Deciphering Adipose Tissue Extracellular Vesicles Protein Cargo and Its Role in Obesity

The extracellular vesicles (EVs) have emerged as key players in metabolic disorders rising as an alternative way of paracrine/endocrine communication. In particular, in relation to adipose tissue (AT) secreted EVs, the current knowledge about its composition and function is still very limited. Nevertheless, those vesicles have been lately suggested as key players in AT communication at local level, and also with other metabolic peripheral and central organs participating in physiological homoeostasis, and also contributing to the metabolic deregulation related to obesity, diabetes, and associated comorbidities. The aim of this review is to summarize the most relevant data around the EVs secreted by adipose tissue, and especially in the context of obesity, focusing in its protein cargo. The description of the most frequent proteins identified in EVs shed by AT and its components, including their changes under pathological status, will give the reader a whole picture about the membrane/antigens, and intracellular proteins known so far, in an attempt to elucidate functional roles, and also suggesting biomarkers and new paths of therapeutic action

Expansion of different subpopulations of CD26 ?/low T cells in allergic and non-allergic asthmatics

CD26 displays variable levels between effector (TH17 >> TH1 > TH2 > Treg) and naive/memory (memory > naive) CD4(+) T lymphocytes. Besides, IL-6/IL(-)6R is associated with TH17-differentiation and asthma severity. Allergic/atopic asthma (AA) is dominated by TH2 responses, while TH17 immunity might either modulate the TH2-dependent inflammation in AA or be an important mechanism boosting non-allergic asthma (NAA). Therefore, in this work we have compared the expression of CD26 and CD126 (IL-6Ralpha) in lymphocytes from different groups of donors: allergic (AA) and non-allergic (NAA) asthma, rhinitis, and healthy subjects. For this purpose, flow cytometry, haematological/biochemical, and in vitro proliferation assays were performed. Our results show a strong CD26-CD126 correlation and an over-representation of CD26(-) subsets with a highly-differentiated effector phenotype in AA (CD4(+)CD26(-/low) T cells) and NAA (CD4(-)CD26(-) gammadelta-T cells). In addition, we found that circulating levels of CD26 (sCD26) were reduced in both AA and NAA, while loss of CD126 expression on different leukocytes correlated with higher disease severity. Finally, selective inhibition of CD26-mRNA translation led to enhanced T cell proliferation in vitro. These findings support that CD26 down-modulation could play a role in facilitating the expansion of highly-differentiated effector T cell subsets in asthma

Prognostic value of discharge heart rate in acute heart failure patients: More relevant in atrial fibrillation?

Aims: The prognostic impact of heart rate (HR) in acute heart failure (AHF) patients is not well known especially in atrial fibrillation (AF) patients. The aim of the study was to evaluate the impact of admission HR, discharge HR, HR difference (admission-discharge) in AHF patients with sinus rhythm (SR) or AF on long- term outcomes. Methods: We included 1398 patients consecutively admitted with AHF between October 2013 and December 2014 from a national multicentre, prospective registry. Logistic regression models were used to estimate the association between admission HR, discharge HR and HR difference and one- year all-cause mortality and HF readmission. Results: The mean age of the study population was 72+/-12years. Of these, 594 (42.4%) were female, 655 (77.8%) were hypertensive and 655 (46.8%) had diabetes. Among all included patients, 745 (53.2%) had sinus rhythm and 653 (46.7%) had atrial fibrillation. Only discharge HR was associated with one year all-cause mortality (Relative risk (RR)=1.182, confidence interval (CI) 95% 1.024-1.366, p=0.022) in SR. In AF patients discharge HR was associated with one year all cause mortality (RR=1.276, CI 95% 1.115-1.459, p</=0.001). We did not observe a prognostic effect of admission HR or HRD on long-term outcomes in both groups. This relationship is not dependent on left ventricular ejection fraction. Conclusions: In AHF patients lower discharge HR, neither the admission nor the difference, is associated with better long-term outcomes especially in AF patients

Improved personalized survival prediction of patients with diffuse large B-cell Lymphoma using gene expression profiling

