Label-free breast cancer detection and classification by convolutional neural network-based on exosomes surface-enhanced raman scattering

Because the breast cancer is an important factor that threatens women's lives and health,early diagnosis is helpful for disease screening and a good prognosis.Exosomes are nanovesicles,secreted from cells and other body fluids,which can reflect the genetic and phenotypic status of parental cells.Compared with other methods for early diagnosis of cancer(such as circulating tumor cells(CTCs)and circulating tumor DNA),exosomes have a richer number and stronger biological stability,and have great potential in early diagnosis.Thus,it has been proposed as promising biomarkers for diagnosis of early-stage cancer.However,distinguishing different exosomes remain is a major biomedical challenge.In this paper,we used predictive Convolutional Neural model to detect and analyze exosomes of normal and cancer cells with surface-enhanced Raman scattering(SERS).As a result,it can be seen from the SERS spectra that the exosomes of MCF-7,MDA-MB-231 and MCF-10A cells have similar peaks(939,1145 and 1380 cm^(-1)).Based on this dataset,the predictive model can achieve 95%accuracy.Compared with principal component analysis(PCA),the trained CNN can classify exosomes from different breast cancer cells with a superior performance.The results indicate that using the sensitivity of Raman detection and exosomes stable presence in the incubation period of cancer cells,SERS detection combined with CNN screening may be used for the early diagnosis of breast cancer in the future.

Rapid label-free SERS detection of foodborne pathogenic bacteria based on hafnium ditelluride-Au nanocomposites

Two-dimensional(2D)nanomaterials have captured an increasing attention in biophotonics owing to their excellent optical features.Herein,2D hafnium ditelluride(HfTe_(2)),a new member of transition metal tellurides,is exploited to support gold nanoparticles fabricating HfTe_(2)-Au nanocomposites.The nanohybrids can serve as novel 2D surface-enhanced Raman scattering(SERS)substrate for the label-free detection of analyte with high sensitivity and reproducibility.Chemical mechanism originated from HfTe_(2) nanosheets and the electromagnetic enhancement induced by the hot spots on the nano-hybrids may largely contribute to the superior SERS effect of HfTe_(2)-Au nanocomposites.Finally,HfTe_(2)-Au nanocomposites are utilized for the label-free SERS analysis of foodborne pathogenic bac-teria,which realize the rapid and ultrasensitive Raman test of Escherichia coli,Listeria mono-cytogenes,Staphylococcus aureus and Salmonella with the limit of detection of 10 CFU/mL and the maximum Raman enhancement factor up to 1.7×10^(8).Combined with principal component analysis,HfTe_(2)-Au-based SERS analysis also completes the bacterial classification without extra treatment.

Monitoring the penetration and accumulation of gold nanoparticles in rat skin ex vivo using surface-enhanced Raman scattering spectroscopy

Contamination by accidental cutaneous contact with the commercial products and the air pol-hutants raised a considerable health and safety issue.This study aimed to trace the dynamics of the 20 nm gold nanopartide(GNP)penetration and accumulation in rat skin tissues using a surface-enhanced Raman scattering(SERS)techmique.After the topical application of GNPs on rat skin surface,the SERS spectra were recorded for every 15 pum to an overall depth of 75 pum from skin surface for 150 min.The processes of GNP penetration in rat skin were accompanied by aggregation of GNPs,which affected SERS spectra.The results revealed that 20 nm GNPs can penetrate through stratum corneum layer,viable epidermis layer,and then into dermis layer.This study demonstrated for the first time the potential of SERS spectroscopy to monitor the penetration and accumulation of GNPs in rat skin.

Diagnosis of knee osteoarthritis by OCT and surface-enhanced Raman spectroscopy

In this paper,optical coherence tomography(OCT)and surface-enhanced Raman spectroscopy(SERS)were used to characterize normal knee joint(NKJ)tissue and knee osteoarthritis(KOA)tissue ex vivo.OCT images show that there is a clear hierarchical structure in NKJ tissue,including surface layer,transitional layer,radiation layer and cartilage matrix calcification layer tissue structure,while the hierarchical structure of KOA tissue is not clear and unevenly distributed,and the pathological tissues at different stages also show significant di®erences.SERS shows that NKJ tissue and mild osteoarthritic knee cartilage(MiKOA)tissue have strong characteristic Raman peaks at 964,1073(1086),1271,1305,1442,1660 and 1763 cm^(-1).Compared with the Raman spectrum of NKJ tissue,the Raman characteristic peaks of MiKOA tissue have some shifts,moving from 1073 cm^(-1)to 1086 cm^(-1)and from 1542 cm^(-1)to 1442 cm^(-1).There is a characteristic Raman peak of 1271 cm^(-1)in MiKOA tissue,but not in NKJ tissue.Compared with NKJ tissue,severely degenerated cartilage(SdKOA)tissues show some new SERS peaks at 1008,1245,1285,1311 and 1321 cm^(-1),which are not seen in SERS spectra of NKJ tissue.Principal component analysis(PCA)was used to analyze the Raman spectra of 1245–1345 cm^(-1)region.The results show that PCA can distinguish NKJ,MiKOA and SdKOA tissues and the accuracy is about 90%.These results indicate that OCT can clearly distinguish NKJ,MiKOA,moderate osteoarthritic knee cartilage(MoKOA)and SdKOA tissue,while SERS can provide further judgment basis.The results also prove that the contents of protein and polysaccharide in knee tissue are changed during the pathological process of knee tissue,which is the cause of pain caused by poor friction in knee joint during movement.

Lamellar hafnium ditelluride as an ultrasensitive surface-enhanced Raman scattering platform for label-free detection of uric acid

The development of two-dimensional(2D)transition metal dichalcogenides has been in a rapid growth phase for the utilization in surface-enhanced Raman scattering(SERS)analysis.Here,we report a promising 2D transition metal tellurides(TMTs)material,hafnium ditelluride(HfTe2),as an ultrasensitive platform for Raman identification of trace molecules,which demonstrates extraordinary SERS activity in sensitivity,uniformity,and reproducibility.The highest Raman enhancement factor of 2.32×10^(6)is attained for a rhodamine 6G molecule through the highly efficient charge transfer process at the interface between the HfTe2 layered structure and the adsorbed molecules.At the same time,we provide an effective route for large-scale preparation of SERS substrates in practical applications via a facile stripping strategy.Further application of the nanosheets for reliable,rapid,and label-free SERS fingerprint analysis of uric acid molecules,one of the biomarkers associated with gout disease,is performed,which indicates arresting SERS signals with the limits of detection as low as 0.1 mmol/L.The study based on this type of 2D SERS substrate not only reveals the feasibility of applying TMTs to SERS analysis,but also paves the way for nanodiagnostics,especially early marker detection.