Genetic Loci Associated with C-reactive Protein Levels and Risk of Coronary Heart Disease.

CONTEXT: Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain. OBJECTIVE: To investigate association of genetic loci with CRP levels and risk of coronary heart disease. DESIGN, SETTING, AND PARTICIPANTS: We first carried out a genome-wide association (n = 17,967) and replication study (n = 13,615) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a mendelian randomization study of the most closely associated single-nucleotide polymorphism (SNP) in the CRP locus and published data on other CRP variants involving a total of 28,112 cases and 100,823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14,365 cases and 32,069 controls. MAIN OUTCOME MEASURE: Risk of coronary heart disease. RESULTS: Polymorphisms in 5 genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (-14.8%; 95% confidence interval [CI], -17.6% to -12.0%; P = 6.2 x 10(-22)), rs4537545 in IL6R (-11.5%; 95% CI, -14.4% to -8.5%; P = 1.3 x 10(-12)), rs7553007 in the CRP locus (-20.7%; 95% CI, -23.4% to -17.9%; P = 1.3 x 10(-38)), rs1183910 in HNF1A (-13.8%; 95% CI, -16.6% to -10.9%; P = 1.9 x 10(-18)), and rs4420638 in APOE-CI-CII (-21.8%; 95% CI, -25.3% to -18.1%; P = 8.1 x 10(-26)). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave an odds ratio (OR) of 0.98 (95% CI, 0.94 to 1.01) per 20% lower CRP level. Our mendelian randomization study of variants in the CRP locus showed no association with coronary heart disease: OR, 1.00; 95% CI, 0.97 to 1.02; per 20% lower CRP level, compared with OR, 0.94; 95% CI, 0.94 to 0.95; predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (z score, -3.45; P < .001). SNPs rs6700896 in LEPR (OR, 1.06; 95% CI, 1.02 to 1.09; per minor allele), rs4537545 in IL6R (OR, 0.94; 95% CI, 0.91 to 0.97), and rs4420638 in the APOE-CI-CII cluster (OR, 1.16; 95% CI, 1.12 to 1.21) were all associated with risk of coronary heart disease. CONCLUSION: The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.

River and Stream Health in Iowa, 2001

A report by the Iowa Department of Natural Resources on how the health of Iowa's River and Stream are today.

Enhanced generation of specific tumor-reactive CTL in vitro by selected Melan-A/MART-1 immunodominant peptide analogues.

The Melan-A/MART-1 gene, which is expressed by normal melanocytes as well as by most fresh melanoma samples and melanoma cell lines, codes for Ags recognized by tumor-reactive CTL. HLA-A*0201-restricted Melan-A-specific CTL recognize primarily the Melan-A(27-35) (AAGIGILTV) and the Melan-A(26-35) (EAAGIGILTV) peptides. The sequences of these two peptides are not necessarily optimal as far as binding to HLA-A*0201 is concerned, since both lack one of the dominant anchor amino acid residues (leucine or methionine) at position 2. In this study we introduced single amino acid substitutions in either one of the two natural peptide sequences with the aim of improving peptide binding to HLA-A*0201 and/or recognition by specific CTL. Surprisingly, analogues of the Melan-A(27-35) peptide, which bound more efficiently than the natural nonapeptide to HLA-A*0201, were poorly recognized by tumor-reactive CTL. In contrast, among the Melan-A(26-35) peptide analogues tested, the peptide ELAGIGILTV was not only able to display stable binding to HLA-A2.1 but was also recognized more efficiently than the natural peptide by two short-term cultured tumor-infiltrated lymph node cell cultures as well as by five of five tumor-reactive CTL clones. Moreover, in vitro generation of tumor-reactive CTL by stimulation of PBMC from HLA-A*0201 melanoma patients with this particular peptide analogue was much more efficient than that observed with either one of the two natural peptides. These results suggest that the Melan-A(26-35) peptide analogue ELAGIGILTV may be more immunogenic than the natural peptides in HLA-A*0201 melanoma patients and should thus be considered as a candidate for future peptide-based vaccine trials.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Activation of human melanoma reactive CD8+ T cells by vaccination with an immunogenic peptide analog derived from Melan-A/melanoma antigen recognized by T cells-1.

PURPOSE: As compared with natural tumor peptide sequences, carefully selected analog peptides may be more immunogenic and thus better suited for vaccination. However, T cells in vivo activated by such altered analog peptides may not necessarily be tumor specific because sequence and structure of peptide analogs differ from corresponding natural peptides. EXPERIMENTAL DESIGN: Three melanoma patients were immunized with a Melan-A peptide analog that binds more strongly to HLA-A*0201 and is more immunogenic than the natural sequence. This peptide was injected together with a saponin-based adjuvant, followed by surgical removal of lymph node(s) draining the site of vaccination. RESULTS: Ex vivo analysis of vaccine site draining lymph nodes revealed antigen-specific CD8+ T cells, which had differentiated to memory cells. In vitro, these cells showed accelerated proliferation upon peptide stimulation. Nearly all (16 of 17) of Melan-A-specific CD8+ T-cell clones generated from these lymph nodes efficiently killed melanoma cells. CONCLUSIONS: Patient immunization with the analog peptide leads to in vivo activation of T cells that were specific for the natural tumor antigen, demonstrating the usefulness of the analog peptide for melanoma immunotherapy.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Implementing TURF analysis through binary linear programming

