Project description:Kidney disease patients have a high prevalence of cardiovascular morbidity and mortality. It can be challenging to adequately assess their cardiovascular status based on physical examination alone. Cardiac ultrasound has proven to be a powerful tool to accomplish this objective and is increasingly being adopted by noncardiologists to augment their skills and expedite clinical decision-making. With the advent of inexpensive and portable ultrasound equipment, simplified protocols, and focused training, it is becoming easier to master basic cardiac ultrasound techniques. After a short course of training in focused cardiac ultrasound, nephrologists can quickly and reliably assess ventricular size and function, detect clinically relevant pericardial effusion and volume status in their patients. Additional training in Doppler ultrasound can extend their capability to measure cardiac output, right ventricular systolic pressure, and diastolic dysfunction. This information can be instrumental in effectively managing patients in inpatient, office, and dialysis unit settings. The purpose of this review is to highlight the importance and feasibility of incorporating cardiac ultrasound in nephrology practice, discuss the principles of basic and Doppler ultrasound modalities and their clinical utility from a nephrologist's perspective.
Project description:People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. We study whether and how the ability to make or break links in social networks fosters cooperate, paying particular attention to whether information on an individual's actions is freely available to potential partners. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's references, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential partners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in fluid networks.
Project description:Understanding others' feelings, intentions, and beliefs is a crucial social skill both for our personal lives and for meeting the challenges of a globalized world. Recent evidence suggests that the ability to represent and infer others' mental states (Theory of Mind, ToM) can be enhanced by mental training in healthy adults. The present study investigated the role of training-induced understanding of oneself for the enhanced understanding of others. In a large-scale longitudinal study, two independent participant samples (N = 80 and N = 81) received a 3-month contemplative training. This training focused on perspective taking and was inspired by the Internal Family Systems model that conceives the self as being composed of a complex system of inner personality aspects. Specifically, participants practiced perspective taking on their own inner states by learning to identify and classify different inner personality parts. Results revealed that the degree to which participants improved their understanding of themselves-reflected in the number of different inner parts they could identify-predicted their improvements in high-level ToM performance over training. Especially the number of identified parts that were negatively valenced showed a strong relation with enhanced ToM capacities. This finding suggests a close link between getting better in understanding oneself and improvement in social intelligence.
Project description:Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.
Project description:Proteins encoded by newly-emerged genes ('orphan genes') share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene prediction pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes, 99% of ancient genes, and give the highest sensitivity score regardless dataset in Arabidopsis. We provide a light weight, flexible, reproducible, and well-documented solution to improve gene prediction.
Project description:Lizards represent unique model organisms in the study of sex determination and sex chromosome evolution. Among tetrapods, they are characterized by an unparalleled diversity of sex determination systems, including temperature-dependent sex determination (TSD) and genetic sex determination (GSD) under either male or female heterogamety. Sex chromosome systems are also extremely variable in lizards. They include simple (XY and ZW) and multiple (X1X2Y and Z1Z2W) sex chromosome systems and encompass all the different hypothesized stages of diversification of heterogametic chromosomes, from homomorphic to heteromorphic and completely heterochromatic sex chromosomes. The co-occurrence of TSD, GSD and different sex chromosome systems also characterizes different lizard taxa, which represent ideal models to study the emergence and the evolutionary drivers of sex reversal and sex chromosome turnover. In this review, we present a synthesis of general genome and karyotype features of non-snakes squamates and discuss the main theories and evidences on the evolution and diversification of their different sex determination and sex chromosome systems. We here provide a systematic assessment of the available data on lizard sex chromosome systems and an overview of the main cytogenetic and molecular methods used for their identification, using a qualitative and quantitative approach.
Project description:BackgroundPersonas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients.ObjectiveTo develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data.MethodData were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables.ResultsSix clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers.DiscussionPersonas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed.
Project description:Genomes and transcriptomes of non-model organisms can be analyzed using next-generation sequencing technologies, but de-novo sequencing and annotating a full eukaryotic genome is still challenging. So, -omics experimentation with non-model organisms requires a suite of technologies to obtain reliable results in a cost-effective manner. Here, a novel method for microarray-based genome analysis is presented which is especially suitable for non-model organisms. We show that it is useful for complementing regular aCGH analyses and for evaluating transcriptome next-generation sequencing reads. The principle of the method is straightforward: feature intensities obtained after hybridizing the test genome are compared with the feature intensities of a control hybridization. The control hybridization is performed with negative control probes (no targets in the control sample), and with positive control probes (with targets in the control sample). The method has in principle a resolution of a single probe and it does not depend on the structural information of a reference genome: the genomic ordering of probe targets is irrelevant. In a test, analyzing the genome content of a sequenced bacterial strain: Staphylococcus aureus MRSA252, this approach proved to be successful demonstrated by receiver operating characteristic area under the curve values larger than 0.9995. DNA from eleven Staphylococcus aureus strains was extracted in three replicates, fragmented, and hybridized onto the S. aureus multistrain microarray. DNA from MRSA252 was used as common reference, but this channel was omitted in further analyses.