Topical application of silymarin enhances cutaneous wound healing in rats

Abstract Wound healing in a short period with minimum side effects is one of the major goals of medical sciences. Silymarin, an extract from Silybum marianum, has been shown to have antioxidant and anti-inflammatory properties. This study investigates the wound healing activity of silymarin topical formulation in an in experimental model. A 875 mm2 (25 × 35 mm) full-thickness excision was made on the abdominal region of each rat by a surgical blade and the day on which the wound was made considered as day 0. Each rat was treated two times each day. On days 1,4, 8 and 12, the wound area was measured using precise caliber and camera imaging. On day 12, blood samples were collected for the analysis of antioxidant, malondialdehyde and estradiol levels. After 12 days of treatment, rats were sacrificed and abdominal region tissues used for histological analyses. The study showed that topical application of silymarin on wound in rats improved wound healing correlating with less redness, exudates and swelling. Furthermore, in serum of rats treated with silymarin ointment improved antioxidant and estradiol levels, while decreased malondialdehyde levels, a marker of oxidative stress. Histological analyses showed also an improve of novel blood vessels. This effect on angiogenesis correlated with improve nitric oxide synthase expression and epithelial cells after treatment with silymarin. Silymarin ointment represents a promising therapeutic agent for the treatment of wounds through its antioxidant and anti-inflammatory properties

Evaluation of the impact of orally administered carbohydrates on postprandial blood glucose levels in different pre-clinical models

ABSTRACT We developed a pre-clinical model in which to evaluate the impact of orally administered carbohydrates on postprandial blood glucose levels. For this purpose, we compared the effects of different carbohydrates with well-established glycemic indexes. We orally administered (gavage) increasing amounts (0.2, 0.4, 0.6, 0.8, and 1.0 g/kg) of sucrose and lactose to rats which had been fasted for 6 h or 15 h, respectively. In part of the experiments we administered frutose (gavagem). Three different models were compared for measuring postprandial blood glucose levels: a) evaluation of interstitial glucose concentrations by using a real time continuous glucose monitoring system; b) evaluation of glucose levels in blood obtained from the rat tail; c) evaluation of serum glucose levels in blood collected after decapitation. Our results showed that blood obtained from the tails of 15-h fasted rats was the best model in which to evaluate the effect of carbohydrates on postprandial blood glucose levels

Towards self-adaptation planning for complex service-based systems

A complex service-based system (CSBS), which comprises a multi-layer structure possibly spanning multiple organizations, operates in a highly dynamic and heterogeneous environment. At run time the quality of service provided by a CSBS may suddenly change, so that violations of the Service Level Agreements (SLAs) established within and across the boundaries of organizations can occur. Hence, a key management choice is to design the CSBS as a self-adaptive system, so that it can properly plan adaptation decisions to maintain the overall quality defined in the SLAs. However, the challenge in planning the CSBS adaptation is the uncertainty effect of adaptation actions that can variously affect the multiple layers of the CSBS. In a dynamic and constantly evolving environment, there is no guarantee that the adaptation action taken at a given layer can have an overall positive effect. Furthermore, the complexity of the cross-layer interactions makes the decision making process a non-trivial task. In this paper, we address the problem by proposing a multi-layer adaptation planning with local and global adaptation managers. The local manager is associated with a single planning model, while the global manager is associated with a multiple planning model. Both planning models are based on Markov Decision Processes (MDPs) that provide a suitable technique to model decisions under uncertainty. We present an example of scenario to show the practicality of the proposed approach