Discrimination between ricin and sulphur mustard toxicity in vitro using Raman spectroscopy

Surface-enhanced Raman spectroscopy analysis of serum samples of typhoid patients of different stages

BACKGROUND

Surface-enhanced Raman spectroscopy (SERS) of body fluids is considered a quick, simple and easy to use method for the diagnosis of disease.

OBJECTIVES

To evaluate rapid, reliable, and non-destructive SERS-based diagnostic tool with multivariate data analysis including principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) for classification of different stages of typhoid on the basis of characteristic SERS spectral features.

METHODS

SERS has been used for analysis of serum samples of different stages of typhoid including early acute stage and late acute stage in comparison with healthy samples, in order to investigate capability of this technique for diagnosis of typhoid. SERS spectral features associated with the biochemical changes taking place during the development of the typhoid fever were analyzed and identified.

RESULTS

The value of area under the receiver operating characteristics (AUROC) for early acute stage versus healthy is 0.87 and that for healthy versus late acute stage is 0.52. PLS-DA classifier model gives values of 100 % for accuracy, sensitivity and specificity, respectively for the SERS spectral data sets of healthy versus early acute stage. Moreover, this classifier model gives values of 91 %, 89 % and 97 % for accuracy, sensitivity and specificity, respectively for the SERS spectral data sets of healthy versus late acute stage.

CONCLUSIONS

Based on preliminary work it is concluded that SERS has potential to diagnose various stages of typhoid fever including early acute and late acute stage in comparison with healthy samples.

Raman microspectroscopy and Raman imaging reveal biomarkers specific for thoracic aortic aneurysms

Aortic rupture and dissection are life-threatening complications of ascending thoracic aortic aneurysms (aTAAs), and risk assessment has been largely based on the monitoring of lumen size enlargement. Temporal changes in the extracellular matrix (ECM), which has a critical impact on aortic remodeling, are not routinely evaluated, and cardiovascular biomarkers do not exist to predict aTAA formation. Here, Raman microspectroscopy and Raman imaging are used to identify spectral biomarkers specific for aTAAs in mice and humans by multivariate data analysis (MVA). Multivariate curve resolution-alternating least-squares (MCR-ALS) combined with Lasso regression reveals elastic fiber-derived (Ce1) and collagen fiber-derived (Cc6) components that are significantly increased in aTAA lesions of murine and human aortic tissues. In particular, Cc6 detects changes in amino acid residues, including phenylalanine, tyrosine, tryptophan, cysteine, aspartate, and glutamate. Ce1 and Cc6 may serve as diagnostic Raman biomarkers that detect alterations of amino acids derived from aneurysm lesions.

Label-free Raman imaging of human/murine ascending thoracic aortic aneurysm (aTAA)

Multivariate analysis of Raman spectra allows detection of aTAA molecular features

Identification of spectral biomarkers for aTAA in elastic and collagen fibers

Alterations in amino acid spectra correlate with aTAA formation

Non-invasive cell classification using the Paint Raman Express Spectroscopy System (PRESS)

Raman scattering represents the distribution and abundance of intracellular molecules, including proteins and lipids, facilitating distinction between cellular states non-invasively and without staining. However, the scattered light obtained from cells is faint and cells have complex structures, making it difficult to obtain a Raman spectrum covering the entire cell in a short time using conventional methods. This also prevents efficient label-free cell classification. In the present study, we developed the Paint Raman Express Spectroscopy System, which uses two fast-rotating galvano mirrors to obtain spectra from a wide area of a cell. By using this system and applying machine learning, we were able to acquire broad spectra of a variety of human and mouse cell types, including pluripotent stem cells and confirmed that each cell type can be classified with high accuracy. Moreover, we classified different activation states of human T cells, despite their similar morphology. This system could be used for rapid and low-cost drug evaluation and quality management for drug screening in cell-based assays.

Label-Free Evaluation of Chromatin Condensation in Human Normal Morphology Sperm Using Raman Spectroscopy

Chromatin condensation is one of the main factors essential for sperm function. Evaluation of chromatin condensation by current methods render the assessed sperm unsuitable for assisted reproduction. We examined the Raman spectra of normal morphology sperm to determine whether a non-invasive confocal Raman spectroscopy can detect spectral differences between groups having different levels of chromatin condensation. Semen samples from 85 donors who underwent ICSI were obtained. Chromomycin A3, aniline blue and acridine orange staining were performed to evaluate the protamine deficiency, histone retention and DNA fragmentation respectively. Raman spectra were obtained from 50 normal morphology sperm for each donor. Spectral analysis was performed using home written programs in LabVIEW software and samples were grouped based on chromomycin A3 staining. Raman peaks intensities at 670 cm^-1, 731 cm^-1, 785 cm^-1, 858 cm^-1, 1062 cm^-1, 1098 cm^-1, 1185 cm^-1, 1372 cm^-1, 1424 cm^-1, 1450 cm^-1, 1532 cm^-1, 1618 cm^-1 and 1673 cm^-1 were significantly correlated with at least one of the sperm staining methods. The median intensity of the Raman peaks at 670 cm^-1, 731 cm^-1, 785 cm^-1, 1062 cm^-1, 1098 cm^-1, 1185 cm^-1, 1372 cm^-1, 1424 cm^-1, 1450 cm^-1, 1532 cm^-1, 1618 cm^-1 and 1673 cm^-1 show a significant difference between the CMA3≤41 and CMA3>41groups. The Raman spectroscopic measurements represent a promising diagnostic tool that has the ability to label-free detect sperm with chromatin abnormalities, such as improper chromatin condensation and DNA fragmentation to a certain degree similar to that of the existing staining techniques at the individual cell level.

Raman spectroscopy and artificial intelligence to predict the Bayesian probability of breast cancer

This study addresses the core issue facing a surgical team during breast cancer surgery: quantitative prediction of tumor likelihood including estimates of prediction error. We have previously reported that a molecular probe, Laser Raman spectroscopy (LRS), can distinguish healthy and tumor tissue. We now report that combining LRS with two machine learning algorithms, unsupervised k-means and stochastic nonlinear neural networks (NN), provides rapid, quantitative, probabilistic tumor assessment with real-time error analysis. NNs were first trained on Raman spectra using human expert histopathology diagnostics as gold standard (74 spectra, 5 patients). K-means predictions using spectral data when compared to histopathology produced clustering models with 93.2-94.6% accuracy, 89.8-91.8% sensitivity, and 100% specificity. NNs trained on k-means predictions generated probabilities of correctness for the autonomous classification. Finally, the autonomous system characterized an extended dataset (203 spectra, 8 patients). Our results show that an increase in DNA|RNA signal intensity in the fingerprint region (600-1800 cm-1) and global loss of high wavenumber signal (2800-3200 cm-1) are particularly sensitive LRS warning signs of tumor. The stochastic nature of NNs made it possible to rapidly generate multiple models of target tissue classification and calculate the inherent error in the probabilistic estimates for each target.

Applicability of Raman spectroscopy on porcine parvovirus and porcine circovirus type 2 detection

Porcine parvovirus (PPV) is one of the major infectious causes of reproductive failure of swine. This disease is characterized by embryonic and fetal infection and death, responsible for important economic losses. PPV is also implicated as a trigger in the development of post-weaning multisystemic wasting syndrome (PMWS) caused by Porcine circovirus type 2 (PCV2). Their detection is PCR-based, which is quite sensitive and specific, but laborious, costly and time-demanding. Therefore, this study aimed to assess Raman spectroscopy (RS) as a diagnostic tool for PPV and PCV2 due to its label-free properties and unique ability to search and identify molecular fingerprints. Briefly, swine testis (ST) cells were inoculated with PPV or PCV2 and in vitro cultured (37 °C, 5% CO₂) for four days. Fixed cells were then submitted to RS investigation using a 633 nm laser. A total of 225 spectra centered at 1300 cm^-1 was obtained for each sample (5 spectra/cell; 15 cells/replicate; 3 replicates) of PPV-, PCV2-infected and uninfected (control) ST cells. Clear statistical discrimination between samples from both virus-infected cells was achieved with a Principal Component - Linear Discriminant Analysis (PCA-LDA) model, reaching sensitivity rates from 95.55% to 97.77%, respectively to PCV2- and PPV-infected cells. These results were then submitted to a Leave-One-Out (LOO) validation algorithm resulting in 99.97% of accuracy. Extensive band assignment was analyzed and compiled for better understanding of PPV and PCV2 virus-cell interaction, demonstrating that specific protein, lipids and DNA/RNA bands are the most important assignments related to discrimination of virus-infected from uninfected cells. In conclusion, these results represent promising bases for RS application on PCV2 and PPV detection for future diagnostic applications.

Laparoscopic Peritoneal Wash Cytology-Derived Primary Human Mesothelial Cells for In Vitro Cell Culture and Simulation of Human Peritoneum

Peritoneal mucosa of mesothelial cells line the abdominal cavity, surround intestinal organs and the female reproductive organs and are responsible for immunological integrity, organ functionality and regeneration. Peritoneal diseases range from inflammation, adhesions, endometriosis, and cancer. Efficient technologies to isolate and cultivate healthy patient-derived mesothelial cells with maximal purity enable the generation of capable 2D and 3D as well as in vivo-like microfluidic cell culture models to investigate pathomechanisms and treatment strategies. Here, we describe a new and easily reproducible technique for the isolation and culture of primary human mesothelial cells from laparoscopic peritoneal wash cytology. We established a protocol containing multiple washing and centrifugation steps, followed by cell culture at the highest purity and over multiple passages. Isolated peritoneal mesothelial cells were characterized in detail, utilizing brightfield and immunofluorescence microscopy, flow cytometry as well as Raman microspectroscopy and multivariate data analysis. Thereby, cytokeratin expression enabled specific discrimination from primary peritoneal human fibroblasts. Raman microspectroscopy and imaging were used to study morphology and biochemical properties of primary mesothelial cell culture compared to cryo-fixed and cryo-sectioned peritoneal tissue.

Comparison of surface enhanced Raman spectroscopy and Raman spectroscopy for the detection of breast cancer based on serum samples

In this study, surface enhanced Raman spectroscopy (SERS) and Raman spectroscopy (RS), are employed for the classification of different stages of breast cancer using clinically diagnosed serum samples from breast cancer patients and healthy individuals. These serum samples are compared for their spectral features acquired by SERS and RS to establish spectral features that can be considered as spectral markers of breast cancer diagnosis and classification. SERS features related to DNA, proteins and lipids were observed which are solely observed in the serum samples of patients at different stages of breast cancer as compared to healthy samples. In order to explore the capability of SERS and RS and their comparison as an analytical tool for the efficient understanding of the progression of breast cancer, Principal Component Analysis (PCA) is done for the SERS and RS spectra of control, stage 2, stage 3 and stage 4. Furthermore, the Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to compare the diagnostic performance of SERS and Raman spectroscopy for the classification of disease positive samples and healthy ones. The sensitivity and specificity and area under receiver operating characteristic (AUROC) curve values for SERS data were 90%, 98.4%, and 94% respectively which were higher as compared to Raman spectral data for which these values were found to be 88.2%, 97.7%, and 83.4% respectively.

Surface Enhanced Raman Spectroscopy of the serum samples for the diagnosis of Hepatitis C and prediction of the viral loads

In this study, Surface Enhanced Raman Spectroscopy (SERS) was used for the characterization of Hepatitis C virus (HCV) in blood serum samples. For this purpose silver nanoparticles (Ag NPs) were used as substrates and SERS spectra were acquired from different clinically diagnosed HCV positive serum samples as well as from healthy individuals. Notably, same set of samples were also evaluated with Raman spectroscopy and SERS was found to be more helpful for the identification of the spectral features associated with the development of HCV infection. Different SERS features associated with the RNA bases were observed solely in the HCV positive serum as compared to the healthy samples which can be considered as SERS spectral markers of the HCV infection. Furthermore, principal component analysis (PCA) of the SERS spectral data was found to be very helpful in differentiation of spectral data of serum samples with different viral loads PLSR model was constructed to compare the capability of SERS and Raman analysis in the prediction of viral loads. It is found that SERS shows lower root mean square error of cross validation (RMSECV) and higher goodness of the model (R²) values than Raman data.

Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum

BACKGROUND

Colorectal cancer (CRC) is an important disease worldwide, accounting for the second highest number of cancer-related deaths and the third highest number of new cancer cases. The blood test is a simple and minimally invasive diagnostic test. However, there is currently no blood test that can accurately diagnose CRC.

AIM

To develop a comprehensive, spontaneous, minimally invasive, label-free, blood-based CRC screening technique based on Raman spectroscopy.

METHODS

We used Raman spectra recorded using 184 serum samples obtained from patients undergoing colonoscopies. Patients with malignant tumor histories as well as those with cancers in organs other than the large intestine were excluded. Consequently, the specific diseases of 184 patients were CRC (12), rectal neuroendocrine tumor (2), colorectal adenoma (68), colorectal hyperplastic polyp (18), and others (84). We used the 1064-nm wavelength laser for excitation. The power of the laser was set to 200 mW.

RESULTS

Use of the recorded Raman spectra as training data allowed the construction of a boosted tree CRC prediction model based on machine learning. Therefore, the generalized R² values for CRC, adenomas, hyperplastic polyps, and neuroendocrine tumors were 0.9982, 0.9630, 0.9962, and 0.9986, respectively.

CONCLUSION

For machine learning using Raman spectral data, a highly accurate CRC prediction model with a high R² value was constructed. We are currently planning studies to demonstrate the accuracy of this model with a large amount of additional data.

Fixed versus live endothelial cells: The effect of glutaraldehyde fixation manifested by characteristic bands on the Raman spectra of cells

This work shows an impact of glutaraldehyde (GA) fixation on endothelial cells. Raman spectroscopy imaging was used as a method to monitor biochemical content of the cells due to GA fixation since this is an approach frequently used for studying cells by means of Raman imaging. To get a deeper insight into the changes and to understand them better the measurements of live and fixed cells were performed using two lasers, i.e. 488 and 532 nm. It has been demonstrated that GA fixation affects lipids, proteins, nucleic acid and carbohydrates to small extent. The application of 488 nm laser line seems to be more efficient for live cells due to the small impact of cytochrome resonance on Raman spectra, however 532 nm line is more beneficial for fixed cells due to higher quantum efficiency of the detector, thus leading to higher intensity of Raman bands. Generally, the changes due to fixation are not pronounced but cannot be ignored and the knowledge about them can help in a proper interpretation of data collected for fixed versus live cells.

Machine Learning Approach to Raman Spectrum Analysis of MIA PaCa-2 Pancreatic Cancer Tumor Repopulating Cells for Classification and Feature Analysis

A machine learning approach is applied to Raman spectra of cells from the MIA PaCa-2 human pancreatic cancer cell line to distinguish between tumor repopulating cells (TRCs) and parental control cells, and to aid in the identification of molecular signatures. Fifty-one Raman spectra from the two types of cells are analyzed to determine the best combination of data type, dimension size, and classification technique to differentiate the cell types. An accuracy of 0.98 is obtained from support vector machine (SVM) and k-nearest neighbor (kNN) classifiers with various dimension reduction and feature selection tools. We also identify some possible biomolecules that cause the spectral peaks that led to the best results.

