Impact of the 2016 ASE/EACVI recommendations on the prevalence of diastolic dysfunction in the general population

Aims: Diastolic dysfunction (DD) is frequent in the general population; however, the assessment of diastolic function remains challenging. We aimed to evaluate the impact of the recent 2016 American Society of Echocardiography (ASE)/European Association of Cardiovascular Imaging (EACVI) recommendations in the prevalence and grades of DD compared with the 2009 guidelines and the Canberra Study Criteria (CSC). Methods and results: Within a population-based cohort, a total of 1000 individuals, aged ≥45 years, were evaluated retrospectively. Patients with previously known cardiac disease or ejection fraction <50% were excluded. Diastolic function was assessed by transthoracic echocardiography. DD prevalence and grades were determined according to the three classifications. The mean age was 62.0 ± 10.5 years and 37% were men. The prevalence of DD was 1.4% (n = 14) with the 2016 recommendations, 38.1% (n = 381) with the 2009 recommendations, and 30.4% (n = 304) using the CSC. The concordance between the updated recommendations and the other two was poor (from k = 0.13 to k = 0.18, P < 0.001). Regarding the categorization in DD grades, none of the 14 individuals with DD by the 2016 guidelines were assigned to Grade 1 DD, 64% were classified as Grade 2, 7% had Grade 3, and 29% had indeterminate grade. Conclusion: The application of the new 2016 ASE/EACVI recommendations resulted in a much lower prevalence of DD. The concordance between the classifications was poor. The updated algorithm seems to be able to diagnose only the most advanced cases

Identification of a fibrinogen-related protein (FBN9) gene in neotropical anopheline mosquitoes

<p>Abstract</p> <p>Background</p> <p>Malaria has a devastating impact on worldwide public health in many tropical areas. Studies on vector immunity are important for the overall understanding of the parasite-vector interaction and for the design of novel strategies to control malaria. A member of the fibrinogen-related protein family, <it>fbn9</it>, has been well studied in <it>Anopheles gambiae </it>and has been shown to be an important component of the mosquito immune system. However, little is known about this gene in neotropical anopheline species.</p> <p>Methods</p> <p>This article describes the identification and characterization of the <it>fbn9 </it>gene partial sequences from four species of neotropical anopheline primary and secondary vectors: <it>Anopheles darlingi, Anopheles nuneztovari, Anopheles aquasalis</it>, and <it>Anopheles albitarsis </it>(namely <it>Anopheles marajoara</it>). Degenerate primers were designed based on comparative analysis of publicly available <it>Aedes aegypti </it>and <it>An. gambiae </it>gene sequences and used to clone putative homologs in the neotropical species. Sequence comparisons and Bayesian phylogenetic analyses were then performed to better understand the molecular diversity of this gene in evolutionary distant anopheline species, belonging to different subgenera.</p> <p>Results</p> <p>Comparisons of the <it>fbn9 </it>gene sequences of the neotropical anophelines and their homologs in the <it>An. gambiae </it>complex (Gambiae complex) showed high conservation at the nucleotide and amino acid levels, although some sites show significant differentiation (non-synonymous substitutions). Furthermore, phylogenetic analysis of <it>fbn9 </it>nucleotide sequences showed that neotropical anophelines and African mosquitoes form two well-supported clades, mirroring their separation into two different subgenera.</p> <p>Conclusions</p> <p>The present work adds new insights into the conserved role of <it>fbn9 </it>in insect immunity in a broader range of anopheline species and reinforces the possibility of manipulating mosquito immunity to design novel pathogen control strategies.</p

Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes