Balancing the immune response in the brain: IL-10 and its regulation

Background: The inflammatory response is critical to fight insults, such as pathogen invasion or tissue damage, but if not resolved often becomes detrimental to the host. A growing body of evidence places non-resolved inflammation at the core of various pathologies, from cancer to neurodegenerative diseases. It is therefore not surprising that the immune system has evolved several regulatory mechanisms to achieve maximum protection in the absence of pathology. Main body: The production of the anti-inflammatory cytokine interleukin (IL)-10 is one of the most important mechanisms evolved by many immune cells to counteract damage driven by excessive inflammation. Innate immune cells of the central nervous system, notably microglia, are no exception and produce IL-10 downstream of pattern recognition receptors activation. However, whereas the molecular mechanisms regulating IL-10 expression by innate and acquired immune cells of the periphery have been extensively addressed, our knowledge on the modulation of IL-10 expression by central nervous cells is much scattered. This review addresses the current understanding on the molecular mechanisms regulating IL-10 expression by innate immune cells of the brain and the implications of IL-10 modulation in neurodegenerative disorders. Conclusion: The regulation of IL-10 production by central nervous cells remains a challenging field. Answering the many remaining outstanding questions will contribute to the design of targeted approaches aiming at controlling deleterious inflammation in the brain.We acknowledge the Portuguese Foundation for Science and Technology (FCT) for providing a PhD grant to DLS (SFRH/BD/88081/2012) and a post-doctoral fellowship to SR (SFRH/BPD/72710/2010). DS, AGC and SR were funded by FEDER through the Competitiveness Factors Operational Programme (COMPETE) and National Funds through FCT under the scope of the project POCI-01-0145-FEDER007038; and by the project NORTE-01-0145-FEDER-000013, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). The MS lab was financed by Fundo Europeu de Desenvolvimento Regional (FEDER) funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT in the framework of the project “Institute for Research and Innovation in Health Sciences ” (POCI-01-0145-FEDER-007274). MS is a FCT Associate Investigator. The funding body had no role in the design of the study and collection, analysis, and interpretation of the data and in writing the manuscript

Adopting a high-polyphenolic diet is associated with an improved glucose profile: prospective analysis within the PREDIMED-plus trial

Previous studies suggested that dietary polyphenols could reduce the incidence and complications of type-2 diabetes (T2D); although the evidence is still limited and inconsistent. This work analyzes whether changing to a diet with a higher polyphenolic content is associated with an improved glucose profile. At baseline, and at 1 year of follow-up visits, 5921 participants (mean age 65.0 ± 4.9, 48.2% women) who had overweight/obesity and metabolic syndrome filled out a validated 143-item semi-quantitative food frequency questionnaire (FFQ), from which polyphenol intakes were calculated. Energy-adjusted total polyphenols and subclasses were categorized in tertiles of changes. Linear mixed-effect models with random intercepts (the recruitment centers) were used to assess associations between changes in polyphenol subclasses intake and 1-year plasma glucose or glycosylated hemoglobin (HbA1c) levels. Increments in total polyphenol intake and some classes were inversely associated with better glucose levels and HbA1c after one year of follow-up. These associations were modified when the analyses were run considering diabetes status separately. To our knowledge, this is the first study to assess the relationship between changes in the intake of all polyphenolic groups and T2D-related parameters in a senior population with T2D or at high-risk of developing T2D

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified