The window of opportunity: A relevant concept for axial spondyloarthritis

The window of opportunity is a concept critical to rheumatoid arthritis treatment. Early treatment changes the outcome of rheumatoid arthritis treatment, in that response rates are higher with earlier disease-modifying anti-rheumatic drug treatment and damage is substantially reduced. Axial spondyloarthritis is an inflammatory axial disease encompassing both nonradiographic axial spondyloarthritis and established ankylosing spondylitis. In axial spondyloarthritis, studies of magnetic resonance imaging as well as tumor necrosis factor inhibitor treatment and withdrawal studies all suggest that early effective suppression of inflammation has the potential to reduce radiographic damage. This potential would suggest that the concept of a window of opportunity is relevant not only to rheumatoid arthritis but also to axial spondyloarthritis. The challenge now remains to identify high-risk patients early and to commence treatment without delay. Developments in risk stratification include new classification criteria, identification of clinical risk factors, biomarkers, genetic associations, potential antibody associations and an ankylosing spondylitis-specific microbiome signature. Further research needs to focus on the evidence for early intervention and the early identification of high-risk individuals.

Avaliação do extrato de Momordica charantia em Salmonella typhimurium: Mutagenicidade e antimutagenicidade

In the last years some natural products has been described as supressors of the mutagenic process in bacteria, the antimutagenics. The literature reference that in most of the countries, the population makes use of medicinal plants. The plant Momordica charantia (Cucurbitaceae) is original from Africa being used popularly as purgative, antirheumatic and for skin problems, burns and hemorrhoids. The present work had as objective to evaluate the mutagenic and antimutagenic activities of the ethanolic extract of M. charantia in Salmonella/microsome assays using TA100, TA98 and TA102 strains. It was verified that the extract did not present mutagenic activity when evaluated in different concentrations (0.64, 1.27, 2.55 and 3.84 mg/plate) but acted as antimutagenic agent against the mutations induced by the sodium azide (TA100,-S9), 4-nitro-phenylenediamine (TA98, -S9), daunomycin (TA102, +S9) 2-anthramine (TA100 and TA98, +S9) and 2-aminofluorene (TA102, +S9). When the metabolic activation (+S9) was used, the percentage of inhibition of the mutagenicity varied in the range of 31%-96%, while in absence of metabolizing system (-S9), the maximum percentage of inhibition of the mutagenicity was 44%. In that way, we can conclude that the metabolites found in the extract has potential to protect the genetic material against the damages induced by different chemical agents.

Lyprinol : is it a useful anti-inflammatory agent?

The New Zealand green lipped mussel preparation Lyprinol is available without a prescription from a supermarket, pharmacy or Web. The Food and Drug Administration have recently warned Lyprinol USA about their extravagant anti-inflammatory claims for Lyprinol appearing on the web. These claims are put to thorough review. Lyprinol does have anti-inflammatory mechanisms, and has anti-inflammatory effects in some animal models of inflammation. Lyprinol may have benefits in dogs with arthritis. There are design problems with the clinical trials of Lyprinol in humans as an anti-inflammatory agent in osteoarthritis and rheumatoid arthritis, making it difficult to give a definite answer to how effective Lyprinol is in these conditions, but any benefit is small. Lyprinol also has a small benefit in atopic allergy. As anti-inflammatory agents, there is little to choose between Lyprinol and fish oil. No adverse effects have been reported with Lyprinol. Thus, although it is difficult to conclude whether Lyprinol does much good, it can be concluded that Lyprinol probably does no major harm.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.