Differences in infrared spectroscopic data of connective tissues in transflectance and transmittance modes

Fourier transform infrared imaging spectroscopy (FT-IRIS) has been used extensively to characterize the composition and orientation of macromolecules in thin tissue sections. Earlier and current studies of normal and polarized FT-IRIS data have primarily used tissues sectioned onto infrared transmissive substrates, such as salt windows. Recently, the use of low-emissivity (“low-e”) substrates has become of great interest because of their low cost and favorable infrared optical properties. However, data are collected in transflectance mode when using low-e slides and in transmittance mode using salt windows. In the current study we investigated the comparability of these two modes for assessment of the composition of connective tissues. FT-IRIS data were obtained in transflectance and transmittance modes from serial sections of cartilage, bone and tendon, and from a standard polymer, polymethylmethacrylate. Both non-polarized and polarized FTIR data differed in absorbance, and in some cases peak position, between transflectance and transmittance modes. However, the FT-IRIS analysis of the collagen fibril orientation in cartilage resulted in the expected zonal arrangement of fibrils in both transmittance and transflectance. We conclude that numerical comparison of FT-IRIS-derived parameters of tissue composition should account for substrate type and data collection mode, while analysis of overall tissue architecture may be more invariant between modes.     

Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics

Undesired germination of cereal grains diminishes process utility and economic return. Pre-germination, the term used to describe untimely germination, leads to reduced viability of a grain sample. Accurate and rapid identification of non-viable grain is necessary to reduce losses associated with pre-germination. Viability of barley, wheat and sorghum grains was investigated with near-infrared hyperspectral imaging. Principal component analyses applied to cleaned hyperspectral images were able to differentiate between viable and non-viable classes in principal component (PC) five for barley and sorghum and in PC6 for wheat. An OH stretching and deformation combination mode (1,920–1,940 nm) featured in the loading line plots of these PCs; this water-based vibrational mode was a major contributor to the viable/non-viable differentiation. Viable and non-viable classes for partial least squares-discriminant analysis (PLS-DA) were assigned from PC scores that correlated with incubation time. The PLS-DA predictions of the viable proportion correlated well with the viable proportion observed using the tetrazolium test. Partial least squares regression analysis could not be used as a source of contrast in the hyperspectral images due to sampling issues.     

Pharmaceutical polymorphs quantified with transmission Raman spectroscopy

The quantification of polymorphs in dosage forms is important in the pharmaceutical industry. Conventional Raman spectroscopy of solid‐state pharmaceuticals may be used for this, but it has some limitations such as sub‐sampling and fluorescence. These problems can be mitigated through the use of transmission Raman spectroscopy (TRS). The efficacy of TRS measurements for the prediction of polymorph content was evaluated using a ranitidine hydrochloride test system. Four groups of ranitidine hydrochloride‐based samples were prepared: three containing form I and II ranitidine hydrochloride and microcrystalline cellulose (spanning the ranges 0–10%, 90–100% and 0–100% form I fraction of total ranitidine hydrochloride), and a fourth group comprising form I ranitidine hydrochloride (0–10%) spiked commercial formulation. Transmission and conventional Raman spectroscopic measurements were recorded from both capsules and tablets of the four sample groups. Prediction models for polymorph and total ranitidine hydrochloride content were more accurate for the tablet than for the capsule systems. TRS was found to be superior to conventional backscattering Raman spectroscopy in the prediction of polymorph and total ranitidine hydrochloride content. The prediction model calculated for form I content across the 0–100% range was appropriate for process control [ratio of prediction to deviation (RPD) equal to 14.62 and 7.42 for tablets and capsules, respectively]. The 10% range calibrations for both form I and total ranitidine hydrochloride content were sufficient for screening (RPDs greater than 2.6). TRS is an effective tool for polymorph process control within the pharmaceutical industry. Copyright © 2011 John Wiley & Sons, Ltd.     

Rapid and cost-effective evaluation of bacterial viability using fluorescence spectroscopy

A rapid and easy method that takes advantage of an inexpensive and portable fibre-based spectroscopic system (optrode) to determine the ratio of live to dead bacteria is proposed. Mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were stained using SYTO 9 and propidium iodide (PI) and measured using the optrode. We demonstrated several approaches to obtaining the proportions of live:dead E. coli in a mixture of both live and dead, from analyses of the fluorescence spectra collected by the optrode. To find a suitable technique for predicting the percentage of live bacteria in a sample, four analysis methods were assessed and compared: SYTO 9:PI fluorescence intensity ratio, an adjusted fluorescence intensity ratio, single-spectrum support vector regression (SVR) and multi-spectra SVR. Of the four analysis methods, multi-spectra SVR obtained the most reliable results and was able to predict the percentage of live bacteria in 10⁸ bacteria/mL samples between c. 7 and 100% live, and in 10⁷ bacteria/mL samples between c. 7 and 73% live. By demonstrating the use of multi-spectra SVR and the optrode to monitor E. coli viability, we raise points of consideration for spectroscopic analysis of SYTO 9 and PI and aim to lay the foundation for future work that uses similar methods for different bacterial species.