BACKGROUND: Thirty to forty percent of patients with Diffuse Large B-cell Lymphoma (DLBCL) have an adverse clinical evolution. The increased understanding of DLBCL biology has shed light on the clinical evolution of this pathology, leading to the discovery of prognostic factors based on gene expression data, genomic rearrangements and mutational subgroups. Nevertheless, additional efforts are needed in order to enable survival predictions at the patient level. In this study we investigated new machine learning-based models of survival using transcriptomic and clinical data. METHODS: Gene expression profiling (GEP) of in 2 different publicly available retrospective DLBCL cohorts were analyzed. Cox regression and unsupervised clustering were performed in order to identify probes associated with overall survival on the largest cohort. Random forests were created to model survival using combinations of GEP data, COO classification and clinical information. Cross-validation was used to compare model results in the training set, and Harrel's concordance index (c-index) was used to assess model's predictability. Results were validated in an independent test set. RESULTS: Two hundred thirty-three and sixty-four patients were included in the training and test set, respectively. Initially we derived and validated a 4-gene expression clusterization that was independently associated with lower survival in 20% of patients. This pattern included the following genes: TNFRSF9, BIRC3, BCL2L1 and G3BP2. Thereafter, we applied machine-learning models to predict survival. A set of 102 genes was highly predictive of disease outcome, outperforming available clinical information and COO classification. The final best model integrated clinical information, COO classification, 4-gene-based clusterization and the expression levels of 50 individual genes (training set c-index, 0.8404, test set c-index, 0.7942). CONCLUSION: Our results indicate that DLBCL survival models based on the application of machine learning algorithms to gene expression and clinical data can largely outperform other important prognostic variables such as disease stage and COO. Head-to-head comparisons with other risk stratification models are needed to compare its usefulness

Wage inequality, segregation by skill and the price of capital in an assignment model

Some pieces of empirical evidence suggest that in the U.S., over the last few decades, (i) wage inequality between-plants has risen much more than wage inequality within-plants and (ii) there has been an increase in the segregation of workers by skill into separate plants. This paper presents a frictionless assignment model in which these two features can be explained simultaneously as the result of the decline in the relative price of capital. Additional implications of the model regarding the skill premium and the dispersion in labor productivity across plants are also consistent with the empirical evidence. [resumen de autor

Anti-tumour necrosis factor discontinuation in inflammatory bowel disease patients in remission: study protocol of a prospective, multicentre, randomized clinical trial

Background: Patients with inflammatory bowel disease who achieve remission with anti-tumour necrosis factor (anti-TNF) drugs may have treatment withdrawn due to safety concerns and cost considerations, but there is a lack of prospective, controlled data investigating this strategy. The primary study aim is to compare the rates of clinical remission at 1?year in patients who discontinue anti-TNF treatment versus those who continue treatment. Methods: This is an ongoing, prospective, double-blind, multicentre, randomized, placebo-controlled study in patients with Crohn?s disease or ulcerative colitis who have achieved clinical remission for ?6?months with an anti-TNF treatment and an immunosuppressant. Patients are being randomized 1:1 to discontinue anti-TNF therapy or continue therapy. Randomization stratifies patients by the type of inflammatory bowel disease and drug (infliximab versus adalimumab) at study inclusion. The primary endpoint of the study is sustained clinical remission at 1?year. Other endpoints include endoscopic and radiological activity, patient-reported outcomes (quality of life, work productivity), safety and predictive factors for relapse. The required sample size is 194 patients. In addition to the main analysis (discontinuation versus continuation), subanalyses will include stratification by type of inflammatory bowel disease, phenotype and previous treatment. Biological samples will be obtained to identify factors predictive of relapse after treatment withdrawal. Results: Enrolment began in 2016, and the study is expected to end in 2020. Conclusions: This study will contribute prospective, controlled data on outcomes and predictors of relapse in patients with inflammatory bowel disease after withdrawal of anti-TNF agents following achievement of clinical remission. Clinical trial reference number: EudraCT 2015-001410-1