Genomic Risk Factors Driving Immune-Mediated Delayed Drug Hypersensitivity Reactions

Adverse drug reactions (ADRs) remain associated with significant mortality. Delayed hypersensitivity reactions (DHRs) that occur greater than 6 h following drug administration are T-cell mediated with many severe DHRs now associated with human leukocyte antigen (HLA) risk alleles, opening pathways for clinical prediction and prevention. However, incomplete negative predictive value (NPV), low positive predictive value (PPV), and a large number needed to test (NNT) to prevent one case have practically prevented large-scale and cost-effective screening implementation. Additional factors outside of HLA contributing to risk of severe T-cell-mediated DHRs include variation in drug metabolism, T-cell receptor (TCR) specificity, and, most recently, HLA-presented immunopeptidome-processing efficiencies via endoplasmic reticulum aminopeptidase (ERAP). Active research continues toward identification of other highly polymorphic factors likely to impose risk. These include those previously associated with T-cell-mediated HLA-associated infectious or auto-immune disease such as Killer cell immunoglobulin-like receptors (KIR), epistatically linked with HLA class I to regulate NK- and T-cell-mediated cytotoxic degranulation, and co-inhibitory signaling pathways for which therapeutic blockade in cancer immunotherapy is now associated with an increased incidence of DHRs. As such, the field now recognizes that susceptibility is not simply a static product of genetics but that individuals may experience dynamic risk, skewed toward immune activation through therapeutic interventions and epigenetic modifications driven by ecological exposures. This review provides an updated overview of current and proposed genetic factors thought to predispose risk for severe T-cell-mediated DHRs

A low‐cost, sensitive and specific PCR ‐based tool for rapid clinical detection of HLA‐B*35 alleles associated with delayed drug hypersensitivity reactions

HLA (HLA) alleles are risk factors for CD8+ T-cell-mediated drug hypersensitivity reactions. However, as most HLA associations are incompletely predictive and/or involve risk alleles at low frequency, costly sequence-based typing can elude an economically productive cost: benefit ratio for clinical validation studies and diagnostic and/or preventative screening. Hence rapid and low-cost detection assays are now required, both for single alleles but also across risk loci associated with broader multi-disease risk; exemplified by associations with diverse alleles in HLA-B*35, including HLA-B*35:01 and green tea- or co-trimoxazole-induced liver injury. Here, we developed a cost-effective (<$10USD) qPCR assay for rapid (<2.5 h) clinical detection of HLA-B*35 alleles. The assay was validated using 430 DNA samples with previous American society for histocompatibility and immunogenetics-accredited sequence-based high-resolution HLA typing, positively detecting all HLA-B*35 allelic variants in our cohort, and as expected by primer design, the six samples that expressed low-frequency B*78:01. The assay did not result in positive detection for any negative control allele. With expected detection of B*35 and B*78, our assay sensitivity (95% CI, 95.07%–100.00%) and specificity (95% CI, 98.97%–100.00%) of 100% using as low as 10 ng of DNA provides a reliable HLA-B*35 screening tool for clinical validation and HLA–risk-based prevention and diagnostics

Elastic moduli of model random three-dimensional closed-cell cellular solids

Most cellular solids are random materials, while practically all theoretical results are for periodic models. To be able to generate theoretical results for random models, the finite element method (FEM) was used to study the elastic properties of solids with a closed-cell cellular structure. We have computed the density ($\rho$) and microstructure dependence of the Young's modulus ($E$) and Poisson's ratio (PR) for several different isotropic random models based on Voronoi tessellations and level-cut Gaussian random fields. The effect of partially open cells is also considered. The results, which are best described by a power law $E\propto\rho^n$ ($1 < n <2$), show the influence of randomness and isotropy on the properties of closed-cell cellular materials, and are found to be in good agreement with experimental data.Comment: 13 pages, 13 figure

Distributions of fatigue damage from data-driven strain prediction using Gaussian process regression

Fatigue is a leading cause of structural failure; however, monitoring and prediction of damage accumulation remains an open problem, particularly in complex environments where maintaining sensing equipment is challenging. As a result, there is a growing interest in virtual loads monitoring, or inferential sensing, particularly for predicting strain in areas of interest using machine learning methods. This paper pursues a probabilistic approach, relying on a Gaussian process (GP) regression, to produce both strain predictions and a predictive distribution of the accumulated fatigue damage in a given time period. Here, the fatigue distribution is achieved via propagation of successive draws from the posterior GP through a rainflow count. The establishment of such a distribution crucially accounts for uncertainty in the predictive model and will form a valuable element in any probabilistic risk assessment. For demonstration of the method, distributions for predicted fatigue damage in an aircraft wing are produced across 84 flights. The distributions provide a robust measure of predicted damage accumulation and model uncertainty

The Influence of an Orienting Task on the Memory Performance of Children with Reading Problems

