Regulation of Cathepsin G Reduces the Activation of Proinsulin-Reactive T Cells from Type 1 Diabetes Patients

Autoantigenic peptides resulting from self-proteins such as proinsulin are important players in the development of type 1 diabetes mellitus (T1D). Self-proteins can be processed by cathepsins (Cats) within endocytic compartments and loaded to major histocompatibility complex (MHC) class II molecules for CD4+ T cell inspection. However, the processing and presentation of proinsulin by antigen-presenting cells (APC) in humans is only partially understood. Here we demonstrate that the processing of proinsulin by B cell or myeloid dendritic cell (mDC1)-derived lysosomal cathepsins resulted in several proinsulin-derived intermediates. These intermediates were similar to those obtained using purified CatG and, to a lesser extent, CatD, S, and V in vitro. Some of these intermediates polarized T cell activation in peripheral blood mononuclear cells (PBMC) from T1D patients indicative for naturally processed T cell epitopes. Furthermore, CatG activity was found to be elevated in PBMC from T1D patients and abrogation of CatG activity resulted in functional inhibition of proinsulin-reactive T cells. Our data suggested the notion that CatG plays a critical role in proinsulin processing and is important in the activation process of diabetogenic T cells

Using population admixture to help complete maps of the human genome

Tens of millions of base pairs of euchromatic human genome sequence, including many protein-coding genes, have no known location in the human genome. We describe an approach for localizing the human genome's missing pieces by utilizing the patterns of genome sequence variation created by population admixture. We mapped the locations of 70 scaffolds spanning four million base pairs of the human genome's unplaced euchromatic sequence, including more than a dozen protein-coding genes, and identified eight large novel inter-chromosomal segmental duplications. We find that most of these sequences are hidden in the genome's heterochromatin, particularly its pericentromeric regions. Many cryptic, pericentromeric genes are expressed in RNA and have been maintained intact for millions of years while their expression patterns diverged from those of paralogous genes elsewhere in the genome. We describe how knowledge of the locations of these sequences can inform disease association and genome biology studies

Building the Field of Health Policy and Systems Research: Social Science Matters

In the second in a series of articles addressing the current challenges and opportunities for the development of Health Policy and Systems Research (HPSR), Lucy Gilson and colleagues argue the importance of insights from the social sciences

Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment

Gene-expression signature-based disease classification and clinical outcome prediction has not been widely introduced in clinical medicine as initially expected, mainly due to the lack of extensive validation needed for its clinical deployment. Obstacles include variable measurement in microarray assay, inconsistent assay platform, analytical requirement for comparable pair of training and test datasets, etc. Furthermore, as medical device helping clinical decision making, the prediction needs to be made for each single patient with a measure of its reliability. To address these issues, there is a need for flexible prediction method less sensitive to difference in experimental and analytical conditions, applicable to each single patient, and providing measure of prediction confidence. The nearest template prediction (NTP) method provides a convenient way to make class prediction with assessment of prediction confidence computed in each single patient's gene-expression data using only a list of signature genes and a test dataset. We demonstrate that the method can be flexibly applied to cross-platform, cross-species, and multiclass predictions without any optimization of analysis parameters

Brief review on systematic hypothermia for the protection of central nervous system during aortic arch surgery: a double-sword tool?

Antegrade selective cerebral perfusion in conjunction with hypothermia attenuate postoperative neurological injury, which in turn still remains the main cause of mortality and morbidity following aortic arch surgery. Hypothermic circulatory arrest however could be a useful tool during arch surgery, surgery for chronic thromboembolic disease, air on the arterial line during CPB, during cavotomy for extraction of renal cell carcinoma with level IV extension, or when dealing with difficult trauma to the SVC or IVC. Cerebral protective effects with hypothermic procedures including inhibition of neuron excitation, and discharge of excitable amino acids, and thereby, prevention of an increase in intercellular calcium ions, hyperoxidation of lipids in cell membranes, and free radical production

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Assessment of a continuous blood gas monitoring system in animals during circulatory stress

<p>Abstract</p> <p>Background</p> <p>The study was aimed to determine the measurement accuracy of The CDI™ blood parameter monitoring system 500 (Terumo Cardiovascular Systems Corporation, Ann Arbor MI) in the real-time continuous measurement of arterial blood gases under different cardiocirculatory stress conditions</p> <p>Methods</p> <p>Inotropic stimulation (Dobutamine 2.5 and 5 μg/kg/min), vasoconstriction (Arginine-vasopressin 4, 8 and 16 IU/h), hemorrhage (-10%, -20%, -35%, and -50% of the theoretical volemia), and volume resuscitation were induced in ten swine (57.4 ± 10.7 Kg).Intermittent blood gas assessments were carried out using a routine gas analyzer at any experimental phase and compared with values obtained at the same time settings during continuous monitoring with CDI™ 500 system. The Bland-Altman analysis was employed.</p> <p>Results</p> <p>Bias and precision for pO₂were - 0.06 kPa and 0.22 kPa, respectively (r²= 0.96); pCO₂- 0.02 kPa and 0.15 kPa, respectively; pH -0.001 and 0.01 units, respectively ( r²= 0.96). The analysis showed very good agreement for SO₂(bias 0.04,precision 0.33, r²= 0.95), Base excess (bias 0.04,precision 0.28, r²= 0.98), HCO₃(bias 0.05,precision 0.62, r²= 0.92),hemoglobin (bias 0.02,precision 0.23, r²= 0.96) and K⁺(bias 0.02, precision 0.27, r²= 0.93). The sensor was reliable throughout the experiment during hemodynamic variations.</p> <p>Conclusions</p> <p>Continuous blood gas analysis with the CDI™ 500 system was reliable and it might represent a new useful tool to accurately and timely monitor gas exchange in critically ill patients. Nonetheless, our findings need to be confirmed by larger studies to prove its reliability in the clinical setting.</p

Inference of Population Structure using Dense Haplotype Data

The advent of genome-wide dense variation data provides an opportunity to investigate ancestry in unprecedented detail, but presents new statistical challenges. We propose a novel inference framework that aims to efficiently capture information on population structure provided by patterns of haplotype similarity. Each individual in a sample is considered in turn as a recipient, whose chromosomes are reconstructed using chunks of DNA donated by the other individuals. Results of this “chromosome painting” can be summarized as a “coancestry matrix,” which directly reveals key information about ancestral relationships among individuals. If markers are viewed as independent, we show that this matrix almost completely captures the information used by both standard Principal Components Analysis (PCA) and model-based approaches such as STRUCTURE in a unified manner. Furthermore, when markers are in linkage disequilibrium, the matrix combines information across successive markers to increase the ability to discern fine-scale population structure using PCA. In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. We analyse Human Genome Diversity Panel data for 938 individuals and 641,000 markers, and we identify 226 populations reflecting differences on continental, regional, local, and family scales. We present multiple lines of evidence that, while many methods capture similar information among strongly differentiated groups, more subtle population structure in human populations is consistently present at a much finer level than currently available geographic labels and is only captured by the haplotype-based approach. The software used for this article, ChromoPainter and fineSTRUCTURE, is available from http://www.paintmychromosomes.com/

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.https://doi.org/10.1186/1471-2105-12-35