Super-resolution infrared microspectroscopy reveals heterogeneous distribution of photosensitive lipids in human hair medulla

Human hair medulla chemical composition appears mostly homogenous when mapped by FTIR micro -spectroscopy even when using a synchrotron radiation source (SR-mu FTIR) but it is expected to be heterogeneous. We performed sub-micron chemical mapping of hair cortex and medullas using Optical Photothermal Infrared microspectroscopy (OPTIR) and a mid-infrared Quantum Cascade Laser (QCL) source covering the fingerprint and the CH stretching region. Photodamages were observed in the hair cortex at mild laser power and occurred in the hair medulla even at the lowest power settings of the IR QCL pulsed at 100 kHz rate (4 mu W/mu m2 average power density) and visible probe laser (200 mu w/mu m2 average power density). Photoconversion of calcium car-boxylates in other molecules, possibly sodium carboxylates, was observed. Attenuation of the IR QCL power by 40% using ZnSe filter and/or high-speed measurements (1000 cm? 1/s) succeeded in almost completely elimi-nating the photodamages and photoconversion. OPTIR maps and images showed that the medullas were highly heterogeneous at the submicron scale. We found calcium carboxylates, aliphatic lipids and wax esters in small units, hundreds of nanometers in size. The 1470 cm -1 C--O sym stretching peak of calcium carboxylates and the CH2 asym stretching peak from aliphatic lipids proved to be the most efficient peaks to track the distribution of these molecules. OPTIR had enough sensitivity to map accurately only the strongest peaks from lipids and cal-cium carboxylates, weaker peaks such as the ester C--O and sulfoxide S--O bands were not accurately detected by OPTIR even when they were shown to be present by SR-mu FTIR. Quantification of the medulla components by OPTIR is difficult due to several factors: discontinuous QCL emission, and noise. The weaker peaks such as CH3, C--O, S--O are often underestimated or not detected. We demonstrate here that OPTIR can be used to measure, map and image dark, photosensitive samples using very low IR power.