Towards mechanisms and standardization in extracellular vesicle and extracellular RNA studies: results of a worldwide survey

The discovery that extracellular vesicles (EVs) can transfer functional extracellular RNAs (exRNAs) between cells opened new avenues into the study of EVs in health and disease. Growing interest in EV RNAs and other forms of exRNA has given rise to research programmes including but not limited to the Extracellular RNA Communication Consortium (ERCC) of the US National Institutes of Health. In 2017, the International Society for Extracellular Vesicles (ISEV) administered a survey focusing on EVs and exRNA to canvass-related views and perceived needs of the EV research community. Here, we report the results of this survey. Overall, respondents emphasized opportunities for technical developments, unraveling of molecular mechanisms and standardization of methodologies to increase understanding of the important roles of exRNAs in the broader context of EV science. In conclusion, although exRNA biology is a relatively recent emphasis in the EV field, it has driven considerable interest and resource commitment. The ISEV community looks forward to continuing developments in the science of exRNA and EVs, but without excluding other important molecular constituents of EVs

Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores

BACKGROUND: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. RESULTS: The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 A(ROC )for the MHCBench data sets (up from 0.756), and an average of 0.96 A(ROC )for multiple alleles of the MHCPEP database. CONCLUSION: The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems

Methotrexate reduces antibody responses to recombinant human α-galactosidase A therapy in a mouse model of Fabry disease

Therapeutic enzymes are often recognized as foreign by the immune system of patients undergoing enzyme replacement therapy. The antibodies that develop may alter pharmacokinetics and biodistribution of the therapeutic protein, may be able to neutralize the activity of the enzyme, or may cause immune reactions in certain patients. We have explored treatment regimens to reduce the antibody response to human α-galactosidase A (r-hαGAL) in Fabry (αGAL knock-out) and normal BALB/c mice. A wide variety of treatment modalities were tested, including high dose tolerance induction, increased frequency of therapeutic doses and immunosuppressive drugs in combination with administration of enzyme. The most substantial effects were observed in mice injected intravenously with r-hαGAL in combination with methotrexate (MTX), which significantly lowered r-hαGAL-specific serum antibody levels. A short course of treatment with MTX was able to reduce antibody and spleen cell proliferative responses to long-term r-hαGAL treatment. MTX was able to suppress the development of r-hαGAL-specific IgG in antigen-primed mice. However, MTX was not effective in dampening robust ongoing antibody responses. These experiments provide a framework for the design of clinical protocols to prevent the drug-specific antibody responses of patients undergoing enzyme replacement therapy

Desnutrição perinatal e o controle hipotalâmico do comportamento alimentar e do metabolismo do músculo esquelético

A deficiência de nutrientes durante os períodos críticos do desenvolvimento tem sido associada com maior risco para desenvolver obesidade e diabetes Mellitus na vida adulta. Um dos mecanismos propostos refere-se à regulação do comportamento alimentar e às alterações do metabolismo energético do músculo esquelético. Recentemente, tem sido proposta a existência de uma comunicação entre o hipotálamo e o músculo esquelético a partir de sinais autonômicos que podem explicar as repercussões da desnutrição perinatal. Assim, esta revisão tem como objetivo discutir as repercussões da desnutrição perinatal sobre o comportamento alimentar e o metabolismo energético muscular e a comunicação existente entre o hipotálamo e o músculo via sinais adrenérgicos. Foram utilizadas as bases de dados MedLine/PubMed, Lilacs e Bireme, com publicações entre 2000 e 2011. Os termos de indexação utilizados foram: feeding behavior, energy metabolism, protein malnutrition, developmental plasticity, skeletal muscle e autonomic nervous system. Concluiu-se que a desnutrição perinatal pode atuar no controle hipotalâmico do comportamento alimentar e no metabolismo energético muscular, e a comunicação hipotálamo-músculo pode favorecer o desenvolvimento de obesidade e comorbidades durante o desenvolvimento