Electrospun Gelatin Scaffolds with Incorporated Antibiotics for Skin Wound Healing.

Recent advances in regenerative medicine provide encouraging strategies to produce artificial skin substitutes. Gelatin scaffolds are successfully used as wound-dressing materials due to their superior properties, such as biocompatibility and the ability to mimic the extracellular matrix of the surrounding environment. In this study, five gelatin combination solutions were prepared and successfully electrospun using an electrospinning technique.

Bioactivities and Medicinal Value of the Fruiting Body Extracts of Laetiporus sulphureus and Meripilus giganteus Polypore Mushrooms (Agaricomycetes).

In the present investigation methanol and acetone extracts of basidiocarps of mushrooms Laetiporus sulphureus and Meripilus giganteus were evaluated for their antimicrobial, cytotoxic and antioxidant/prooxidant effects. The antimicrobial potential was determined by the microdilution method against ten microorganisms. Cytotoxic effects were evaluated by MTT test, while changes of the redox status parameters (superoxide anion radical, nitrites and reduced glutathione) were determined spectrophotometrically on a human colorectal cancer cell line and human health fibroblasts cells.

Sacubitril/valsartan reverses cardiac structure and function in experimental model of hypertension-induced hypertrophic cardiomyopathy.

This study evaluated the effect of sacubtril/valsartan on cardiac remodeling, molecular and cellular adaptations in experimental (rat) model of hypertension-induced hypertrophic cardiomyopathy. Thirty Wistar Kyoto rats, 10 healthy (control) and 20 rats with confirmed hypertension-induced hypertrophic cardiomyopathy (HpCM), were used for this study. The HpCM group was further subdivided into untreated and sacubitril/valsartan-treated groups.

Computational Modeling on Drugs Effects for Left Ventricle in Cardiomyopathy Disease.

Cardiomyopathy is associated with structural and functional abnormalities of the ventricular myocardium and can be classified in two major groups: hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Computational modeling and drug design approaches can speed up the drug discovery and significantly reduce expenses aiming to improve the treatment of cardiomyopathy. In the SILICOFCM project, a multiscale platform is developed using coupled macro- and microsimulation through finite element (FE) modeling of fluid-structure interactions (FSI) and molecular drug interactions with the cardiac cells.

Application of Machine Learning for Segmentation of the Pulmonary Acinus Imaged by Synchrotron X-Ray Tomography.

To assess the effectiveness of inhalation therapy, it is important to evaluate the lungs' structure; thus, visualization of the entire lungs at the level of the alveoli is necessary. To achieve this goal, the applied visualization technique must satisfy the following two conditions simultaneously: (1) it has to obtain images of the entire lungs, since one part of the lungs is influenced by the other parts, and (2) the images have to capture the detailed structure of the alveolus/acinus in which gas exchange occurs. However, current visualization techniques do not fulfill these two conditions simultaneously.

SILICOFCM platform, multiscale modeling of left ventricle from echocardiographic images and drug influence for cardiomyopathy disease.

Background And Objective: In silico clinical trials are the future of medicine and virtual testing and simulation are the future of medical engineering. The use of a computational platform can reduce costs and time required for developing new models of medical devices and drugs. The computational platform, which is one of the main results of the SILICOFCM project, was developed using state-of-the-art finite element modeling for macro simulation of fluid-structure interaction with micro modeling at the molecular level for drug interaction with the cardiac cells.

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy.

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM.

Synthesis, Characterization and Biological Studies of Organoselenium trans-Palladium(II) Complexes.

Background: Over the years, transition metal complexes have exhibited significant antimicrobial and antitumor activity. It all started with cisplatin discovery, but due to the large number of side effects it shows, there is a growing need to find a new metal-based compound with higher selectivity and activity on more tumors.

Objectives: Two novel trans-palladium(II) complexes with organoselenium compounds as ligands, [Pd(L1)Cl] (L1 = 5-(phenylselanylmethyl)-dihydrofuran-2(3H)-one) and [Pd(L2)Cl] (L2 = 2- methyl-5-(phenylselanylmethyl)- tetrahydrofuran) were synthesized, in the text referred to as Pd-Se1 and Pd-Se2.

Computational and experimental model of transdermal iontophorethic drug delivery system.

The concept of iontophoresis is often applied to increase the transdermal transport of drugs and other bioactive agents into the skin or other tissues. It is a non-invasive drug delivery method which involves electromigration and electroosmosis in addition to diffusion and is shown to be a viable alternative to conventional administration routs such as oral, hypodermic and intravenous injection. In this study we investigated, experimentally and numerically, in vitro drug delivery of dexamethasone sodium phosphate to porcine skin.