Geographic Variation in Out‐of‐Pocket Expenditures of Elderly Medicare Beneficiaries

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107567/1/jgs12834.pd

T-Cell Memory Responses Elicited by Yellow Fever Vaccine are Targeted to Overlapping Epitopes Containing Multiple HLA-I and -II Binding Motifs

The yellow fever vaccines (YF-17D-204 and 17DD) are considered to be among the safest vaccines and the presence of neutralizing antibodies is correlated with protection, although other immune effector mechanisms are known to be involved. T-cell responses are known to play an important role modulating antibody production and the killing of infected cells. However, little is known about the repertoire of T-cell responses elicited by the YF-17DD vaccine in humans. In this report, a library of 653 partially overlapping 15-mer peptides covering the envelope (Env) and nonstructural (NS) proteins 1 to 5 of the vaccine was utilized to perform a comprehensive analysis of the virus-specific CD4+ and CD8+ T-cell responses. The T-cell responses were screened ex-vivo by IFN-γ ELISPOT assays using blood samples from 220 YF-17DD vaccinees collected two months to four years after immunization. Each peptide was tested in 75 to 208 separate individuals of the cohort. The screening identified sixteen immunodominant antigens that elicited activation of circulating memory T-cells in 10% to 33% of the individuals. Biochemical in-vitro binding assays and immunogenetic and immunogenicity studies indicated that each of the sixteen immunogenic 15-mer peptides contained two or more partially overlapping epitopes that could bind with high affinity to molecules of different HLAs. The prevalence of the immunogenicity of a peptide in the cohort was correlated with the diversity of HLA-II alleles that they could bind. These findings suggest that overlapping of HLA binding motifs within a peptide enhances its T-cell immunogenicity and the prevalence of the response in the population. In summary, the results suggests that in addition to factors of the innate immunity, "promiscuous" T-cell antigens might contribute to the high efficacy of the yellow fever vaccines. © 2013 de Melo et al

Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).

PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on patient health record data for the early prediction of ARDS. MATERIALS AND METHODS: 9919 patient encounters were retrospectively analyzed from the Medical Information Mart for Intensive Care III (MIMIC-III) data base. XGBoost gradient boosted tree models for early ARDS prediction were created using routinely collected clinical variables and numerical representations of radiology reports as inputs. XGBoost models were iteratively trained and validated using 10-fold cross validation. RESULTS: On a hold-out test set, algorithm classifiers attained area under the receiver operating characteristic curve (AUROC) values of 0.905 when tested for the detection of ARDS at onset and 0.827, 0.810, and 0.790 for the prediction of ARDS at 12-, 24-, and 48-h windows prior to onset, respectively. CONCLUSION: Supervised machine learning predictions may help predict patients with ARDS up to 48 h prior to onset

Impact of post-procedural glycemic variability on cardiovascular morbidity and mortality after transcatheter aortic valve implantation : a post hoc cohort analysis

International audienceBackground : Glycemic variability is associated with worse outcomes after cardiac surgery, but the prognosis value of early glycemic variability after transcatheter aortic valve implantation is not known. This study was therefore designed to analyze the prognosis significance of post-procedural glycemic variability within 30 days after transcatheter aortic valve implantation.Methods : A post hoc analysis of patients from our center included in the FRANCE and FRANCE-2 registries was conducted. Post-procedural glycemic variability was assessed by calculating the mean daily δ blood glucose during the first 2 days after transcatheter aortic valve implantation. Major complications within 30 days were death, stroke, myocardial infarction, acute heart failure, and life-threatening cardiac arrhythmias.Results : We analyzed 160 patients (age (median [interquartile] = 84 [80–88] years; diabetes mellitus (n) = 41 (26%) patients; logistic Euroscore = 20 [12–32]). The median value of mean daily δ blood glucose was 4.3 mmol l−1. The rate of major complications within 30 days after procedure among patients with the lowest quartile of glycemic variability was 12%, increasing from 12 to 26%, and 39% in the second, third, and fourth quartiles, respectively. In multivariate analysis, glycemic variability was independently associated with an increased risk of major complications within 30 days after the procedure (odds ratio [95% CI] = 1.83 [1.19–2.83]; p = 0.006).Conclusions : This study showed that post-procedural glycemic variability was associated with an increased risk of major complications within 30 days after transcatheter aortic valve implantation