Combination of an Artificial Intelligence Approach and Laser Tweezers Raman Spectroscopy for Microbial Identification

Raman spectroscopy is a nondestructive, label-free, highly specific approach that provides the chemical information on materials. Thus, it is suitable to be used as an effective analytical tool to characterize biological samples. Here we introduce a novel method that uses artificial intelligence to analyze biological Raman spectra and identify the microbes at a single-cell level. The combination of a framework of convolutional neural network (ConvNet) and Raman spectroscopy allows the extraction of the Raman spectral features of a single microbial cell and then categorizes cells according to their spectral features. As the proof of concept, we measured Raman spectra of 14 microbial species at a single-cell level and constructed an optimal ConvNet model using the Raman data. The average accuracy of classification by ConvNet is 95.64 ± 5.46%. Meanwhile, we introduced an occlusion-based Raman spectra feature extraction to visualize the weights of Raman features for distinguishing different species.

Prostate and breast cancer cells death induced by xanthohumol investigated with Fourier transform infrared spectroscopy

Fourier Transform Infrared spectroscopy was applied to detect in vitro cell death induced in prostate (PC-3) and breast (T47D) cancer cell lines treated with xanthohumol (XN). After incubation of the cancer cells with XN, specific spectral shifts in the infrared spectra arising from selected cellular components were identified that reflected biochemical changes characteristic for apoptosis and necrosis. Detailed analysis of specific absorbance intensity ratios revealed the compositional changes in the secondary structure of proteins and membrane lipids. In this study, for the first time we examined the changes in these molecular components and linked them to deduce the involvement of molecular mechanisms in the XN-induced death of the selected cancer cells. We showed that XN concentration-dependent changes were attributed to phospholipid ester carbonyl groups, especially in the case of T47D cells, suggesting that XN acts as an inhibitor of cell proliferation. Additionally, we observed distinct changes in the region assigned to the absorption of DNA, which were correlated with a specific marker of cell death and dependent on the XN dose and the type of cancer cells. The microscopic observation and flow cytometry analysis revealed that the decrease in cancer cell viability was mainly related to the induction of necrotic cell death. Moreover, the T47D cells were slightly more sensitive to XN than the PC-3 cells. Considering the results obtained, it can be assumed that apoptosis and necrosis induced by XN may contribute to the anti-proliferative and cytotoxic properties of this flavonoid against cancer cell lines PC-3 and T47D.

Confocal Raman Spectral Imaging Study of DAPT, a γ-secretase Inhibitor, Induced Physiological and Biochemical Reponses in Osteosarcoma Cells

Confocal Raman microspectral imaging was adopted to elucidate the cellular drug responses of osteosarcoma cells (OC) to N-[N-(3, 5-difluorophenyl acetyl)-L-alanyl]-sphenylglycine butyl ester (DAPT), a γ-secretase inhibitor, by identifying the drug induced subcellular compositional and structural changes. Methods: Spectral information were acquired from cultured osteosarcoma cells treated with 0 (Untreated Group, UT), 10 (10 μM DAPT treated, 10T), 20 μM (20 μM DAPT treated, 20T) DAPT for 24 hours. A one-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple test were sequentially applied to address spectral features among three groups. Multivariate algorithms such as K-means clustering analysis (KCA) and Principal component analysis (PCA) were used to highlight the structural and compositional differences, while, univariate imaging was applied to illustrate the distribution pattern of certain cellular components after drug treatment. Results: Major biochemical changes in DAPT-induced apoptosis came from changes in the content and structure of proteins, lipids, and nucleic acids. By adopted multivariate algorithms, the drug induced cellular changes was identified by the morphology and spectral characteristics between untreated cells and treated cells, testified that DAPT mainly acted in the nuclear region. With the increase of the drug concentration, the content of main subcellular compositions, such nucleic acid, protein, and lipid decreased. In an addition, DAPT-induced nuclear fragmentation and apoptosis was depicted by the univariate Raman image of major cellular components (nucleic acids, proteins and lipids). Conclusions: The achieved Raman spectral and imaging results illustrated detailed DAPT-induced subcellular compositional and structural variations as a function of drug dose. Such observations can not only explain drug therapeutic mechanisms of OC DAPT treatment, and also provide new insights for accessing the medicine curative efficacy and predicting prognosis.

Determination of cadmium induced acute and chronic reproductive toxicity with Raman spectroscopy

Cadmium (Cd) is one of the toxic heavy metals which is confirmed to be related to male sterile. Here, confocal Raman spectroscopy was employed to detect biomolecular composition and changes in testis under acute and chronic Cd treatment. Specific Raman shifts associated with mitochondria, nucleic acids, proteins, lipids, and cholesterol were identified which were distinguishing among groups undergoing different Cd treatment times. Supporting evidences were provided by conventional experimental detections. The relevant biochemical parameters, pathological changes, and protein expression related to testosterone synthesis were all changed and consistent with Raman spectrum information. In conclusion, confocal Raman spectroscopy presents a reliable data and provides a novel method which is expected to be a promising strategy in reproduction toxicity research.

Single cell study of adipose tissue mediated lipid droplet formation and biochemical alterations in breast cancer cells

Obesity is a known risk factor for breast cancer and a negative prognostic factor for cancer recurrence and survival. Several studies demonstrated that aggressive breast tumor cells contain higher numbers of intracellular lipid droplets (LDs). Here we applied simultaneous visualization, identification and quantification of the lipid accumulation in lipid droplets (LDs) of aggressive, human triple-negative MDA-MB-231 breast cancer cells treated with adipose tissue-conditioned medium (ACM) derived from overweight and obese patients. In addition to Oil Red O and AdipoRed fluorescent staining, label-free confocal Raman microspectroscopy (CRM) has been applied. CRM enables imaging of cell compartments as well as quantification and monitoring of specific biomolecules and metabolic processes on a single cell level. Interestingly, breast cancer cells incubated with ACM showed a significantly higher number of intracellular LDs. Cultivation of breast tumor cells with ACM of obese patients induced the formation of LDs with a 20-fold higher lipid concentration than cultivation with basal medium. This is in line with the significantly higher levels of NEFAs (non-esterified fatty acids) detected in the ACM obtained from obese patient compared to ACM obtained from overweight patients or basal medium. Further, by principal component analysis, we identified a significant increase in unsaturation, esterification and lipid to protein ratio in LDs in breast cancer cells incubated with ACM. CRM analyses might function as a valuable diagnostic tool to identify metabolic alterations in biological samples which in turn could provide more detailed insights in the pathogenesis of breast cancer in association with obesity.

Size-dependent apoptotic activity of gold nanoparticles on osteosarcoma cells correlated with SERS signal

In the last decade, gold nanoparticles have emerged as promising agents for in vitro bio-sensing and in vivo cancer theranostics. However, different investigations have reported widely varying cytotoxicity and uptake efficiency of gold nanoparticles depending upon their size. Therefore, more extensive studies are needed to standardize these biological effects as a function of size on a particular cell line. In addition, to obtain robust confirmation on the correlation of a size to biological effect, thorough mechanistic study must also be performed. In this study, the size dependent biological activities of gold nanoparticles on osteosarcoma cells is investigated towards exploring their potential theranostic application in bone cancer, for which very scarce literature reports are available. Tris-assisted citrate based method was optimized to synthesize stable gold naoparticles of 40-60 nm sizes. Nanoparticles were characterized through UV-Vis spectroscopy, field emission scanning electron microscope (FESEM) and dynamic light scattering (DLS). Increasing concentrations of gold nanoparticles (AuNPs) of 46 nm size, enhanced the rate of reactive oxygen species (ROS)-induced apoptosis in MG63 cells by disrupting their mitochondrial membrane potential. Considerably higher cell death was observed for 46 and 60 nm AuNPs compared to 38 nm at all concentrations of 200, 400 and 800 ng/mL. Further, molecular signatures of cellular apoptosis under nanoparticle treatment were optically assessed through surface enhanced Raman scattering (SERS). A significant Raman enhancement in cancer cells under treatment of larger gold nanoparticles (46 and 60 nm) at fixed wavelength of 785 nm and laser power of 8.0 mW was evident. In corroboration with molecular biology techniques, SERS observation confirmed the size-dependent apoptotic phenomena in osteosarcoma cells under treatment of gold nanoparticles. Study demonstrates a facile, non-active targeting approach for detection of size-dependent AuNP-induced apoptosis in osteosarcoma cells through label-free SERS method.

