Over the last several years it has become clear that higher order assemblies on membranes, exemplified by signalosomes, are a paradigm for the regulation of many membrane signaling processes. We have recently combined two-color direct stochastic optical reconstruction microscopy (dSTORM) with the (Clus-DoC) algorithm that combines cluster detection and colocalization analysis to observe the organization of 5-lipoxygenase (5-LO) and 5-lipoxygenase–activating protein (FLAP) into higher order assemblies on the nuclear envelope of mast cells; these assemblies were linked to leukotriene (LT) C4 production. In this study we investigated whether higher order assemblies of 5-LO and FLAP included cytosolic phospholipase A2 (cPLA2) and were linked to LTB4 production in murine neutrophils. Using two- and three-color dSTORM supported by fluorescence lifetime imaging microscopy we identified higher order assemblies containing 40 molecules (median) (IQR: 23, 87) of 5-LO, and 53 molecules (62, 156) of FLAP monomer. 98 (18, 154) molecules of cPLA2 were clustered with 5-LO, and 77 (33, 114) molecules of cPLA2 were associated with FLAP. These assemblies were tightly linked to LTB4 formation. The activation-dependent close associations of cPLA2, FLAP, and 5-LO in higher order assemblies on the nuclear envelope support a model in which arachidonic acid is generated by cPLA2 in apposition to FLAP, facilitating its transfer to 5-LO to initiate LT synthesis.

This paper considers online convex optimization over a complicated constraint set, which typically consists of multiple functional constraints and a set constraint. The conventional online projection algorithm (Zinkevich, 2003) can be difficult to implement due to the potentially high computation complexity of the projection operation. In this paper, we relax the functional constraints by allowing them to be violated at each round but still requiring them to be satisfied in the long term. This type of relaxed online convex optimization (with long term constraints) was first considered in Mahdavi et al. (2012). That prior work proposes an algorithm to achieve $O(sqrt{T})$ regret and $O(T^{3/4})$ constraint violations for general problems and another algorithm to achieve an $O(T^{2/3})$ bound for both regret and constraint violations when the constraint set can be described by a finite number of linear constraints. A recent extension in Jenatton et al. (2016) can achieve $O(T^{max{ heta,1- heta}})$ regret and $O(T^{1- heta/2})$ constraint violations where $ hetain (0,1)$. The current paper proposes a new simple algorithm that yields improved performance in comparison to prior works. The new algorithm achieves an $O(sqrt{T})$ regret bound with $O(1)$ constraint violations.

Dual first-order methods are essential techniques for large-scale constrained convex optimization. However, when recovering the primal solutions, we need $T(epsilon^{-2})$ iterations to achieve an $epsilon$-optimal primal solution when we apply an algorithm to the non-strongly convex dual problem with $T(epsilon^{-1})$ iterations to achieve an $epsilon$-optimal dual solution, where $T(x)$ can be $x$ or $sqrt{x}$. In this paper, we prove that the iteration complexity of the primal solutions and dual solutions have the same $Oleft(frac{1}{sqrt{epsilon}} ight)$ order of magnitude for the accelerated randomized dual coordinate ascent. When the dual function further satisfies the quadratic functional growth condition, by restarting the algorithm at any period, we establish the linear iteration complexity for both the primal solutions and dual solutions even if the condition number is unknown. When applied to the regularized empirical risk minimization problem, we prove the iteration complexity of $Oleft(nlog n+sqrt{frac{n}{epsilon}} ight)$ in both primal space and dual space, where $n$ is the number of samples. Our result takes out the $left(log frac{1}{epsilon} ight)$ factor compared with the methods based on smoothing/regularization or Catalyst reduction. As far as we know, this is the first time that the optimal $Oleft(sqrt{frac{n}{epsilon}} ight)$ iteration complexity in the primal space is established for the dual coordinate ascent based stochastic algorithms. We also establish the accelerated linear complexity for some problems with nonsmooth loss, e.g., the least absolute deviation and SVM.

Israel Martínez-Hernández, Marc G. Genton.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 204--229.

