Sample preparation of biological tissues for infrared spectroscopy using frustrated multiple internal reflectance

1965 ◽  
Vol 12 (2) ◽  
pp. 406-411 ◽  
Author(s):  
T.S. Hermann
2016 ◽  
Vol 51 (12) ◽  
pp. 1168-1179 ◽  
Author(s):  
Faizan Zubair ◽  
Paul E. Laibinis ◽  
William G. Swisher ◽  
Junhai Yang ◽  
Jeffrey M. Spraggins ◽  
...  

Molecules ◽  
2019 ◽  
Vol 24 (8) ◽  
pp. 1639 ◽  
Author(s):  
Liakh ◽  
Pakiet ◽  
Sledzinski ◽  
Mika

Oxylipins are potent lipid mediators derived from polyunsaturated fatty acids, which play important roles in various biological processes. Being important regulators and/or markers of a wide range of normal and pathological processes, oxylipins are becoming a popular subject of research; however, the low stability and often very low concentration of oxylipins in samples are a significant challenge for authors and continuous improvement is required in both the extraction and analysis techniques. In recent years, the study of oxylipins has been directly related to the development of new technological platforms based on mass spectrometry (LC–MS/MS and gas chromatography–mass spectrometry (GC–MS)/MS), as well as the improvement in methods for the extraction of oxylipins from biological samples. In this review, we systematize and compare information on sample preparation procedures, including solid-phase extraction, liquid–liquid extraction from different biological tissues.


2002 ◽  
Vol 32 (6) ◽  
pp. 1029-1037 ◽  
Author(s):  
K. MATSUO, ◽  
N. KATO ◽  
T. KATO

Background. Hypofrontality has been demonstrated in mood disorders by functional brain imaging methods such as positron emission tomography. However, the neurobiological basis of hypofrontality has not been well clarified. Near-infrared spectroscopy (NIRS) is a non-invasive technique for continuous monitoring of alterations in oxygenated (oxyHb) and deoxygenated (deoxyHb) haemoglobin using near-infrared light, which penetrates biological tissues.Methods. We used NIRS during cognitive and physiological tasks to investigate alterations of haemoglobin oxygenation in the frontal region of euthymic patients with mood disorders (major depressive disorder (MD) and bipolar disorder (BP)) and in controls.Results. The increase of oxyHb during a verbal fluency task was significantly less in the MD and the BP groups than in the controls. The MD group showed a significantly smaller decrease of oxyHb during hyperventilation than the controls. The BP group also showed a similar trend.Conclusions. These findings suggest that the hypofrontality in mood disorders may be associated with a poor response in the cerebral blood vessels to neuronal and chemical stimuli.


2020 ◽  
pp. 000370282096806
Author(s):  
Robert Stach ◽  
Teresa Barone ◽  
Emanuele Cauda ◽  
Boris Mizaikoff

The exposure of mining workers to crystalline particles, e.g., alpha quartz in respirable dust, is a ubiquitous global problem in occupational safety and health at surface and underground operations. The challenge of rapid in-field monitoring for direct assessment and adoption of intervention has not been solved satisfactorily to date, as conventional analytical methods such as X-ray diffraction and infrared spectroscopy require laboratory environments, complex system handling, tedious sample preparation, and are limited by, e.g., addressable particle size. A novel monitoring approach was developed for potential in-field application enabling the quantification of crystalline particles in the respirable regime based on transmission infrared spectroscopy. This on-site approach analyzes samples of dust in ambient air collected onto PVC filters using respirable dust sampling devices. In the present study, we demonstrate that portable Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate data analysis provides a versatile tool for the identification and quantification of minerals in complex real-world matrices. Without further sample preparation, the loaded filters are immediately analyzed via transmission infrared spectroscopy, and the mineral amount is quantified in real-time using a partial least squares regression algorithm. Due to the inherent molecular selectivity for crystalline as well as organic matrix components, infrared spectroscopy uniquely allows to precisely determine the particle composition even in complex samples such as dust from coal mines or clay-rich environments. For establishing a robust partial least squares regression model, a method was developed for generating calibration samples representative in size and composition for respirable mine dust via aerodynamic size separation. Combined with experimental design strategies, this allows tailoring the calibration set to the demands of air quality management in underground mining scenarios, i.e., the respirable particle size regime and the matrix of the target analyte.


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