Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy.

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field.AIMS/HYPOTHESIS: The aim of this study was to reduce the frequency of diabetic eye-screening visits, while maintaining safety, by using information technology and individualised risk assessment to determine screening intervals. METHODS: A mathematical algorithm was created based on epidemiological data on risk factors for diabetic retinopathy. Through a website, www.risk.is , the algorithm receives clinical data, including type and duration of diabetes, HbA(1c) or mean blood glucose, blood pressure and the presence and grade of retinopathy. These data are used to calculate risk for sight-threatening retinopathy for each individual's worse eye over time. A risk margin is defined and the algorithm recommends the screening interval for each patient with standardised risk of developing sight-threatening retinopathy (STR) within the screening interval. We set the risk margin so that the same number of patients develop STR within the screening interval with either fixed annual screening or our individualised screening system. The database for diabetic retinopathy at the Department of Ophthalmology, Aarhus University Hospital, Denmark, was used to empirically test the efficacy of the algorithm. Clinical data exist for 5,199 patients for 20 years and this allows testing of the algorithm in a prospective manner. RESULTS: In the Danish diabetes database, the algorithm recommends screening intervals ranging from 6 to 60 months with a mean of 29 months. This is 59% fewer visits than with fixed annual screening. This amounts to 41 annual visits per 100 patients. CONCLUSION: Information technology based on epidemiological data may facilitate individualised determination of screening intervals for diabetic eye disease. Empirical testing suggests that this approach may be less expensive than conventional annual screening, while not compromising safety. The algorithm determines individual risk and the screening interval is individually determined based on each person's risk profile. The algorithm has potential to save on healthcare resources and patients' working hours by reducing the number of screening visits for an ever increasing number of diabetic patients in the world

Case Report: Successful Implementation of Integrative Cognitive Remediation for Early Psychosis.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadMany individuals demonstrate functionally relevant impairment in neurocognition as well as social cognition early on in the course of their psychotic disorder. There is robust evidence supporting cognitive remediation as an effective treatment of cognitive dysfunction in schizophrenia. Increasingly it is accepted that earlier treatment is associated with better outcome and that it is important to systematically assess and treat cognitive dysfunction before the cognitive and functional disabilities are fully realized. However, the clinical availability of these interventions remains sparse. As we move forward with implementing evidence-based interventions into multi-component treatment for early psychosis, it is important to reflect on experience as well as evidence. This case report aims to describe the implementation of an integrative cognitive remediation program in coordinated specialty care (CSC) for early psychosis in Iceland and investigate whether the intervention is sustainable in a CSC setting. Data on the number of patients treated, facilitators trained, groups conducted, and funding was used to assess the sustainability. The results show that since initial implementation in 2016, the intervention has been routinely available as part of standard care, with over 100 patients having received the treatment. The report discusses key factors in the successful implementation of the program. Keywords: compensatory cognitive training; functional outcome; rehabilitation; schizophrenia; social cognition and interaction training.Research Fund Landspitali-The National University Hospital of Iceland 2017/2018 University of Icelan

A Novel Adaptive Method for the Analysis of Next-Generation Sequencing Data to Detect Complex Trait Associations with Rare Variants Due to Gene Main Effects and Interactions

There is solid evidence that rare variants contribute to complex disease etiology. Next-generation sequencing technologies make it possible to uncover rare variants within candidate genes, exomes, and genomes. Working in a novel framework, the kernel-based adaptive cluster (KBAC) was developed to perform powerful gene/locus based rare variant association testing. The KBAC combines variant classification and association testing in a coherent framework. Covariates can also be incorporated in the analysis to control for potential confounders including age, sex, and population substructure. To evaluate the power of KBAC: 1) variant data was simulated using rigorous population genetic models for both Europeans and Africans, with parameters estimated from sequence data, and 2) phenotypes were generated using models motivated by complex diseases including breast cancer and Hirschsprung's disease. It is demonstrated that the KBAC has superior power compared to other rare variant analysis methods, such as the combined multivariate and collapsing and weight sum statistic. In the presence of variant misclassification and gene interaction, association testing using KBAC is particularly advantageous. The KBAC method was also applied to test for associations, using sequence data from the Dallas Heart Study, between energy metabolism traits and rare variants in ANGPTL 3,4,5 and 6 genes. A number of novel associations were identified, including the associations of high density lipoprotein and very low density lipoprotein with ANGPTL4. The KBAC method is implemented in a user-friendly R package

Flexible mapping of homology onto structure with Homolmapper

<p>Abstract</p> <p>Background</p> <p>Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.</p> <p>Results</p> <p>We describe homolmapper, a command-line application for mapping information from a multiple protein sequence alignment onto a protein structure for analysis in the viewing software of the user's choice. Homolmapper is small (under 250 K for the application itself) and is written in Python to ensure portability. It is released for non-commercial use under a modified University of California BSD license. Homolmapper permits facile import of additional scoring schemes and can incorporate arbitrary additional amino acids to allow handling of residues such as selenocysteine or pyrrolysine. Homolmapper also provides tools for defining and analyzing subfamilies relative to a larger alignment, for mutual information analysis, and for rapidly visualizing the locations of mutations and multi-residue motifs.</p> <p>Conclusion</p> <p>Homolmapper is a useful tool for analysis of homology relationships among proteins in a structural context. There is also extensive, example-driven documentation available. More information about homolmapper is available at <url>http://www.mcb.ucdavis.edu/faculty-labs/lagarias/homolmapper_home/homolmapper%20web%20page.htm</url>.</p

A Genome-Scale DNA Repair RNAi Screen Identifies SPG48 as a Novel Gene Associated with Hereditary Spastic Paraplegia

We have identified a novel gene in a genome-wide, double-strand break DNA repair RNAi screen and show that is involved in the neurological disease hereditary spastic paraplegia

Two Host Factors Regulate Persistence of H7a-Specific T Cells Injected in Tumor-Bearing Mice

BACKGROUND: Injection of CD8 T cells primed against immunodominant minor histocompatibility antigens (MiHA) such as H7(a) can eradicate leukemia and solid tumors. To understand why MiHA-targeted T cells have such a potent antitumor effect it is essential to evaluate their in vivo behavior. In the present work, we therefore addressed two specific questions: what is the proliferative dynamics of H7(a)-specifc T cells in tumors, and do H7(a)-specific T cells persist long-term after adoptive transfer? METHODOLOGY/PRINCIPAL FINDINGS: By day 3 after adoptive transfer, we observed a selective infiltration of melanomas by anti-H7(a) T cells. Over the next five days, anti-H7(a) T cells expanded massively in the tumor but not in the spleen. Thus, by day 8 after injection, anti-H7(a) T cells in the tumor had undergone more cell divisions than those in the spleen. These data strongly suggest that anti-H7(a) T cells proliferate preferentially and extensively in the tumors. We also found that two host factors regulated long-term persistence of anti-H7(a) memory T cells: thymic function and expression of H7(a) by host cells. On day 100, anti-H7(a) memory T cells were abundant in euthymic H7(a)-negative (B10.H7(b)) mice, present in low numbers in thymectomized H7(a)-positive (B10) hosts, and undetectable in euthymic H7(a)-positive recipients. CONCLUSIONS/SIGNIFICANCE: Although in general the tumor environment is not propitious to T-cell invasion and expansion, the present work shows that this limitation may be overcome by adoptive transfer of primed CD8 T cells targeted to an immunodominant MiHA (here H7(a)). At least in some cases, prolonged persistence of adoptively transferred T cells may be valuable for prevention of late cancer relapse in adoptive hosts. Our findings therefore suggest that it may be advantageous to target MiHAs with a restricted tissue distribution in order to promote persistence of memory T cells and thereby minimize the risk of cancer recurrence