959 resultados para TG-FTIR spectroscopy


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After the landmark studies reporting changes in the cerebral metabolic rate of glucose (CMRGlc ) in excess of those in oxygen (CMRO2 ) during physiological stimulation, several studies have examined the fate of the extra carbon taken up by the brain, reporting a wide range of changes in brain lactate from 20% to 250%. The present study reports functional magnetic resonance spectroscopy measurements at 7 Tesla using the enhanced sensitivity to study a small cohort (n = 6). Small increases in lactate (19% ± 4%, P < 0.05) and glutamate (4% ± 1%, P < 0.001) were seen within the first 2 min of activation. With the exception of glucose (12% ± 5%, P < 0.001), no other metabolite concentration changes beyond experimental error were significantly observed. Therefore, the present study confirms that lactate and glutamate changes during physiological stimulation are small (i.e. below 20%) and shows that the increased sensitivity allows reproduction of previous results with fewer subjects. In addition, the initial rate of glutamate and lactate concentration increases implies an increase in CMRO2 that is slightly below that of CMRGlc during the first 1-2 min of activation.

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Raman spectroscopy has become a widespread technique for the analysis ofpharmaceutical solid forms. The application proposed here is the investigationof counterfeit medicines. This serious global issue requires quick and accurateidentification methods to fight against this phenomenon. Thanks to its chemicalselectivity, rapidity of analysis and potential of generating repeatable spectralprofiles, Raman spectroscopy presents distinct advantages for the analysis ofcounterfeits. Combined with chemometric tools, the technique enablesthe detection, the determination of chemical composition and the profiling ofmedicine counterfeits.

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Measurement of the hepatic oxygenation index by near infrared spectroscopy is a suitable method to estimate the oxygenation and can be a non-invasive means to continuously monitor tissue perfusion and to detect early haemodynamic disturbances in critically ill children.

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In this study, glyoxalated alkaline lignins with a non-volatile and non-toxic aldehyde, which can be obtained from several natural resources, namely glyoxal, were prepared and characterized for its use in wood adhesives. The preparation method consisted of the reaction of lignin with glyoxal under an alkaline medium. The influence of reaction conditions such as the molar ratio of sodium hydroxide-to-lignin and reaction time were studied relative to the properties of the prepared adducts. The analytical techniques used were FTIR and 1H-NMR spectroscopies, gel permeation chromatography (GPC), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Results from both the FTIR and 1H-NMR spectroscopies showed that the amount of introduced aliphatic hydroxyl groups onto the lignin molecule increased with increasing reaction time and reached a maximum value at 10 h, and after they began to decrease. The molecular weights remained unchanged until 10 h of reaction time, and then started to increase, possibly due to the repolymerization reactions. DSC analysis showed that the glass transition temperature (Tg) decreased with the introduction of glyoxal onto the lignin molecule due to the increase in free volume of the lignin molecules. TGA analysis showed that the thermal stability of glyoxalated lignin is not influenced and remained suitable for wood adhesives. Compared to the original lignin, the improved lignin is reactive and a suitable raw material for adhesive formula

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Besides polyurethanes and polyesters, phenolic and epoxy resins are the most prominent applications for technical lignins in thermosetting materials. To evaluate the potential application of lignin raw materials in phenol formaldehyde and epoxy resins, three types of alkaline lignins were characterized in terms of their structures and thermal properties. The lignin samples analyzed were kraft lignin (LIG-1), soda–rice straw lignin (LIG-2), and soda-wheat straw lignin (LIG-3). FTIR and 1H-NMR methods were used to determine their structure. Gel permeation chromatography (GPC) was used to determine the molecular weight distribution (MWD). Differential scanning calorimetry (DSC) was used to measure the glass transition temperature (Tg), and thermogravimetric analysis (TGA) to determine the thermal stability of lignin samples. Results showed that kraft lignin (LIG-1) has moderate hydroxyl-group content, is rich in G-type units, and has good thermal stability. These properties make it more suitable for direct use in phenol formaldehyde resins, and it is therefore a good raw material for this purpose. The alkaline soda-rice straw lignin (LIG-2) with a high hydroxyl-group content and excellent thermal stability is most suited to preparing lignin-based epoxy resin

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A series of InxAl1-xAs samples (0.51≪x≪0.55)coherently grown on InP was studied in order to measure the band-gap energy of the lattice matched composition. As the substrate is opaque to the relevant photon energies, a method is developed to calculate the optical absorption coefficient from the photoluminescence excitation spectra. The effect of strain on the band-gap energy has been taken into account. For x=0.532, at 14 K we have obtained Eg0=1549±6 meV

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Background. Age is an important risk factor for perioperative cerebral complications such as stroke, postoperative cognitive dysfunction, and delirium. We explored the hypothesis that intraoperative cerebrovascular autoregulation is less efficient and brain tissue oxygenation lower in elderly patients, thus, increasing the vulnerability of elderly brains to systemic insults such as hypotension.Methods. We monitored intraoperative cerebral perfusion in 50 patients aged 18-40 and 77 patients >65 yr at two Swiss university hospitals. Mean arterial pressure (MAP) was measured continuously using a plethysmographic method. An index of cerebrovascular autoregulation (Mx) was calculated based on changes in transcranial Doppler flow velocity due to changes in MAP. Cerebral oxygenation was assessed by the tissue oxygenation index (TOI) using near-infrared spectroscopy. End-tidal CO(2), O(2), and sevoflurane concentrations and peripheral oxygen saturation were recorded continuously. Standardized anaesthesia was administered in all patients (thiopental, sevoflurane, fentanyl, atracurium).Results. Autoregulation was less efficient in patients aged >65 yr [by 0.10 (SE 0.04; P=0.020)] in a multivariable linear regression analysis. This difference was not attributable to differences in MAP, end-tidal CO2, or higher doses of sevoflurane. TOI was not significantly associated with age, sevoflurane dose, or Mx but increased with increasing flow velocity [by 0.09 (SE 0.04; P=0.028)] and increasing MAP [by 0.11 (SE 0.05; P=0.043)].Conclusions. Our results do not support the hypothesis that older patients' brains are more vulnerable to systemic insults. The difference of autoregulation between the two groups was small and most likely clinically insignificant.

