Quantification of gliadin levels to the picogram level by flow cytometry

Celiac disease is a widely prevalent enteropathy caused by intolerance to gliadin, one of the gluten proteins. We developed two methods for the analysis of gliadin levels. Both methods use flow cytometry and rat antibodies against a 16-residue peptide of gliadin. The peptide is common to the alpha-, beta-, gamma-, and omega-gliadins

Media, Participation, and Social Change

Introduction to special issue

Age influenced cattle serum antigen detected by autoantibodies

International audienc

Microbiota–Liver Diseases Interactions

: Gut microbiota regulates essential processes of host metabolism and physiology: synthesis of vitamins, digestion of foods non-digestible by the host (such as fibers), and-most important-protects the digestive tract from pathogens. In this study, we focus on the CRISPR/Cas9 technology, which is extensively used to correct multiple diseases, including liver diseases. Then, we discuss the non-alcoholic fatty liver disease (NAFLD), affecting more than 25% of the global population; colorectal cancer (CRC) is second in mortality. We give space to rarely discussed topics, such as pathobionts and multiple mutations. Pathobionts help to understand the origin and complexity of the microbiota. Since several types of cancers have as target the gut, it is vital extending the research of multiple mutations to the type of cancers affecting the gut-liver axis

Dynamics of a structured slug population model in the absence of seasonal variation

We develop a novel, nonlinear structured population model for the slug Deroceras reticulatum, a highly significant agricultural pest of great economic impact, in both organic and non-organic settings. In the absence of seasonal variations, we numerically explore the effect of life history traits that are dependent on an individual's size and measures of population biomass. We conduct a systematic exploration of parameter space and highlight the main mechanisms and implications of model design. A major conclusion of this work is that strong size dependent predation significantly adjusts the competitive balance, leading to non-monotonic steady state solutions and slowly decaying transients consisting of distinct generational cycles. Furthermore, we demonstrate how a simple ratio of adult to juvenile biomass can act as a useful diagnostic to distinguish between predated and non-predated environments, and may be useful in agricultural settings

Kinetic theory of age-structured stochastic birth-death processes

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but are unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Stochastic theories that treat semi-Markov age-dependent processes using, e.g., the Bellman-Harris equation do not resolve a population's age structure and are unable to quantify population-size dependencies. Conversely, current theories that include size-dependent population dynamics (e.g., mathematical models that include carrying capacity such as the logistic equation) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new, fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a Bogoliubov-–Born–-Green–-Kirkwood-–Yvon-like hierarchy. Explicit solutions are derived in three limits: no birth, no death, and steady state. These are then compared with their corresponding mean-field results. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution