Fourier Transform Infrared Spectroscopy Reveals Molecular Changes in Blood Vessels of Rats Treated with Pentadecapeptide BPC 157.

Recently, it was found that when confronted with major vessel occlusion and vascular failure, stable gastric pentadecapeptide BPC 157 therapy might rapidly functionally improve minor vessels to take over the function of disabled major vessels, reorganize blood flow, and compensate failed vessel function. We focused on the BPC 157 therapy effect obtained by giving 10 ng/kg ip to rats 5 min before sacrifice on the rat thoracic aorta, which we assessed with Fourier transform infrared spectroscopy (FTIR) 90 min thereafter. We applied a principal component analysis (PCA). The PCA model showed, with a clear distinction being mostly due to the PC1 score, differences between the spectra of BPC 157- and saline-treated rats. The comparison of the averaged spectra of these two groups with their differential spectrum and PC loadings allowed us to identify the parts of the FTIR spectra that contributed the most to the spectral separation of the two observed groups. The PC1 loadings and the differential spectrum showed that the main bands affecting the separation were the amid I band around 1650 cm-1, the amid II band around 1540 cm-1, and the vibrational band around 1744 cm-1. Fitting the spectral range between 1450 and 1800 cm-1 showed changes in protein conformation and confirmed the appearance of the vibrational band at 1744 cm-1. Controls had a substantially more intense vibrational band at 1744 cm-1. These spectral results showed the cells from saline-treated (control) rats to be in the early stage of cell death, while the samples from BPC 157-rats were protected. Thus, BPC 157 therapy changed the lipid contents and protein secondary structure conformation, with a rapid effect on vessels, within a short time upon application.

Comparison of Glyphosate Detection by Surface-Enhanced Raman Spectroscopy Using Gold and Silver Nanoparticles at Different Laser Excitations.

Glyphosate is one of the most widely used pesticides in the world, but it has been shown to persist in the environment and therefore needs to be detected in food. In this work, the detection of glyphosate by surface-enhanced Raman scattering (SERS) using gold and silver nanoparticles and three different commonly used laser excitations (532, 632, and 785 nm wavelengths) of a Raman microscope complemented with a portable Raman spectrometer with 785 nm excitation is compared. The silver and gold nanosphere SERS substrates were prepared by chemical synthesis. In addition, colorimetric detection of glyphosate using cysteamine-modified gold and silver nanoparticles was also tested. The best results were obtained with Ag NPs at 532 nm excitation with a detection limit of 1 mM and with Au nanoparticles at 785 nm excitation with a detection limit of 100 µM. The SERS spectra of glyphosate with cysteamine-modified silver NPs improved the detection limits by two orders of magnitude for 532 nm excitation, i.e., up to 10 µM, and by one order of magnitude for 632 and 785 nm excitation wavelengths.

Glucosamine to gold nanoparticles binding studied using Raman spectroscopy.

The binding of glucosamine to gold in water solutions of glucosamine hydrochloride mixed with clean colloidal gold nanoparticles obtained by laser ablation in liquid was studied using surface-enhanced Raman scattering (SERS), dynamic light scattering (DLS) and UV-VIS spectroscopy. The purpose of this study was to establish whether the binding of charged aminogroup to gold nanoparticles (AuNPs) is taking place, and if it does, how can it be identified by means of SERS. The average size of dried gold nanoparticles was (20 ± 4) nm determined by averaging the sizes observed in transmission electron microscopy micrographs, which is smaller than the average size of gold nanoparticles in water solution as determined by DLS: (52 ± 2) nm. Upon adding the glucosamine solutions to gold colloid, average hydrodynamic diameter of ions was slightly larger for 0.1 mM glucosamine solution (55 ± 2 nm), while it increased to (105 ± 22) nm in the case of 1 mM solution, and was (398 ± 54) nm when 10 mM glucosamine solution was added. Most prominent Raman bands observed both for 0.1 mM and 1 mM glucosamine solutions were located at 1165 cm-1, 1532 and 1586 cm-1 and assigned to C-N coupled with C-C stretching, and C-NH3+ deformation angles bending. In SERS spectrum of 1 mM GlcN+ solution, two strong bands at 999 and 1075 cm-1 were found and attributed to C-Oring stretching coupled with C-NH3+ bending (999 cm-1) and to dominantly C-O stretching vibration. The differences in SERS spectra are attributed to different number of glucosamine molecules that attach to gold nanoparticles and their orientation with respect to the metal particle surface, partly due to presence of beta anomers protonated at anomeric oxygen position. The assignment of glucosamine bands was further corroborated by comparison with vibrational spectra of alpha and beta glucose and of polycrystalline powder of glucosamine hydrochloride. For all three substances comprehensive calculation of vibrational density of states was conducted using density functional theory. Benchmark bands for polycrystalline glucose anomers distinction are 846 and 915 cm-1 for alpha glucose, and 902 cm-1 for beta glucose. However, the bands observed in SERS spectra of 0.1 mM glucosamine solution at 831, 899, and 946 cm-1 or in 1 mM solution at 934 cm-1 cannot be easily identified as belonging either to alpha or beta glucosamine anomer, due to complexity of atomic motions involved. The identification of vibrational bands associated with -CNH3+ group will aid SERS studies on amino acids, especially in cases when several atomic groups could possibly bind to AuNPs.

Possibility of Human Gender Recognition Using Raman Spectra of Teeth.

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events.

Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy.

Histopathology, despite being the gold standard as a diagnostic tool, does not always provide a correct diagnosis for different pleural lesions. Although great progress was made in this field, the problem to differentiate between reactive and malignant pleural lesions still stimulates the search for additional diagnostic tools. Our research using vibrational spectroscopy and principal component analysis (PCA) statistical modeling represents a potentially useful tool to approach the problem. The objective method this paper explores is based on the correlation between different types of pleural lesions and their vibrational spectra. Obtained tissue spectra recorded by infrared spectroscopy allowed us to categorize spectra in different groups using a created PCA statistical model. The PCA model was built using tissues of known pathology as the model group. The validation samples were then used to confirm the functionality of our PCA model. Student's t-test was also used for comparing samples in paired groups. The PCA model was able to clearly differentiate the spectra of mesothelioma, metastasis and reactive changes (inflammation), and place them in discrete groups. Thus, we showed that Fourier transform infrared spectroscopy combined with PCA can differentiate pleural lesions with high sensitivity and specificity. This new approach could contribute in objectively differentiating specific pleural lesions, thus helping pathologists to better diagnose difficult pleural samples but also could shed additional light into the biology of malignant pleural mesothelioma.

Principal Component Regression for Forensic Age Determination Using the Raman Spectra of Teeth.

Raman spectra of mineralized tooth tissues were used to build a principal component regression (PCR) age determination model for forensic application. A sample of 71 teeth was obtained from donors aging from 11 to 76 years. No particular selection criteria were applied; teeth affected with various pathological processes were deliberately included to simulate a realistic forensic scenario. In order to comply with the nondestructive specimen handling, Raman spectra were collected from tooth surfaces without any previous preparation. Different tooth tissues were evaluated by collecting the spectra from three distinct sites: tooth crown, tooth neck, and root apex. Whole recorded spectra (3500-200 cm-1) were used for principal component analysis and building of the age determination model using PCR. The predictive capabilities of the obtained age determination models varied according to the spectra collection site. Optimal age determination was attained by using Raman spectra collected from cementum at root apex (R2 values of 0.84 and 0.71 for male and female donors, respectively). For optimal performance of that model, male and female donors had to be analyzed separately, as merging both genders into a single model considerably diminished its predictive capability (R2 = 0.29).

Embryo-derived teratoma in vitro biological system reveals antitumor and embryotoxic activity of valproate.