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A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units. © RSNA, 2014 Online supplemental material is available for this article.

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This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.

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CONTEXT: Recent magnetic resonance imaging studies have attempted to relate volumetric brain measurements in early schizophrenia to clinical and functional outcome some years later. These studies have generally been negative, perhaps because gray and white matter volumes inaccurately assess the underlying dysfunction that might be predictive of outcome. OBJECTIVE: To investigate the predictive value of frontal and temporal spectroscopy measures for outcome in patients with first-episode psychoses. DESIGN: Left prefrontal cortex and left mediotemporal lobe voxels were assessed using proton magnetic resonance spectroscopy to provide the ratio of N-acetylaspartate (NAA) and choline-containing compounds to creatine and phosphocreatine (Cr) (NAA/Cr ratio). These data were used to predict outcome at 18 months after admission, as assessed by a systematic medical record audit. SETTING: Early psychosis clinic. PARTICIPANTS: Forty-six patients with first-episode psychosis. MAIN OUTCOME MEASURES: We used regression models that included age at imaging and duration of untreated psychosis to predict outcome scores on the Global Assessment of Functioning Scale, Clinical Global Impression scales, and Social and Occupational Functional Assessment Scale, as well as the number of admissions during the treatment period. We then further considered the contributions of premorbid function and baseline level of negative symptoms. RESULTS: The only spectroscopic predictor of outcome was the NAA/Cr ratio in the prefrontal cortex. Low scores on this variable were related to poorer outcome on all measures. In addition, the frontal NAA/Cr ratio explained 17% to 30% of the variance in outcome. CONCLUSIONS: Prefrontal neuronal dysfunction is an inconsistent feature of early psychosis; rather, it is an early marker of poor prognosis across the first years of illness. The extent to which this can be used to guide treatment and whether it predicts outcome some years after first presentation are questions for further research.

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Accomplish high quality of final products in pharmaceutical industry is a challenge that requires the control and supervision of all the manufacturing steps. This request created the necessity of developing fast and accurate analytical methods. Near infrared spectroscopy together with chemometrics, fulfill this growing demand. The high speed providing relevant information and the versatility of its application to different types of samples lead these combined techniques as one of the most appropriated. This study is focused on the development of a calibration model able to determine amounts of API from industrial granulates using NIR, chemometrics and process spectra methodology.

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Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

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Purpose Carbon-13 magnetic resonance spectroscopy (13C-MRS) is challenging because of the inherent low sensitivity of 13C detection and the need for radiofrequency transmission at the 1H frequency while receiving the 13C signal, the latter requiring electrical decoupling of the 13C and 1H radiofrequency channels. In this study, we added traps to the 13C coil to construct a quadrature-13C/quadrature-1H surface coil, with sufficient isolation between channels to allow simultaneous operation at both frequencies without compromise in coil performance. Methods Isolation between channels was evaluated on the bench by measuring all coupling parameters. The quadrature mode of the quadrature-13C coil was assessed using in vitro 23Na gradient echo images. The signal-to-noise ratio (SNR) was measured on the glycogen and glucose resonances by 13C-MRS in vitro, compared with that obtained with a linear-13C/quadrature-1H coil, and validated by 13C-MRS in vivo in the human calf at 7T. Results Isolation between channels was better than â^'30 dB. The 23Na gradient echo images indicate a region where the field is strongly circularly polarized. The quadrature coil provided an SNR enhancement over a linear coil of 1.4, in vitro and in vivo. Conclusion It is feasible to construct a double-quadrature 13C-1H surface coil for proton decoupled sensitivity enhanced 13C-NMR spectroscopy in humans at 7T. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

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Quantification of short-echo time proton magnetic resonance spectroscopy results in >18 metabolite concentrations (neurochemical profile). Their quantification accuracy depends on the assessment of the contribution of macromolecule (MM) resonances, previously experimentally achieved by exploiting the several fold difference in T(1). To minimize effects of heterogeneities in metabolites T(1), the aim of the study was to assess MM signal contributions by combining inversion recovery (IR) and diffusion-weighted proton spectroscopy at high-magnetic field (14.1 T) and short echo time (= 8 msec) in the rat brain. IR combined with diffusion weighting experiments (with δ/Δ = 1.5/200 msec and b-value = 11.8 msec/μm(2)) showed that the metabolite nulled spectrum (inversion time = 740 msec) was affected by residuals attributed to creatine, inositol, taurine, choline, N-acetylaspartate as well as glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost not affected (< 8%). The combination of metabolite-nulled IR spectra with diffusion weighting allows a specific characterization of MM resonances with minimal metabolite signal contributions and is expected to lead to a more precise quantification of the neurochemical profile.