Ningalins, Pyrrole-Bearing Metabolites Isolated from Didemnum spp. Synthesis and MDR-Reversion Activity in Cancer Therapy.

Multi-Drug Resistance (MDR) is one of the most frequent problems observed in the course of cancer chemotherapy. Cells under treatment, tend to develop survival mechanisms to drug-action thus generating drug-resistance. One of the most important mechanism to get it is the over expression of P-gp glycoprotein, which acts as an efflux-pump releasing the drug outside of the cancer cell. A strategy for a succesfull treatment consists in the co-administration of one compound that acts against P-gp and another which acts against the cell during chemotherapy. Ningalins are pyrrole-containing naturally occurring compounds isolated mainly from the marine tunicate Didemnum spp and also they are some of the top reversing agents in MDR treatment acting on P-gp. Considering the relevance displayed for some of these isolated alkaloids or their core as a drug for co-administration in cancer therapy, all the total synthesis described to date for the members of ningalins family are reviewed herein.

Metabolomics as a tool for geographic origin assessment of roasted and green coffee beans.

Coffee is widely consumed across the globe. The most sought out varieties are Arabica and Robusta which differ significantly in their aroma and taste. Furthermore, varieties cultivated in different regions are perceived to have distinct characteristics encouraging some producers to adopt the denomination of origin label. These differences arise from variations on metabolite content related to edaphoclimatic conditions and post-harvest management among other factors. Although sensory analysis is still standard for coffee brews, instrumental analysis of the roasted and green beans to assess the quality of the final product has been encouraged. Metabolomic profiling has risen as a promising approach not only for quality purposes but also for geographic origin assignment. Many techniques can be applied for sample analysis: chromatography, mass spectrometry, and NMR have been explored. The data collected is further sorted by multivariate analysis to identify similar characteristics among the samples, reduce dimensionality and/or even propose a model for predictive purposes. This review focuses on the evolution of metabolomic profiling for the geographic origin assessment of roasted and green coffee beans in the last 21 years, the techniques that are usually applied for sample analysis and also the most common approaches for the multivariate analysis of the collected data. The prospect of applying a wide range of analytical techniques is becoming an unbiased approach to determine the origin of different roasted and green coffee beans samples with great correlation. Predictive models worked accurately for the geographic assignment of unknown samples once the variety was known.