Identification of Conserved and HLA Promiscuous DENV3 T-Cell Epitopes

Anti-dengue T-cell responses have been implicated in both protection and immunopathology. However, most of the T-cell studies for dengue include few epitopes, with limited knowledge of their inter-serotype variation and the breadth of their human leukocyte antigen (HLA) affinity. In order to expand our knowledge of HLA-restricted dengue epitopes, we screened T-cell responses against 477 overlapping peptides derived from structural and non-structural proteins of the dengue virus serotype 3 (DENV3) by use of HLA class I and II transgenic mice (TgM): A2, A24, B7, DR2, DR3 and DR4. TgM were inoculated with peptides pools and the T-cell immunogenic peptides were identified by ELISPOT. Nine HLA class I and 97 HLA class II novel DENV3 epitopes were identified based on immunogenicity in TgM and their HLA affinity was further confirmed by binding assays analysis. A subset of these epitopes activated memory T-cells from DENV3 immune volunteers and was also capable of priming naïve T-cells, ex vivo, from dengue IgG negative individuals. Analysis of inter- and intra-serotype variation of such an epitope (A02-restricted) allowed us to identify altered peptide ligands not only in DENV3 but also in other DENV serotypes. These studies also characterized the HLA promiscuity of 23 HLA class II epitopes bearing highly conserved sequences, six of which could bind to more than 10 different HLA molecules representing a large percentage of the global population. These epitope data are invaluable to investigate the role of T-cells in dengue immunity/pathogenesis and vaccine design. © 2013 Nascimento et al

A combined prediction strategy increases identification of peptides bound with high affinity and stability to porcine MHC class I molecules SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01

Affinity and stability of peptides bound by major histocompatibility complex (MHC) class I molecules are important factors in presentation of peptides to cytotoxic T lymphocytes (CTLs). In silico prediction methods of peptide-MHC binding followed by experimental analysis of peptide-MHC interactions constitute an attractive protocol to select target peptides from the vast pool of viral proteome peptides. We have earlier reported the peptide binding motif of the porcine MHC-I molecules SLA-1*04:01 and SLA-2*04:01, identified by an ELISA affinity-based positional scanning combinatorial peptide library (PSCPL) approach. Here, we report the peptide binding motif of SLA-3*04:01 and combine two prediction methods and analysis of both peptide binding affinity and stability of peptide-MHC complexes to improve rational peptide selection. Using a peptide prediction strategy combining PSCPL binding matrices and in silico prediction algorithms (NetMHCpan), peptide ligands from a repository of 8900 peptides were predicted for binding to SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01 and validated by affinity and stability assays. From the pool of predicted peptides for SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01, a total of 71, 28, and 38 % were binders with affinities below 500 nM, respectively. Comparison of peptide-SLA binding affinity and complex stability showed that peptides of high affinity generally, but not always, produce complexes of high stability. In conclusion, we demonstrate how state-of-the-art prediction and in vitro immunology tools in combination can be used for accurate selection of peptides for MHC class I binding, hence providing an expansion of the field of peptide-MHC analysis also to include pigs as a livestock experimental model.Fil: Pedersen, Lasse Eggers. Technical University of Denmark; DinamarcaFil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Harndahl, Mikkel. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas (subsede Chascomús) | Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas (subsede Chascomús); ArgentinaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaFil: Jungersen, Gregers. Technical University of Denmark; Dinamarc

Symptomatic and Asymptomatic Neurological Complications of Infective Endocarditis: Impact on Surgical Management and Prognosis

