Manciu, Felicia S

In this study, we demonstrate that Raman microscopy combined with computational analysis is a useful approach to discriminating accurately between brain tumor bio-specimens and to identifying structural changes in glioblastoma (GBM) bio-signatures after nordihydroguaiaretic acid (NDGA) administration. NDGA phenolic lignan was selected as a potential therapeutic agent because of its reported beneficial effects in alleviating and inhibiting the formation of multi-organ malignant tumors. The current analysis of NDGA’s impact on GBM human cells demonstrates a reduction in the quantity of altered protein content and of reactive oxygen species (ROS)-damaged phenylalanine; results that correlate with the ROS scavenger and anti-oxidant properties of NDGA. A novel outcome presented here is the use of phenylalanine as a biomarker for differentiating between samples and assessing drug efficacy. Treatment with a low NDGA dose shows a decline in abnormal lipid-protein metabolism, which is inferred by the formation of lipid droplets and a decrease in altered protein content. A very high dose results in cell structural and membrane damage that favors transformed protein overexpression. The information gained through this work is of substantial value for understanding NDGA’s beneficial as well as detrimental bio-effects as a potential therapeutic drug for brain cancer.

Accurate clinical evaluation of renal osteodystrophy (ROD) is currently accomplished using invasive in vivo transiliac bone biopsy, followed by in vitro histomorphometry. In this study, we demonstrate that an alternative method for ROD assessment is through a fast, label-free Raman recording of multiple biomarkers combined with computational analysis for predicting the minimally required number of spectra for sample classification at defined accuracies. Four clinically relevant biomarkers: the mineral-to-matrix ratio, the carbonate-to-matrix ratio, phenylalanine, and calcium contents were experimentally determined and simultaneously considered as input to a linear discriminant analysis (LDA). Additionally, sample evaluation was performed with a linear support vector machine (LSVM) algorithm, with a 300 variable input. The computed probabilities based on a single spectrum were only marginally different (~80% from LDA and ~87% from LSVM), both providing an unacceptable classification power for a correct sample assignment. However, the Type I and Type II assignment errors confirm that a relatively small number of independent spectra (7 spectra for Type I and 5 spectra for Type II) is necessary for a p < 0.05 error probability. This low number of spectra supports the practicality of future in vivo Raman translation for a fast and accurate ROD detection in clinical settings.

The comprehensive microscopic, spectroscopic, and in vitro voltammetric analysis presented in this work, which builds on the well-studied properties of carbon-based materials, facilitates potential ways for improvement of carbon fiber microelectrodes (CFMs) for neuroscience applications. Investigations by both, scanning electron microscopy (SEM) and confocal Raman spectroscopy, confirm a higher degree of structural ordering for the fibers exposed to carbonization temperatures. An evident correlation is also identified between the extent of structural defects observed from SEM and Raman results with the CFM electrochemical performance for dopamine detection. To improve CFM physico-chemical surface stability and increase its mechanical resistance to the induced compressive stress during anticipated in vivo tissue penetration, successful coating of the carbon fiber with boron-doped diamond (BDD) is also performed and microspectroscopically analyzed here. The absence of spectral shifts of the diamond Raman vibrational signature verifies that the growth of an unstrained BDD thin film was achieved. Although more work needs to be done to identify optimal parameter values for improved BDD deposition, this study serves as a demonstration of foundational technology for the development of more sensitive electrochemical sensors, that may have been impractical previously for clinical applications, due to limitations in either safety or performance.

With the goal of accurately detecting and quantifying the amounts of dopamine (DA) and serotonin (5-HT) in mixtures of these neurotransmitters without using any labelling, we present a detailed, comparative computational and Raman experimental study. Although discrimination between these two analytes is achievable in such mixtures for concentrations in the millimolar range, their accurate quantification remains unattainable. As shown for the first time in this work, the formation of a new composite resulting from their interactions with each other is the main reason for this lack of quantification. While this new hydrogen-bonded complex further complicates potential analyte discrimination and quantification at concentrations characteristic of physiological levels (i.e., nanomolar concentrations), it can also open new avenues for its use in drug delivery and pharmaceutical research. This remark is based not only on chemical interactions analyzed here from both theoretical and experimental approaches, but also on biological relationship, with consideration of both functional and neural proximity perspectives. Thus, this research constitutes an important contribution toward better understanding of neural processes, as well as toward possible future development of label-free biosensors.

