DGLinker: flexible knowledge-graph prediction of disease-gene associations

As a result of the advent of high-throughput technologies, there has been rapid progress in our understanding of the genetics underlying biological processes. However, despite such advances, the genetic landscape of human diseases has only marginally been disclosed. Exploiting the present availability of large amounts of biological and phenotypic data, we can use our current understanding of disease genetics to train machine learning models to predict novel genetic factors associated with the disease. To this end, we developed DGLinker, a webserver for the prediction of novel candidate genes for human diseases given a set of known disease genes. DGLinker has a user-friendly interface that allows non-expert users to exploit biomedical information from a wide range of biological and phenotypic databases, and/or to upload their own data, to generate a knowledge-graph and use machine learning to predict new disease-associated genes. The webserver includes tools to explore and interpret the results and generates publication-ready figures. DGLinker is available at https://dglinker.rosalind.kcl.ac.uk. The webserver is free and open to all users without the need for registration

DGLinker: flexible knowledge-graph prediction of disease-gene associations

As a result of the advent of high-throughput technologies, there has been rapid progress in our understanding of the genetics underlying biological processes. However, despite such advances, the genetic landscape of human diseases has only marginally been disclosed. Exploiting the present availability of large amounts of biological and phenotypic data, we can use our current understanding of disease genetics to train machine learning models to predict novel genetic factors associated with the disease. To this end, we developed DGLinker, a webserver for the prediction of novel candidate genes for human diseases given a set of known disease genes. DGLinker has a user-friendly interface that allows non-expert users to exploit biomedical information from a wide range of biological and phenotypic databases, and/or to upload their own data, to generate a knowledge-graph and use machine learning to predict new disease-associated genes. The webserver includes tools to explore and interpret the results and generates publication-ready figures. DGLinker is available at https://dglinker.rosalind.kcl.ac.uk. The webserver is free and open to all users without the need for registration

Cave spiders choose optimal environmental factors with respect to the generated entropy when laying their cocoon

The choice of a suitable area to spiders where to lay eggs is promoted in terms of Darwinian fitness. Despite its importance, the underlying factors behind this key decision are generally poorly understood. Here, we designed a multidisciplinary study based both on in-field data and laboratory experiments focusing on the European cave spider Meta menardi (Araneae, Tetragnathidae) and aiming at understanding the selective forces driving the female in the choice of the depositional area. Our in-field data analysis demonstrated a major role of air velocity and distance from the cave entrance within a particular cave in driving the female choice. This has been interpreted using a model based on the Entropy Generation Minimization - EGM - method, without invoking best fit parameters and thanks to independent lab experiments, thus demonstrating that the female chooses the depositional area according to minimal level of thermo-fluid-dynamic irreversibility. This methodology may pave the way to a novel approach in understanding evolutionary strategies for other living organisms

Standard versus prosocial online support groups for distressed breast cancer survivors: a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>The Internet can increase access to psychosocial care for breast cancer survivors through online support groups. This study will test a novel prosocial online group that emphasizes both opportunities for getting and giving help. Based on the helper therapy principle, it is hypothesized that the addition of structured helping opportunities and coaching on how to help others online will increase the psychological benefits of a standard online group.</p> <p>Methods/Design</p> <p>A two-armed randomized controlled trial with pretest and posttest. Non-metastatic breast cancer survivors with elevated psychological distress will be randomized to either a standard facilitated online group or to a prosocial facilitated online group, which combines online exchanges of support with structured helping opportunities (blogging, breast cancer outreach) and coaching on how best to give support to others. Validated and reliable measures will be administered to women approximately one month before and after the interventions. Self-esteem, positive affect, and sense of belonging will be tested as potential mediators of the primary outcomes of depressive/anxious symptoms and sense of purpose in life.</p> <p>Discussion</p> <p>This study will test an innovative approach to maximizing the psychological benefits of cancer online support groups. The theory-based prosocial online support group intervention model is sustainable, because it can be implemented by private non-profit or other organizations, such as cancer centers, which mostly offer face-to-face support groups with limited patient reach.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01396174">NCT01396174</a></p

Living with prostate cancer: randomised controlled trial of a multimodal supportive care intervention for men with prostate cancer

