bioRxiv Science⌕ Search

Biology subjects

Mehrotra, D. R.

Publications and source records attributed to Mehrotra, D. R..

2 recordsLinked to original sources

Absolute Quantification of Tissue Composition by Raman Spectroscopy

Raman spectroscopy captures the molecular fingerprints of living tissues without labels or tissue destruction. Translating these spectra into absolute measures of tissue biochemical composition remains a challenge owing to tissue-dependent optical properties, variations in sampling volume, and lack of normalization standards requisite for quantitative scaling. Here we introduce a scheme to derive the biochemical constituents of a tissue expressed as a percentage of the tissue wet weight, like biochemical assays, from Raman spectra measured optically. Nonlinear polynomial models of Raman spectra are trained on chemically defined phantoms that mimic the variability of the essential biochemical constituents of a tissue, accommodating spectral overlap and tissue-dependent optical effects. We validated this scheme using cartilage, a tissue fundamental to diarthrodial joint function. Cartilage is comprised of glycosaminoglycans, collagens and water that act synergistically to impart the rheological and tribological material properties essential to tissue function. Using biochemically perturbed live cartilage explants, phantom-calibrated Raman spectroscopy (PC-Raman) resolved constituent-specific changes and achieved quantitative agreement with independent biochemical assays (R-squared = 0.88-0.92; slopes {approx} 1.0; 95% confidence intervals {+/-}2.7-3.2%pt). We demonstrate that PC-Raman is applicable across the hierarchy of tissue interrogation from microscopic imaging of tissue extracellular matrix composition to macroscopic longitudinal monitoring of drug effects in-vitro using live tissue constructs and in-vivo assessments of cartilage regeneration in an equine cartilage repair model. Converting Raman spectra measurements of the essential biochemical constituents of a tissue in absolute terms (tissue wet-weight-%) allows for the non-destructive, longitudinal quantification of tissue composition in disease (tissue degeneration) and in response to treatment (tissue repair).

biochemistry↗

A Teensy microcontroller-based interface for optical imaging camera control during behavioral experiments

BackgroundSystems neuroscience experiments often require the integration of precisely timed data acquisition and behavioral monitoring. While specialized commercial systems have been designed to meet various needs of data acquisition and device control, they often fail to offer flexibility to interface with new instruments and variable behavioral experimental designs. New methodWe developed a Teensy 3.2 microcontroller-based interface that offers high-speed, precisely timed behavioral data acquisition and digital and analog outputs for controlling sCMOS cameras and other devices. ResultsWe demonstrate the flexibility and the temporal precision of the Teensy interface in two experimental settings. We first used the Teensy interface for reliable recordings of an animals directional movement on a spherical treadmill, while delivering repeated digital pulses that can be used to control image acquisition from a sCMOS camera. In another example, we used the Teensy interface to control temporally precise delivery of an auditory stimulus and a gentle eye puff in a trace conditioning eye blink behavioral paradigm, while delivering repeated digital pulses to initiate camera image acquisition. Comparison with existing methodsThis interface allows high-speed and temporally precise digital data acquisition and device control during diverse behavioral experiments. ConclusionThe Teensy interface, consisting of a Teensy 3.2 and custom software functions, provides a temporally precise, low-cost, and flexible platform to integrate sCMOS camera control into behavioral experiments.

neuroscience↗