Abstract:
As high-dimensional and high-frequency data are being collected on a large scale, the development of new statistical models is being pushed forward. Functional data analysis provides the required statistical methods to deal with large-scale and complex data by assuming that data are continuous functions, for example, realizations of a continuous process (curves) or continuous random field (surfaces), and that each curve or surface is considered as a single observation. Here, we provide an overview of functional data analysis when data are complex and spatially correlated. We provide definitions and estimators of the first and second moments of the corresponding functional random variable. We present two main approaches: The first assumes that data are realizations of a functional random field, that is, each observation is a curve with a spatial component. We call them spatial functional data . The second approach assumes that data are continuous deterministic fields observed over time. In this case, one observation is a surface or manifold, and we call them surface time series . For these two approaches, we describe software available for the statistical analysis. We also present a data illustration, using a high-resolution wind speed simulated dataset, as an example of the two approaches. The functional data approach offers a new paradigm of data analysis, where the continuous processes or random fields are considered as a single entity. We consider this approach to be very valuable in the context of big data.

Phillip S. Kott.

Source: Statistics Surveys, Volume 12, 1--17.

Abstract:
Fitting complex survey data to regression equations is explored under a design-sensitive model-based framework. A robust version of the standard model assumes that the expected value of the difference between the dependent variable and its model-based prediction is zero no matter what the values of the explanatory variables. The extended model assumes only that the difference is uncorrelated with the covariates. Little is assumed about the error structure of this difference under either model other than independence across primary sampling units. The standard model often fails in practice, but the extended model very rarely does. Under this framework some of the methods developed in the conventional design-based, pseudo-maximum-likelihood framework, such as fitting weighted estimating equations and sandwich mean-squared-error estimation, are retained but their interpretations change. Few of the ideas here are new to the refereed literature. The goal instead is to collect those ideas and put them into a unified conceptual framework.

Sean L. Simpson, F. DuBois Bowman, Paul J. Laurienti

Source: Statist. Surv., Volume 7, 1--36.

Abstract:
Complex functional brain network analyses have exploded over the last decade, gaining traction due to their profound clinical implications. The application of network science (an interdisciplinary offshoot of graph theory) has facilitated these analyses and enabled examining the brain as an integrated system that produces complex behaviors. While the field of statistics has been integral in advancing activation analyses and some connectivity analyses in functional neuroimaging research, it has yet to play a commensurate role in complex network analyses. Fusing novel statistical methods with network-based functional neuroimage analysis will engender powerful analytical tools that will aid in our understanding of normal brain function as well as alterations due to various brain disorders. Here we survey widely used statistical and network science tools for analyzing fMRI network data and discuss the challenges faced in filling some of the remaining methodological gaps. When applied and interpreted correctly, the fusion of network scientific and statistical methods has a chance to revolutionize the understanding of brain function.

Qian Qin, James P. Hobert.

Source: The Annals of Statistics, Volume 47, Number 4, 2320--2347.

Abstract:
The use of MCMC algorithms in high dimensional Bayesian problems has become routine. This has spurred so-called convergence complexity analysis, the goal of which is to ascertain how the convergence rate of a Monte Carlo Markov chain scales with sample size, $n$, and/or number of covariates, $p$. This article provides a thorough convergence complexity analysis of Albert and Chib’s [ J. Amer. Statist. Assoc. 88 (1993) 669–679] data augmentation algorithm for the Bayesian probit regression model. The main tools used in this analysis are drift and minorization conditions. The usual pitfalls associated with this type of analysis are avoided by utilizing centered drift functions, which are minimized in high posterior probability regions, and by using a new technique to suppress high-dimensionality in the construction of minorization conditions. The main result is that the geometric convergence rate of the underlying Markov chain is bounded below 1 both as $n ightarrowinfty$ (with $p$ fixed), and as $p ightarrowinfty$ (with $n$ fixed). Furthermore, the first computable bounds on the total variation distance to stationarity are byproducts of the asymptotic analysis.

Lisa Schlosser, Torsten Hothorn, Reto Stauffer, Achim Zeileis.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1564--1589.