International audienceObjectives:Symptomatic neurological complications (NC) are a major cause of mortality in infective endocarditis (IE) but the impact of asymptomatic complications is unknown. We aimed to assess the impact of asymptomatic NC (AsNC) on the management and prognosis of IE.Methods: From the database of cases collected for a population-based study on IE, we selected 283 patients with definite left-sided IE who had undergone at least one neuroimaging procedure (cerebral CT scan and/or MRI) performed as part of initial evaluation.Results Among those 283 patients, 100 had symptomatic neurological complications (SNC) prior to the investigation, 35 had an asymptomatic neurological complications (AsNC), and 148 had a normal cerebral imaging (NoNC). The rate of valve surgery was 43% in the 100 patients with SNC, 77% in the 35 with AsNC, and 54% in the 148 with NoNC (p<0.001). In-hospital mortality was 42% in patients with SNC, 8.6% in patients with AsNC, and 16.9% in patients with NoNC (p<0.001). Among the 135 patients with NC, 95 had an indication for valve surgery (71%), which was performed in 70 of them (mortality 20%) and not performed in 25 (mortality 68%). In a multivariate adjusted analysis of the 135 patients with NC, age, renal failure, septic shock, and IE caused by S. aureus were independently associated with in-hospital and 1-year mortality. In addition SNC was an independent predictor of 1-year mortality.Conclusions The presence of NC was associated with a poorer prognosis when symptomatic. Patients with AsNC had the highest rate of valve surgery and the lowest mortality rate, which suggests a protective role of surgery guided by systematic neuroimaging results

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Development and Validation of an Epitope Prediction Tool for Swine (PigMatrix) Based on the Pocket Profile Method

Background: T cell epitope prediction tools and associated vaccine design algorithms have accelerated the development of vaccines for humans. Predictive tools for swine and other food animals are not as well developed, primarily because the data required to develop the tools are lacking. Here, we overcome a lack of T cell epitope data to construct swine epitope predictors by systematically leveraging available human information. Applying the “pocket profile method”, we use sequence and structural similarities in the binding pockets of human and swine major histocompatibility complex proteins to infer Swine Leukocyte Antigen (SLA) peptide binding preferences. We developed epitope-prediction matrices (PigMatrices), for three SLA class I alleles (SLA-1*0401, 2*0401 and 3*0401) and one class II allele (SLA-DRB1*0201), based on the binding preferences of the best-matched Human Leukocyte Antigen (HLA) pocket for each SLA pocket. The contact residues involved in the binding pockets were defined for class I based on crystal structures of either SLA (SLA-specific contacts, Ssc) or HLA supertype alleles (HLA contacts, Hc); for class II, only Hc was possible. Different substitution matrices were evaluated (PAM and BLOSUM) for scoring pocket similarity and identifying the best human match. The accuracy of the PigMatrices was compared to available online swine epitope prediction tools such as PickPocket and NetMHCpan. Results: PigMatrices that used Ssc to define the pocket sequences and PAM30 to score pocket similarity demonstrated the best predictive performance and were able to accurately separate binders from random peptides. For SLA-1*0401 and 2*0401, PigMatrix achieved area under the receiver operating characteristic curves (AUC) of 0.78 and 0.73, respectively, which were equivalent or better than PickPocket (0.76 and 0.54) and NetMHCpan version 2.4 (0.41 and 0.51) and version 2.8 (0.72 and 0.71). In addition, we developed the first predictive SLA class II matrix, obtaining an AUC of 0.73 for existing SLA-DRB1*0201 epitopes. Notably, PigMatrix achieved this level of predictive power without training on SLA binding data. Conclusions: Overall, the pocket profile method combined with binding preferences from HLA binding data shows significant promise for developing T cell epitope prediction tools for pigs. When combined with existing vaccine design algorithms, PigMatrix will be useful for developing genome-derived vaccines for a range of pig pathogens for which no effective vaccines currently exist (e.g. porcine reproductive and respiratory syndrome, influenza and porcine epidemic diarrhea)