Control de calidad de residuos de biocidas en frutos de Silybum marianum L.

Analytical studies of organochlorine biocides show that their concentration in the plants (roots) is higherthan in the ground and particularly in the medicinal plants used in the therapy and the pharmacyindustry. The most favorite Bulgarian drugs (Carsil, Tribestan and Nivalin) contain plant extracts andthey have to be analyzed in respect to European Community Directives EEC/76/895 and EEC/90/6421998;In view of that the gas chromatography method for quantitative determination of organochlorine biocides(HCH and isomers, DDT and metabolites) was studied. Plant material from different regions of Bulgaria(fructus from Silybum marianum, L) and Carsil dragee produced by Sopharma Ltd. were analyzed inrespect to European Pharmacopoeia regulations. The method was validated and analytical parametersspecificity, linearity, precision, repeatability and range were studied.Los estudios analíticos de los biocidas organoclorados demuestran que su nivel de concentración en lasraíces de plantas es mayor que la concentración en el suelo, y especialmente en las plantas medicinalesutilizadas en las industrias farmacéutica y medicinal. Los fármacos búlgaros más utilizados (Carsil,Tribestan y Nivalin) contienen extractos de plantas y deben ser analizados de acuerdo con las directivasde la Comunidad Europea EEC/76/895 y EEC/90/642 1998;Por ello, se ha estudiado el método de cromatografía de gases para la determinación cuantitativa debiocidas organoclorados (HCH e isómeros, DDT y metabolitos). Se han analizado conforme a lasregulaciones de la Pharmacopoeia Europea materiales procedentes de plantas de distintas regiones deBulgaria (frutos de Silybum marianum, L) y grageas de Carsil producidas por Sopharma Ltd. El métodoha sido validado y se han estudiado parámetros analíticos de especificidad, linealidad, precisión, replicabilidady rango

VITREOPUPILLARY BLOCK AFTER INTRACAPSULAR CATARACT EXTRACTION

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AMMOS: A Software Platform to Assist in silico Screening

Three software packages based on the common platform of AMMOS (Automated Molecular Mechanics Optimization tool for in silico Screening) for assisting virtual ligand screening purposes have been recently developed. DG-AMMOS allows generation of 3D conformations of small molecules using distance geometry and molecular mechanics optimization. AMMOS_SmallMol is a package for structural refinement of compound collections that can be used prior to docking experiments. AMMOS_ProtLig is a package for energy minimization of protein-ligand complexes. It performs an automatic procedure for molecular mechanics minimization at different levels of flexibility - from rigid to fully flexible structures of both the ligand and the receptor. The packages have been tested on small molecules with a high structural diversity and proteins binding sites of completely different geometries and physicochemical properties. The platform is developed as an open source software and can be used in a broad range of in silico drug design studies

Big Data and AI – A transformational shift for government: So, what next for research?

Big Data and artificial intelligence will have a profound transformational impact on governments around the world. Thus, it is important for scholars to provide a useful analysis on the topic to public managers and policymakers. This study offers an in-depth review of the Policy and Administration literature on the role of Big Data and advanced analytics in the public sector. It provides an overview of the key themes in the research field, namely the application and benefits of Big Data throughout the policy process, and challenges to its adoption and the resulting implications for the public sector. It is argued that research on the subject is still nascent and more should be done to ensure that the theory adds real value to practitioners. A critical assessment of the strengths and limitations of the existing literature is developed, and a future research agenda to address these gaps and enrich our understanding of the topic is proposed

Big Data and AI – A transformational shift for government: So, what next for research?

