets, label-free methods do not require pre-specified analytes to be present in the sample, hence reducing the synthetic difficulties and costs associated with attaching Raman-probes to target-binding molecules (e.g. antibodies).4 Within Prof Molly Stevens' group, an artificial nose approach based on SERS was developed by covering gold surfaces with small molecules forming a self-assembling monolayer (SAM).4 When different analytes were layered on this surface, their affinity to the SAM determined their orientation with respect to the surface enhancing selectively different vibrational modes. The spectra could then be analysed and the data from 9 different SAMs combined using PCA (principal component analysis) to extract information regarding the chemical composition of complex samples. With the successes obtained from biological media, we are interested in improving this technique by expanding the chemical functionalities used to decorate the gold surface and provide further discrimination between samples from healthy and diseased patients suffering from illnesses that are hard to diagnose and rely on early diagnosis for low mortality. The synthetic work will be accompanied by computational techniques which will allow the analysis of the data by artificial intelligence and the discrimination of healthy and unhealthy populations. Bibliography:(1) Wang, J.; Liang, D.; Jin, Q.; Feng, J.; Tang, X. Bioorthogonal SERS Nanotags as a Precision Theranostic Platform for in Vivo SERS Imaging and Cancer Photothermal Therapy. Bioconjug. Chem. 2020, 31 (2), 182-193. https://doi.org/10.1021/acs.bioconjchem.0c00022.(2) Haroon, M.; Tahir, M.; Nawaz, H.; Majeed, M. I.; Al-Saadi, A. A. Surface-Enhanced Raman Scattering (SERS) Spectroscopy for Prostate Cancer Diagnosis: A Review. Photodiagnosis Photodyn. Ther. 2022, 37, 102690. https://doi.org/10.1016/j.pdpdt.2021.102690.(3) Tahir, M. A.; Dina, N. E.; Cheng, H.; Valev, V. K.; Zhang, L. Surface-Enhanced Raman Spectroscopy for Bioanalysis and Diagnosis. Nanoscale 2021, 13 (27), 11593-11634. https://doi.org/10.1039/D1NR00708D.(4) Kim, N.; Thomas, M. R.; Bergholt, M. S.; Pence, I. J.; Seong, H.; Charchar, P.; Todorova, N.; Nagelkerke, A.; Belessiotis-Richards, A.; Payne, D. J.; Gelmi, A.; Yarovsky, I.; Stevens, M. M. Surface Enhanced Raman Scattering Artificial Nose for High Dimensionality Fingerprinting. Nat. Commun. 2020, 11 (1), 207. https://doi.org/10.1038/s41467-019-13615-2.
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