Measurement of photon penetration in biological tissues is a central theme in optical imaging. A great number of endogenous tissue factors such as absorption, scattering, and anisotropy affect the path of photons in tissue, making it difficult to predict the penetration depth at different wavelengths. Traditional studies evaluating photon penetration at different wavelengths are focused on tissue spectroscopy that does not take into account the heterogeneity within the sample. This is especially critical in shortwave infrared where the individual vibration-based absorption properties of the tissue molecules are affected by nearby tissue components. We have explored the depth penetration in biological tissues from 900 to 1650 nm using Monte–Carlo simulation and a hyperspectral imaging system with Michelson spatial contrast as a metric of light penetration. Chromatic aberration-free hyperspectral images in transmission and reflection geometries were collected with a spectral resolution of 5.27 nm and a total acquisition time of 3 min. Relatively short recording time minimized artifacts from sample drying. Results from both transmission and reflection geometries consistently revealed that the highest spatial contrast in the wavelength range for deep tissue lies within 1300 to 1375 nm; however, in heavily pigmented tissue such as the liver, the range 1550 to 1600 nm is also prominent.

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health.

(2015). Fluorescence anisotropy (polarization): from drug screening to precision medicine. Expert Opinion on Drug Discovery: Vol. 10, No. 11, pp. 1145-1161.

Self‐aggregation of dyes even at low concentrations poses a considerable challenge in preparing sufficiently bright molecular probes forin vivoimaging, particularly in the conjugation of near infrared cyanine dyes to polypeptides with multiple labeling sites. Such self‐aggregation leads to a significant energy transfer between the dyes, resulting in severe quenching and low brightness of the targeted probe. To address this problem, we designed a novel type of dye with an asymmetrical distribution of charge. Asymmetrical distribution prevents the chromophores fromπ‐stacking thus minimizing the energy transfer and fluorescence quenching. The conjugation of the dye to polypeptides showed only a small presence of an H‐aggregate band in the absorption spectra and, hence, a relatively high quantum efficiency. Copyright © 2014 John Wiley & Sons, Ltd.