Atrial fibrillation (AF) is the most common sustained arrhythmia and a challenging clinical problem encountered in daily clinical practice. There is an increasing body of evidence linking inflammation to a broad spectrum of cardiovascular conditions including AF. Historical evidence supports an association between AF and inflammation and is consistent with the association of AF with inflammatory conditions of the heart, such as myocarditis and pericarditis. AF has been associated with myocardial oxidative stress, and antioxidant agents have demonstrated antiarrhythmic benefit in humans. Increased plasma interleukin (IL)-6, C-reactive protein (CRP), and plasma viscosity support the existence of an inflammatory state among “typical” populations with chronic AF. These indexes of inflammation are related to the prothrombotic state and may be linked to the clinical characteristics of the patients (underlying vascular disease and comorbidities), rather than simply to the presence of AF itself. It has been suggested that inflammation may have a role in the development of atrial arrhythmias after cardiac surgery, and that a genetic predisposition to develop postoperative complications exists. Cytokines can have a prognostic significance; IL-6 levels, CRP, and other cytokines may have prognostic value in AF. Cytokine lowering therapies, statins, angiotensin converting enzyme inhibitors and other anti-inflammatory agents may have a role in the treatment of AF. The present article provides an overview of the evidence linking inflammatory cytokines to AF and their therapeutic and prognostic implications.
In recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived.
The objective of this study was to develop sustained release tablets of glimepiride by wet granulation method based on combination of hydrophilic (HPMC15cps, HPC) and hydrophobic (Ethyl cellulose) polymers. The drug excipient mixtures were subjected to preformulation studies. The tablets were subjected to physicochemical studies, in-vitro drug release, kinetic studies and stability studies. FTIR and DSC studies shown there was no interaction between drug and polymers. The physicochemical properties of tablets were found within the limits. Glimepiride is a first third generation sulphonyl urea agent for the treatment type II diabetes mellitus. The drug release from the optimized formulation was extended for a period of 12 hrs. The kinetic treatment showed that the release of drug follows first order models. The optimized formulations were subjected to stability studies and shown there were no significant changes in drug content, physicochemical parameters and release pattern. Results of the present study indicated the suitability of the above mentioned polymers in the preparation of sustained release formulation of glimepiride.
Monitoring large forest areas is presently feasible with satellite remote sensing as opposed to time-consuming and expensive ground surveys as alternative. This study evaluated, for the first time, the potential of using freely available medium resolution (30 m) Landsat time series data for deforestation monitoring in tropical rainforests of Kalimantan, Indonesia, at sub-annual time scales. A simple, generic, data-driven algorithm for deforestation detection based on a consecutive anomalies criterion was proposed. An accuracy assessment in the spatial and the temporal domain was carried out using high-confidence reference sample pixels interpreted with the aid of multi-temporal very high spatial resolution image series. Results showed a promising spatial accuracy, when three consecutive anomalies were required to confirm a deforestation event. Recommendations in tuning the algorithm for different operational use cases were provided within the context of satisfying REDD+ requirements, depending on whether spatial accuracy or temporal accuracy need to be optimized.
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