To better understand detection and monitoring of the important neurotransmitter adenosine at physiological levels, this study combines quantum chemical density functional modeling and ultrasensitive surface-enhanced Raman spectroscopic (SERS) measurements. Combined simulation results and experimental data for an analyte concentration of about 10−11 molar indicate the presence of all known molecular forms resulting from adenosine’s complex redox-reaction. Detailed analysis presented here, besides assessing potential Raman signatures of these adenosinic forms, also sheds light on the analytic redox process and voltammetric detection. Examples of adenosine Raman fingerprints for different molecular orientations with respect to the SERS substrate are the vibrational line around 920 ± 10 cm−1 for analyte physisorption through the carbinol moiety and around 1600 ± 20 cm−1 for its fully oxidized form. However, both hydroxyl/oxygen sites and NH2/nitrogen sites contribute to molecule’s interaction with the SERS environment. Our results also reveal that contributions of partially oxidized adenosine forms and of the standard form are more likely to be detected with the first recorded voltammetric oxidation peak. The fully oxidized adenosine form contributes mostly to the second peak. Thus, this comparative theoretical–experimental investigation of adenosine’s vibrational signatures provides significant insights for advancing its detection, and for future development of opto-voltammetric biosensors.

Defining the pathogenesis of renal osteodystrophy (ROD) and its treatment efficacy are difficult, since many factors potentially affect bone quality. In this study, confocal Raman microscopy and parallel statistical analysis were used to identify differences in bone composition between healthy and ROD bone tissues through direct visualization of three main compositional parametric ratios, namely, calcium content, mineral-to-matrix, and carbonate-to-matrix. Besides the substantially lower values found in ROD specimens for these representative ratios, an obvious accumulation of phenylalanine is Raman spectroscopically observed for the first time in ROD samples and reported here. Thus, elevated phenylalanine could also be considered as an indicator of the disease. Since the image results are based on tens of thousands of spectra per sample, not only are the average ratios statistically significantly different for normal and ROD bone, but the method is clearly powerful in distinguishing between the two types of samples. Furthermore, the statistical outcomes demonstrate that only a relatively small number of spectra need to be recorded in order to classify the samples. This work thus opens the possibility of future development of in vivo Raman sensors for assessment of bone structure, remodeling, and mineralization, where different biomarkers are simultaneously detected with unprecedented accuracy.

A combined theoretical and experimental analysis of dopamine (DA) is presented in this work with the objective of achieving more accurate detection and monitoring of this neurotransmitter at very low concentrations, specific to physiological levels. Surface-enhanced Raman spectroscopy on silver nanoparticles was employed for recording DA concentrations as low as 10−11 molar. Quantum chemical density functional calculations were carried out using Gaussian-09 analytical suite software. Relatively good agreement between the simulated and experimentally determined results indicates the presence of different DA molecular forms, such as uncharged DA±, anionic DA−, and dopaminequinone. Disappearance of the strongest bands of dopamine around 750 cm−1 and 790 cm−1, which suggests its adsorption onto the metallic surface, is not only consistent with all of these DA configurations, but also provides additional information about the analyte’s redox process and voltammetric detection. On the other hand, occurrence of the abovementioned Raman lines could indicate the formation of multilayers of DA or its presence in a cationic DA+ form. Thus, through coordinated experiment and theory, valuable insights into changes observed in the vibrational signatures of this important neurotransmitter can be achieved for a better understanding of its detection at physiological levels, which is crucial if further optovoltammetric medical device development is envisioned.

Combined theoretical and experimental analysis of serotonin by quantum chemical density functional calculations and surface-enhanced Raman spectroscopy, respectively, is presented in this work to better understand phenomena related to this neurotransmitter’s detection and monitoring at very low concentrations specific to physiological levels. In addition to the successful ultrasensitive analyte detection on silver nanoparticles for concentrations as low as 10−11 molar, the relatively good agreement between the simulated and experimentally determined results indicates the presence of all serotonin molecular forms, such as neutral, ionic, and those oxidized through redox reactions. Obvious structural molecular deformations such as bending of lateral amino chains are observed for both ionic and oxidized forms. Not only does this combined approach reveal more probable adsorption of serotonin into the silver surface through hydroxyl/oxygen sites than through NH/nitrogen sites, but also that it does so predominantly in its neutral (reduced) form, somewhat less so in its ionic forms, and much less in its oxidized forms. If the development of opto-voltammetric biosensors and their effective implementation is envisioned for the future, this study provides some needed scientific background for comprehending changes in the vibrational signatures of this important neurotransmitter.

In this study, we present a comprehensive investigation of graphene’s optical and conductive properties using confocal Raman and a Drude model. A comparative analysis between experimental findings and theoretical predictions of the material’s changes and improvements as it transitioned from three-dimensional graphite is also presented and discussed. Besides spectral recording by Raman, which reveals whether there is a single, a few, or multi-layers of graphene, the confocal Raman mapping allows for distinction of such domains and a direct visualization of material inhomogeneity. Drude model employment in the analysis of the far-infrared transmittance measurements demonstrates a distinct increase of the material’s conductivity with dimensionality reduction. Other particularly important material characteristics, including carrier concentration and time constant, were also determined using this model and presented here. Furthermore, the detection of micromolar concentration of dopamine on graphene surfaces not only proves that the Raman technique facilitates ultrasensitive chemical detection of analytes, besides offering high information content about the biomaterial under study, but also that carbon-based materials are biocompatible and favorable micro-environments for such detection. Such information is valuable for the development of bio-medical sensors, which is the main application envisioned for this analysis.

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.