This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

Restless bandits, linear programming relaxations and a primal-dual index heuristic

We develop a mathematical programming approach for the classicalPSPACE - hard restless bandit problem in stochastic optimization.We introduce a hierarchy of n (where n is the number of bandits)increasingly stronger linear programming relaxations, the lastof which is exact and corresponds to the (exponential size)formulation of the problem as a Markov decision chain, while theother relaxations provide bounds and are efficiently computed. Wealso propose a priority-index heuristic scheduling policy fromthe solution to the first-order relaxation, where the indices aredefined in terms of optimal dual variables. In this way wepropose a policy and a suboptimality guarantee. We report resultsof computational experiments that suggest that the proposedheuristic policy is nearly optimal. Moreover, the second-orderrelaxation is found to provide strong bounds on the optimalvalue.

Biomass estimation of Triplectides egleri Sattler (Trichoptera, Leptoceridae) in a stream at Ducke Reserve, Central Amazonia

ABSTRACT Biomass is a fundamental measure for understanding the structure and functioning (e.g. fluxes of energy and nutrients in the food chain) of aquatic ecosystems. We aim to provide predictive models to estimate the biomass of Triplectides egleri Sattler, 1963, in a stream in Central Amazonia, based on body and case dimensions. We used body length, head-capsule width, interocular distance and case length and width to derive biomass estimations. Linear, exponential and power regression models were used to assess the relationship between biomass and body or case dimensions. All regression models used in the biomass estimation of T. egleri were significant. The best fit between biomass and body or case dimensions was obtained using the power model, followed by the exponential and linear models. Body length provided the best estimate of biomass. However, the dimensions of sclerotized structures (interocular distance and head-capsule width) also provided good biomass predictions, and may be useful in estimating biomass of preserved and/or damaged material. Case width was the dimension of the case that provided the best estimate of biomass. Despite the low relation, case width may be useful in studies that require low stress on individuals.

Superantigen-reactive CD4+ T cells are required to stimulate B cells after infection with mouse mammary tumor virus.

Superantigens are defined by their ability to stimulate a large fraction of T cells via interaction with the T cell receptor (TCR) V beta domain. Endogenous superantigens, classically termed minor lymphocyte-stimulating (Mls) antigens, were recently identified as products of open reading frames (ORF) in integrated proviral copies of mouse mammary tumor virus (MMTV). We have described an infectious MMTV homologue of the classical endogenous superantigen Mls-1a (Mtv-7). The ORF molecules of both the endogenous Mtv-7 and the infectious MMTV(SW) interact with T cells expressing the TCR V beta 6, 7, 8.1, and 9 domains. Furthermore, the COOH termini of their ORF molecules, thought to confer TCR specificity, are very similar. Since successful transport of MMTV from the site of infection in the gut to the mammary gland depends on a functional immune system, we were interested in determining the early events after and requirements for MMTV infection. We show that MMTV(SW) infection induces a massive response of V beta 6+ CDC4+ T cells, which interact with the viral ORF. Concomitantly, we observed a B cell response and differentiation that depends on both the presence and stimulation of the superantigen-reactive T cells. Furthermore, we show that B cells are the main target of the initial MMTV infection as judged by the presence of the reverse-transcribed viral genome and ORF transcripts. Thus, we suggest that MMTV infection of B cells leads to ORF-mediated B-T cell interaction, which maintains and possibly amplifies viral infection.

Clinical outcome after a reactive hypothermic EEG following cardiac arrest.

BACKGROUND: Reactive electroencephalography (EEG) background during therapeutic hypothermia (TH) is related to favorable prognosis after cardiac arrest (CA), but its predictive value is not 100 %. The aim of this study was to investigate outcome predictors after a first reactive EEG recorded during TH after CA. METHODS: We studied a cohort of consecutive comatose adults admitted between February 2008 and November 2012, after successful resuscitation from CA, selecting patients with reactive EEG during TH. Outcome was assessed at three months, and categorized as survivors and non-survivors (no patient was in vegetative state). Demographics, clinical variables, EEG features, serum neuron-specific enolase (NSE) and procalcitonin, were compared using uni- and multivariable analyses. RESULTS: A total of 290 patients were treated with TH after cardiac arrest; 146 had an EEG during TH, which proved reactive in 90 of them; 77 (86 %) survived and 13 (14 %) died (without recovery from coma). The group of non-survivors had a higher occurrence of discontinuous EEG (p = 0.006; multivariate analysis p = 0.026), and a higher serum NSE peak (p = 0.021; multivariate analysis p = 0.014); conversely, demographics, and other clinical variables including serum procalcitonin did not differ. CONCLUSIONS: A discontinuous EEG and high serum NSE are associated with mortality after CA in patients with poor outcome despite a reactive hypothermic EEG. This suggests more severe cerebral damage, but not to higher extent of systemic disease.