Background: Prostate cancer is the most common male cancer in developed countries and diagnosis and treatment carries with it substantial morbidity and related unmet supportive care needs. These difficulties may be amplified by physical inactivity and obesity. We propose to apply a multimodal intervention approach that targets both unmet supportive care needs and physical activity.Methods/design: A two arm randomised controlled trial will compare usual care to a multimodal supportive care intervention &ldquo;Living with Prostate Cancer&rdquo; that will combine self-management with tele-based group peer support. A series of previously validated and reliable self-report measures will be administered to men at four time points: baseline/recruitment (when men are approximately 3-6 months post-diagnosis) and at 3, 6, and 12 months after recruitment and intervention commencement. Social constraints, social support, self-efficacy, group cohesion and therapeutic alliance will be included as potential moderators/mediators of intervention effect. Primary outcomes are unmet supportive care needs and physical activity levels. Secondary outcomes are domain-specific and healthrelated quality of life (QoL); psychological distress; benefit finding; body mass index and waist circumference. Disease variables (e.g. cancer grade, stage) will be assessed through medical and cancer registry records. An economic evaluation will be conducted alongside the randomised trial.Discussion: This study will address a critical but as yet unanswered research question: to identify a populationbased way to reduce unmet supportive care needs; promote regular physical activity; and improve disease-specific and health-related QoL for prostate cancer survivors. The study will also determine the cost-effectiveness of the intervention.<br /

Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies

Motivation: Antibodies are able to recognize a wide range of antigens through their complementary determining regions formed by six hypervariable loops. Predicting the 3D structure of these loops is essential for the analysis and reengineering of novel antibodies with enhanced affinity and specificity. The canonical structure model allows high accuracy prediction for five of the loops. The third loop of the heavy chain, H3, is the hardest to predict because of its diversity in structure, length and sequence composition.Results: We describe a method, based on the Random Forest automatic learning technique, to select structural templates for H3 loops among a dataset of candidates. These can be used to predict the structure of the loop with a higher accuracy than that achieved by any of the presently available methods. The method also has the advantage of being extremely fast and returning a reliable estimate of the model quality.Availability and implementation: The source code is freely available at http://www.biocomputing.it/H3Loopred/Contact: [email protected] Information: Supplementary data are available at Bioinformatics online

International cohort study for pediatric Behçet’s Disease: update 2011

PubMe

Avascular Peripheral Retina in Infants

Avascular peripheral retina in an infant is a common characteristic of numerous pediatric retinal vascular disorders and often presents a diagnostic challenge to the clinician. In this review, key features of each disease in the differential diagnosis, from retinopathy of prematurity, familial exudative vitreoretinopathy, Coats disease, incontinentia pigmenti, Norrie disease, and persistent fetal vasculature, to other rare hematologic conditions and telomere disorders, will be discussed by expert ophthalmologists in the field

Intravitreally injected anti-VEGF antibody reduces brown fat in neonatal mice

Anti-vascular endothelial growth factor (VEGF) agents are the mainstay treatment for various angiogenesis-related retinal diseases. Currently, bevacizumab, a recombinant humanized anti-VEGF antibody, is trailed in retinopathy of prematurity, a vasoproliferative retinal disorder in premature infants. However, the risks of systemic complications after intravitreal injection of anti-VEGF antibody in infants are not well understood. In this study, we show that intravitreally injected anti-VEGF antibody is transported into the systemic circulation into the periphery where it reduces brown fat in neonatal C57BL/6 mice. A considerable amount of anti-VEGF antibody was detected in serum after intravitreal injection. Furthermore, in interscapular brown adipose tissue, we found lipid droplet accumulation, decreased VEGF levels, loss of vascular network, and decreased expression of mitochondriarelated genes, Ppargc1a and Ucp1, all of which are characteristics of "whitening" of brown fat. With increasing age and body weight, brown fat restored its morphology and vascularity. Our results show that there is a transient, but significant impact of intravitreally administered anti-VEGF antibody on brown adipose tissue in neonatal mice. We suggest that more attention should be focused on the metabolic and developmental significance of brown adipose tissue in bevacizumab treated retinopathy of prematurity infants. Copyright