RESUMEN
One new aporphine, dicentrine-ß-N-oxide (1), together with five related known alkaloids dehydrodicentrine (2), predicentrine (3), N-methyllaurotetanine (4), cassythicine (5), and dicentrine (6) were isolated from the leaves of Ocotea puberula (Lauraceae). Antiprotozoal activity of the isolated compounds was evaluated inâ vitro against trypomastigote forms of Trypanosoma cruzi. Among the tested compounds, alkaloid 1 exhibited higher potential with EC50 value of 18.2â µM and reduced toxicity against NCTC cells (CC50 >200â µM - SI>11.0), similar to positive control benznidazole (EC50 of 17.7â µM and SI=10.7). Considering the promising results of dicentrine-ß-N-oxide (1) against trypomastigotes, the mechanism of parasite death caused by this alkaloid was investigated. As observed, this compound reached the plasma membrane electric potential directly after 2â h of incubation and triggered mitochondrial depolarization, which probably leads to trypomastigote death. Therefore, dicentrine-ß-N-oxide (1), reported for the first time in this work, can contribute to future works for the development of new trypanocidal agents.
Asunto(s)
Aporfinas/farmacología , Membrana Celular/efectos de los fármacos , Ocotea/química , Extractos Vegetales/farmacología , Tripanocidas/farmacología , Trypanosoma cruzi/efectos de los fármacos , Animales , Aporfinas/química , Aporfinas/aislamiento & purificación , Línea Celular , Membrana Celular/metabolismo , Potencial de la Membrana Mitocondrial/efectos de los fármacos , Ratones , Estructura Molecular , Extractos Vegetales/química , Extractos Vegetales/aislamiento & purificación , Tripanocidas/química , Tripanocidas/aislamiento & purificaciónRESUMEN
BACKGROUND: Predictive policing and crime analytics with a spatiotemporal focus get increasing attention among a variety of scientific communities and are already being implemented as effective policing tools. The goal of this paper is to provide an overview and evaluation of the state of the art in spatial crime forecasting focusing on study design and technical aspects. METHODS: We follow the PRISMA guidelines for reporting this systematic literature review and we analyse 32 papers from 2000 to 2018 that were selected from 786 papers that entered the screening phase and a total of 193 papers that went through the eligibility phase. The eligibility phase included several criteria that were grouped into: (a) the publication type, (b) relevance to research scope, and (c) study characteristics. RESULTS: The most predominant type of forecasting inference is the hotspots (i.e. binary classification) method. Traditional machine learning methods were mostly used, but also kernel density estimation based approaches, and less frequently point process and deep learning approaches. The top measures of evaluation performance are the Prediction Accuracy, followed by the Prediction Accuracy Index, and the F1-Score. Finally, the most common validation approach was the train-test split while other approaches include the cross-validation, the leave one out, and the rolling horizon. LIMITATIONS: Current studies often lack a clear reporting of study experiments, feature engineering procedures, and are using inconsistent terminology to address similar problems. CONCLUSIONS: There is a remarkable growth in spatial crime forecasting studies as a result of interdisciplinary technical work done by scholars of various backgrounds. These studies address the societal need to understand and combat crime as well as the law enforcement interest in almost real-time prediction. IMPLICATIONS: Although we identified several opportunities and strengths there are also some weaknesses and threats for which we provide suggestions. Future studies should not neglect the juxtaposition of (existing) algorithms, of which the number is constantly increasing (we enlisted 66). To allow comparison and reproducibility of studies we outline the need for a protocol or standardization of spatial forecasting approaches and suggest the reporting of a study's key data items.
RESUMEN
An HPLC-PAD method has been developed in order to evaluate simultaneously the main secondary metabolites, flavonoid glycosides and styrylpyrones, of leaves of Cryptocarya moschata. The sample preparation, consisting of extraction, liquid-liquid extraction and centrifugation, requires minimum sample manipulation but produces high yields with reproducibility, selectivity and simplicity. HPLC on a C18 column presents each class of metabolites grouped and with good resolution of the main compounds. The experimental conditions can be used to study inter- and intra-specific variability of secondary metabolites in Cryptocarya spp.