95 research outputs found

    Convergence of socio-ecological dynamics in disparate ecological systems under strong coupling to human social systems

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    bioRxiv preprint first posted online Apr. 6, 2018; doi: http://dx.doi.org/10.1101/296202. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.It is widely recognized that coupled socio-ecological dynamics can be qualitatively different from the dynamics of social or ecological systems in isolation from one another. The influence of the type of ecological dynamics on the dynamics of the larger socio-ecological system is less well studied, however. Here, we carry out such a comparison using a mathematical model of a common pool resource problem. A population must make decisions about harvesting a renewable resource. Individuals may either be cooperators, who harvest at a sustainable level, or defectors, who over-harvest. Cooperators punish defectors through social ostracism. Individuals can switch strategies according the costs and benefits of harvesting and the strength of social ostracism. These mechanisms are represented by a differential equation for social dynamics which is coupled to three different types of resource dynamics: logistic growth, constant inflow, and threshold growth. We find that when human influence is sufficiently weak, the form of natural dynamics leaves a strong imprint on the socio-ecological dynamics, and human social dynamics are qualitatively very different from natural dynamics. However, stronger human influence introduces a broad intermediate parameter regime where dynamical patterns converge to a common type: the three types of ecological systems exhibit similar dynamics, but also, social and ecological dynamics strongly mirror one another. This is a consequence of stronger coupling and is reminiscent of synchrony from other fields, such as the classic problem of coupled oscillators in physics. Socio-ecological convergence has implications for how we understand and manage complex socio-ecological systems. In an era of growing human influence on ecological systems, further empirical and theoretical work is required to determine whether socio-ecological convergence is present in real systems

    Pneumococcal hemolytic uremic syndrome and steroid resistant nephrotic syndrome

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    Pneumococcal-associated hemolytic uremic syndrome (pHUS) is a rare but severe complication of invasive Streptococcus pneumoniae infection. We report the case of a 12-year-old female with steroid-resistant nephrotic syndrome treated with adrenocorticotrophic hormone (H.P. Acthar(®) Gel), who developed pneumococcal pneumonia and subsequent pHUS. While nephrotic syndrome is a well-known risk factor for invasive pneumococcal disease, this is the first reported case of pHUS in an adolescent patient with nephrotic syndrome, and reveals novel challenges in the diagnosis, treatment and potential prevention of this complication

    Etiological Profile and Management of Epistaxis in Tertiary Care Hospital

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    Introduction: Epistaxis is a common otolaryngological emergency condition. It occurs due to local and systemic cause. Local cause lies within the nose bleeding either anterior or posterior. Commonest site of bleeding anterior epistaxis is kiesselbach’s plexus. In posterior epistaxis, it is difficult to locate bleeding site. Epistaxis is controlled by simply pinching of nose, decongested nasal drop and abgel packing. Some cases become more challenging required nasal packing and arterial ligation. Objectives: To study the epidemiological pattern and management of epistaxis. Methods: This was a retrospective study on pattern of epistaxis man­aged at Gandaki Medical College Teaching Hospital over a period from April 2015 to April 2016. Information regarding demographic profile, presentation and management of epistaxis was obtained from the Hospital records, ENT Outpatient clinic, Emergency Department, ENT ward and operation theatre. Results: A total of 78 cases were managed during study period. There was a significant male preponderance with male to female ratio 1.78:1. Patients’ age varied from eight to 80 years with mean age 40.7 years. The peak age of incidence was 21 - 30 years group. Idiopathic nasal bleeding 27 (34.6%) was commonest followed by nasal trauma 23 (29.5%) cases and hypertension 16 (20.5%) cases. Seventeen (21.8%) cases managed in day care basis with decongested nasal drop, chemi­cal cautery and abgel packing. Remaining cases required nasal packing and bipolar cautery and other specific form of treatment. Five (6.4%) cases required sphenopalatine artery ligation with no recurrence of bleeding. Conclusions: Epistaxis is common ENT emergency. Most common causes are idiopathic followed by nasal trauma and hypertension. Prompt management is instituted according to cases. Most of the cas­es are managed by non-surgical method

    Multiple stochastic pathways in forced peptide-lipid membrane detachment

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    We have used high resolution AFM based dynamic force spectroscopy to investigate peptide-lipid membrane interactions by measuring the detachment (last-rupture) force distribution, P(F), and the corresponding force dependent rupture rate, k(F), for two different peptides and lipid bilayers. The measured quantities, which differed considerably for different peptides, lipid-membranes, AFM tips (prepared under identical conditions), and retraction speeds of the AFM cantilever, could not be described in terms of the standard theory, according to which detachment occurs along a single pathway, corresponding to a diffusive escape process across a free energy barrier. In particular, the prominent retraction speed dependence of k(F) was a clear indication that peptide-lipid membrane dissociation occurs stochastically along several detachment pathways. Thereby, we have formulated a general theoretical approach for describing P(F) and k(F), by assuming that peptide detachment from lipid membranes occurs, with certain probability, along a few dominant diffusive pathways. This new method was validated through a consistent interpretation of the experimental data. Furthermore, we have found that for moderate retraction speeds at intermediate force values, k(F) exhibits catch-bond behavior (i.e. decreasing detachment rate with increasing force). According to the proposed model this behavior is due to the stochastic mixing of individual detachment pathways which do not convert or cross during rupture. To our knowledge, such catch-bond mechanism has not been proposed and demonstrated before for a peptide-lipid interaction

    Competition Between Injunctive Social Norms And Conservation Priorities Gives Rise To Complex Dynamics In A Model Of Forest Growth And Opinion Dynamics

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    The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.jtbi.2017.07.029 © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/Human and environmental systems are often treated as existing in isolation from one another, whereas in fact they are often two parts of a single, coupled human-environment system. Developing theoretical models of coupled human-environment systems is a continuing area of research, although relatively few of these models are based on differential equations. Here we develop a simple differential equation coupled human-environment system model of forest growth dynamics and conservationist opinion dynamics in a human population. The model assumes logistic growth and harvesting in the forest. Opinion spread in the human population is based on the interplay between conservation values stimulated by forest rarity, and injunctive social norms that tend to support population conformity. We find that injunctive social norms drive the system to the boundaries of phase space, whereas rarity-based conservation priorities drive the system to the interior. The result is complex dynamics including limit cycles and alternative stable states that do not occur if injunctive social norms are absent. We found that the model with injunctive social norms had five possible observable outcomes, whereas the model without social norms had only two stable states. Thus social norms and have dramatic influence in conservation dynamics. We also find that increasing the conservation value of forests is the best way to boost and stabilize forest cover while also boosting conservationist opinion in the population, although for some parameter regimes it can also give rise to long-term oscillations in opinions and forest cover. We conclude that simple models can provide insights and reveal patterns that might be difficult to see with high-dimensional computational models, and therefore should be used more often in research on coupled human-environment systems.NSERCMcDonnell Foundation Complex Systems Scholar Awar

    The kSORT Assay to Detect Renal Transplant Patients at High Risk for Acute Rejection: Results of the Multicenter AART Study

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    Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR. We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set—the Kidney Solid Organ Response Test (kSORT)—was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91–0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88–1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86–0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials. The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants

    The hArtes Tool Chain

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    This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform

    Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

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    Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers

    An Improvement of Shotgun Proteomics Analysis by Adding Next-Generation Sequencing Transcriptome Data in Orange

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    BACKGROUND: Shotgun proteomics data analysis usually relies on database search. Because commonly employed protein sequence databases of most species do not contain sufficient protein information, the application of shotgun proteomics to the research of protein sequence profile remains a big challenge, especially to the species whose genome has not been sequenced yet. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we present a workflow with integrated database to partly address this problem. First, we downloaded the homologous species database. Next, we identified the transcriptome of the sample, created a protein sequence database based on the transcriptome data, and integtrated it with homologous species database. Lastly, we developed a workflow for identifying peptides simultaneously from shotgun proteomics data. CONCLUSIONS/SIGNIFICANCE: We used datasets from orange leaves samples to demonstrate our workflow. The results showed that the integrated database had great advantage on orange shotgun proteomics data analysis compared to the homologous species database, an 18.5% increase in number of proteins identification

    A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses

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    <p>Abstract</p> <p>Background</p> <p>Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algorithm to help clinicians distinguish Kawasaki disease patients from febrile controls to allow timely initiation of treatment.</p> <p>Methods</p> <p>Urine peptidome profiling and whole blood cell type-specific gene expression analyses were integrated with clinical multivariate analysis to improve differentiation of Kawasaki disease subjects from febrile controls.</p> <p>Results</p> <p>Comparative analyses of multidimensional protein identification using 23 pooled Kawasaki disease and 23 pooled febrile control urine peptide samples revealed 139 candidate markers, of which 13 were confirmed (area under the receiver operating characteristic curve (ROC AUC 0.919)) in an independent cohort of 30 Kawasaki disease and 30 febrile control urine peptidomes. Cell type-specific analysis of microarrays (csSAM) on 26 Kawasaki disease and 13 febrile control whole blood samples revealed a 32-lymphocyte-specific-gene panel (ROC AUC 0.969). The integration of the urine/blood based biomarker panels and a multivariate analysis of 7 clinical parameters (ROC AUC 0.803) effectively stratified 441 Kawasaki disease and 342 febrile control subjects to diagnose Kawasaki disease.</p> <p>Conclusions</p> <p>A hybrid approach using a multi-step diagnostic algorithm integrating both clinical and molecular findings was successful in differentiating children with acute Kawasaki disease from febrile controls.</p
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