Antiepileptic/teratogen valproate (VPA) is a histone deacetylase inhibitor/epigenetic drug proposed for the antitumor therapy where it is generally crucial to target poorly or undifferentiated cells to prevent a recurrence. Transplanted rodent gastrulating embryos-proper (primitive streak and three germ layers) are the source of teratoma/teratocarcinoma tumors. Human primitive-streak remnants develop sacrococcygeal teratomas that may recur even when benign (well differentiated). To screen for unknown VPA impact on teratoma-type tumors, we used original 2-week embryo-derived teratoma in vitro biological system completed by a spent media metabolome analysis. Gastrulating 9.5-day-old rat embryos-proper were cultivated in Eagle's minimal essential medium (MEM) with 50% rat serum (controls) or with the addition of 2 mmVPA. Spent media metabolomes were analyzed by FTIR. Compared to controls, VPA acetylated histones; significantly diminished overall teratoma growth, impaired survival, increased the apoptotic index, and decreased proliferation index and incidence of differentiated tissues (e.g., neural tissue). Control teratomas continued to grow and differentiate for 14 days in isotransplants in vivo, but in vitro VPA-treated teratomas resorbed. Principal component analysis of FTIR results showed that spent media metabolomes formed well-separated clusters reflecting the treatment and day of cultivation. In metabolomes of VPA-treated teratomas, we found elevation of previously described histone acetylation biomarkers [amide I α-helix and A(CH3 )/A(CH2 )]) with apoptotic biomarkers within the amide I region for ß-sheets, and unordered and CH2 vibrations of lipids. VPA may be proposed for therapy of the undifferentiated component of teratoma tumors and this biological system completed by metabolome analysis, for a faster dual screening of antitumor/embryotoxic agents.

Nanostructured Silicon as Potential Anode Material for Li-Ion Batteries.

Commercial micrometer silicon (Si) powder was investigated as a potential anode material for lithium ion (Li-ion) batteries. The characterization of this powder showed the mean particle size of approx.75.2 nm, BET surface area of 10.6 m2/g and average pore size of 0.56 nm. Its band gap was estimated to 1.35 eV as determined using UV-Vis diffuse reflectance spectra. In order to increase the surface area and porosity which is important for Li-ion batteries, the starting Si powder was ball-milled and threatened by metal-assisted chemical etching. The mechanochemical treatment resulted in decrease of the particle size from 75 nm to 29 nm, an increase of the BET surface area and average pore size to 16.7 m2/g and 1.26 nm, respectively, and broadening of the X-ray powder diffraction (XRD) lines. The XRD patterns of silver metal-assisted chemical etching (MACE) sample showed strong and narrow diffraction lines typical for powder silicon and low-intensity diffraction lines typical for silver. The metal-assisted chemical etching of starting Si material resulted in a decrease of surface area to 7.3 m2/g and an increase of the average pore size to 3.44 nm. These three materials were used as the anode material in lithium-ion cells, and their electrochemical properties were investigated by cyclic voltammetry and galvanostatic charge-discharge cycles. The enhanced electrochemical performance of the sample prepared by MACE is attributed to increase in pore size, which are large enough for easy lithiation. These are the positive aspects of the application of MACE in the development of an anode material for Li-ion batteries.

Near-Infrared Surface-Enhanced Raman Scattering on Silver-Coated Porous Silicon Photonic Crystals.

Surface-enhanced Raman scattering (SERS) with near-infrared (NIR) excitation offers a safe way for the detection and study of fragile biomolecules. In this work, we present the possibility of using silver-coated porous silicon photonic crystals as SERS substrates for near-infrared (1064 nm) excitation. Due to the deep penetration of NIR light inside silicon, the fabrication of photonic crystals was necessary to quench the band gap photoluminescence of silicon crystal, which acts as mechanical support for the porous layer. Optimal parameters of the immersion plating process that gave maximum enhancement were found and the activity of SERS substrates was tested using rhodamine 6G and crystal violet dye molecules, yielding significant SERS enhancement for off-resonant conditions. To our knowledge, this is the first time that the 1064 nm NIR laser excitation is used for obtaining the SERS effect on porous silicon as a substrate.