Study of tensiometric properties,microbiological and collagen content in nile tilapia skin submitted to different sterilization methods

Tissue bioengineering development is a global concern and different materials are studied and created to be safe, effective and with low cost. Nile Tilapia skin had shown its biological potential as covers for the burn wound. This study evaluates the tilapia skin histological, collagen properties and tensiometric resistance, after treatment by different sterilization methods. Tilapia skin samples were submitted to two sterilization processes: (1) chemical, which consisted in two 2% chlorhexidin baths, followed by sequential baths in increasing glycerol concentrations; and (2) radiation, when glycerolized skin samples were submitted to gamma radiation at 25, 30 and 50 kGy. Microscopic analyzes were performed through Haematoxylin–eosin and Picrosirius Red under polarized light. For tensiometric analysis, traction tests were performed. Glycerol treated skin presented a discrete collagen fibers disorganization within the deep dermis, while irradiated skin did not show any additional change. Throughout the steps of chemical sterilization, there was a higher proportion of collagen with red/yellow birefringence (type I) in the skin samples up to the first bath in chlorhexidin, when compared to samples after the first two glycerol baths (P < 0.005). However, there was no difference in relation to total collagen between groups. In irradiated skin, there was a larger total collagen preservation when using until 30 kGy (P < 0.005). Tensiometric evaluation did not show significant differences in relation to maximum load in the groups studied. We concluded that chemical and radiation (25 and 30 kGy) are efficient methods to sterilize Nile Tilapia skin without altering its microscopic or tensiometric characteristics.     

Cookie‐cutter shark Isistius spp. predation upon different tuna species from the south‐western Atlantic Ocean

The predation of cookie‐cutter sharks Isistius spp. upon the early life stages of yellowfin tuna Thunnus albacares, skipjack tuna Katsuwonus pelamis and little tunny Euthynnus alletteratus are described. New evidence suggesting a connection between commercial fishing and predation by Isistius sp. is presented, with these sharks biting tunas hooked in surface waters during daylight. The healing patterns of the wounds made by the sharks are described in detail and, although such damage is known to negatively influence market price elsewhere, it is not the case on the south‐east Brazilian coast.     

Efficacy of different interaction devices using non-immersive virtual tasks in individuals with Amyotrophic Lateral Sclerosis: a cross-sectional randomized trial

Background

Amyotrophic Lateral Sclerosis (ALS) is a rapid progressive neurodegenerative disease, characterized by a selective loss of motor neurons, brain stem and spinal cord which leads to deterioration of motor abilities. Devices that promote interaction with tasks on computers can enhance performance and lead to greater independence and utilization of technology.

Objective

To evaluate performance on a computer task in individuals with ALS using three different commonly used non-immersive devices.

Method

Thirty individuals with ALS (18 men and 12 women, mean age 59?years, range 44–74?years) with a mean score of 26, (minimum score of 14 and maximum 41) on the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) and 30 healthy controls matched for age and gender, participated. All participants were randomly divided into three groups, each using a different device system (motion tracking, finger motion control or touchscreen) to perform three task phases (acquisition, retention and transfer).

Results

Both the ALS and control group (CG) showed better performance on the computer task when using the touchscreen device, but there was limited transfer of performance onto the task performed on the Finger Motion control or motion tracking. However, we found that using the motion tracking device led to transfer of performance to the touchscreen.

Conclusion

This study presents novel and important findings when selecting interaction devices for individuals with ALS to access technology by demonstrating immediate performance benefits of using a touchscreen device, such as improvement of motor skills. There were possible transferable skills obtained when using virtual systems which may allow flexibility and enable individuals to maintain performance overtime.

Trial registration

Registration name: Virtual Task in Amyotrophic Lateral Sclerosis; Registration number: NCT03113630; retrospectively registered on 04/13/2017. Date of enrolment of the first participant to the trial: 02/02/2016.

     

A near-tetrapod from the Baltic Middle Devonian

The tetrapodomorph sarcopterygian Livoniana multidentata gen. et sp. nov. is described on the basis of lower jaw fragments from the Middle Devonian(late Givetian) of Latvia and Estonia. It possesses a suite of derived characters previously only known from tetrapods, which first appear in the late Devonian (late Frasnian), and a phylogenetic analysis places it on the internode between Panderichthys and the base of the Tetrapoda. The analysis also reveals that the 'Elpistostegalia' are paraphyletic to Tetrapoda, with Elpistostege closer to tetrapods than is Panderichthys. Owing to incompleteness of the material, there is almost no overlap between the data sets for Elpistostege Livoniana ; the analysis places the two genera in an unresolved trichotomy. In addition to the tetrapod features, Livoniana has a strikingly autapomorphic dentary dentition comprising multiple tooth rows. It thus provides evidence both for the unexpectedly early evolution of tetrapod characteristics and for morphological radiation around the fish-tetrapod transition.     

