Perspectives on the Trypanosoma cruzi-host cell receptor interaction

Chagas disease is caused by the parasite Trypanosoma cruzi. The critical initial event is the interaction of the trypomastigote form of the parasite with host receptors. This review highlights recent observations concerning these interactions. Some of the key receptors considered are those for thromboxane, bradykinin, and for the nerve growth factor TrKA. Other important receptors such as galectin-3, thrombospondin, and laminin are also discussed. Investigation into the molecular biology and cell biology of host receptors for T. cruzi may provide novel therapeutic targets

Born to be green: new insights into the economics and management of green entrepreneurship

While the number of green start-ups has steadily increased around the world in response to the environmental problems demanding immediate solutions, there are several unresolved questions on the behaviour and performance of such ventures. The papers in this special issue shed light on these issues by underscoring the role of several factors, such as industry life cycles, knowledge spillovers, institutions, and availability of external finance, in shaping decision-making and firm behaviour in green start-ups. This paper highlights the state-of-the art developments in the literature, discusses the key contributions of the papers put together in this special issue and presents a future research agenda for scholars interested in green entrepreneurship

Characterization of the Rabbit Neonatal Fc Receptor (FcRn) and Analyzing the Immunophenotype of the Transgenic Rabbits That Overexpresses FcRn

The neonatal Fc receptor (FcRn) regulates IgG and albumin homeostasis, mediates maternal IgG transport, takes an active role in phagocytosis, and delivers antigen for presentation. We have previously shown that overexpression of FcRn in transgenic mice significantly improves the humoral immune response. Because rabbits are an important source of polyclonal and monoclonal antibodies, adaptation of our FcRn overexpression technology in this species would bring significant advantages. We cloned the full length cDNA of the rabbit FcRn alpha-chain and found that it is similar to its orthologous analyzed so far. The rabbit FcRn - IgG contact residues are highly conserved, and based on this we predicted pH dependent interaction, which we confirmed by analyzing the pH dependent binding of FcRn to rabbit IgG using yolk sac lysates of rabbit fetuses by Western blot. Using immunohistochemistry, we detected strong FcRn staining in the endodermal cells of the rabbit yolk sac membrane, while the placental trophoblast cells and amnion showed no FcRn staining. Then, using BAC transgenesis we generated transgenic rabbits carrying and overexpressing a 110 kb rabbit genomic fragment encoding the FcRn. These transgenic rabbits – having one extra copy of the FcRn when hemizygous and two extra copies when homozygous - showed improved IgG protection and an augmented humoral immune response when immunized with a variety of different antigens. Our results in these transgenic rabbits demonstrate an increased immune response, similar to what we described in mice, indicating that FcRn overexpression brings significant advantages for the production of polyclonal and monoclonal antibodies

Neonatal Fc Receptor: From Immunity to Therapeutics

The neonatal Fc receptor (FcRn), also known as the Brambell receptor and encoded by Fcgrt, is a MHC class I like molecule that functions to protect IgG and albumin from catabolism, mediates transport of IgG across epithelial cells, and is involved in antigen presentation by professional antigen presenting cells. Its function is evident in early life in the transport of IgG from mother to fetus and neonate for passive immunity and later in the development of adaptive immunity and other functions throughout life. The unique ability of this receptor to prolong the half-life of IgG and albumin has guided engineering of novel therapeutics. Here, we aim to summarize the basic understanding of FcRn biology, its functions in various organs, and the therapeutic design of antibody- and albumin-based therapeutics in light of their interactions with FcRn

Food emulsions with amidated pectin from celery (Apium graveolens var. rapaceum D.C.) tubers

Abstract. Hydrocolloids, especially polysaccharides from traditional plant sources and their derivatives possessed significant emulsifying properties. Pectin was isolated from celery tubers by accelerated “green” method for extraction based on ultrasonic irradiation. Further chemical modification of celery pectin was performed with 4 mol/L NH The amidated celery pectin was obtained with the following characteristics: the degree of esterification (DE) 31%, the degree of 3. amidation (DA) 16%, degree of acetylation (DAc) 2% and anhydrouronic acid content (AUAC) 68%. This modified pectin was incorporated in preparation of model 30, 40 and 50% oil-in-water emulsions. The effect of amidation of celery pectin on the stability of emulsions was investigated. The results showed that amidation increased the emulsifying properties of pectic polysaccharides. It affected also the rheological characteristics of model emulsion. The current study demonstrated preparation of emulsion with low-caloric amidated pectin as proper alternative to the traditional emulsifiers

Latent Regression Analysis

Finite mixture models have come to play a very prominent role in modelling data. The finite mixture model is predicated on the assumption that distinct latent groups exist in the population. The finite mixture model therefore is based on a categorical latent variable that distinguishes the different groups. Often in practice, distinct sub-populations do not actually exist. For example, disease severity (e.g., depression) may vary continuously and therefore, a distinction of diseased and non-diseased may not be based on the existence of distinct sub-populations. Thus, what is needed is a generalization of the finite mixture\u27s discrete latent predictor to a continuous latent predictor. We cast the finite mixture model as a regression model with a latent Bernoulli predictor. A latent regression model is proposed by replacing the discrete Bernoulli predictor by a continuous latent predictor with a beta distribution. Motivation for the latent regression model arises from applications where distinct latent classes do not exist, but instead individuals vary according to a continuous latent variable. The shapes of the beta density are very flexible and can approximate the discrete Bernoulli distribution. Examples and a simulation are provided to illustrate the latent regression model. In particular, the latent regression model is used to model placebo effect among drug-treated subjects in a depression study