We introduce an efficacious machine learning classification plus chemostructural characterization of proteins by a mixed data processing based on Principal Component Analysis applied to multipeak fitting on Surface-enhanced Raman Scattering spectra.
Significance: Alzheimer’s disease (AD) is an irreversible and progressive disorder that damages brain cells and impairs the cognitive abilities of the affected. Developing a sensitive and cost-effective method to detect Alzheimer’s biomarkers appears vital in both a diagnostic and therapeutic perspective.
Aim: Our goal is to develop a sensitive and reliable tool for detection of amyloid β (1-42) peptide (Aβ42), a major AD biomarker, using fiber-enhanced Raman spectroscopy (FERS).
Approach: A hollow core photonic crystal fiber (HCPCF) was integrated with a conventional Raman spectroscopic setup to perform FERS measurements. FERS was then coupled with surface-enhanced Raman spectroscopy (SERS) to further amplify the Raman signal thanks to a combined FERS-SERS assay.
Results: A minimum 20-fold enhancement of the Raman signal of Aβ42 as compared to a conventional Raman spectroscopy scheme was observed using the HCPCF-based light delivery system. The signal was further boosted by decorating the fiber core with gold bipyramids generating an additional SERS effect, resulting in an overall 200 times amplification.
Conclusions: The results demonstrate that the use of an HCPCF-based platform can provide sharp and intense Raman signals of Aβ42, in turn paving the way toward the development of a sensitive label-free detection tool for early diagnosis of AD.
The well-known enhancement effect of surface-enhanced Raman spectroscopy (SERS) is associated with the presence of metallic nanostructures at the substrate surface. Different bottom-up and top-down processes have been proposed to impart the substrate with such a nanostructured layer. The former approaches are low cost but may suffer from reusability and stability. The latter strategies are expensive, time consuming and require special equipment that complicate the fabrication process.
Here, we present the possibility to obtain stable and reusable SERS substrates by a low-cost silver-sodium ion-exchange process in soda-lime glass microrods. The microrods were obtained by cutting the tip of the ion-exchanged soda-lime fiber, resulting in disks of about few millimeters in length and one hundred microns in diameter. A thermal annealing post-process was applied to trigger the reduction of Ag+ ions into nanoparticles (AgNPs) within the ion-exchanged glass microrods. Afterwards, ion-exchange and thermal treatments were carefully tuned to assure the presence of silver NPs exposed on the surface of the microrods, without using any chemical etching. An AFM analysis confirmed the presence of AgNPs with size of tens of nm on the surface of the fiber probe.
A SERS affinity bioassay was developed on the probe with the final aim of detecting microRNA fragments acting as biomarkers of different diseases. Specifically a DNA hybridization assay was built up by anchoring a molecular beacon containing a Raman tag on the Ag surface via thiol chemistry. Initial SERS experiments confirmed the presence of the beacon on the NPs embedded on the microrods surface, as monitored by detecting main spectral bands ascribed to the oligonucleotide chain. Finally, the ability of the platform to interact with the target microRNA sequence was assessed. The analysis was repeated on a number of miRNA sequences differing from the target to evaluate the specificity of the proposed assay.
Alzheimer’s disease (AD) is an irreversible progressive disease that damages the brain cell and affects the cognitive abilities. Hence an early detection of AD biomarkers is vital for the drug treatment. Considering this, we developed a sensitive and reliable sensing tool based on fiber-enhanced Raman spectroscopic technique for the detection of AD biomarkers. The fiber-enhanced Raman measurements were performed using a hollow core photonic crystal fiber, and a comparison of Raman spectra of samples in a conventional cuvette and with the fiber was carried out. The results showed a high enhancement of Raman signal of samples measured with a fiber compared to the measurements carried out in the cuvette.
Plasmon-enhanced spectroscopies such as surface-enhanced Raman spectroscopy (SERS) concern the detection of enhanced optical responses of molecules in close proximity to plasmonic structures, which results in a strong increase in sensitivity. Recent advancements in nanofabrication methods have paved the way for a controlled design of tailor-made nanostructures with fine-tuning of their optical and surface properties. Among these, silver nanocubes (AgNCs) represent a convenient choice in SERS owing to intense electromagnetic fields localized at their extremities, which are further intensified in the gap regions between closely spaced nanoparticles. The integration of AgNCs assemblies within an optofluidic platform may confer potential for superior optical investigation due to a molecular enrichment on the plasmonic structures to collect an enhanced photonic response. We developed a novel sensing platform based on an optofluidic system involving assembled silver nanocubes of 50 nm in size for ultrasensitive SERS detection of biomolecules in wet conditions. The proposed system offers the perspective of advanced biochemical and biological characterizations of molecules as well as of effective detection of body fluid components and other molecules of biomedical interest in their own environment.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.