Abstract:
To obtain a probabilistic model for a dependent variable based on some set of explanatory variables, a distributional approach is often adopted where the parameters of the distribution are linked to regressors. In many classical models this only captures the location of the distribution but over the last decade there has been increasing interest in distributional regression approaches modeling all parameters including location, scale and shape. Notably, so-called nonhomogeneous Gaussian regression (NGR) models both mean and variance of a Gaussian response and is particularly popular in weather forecasting. Moreover, generalized additive models for location, scale and shape (GAMLSS) provide a framework where each distribution parameter is modeled separately capturing smooth linear or nonlinear effects. However, when variable selection is required and/or there are nonsmooth dependencies or interactions (especially unknown or of high-order), it is challenging to establish a good GAMLSS. A natural alternative in these situations would be the application of regression trees or random forests but, so far, no general distributional framework is available for these. Therefore, a framework for distributional regression trees and forests is proposed that blends regression trees and random forests with classical distributions from the GAMLSS framework as well as their censored or truncated counterparts. To illustrate these novel approaches in practice, they are employed to obtain probabilistic precipitation forecasts at numerous sites in a mountainous region (Tyrol, Austria) based on a large number of numerical weather prediction quantities. It is shown that the novel distributional regression forests automatically select variables and interactions, performing on par or often even better than GAMLSS specified either through prior meteorological knowledge or a computationally more demanding boosting approach.

Quan Zhou, Yongtao Guan.

Source: Bayesian Analysis, Volume 14, Number 2, 573--594.

Abstract:
Bayesian variable selection regression (BVSR) is able to jointly analyze genome-wide genetic datasets, but the slow computation via Markov chain Monte Carlo (MCMC) hampered its wide-spread usage. Here we present a novel iterative method to solve a special class of linear systems, which can increase the speed of the BVSR model-fitting tenfold. The iterative method hinges on the complex factorization of the sum of two matrices and the solution path resides in the complex domain (instead of the real domain). Compared to the Gauss-Seidel method, the complex factorization converges almost instantaneously and its error is several magnitude smaller than that of the Gauss-Seidel method. More importantly, the error is always within the pre-specified precision while the Gauss-Seidel method is not. For large problems with thousands of covariates, the complex factorization is 10–100 times faster than either the Gauss-Seidel method or the direct method via the Cholesky decomposition. In BVSR, one needs to repetitively solve large penalized regression systems whose design matrices only change slightly between adjacent MCMC steps. This slight change in design matrix enables the adaptation of the iterative complex factorization method. The computational innovation will facilitate the wide-spread use of BVSR in reanalyzing genome-wide association datasets.

RJ Wenthold
Mar 15, 1996; 16:1982-1989
Articles

RU Muller
Jul 1, 1987; 7:1951-1968
Articles

The researchers gathered data from 166 surveys of insect abundance around the world, mostly conducted since the 1980s

This paper studies the relationship between bank geographic complexity and risk. We use a unique dataset of 96 bank holding companies around the world to measure the geographic dispersion of their affiliates. We study how this dispersion interacts with economic and regulatory conditions to affect the riskiness of the bank.

Repair site iFixit has shared x-ray photographs of the new Magic Keyboard for iPad Pro, and they reveal an accessory more complicated than it might appear from the outside.

Structure System Solidworks The term structural system or structural frame in structural engineering refers to the load-resisting sub-system of a building or object that transfers loads through interconnected elements or members. In SOLIDWORKS 2020, the structure system feature is an advanced

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The post SOLIDWORKS Solution for Complex Structure Design appeared first on SOLIDWORKS Tech Blog.

There are known gaps in quality measures for children. More clinical effectiveness research is needed. The patient-centered medical home may serve as a model to guide the development of quality measures, particularly for children with complex medical conditions.

This study combined systematic literature review and the Rand/University of California Los Angeles appropriateness method to develop quality measures for children with complex medical conditions. These are valid and feasible quality measures based on the patient-centered medical home framework that may be used to assess care. (Read the full article)

Children with medical complexity are high users of acute health care, but little is known about their service use across the continuum of care services and in the context of overall health care expenditures.

Although accounting for <1% of the child population, children with medical complexity use almost one-third of all pediatric health care expenditures and make multiple transitions across providers and health care settings. (Read the full article)

Few reports have explored the measurement validity of the relative value unit (RVU) system, particularly in pediatrics. The RVU system, although broadly applied in health care settings, was developed for the adult population and thus may possess unique inadequacies in pediatrics.

We found deficiencies in the ability of the RVU system to capture features of case mix complexity and differences related to age. Additional investigation may be warranted to determine the validity of RVU as a measurement tool in pediatrics. (Read the full article)

Quality measures developed by the Pediatric Quality Measures Program are required to assess disparities in performance according to special health care need status. Methods are needed to identify children according to level of medical complexity in administrative data.

The Pediatric Medical Complexity Algorithm is a new, publicly available algorithm that identifies the small proportion of children with complex chronic disease in Medicaid claims and hospital discharge data with good sensitivity and good to excellent specificity. (Read the full article)

Children who experience outpatient adverse drug events represent 0.5% of pediatric emergency department visits. The subset of children with complex chronic conditions often take multiple medications, but the incidence and severity of adverse drug events in these children is unknown.

Children with complex chronic conditions have a higher risk of emergency department visits related to adverse drug events, compared with other children. The implicated drugs with the highest rates include psychotropic agents, antimicrobial agents, anticonvulsants, hormones/steroids, and analgesics. (Read the full article)

Neurodevelopmental outcomes after cardiac surgery in early life provide critical information for understanding and improving care. Studies show these children are at risk for arterial ischemic stroke and acquired brain injury; further characterization of motor impairment is needed.

This study focuses on the presence of chronic neuromotor disabilities including cerebral palsy and motor impairments after acquired brain injury in children surviving early complex cardiac surgery, providing information on the frequency, characteristics, and predictors that may assist in prevention. (Read the full article)

Children with life-threatening complex chronic conditions (LT-CCCs) experience high hospital use.

Hospital use in the last year of life for these children varies by type and number of LT-CCCs. Most children with ≥3 LT-CCCs are admitted to the hospital for more than 2 months in the last year of life. (Read the full article)

Children with medical complexity require a disproportionate amount of health services due to a multitude of chronic severe illness, and their impact on the health care system appears to be increasing.

This study provides one of the first comparisons of health care utilization patterns for children with medical complexity between medical centers in a population-based cohort. (Read the full article)

The Cpx stress response is widespread among Enterobacteriaceae. We have previously reported a mutation in cpxA in a multidrug resistant strain of Klebsiella aerogenes isolated from a patient treated with imipenem. This mutation yields to a single amino acid substitution (Y144N) located in the periplasmic sensor domain of CpxA. In this work, we sought to characterize this mutation in Escherichia coli by using genetic and biochemical approaches. Here, we show that cpxA^Y144N is an activated allele that confers resistance to β-lactams and aminoglycosides in a CpxR-dependent manner, by regulating the expression of the OmpF porin and the AcrD efflux pump, respectively. We also demonstrate the intimate interconnection between Cpx system and peptidoglycan integrity on the expression of an exogenous AmpC β-lactamase by using imipenem as a cell wall active antibiotic or inactivation of penicillin-binding proteins. Moreover, our data indicate that the Y144N substitution abrogates the interaction between CpxA and CpxP and increase phosphotransfer activity on CpxR. Because the addition of a strong AmpC inducer such as imipenem is known to causes abnormal accumulation of muropeptides (disaccharide-pentapeptide, N-acetylglucosamyl-1,6-anhydro-N-acetylmuramyl-l-alanyl-d-glutamy-meso-diaminopimelic-acid-d-alanyl-d-alanine) in the periplasmic space, we propose these molecules activate the Cpx system by displacing CpxP from the sensor domain of CpxA. Altogether, these data could explain why large perturbations to peptidoglycan caused by imipenem lead to mutational activation of the Cpx system and bacterial adaptation through multidrug resistance. These results also validate the Cpx system, in particular the interaction between CpxA and CpxP, as a promising therapeutic target.

Treatment of Mycobacterium avium complex pulmonary disease (MAC-PD) is challenging partly due to high efflux pump expression. Thioridazine might block these efflux pumps. We explore thioridazine's efficacy against M. avium using minimum inhibitory concentrations (MICs), time-kill combination assays, ex vivo macrophage infection assays and efflux assays. Thioridazine is bactericidal against M. avium, inhibits intracellular growth at 2x MIC and blocks ethidium bromide efflux. However, its toxicity and low plasma concentrations, make it unlikely to add efficacy to MAC-PD therapy.

BACKGROUND AND OBJECTIVES:

Children with medical complexity (CMC) comprise only 6% of the pediatric population, account for ~40% of pediatric health care spending, and provide an important opportunity for cost saving. Savings in this group can have an important impact on pediatric health care costs. The objective of this study was to assess the impact of a multicenter care management program on spending and use in CMC.

Katherine H. Burns
Oct 1, 2010; 126:638-646
ARTICLES

Tamara D. Simon
Oct 1, 2010; 126:647-655
ARTICLES

Review of: How Behavior Spreads: The Science of Complex Contagions by Centola, Damon, reviewed by Srebrenka Letina

NEW CASTLE (May 30, 2018) – As a way to better support the needs of children with medical complexity and their families, the Division of Medicaid and Medical Assistance this week released Delaware’s Plan for Managing the Health Care Needs of Children with Medical Complexity and announced that stakeholders will continue work to develop longer-term […]

With more and more SoCs employing sophisticated interconnect IP to link multiple processor cores, caches, memories, and dozens of other IP functions, the designs are enabling a new generation of low-power servers and high-performance mobile devices. The complexity of the interconnects and their advanced configurability contributes to already formidable design and verification challenges which lead to the following questions:

While your interconnect subsystem might have a correct functionality, are you starving your IP functions of the bandwidth they need? Are requests from latency-critical initiators processed on time? How can you ensure that all applications will receive the desired bandwidth in steady-state and corner use-cases?

To answer these questions, Cadence recommends the Performance Verification Methodology to ensure that the system performance meets requirements at the different levels:

1. Performance characterization: The first level of verification aims to verify the path-to-path traffic measuring the performance envelope. It targets integration bugs like clock frequency, buffer sizes, and bridge configuration. It requires to analyze the latency and bandwidth of design’s critical paths.
2. Steady state workloads: The second level of verification aims to verify the master-by-master defined loads using traffic profiles. It identifies the impact on bandwidth when running multi-master traffic with various Quality-of-Service (QoS) settings. It analyzes the DDR sub-system’s efficiency, measures bandwidth and checks whether masters’ QoS requirements are met.
3. Application specific use cases: The last level of verification simulates the use-cases and reaches the application performance corner cases. It analyzes the master-requested bandwidth as well as the DDR sub-system’s efficiency and bandwidth.

Cadence has developed a set of tools to assist customers in performance validation of their SoCs. Cadence Interconnect Workbench simplifies the setup and measurement of performance and verification testbenches and makes debugging of complex system behaviors a snap. The solution works with Cadence Verification IPs and executes on the Cadence Xcelium® Enterprise Simulator or Cadence Palladium® Accellerator/Emulator, with coverage results collected and analyzed in the Cadence vManager  Metric-Driven Signoff Platform.

To verify the performance of the Steady State Workloads, Arm has just released a new AMBA Adaptive Traffic Profile (ATP) specification which describes AMBA abstract traffic attributes and defines the behavior of the different traffic profiles in the system.

With the availability of Cadence Interconnect Workbench and AMBA VIP support of ATP, early adopters of the AMBA ATP specification can begin working immediately, ensuring compliance with the standard, and achieving the fastest path to SoC performance verification closure.

For more information on the AMBA Adaptive Traffic Profile, you can visit Dimitry's blog on AMBA Adaptive Traffic Profiles: Addressing The Challenge. 

More information on Cadence Interconnect Workbench solution is available at Cadence Interconnect Solution webpage.

Thierry

Learn about the challenges and solutions for integrating and verification PCIe(r) Gen4 into an Arm-Based Server SoC. Listen to this relatively short webinar by Arm and Cadence, as they describe the collaboration and results, including methodology and...(read more)

In this session we look at high value/reputationally sensitive disputes in the education sector. Running a university or Higher Education Institution is always a complicated business – and never more so than now. The sector is facing a time of unp...

