Analyzing bronchoalveolar fluid derived small extracellular vesicles using single-vesicle SERS for non-small cell lung cancer detection.

An emerging body of research by biologists and clinicians has demonstrated the clinical application of small extracellular vesicles (sEVs, also commonly referred to as exosomes) as biomarkers for cancer detections. sEVs isolated from various body fluids such as blood, saliva, urine, and cerebrospinal fluid have been used for biomarker discoveries with highly encouraging outcomes. Among the biomarkers discovered are those responsible for multiple cancer types and immune responses. These biomarkers are recapitulated from the tumor microenvironments. Yet, despite numerous discussions of sEVs in scientific literature, sEV-based biomarkers have so far played only a minor role for cancer diagnostics in the clinical setting, notably less so than other techniques such as imaging and biopsy. In this paper, we report the results of a pilot study (n = 10 from each of the patient and the control group) using bronchoalveolar lavage fluid to determine the presence of sEVs related to non-small cell lung cancer in twenty clinical samples examined using surface enhanced Raman spectroscopy (SERS).

Gold Nanopyramid Arrays for Non-Invasive Surface-Enhanced Raman Spectroscopy-Based Gastric Cancer Detection via sEVs.

Gastric cancer (GC) is one of the most common and lethal types of cancer affecting over one million people, leading to 768,793 deaths globally in 2020 alone. The key for improving the survival rate lies in reliable screening and early diagnosis. Existing techniques including barium-meal gastric photofluorography and upper endoscopy can be costly and time-consuming and are thus impractical for population screening. We look instead for small extracellular vesicles (sEVs, currently also referred as exosomes) sized ⌀ 30-150 nm as a candidate. sEVs have attracted a significantly higher level of attention during the past decade or two because of their potentials in disease diagnoses and therapeutics. Here, we report that the composition information of the collective Raman-active bonds inside sEVs of human donors obtained by surface-enhanced Raman spectroscopy (SERS) holds the potential for non-invasive GC detection. SERS was triggered by the substrate of gold nanopyramid arrays we developed previously. A machine learning-based spectral feature analysis algorithm was developed for objectively distinguishing the cancer-derived sEVs from those of the non-cancer sub-population. sEVs from the tissue, blood, and saliva of GC patients and non-GC participants were collected (n = 15 each) and analyzed. The algorithm prediction accuracies were reportedly 90, 85, and 72%. "Leave-a-pair-of-samples out" validation was further performed to test the clinical potential. The area under the curve of each receiver operating characteristic curve was 0.96, 0.91, and 0.65 in tissue, blood, and saliva, respectively. In addition, by comparing the SERS fingerprints of individual vesicles, we provided a possible way of tracing the biogenesis pathways of patient-specific sEVs from tissue to blood to saliva. The methodology involved in this study is expected to be amenable for non-invasive detection of diseases other than GC.

Label-free distinction between p53+/+ and p53 -/- colon cancer cells using a graphene based SERS platform.

Surface-Enhanced Raman Scattering (SERS) is used to differentiate two colon cancer cell line HCT 116, that is, to distinguish a TP53 gene knockout cell line (p53 -/-) from a wild type (p53 +/+). A label-free graphene/gold nanopyramid based SERS platform, combined with the multivariate analysis: principal component analysis, is used to profile live, dead, and burst colon cancer cells suspended in simulated body fluid (SBF). The graphene sheet permits SERS hotspot identification and provides a chemical enhancement for the biological constituents. This study found that a unique fingerprint exists for three different states of the cell, burst, live, and dead, which were used to differentiate the p53 +/+ and p53 -/- cell lines. Perceptron with Pocket Algorithm was also coupled with PCA to demonstrate an average of 81% sensitivity and 97% specificity in separating the two cell lines. The demonstration of single gene differentiation shows the great applicable potential of this SERS graphene hybrid platform for cancer diagnosis.

Surface enhanced Raman spectroscopy distinguishes amyloid Β-protein isoforms and conformational states.

Amyloid ß-protein (Aß) self-association is one process linked to the development of Alzheimer's disease (AD). Aß peptides, including its most abundant forms, Aß40 and Aß42, are associated with the two predominant neuropathologic findings in AD, vascular and parenchymal amyloidosis, respectively. Efforts to develop therapies for AD often have focused on understanding and controlling the assembly of these two peptides. An obligate step in these efforts is the monitoring of assembly state. We show here that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) readily distinguishes Aß40 and Aß42. We show further, through comparison of assembly dependent changes in secondary structure and morphology, that the SERS/PCA approach unambiguously differentiates closely related assembly stages not readily differentiable by circular dichroism spectroscopy, electron microscopy, or other techniques. The high discriminating power of SERS/PCA is based on the rich structural information present in its spectra, which comprises not only on interatomic resonances between covalently associated atoms and hydrogen bond interactions important in controlling secondary structure, but effects of protein orientation relative to the substrate surface. Coupled with the label-free, single molecule sensitivity of SERS, the approach should prove useful for determining structure activity relationships, suggesting target sites for drug development, and for testing the effects of such drugs on the assembly process. The approach also could be of value in other systems in which assembly dependent changes in protein structure correlate with the formation of toxic peptide assemblies.

Cardiac Fibroblasts Adopt Osteogenic Fates and Can Be Targeted to Attenuate Pathological Heart Calcification.

Mammalian tissues calcify with age and injury. Analogous to bone formation, osteogenic cells are thought to be recruited to the affected tissue and induce mineralization. In the heart, calcification of cardiac muscle leads to conduction system disturbances and is one of the most common pathologies underlying heart blocks. However the cell identity and mechanisms contributing to pathological heart muscle calcification remain unknown. Using lineage tracing, murine models of heart calcification and in vivo transplantation assays, we show that cardiac fibroblasts (CFs) adopt an osteoblast cell-like fate and contribute directly to heart muscle calcification. Small-molecule inhibition of ENPP1, an enzyme that is induced upon injury and regulates bone mineralization, significantly attenuated cardiac calcification. Inhibitors of bone mineralization completely prevented ectopic cardiac calcification and improved post injury heart function. Taken together, these findings highlight the plasticity of fibroblasts in contributing to ectopic calcification and identify pharmacological targets for therapeutic development.

Study of Ni Metallization in Macroporous Si Using Wet Chemistry for Radio Frequency Cross-Talk Isolation in Mixed Signal Integrated Circuits.

A highly conductive moat or Faraday cage of through-the-wafer thickness in Si substrate was proposed to be effective in shielding electromagnetic interference thereby reducing radio frequency (RF) cross-talk in high performance mixed signal integrated circuits. Such a structure was realized by metallization of selected ultra-high-aspect-ratio macroporous regions that were electrochemically etched in p- Si substrates. The metallization process was conducted by means of wet chemistry in an alkaline aqueous solution containing Ni2+ without reducing agent. It is found that at elevated temperature during immersion, Ni2+ was rapidly reduced and deposited into macroporous Si and a conformal metallization of the macropore sidewalls was obtained in a way that the entire porous Si framework was converted to Ni. A conductive moat was as a result incorporated into p- Si substrate. The experimentally measured reduction of crosstalk in this structure is 5~18 dB at frequencies up to 35 GHz.

Moiré superstructures of graphene on faceted nickel islands.

Using scanning tunneling microscopy and spectroscopy, in combination with density functional theory calculations, we investigated the morphology and electronic structure of monolayer graphene grown on the (111) and (110) facets of three-dimensional nickel islands on highly oriented pyrolytic graphite substrate. We observed graphene domains exhibiting hexagonal and striped moiré patterns with periodicities of 22 and 12 Å, respectively, on (111) and (110) facets of the Ni islands. Graphene domains are also observed to grow, as single crystals, across adjacent facets and over facet boundaries. Scanning tunneling spectroscopy data indicate that the graphene layers are metallic on both Ni(111) and Ni(110), in agreement with the calculations. We attribute this behavior to a strong hybridization between the d-bands on Ni and the π-bands of carbon. Our findings point to the possibility of preparing large-area epitaxial graphene layers even on polycrystalline Ni substrates.