A better understanding of the role of endothelium in CKD will help in the development of effective interventions for renal microcirculation improvement. This review focuses on the role of microvascular injury in CKD, the methods to detect microvessels and the novel treatments to ameliorate renal fibrosis.
  American cutaneous leishmaniasis (CL) is a neglected tropical disease typically associated with men working in remote, sylvatic environments. We sought to identify CL risk factors in a highly deforested region where anecdotal reports suggested an atypical proportion of women and children were infected with CL raising concern among authorities that transmission was shifting towards domestic spaces and population centers.
 
  We describe the characteristics of CL patients from four participating clinics after digitizing up to 10 years of patient data from each clinic's CL registries. We assessed risk factors of CL associated with intradomestic, peridomestic, or non-domestic transmission through a matched case-control study with 63 patients who had visited these same clinics for CL (cases) or other medical reasons (controls) between January 2014 and August 2016. The study consisted of an in-home interview of participants by a trained field worker using a standard questionnaire. Risk factors were identified usinge demographic information obtained from clinic-based data to understand basic epidemiological trends of vector-borne infections.
 Women and children may be underappreciated as CL risk groups in agriculturally dependent regions. Despite the age-sex breakdown of clinical CL patients and high rates of deforestation occurring in the study area, transmission is mostly occurring outside of the largest population centers. Curbing transmission in non-domestic spaces may be limited to decreasing exposure to sandflies during the evening, nighttime, and early morning hours. Our paper serves as a cautionary tale for those relying solely on the demographic information obtained from clinic-based data to understand basic epidemiological trends of vector-borne infections.
  Cognitive behavioural therapy (CBT) is the most widely recognised and efficacious psychological therapy for the treatment of anxiety disorders in children and adults. However, suboptimal remission rates indicate room for improvement in treatments, particularly when both children and their parents have anxiety disorders. Bidirectional transmission and maintenance of anxiety within parent-child dyads could be better targeted by CBT, to improve treatment outcomes for children and parents with anxiety disorders. This study aimed to develop and evaluate the feasibility and acceptability of a concurrent parent-child enhanced CBT intervention that targets the individual's anxiety disorder(s), as well as the bidirectional factors that influence and maintain anxiety in the dyad.
 
  Feasibility and acceptability of the proposed CBT protocol will be evaluated in an open-label pilot trial of the intervention utilising qualitative and quantitative data collection. Ten parent-child dyad participants (n = 20) with anxiety (n = 10). Acceptability measures will include prospective and retrospective quantitative self-report and qualitative interview data.
 
  This pilot trial will utilise a mixed-methods design to determine the feasibility and acceptability of delivering an enhanced CBT intervention for the concurrent treatment of parent-child dyads with anxiety disorders. The results of this trial will inform the development and implementation of a future definitive randomised clinical trial to evaluate intervention efficacy.
 
  Australian and New Zealand Clinical Trials Registry, ANZCTR1261900033410 . Prospectively registered pre-results. Registered 04 March 2019.
 Australian and New Zealand Clinical Trials Registry, ANZCTR1261900033410 . Prospectively registered pre-results. Registered 04 March 2019.
  There are clearly sex differences in cardiovascular disease. On average, women experience cardiovascular events at an older age, and at any age, women, on average, have less atherosclerotic plaque than men. The role of the human intestinal microbiome in health and disease has garnered significant interest in recent years, and there have been indications of sex differences in the intestinal microbiome. The purpose of this narrative review was to evaluate evidence of sex differences in the interaction between the intestinal microbiome and risk factors for cardiovascular disease. Several studies have demonstrated changes in microbiota composition and metabolic profile as a function of diet, sex hormones, and host metabolism, among other factors. This dysbiosis has consequently been associated with several disease states, including atherosclerosis and cardiovascular disease.  https://www.selleckchem.com/products/ly2157299.html  In this respect, there is a growing appreciation for the microbiota and its secreted metabolites, including trimethylamine N-oxide (TMAO),ion to traditional vascular risk factors. In this context, circulating SCFAs and TMAO are recognized as key metabolites of the intestinal microbiome that can be readily measured in the blood for the evaluation of metabolic profile.
 
  Novel strategies focused on resolving intestinal dysbiosis as a means to slow progression of atherosclerosis and reduce the risk of cardiovascular disease should be evaluated through a lens of sex differences.
 Novel strategies focused on resolving intestinal dysbiosis as a means to slow progression of atherosclerosis and reduce the risk of cardiovascular disease should be evaluated through a lens of sex differences.
  Named Entity Recognition is a common task in Natural Language Processing applications, whose purpose is to recognize named entities in textual documents. Several systems exist to solve this task in the biomedical domain, based on Natural Language Processing techniques and Machine Learning algorithms. A crucial step of these applications is the choice of the representation which describes data. Several representations have been proposed in the literature, some of which are based on a strong knowledge of the domain, and they consist of features manually defined by domain experts. Usually, these representations describe the problem well, but they require a lot of human effort and annotated data. On the other hand, general-purpose representations like word-embeddings do not require human domain knowledge, but they could be too general for a specific task.
 
  This paper investigates methods to learn the best representation from data directly, by combining several knowledge-based representations and word embeddings.