Mathematical modeling of the proliferation gradient in multicellular tumor spheroids.

MultiCellular Tumor Spheroids are 3D cell cultures that can accurately reproduce the behavior of solid tumors. It has been experimentally observed that large spheroids exhibit a decreasing gradient of proliferation from the periphery to the center of these multicellular 3D models: the proportion of proliferating cells is higher in the periphery while the non-proliferating quiescent cells increase in depth. In this paper, we propose to investigate the key mechanisms involved in the establishment of this gradient with a Partial Differential Equations model that mimics the experimental set-up of growing spheroids under different nutrients supply conditions. The model consists of mass balance equations on the two cell populations observed in the data: the proliferating cells and the quiescent cells. The spherical symmetry is used to rewrite the model in radial and relative coordinates. Thanks to a rigorous data postprocessing the model is then fit and compared quantitatively with the experimental quantification of the percentage of proliferating cells from EdU immunodetection on 2D spheroid cryosection images. The results of this calibration show that the proliferation gradient observed in spheroids can be quantitatively reproduced by our model.

3D imaging of cleared human skin biopsies using light-sheet microscopy: A new way to visualize in-depth skin structure.

BACKGROUND: Human skin is composed of the superimposition of tissue layers of various thicknesses and components. Histological staining of skin sections is the benchmark approach to analyse the organization and integrity of human skin biopsies; however, this approach does not allow 3D tissue visualization. Alternatively, confocal or two-photon microscopy is an effective approach to perform fluorescent-based 3D imaging. However, owing to light scattering, these methods display limited light penetration in depth. The objectives of this study were therefore to combine optical clearing and light-sheet fluorescence microscopy (LSFM) to perform in-depth optical sectioning of 5 mm-thick human skin biopsies and generate 3D images of entire human skin biopsies. MATERIALS AND METHODS: A benzyl alcohol and benzyl benzoate solution was used to successfully optically clear entire formalin fixed human skin biopsies, making them transparent. In-depth optical sectioning was performed with LSFM on the basis of tissue-autofluorescence observations. 3D image analysis of optical sections generated with LSFM was performed by using the Amira® software. RESULTS: This new approach allowed us to observe in situ the different layers and compartments of human skin, such as the stratum corneum, the dermis and epidermal appendages. With this approach, we easily performed 3D reconstruction to visualise an entire human skin biopsy. Finally, we demonstrated that this method is useful to visualise and quantify histological anomalies, such as epidermal hyperplasia. CONCLUSION: The combination of optical clearing and LSFM has new applications in dermatology and dermatological research by allowing 3D visualization and analysis of whole human skin biopsies.

Alternating direction method of multipliers applied to 3D light sheet fluorescence microscopy image deblurring using GPU hardware.

This paper focuses on the deblurring and denoising of Poisson noise contaminated images acquired with a new imaging technique producing large 3D data sets: Light Sheet Fluorescence Microscopy. This paper details the optimization algorithm used, which is based on the Alternating Direction Method of Multipliers, and its efficient implementation using GPU hardware. In practice, a 3D 100 million voxel image is deconvolved in five minutes, which is at least 25 times faster than a state-of-the-art MATLAB implementation.

A muscle transcriptome analysis identifies positional candidate genes for a complex trait in pig.

Muscle tenderness is an important complex trait for meat quality and thus for genetic improvement through animal breeding. However, the physiological or genetic control of tenderness development in muscle is still poorly understood. In this work, using transcriptome analysis, we found a relationship between gene expression variability and tenderness. Muscle (longissimus dorsi) samples from 30 F(2) pigs were characterized by Warner-Bratzler Shear Force (WBSF) on cooked meat as a measurement of muscle tenderness. Gene expression levels were measured using microarrays for 17 muscle samples selected to represent a range of WBSF values. Using a linear regression model, we determined that samples with WBSF values above 30 N could be effectively analysed for genes exhibiting a significant association of their expression level on shear force (false discovery rate <0.05). These genes were shown to be involved in three functional networks: cell cycle, energy metabolism and muscle development. Twenty-two genes were mapped on the pig genome and 12 were found to be located in regions previously reported to contain quantitative trait loci (QTL) affecting pig meat tenderness (chromosomes 2, 6 and 13). Some genes appear therefore as positional candidate genes for QTL.