Big Data and artificial intelligence will have a profound transformational impact on governments around the world. Thus, it is important for scholars to provide a useful analysis on the topic to public managers and policymakers. This study offers an in-depth review of the Policy and Administration literature on the role of Big Data and advanced analytics in the public sector. It provides an overview of the key themes in the research field, namely the application and benefits of Big Data throughout the policy process, and challenges to its adoption and the resulting implications for the public sector. It is argued that research on the subject is still nascent and more should be done to ensure that the theory adds real value to practitioners. A critical assessment of the strengths and limitations of the existing literature is developed, and a future research agenda to address these gaps and enrich our understanding of the topic is proposed

In vitro and in silico studies of the membrane permeability of natural flavonoids from Silybum marianum (L.) Gaertn. and their derivatives

Background: In recent years the number of natural products used as pharmaceuticals, components of dietary supplements and cosmetics has increased tremendously requiring more extensive evaluation of their pharmacokinetic properties. Purpose: This study aims at combining in vitro and in silico methods to evaluate the gastrointestinal absorption (GIA) of natural flavonolignans from milk thistle (Silybum marianum (L.) Gaertn.) and their derivatives. Methods: A parallel artificial membrane permeability assay (PAMPA) was used to evaluate the transcellular permeability of the plant main components. A dataset of 269 compounds with measured PAMPA values and specialized software tools for calculating molecular descriptors were utilized to develop a quantitative structure-activity relationship (QSAR) model to predict PAMPA permeability. Results: The PAMPA permeabilities of 7 compounds constituting the main components of the milk thistle were measured and their GIA was evaluated. A freely-available and easy to use QSAR model predicting PAMPA permeability from calculated physico-chemical molecular descriptors was derived and validated on an external dataset of 783 compounds with known GIA. The predicted permeability values correlated well with obtained in vitro results. The QSAR model was further applied to predict the GIA of 31 experimentally untested flavonolignans. Conclusions: According to both in vitro and in silico results most flavonolignans are highly permeable in the gastrointestinal tract, which is a prerequisite for sufficient bioavailability and use as lead structures in drug development. The combined in vitro/in silico approach can be used for the preliminary evaluation of GIA and to guide further laboratory experiments on pharmacokinetic characterization of bioactive compounds, including natural products

Advances in the Prediction of Gastrointestinal Absorption: Quantitative Structure-Activity Relationship (QSAR) modelling of PAMPA Permeability

Gastrointestinal absorption (GI absorption) is a key absorption, distribution, metabolism, and excretion (ADME) property when the biological effects of substances are evaluated. The Parallel Artificial Membrane Permeability Assay (PAMPA) has emerged as a primary screen for determining passive transcellular permeability, the dominant GI absorption mechanism for many drugs, thus helping with the prioritisation of the most promising lead compounds for pharmacokinetic studies. Recently the PAMPA assay has attracted increasing interest from various other industrial sectors, including cosmetics, where such non-animal models may provide a crucial source of information for in vitro - in vivo extrapolation. This method is also a reliable source of experimental data for Quantitative Structure-Activity Relationship (QSAR) modelling of GI absorption. In this investigation, published QSAR models for PAMPA were reviewed with the aim to summarise and assess critically the current state of the art. The review indicates a relatively small number of QSARs compared to some endpoints, but much consistency within the models. PAMPA permeability increases with hydrophobicity and decreases with the surface area occupied by hydrogen bond acceptor/donor atoms. The models can be applied to screening for bioactive compounds with the potential to pass the gastrointestinal barrier as well as to design new structures with increased PAMPA permeability, thus with better expectations towards improved in vivo GI absorption

Open Babel: An open chemical toolbox

Background: A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendorneutral formats. Results: We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Conclusions: Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license fro

Preclinical Models of Brain Metastasis

Research at the Brain Metastasis Group is supported by MINECO grants MINECO-Retos SAF2017-89643-R (M.V.), Bristol-Myers Squibb- Melanoma Research Alliance Young Investigator Award 2017 (498103) (M.V.), Beug Foundation’s Prize for Metastasis Research 2017 (M.V.), Fundación Ramón Areces (CIVP19S8163) (M.V.), Worldwide Cancer Research (19-0177) (M.V.), H2020-FETOPEN (828972)N