Detection and Monitoring of Stem Cell Differentiation Using Nanotechnology

Stem cell differentiation and pluripotency are important stages in the regenerative medicine. The design and fabrication of user-friendly approach to save cost and time as well as monitor this process is crucial. Surface-enhanced Raman spectroscopy (SERS) is a sensitive technique to fabricate smart sensors for biological applications. In this technique, double enhancement effect on SERS signals is induced by utilizing graphene oxide (GO)-encapsulated gold nanoparticles (GNPs). The undifferentiated neural stem cells (NSCs) produced Raman peaks which were 3.5 times higher than those obtained from normal metal structures. The surface decorated using 3D GO-encapsulated GNPs was an effective, cost-saving, and nondestructive tool for distinguishing the differentiation state of NSCs. Moreover, the substrate composed of 3D GO-encapsulated gold nanoparticles was also effective for distinguishing the differentiation state of single NSC by using electrochemical and electrical techniques. Therefore, the recommended technique can be utilized as a powerful nondestructive in situ monitoring tool for the identification of the differentiation potential of various kinds of stem cells.

Ex vivo detection of cadmium-induced renal damage by using confocal Raman spectroscopy

Cadmium (Cd) is a toxic heavy metal which is harmful to environment and organisms. The reabsorption of Cd in kidney leads it to be the main damaged organ in animals under the Cd exposure. In this work, we applied confocal Raman spectroscopy to map the pathological changes in situ in normal and Cd-exposed mice kidney. The renal tissue from Cd-exposed group displayed a remarkable decreasing in the intensity of typical peaks related to mitochondria, DNA, proteins and lipids. On the contrary, the peaks of collagen in Cd-exposed group elevated significantly. The components in each tissue were identified and distinguished by principal component analysis. Furthermore, all the biological investigations in this study were consistent with the Raman spectrum detection, which revealed the progression and degree of lesion induced by Cd. The confocal Raman spectroscopy provides a new perspective for in situ monitoring of substances changes in tissues, which exhibits more comprehensive understanding of the pathogenic mechanisms of heavy metals in molecular toxicology.

Raman spectroscopy of blood plasma samples from breast cancer patients at different stages

Raman spectroscopy was employed for the characterization of blood plasma samples from patients at different stages of breast cancer. Blood plasma samples taken from clinically diagnosed breast cancer patients were compared with healthy controls using multivariate data analysis techniques (principal components analysis - PCA) to establish Raman spectral features which can be considered spectral markers of breast cancer development. All the stages of the disease can be differentiated from normal samples. It is also found that stage 2 and 3 are biochemically similar, but can be differentiated from each other by PCA. The Raman spectral data of the stage 4 is found to be biochemically distinct, but very variable between patients. Raman spectral features associated with DNA and proteins were identified, which are exclusive to patient plasma samples. Moreover, there are several other spectral features which are strikingly different in the blood plasma samples of different stages of breast cancer. In order to further explore the potential of Raman spectroscopy as the basis of a minimally invasive screening technique for breast cancer diagnosis and staging, PCA-Factorial Discriminant Analysis (FDA) was employed to classify the Raman spectral datasets of the blood plasma samples of the breast cancer patients, according to different stages of the disease, yielding promisingly high values of sensitivity and specificity for all stages.

Principal components analysis of Raman spectral data for screening of Hepatitis C infection

In the current study, Raman spectroscopy is employed for the identification of the biochemical changes taking place during the development of Hepatitis C. The Raman spectral data acquired from the human blood plasma samples of infected and healthy individuals is analysed by Principal Components Analysis and the Raman spectral markers of the Hepatitis C Virus (HCV) infection are identified. Spectral changes include those associated with nucleic acidsat720 cm^-1, 1077 cm^-1 1678 (CO stretching mode of dGTP of RNA), 1778 cm^-1 (RNA), with proteins at 1641 cm^-1(amide-I), 1721 cm^-1(CC stretching of proteins) and lipids at 1738 cm^-1(CO of ester group in lipids). These differences in Raman spectral features of blood plasma samples of the patients and healthy volunteers can be associated with the development of the biochemical changes during HCV infection.

The non-homogenous distribution and aggregation of carotenoids in the stratum corneum correlates with the organization of intercellular lipids in vivo

The human stratum corneum (SC) contains an abundant amount of carotenoid antioxidants, quenching free radicals and thereby protecting the skin. For the precise measurements of the depth-dependent carotenoid concentration, confocal Raman microscopy is a suitable method. The quantitative concentration can be determined by the carotenoid-related peak intensity of a Gaussian function approached at ≈1524 cm^-1 using non-linear regression. Results show that the carotenoid concentration is higher at the superficial layers of the SC then decreases to a minimum at 20% SC depth and increases again towards the bottom of the SC. In the present work, two carotenoid penetration pathways into the SC are postulated. The first pathway is from the stratum granulosum to the bottom of the SC, while in the second pathway, the carotenoids are delivered to the skin surface by sweat and/or sebum secretion and penetrate from outside. The carotenoids are aggregated at the superficial layers, which are shown by high correlation between the aggregation states of carotenoids and the lateral organization of lipids. At the 30%-40% SC depths, the ordered and dense lipid molecules intensify the lipid-carotenoid interactions and weaken the carotenoid-carotenoid interaction and thus exhibit the disaggregation of carotenoids. At 90%-100% SC depths, the carotenoid-lipid interaction is weakened and the carotenoids have a tendency to be aggregated. Thus, the molecular structural correlation of carotenoid and SC lipid might be reserved in the intercellular space of the SC and also serves as the skeleton of the intercellular lipids.

Off-Stoichiometric Reactions at the Cell-Substrate Biomolecular Interface of Biomaterials: In Situ and Ex Situ Monitoring of Cell Proliferation, Differentiation, and Bone Tissue Formation

The availability of osteoinductive biomaterials has encouraged new therapies in bone regeneration and has potentially triggered paradigmatic shifts in the development of new implants in orthopedics and dentistry. Among several available synthetic biomaterials, bioceramics have gained attention for their ability to induce mesenchymal cell differentiation and successive bone formation when implanted in the human body. However, there is currently a lack of understanding regarding the fundamental biochemical mechanisms by which these materials can induce bone formation. Phenomenological studies of retrievals have clarified the final effect of bone formation, but have left the chemical interactions at the cell-material interface uncharted. Accordingly, the knowledge of the intrinsic material properties relevant for osteoblastogenesis and osteoinduction remains incomplete. Here, we systematically monitored in vitro the chemistry of mesenchymal cell metabolism and the ionic exchanges during osteoblastogenesis on selected substrates through conventional biological assays as well as via in situ and ex situ spectroscopic techniques. Accordingly, the chemical behavior of different bioceramic substrates during their interactions with mesenchymal cells could be unfolded and compared with that of biomedical titanium alloy. Our goal was to clarify the cascade of chemical equations behind the biological processes that govern osteoblastogenic effects on different biomaterial substrates.

Silicon Nitride: A Bioceramic with a Gift

In the closing decades of the 20th century, silicon nitride (Si₃N₄) was extensively developed for high-temperature gas turbine applications. Technologists attempted to take advantage of its superior thermal and mechanical properties to improve engine reliability and fuel economy. Yet, this promise was never realized in spite of the worldwide research, which was conducted at that time. Notwithstanding this disappointment, its use in medical applications in the early 21st century has been an unexpected gift. While retaining all of its engineered mechanical properties, it is now recognized for its peculiar surface chemistry. When immersed in an aqueous environment, the slow elution of silicon and nitrogen from its surface enhances healing of soft and osseous tissue, inhibits bacterial proliferation, and eradicates viruses. These benefits permit it to be used in a wide array of different disciplines inside and outside of the human body including orthopedics, dentistry, virology, agronomy, and environmental remediation. Given the global public health threat posed by mutating viruses and bacteria, silicon nitride offers a valid and straightforward alternative approach to fighting these pathogens. However, there is a conundrum behind these recent discoveries: How can this unique bioceramic be both friendly to mammalian cells while concurrently lysing invasive pathogens? This unparalleled characteristic can be explained by the pH-dependent kinetics of two ammonia species-NH₄⁺ and NH₃-both of which are leached from the wet Si₃N₄ surface.

Detection of circulating tumor cells in blood by shell-isolated nanoparticle - enhanced Raman spectroscopy (SHINERS) in microfluidic device

Isolation and detection of circulating tumor cells (CTCs) from human blood plays an important role in non- invasive screening of cancer evolution and in predictive therapeutic treatment. Here, we present the novel tool utilizing: (i) the microfluidic device with (ii) incorporated photovoltaic (PV) based SERS-active platform, and (iii) shell-isolated nanoparticles (SHINs) for simultaneous separation and label-free analysis of circulating tumour cells CTCs in the blood specimens with high specificity and sensitivity. The proposed microfluidic chip enables the efficient size - based inertial separation of circulating cancer cells from the whole blood samples. The SERS-active platform incorporated into the microfluidic device permits the label-free detection and identification of isolated cells through the insight into their molecular and biochemical structure. Additionally, the silver nanoparticles coated with an ultrathin shell of silica (Ag@SiO2) was used to improve the detection accuracy and sensitivity of analysed tumor cells via taking advantages of shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS). The empirical analysis of SHINERS spectra revealed that there are some differences among studied (HeLa), renal cell carcinoma (Caki-1), and blood cells. Unique SHINERS features and differences in bands intensities between healthy and cancer cells might be associated with the variations in the quantity and quality of molecules such as lipid, protein, and DNA or their structure during the metastasis cancer formation. To demonstrate the statistical efficiency of the developed method and improve the differentiation for circulating tumors cells detection the principal component analysis (PCA) has been performed for all SHINERS data. PCA method has been applied to recognize the most significant differences in SHINERS data among the three analyzed cells: Caki-1, HeLa, and blood cells. The proposed approach challenges the current multi-steps CTCs detection methods in the terms of simplicity, sensitivity, invasiveness, destructivity, time and cost of analysis, and also prevents the defragmentation/damage of tumor cells and thus leads to improving the accuracy of analysis. The results of this research work show the potential of developed SERS based tool for the separation of tumor cells from whole blood samples in a simple and minimally invasive manner, their detection and molecular characterization using one single technology.

Non-invasive marker-independent high content analysis of a microphysiological human pancreas-on-a-chip model

The increasing prevalence of diabetes, its heterogeneity, and the limited number of treatment options drive the need for physiologically relevant assay platforms with human genetic background that have the potential to improve mechanistic understanding and e\xpedite diabetes-related research and treatment. In this study, we developed an endocrine pancreas-on-a-chip model based on a tailored microfluidic platform, which enables self-guided trapping of single human pseudo-islets. Continuous, low-shear perfusion provides a physiologically relevant microenvironment especially important for modeling and monitoring of the endocrine function as well as sufficient supply with nutrients and oxygen. Human pseudo-islets, generated from the conditionally immortalized EndoC-βH3 cell line, were successfully injected by hydrostatic pressure-driven flow without altered viability. To track insulin secretion kinetics in response to glucose stimulation in a time-resolved manner, dynamic sampling of the supernatant as well as non-invasive real-time monitoring using Raman microspectroscopy was established on-chip. Dynamic sampling indicated a biphasic glucose-stimulated insulin response. Raman microspectroscopy allowed to trace glucose responsiveness in situ and to visualize different molecular structures such as lipids, mitochondria and nuclei. In-depth spectral analyses demonstrated a glucose stimulation-dependent, increased mitochondrial activity, and a switch in lipid composition of insulin secreting vesicles, supporting the high performance of our pancreas-on-a-chip model.

Effect of a novel quaternary ammonium silane cavity disinfectant on cariogenic biofilm formation

OBJECTIVE

Evaluate effect of quaternary ammonium silane (QAS) cavity disinfectant on cariogenic biofilm.

MATERIALS AND METHODS

Single- (Streptococcus mutans or Lactobacillus acidophilus), dual- (Streptococcus mutans/Lactobacillus Acidophilus), and multi-species (Streptococcus mutans, Actinomyces naeslundii, and Streptococcus sanguis) biofilms were grown on acid-etched dentine discs. Biofilms were incubated (120 min/37 °C) and allowed to grow for 3 days anaerobically. Discs (no treatment) served as control (group 1). Groups II, III, IV, and V were then treated with 2% chlorhexidine, and 2%, 5%, and 10% QAS (20 s). Discs were returned to well plates with 300 μL of bacterial suspension and placed in anaerobic incubator at 37 °C and biofilms redeveloped for 4 days. Confocal microscopy, Raman, CFU, and MTT assay were performed.

RESULTS

Raman peaks show shifts at 1450 cm^-1, 1453 cm^-1, 1457 cm^-1, 1460 cm^-1, and 1462 cm^-1 for control, 2% CHX, 2%, 5%, and 10% QAS groups in multi-species biofilms. There was reduction of 484 cm^-1 band in 10% QAS group. CLSM revealed densely clustered green colonies in control group and red confluent QAS-treated biofilms with significantly lower log CFU for single/dual species. Metabolic activities of Streptococcus mutans and Lactobacillus acidophilus decreased with increasing QAS exposure time.

CONCLUSION

Quaternary ammonium silanes possess antimicrobial activities and inhibit growth of cariogenic biofilms.

CLINICAL SIGNIFICANCE

Available data demonstrated use of QAS as potential antibacterial cavity disinfectant in adhesive dentistry. Experimental QAS can effectively eliminate caries-forming bacteria, when used inside a prepared cavity, and can definitely overcome problems associated with present available cavity disinfectants.

Non-invasive detection of DNA methylation states in carcinoma and pluripotent stem cells using Raman microspectroscopy and imaging

DNA methylation plays a critical role in the regulation of gene expression. Global DNA methylation changes occur in carcinogenesis as well as early embryonic development. However, the current methods for studying global DNA methylation levels are invasive and require sample preparation. The present study was designed to investigate the potential of Raman microspectroscopy and Raman imaging as non-invasive, marker-independent and non-destructive tools for the detection of DNA methylation in living cells. To investigate global DNA methylation changes, human colon carcinoma HCT116 cells, which were hypomorphic for DNA methyltransferase 1, therefore showing a lower global DNA methylation (DNMT1^−/− cells), were compared to HCT116 wildtype cells. As a model system for early embryogenesis, murine embryonic stem cells were adapted to serum-free 2i medium, leading to a significant decrease in DNA methylation. Subsequently, 2i medium -adapted cells were compared to cells cultured in serum-containing medium. Raman microspectroscopy and imaging revealed significant differences between high- and low-methylated cell types. Higher methylated cells demonstrated higher relative intensities of Raman peaks, which can be assigned to the nucleobases and 5-methylcytosine. Principal component analysis detected distinguishable populations of high- and low-methylated samples. Based on the provided data we conclude that Raman microspectroscopy and imaging are suitable tools for the real-time, marker-independent and artefact-free investigation of the DNA methylation states in living cells.

The label-free detection and distinction of CYP2C9-expressing and non-expressing cells by surface-enhanced Raman scattering substrates based on bimetallic AuNPs-AgNWs

Cytochrome P450 2C9 (CYP2C9) is capable of catalyzing the biotransformation of endogenous compounds in cells, indicating that this enzyme could change the intracellular environment and is related to the pathogenesis of diseases. Currently, it is still a challenge to study the differences in cellular components between CYP2C9-expressing and non-expressing cells. In this study, employing a Au nanoparticles-Ag nanowires (AuNPs-AgNWs) decorated silicon wafer as a novel non-destructive and label-free tool, we applied surface-enhanced Raman scattering (SERS) spectroscopy to detect and distinguish the cellular composition of CYP2C9-expressing cells (293T-Mig-2C9) and non-expressing cells (293T-Mig-R1). AgNWs with high surface roughness were formed by modification of AuNPs onto their surface by electrostatic interactions, which enabled them to exhibit greatly enhanced SERS ability. Then, they were employed to fabricate SERS substrates via an electrostatically assisted 3-aminopropyltriethoxysilane (APTES)-functionalized surface-assembly method. The SERS substrates exhibited high sensitivity with a detection limit of 1 × 10-9 M for 4-mercaptobenzoic acid (4-MBA). Meanwhile, the SERS substrates exhibited good uniformity and reproducibility. The cytotoxicity assay demonstrated that the SERS substrates displayed good biocompatibility with 293T cells. Before SERS measurements, CYP2C9 constantly expressed cells (293T-Mig-2C9 cells) and control cells (293T-Mig-R1 cells) were constructed. The expression of CYP2C9 and the catalytic activity in the cells were checked. Using the AuNPs-AgNWs substrates as a high-performance in vitro sensing platform allowed us to obtain fingerprint spectra of 293T-Mig-R1 and 293T-Mig-2C9 cells. The difference spectra between the two cell lines were studied to interpret the spectral differences and gain insight into the biochemical variations. Finally, principal component analysis (PCA) score plots of the SERS spectra were also used to better view the differences between the two cell lines. SERS detection based on the AuNPs-AgNWs substrates provides a sensitive, non-destructive and label-free method for differentiation between 293T-Mig-R1 and 293T-Mig-2C9 cells.

Non-invasive functional molecular phenotyping of human smooth muscle cells utilized in cardiovascular tissue engineering

Smooth muscle cell (SMC) diversity and plasticity are limiting factors in their characterization and application in cardiovascular tissue engineering. This work aimed to evaluate the potential of Raman microspectroscopy and Raman imaging to distinguish SMCs of different tissue origins and phenotypes. Cultured human SMCs isolated from different vascular and non-vascular tissues as well as fixed human SMC-containing tissues were analyzed. In addition, Raman spectra and images of tissue-engineered SMC constructs were acquired. Routine techniques such as qPCR, histochemistry, histological and immunocytological staining were performed for comparative gene and protein expression analysis. We identified that SMCs of different tissue origins exhibited unique spectral information that allowed a separation of all groups of origin by multivariate data analysis (MVA). We were further able to non-invasively monitor phenotypic switching in cultured SMCs and assess the impact of different culture conditions on extracellular matrix remodeling in the tissue-engineered ring constructs. Interestingly, we identified that the Raman signature of the human SMC-based ring constructs was similar to the one obtained from native aortic tissue. We conclude that Raman microspectroscopic methods are promising tools to characterize cells and define cellular and extracellular matrix components on a molecular level. In this study, in situ measurements were marker-independent, fast, and identified cellular differences that were not detectable by established routine techniques. Perspectively, Raman microspectroscopy and MVA in combination with artificial intelligence can be suitable for automated quality monitoring of (stem) cell and cell-based tissue engineering products. STATEMENT OF SIGNIFICANCE: The accessibility of autologous blood vessels for surgery is limited. Tissue engineering (TE) aims to develop functional vascular replacements; however, no commercially available TE vascular graft (TEVG) exists to date. One limiting factor is the availability of a well-characterized and safe cell source. Smooth muscle cells (SMCs) are generally used for TEVGs. To engineer a TEVG, proliferating SMCs of the synthesizing phenotype are essential, whereas functional, sustainable TEVGs require SMCs of the contractile phenotype. SMC diversity and plasticity are therefore limiting factors, also for their quality monitoring and application in TE. In this study, Raman microspectroscopy and imaging combined with machine learning tools allowed the non-destructive, marker-independent characterization of SMCs, smooth muscle tissues and TE SMC-constructs. The spectral information was specific enough to distinguish for the first time the phenotypic switching in SMCs in real-time, and monitor the impact of culture conditions on ECM remodeling in the TE SMC-constructs.

Vibrational characterization of granulosa cells from patients affected by unilateral ovarian endometriosis: New insights from infrared and Raman microspectroscopy

Endometriosis is a chronic gynaecological disease characterised by the presence of endometrial cells in extra-uterine regions. One of the main factors impacting on the fertility of women affected by endometriosis is the poor oocyte quality. Granulosa Cells (GCs) regulate oocyte development and maintain the appropriate microenvironment for the acquisition of its competence; hence, the dysregulation of these functions in GCs can lead to severe cellular damages also in oocytes. In this study, luteinized GCs samples were separately collected from both ovaries of women affected by Unilateral Ovarian Endometriosis and analysed by infrared and Raman microspectroscopy. The spectral data were compared with those of GCs from women with diagnosis of tubal, idiopathic or male infertility (taken as control group). The coupling of these two spectroscopic techniques sheds new light on the alteration induced by this pathology on GCs metabolism and biochemical composition. In fact, the study revealed similar biochemical modifications in GCs from both ovaries of women affected by unilateral ovarian endometriosis, such as the alteration of the protein pattern, the induction of oxidative stress mechanisms, and the deregulation of lipid and carbohydrate metabolisms. These evidences suggest that unilateral endometriosis impairs the overall ovarian functions, causing alterations not only in the ovary with endometriotic lesions but also in the contralateral "healthy" one.

Detection of Circulating Tumor Cells Using Membrane-Based SERS Platform: A New Diagnostic Approach for 'Liquid Biopsy'

The detection and monitoring of circulating tumor cells (CTCs) in blood is an important strategy for early cancer evidence, analysis, monitoring of therapeutic response, and optimization of cancer therapy treatments. In this work, tailor-made membranes (MBSP) for surface-enhanced Raman spectroscopy (SERS)-based analysis, which permitted the separation and enrichment of CTCs from blood samples, were developed. A thin layer of SERS-active metals deposited on polymer mat enhanced the Raman signals of CTCs and provided further insight into CTCs molecular and biochemical composition. The SERS spectra of all studied cells—prostate cancer (PC3), cervical carcinoma (HeLa), and leucocytes as an example of healthy (normal) cell—revealed significant differences in both the band positions and/or their relative intensities. The multivariate statistical technique based on principal component analysis (PCA) was applied to identify the most significant differences (marker bands) in SERS data among the analyzed cells and to perform quantitative analysis of SERS data. Based on a developed PCA algorithm, the studied cell types were classified with an accuracy of 95% in 2D PCA to 98% in 3D PCA. These results clearly indicate the diagnostic efficiency for the discrimination between cancer and normal cells. In our approach, we exploited the one-step technology that exceeds most of the multi-stage CTCs analysis methods used and enables simultaneous filtration, enrichment, and identification of the tumor cells from blood specimens.