The Daesan petrochemical industrial zone in Seosan, South Chungcheong Province, will transform into an advanced chemical industrial complex. The nation's major petrochemical companies may invest up to 10 trillion won in this area. On September 14, S-Oil, Lotte Chemical, Hanwha Total, South Chungcheong provincial government, and Seosan city gathered in Lotte World Tower and signed a memorandum to create a Daesan specialized industrial complex. Currently the area is home to large petrochemical ...

Uzbekistan widely celebrates the Day of Memory and Honor and the 75th Anniversary of the Victory in World War II. President of the Republic of Uzbekistan Shavkat Mirziyoyev takes part in celebrations in Tashkent. On May 9, the Head of the state visited Victory Park, created in honor of this glorious date. People of Uzbekistan made a great contribution to the victory in World War II. But there was no single memorial complex in the...

A.L. Sadler examines in minute detail the origins of tea drinking and the rich and complex components of its ritualization.

Negotiations between China and its Southeast Asian neighbours for a South China Sea code of conduct have been postponed as the nations involved put their efforts into containing the Covid-19 pandemic, creating uncertainty about whether the two sides can work together amid rising tensions in the contested territory.Southeast Asian nations are increasingly caught in a dilemma whether to maintain relations with Beijing during the pandemic while also fearing that tensions over the disputed waters…

Sensuous and unique, the smooth white structures of the John F. Kennedy Center for the Performing Arts new, 21st century The REACH complex promises a different sort of experience than its more formal neighbor. Featuring innovative indoor and outdoor...

Fossils of single cells found in China are 2 billion years old, making them the oldest eukaryotic cells in the fossil record and possibly our distant relatives

Gulls are often misunderstood. Many people think of them as chip-stealing pests, but that's just because they haven't spent the time to get to know them, says Madeleine Goumas

ABSTRACT

Pneumocystis, a major opportunistic pathogen in patients with a broad range of immunodeficiencies, contains abundant surface proteins encoded by a multicopy gene family, termed the major surface glycoprotein (Msg) gene superfamily. This superfamily has been identified in all Pneumocystis species characterized to date, highlighting its important role in Pneumocystis biology. In this report, through a comprehensive and in-depth characterization of 459 msg genes from 7 Pneumocystis species, we demonstrate, for the first time, the phylogeny and evolution of conserved domains in Msg proteins and provide a detailed description of the classification, unique characteristics, and phylogenetic relatedness of five Msg families. We further describe, for the first time, the relative expression levels of individual msg families in two rodent Pneumocystis species, the substantial variability of the msg repertoires in P. carinii from laboratory and wild rats, and the distinct features of the expression site for the classic msg genes in Pneumocystis from 8 mammalian host species. Our analysis suggests multiple functions for this superfamily rather than just conferring antigenic variation to allow immune evasion as previously believed. This study provides a rich source of information that lays the foundation for the continued experimental exploration of the functions of the Msg superfamily in Pneumocystis biology.

IMPORTANCE Pneumocystis continues to be a major cause of disease in humans with immunodeficiency, especially those with HIV/AIDS and organ transplants, and is being seen with increasing frequency worldwide in patients treated with immunodepleting monoclonal antibodies. Annual health care associated with Pneumocystis pneumonia costs ~$475 million dollars in the United States alone. In addition to causing overt disease in immunodeficient individuals, Pneumocystis can cause subclinical infection or colonization in healthy individuals, which may play an important role in species preservation and disease transmission. Our work sheds new light on the diversity and complexity of the msg superfamily and strongly suggests that the versatility of this superfamily reflects multiple functions, including antigenic variation to allow immune evasion and optimal adaptation to host environmental conditions to promote efficient infection and transmission. These findings are essential to consider in developing new diagnostic and therapeutic strategies.