This study investigated the hypothesis that differences in performance between reading disabled and normal children on a rote memory task could be eliminated if both groups were induced to process the material to be remembered in the same manner. The free recall of fourth-grade good and poor readers was tested following a free study period and the performance of an orienting task that required subjects to sort the material into taxonomic categories. There was a significant group by conditions interaction, with recall differences in the free study condition being eliminated following performance of the orienting task. The results have important implications for theoretical explanations of performance deficits in reading disabled children.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68893/2/10.1177_002221947901200608.pd

RAFT dispersion polymerisation of lauryl methacrylate in ethanol–water binary mixtures: synthesis of diblock copolymer vesicles with deformable membranes

Polymerisation-induced self-assembly (PISA) is widely recognised to be a powerful platform technology for the rational synthesis of diblock copolymer nano-objects. RAFT alcoholic dispersion polymerisation is an important PISA formulation that has been used to prepare block copolymer spheres, worms and vesicles. In this study, we have utilised the RAFT dispersion polymerisation of lauryl methacrylate (LMA) using a poly(N-(2-methacryloyloxy)ethyl pyrrolidone) (PNMEP) stabiliser in order to prepare vesicles with highly deformable membranes. More specifically, a PNMEP28 precursor was chain-extended with LMA in an 80 : 20 w/w ethanol–water mixture to produce a series of PNMEP28-PLMAx diblock copolymer nano-objects (Mw/Mn ≤ 1.40; LMA conversions ≥98% in all cases, as indicated by 1H NMR spectroscopy). Differential scanning calorimetry studies confirmed that the membrane-forming PLMA block had a relatively low glass transition temperature. Transmission electron microscopy and small angle X-ray scattering were used to identify copolymer morphologies for these highly asymmetric diblock copolymers. A mixed sphere and vesicle morphology was observed when targeting x = 43, while polydisperse vesicles were obtained for x = 65–151. Slightly smaller vesicles with lower mean aggregation numbers and thicker membranes were obtained when targeting higher PLMA DPs. A minor population of sheet-like lamellae was observed for each target copolymer composition, with lamellar stacking leading to a structure peak in the scattering patterns recorded for PNMEP28-PLMA129 and PNMEP28-PLMA151. Bearing in mind potential industrial applications, RAFT chain-end removal strategies were briefly explored for such PNMEP28-PLMAx vesicles. Thus, 96% of dithiobenzoate chain-ends could be removed within 3 h at 50 °C via LED irradiation of a 7.5% aqueous dispersion of PNMEP28-PLMA87 vesicles at a wavelength of 405 nm. This appears to be an attractive method for RAFT chain-end removal from diblock copolymer nano-objects, particularly those comprising highly hydrophobic cores

From microscopic to macroscopic descriptions of cell\ud migration on growing domains

Cell migration and growth are essential components of the development of multicellular organisms. The role of various cues in directing cell migration is widespread, in particular, the role of signals in the environment in the control of cell motility and directional guidance. In many cases, especially in developmental biology, growth of the domain also plays a large role in the distribution of cells and, in some cases, cell or signal distribution may actually drive domain growth. There is a ubiquitous use of partial differential equations (PDEs) for modelling the time evolution of cellular density and environmental cues. In the last twenty years, a lot of attention has been devoted to connecting macroscopic PDEs with more detailed microscopic models of cellular motility, including models of directional sensing and signal transduction pathways. However, domain growth is largely omitted in the literature. In this paper, individual-based models describing cell movement and domain growth are studied, and correspondence with a macroscopic-level PDE describing the evolution of cell density is demonstrated. The individual-based models are formulated in terms of random walkers on a lattice. Domain growth provides an extra mathematical challenge by making the lattice size variable over time. A reaction-diffusion master equation formalism is generalised to the case of growing lattices and used in the derivation of the macroscopic PDEs

A spectrum of physics-informed Gaussian processes for regression in engineering

Despite the growing availability of sensing and data in general, we remain unable to fully characterize many in-service engineering systems and structures from a purely data-driven approach. The vast data and resources available to capture human activity are unmatched in our engineered world, and, even in cases where data could be referred to as “big,” they will rarely hold information across operational windows or life spans. This paper pursues the combination of machine learning technology and physics-based reasoning to enhance our ability to make predictive models with limited data. By explicitly linking the physics-based view of stochastic processes with a data-based regression approach, a derivation path for a spectrum of possible Gaussian process models is introduced and used to highlight how and where different levels of expert knowledge of a system is likely best exploited. Each of the models highlighted in the spectrum have been explored in different ways across communities; novel examples in a structural assessment context here demonstrate how these approaches can significantly reduce reliance on expensive data collection. The increased interpretability of the models shown is another important consideration and benefit in this context

Mixed configuration-interaction and many-body perturbation theory calculations of energies and oscillator strengths of J=1 odd states of neon

Ab-initio theory is developed for energies of J=1 particle-hole states of neutral neon and for oscillator strengths of transitions from such states to the J=0 ground state. Hole energies of low-Z neonlike ions are evaluated.Comment: 5 pages, 1 figure, 4 table

Leadership training to improve adenoma detection rate in screening colonoscopy: A randomised trial

Objective Suboptimal adenoma detection rate (ADR) at colonoscopy is associated with increased risk of interval colorectal cancer. It is uncertain how ADR might be improved. We compared t