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The actual implementation of on-site analysis of biomarkers, such as miRNAs, depends on the availability of portable and easy-to-handle detection systems that can be used as point-of-care in real life applications. In this work, an automatized microfluidic platform combined with a portable Raman spectrometer is reported and tested for miR-214 detection by surface enhanced Raman scattering (SERS). A multi-chamber SERS-active chip, functionalized according to a previously optimized two-step hybridization assay, was automatically incubated with the analyte solution. Preliminary tests allowed to adjust the portable Raman spectrometer acquisition conditions and to compare the obtained results with those of a bench Raman microscope. Finally, miR-214 at different concentrations was analyzed through an automatic procedure, achieving a limit of detection (LOD) in the picomolar range.

Hazelnuts (Corylus avellana L.) are among the most consumed dry fruits all over the world. Their commercial quality is defined, above all, by origin and dimension, as well as by lipid content. Evaluation of this parameter is currently performed with chemical methods, which are expensive, time consuming, and complex. In the present work, the near-infrared (NIR) spectroscopy, using both a benchtop research spectrometer and a retail handheld instrument, was evaluated in comparison with the traditional chemical approach. The lipid content of hazelnuts from different growing regions of origin (Italy, Chile, Turkey, Georgia, and Azerbaijan) was determined with two NIR instruments: a benchtop FT-NIR spectrometer (Multi Purpose Analyser—MPA, by Bruker), equipped with an integrating sphere and an optic fibre probe, and the pocket-sized, battery-powered SCiO molecular sensor (by Consumer Physics). The Randall/Soxtec method was used as the reference measurement of total lipid content. The collected NIR spectra were inspected through multivariate data analysis. First, a Principal Component Analysis (PCA) model was built to explore the information contained in the spectral datasets. Then, a Partial Least Square (PLS) regression model was developed to predict the percentage of lipid content. PCA showed samples distributions that could be linked to their total crude fat content determined with the Randall/Soxtec method, confirming that a trend related to the lipid content could be detected in the spectral data, based on their chemical profiles. PLS models performed better with the MPA instrument than SCiO, with the highest R2 of prediction (R2PRED = 0.897) achieved by MPA probe, while this parameter for SCiO was much lower (R2PRED = 0.550). Further analyses are necessary to evaluate if more acquisitions may lead to better performances when using the SCiO portable spectrometer. [ABSTRACT FROM AUTHOR]

This in vitro study investigated the depth of cure of a microhybrid composite resin when cured with reduced times of exposure to three commercially available curing lights. Different sample thicknesses (1, 2, and 3 mm) were light cured in high intensity polymerization mode (2,400 mW/cm2 for 5, 10, 15, and 20 seconds; 1,100 mW/cm2 for 10, 20, 30, and 40 seconds; and 1,100 mW/cm2 for 10, 20, 30, and 40 seconds, respectively). The degree of conversion (%) at the bottom of each sample was measured by Attenuated Total Reflection Fourier Transform Infrared (ATR F-TIR) analysis after each polymerization step. Data were analyzed by ANOVA for repeated measures, showing the degree of conversion was not influenced by the curing light employed (P = .622) but was significantly influenced by the thickness of composite resin (P < .05). Variations in the degree of conversion vs the shorter irradiation time permitted (T1) were not significant among different lamps but were significant among different thicknesses. The depth of cure of microhybrid composite resin appears not to be influenced by the curing light employed. Increased irradiation time significantly increases the degree of conversion. Thickness strongly influences depth of cure. (Quintessence Int 2011;42:e89-e95) [ABSTRACT FROM AUTHOR]

The amount of hydrogen present in porous silicon (PS) nanostructures is analyzed in detail. Concentration of atomic hydrogen chemically bound to the specific surface of PS is quantitatively evaluated by means of attenuated total reflection infrared spectroscopy and temperature-programmed desorption spectroscopy.

When a molecule, engaged in H-bonding with an acidic proton in zeolites, is large enough to interact with the surrounding walls, the IR spectroscopic measure of the acidity is affected, but information may be gained on the geometry of the site. Examples concerning MCM-22, ZSM-5, SAPO-40, and Theta-1 are deiscussed.