ABSTRACT

Recognition modes of individual T cell receptors (TCRs) are well studied, but factors driving the selection of TCR repertoires from primary through persistent human virus infections are less well understood. Using deep sequencing, we demonstrate a high degree of diversity of Epstein-Barr virus (EBV)-specific clonotypes in acute infectious mononucleosis (AIM). Only 9% of unique clonotypes detected in AIM persisted into convalescence; the majority (91%) of unique clonotypes detected in AIM were not detected in convalescence and were seeming replaced by equally diverse "de novo" clonotypes. The persistent clonotypes had a greater probability of being generated than nonpersistent clonotypes due to convergence recombination of multiple nucleotide sequences to encode the same amino acid sequence, as well as the use of shorter complementarity-determining regions 3 (CDR3s) with fewer nucleotide additions (i.e., sequences closer to germ line). Moreover, the two most immunodominant HLA-A2-restricted EBV epitopes, BRLF1₁₀₉ and BMLF1₂₈₀, show highly distinct antigen-specific public (i.e., shared between individuals) features. In fact, TCRα CDR3 motifs played a dominant role, while TCRβ played a minimal role, in the selection of TCR repertoire to an immunodominant EBV epitope, BRLF1. This contrasts with the majority of previously reported repertoires, which appear to be selected either on TCRβ CDR3 interactions with peptide/major histocompatibility complex (MHC) or in combination with TCRα CDR3. Understanding of how TCR-peptide-MHC complex interactions drive repertoire selection can be used to develop optimal strategies for vaccine design or generation of appropriate adoptive immunotherapies for viral infections in transplant settings or for cancer.

IMPORTANCE Several lines of evidence suggest that TCRα and TCRβ repertoires play a role in disease outcomes and treatment strategies during viral infections in transplant patients and in cancer and autoimmune disease therapy. Our data suggest that it is essential that we understand the basic principles of how to drive optimum repertoires for both TCR chains, α and β. We address this important issue by characterizing the CD8 TCR repertoire to a common persistent human viral infection (EBV), which is controlled by appropriate CD8 T cell responses. The ultimate goal would be to determine if the individuals who are infected asymptomatically develop a different TCR repertoire than those that develop the immunopathology of AIM. Here, we begin by doing an in-depth characterization of both CD8 T cell TCRα and TCRβ repertoires to two immunodominant EBV epitopes over the course of AIM, identifying potential factors that may be driving their selection.

ABSTRACT

Hantaviruses are the etiological agent of hemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS). The latter is associated with case fatality rates ranging from 30% to 50%. HCPS cases are rare, with approximately 300 recorded annually in the Americas. Recently, an HCPS outbreak of unprecedented size has been occurring in and around Epuyén, in the southwestern Argentinian state of Chubut. Since November of 2018, at least 29 cases have been laboratory confirmed, and human-to-human transmission is suspected. Despite posing a significant threat to public health, no treatment or vaccine is available for hantaviral disease. Here, we describe an effort to identify, characterize, and develop neutralizing and protective antibodies against the glycoprotein complex (Gn and Gc) of Andes virus (ANDV), the causative agent of the Epuyén outbreak. Using murine hybridoma technology, we generated 19 distinct monoclonal antibodies (MAbs) against ANDV GnGc. When tested for neutralization against a recombinant vesicular stomatitis virus expressing the Andes glycoprotein (GP) (VSV-ANDV), 12 MAbs showed potent neutralization and 8 showed activity in an antibody-dependent cellular cytotoxicity reporter assay. Escape mutant analysis revealed that neutralizing MAbs targeted both the Gn and the Gc. Four MAbs that bound different epitopes were selected for preclinical studies and were found to be 100% protective against lethality in a Syrian hamster model of ANDV infection. These data suggest the existence of a wide array of neutralizing antibody epitopes on hantavirus GnGc with unique properties and mechanisms of action.

IMPORTANCE Infections with New World hantaviruses are associated with high case fatality rates, and no specific vaccine or treatment options exist. Furthermore, the biology of the hantaviral GnGc complex, its antigenicity, and its fusion machinery are poorly understood. Protective monoclonal antibodies against GnGc have the potential to be developed into therapeutics against hantaviral disease and are also great tools to elucidate the biology of the glycoprotein complex.