Abstract
The increase of tissue transparency through sequential optical immersion clearing treatments and treatment reversibility have high interest for clinical applications. To evaluate the clearing reversibility in a broad spectral range and the magnitude of the transparency created by a second treatment, the present study consisted on measuring the spectral collimated transmittance of lung tissues during a sequence of two treatments with electronic cigarette (e-cig) fluid, which was intercalated with an immersion in saline. The saline immersion clearly reverted the clearing effect in the lung tissue in the spectral range between 220 and 1000 nm. By a later application of a second treatment with the e-cig fluid, the magnitude of the optical clearing effect was observed to be about the double as the one observed in the first treatment, showing that the molecules of the optical clearing agent might have converted some bound water into mobile water during the first treatment.

Abstract
Apart from radiation, which constitutes the primary source of information in laser-induced breakdown spectroscopy, the process is accompanied by secondary processes such as shock wave generation and sound emission. In this manuscript, we explore the possibility of relating plasma properties with the sound from the shock waves in multiple materials, from metals to minerals. By analyzing the behavior of shock wave sound from homogeneous reference metallic targets, we investigate the relation between plasma properties and sound signal, demonstrating that distinct materials and plasma characteristics correspond to distinct plasma sound fingerprints. © Published under licence by IOP Publishing Ltd.

Abstract
The possibility to map the element distribution on a sample surface is one of the interesting applications of laser-induced breakdown spectroscopy that has been extensively explored in recent years. In this manuscript, we explore the combination of photogrammetry and LIBS techniques for the creation of a three-dimensional model of the map of the elements on the surface of the sample. Using a dedicated photogrammetry solution and software, we reconstruct the three-dimensional model of the mineral sample whose mesh is later exploited for the interactive interpretation of the results. Then, making use of Paraview software, which integrates production algorithms and computing performance in a unified solution for scientific purposes, we establish a process pipeline that allows the creation of an interactive three-dimensional model with the spatial distribution of the target elements on top of the sample surface. Our results demonstrate that combining these two techniques can give us a valuable resource for better qualitative analysis and insight, providing an innovative three-dimensional modeling solution that may open the door to a new range of possibilities, from quality control technology involving alloys and mechanical parts to interactive teaching environments for geo and biosciences, just to name a few examples. © Published under licence by IOP Publishing Ltd.

Abstract
The recent increasing interest in the application of radiology contrasting agents to create transparency in biological tissues implies that the diffusion properties of those agents need evaluation. The comparison of those properties with the ones obtained for other optical clearing agents allows to perform an optimized agent selection to create optimized transparency in clinical applications. In this study, the evaluation and comparison of the diffusion properties of gadobutrol and glycerol in skeletal muscle was made, showing that although gadobutrol has a higher molar mass than glycerol, its low viscosity allows for a faster diffusion in the muscle. The characterization of the tissue dehydration and refractive index matching mechanisms of optical clearing was made in skeletal muscle, namely by the estimation of the diffusion coefficients for water, glycerol and gadobutrol. The estimated tortuosity values of glycerol (2.2) and of gadobutrol (1.7) showed a longer path-length for glycerol in the muscle.

Abstract
The pancreas is a highly important organ, since it produces insulin and prevents the occurrence of diabetes. Although rare, pancreatic cancer is highly lethal, with a small life expectancy after being diagnosed. The pancreas is one of the organs less studied in the field of biophotonics. With the objective of acquiring information that can be used in the development of future applications to diagnose and treat pancreas diseases, the spectral optical properties of the rabbit pancreas were evaluated in a broad-spectral range, between 200 and 1000 nm. The method used to obtain such optical properties is simple, based almost on direct calculations from spectral measurements. The optical properties obtained show similar wavelength dependencies to the ones obtained for other tissues, but a further analysis on the spectral absorption coefficient showed that the pancreas tissues contain pigments, namely melanin, and lipofuscin. Using a simple calculation, it was possible to retrieve similar contents of these pigments from the absorption spectrum of the pancreas, which indicates that they accumulate in the same proportion as a result of the aging process. Such pigment accumulation was camouflaging the real contents of DNA, hemoglobin, and water, which were precisely evaluated after subtracting the pigment absorption.

Abstract
Optical trapping provides a way to isolate, manipulate, and probe a wide range of microscopic particles. Moreover, as particle dynamics are strongly affected by their shape and composition, optical tweezers can also be used to identify and classify particles, paving the way for multiple applications such as intelligent microfluidic devices for personalized medicine purposes, or integrated sensing for bioengineering. In this work, we explore the possibility of using properties of the forward scattered radiation of the optical trapping beam to analyze properties of the trapped specimen and deploy an autonomous classification algorithm. For this purpose, we process the signal in the Fourier domain and apply a dimensionality reduction technique using UMAP algorithms, before using the reduced number of features to feed standard machine learning algorithms such as K-nearest neighbors or random forests. Using a stratified 5-fold cross-validation procedure, our results show that the implemented classification strategy allows the identification of particle material with accuracies up to 80%, demonstrating the potential of using signal processing techniques to probe properties of optical trapped particles based on the forward scattered light. Furthermore, preliminary results of an autonomous implementation in a standard experimental optical tweezers setup show similar differentiation capabilities for real-time applications, thus opening some opportunities towards technological applications such as intelligent microfluidic devices and solutions for biochemical and biophysical sensing. © Published under licence by IOP Publishing Ltd.