Raman imaging in biochemical and biomedical applications. Diagnosis and treatment of breast cancer

Biocompatible fluorescent carbon nanoparticles as nanocarriers for targeted delivery of tamoxifen for regression of Breast carcinoma

Breast cancer (BC) is the most common malignancy among females worldwide, and its high metastasis rates are the leading cause of death just after lung cancer. Currently, tamoxifen (TAM) is a hydrophobic anticancer agent and a selective estrogen modulator (SERM), approved by the FDA that has shown potential anticancer activity against BC, but the non-targeted delivery has serious side effects that limit its ubiquitous utility. Therefore, releasing anti-cancer drugs precisely to the tumor site can improve efficacy and reduce the side effects on the body. Nanotechnology has emerged as one of the most important strategies to solve the issue of overdose TAM toxicity, owing to the ability of nano-enabled formulations to deliver desirable quantity of TAM to cancer cells over a longer period of time. In view of this, use of fluorescent carbon nanoparticles in targeted drug delivery holds novel promise for improving the efficacy, safety, and specificity of TAM therapy. Here, we synthesized biocompatible carbon nanoparticles (CNPs) using chitosan molecules without any toxic surface passivating agent. Synthesized CNPs exhibit good water dispersibility and emit intense blue fluorescence upon excitation (360 nm source). The surface of the CNPs has been functionalized with folate using click chemistry to improve the targeted drug uptake by the malignant cell. The pH difference between cancer and normal cells was successfully exploited to trigger TAM release at the target site. After six hours of incubation, CNPs released ∼ 74 % of the TAM drug in acidic pH. In vitro, studies have also demonstrated that after treatment with the synthesized CNPs, significant inhibition of the tumor growth could be achieved.

A shifted ratio spectrum strategy for effective subtraction of fluorescence interference in Raman spectra

Raman spectroscopy is an important technique for analyzing the chemical composition of samples in many fields. A severe challenge often encountered in Raman measurements is the presence of a concurrent fluorescence background, especially in biological samples. In order to obtain accurate Raman spectra, the fluorescence background must be subtracted from the original Raman spectra. We proposed a shifted ratio spectrum method to subtract the strong fluorescence background from the original Raman spectrum. First, the original Raman spectrum is divided into multiple regions according to the spectral shape of the shifted ratio spectra, and then, Gaussian fitting is performed in each region. The fitting results are stitched together in order to obtain the complete fluorescence background. Finally, this fluorescence background is subtracted from the original spectrum to obtain a pure Raman spectrum. This method can accurately subtract the fluorescence background of Rhodamine 6G (R6G)/ethanol solution and serum. This highlights the great potential of this method for applications in both biological and non-biological samples.

Rapid Identification of Drug Mechanisms with Deep Learning-Based Multichannel Surface-Enhanced Raman Spectroscopy

Rapid identification of drug mechanisms is vital to the development and effective use of chemotherapeutics. Herein, we develop a multichannel surface-enhanced Raman scattering (SERS) sensor array and apply deep learning approaches to realize the rapid identification of the mechanisms of various chemotherapeutic drugs. By implementing a series of self-assembled monolayers (SAMs) with varied molecular characteristics to promote heterogeneous physicochemical interactions at the interfaces, the sensor can generate diversified SERS signatures for directly high-dimensionality fingerprinting drug-induced molecular changes in cells. We further train the convolutional neural network model on the multidimensional SAM-modulated SERS data set and achieve a discriminatory accuracy toward 99%. We expect that such a platform will contribute to expanding the toolbox for drug screening and characterization and facilitate the drug development process.

Microlens Hollow-Core Fiber Probes for Operando Raman Spectroscopy

We introduce a flexible microscale all-fiber-optic Raman probe which can be embedded into devices to enable operando in situ spectroscopy. The facile-constructed probe is composed of a nested antiresonant nodeless hollow-core fiber combined with an integrated high refractive index barium titanate microlens. Pump laser 785 nm excitation and near-infrared collection are independently characterized, demonstrating an excitation spot of full-width-half-maximum 1.1 μm. Since this is much smaller than the effective collection area, it has the greatest influence on the collected Raman scattering. Our characterization scheme provides a suitable protocol for testing the efficacy of these fiber probes using various combinations of fiber types and microspheres. Raman measurements on a surface-enhanced Raman spectroscopy sample and a copper battery electrode demonstrate the viability of the fiber probe as an alternative to bulk optic Raman microscopes, giving comparable collection to a 10 objective, thus paving the way for operando Raman studies in applications such as lithium battery monitoring.

A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections

As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.

The Difference between Plasmon Excitations in Chemically Heterogeneous Gold and Silver Atomic Clusters

Weak doping can broaden, shift, and quench plasmon peaks in nanoparticles, but the mechanistic intricacies of the diverse responses to doping remain unclear. In this study, we used the time-dependent density functional theory (TD-DFT) to compute the excitation properties of transition-metal Pd- or Pt-doped gold and silver atomic arrays and investigate the evolution characteristics and response mechanisms of their plasmon peaks. The results demonstrated that the Pd or Pt doping of the off-centered 10 × 2 atomic arrays broadened or shifted the plasmon peaks to varying degrees. In particular, for Pd-doped 10 × 2 Au atomic arrays, the broadened plasmon peak significantly blueshifted, whereas a slight red shift was observed for Pt-doped arrays. For the 10 × 2 Ag atomic arrays, Pd doping caused almost no shift in the plasmon peak, whereas Pt doping caused a substantial red shift in the broadened plasmon peak. The analysis revealed that the diversity in these doping responses was related to the energy positions of the d electrons in the gold and silver atomic clusters and the positions of the doping atomic orbitals in the energy bands. The introduction of doping atoms altered the symmetry and gap size of the occupied and unoccupied orbitals, so multiple modes of single-particle transitions were involved in the excitation. An electron transfer analysis indicated a close correlation between excitation energy and the electron transfer of doping atoms. Finally, the differences in the symmetrically centered 11 × 2 doped atomic array were discussed using electron transfer analysis to validate the reliability of this analytical method. These findings elucidate the microscopic mechanisms of the evolution of plasmon peaks in doped atomic clusters and provide new insights into the rational control and application of plasmons in low-dimensional nanostructures.

Chick sexing based on the blood analysis using Raman spectroscopy

Efforts are underway to develop technology for automatically determining the sex of chick embryos, aimed at establishing a stable and efficient poultry farming system while also addressing animal welfare concerns. This study investigated the possibility of chick sexing through blood analysis using Raman spectroscopy. Raman spectra were obtained from whole blood and its constituents, such as red blood cells (RBCs) and blood plasma, collected from chicks aged 1-2 days, using a 785-nm excitation wavelength. Principal component analysis (PCA) revealed statistically significant sex-dependent spectral variations in whole blood and RBCs, whereas blood plasma showed less clear dependency. These spectral differences between male and female chicks were attributed to differences in the proportion of spectral components from oxygenated (oxy-) and deoxygenated (deoxy-) RBCs, with males exhibiting a slightly stronger contribution of oxy-RBCs compared to females. This reflects the higher oxygen affinity of hemoglobin (Hb) in males compared to females. A model for discriminating chick sex was built using the ratios of certain Raman band characteristics of oxy-RBCs and deoxy-RBCs, achieving a sensitivity of 100%. This spectroscopic method holds promise for developing technology to discriminate the sex of early chicken embryos in ovo by detecting differences in oxygen saturation of RBCs based on sex.

Correlative Raman Imaging: Development and Cancer Applications

Despite extensive research efforts, cancer continues to stand as one of the leading causes of death on a global scale. To gain profound insights into the intricate mechanisms underlying cancer onset and progression, it is imperative to possess methodologies that allow the study of cancer cells at the single-cell level, focusing on critical parameters such as cell morphology, metabolism, and molecular characteristics. These insights are essential for effectively discerning between healthy and cancerous cells and comprehending tumoral progression. Recent advancements in microscopy techniques have significantly advanced the study of cancer cells, with Raman microspectroscopy (RM) emerging as a particularly powerful tool. Indeed, RM can provide both biochemical and spatial details at the single-cell level without the need for labels or causing disruptions to cell integrity. Moreover, RM can be correlated with other microscopy techniques, creating a synergy that offers a spectrum of complementary insights into cancer cell morphology and biology. This review aims to explore the correlation between RM and other microscopy techniques such as confocal fluoresce microscopy (CFM), atomic force microscopy (AFM), digital holography microscopy (DHM), and mass spectrometry imaging (MSI). Each of these techniques has their own strengths, providing different perspectives and parameters about cancer cell features. The correlation between information from these various analysis methods is a valuable tool for physicians and researchers, aiding in the comprehension of cancer cell morphology and biology, unraveling mechanisms underlying cancer progression, and facilitating the development of early diagnosis and/or monitoring cancer progression.

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

Activation of epidermal growth factor receptors in triple-negative breast cancer cells by morphine; analysis through Raman spectroscopy and machine learning

Triple negative breast cancer (TNBC) is a very aggressive form of breast cancer, and the analgesic drug morphine has been shown to promote the proliferation of TNBC cells. This article investigates whether morphine causes activation of epidermal growth factor receptors (EGFR), the roles of μ-opioid and EGFR receptors on TNBC cell proliferation and migration. While examining the changes with molecular techniques, we also aimed to investigate the analysis ability of Raman spectroscopy and machine learning-based approach. Effects of morphine on the proliferation and migration of MDA.MB.231 cells were evaluated by MTT and scratch wound-healing tests, respectively. Morphine-induced phosphorylation of the EGFR was analyzed by western blotting in the presence and absence of μ-receptor antagonist naltrexone and the EGFR-tyrosine kinase inhibitor gefitinib. Morphine-induced EGFR phosphorylation and cell migration were significantly inhibited by pretreatments with both naltrexone and gefitinib; however, morphine-increased cell proliferation was inhibited only by naltrexone. While morphine-induced changes were observed in the Raman scatterings of the cells, the inhibitory effect of naltrexone was analyzed with similarity to the control group. Principal component analysis (PCA) of the Raman confirmed the epidermal growth factor (EGF)-like effect of morphine and was inhibited by naltrexone and partly by gefitinib pretreatments. Our in vitro results suggest that combining morphine with an EGFR inhibitor or a peripherally acting opioidergic receptor antagonist may be a good strategy for pain relief without triggering cancer proliferation and migration in TNBC patients. In addition, our results demonstrated the feasibility of the Raman spectroscopy and machine learning-based approach as an effective method to investigate the effects of agents in cancer cells without the need for complex and time-consuming sample preparation. The support vector machine (SVM) with linear kernel automatically classified the effects of drugs on cancer cells with ∼95% accuracy.

A review of recent advances in the use of complex metal nanostructures for biomedical applications from diagnosis to treatment

Complex metal nanostructures represent an exceptional category of materials characterized by distinct morphologies and physicochemical properties. Nanostructures with shape anisotropies, such as nanorods, nanostars, nanocages, and nanoprisms, are particularly appealing due to their tunable surface plasmon resonances, controllable surface chemistries, and effective targeting capabilities. These complex nanostructures can absorb light in the near-infrared, enabling noteworthy applications in nanomedicine, molecular imaging, and biology. The engineering of targeting abilities through surface modifications involving ligands, antibodies, peptides, and other agents potentiates their effects. Recent years have witnessed the development of innovative structures with diverse compositions, expanding their applications in biomedicine. These applications encompass targeted imaging, surface-enhanced Raman spectroscopy, near-infrared II imaging, catalytic therapy, photothermal therapy, and cancer treatment. This review seeks to provide the nanomedicine community with a thorough and informative overview of the evolving landscape of complex metal nanoparticle research, with a specific emphasis on their roles in imaging, cancer therapy, infectious diseases, and biofilm treatment. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Diagnostic Tools > Diagnostic Nanodevices.

A database of computed Raman spectra of inorganic compounds with accurate hybrid functionals

Raman spectroscopy is widely applied in identifying local structures in materials, but the interpretation of Raman spectra is non-trivial. An accurate computational database of reference spectra calculated with a consistent level of theory can significantly aid in interpreting measured Raman spectra. Here, we present a database of Raman spectra of inorganic compounds calculated with accurate hybrid functionals in density functional theory. Raman spectra were obtained by calculating dynamical matrices and polarizability tensors for structures from the Inorganic Crystal Structure Database. The calculated Raman spectra and other phonon properties (e.g., infrared spectra) are stored in a MongoDB database publicly shared through a web application. We assess the accuracy of our Raman calculations by statistically comparing ~80 calculated spectra with an existing experimental Raman database. To date, the database contains 161 compounds and is continuously growing as we add more materials computed with our automated workflow.

Colocalization of β-Sheets and Carotenoids in Aβ Plaques Revealed with Multimodal Spatially Resolved Vibrational Spectroscopy

The aggregation of amyloid β(Aβ) peptides is at the heart of Alzheimer's disease development and progression. As a result, amyloid aggregates have been studied extensively in vitro, and detailed structural information on fibrillar amyloid aggregates is available. However, forwarding these structural models to amyloid plaques in the human brain is still a major challenge. The chemistry of amyloid plaques, particularly in terms of the protein secondary structure and associated chemical moieties, remains poorly understood. In this report, we use Raman microspectroscopy to identify the presence of carotenoids in amyloid plaques and demonstrate that the abundance of carotenoids is correlated with the overall protein secondary structure of plaques, specifically to the population of β-sheets. While the association of carotenoids with plaques has been previously identified, their correlation with the β structure has never been identified. To further validate these findings, we have used optical photothermal infrared (O-PTIR) spectroscopy, which is a spatially resolved technique that yields complementary infrared contrast to Raman. O-PTIR unequivocally demonstrates the presence of elevated β-sheets in carotenoid-containing plaques and the lack of β structure in noncarotenoid plaques. Our findings underscore the potential link between anti-inflammatory species as carotenoids to specific secondary structural motifs within Aβ plaques and highlight the possible role of chemically distinct plaques in neuroinflammation, which can uncover new mechanistic insights and lead to new therapeutic strategies for AD.

Novel SERS biosensor for rapid detection of breast cancer based on Ag2O-Ag-PSi nanochips

Ag2O-Ag-PSi (porous silicon) surface-enhanced Raman scattering (SERS) chip was successfully synthesized by electrochemical corrosion, in situ reduction and heat treatment technology. The influence of different heat treatment temperature on SERS performance of the chip is studied. The results show that the chip treated at 300 °C has the best SERS performance. The chip was composed of Ag2O-Ag nano core shell with a diameter of 40-60 nm and porous silicon substrate. Then, the optimized chip was used to perform SERS test on serum samples from 30 healthy volunteers and 30 early breast cancer patients, and the baseline was corrected by LabSpec6 software. Finally, the data were analyzed by principal component analysis combined with t-distributed Stochastic Neighbor Embedding (PCA-t-SNE). The results showed that the accuracy of the improved substrate combined with multivariate statistical method was 98%. The shelf life of the chips exceeded six months due to the presence of the Ag2O shell. This study provides a basis for developing a low-cost rapid and sensitive early screening technology for breast cancer.

Conjugation Length-Dependent Raman Scattering Intensity of Conjugated Polymers

Polydiacetylenes, as a class of conjugated polymers with alternating conjugated C═C and C≡C bonds, have emerged as a promising probe material for biomedical Raman imaging, given their ultrastrong Raman scattering intensity. However, the relationship between the structure, especially the molecular length of polydiacetylenes, and their Raman scattering intensity remains unclear. In this work, a series of water-soluble polydiacetylenes, namely poly(deca-4,6-diynedioic acid) (PDDA) with different molecular weights (MWs), is prepared through controlled polymerization and degradation. The ultraviolet-visible (UV-vis) absorption spectroscopic and Raman spectroscopic studies on these polymers reveal that the Raman scattering intensity of PDDA increases nonlinearly with the MW. The MW-Raman scattering intensity relationship in the polymerization process is completely different from that in the degradation process. In contrast, the Raman scattering intensity increases more linearly with the maximal absorbance of the polymer, and the relationship between the Raman scattering intensity and the maximal absorbance of PDDA in the polymerization process is consistent with that in the degradation process. The Raman scattering intensity of PDDA hence exhibits a better dependence on the effective conjugation length of the polymer, which should guide the future design of conjugated polymers for Raman imaging applications.

Conjugated Polymeric Materials in Biological Imaging and Cancer Therapy

Conjugated polymers (CPs) have attracted much attention in the fields of chemistry, medicine, life science, and material science. Researchers have carried out a series of innovative researches and have made significant research progress regarding the unique photochemical and photophysical properties of CPs, expanding the application range of polymers. CPs are polymers formed by the conjugation of multiple repeating light-emitting units. Through precise control of their structure, functional molecules with different properties can be obtained. Fluorescence probes with different absorption and emission wavelengths can be obtained by changing the main chain structure. By modifying the side chain structure with water-soluble groups or selective recognition molecules, electrostatic interaction or specific binding with specific targets can be achieved; subsequently, the purpose of selective recognition can be achieved. This article reviews the research work of CPs in cell imaging, tumor diagnosis, and treatment in recent years, summarizes the latest progress in the application of CPs in imaging, tumor diagnosis, and treatment, and discusses the future development direction of CPs in cell imaging, tumor diagnosis, and treatment.

Nucleic Acid Probes in Bio-Imaging and Diagnostics: Recent Advances in ODN-Based Fluorescent and Surface-Enhanced Raman Scattering Nanoparticle and Nanostructured Systems

Raman nanoparticle probes are a potent class of optical labels for the interrogation of pathological and physiological processes in cells, bioassays, and tissues. Herein, we review the recent advancements in fluorescent and Raman imaging using oligodeoxyribonucleotide (ODN)-based nanoparticles and nanostructures, which show promise as effective tools for live-cell analysis. These nanodevices can be used to investigate a vast number of biological processes occurring at various levels, starting from those involving organelles, cells, tissues, and whole living organisms. ODN-based fluorescent and Raman probes have contributed to the achievement of significant advancements in the comprehension of the role played by specific analytes in pathological processes and have inaugurated new possibilities for diagnosing health conditions. The technological implications that have emerged from the studies herein described could open new avenues for innovative diagnostics aimed at identifying socially relevant diseases like cancer through the utilization of intracellular markers and/or guide surgical procedures based on fluorescent or Raman imaging. Particularly complex probe structures have been developed within the past five years, creating a versatile toolbox for live-cell analysis, with each tool possessing its own strengths and limitations for specific studies. Analyzing the literature reports in the field, we predict that the development of ODN-based fluorescent and Raman probes will continue in the near future, disclosing novel ideas on their application in therapeutic and diagnostic strategies.

Dual-Drug Delivery by Anisotropic and Uniform Hybrid Nanostructures: A Comparative Study of the Function and Substrate-Drug Interaction Properties

By utilizing nanoparticles to upload and interact with several pharmaceuticals in varying methods, the primary obstacles associated with loading two or more medications or cargos with different characteristics may be addressed. Therefore, it is feasible to evaluate the benefits provided by co-delivery systems utilizing nanoparticles by investigating the properties and functions of the commonly used structures, such as multi- or simultaneous-stage controlled release, synergic effect, enhanced targetability, and internalization. However, due to the unique surface or core features of each hybrid design, the eventual drug-carrier interactions, release, and penetration processes may vary. Our review article focused on the drug's loading, binding interactions, release, physiochemical, and surface functionalization features, as well as the varying internalization and cytotoxicity of each structure that may aid in the selection of an appropriate design. This was achieved by comparing the actions of uniform-surfaced hybrid particles (such as core-shell particles) to those of anisotropic, asymmetrical hybrid particles (such as Janus, multicompartment, or patchy particles). Information is provided on the use of homogeneous or heterogeneous particles with specified characteristics for the simultaneous delivery of various cargos, possibly enhancing the efficacy of treatment techniques for illnesses such as cancer.

Compact and ultracompact spectral imagers: technology and applications in biomedical imaging

Significance

Spectral imaging, which includes hyperspectral and multispectral imaging, can provide images in numerous wavelength bands within and beyond the visible light spectrum. Emerging technologies that enable compact, portable spectral imaging cameras can facilitate new applications in biomedical imaging.

Aim

With this review paper, researchers will (1) understand the technological trends of upcoming spectral cameras, (2) understand new specific applications that portable spectral imaging unlocked, and (3) evaluate proper spectral imaging systems for their specific applications.

Approach

We performed a comprehensive literature review in three databases (Scopus, PubMed, and Web of Science). We included only fully realized systems with definable dimensions. To best accommodate many different definitions of "compact," we included a table of dimensions and weights for systems that met our definition.

Results

There is a wide variety of contributions from industry, academic, and hobbyist spaces. A variety of new engineering approaches, such as Fabry-Perot interferometers, spectrally resolved detector array (mosaic array), microelectro-mechanical systems, 3D printing, light-emitting diodes, and smartphones, were used in the construction of compact spectral imaging cameras. In bioimaging applications, these compact devices were used for in vivo and ex vivo diagnosis and surgical settings.

Conclusions

Compact and ultracompact spectral imagers are the future of spectral imaging systems. Researchers in the bioimaging fields are building systems that are low-cost, fast in acquisition time, and mobile enough to be handheld.

Duplex Phenotype Detection and Targeting of Breast Cancer Cells Using Nanotube Nanoprobes and Raman Imaging

We designed, synthesized, and characterized a Raman nanoprobe made of dye-sensitized single-walled carbon nanotubes (SWCNTs) that can selectively target biomarkers of breast cancer cells. The nanoprobe is composed of Raman-active dyes encapsulated inside a SWCNT, whose surface is covalently grafted with poly(ethylene glycol) (PEG) at a density of ∼0.7% per carbon. Using α-sexithiophene- and β-carotene-derived nanoprobes covalently bound to an antibody, either anti-E-cadherin (E-cad) or anti-keratin-19 (KRT19), we prepared two distinct nanoprobes that specifically recognize biomarkers on breast cancer cells. Immunogold experiments and transmission electron microscopy (TEM) images are first used to guide the synthesis protocol for higher PEG-antibody attachment and biomolecule loading capacity. The duplex of nanoprobes was then applied to target E-cad and KRT19 biomarkers in T47D and MDA-MB-231 breast cancer cell lines. Hyperspectral imaging of specific Raman bands allows for simultaneous detection of this nanoprobe duplex on target cells without the need for additional filters or subsequent incubation steps. Our results confirm the high reproducibility of the nanoprobe design for duplex detection and highlight the potential of Raman imaging for advanced biomedical applications in oncology.

Enhanced characterization of breast cancer phenotypes using Raman micro-spectroscopy on stainless steel substrate

Biochemical insights into varying breast cancer (BC) phenotypes can provide a fundamental understanding of BC pathogenesis, while identifying novel therapeutic targets. Raman spectroscopy (RS) can gauge these biochemical differences with high specificity. For routine RS, cells are traditionally seeded onto calcium fluoride (CaF₂) substrates that are costly and fragile, limiting its widespread adoption. Stainless steel has been interrogated previously as a less expensive alternative to CaF₂ substrates, while reporting increased Raman signal intensity than the latter. We sought to further investigate and compare the Raman signal quality measured from stainless steel versus CaF₂ substrates by characterizing different BC phenotypes with altered human epidermal growth factor receptor 2 (HER2) expression. Raman spectra were obtained on stainless steel and CaF₂ substrates for HER2 negative cells - MDA-MB-231, MDA-MB-468 and HER2 overexpressing cells - AU565, SKBr3. Upon analyzing signal-to-noise ratios (SNR), stainless steel provided a stronger Raman signal, improving SNR by 119% at 1450 cm^-1 and 122% at 2925 cm^-1 on average compared to the CaF₂ substrate. Utilizing only 22% of laser power on sample relative to the CaF₂ substrate, stainless steel still yielded improved spectral characterization over CaF₂, achieving 96.0% versus 89.8% accuracy in BC phenotype discrimination and equivalent 100.0% accuracy in HER2 status classification. Spectral analysis further highlighted increased lipogenesis and altered metabolism in HER2 overexpressing cells, which was subsequently visualized with coherent anti-Stokes Raman scattering microscopy. Our findings demonstrate that stainless steel substrates deliver improved Raman signal and enhanced spectral characterization, underscoring its potential as a cost-effective alternative to CaF₂ for non-invasively monitoring cellular biochemical dynamics in translational cancer research.

The emerging applications and advancements of Raman spectroscopy in pediatric cancers

Although the survival rate of pediatric cancer has significantly improved, it is still an important cause of death among children. New technologies have been developed to improve the diagnosis, treatment, and prognosis of pediatric cancers. Raman spectroscopy (RS) is a non-destructive analytical technique that uses different frequencies of scattering light to characterize biological specimens. It can provide information on biological components, activities, and molecular structures. This review summarizes studies on the potential of RS in pediatric cancers. Currently, studies on the application of RS in pediatric cancers mainly focus on early diagnosis, prognosis prediction, and treatment improvement. The results of these studies showed high accuracy and specificity. In addition, the combination of RS and deep learning is discussed as a future application of RS in pediatric cancer. Studies applying RS in pediatric cancer illustrated good prospects. This review collected and analyzed the potential clinical applications of RS in pediatric cancers.

Raman microspectroscopy based TNM staging and grading of breast cancer

The tumor-node-metastasis (TNM) system is the most common way that doctors determine the anatomical extent of cancer on the basis of clinical and pathological criteria. In this study, a spectral histopathological study has been carried out to bridge Raman micro spectroscopy with the breast cancer TNM system. A total of seventy breast tissue samples, including healthy tissue, early, middle, and advanced cancer, were investigated to provide detailed insights into compositional and structural variations that accompany breast malignant evolution. After evaluating the main spectral variations in all tissue types, the generalized discriminant analysis (GDA) pathological diagnostic model was established to discriminate the TNM staging and grading information. Moreover, micro-Raman images were reconstructed by K-means clustering analysis (KCA) for visualizing the lobular acinar in healthy tissue and ductal structures in all early, middle and advanced breast cancer tissue groups. While, univariate imaging techniques were adapted to describe the distribution differences of biochemical components such as tryptophan, β-carotene, proteins, and lipids in the scanned regions. The achieved spectral histopathological results not only established a spectra-structure correlations via tissue biochemical profiles but also provided important data and discriminative model references for in vivo Raman-based breast cancer diagnosis.

Exposing intracellular molecular changes during the differentiation of human-induced pluripotent stem cells into erythropoietin-producing cells using Raman spectroscopy and imaging

The objective of this study was to explore intracellular molecular changes during the differentiation of human-induced pluripotent stem cells (iPSCs) into erythropoietin (EPO)-producing cells using Raman spectroscopy and imaging. Raman imaging data of fixed cells at four stages of cell differentiation were analyzed by a partial least squares (PLS) regression model, and the variations in the intracellular molecular compositions with cell differentiation were investigated. As a result, three biomarkers characterizing the cell phases were identified: dimethyl sulfoxide (DMSO), fatty acids with a low grade of unsaturation, and glycoproteins. The uptake of DMSO by EPO-producing cells, which was added into a culture medium as an inducer for cell differentiation, was detected, and the increase in unsaturated fatty acid concentrations was revealed that lipid metabolism changed over the course of cell differentiation. The decrease in the glycoprotein concentration after the cell phase during which iPSCs differentiated into EPO-producing cells was also made clear. Raman imaging successfully visualized chemical images of these three biomarkers in two dimensions, where the biomarker concentrations independently varied during cell differentiation. These results demonstrated the application potential of the proposed method to regenerative medicine for monitoring cell differentiation and discriminating cell maturation in situ at the molecular level.

Biochemistry and Nanomechanical Properties of Human Colon Cells upon Simvastatin, Lovastatin, and Mevastatin Supplementations: Raman Imaging and AFM Studies

One of the most important areas of medical science is oncology, which is responsible for both the diagnostics and treatment of cancer diseases. Over the years, there has been an intensive development of cancer diagnostics and treatment. This paper shows the comparison of normal (CCD-18Co) and cancerous (CaCo-2) cell lines of the human gastrointestinal tract on the basis of nanomechanical and biochemical properties to obtain information on cancer biomarkers useful in oncological diagnostics. The research techniques used were Raman spectroscopy and imaging and atomic force microscopy (AFM). In addition, the studies also included the effect of the statin compounds—mevastatin, lovastatin, and simvastatin—and their influence on biochemical and nanomechanical changes of cell properties using Raman imaging and AFM techniques. The cytotoxicity of statins was determined using XTT tests.

High Uniformity and Enhancement Au@AgNS 3D Substrates for the Diagnosis of Breast Cancer

Breast cancer appears to be one of the leading causes of cancer-related morbidity and mortality for women worldwide. The accurate and rapid diagnosis of breast cancer is hence critical for the treatment and prognosis of patients. With the vibrational fingerprint information and high detection sensitivity, surface-enhanced Raman spectroscopy (SERS) has been extensively applied in biomedicine. Here, an optimized bimetallic nanosphere (Au@Ag NS) 3D substrate was fabricated for the aim of the diagnosis of breast cancer based on the SERS analysis of the extracellular metabolites. The unique stacking mode of 3D Au@Ag NSs provided multiple plasmonic hot spots according to the theoretical calculations of the electromagnetic field distribution. The low relative standard deviation (RSD = 2.7%) and high enhancement factor (EF = 1.42 × 10⁵) proved the uniformity and high sensitivity. More importantly, the normal breast cells and breast cancer cells could be readily distinguished from the corresponding SERS spectra based on the extracellular metabolites. Furthermore, the clear clusters of SERS spectra from MCF-7 and MDA-MB-231 extracellular metabolites in the orthogonal partial least-squares discriminant analysis plot indicate the distinct metabolic fingerprint between breast cancer cells, which imply their potential clinical application in the diagnosis of breast cancer.

The role of pro- and antiangiogenic factors in angiogenesis process by Raman spectroscopy

Raman spectroscopy and Raman imaging are powerful techniques to monitor biochemical composition around blood vessel. The aim of this study was to understand the role of pro- and antiangiogenic factors in angiogenesis process. Raman imaging and Raman single spectrum measurements allow the diagnosis of cancer biochemical changes in blood vessel based on several biomarkers simultaneously. We have demonstrated that Raman imaging combined with statistical methods are useful to monitoring pro- and antiangiogenic factors responsible for angiogenesis process. In this work Raman markers of proangiogenic and antiangiogenic factors were identified based on their vibrational signatures. Obtained results can help understand how growing tumor create its vascular system.

Recent Advance in Biological Responsive Nanomaterials for Biosensing and Molecular Imaging Application

In recent decades, as a subclass of biomaterials, biologically sensitive nanoparticles have attracted increased scientific interest. Many of the demands for physiologically responsive nanomaterials in applications involving the human body cannot be met by conventional technologies. Due to the field's importance, considerable effort has been expended, and biologically responsive nanomaterials have achieved remarkable success thus far. This review summarizes the recent advancements in biologically responsive nanomaterials and their applications in biosensing and molecular imaging. The nanomaterials change their structure or increase the chemical reaction ratio in response to specific bio-relevant stimuli (such as pH, redox potentials, enzyme kinds, and concentrations) in order to improve the signal for biologically responsive diagnosis. We use various case studies to illustrate the existing issues and provide a clear sense of direction in this area. Furthermore, the limitations and prospects of these nanomaterials for diagnosis are also discussed.

O-GlcNAcylation mapping of single living cells by in situ quantitative SERS imaging

O-GlcNAcylation is involved in many biological processes including cancerization. Nevertheless, its in situ quantification in single living cells is still a bottleneck. Here we develop a quantitative SERS imaging strategy for mapping the O-GlcNAcylation distribution of single living cells. O-GlcNAcylated compounds (OGCs) can be quantified through their in situ azide labeling and then a click reaction competing with azide and Raman reporter labeled 15 nm-gold nanoparticles (AuNPs) for linking to dibenzocyclooctyne labeled 40 nm-AuNPs to produce OGC-negatively correlated SERS signals. The calibration curve obtained in vitro can be conveniently used for detecting OGCs in different areas of single living cells due to the negligible effect of cell medium on the click linkage and Raman signal. This method has been successfully applied in mapping O-GlcNAcylation distribution in different cell lines and monitoring O-GlcNAcylation variation during cell cycling, which demonstrate its great practicability and expansibility in glycosylation related analysis.

A quantitative SERS imaging strategy is developed for O-GlcNAcylation mapping of single living cells through a competitive click reaction.

Tumor microenvironment-responsive dynamic inorganic nanoassemblies for cancer imaging and treatment

Dynamic inorganic nanoassemblies (DINAs) have emerged as smart nanomedicine platforms with promising potential for bioimaging and targeted drug delivery. In this review, we keep abreast of the advances in development of tumor microenvironment (TME)-responsive DINAs to meet the challenges associated with precise cancer therapy. TME-responsive DINAs are designed to achieve precise switches of structures/functions in response to TME-specific stimuli including reactive oxygen species (ROS), reduced pH and hypoxia, so as to enhance the tumor accumulation of nanoassemblies, overcome the biological barriers during intratumoral penentration of therapeutics, and achieve tumor-specific imaging and therapy. This progress report will summarize various types of recently reported smart DINAs for TME-responsive tumor imaging and therapy. Their future development towards potential clinical translation will also be discussed.

Vibrational Fingerprint Analysis of an Azo-based Resonance Raman Scattering Probe for Imaging Proton Distribution in Cellular Lysosomes

Due to the fundamental mechanism of vibrational state transitions for chemical bonds, the spectra of Raman scattering are narrow-banded and photostable signals capable of probing specific reactions. In the case of protonation/deprotonation reactions, certain chemical bonds are broken and new bonds are formed. Based on the changes of the vibrational modes for the corresponding bonds, fingerprint analysis of multiple Raman bands may allow for the in situ visualization of proton distribution in live cells. However, Raman scattering faces the well-known challenge of low sensitivity. To perform the vibrational fingerprint analysis of Raman scattering by overcoming this challenge, we developed an azo-based resonance Raman pH probe. It was an azobenzene-featured small molecule responsive to protons with the inherent Raman signal ∼10⁴-fold more intense than that of the conventional alkyne-type Raman reporter 5-ethynyl-2'-deoxyuridine. Through the substitution of the electron-donating and -withdrawing entities to the azobenzene group, the effect of resonance Raman scattering and fluorescence quenching was obtained. This effect resulted in a significant Raman enhancement factor of ∼10³ compared to the counterpart molecules without the molecular design. Based on the enhanced Raman sensitivity of the azo-based resonance Raman pH probe, the identification of vibrational fingerprint changes at the azo group was achieved during the protonation/deprotonation reactions, and the vibrational fingerprint analysis resolved a pH difference of less than 0.2 unit. The method enabled sensitive hyperspectral cell imaging that clearly visualized the change of proton distribution in autophagic cells.

From Raman to SESORRS: moving deeper into cancer detection and treatment monitoring

Raman spectroscopy is a non-invasive technique that allows specific chemical information to be obtained from various types of sample. The detailed molecular information that is present in Raman spectra permits monitoring of biochemical changes that occur in diseases, such as cancer, and can be used for the early detection and diagnosis of the disease, for monitoring treatment, and to distinguish between cancerous and non-cancerous biological samples. Several techniques have been developed to enhance the capabilities of Raman spectroscopy by improving detection sensitivity, reducing imaging times and increasing the potential applicability for in vivo analysis. The different Raman techniques each have their own advantages that can accommodate the alternative detection formats, allowing the techniques to be applied in several ways for the detection and diagnosis of cancer. This feature article discusses the various forms of Raman spectroscopy, how they have been applied for cancer detection, and the adaptation of the techniques towards their use for in vivo cancer detection and in clinical diagnostics. Despite the advances in Raman spectroscopy, the clinical application of the technique is still limited and certain challenges must be overcome to enable clinical translation. We provide an outlook on the future of the techniques in this area and what we believe is required to allow the potential of Raman spectroscopy to be achieved for clinical cancer diagnostics.

A decade of alkyne-tag Raman imaging (ATRI): applications in biological systems

Alkyne functional groups have Raman signatures in a region (1800 cm-1 to 2800 cm-1) that is free from interference from cell components, known as the "silent region", and alkyne signals in this region were first utilized a decade ago to visualize the nuclear localization of a thymidine analogue EdU. Since then, the strategy of Raman imaging of biological samples by using alkyne functional groups, called alkyne-tag Raman imaging (ATRI), has become widely used. This article reviews the applications of ATRI in biological samples ranging from organelles to whole animal models, and briefly discusses the prospects for this technique.

A pore-forming protein-induced surface-enhanced Raman spectroscopic strategy for dynamic tracing of cell membrane repair

The plasma membrane repair holds significance for maintaining cell survival and homeostasis. To achieve the sensitive visualization of membrane repair process for revealing its mechanism, this work designs a perforation-induced surface-enhanced Raman spectroscopy (SERS) strategy by conjugating Raman reporter (4-mercaptobenzoic acid) loaded gold nanostars with pore-forming protein streptolysin O (SLO) to induce the SERS signal on living cells. The SERS signal obviously decreases with the initiation of membrane repair and the degradation of SLO pores due to the departure of gold-nanostar-conjugated SLO. Thus, the designed strategy can dynamically visualize the complete cell membrane repair and provide a sensitive method to demonstrate the SLO endocytosis- and exocytosis-mediated repairing mechanism. Using DOX-resistant MCF-7 cells as a model, a timely repair-blocking technology for promoting the highly efficient treatment of drug-resistant cancer cells is also proposed. This work opens an avenue for probing the plasma membrane repairing mechanisms and designing the precision therapeutic schedule.

Interfacial hydration determines orientational and functional dimorphism of sterol-derived Raman tags in lipid-coated nanoparticles

Lipid-coated noble metal nanoparticles (L-NPs) combine the biomimetic surface properties of a self-assembled lipid membrane with the plasmonic properties of a nanoparticle (NP) core. In this work, we investigate derivatives of cholesterol, which can be found in high concentrations in biological membranes, and other terpenoids, as tunable, synthetic platforms to functionalize L-NPs. Side chains of different length and polarity, with a terminal alkyne group as Raman label, are introduced into cholesterol and betulin frameworks. The synthesized tags are shown to coexist in two conformations in the lipid layer of the L-NPs, identified as "head-out" and "head-in" orientations, whose relative ratio is determined by their interactions with the lipid-water hydrogen-bonding network. The orientational dimorphism of the tags introduces orthogonal functionalities into the NP surface for selective targeting and plasmon-enhanced Raman sensing, which is utilized for the identification and Raman imaging of epidermal growth factor receptor-overexpressing cancer cells.

Studying the pathological and biochemical features in breast cancer progression by confocal Raman microspectral imaging of excised tissue samples

Confocal Raman microspectral imaging (CRMI) has been used to detect the spectra-pathological features of ductal carcinoma in situ (DCIS) and lobular hyperplasia (LH) compared with the heathy (H) breast tissue. A total of 15-20 spectra were measured from healthy tissue, LH tissue, and DCIS tissue. One-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple tests were used to evaluate the peak intensity variations in all three tissue types. Besides that, linear discrimination analysis (LDA) algorithm was adopted in combination with principal component analysis (PCA) to classify the spectral features from tissues at different stages along the continuum to breast cancer. Moreover, by using the point-by-point scanning methodology, spectral datasets were obtained and reconstructed for further pathologic visualization by multivariate imaging methods, including K-mean clustering analysis (KCA) and PCA. Univariate imaging of individual Raman bands was also used to describe the differences in the distribution of specific molecular components in the scanning area. After a detailed spectral feature analysis from 800 to 1800 cm^-1 and 2800 to 3000 cm^-1 for all the three tissue types, the histopathological features were visualized based on the content and structural variations of lipids, proteins, phenylalanine, carotenoids and collagen, as well as the calcification phenomena. The results obtained not only allowed a detailed Raman spectroscopy-based understanding of the malignant transformation process of breast cancer, but also provided a solid spectral data support for developing Raman based breast cancer clinical diagnostic techniques.

Label-free breast cancer detection using fiber probe-based Raman spectrochemical biomarker-dominated profiles extracted from a mixture analysis algorithm

We report the development of a label-free, simple, and high efficiency breast cancer detection platform with multimodal biomarker analytic algorithms on a portable 785 nm Raman setup with an endoscopic Raman-lensed fiber optic probe. We propose a multimodal biomarker extraction algorithm (PCMA) implemented by combining a multivariate statistics principal component analysis (PCA) algorithm and a multivariate curve resolution-alternating least squares (MCR-ALS) computational model for extraction of the biomarker information hidden in Raman spectrochemical data. We show that the six Raman spectrochemical peaks at 1009, 1270, 1305/1443, 1658, and 1750 cm-1 assigned to phenylalanine, amide III in proteins, CH2 deformation in lipids, amide I in proteins, and carbonyl, respectively, can be used as a biomarker for breast cancer diagnosis using the biomarker-dominated PCMA spectrochemical spectra of breast tissues. From 20 human breast tissues, the PCMA-linear discriminant analysis (PCMA-LDA) identification method achieved high classification performance with a sensitivity and specificity >99% along with an improvement of approximately 4.5% compared to the performance without the PCMA mixture analysis algorithm. Our label-free breast cancer detection method has the potential for clinical application to diagnose breast cancer in real-time during surgery.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Elucidating the chemical and structural composition of breast cancer using Raman micro-spectroscopy

The current gold standard for breast cancer (BC) diagnosis is the histopathological assessment of biopsy samples. However, this approach limits the understanding of the disease in terms of biochemical changes. Raman spectroscopy has demonstrated its potential to provide diagnostic information and facilitate the prediction of the biochemical progression for different diseases in a rapid non-destructive manner. Raman micro-spectroscopy was used to characterize and differentiate breast cancer and normal breast samples. In this study, tissue microarrays of breast cancer biopsy samples (n=499) and normal breast (n=79) were analyzed using Raman micro-spectroscopy, and principal component analysis (PCA) was used for feature extraction. Linear discriminant analysis (LDA) was used for feature validation. Normal breast and breast cancer were successfully differentiated with a sensitivity of 90 % and specificity of 78 %. Dominance of lipids, specifically fatty acids, was identified in the normal tissue whereas proteins dominated the malignant spectra. Higher intensities of carotenoids, β-carotenoids, and cholesterol were identified in the normal breast while ceramide related peaks were mostly visible in the BC spectra. The biochemical characterization achieved with Raman micro-spectroscopy showed that this technique is a powerful and reliable tool for the monitoring and diagnosis of BC, regardless of the cohort heterogeneity. Raman spectroscopy also provided a powerful insight into the biochemical changes associated with the BC progression and evolution.

Azo-Enhanced Raman Scattering for Enhancing the Sensitivity and Tuning the Frequency of Molecular Vibrations

Raman scattering provides stable narrow-banded signals that potentially allow for multicolor microscopic imaging. The major obstacle for the applications of Raman spectroscopy and microscopy is the small cross section of Raman scattering that results in low sensitivity. Here, we report a new concept of azo-enhanced Raman scattering (AERS) by designing the intrinsic molecular structures using resonance Raman and concomitant fluorescence quenching strategies. Based on the selection of vibrational modes and the enhancing unit of azobenzenes, we obtained a library of AERS molecules with specific Raman signals in the fingerprint and silent frequency regions. The spectral characterization and molecular simulation revealed that the azobenzene unit conjugated to the vibrational modes significantly enhanced Raman signals due to the mechanism of extending the conjugation system, coupling the electronic-vibrational transitions, and improving the symmetry of vibrational modes. The nonradiative decay of azobenzene from the excited state quenched the commitment fluorescence, thus providing a clean background for identifying Raman scattering. The most sensitive AERS molecules produced Raman signals of more than 4 orders of magnitude compared to 5-ethynyl-2'-deoxyuridine (EdU). In addition, a frequency tunability of 10 distinct Raman bands was achieved by selecting different types of vibrational modes. This methodology of AERS allows for designing small-molecule Raman probes to visualize various entities in complex systems by multicolor spontaneous Raman imaging. It will open new prospects to explore innovative applications of AERS in interdisciplinary research fields.

Investigation of dual plasmonic core-shell Ag@CuS nanoparticles for potential surface-enhanced Raman spectroscopy-guided photothermal therapy

Aim: To prepare efficient metal-semiconductor nanoparticles as noninvasive, real-time imaging probes for photothermal therapy (PTT) applications. Materials & methods: A bottom-up approach was used to fabricate core-shell Ag@CuS nanoparticles (NPs). PTT and Raman mapping were done using HeLa cells. Theoretical simulation of electric field enhancement and heat dissipation density of Ag@CuS NPs was performed. Results: PTT-induced hyperthermia was achieved under 940 nm near-infrared light irradiation. Surface-enhanced Raman spectroscopy (SERS) signals of dye molecules were observed when conjugated with Ag@CuS NPs. Conclusion: Ag@CuS NPs are found to be efficient for SERS imaging and localized heating under laser irradiation, making a promising candidate for SERS-guided PTT.

Oxidative stress induced by tBHP in human normal colon cells by label free Raman spectroscopy and imaging. The protective role of natural antioxidants in the form of β-carotene

The present study aimed to investigate the protective effect of β-carotene on the oxidative stress injury of human normal colon cell line CCD-18Co triggered by tert-butyl hydroperoxide (tBHP). XTT examination was used to determine cell viability after β-carotene supplementation and to determine the optimal concentration of antioxidant in spectroscopic studies. Cell biochemistry for the CCD-18Co control group, after tBHP addition and for cells in the β-carotene-tBHP model was studied using label-free Raman microspectroscopy. Results for stress treated CCD-18Co human colon normal cells and human colon cancer cells Caco-2 based on vibration features were also compared. Pretreatment with β-carotene alleviated damage in CCD-18Co human normal colon cells induced by tBHP and showed the preventative effect on cell apoptosis. Treatment with β-carotene altered the level of ROS investigated based on intensities of Raman peaks typical for lipids, proteins and nucleic acids. The present study confirmed the antioxidant, protective role of β-carotene against ROS by using spectroscopic label-free Raman techniques.

Template-assisted fabrication of Ag-nanoparticles@ZnO-nanorods array as recyclable 3D surface enhanced Raman scattering substrate for rapid detection of trace pesticides

We present a template-assisted fabrication method for a large-scale ordered arrays of ZnO nanorods (ZnO-NRs) modified with Ag nanoparticles (Ag-NPs), which possess high-density three-dimensional (3D) hot spots uniformly dispersed all over the substrate, being beneficial to ultrahigh sensitivity of surface enhanced Raman scattering (SERS) detection. These achieved Ag-NPs@ZnO-NRs arrays show high sensitivity, good spectral uniformity and reproducibility as substrates for SERS detection. Using the arrays, both dye molecules (rhodamine 6G, R6G) and organic pollutants like toxic pesticides (thiram and methyl parathion) are detected, with the detection limits of thiram and methyl parathion being 0.79 × 10^-9 M and 1.51 × 10^-8 M, respectively. In addition, the Ag-NPs@ZnO-NRs arrays have a self-cleaning function because the analyte molecules can be photocatalytic degraded using ultraviolet irradiation, showing that the 3D recyclable arrays have promising opportunities to be applied in rapid SERS-based detection of toxic organic pesticides.

Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities

Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.

Vibrational Spectroscopy for Identification of Metabolites in Biologic Samples

Vibrational spectroscopy (mid-infrared (IR) and Raman) and its fingerprinting capabilities offer rapid, high-throughput, and non-destructive analysis of a wide range of sample types producing a characteristic chemical "fingerprint" with a unique signature profile. Nuclear magnetic resonance (NMR) spectroscopy and an array of mass spectrometry (MS) techniques provide selectivity and specificity for screening metabolites, but demand costly instrumentation, complex sample pretreatment, are labor-intensive, require well-trained technicians to operate the instrumentation, and are less amenable for implementation in clinics. The potential for vibration spectroscopy techniques to be brought to the bedside gives hope for huge cost savings and potential revolutionary advances in diagnostics in the clinic. We discuss the utilization of current vibrational spectroscopy methodologies on biologic samples as an avenue towards rapid cost saving diagnostics.

Raman Microscopy: Progress in Research on Cancer Cell Sensing

In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.

A three-dimensional discriminant analysis approach for hyperspectral images

Raman hyperspectral imaging is a powerful technique that provides both chemical and spatial information of a sample matrix being studied. The generated data are composed of three-dimensional (3D) arrays containing the spatial information across the x- and y-axis, and the spectral information in the z-axis. Unfolding procedures are commonly employed to analyze this type of data in a multivariate fashion, where the spatial dimension is reshaped and the spectral data fits into a two-dimensional (2D) structure and, thereafter, common first-order chemometric algorithms are applied to process the data. There are only a few algorithms capable of working with the full 3D array. Herein, we propose new algorithms for 3D discriminant analysis of hyperspectral images based on a three-dimensional principal component analysis linear discriminant analysis (3D-PCA-LDA) and a three-dimensional discriminant analysis quadratic discriminant analysis (3D-PCA-QDA) approach. The analysis was performed in order to discriminate simulated and real-world data, comprising benign controls and ovarian cancer samples based on Raman hyperspectral imaging, in which 3D-PCA-LDA and 3D-PCA-QDA achieved far superior performance than classical algorithms using unfolding procedures (PCA-LDA, PCA-QDA, partial lest squares discriminant analysis [PLS-DA], and support vector machines [SVM]), where the classification accuracies improved from 66% to 83% (simulated data) and from 50% to 100% (real-world dataset) after employing the 3D techniques. 3D-PCA-LDA and 3D-PCA-QDA are new approaches for discriminant analysis of hyperspectral images multisets to provide faster and superior classification performance than traditional techniques.

Integrated Proteomic and N-Glycoproteomic Analyses of Human Breast Cancer

Breast cancer is one of the most common cancers in women worldwide. In the past decades, many advances have been made in understanding and treating breast cancer. However, due to the highly heterogeneous nature of this disease, a precise characterization of breast cancer on the molecular level is of great importance but not yet readily available. In the present study, we systematically profiled proteomes and N-glycoproteomes of cancerous, paracancerous, and distal noncancerous tissues from patients with breast cancer. The data revealed distinct proteomic and N-glycoproteomic landscapes between different tissues, showing biological insights obtained from the two data sets were complementary. Specifically, the complement and angiogenesis pathways in the paracancerous tissues were activated. Taken together, the changes that occurred in paracancer tissue and N-glycoproteomics are important complements to the conventional proteomic analysis of cancer tissue. Their combination provides more precise and sensitive molecular correlates of breast cancer. Our data and strategy shed light on precisely defining breast cancer, providing valuable information for individual patient diagnosis and treatment. The MS data of this study have been deposited under the accession number IPX0001924000 at iProX.