A Label-Free Platform for Identification of Exosomes from Different Sources

Exosomes contain cell- and cell-state-specific cargos of proteins, lipids, and nucleic acids and play significant roles in cell signaling and cell-cell communication. Current research into exosome-based biomarkers has relied largely on analyzing candidate biomarkers, i.e., specific proteins or nucleic acids. However, this approach may miss important biomarkers that are yet to be identified. Alternative approaches are to analyze the entire exosome system, either by "omics" methods or by techniques that provide "fingerprints" of the system without identifying each individual biomolecule component. Here, we describe a platform of the latter type, which is based on surface-enhanced Raman spectroscopy (SERS) in combination with multivariate analysis, and demonstrate the utility of this platform for analyzing exosomes derived from different biological sources. First, we examined whether this analysis could use exosomes isolated from fetal bovine serum using a simple, commercially available isolation kit or necessitates the higher purity achieved by the "gold standard" ultracentrifugation/filtration procedure. Our data demonstrate that the latter method is required for this type of analysis. Having established this requirement, we rigorously analyzed the Raman spectral signature of individual exosomes using a unique, hybrid SERS substrate made of a graphene-covered Au surface containing a quasi-periodic array of pyramids. To examine the source of the Raman signal, we used Raman mapping of low and high spatial resolution combined with morphological identification of exosomes by scanning electron microscopy. Both approaches suggested that the spectra were collected from single exosomes. Finally, we demonstrate for the first time that our platform can distinguish among exosomes from different biological sources based on their Raman signature, a promising approach for developing exosome-based fingerprinting. Our study serves as a solid technological foundation for future exploration of the roles of exosomes in various biological processes and their use as biomarkers for disease diagnosis and treatment monitoring.

Phosphoric acid and phosphorylation levels are potential biomarkers indicating developmental competence of matured oocytes

We identified biomarkers for mice oocyte maturation in metaphase II in vivo and in situ using Raman spectroscopy.

Photovoltaic cells as a highly efficient system for biomedical and electrochemical surface-enhanced Raman spectroscopy analysis

Surface-enhanced Raman scattering (SERS) has been intensively used recently as a highly sensitive, non-destructive, chemical specific, and label-free technique for a variety of studies. Here, we present a novel SERS substrate for: (i) the standard ultra-trace analysis, (ii) detection of whole microorganisms, and (iii) spectroelectrochemical measurements. The integration of electrochemistry and SERS spectroscopy is a powerful approach for in situ investigation of the structural changes of adsorbed molecules, their redox properties, and for studying the intermediates of the reactions. We have developed a conductive SERS platform based on photovoltaic materials (PV) covered with a thin layer of silver, especially useful in electrochemical SERS analysis. These substrates named Ag/PV presented in this study combine crucial spectroscopic features such as high sensitivity, reproducibility, specificity, and chemical/physical stability. The designed substrates permit the label-free identification and differentiation of cancer cells (renal carcinoma) and pathogens (Escherichia coli and Bacillus subtilis). In addition, the developed SERS platform was adopted as the working electrode in an electrochemical SERS approach for p-aminothiophenol (p-ATP) studies. The capability to monitor in real-time the electrochemical changes spectro-electro-chemically has great potential for broadening the application of SERS.

We have developed a conductive SERS platform based on photovoltaic materials (PV) covered with a thin layer of silver, especially useful in electrochemical SERS analysis.

Raman Imaging of Individual Membrane Lipids and Deoxynucleoside Triphosphates in Living Neuronal Cells during Neurite Outgrowth

Recent developments in Raman imaging at the microscopic scale were exploited here with the specific purpose of locating spectral fingerprints of individual membrane lipids and deoxynucleoside triphosphates during neuronal cell networking and separation. After carefully screening the Raman spectra of isolated lipid components, we located an in situ mapped specific Raman fingerprints from individual phospholipids at the micrometric level in comparison with the total lipid distribution within single living cells. We concurrently examined silent zones of lipid emissions and exploited those peculiar spectral ranges for mapping both abundance and localization of individual DNA nucleoside triphosphates. This work represents a first step toward label-free/molecular-selective Raman patterning with high spectral resolution of the relevant chemical species involved with the functionality of neuronal cells.

Enhanced Raman Investigation of Cell Membrane and Intracellular Compounds by 3D Plasmonic Nanoelectrode Arrays

3D nanostructures are widely exploited in cell cultures for many purposes such as controlled drug delivery, transfection, intracellular sampling, and electrical recording. However, little is known about the interaction of the cells with these substrates, and even less about the effects of electroporation on the cellular membrane and the nuclear envelope. This work exploits 3D plasmonic nanoelectrodes to study, by surface-enhanced Raman scattering (SERS), the cell membrane dynamics on the nanostructured substrate before, during, and after electroporation. In vitro cultured cells tightly adhere on 3D plasmonic nanoelectrodes precisely in the plasmonic hot spots, making this kind of investigation possible. After electroporation, the cell membrane dynamics are studied by recording the Raman time traces of biomolecules in contact or next to the 3D plasmonic nanoelectrode. During this process, the 3D plasmonic nanoelectrodes are intracellularly coupled, thus enabling the monitoring of different molecular species, including lipids, proteins, and nucleic acids. Scanning electron microscopy cross-section analysis evidences the possibility of nuclear membrane poration compatible with the reported Raman spectra. These findings may open a new route toward controlled intracellular sampling and intranuclear delivery of genic materials. They also show the possibility of nuclear envelope disruption which may lead to negative side effects.

Label-Free Detection of Human Serum Using Surface-Enhanced Raman Spectroscopy Based on Highly Branched Gold Nanoparticle Substrates for Discrimination of Non-Small Cell Lung Cancer

Surface-enhanced Raman spectroscopy (SERS) is a good candidate for the development of fast and easy-to-use diagnostic tools, possibly used on serum in screening tests. In this study, a potential label-free serum test based on SERS spectroscopy was developed to analyze human serum for the diagnosis of the non-small cell lung cancer (NSCLC). We firstly synthesized novel highly branched gold nanoparticles (HGNPs) at high yield through a one-step reduction of HAuCl4 with dopamine hydrochloride at 60°C. Then, HGNP substrates with good reproducibility, uniformity, and high SERS effect were fabricated by the electrostatically assisted (3-aminopropyl) triethoxysilane-(APTES-) functionalized silicon wafer surface-sedimentary self-assembly method. Using as-prepared HGNP substrates as a high-performance sensing platform, SERS spectral data of serum obtained from healthy subjects, lung adenocarcinoma patients, lung squamous carcinoma patients, and large cell lung cancer patients were collected. The difference spectra among different types of NSCLC were compared, and analysis result revealed their intrinsic difference in types and contents of nucleic acids, proteins, carbohydrates, amino acids, and lipids. SERS spectra were analyzed by principal component analysis (PCA), which was able to distinguish different types of NSCLC. Considering its time efficiency, being label-free, and sensitivity, SERS based on HGNP substrates is very promising for mass screening NSCLC and plays an important role in the detection and prevention of other diseases.

Anti-cancer effect of bee venom on human MDA-MB-231 breast cancer cells using Raman spectroscopy

We demonstrated the apoptotic effect of bee venom (BV) on human MDA-MB-231 breast cancer cells using Raman spectroscopy and principal component analysis (PCA). Biochemical changes in cancer cells were monitored following BV treatment; the results for different concentrations and treatment durations differed markedly. Significantly decreased Raman vibrations for DNA and proteins were observed for cells treated with 3.0 µg/mL BV for 48 h compared with those of control cells. These results suggest denaturation and degradation of proteins and DNA fragmentation (all cell death-related processes). The Raman spectroscopy results agreed with those of atomic force microscopy and conventional biological tests such as viability, TUNEL, and western blot assays. Therefore, Raman spectroscopy, with PCA, provides a noninvasive, label-free tool for assessment of cellular changes on the anti-cancer effect of BV.

