Thermal and hydrolytic degradation of electrospun fish gelatin membranes

The thermal and hydrolytic degradation of electrospun gelatin membranes cross-linked with glutaraldehyde in vapor phase has been studied. In vitro degradation of gelatin membranes was evaluated in phosphate buffer saline solution at 37 ºC. After 15 days under these conditions, a weight loss of 68 % was observed, attributed to solvation and depolymerization of the main polymeric chains. Thermal degradation kinetics of the gelatin raw material and as-spun electrospun membranes showed that the electrospinning processing conditions do not influence polymer degradation. However, for cross-linked samples a decrease in the activation energy was observed, associated with the effect of glutaraldehyde cross-linking reaction in the inter- and intra-molecular hydrogen bonds of the protein. It is also shown that the electrospinning process does not affect the formation of the helical structure of gelatin chains.

An image processing application for quantification of protein aggregates in Caenorhabditis elegans

Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal mi-croscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to pro-cess, analyse and visualize the images obtained from those animals. All segmenta-tion algorithms were based on intensity pixel levels.The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggrega-tion in C. elegans. The results obtained were consistent with the levels of aggrega-tion observed in the images. In conclusion, this novel imaging processing applica-tion allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disor-ders

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Modifying fish gelatin electrospun membranes for biomedical applications: cross- linking and swelling behavior

Development of suitable membranes is a fundamental requisite for tissue and biomedical engineering applications. This work presents fish gelatin random and aligned electrospun membranes cross-linked with glutaraldehyde (GA). It was observed that the fiber average diameter and the morphology is not influenced by the GA exposure time and presents fibers with an average diameter around 250 nm. Moreover, when the gelatin mats are immersed in a phosphate buffered saline solution (PBS), they can retain as much as 12 times its initial weight of solution almost instantaneously, but the material microstructure of the fiber mats changes from the characteristic fibrous to an almost spherical porous structure. Cross-linked gelatin electrospun fiber mats and films showed a water vapor permeability of 1.37 ± 0.02 and 0.13 ± 0.10 (g.mm)/(m2.h.kPa), respectively. Finally, the processing technique and cross-linking process does not inhibit MC-3T3-E1 cell adhesion. Preliminary cell culture results showed good cell adhesion and proliferation in the cross-linked random and aligned gelatin fiber mats.