the unregulated probiotic market

Background & Aims This narrative review provides an overview of the current regulation of probiotics, with a focus on those used for the dietary management of medical conditions (Medical Foods). Findings The probiotic market has grown rapidly, both for foods and supplements intended to enhance wellness in healthy individuals, and for preparations for the dietary management of disease. Regulation of probiotics varies between regions. Unless they make specific disease-related health claims, probiotics are regulated as food supplements and regulation is focused on the legitimacy of any claims, rather than efficacy, safety and quality. Many properties of probiotics are strain-specific, and safety and efficacy findings associated to specific formulations should not be generalized to other probiotic products. Manufacturing processes, conditions and ingredients are important determinants of product characteristics and changes to manufacturing are likely to give rise to a product not identical to the "original" in efficacy and safety if proper measures and controls are not taken. Current trademark law and the lack of stringent regulation of probiotic manufacturing mean that the trademark owner can commercialize any formulation under the same brand, even if significantly different from the original. These regulatory deficits may have serious consequences for patients where probiotics are used as part of clinical guideline-recommended management of serious conditions such as inflammatory bowel diseases, and may make doctors liable for prescribing a formulation not previously tested for safety and efficacy. Conclusions Current regulation of probiotics is inadequate to protect consumers and doctors, especially when probiotics are aimed at the dietary management of serious conditions

Modulation of cytokine production by carnitine

The ability of carnitine congeners to modulate cytokine production by human peripheral blood mononuclear cells (PBMC) was investigated. Modulation of cytokine production by PBMC of young (30 years of age or younger) and old (70 years of age or older) normal donors was first compared. The PBMC were collected over Ficoll–Hypaque and incubated in the presence of various concentrations of acetyl L-carnitine for 24 h. Subsequently the supernatants were collected and examined for cytokine production. The presence of cytokines in tissue culture supernatants was examined by ELISA. The cytokines measured included IL-1α, IL-1β, IL-2, IL-4, IL-6, TNFα, GM–CSF, and IFNγ. The results showed that at 50 μg/ml of acetyl L-carnitine the most significant response was obtained for TNFα. In this regard four of five young donors responded, but only one of five old donors responded. More recently these studies were expanded to examine the ability of L-carnitine to modulate cytokine production at higher doses, 200 and 400 μg/ml, in young donors. The results of these studies showed that in addition to TNFα, significant production of IL-1β and IL-6 was observed. These preliminary studies provide evidence that carnitine may modulate immune functions through the production of selected cytokines

Immunoregulatory biological response modifiers: effect of cytokines on septic shock

Whole bacteria or bacterial components or their extracts were employed to restore or augment the immune system. Beneficial effects were attained with these agents in treating various diseases. These agents were named biological response modifiers (BRMs) because they regulated certain cellular components of the immune system. The cellular regulation induced by these BRMs was found to be due to cytokines. The cytokines were shown to act directly on the various cellular components and to provide therapeutic benefit in various autoimmune and immune deficiency diseases. Overproduction of specific cytokines however leads to a deleterious effect on the host. Overproduction of tumour necrosis factor (endotoxin, lipopolysaccharide) leads to septic shock. Bacteraemia is the leading cause of overproduction of tumour necrosis factor (TNF). Septic shock in many cases leads to death. Several monoclonal antibodies to lipopolysaccharide (LPS) and anticytokines have demonstrated protection against septic shock

A nonparametric approach for model individualization in an artificial pancreas

The identification of patient-tailored linear time invariant glucose-insulin models is investigated for type 1 diabetic patients, that are characterized by a substantial inter-subject variability. The individualized linear models are identified by considering a novel kernel-based nonparametric approach and are compared with a linear time invariant average model in terms of prediction performance by means of the coefficient of determination, fit, positive and negative max errors, and root mean squared error. Model identification and validation are based on in-silico data collected from the adult virtual population of the UVA/Padova simulator. The data generation involves a protocol designed to produce a sufficient input excitation without compromising patient safety, compatible also with real life scenarios. The identified models are exploited to synthesize an individualized Model Predictive Controller (MPC) for each patient, which is used in an Artificial Pancreas to maintain the blood glucose concentration within an euglycemic range. The MPC used in several clinical studies, synthesized on the basis of a non-individualized average linear time invariant model, is also considered as reference. The closed-loop control performance is evaluated in an in-silico study on the adult virtual population of the UVA/Padova simulator in a perturbed scenario, in which the MPC is blind to random variations of insulin sensitivity in each virtual patient. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved

Direct data-driven model-reference control with Lyapunov stability guarantees

In this work, we introduce a novel data-driven model-reference control design approach for unknown linear systems with fully measurable state. The proposed control action is composed by a static feedback term and a reference tracking block, which are shaped from data to reproduce the desired behavior in closed-loop. By focusing on the case where the reference model and the plant share the same order, we propose an optimal design procedure with Lyapunov stability guarantees, tailored to handle state measurements with additive noise. Two simulation examples are finally illustrated to show the potential of the proposed strategy as compared to the state of the art approaches.Comment: 8 pages, 10 figures, Preprint submitted to the 60th IEEE Conference on Decision and Control (CDC) 202

Direct Data-Driven Model-Reference Control with Lyapunov Stability Guarantees

In this work, we introduce a novel data-driven model-reference control design approach for unknown linear systems with fully measurable state. The proposed control action is composed by a static feedback term and a reference tracking block, which are shaped from data to reproduce the desired behavior in closed-loop. By focusing on the case where the reference model and the plant share the same order, we propose an optimal design procedure with Lyapunov stability guarantees, tailored to handle state measurements with additive noise. Two simulation examples are finally illustrated to show the potential of the proposed strategy as compared to the state of the art approaches.Comment: 8 pages, 10 figures, Preprint submitted to the 60th IEEE Conference on Decision and Control (CDC) 202