Biochemical changes in injured sciatic nerve of rats after low-level laser therapy (660 nm and 808 nm) evaluated by Raman spectroscopy

The aim of this study was to identify biochemical changes in sciatic nerve (SN) after crush injury and low-level laser therapy (LLLT) with 660 nm and 808 nm by Raman spectroscopy (RS) analysis. A number of 32 Wistar rats were used, divided into four groups (control 1, control 2, LASER 660 nm, and LASER 808 nm). All animals underwent surgical procedure of the SN and groups control 2, LASER 660 nm, and LASER 808 nm were submitted to SN crush damage (axonotmesis). The LLLT in the groups LASER 660 nm and LASER 808 nm was applied daily for 21 consecutive days (100 mW, 30 s, 133 J/cm² fluence). The hind paw was removed and the SN was dissected and positioned on an aluminum support to collect dispersive Raman spectra (830 nm excitation, 30 s accumulation). To estimate the biochemical changes in the SN associated with LLLT, the principal component analysis (PCA) was applied. The Raman spectra of the sciatic nerve fragments showed peaks of the major biochemical components of the nerve, especially sphingolipids, phospholipids, glycoproteins, and collagen. The spectral features identified in some of the principal component loading vectors are referred to the biochemical elements present on the SN and were increased in the groups treated with LLLT, mainly lipids (sphingo and phospholipids) and proteins (collagen)-constituents of the myelin sheath. The RS was effective in identifying the biochemical differences in the SN after the crush injury, and LASER 660 nm was more efficient than the LASER 808 nm in cell proliferation and repair of the injured SN.

Raman spectroscopy for accurately characterizing biomolecular changes in androgen-independent prostate cancer cells

Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer-related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone-resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid-specific signals were identified, especially loss of arginine band. Androgen-resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L-arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).

Keratin-water-NMF interaction as a three layer model in the human stratum corneum using in vivo confocal Raman microscopy

The secondary and tertiary structure of keratin and natural moisturizing factor (NMF) are of great importance regarding the water regulating functions in the stratum corneum (SC). In this in vivo study, the depth-dependent keratin conformation and its relationship to the hydrogen bonding states of water and its content in the SC, are investigated using confocal Raman microscopy. Based on the obtained depth-profiles for the β-sheet/α-helix ratio, the stability of disulphide bonds, the amount of cysteine forming disulphide bonds, the buried/exposed tyrosine and the folding/unfolding states of keratin, a "three layer model" of the SC, regarding the keratin-water-NMF interaction is proposed. At the uppermost layers (30-0% SC depth), the keratin filaments are highly folded, entailing limited water binding sites, and NMF is mostly responsible for binding water. At the intermediate layers (70-30% SC depth), the keratin filaments are unfolded, have the most water binding sites and are prone to swelling. At the bottom layers (100-80% SC depth), the water binding sites are already occupied with water and cannot swell substantially. The hydrogen bonding states of water molecules can only be explained by considering both, the molecular structure of keratin and the contribution of NMF as a holistic system.

SERS Investigation of Cancer Cells Treated with PDT: Quantification of Cell Survival and Follow-up

In this study Surface Enhanced Raman Spectroscopy (SERS) data recorded from mouse mammary glands cancer cells (4T1 cell line) was used to assess information regarding differences between control, death and viable cells after Photodynamic Therapy (PDT) treatment. The treatment used nanoemulsions (NE/PS) loaded with different chloroaluminumphthalocyanine (ClAlP) photosensitizer (PS) contents (5 and 10 µmol × L⁻¹) and illumination (660 nm wavelength) at 10 J × cm⁻² (10 minutes). The SERS data revealed significant molecular alterations in proteins and lipids due to the PDT treatment. Principal Component Analysis (PCA) was applied to analyze the data recorded. Three-dimensional and well reproductive PCA scatter plots were obtained, revealing that two clusters of dead cells were well separated from one another and from control cluster. Overlap between two clusters of viable cells was observed, though well separated from control cluster. Moreover, the data analysis also pointed out necrosis as the main cell death mechanism induced by the PDT, in agreement with the literature. Finally, Raman modes peaking at 608 cm⁻¹ (proteins) and 1231 cm⁻¹ (lipids) can be selected for follow up of survival rate of neoplastic cells after PDT. We envisage that this finding is key to contribute to a quick development of quantitative infrared thermography imaging.

Exploring cellular uptake of iron oxide nanoparticles associated with rhodium citrate in breast cancer cells

Nanocarriers have the potential to improve the therapeutic index of currently available drugs by improving their efficacy and achieving therapeutic steady-state levels over an extended period. The association of maghemite-rhodium citrate (MRC) nanoparticles (NPs) has the potential to increase specificity of the cytotoxic action. However, the interaction of these NPs with cells, their uptake mechanism, and subcellular localization need to be elucidated. This work evaluates the uptake mechanism of MRC NPs in metastatic and nonmetastatic breast cancer-cell models, comparing them to a nontumor cell line. MRC NPs uptake in breast cancer cells was more effective than in normal cells, with regard to both the amount of internalized material and the achievement of more strategic intracellular distribution. Moreover, this process occurred through a clathrin-dependent endocytosis pathway with different basal expression levels of this protein in the cell lines tested.

In vivo analysis of mucosal lipids reveals histological disease activity in ulcerative colitis using endoscope-coupled Raman spectroscopy

The goal of this study is to evaluate endoscopic Raman spectroscopy as a noninvasive technique to determine histological inflammatory status of colitis. Colon mucosal composition was investigated in vivo from patients with ulcerative colitis (UC) and from age- and body mass index (BMI) matched controls using endoscope-coupled Raman spectroscopy. The results were co-registered with histological assessment of inflammatory status at the same locations. Substantial decreases (50-60%) in the content of phosphotidylcholines (PCs) and total lipids were observed in inflamed colon tissue (histology grade 1, 2 and 3) compared to those from the quiescent (histology grade 0) and from the controls. No significant difference was observed in lipids or PC contents between control and grade 0, or among grades 1 - 3. The degree of lipid unsaturation increased in the inflamed tissue regardless of disease severity. The inflammation-associated alterations in lipids and PC are observed independent of BMI or the anatomical locations for data collection. Multivariate analysis using support vector machine (SVM) algorithm classified the spectra of the controls or the inactive colitis from those of inflamed tissue with a sensitivity of 83.5% and 97.1% respectively. Our results showed that mucosal lipid content is related to the microscopic disease activity, and thus could serve as a valuable spectral marker to differentiate active colitis from the quiescent.

Steps toward Maturation of Embryonic Stem Cell-Derived Cardiomyocytes by Defined Physical Signals

Cardiovascular disease remains a leading cause of mortality and morbidity worldwide. Embryonic stem cell-derived cardiomyocytes (ESC-CMs) may offer significant advances in creating in vitro cardiac tissues for disease modeling, drug testing, and elucidating developmental processes; however, the induction of ESCs to a more adult-like CM phenotype remains challenging. In this study, we developed a bioreactor system to employ pulsatile flow (1.48 mL/min), cyclic strain (5%), and extended culture time to improve the maturation of murine and human ESC-CMs. Dynamically-cultured ESC-CMs showed an increased expression of cardiac-associated proteins and genes, cardiac ion channel genes, as well as increased SERCA activity and a Raman fingerprint with the presence of maturation-associated peaks similar to primary CMs. We present a bioreactor platform that can serve as a foundation for the development of human-based cardiac in vitro models to verify drug candidates, and facilitates the study of cardiovascular development and disease.

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Custom-made bioreactor exposes ESC-CMs to defined shear stress and cyclic stretch

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Physical signals and extended culture significantly improve maturation of ESC-CMs

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Biochemical fingerprint of dynamically cultured ESC-CMs is similar to primary CMs