184 resultados para Clinical analysis. Near-infrared spectroscopy. Multivariate calibration
Resumo:
Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.
Resumo:
The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δ(r), characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δ(r) and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δ(r). This correlation of δ(r) with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δ(r) values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.
Resumo:
In this report, a detailed FTIR fitting analysis was used to recognize Mg, Zn and Al homogeneous distribution in MgxZnyAl(x+y)/2-Layered double hydroxide (LDH) hydroxyl layer. In detail, OH-Mg2Al:OH-Mg3 ratios decreased from 95.2:4.8 (MIR) and 94.2:5.8 (NIR) to 58.9:41.1 (MIR) and 61.8:38.2 (NIR), when Mg:Al increased from 2.2:1.0 to 4.1:1.0 in MgAl-LDHs. These fitting results were similar with theoretical calculations of 94.3:5.7 and 59.0:41.0. In a further analysis of MgxZnyAl(x+y)/2-LDHs, OH bonded Zn2Mg, Zn2Al, MgZnAl, Mg2Al and Mg2Zn peaks were identified at 3420, 3430, 3445–3450, 3454 and 3545 cm-1, respectively. With the decrease of Mg:Zn from 3:1 to 1:3, metal-hydroxyl bands changed from OH-Mg2Al and MgZnAl (with a ratio of 49.4:50.6) to OH-MgZnAl and Zn2Al (with a ratio of 55.0:45.0). They were also similar with theoretical calculations of 47.6:52.4 and 54.6:45.4. As a result, these results show that there is an ordered cation distribution in MgxZnyAl(x+y)/2-LDH, and FTIR is feasible in recognizing this structure.
Resumo:
Na-dodecylbenzenesulfate (SDBS), a natural anionic surfactant, has been successfully intercalated into a Ca based LDH host structure during tricalcium aluminate hydration in the presence of SDBS aqueous solution (CaAl-SDBS-LDH). The resulting product was characterized by powder X-ray diffraction (XRD), mid-infrared (MIR) spectroscopy combined with near-infrared (NIR) spectroscopy technique, thermal analysis (TG–DTA) and scan electron microscopy (SEM). The XRD results revealed that the interlayer distance of resultant product was expanded to 30.46 Å. MIR combined with NIR spectra offered an effective method to illustrate this intercalation. The NIR spectra (6000–5500 cm−1) displayed prominent bands to expound SDBS intercalated into hydration product of C3A. And the bands around 8300 cm−1 were assigned to the second overtone of the first fundamental of CH stretching vibrations of SDBS. In addition, thermal analysis showed that the dehydration and dehydroxylation took place at ca. 220 °C and 348 °C, respectively. The SEM results appeared approximately hexagonal platy crystallites morphology for CaAl-SDBS-LDH, with particle size smaller and thinner.
Resumo:
The mineral chloritoid collected from the argillite in the bottom of Yaopo Formation of Western Beijing was characterized by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. The MIR spectra showed all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and the influence of iron on the chloritoid structure. The NIR spectrum of the chloritoid showed combination (ν + δ)OH bands with the fundamental stretching (ν) and bending (δ) vibrations. Based on the chemical component data and the analysis result from the MIR and NIR spectra, the crystal structure of chloritoid from western hills of Beijing, China, can be illustrated. Therefore, the application of the technique across the entire infrared region is expected to become more routine and extend its usefulness, and the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for the unit cell structural analysis.
Resumo:
Dolomite mineral samples having white and light green colours of Indian origin have been characterized by EPR, optical and NIR spectroscopy. The optical spectrum exhibits a number of electronic bands due to presence of Fe(III) ions in the mineral. From EPR studies, the parameters of g for Fe(III) and g, A and D for Mn(II) are evaluated and the data confirm that the ions are in distorted octahedron. Optical absorption studies reveal that Fe(III) is in distorted octahedron. The bands in NIR spectra are due to the overtones and combinations of water molecules. Thus EPR and optical absorption spectral studies have proven useful for the study of the chemistry of dolomite.
Resumo:
Mottramite mineral originated from Tsumeb Corporation Mine, Tsumeb, Otavi, Namibia, is used in the present work. The mineral contains of vanadium and copper to the extent of 22.73% and 16.84% by weight respectively as V2O5 and CuO. An EPR study of sample confirms the presence of Cu(II) with g = 2.2. Optical absorption spectrum of mottramite indicates that Cu(II) is present in rhombic environment. NIR results are due to water fundamentals.
Resumo:
The thermal decomposition of halloysite-potassium acetate intercalation compound was investigated by thermogravimetric analysis and infrared emission spectroscopy. The X-ray diffraction patterns indicated that intercalation of potassium acetate into halloysite caused an increase of the basal spacing from 1.00 to 1.41 nm. The thermogravimetry results show that the mass losses of intercalation the compound occur in main three main steps, which correspond to (a) the loss of adsorbed water (b) the loss of coordination water and (c) the loss of potassium acetate and dehydroxylation. The temperature of dehydroxylation and dehydration of halloysite is decreased about 100 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the halloysite intercalation compound when the temperature is raised. The dehydration of the intercalation compound is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration was completed by 300 °C and partial dehydroxylation by 350 °C. The inner hydroxyl group remained until around 500 °C.
Resumo:
Raman spectroscopy has enabled insights into the molecular structure of the richelsdorfite Ca2Cu5Sb[Cl|(OH)6|(AsO4)4]·6H2O. This mineral is based upon the incorporation of arsenate or phosphate with chloride anion into the structure and as a consequence the spectra reflect the bands attributable to these anions, namely arsenate or phosphate and chloride. The richelsdorfite Raman spectrum reflects the spectrum of the arsenate anion and consists of ν1 at 849, ν2 at 344 cm−1, ν3 at 835 and ν4 at 546 and 498 cm−1. A band at 268 cm−1 is attributed to CuO stretching vibration. Low wavenumber bands at 185 and 144 cm−1 may be assigned to CuCl TO/LO optic vibrations.
Resumo:
The thermal behavior and decomposition of kaolinite-potassium acetate intercalation complex was investigated through a combination of thermogravimetric analysis and infrared emission spectroscopy. Three main changes were observed at 48, 280, 323 and 460 °C which were attributed to (a) the loss of adsorbed water (b) loss of the water coordinated to acetate ion in the layer of kaolinite (c) loss of potassium acetate in the complex and (d) water through dehydroxylation. It is proposed that the KAc intercalation complex is stability except heating at above 300 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the kaolinite intercalation complex when the temperature is raised. The dehydration of the intercalation complex is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration is completed by 400 °C and partial dehydroxylation by 650 °C. The inner hydroxyl group remained until around 700 °C.
Resumo:
Mid-infrared (MIR) and near-infrared (NIR) spectroscopy have been used to study the molecular structure of halloysite and potassium acetate intercalated halloysite and to determine the structural changes of halloysite through intercalation. The MIR spectra show all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and water molecules in the structure of halloysite and its intercalation complex. Comparison between halloysite and halloysite-potassium acetate intercalation complex shows almost all bands observed for halloysite are also observed for halloysite-potassium acetate intercalation complex apart from bands observed in the 1700-1300 cm-1 region, but with differences in band intensity. However, NIR, based on MIR spectra, provide sufficient evidence to analyze the structural changes of halloysite through intercalation. There are obvious differences between halloysite and halloysite-potassium acetate intercalation complex in the all spectral ranges. Therefore, the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for molecular structural analysis.
Resumo:
Photochemistry has made significant contributions to our understanding of many important natural processes as well as the scientific discoveries of the man-made world. The measurements from such studies are often complex and may require advanced data interpretation with the use of multivariate or chemometrics methods. In general, such methods have been applied successfully for data display, classification, multivariate curve resolution and prediction in analytical chemistry, environmental chemistry, engineering, medical research and industry. However, in photochemistry, by comparison, applications of such multivariate approaches were found to be less frequent although a variety of methods have been used, especially with spectroscopic photochemical applications. The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses). Applications of such methods are discussed in this overview and typical examples include photodegradation of herbicides, prediction of antibiotics in human fluids (fluorescence spectroscopy), non-destructive in- and on-line monitoring (near infrared spectroscopy) and fast-time resolution of spectroscopic signals from photochemical reactions. It is also quite clear from the literature that the scope of spectroscopic photochemistry was enhanced by the application of chemometrics. To highlight and encourage further applications of chemometrics in photochemistry, several additional chemometrics approaches are discussed using data collected by the authors. The use of a PCA biplot is illustrated with an analysis of a matrix containing data on the performance of photocatalysts developed for water splitting and hydrogen production. In addition, the applications of the Multi-Criteria Decision Making (MCDM) ranking methods and Fuzzy Clustering are demonstrated with an analysis of water quality data matrix. Other examples of topics include the application of simultaneous kinetic spectroscopic methods for prediction of pesticides, and the use of response fingerprinting approach for classification of medicinal preparations. In general, the overview endeavours to emphasise the advantages of chemometrics' interpretation of multivariate photochemical data, and an Appendix of references and summaries of common and less usual chemometrics methods noted in this work, is provided. Crown Copyright © 2010.