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Biology subjects

Walther, A. R.

Publications and source records attributed to Walther, A. R..

2 recordsLinked to original sources

Label-free 3-D molecular imaging of living tissues using Raman Spectral Projection Tomography

The ability to image tissues in three-dimensions (3-D) with label-free molecular contrast at mesoscale would be a valuable capability in biology and biomedicine. Here, we introduce Raman spectral projection tomography (RSPT) for volumetric molecular imaging with sub-millimeter spatial resolution. We have developed a RSPT imaging instrument capable of providing 3-D molecular contrast in transparent and semi-transparent samples. A computational pipeline for multivariate reconstruction was established to extract label-free spatial molecular information from Raman projection data. We demonstrate imaging and visualization of phantoms of various complex shapes with label-free molecular contrast. Finally, we apply RSPT as a novel tool for imaging of molecular gradients and extracellular matrix heterogeneities in fixed and live tissue-engineered constructs and explanted native tissues. RSPT imaging opens new possibilities for label-free molecular monitoring of tissues.

bioengineering↗

Detection of low numbers of bacterial cells in pharmaceutical drug product using Raman Spectroscopy and PLS-DA multivariate analysis.

Sterility testing is a laborious and slow process to detect contaminants present in drug products. Raman spectroscopy is a promising label-free tool to detect microorganisms and thus gaining relevance as future alternative culture-free method for sterility testing in pharmaceutical industry. However, reaching detection limits similar to standard procedures while keeping a high accuracy remains challenging, due to weak bacterial Raman signal. In this work, we show a new non-invasive approach focusing on detect different bacteria in concentrations below 100 CFU/ml within drug product containers using Raman spectroscopy and multivariate data analysis. Even though Raman spectra form drug product with and without bacteria are similar, a partial least squared discriminant analysis (PLS-DA) model shows great performance to distinguish samples with bacteria contaminants in limits below 10 CFU/ml. We use spiked samples with bacteria spores for independent validation achieving a detection accuracy of 99%. Our results indicate a great potential of this rapid, and cost-effective approach to be use in quality control of pharmaceutical industry.

bioengineering↗