Combinatorial Approach for Large-scale Identification of Linked Peptides from Tandem Mass Spectrometry Spectra

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein–protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides.The study of protein–protein interactions is crucial to understanding how cellular systems function because proteins act in concert through a highly organized set of interactions. Most cellular processes are carried out by large macromolecular assemblies and regulated through complex cascades of transient protein–protein interactions (1). In the past several years numerous high-throughput studies have pioneered the systematic characterization of protein–protein interactions in model organisms (2–4). Such studies mainly utilize two techniques: the yeast two-hybrid system, which aims at identifying binary interactions (5), and affinity purification combined with tandem mass spectrometry analysis for the identification of multi-protein assemblies (6–8). Together these led to a rapid expansion of known protein–protein interactions in human and other model organisms. Patche and Aloy recently estimated that there are more than one million interactions catalogued to date (9).But despite rapid progress, most current techniques allow one to determine only whether proteins interact, which is only the first step toward understanding how proteins interact. A more complete picture comes from characterizing the three-dimensional structures of protein complexes, which provide mechanistic insights that govern how interactions occur and the high specificity observed inside the cell. Traditionally the gold-standard methods used to solve protein structures are x-ray crystallography and NMR, and there have been several efforts similar to structural genomics (10) aiming to comprehensively solve the structures of protein complexes (11, 12). Although there has been accelerated growth of structures for protein monomers in the Protein Data Bank in recent years (11), the growth of structures for protein complexes has remained relatively small (9). Many factors, including their large size, transient nature, and dynamics of interactions, have prevented many complexes from being solved via traditional approaches in structural biology. Thus, the development of complementary analytical techniques with which to probe the structure of large protein complexes continues to evolve (13–18).Recent developments have advanced the analysis of protein structures and interaction by combining cross-linking and tandem mass spectrometry (17, 19–24). The basic idea behind this technique is to capture and identify pairs of amino acid residues that are spatially close to each other. When these linked pairs of residues are from the same protein (intraprotein cross-links), they provide distance constraints that help one infer the possible conformations of protein structures. Conversely, when pairs of residues come from different proteins (interprotein cross-links), they provide information about how proteins interact with one another. Although cross-linking strategies date back almost a decade (25, 26), difficulty in analyzing the complex MS/MS spectrum generated from linked peptides made this approach challenging, and therefore it was not widely used. With recent advances in mass spectrometry instrumentation, there has been renewed interest in employing this strategy to determine protein structures and identify protein–protein interactions. However, most studies thus far have been focused on purified protein complexes. With today''s mass spectrometers being capable of analyzing tens of thousands of spectra in a single experiment, it is now potentially feasible to extend this approach to the analysis of complex biological samples. Researchers have tried to realize this goal using both experimental and computational approaches. Indeed, a plethora of chemical cross-linking reagents are now available for stabilizing these complexes, and some are designed to allow for easier peptide identification when employed in concert with MS analysis (20, 27, 28). There have also been several recent efforts to develop computational methods for the automatic identification of linked peptides from MS/MS spectra (29–36). However, because of the lack of large annotated training data, most approaches to date either borrow fragmentation models learned from unlinked, linear peptides or learn the fragmentation statistics from training data of limited size (30, 37), which might not generalize well across different samples. In some cases it is possible to generate relatively large training data, but it is often very labor intensive and involves hundreds of separate LC-MS/MS runs (36). Here, employing disulfide-bridged peptides as an example, we propose a novel method that uses a combinatorial peptide library to (a) efficiently generate a large mass spectral reference dataset for linked peptides and (b) use these data to automatically train our new algorithm, MXDB, which can efficiently and accurately identify linked peptides from MS/MS spectra.     

Regulatory CD4 T cells control the size of the peripheral activated/memory CD4 T cell compartment

The mechanisms leading to stable T cell numbers in the periphery of a healthy animal are, to date, not well understood. We followed the expansion of CD45RBhigh (naive) and CD45RBlow (activated/memory) CD4 T cells transferred from normal mice into syngeneic Rag-20/0 recipients and the dynamics of peripheral reconstitution when both populations were coinjected. Naive cells acquired an activated phenotype and showed a high proliferative capacity that was dependent on the environment in which the recipients were kept (specific pathogen-free vs conventional housing conditions), the age of the recipients, and the presence of CD45RBlow T cells in the injected cohort. CD45RBlow CD4 T cells protected the host from CD45RBhigh CD4 T cell-induced inflammatory bowel disease and showed a limited degree of expansion. CD45RBlow CD4 T cells isolated from GF mice also showed the ability to prevent inflammatory bowel disease, indicating that at least part of the natural regulatory T cells are self-reactive. The results indicate that 1) peripheral T cell expansion in lymphocyte-deficient recipients represent classical immune responses, which are mainly promoted by exogenous Ags and 2) natural regulatory T cells control the size of the activated/memory peripheral CD4 T cell compartment.