Three novel complexes of deprotonated diflunisal (dif) with neocuproine (neo) were synthesized and characterized via elemental, spectral (UV-vis, FTIR, fluorescence, and mass spectrometry), and single-crystal X-ray diffraction analyses. Although the compounds shared a similar composition of [MCl(dif)(neo)], where M represents Zn(II) (1), Co(II) (2) and Cu(II) (3), only 1 and 2 were isostructural, while 3 differed in both the molecular and supramolecular structures. In all three complex molecules, the central atom is coordinated by two nitrogen atoms of neo in a bidentate chelate mode, and one chlorido ligand and dif is bonded in either a monodentate mode via one oxygen atom of the carboxylate in 1 and 2 or in a bidentate chelate mode via both carboxylate oxygen atoms in 3. All three compounds demonstrated remarkable antiproliferative activity against human prostate (PC-3), colon (HCT116) and breast (MDA-MB-468) cancer cell lines with IC50 values in the nanomolar range, with the lowest values observed in the case of PC-3 and MDA-MB-468 with 2 (20.0 nM) and 3 (31.1 nM), respectively. Moreover, complex 2, as the most active, was further investigated for its potential to induce perturbations in the cell cycle of PC-3 cells. The results indicated an induction of caspase-independent apoptosis. The interaction of the complexes with genomic DNA isolated from the respective cancer cell lines was evaluated for the intercalative mode, with binding strength correlated with the antiproliferative activity against PC-3 and MDA-MB-468 cancer cell lines.

Introduction Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown. Objectives To investigate the metabolic stress-response of the leafy liverwort Radula complanata. Methods Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts.Results It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments. Conclusion Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.

For the development of anticancer drugs with higher activity and reduced toxicity, two approaches were combined: preparation of platinum(IV) complexes exhibiting higher stability compared to their platinum(II) counterparts and loading them into mesoporous silica SBA-15 with the aim to utilise the passive enhanced permeability and retention (EPR) effect of nanoparticles for accumulation in tumour tissues. Three conjugates based on a cisplatin scaffold bearing the anti-inflammatory drugs naproxen, ibuprofen or flurbiprofen in the axial positions (1, 2 and 3, respectively) were synthesised and loaded into SBA-15 to afford the mesoporous silica nanoparticles (MSNs) SBA-15|1, SBA-15|2 and SBA-15|3. Superior antiproliferative activity of both free and immobilised conjugates in a panel of four breast cancer cell lines (MDA-MB-468, HCC1937, MCF-7 and BT-474) with markedly increased cytotoxicity with respect to cisplatin was demonstrated. All compounds exhibit highest activity against the triple-negative cell line MDA-MB-468, with conjugate 1 being the most potent. However, against MCF-7 and BT-474 cell lines, the most notable improvement was found, with IC50 values up to 240-fold lower than cisplatin. Flow cytometry assays clearly show that all compounds induce apoptotic cell death elevating the levels of both early and late apoptotic cells. Furthermore, autophagy as well as formation of reactive oxygen species (ROS) and nitric oxide (NO) were elevated to a similar or greater extent than with cisplatin.

IntroductionThe demand to develop efficient and reliable analytical methods for the quality control of nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of its active principles.ObjectiveTo establish a reliable model for the quality control of widely used Senna preparations used as laxatives and assess its phyto-equivalency.MethodsA comparative metabolomics approach via NMR and MS analyses was employed for the comprehensive measurement of metabolites and analyzed using chemometrics.ResultsUnder optimized conditions, 30 metabolites were simultaneously identified and quantified including anthraquinones, bianthrones, acetophenones, flavonoid conjugates, naphthalenes, phenolics, and fatty acids. Principal component analysis (PCA) was used to define relative metabolite differences among Senna preparations. Furthermore, quantitative 1H NMR (qHNMR) was employed to assess absolute metabolites levels in preparations. Results revealed that 6-hydroxy musizin or tinnevellin were correlated with active metabolites levels, suggesting the use of either of these naphthalene glycosides as markers for official Senna drugs authentication.ConclusionThis study provides the first comparative metabolomics approach utilizing NMR and UPLC–MS to reveal for secondary metabolite compositional differences in Senna preparations that could readily be applied as a reliable quality control model for its analysis.

IntroductionThe production of marine drugs in its normal habitats is often low and depends greatly on ecological conditions. Chemical synthesis of marine drugs is not economically feasible owing to their complex structures. Biotechnology application via elicitation represents a promising tool to enhance metabolites yield that has yet to be explored in soft corals.ObjectivesStudy the elicitation impact of salicylic acid (SA) and six analogues in addition to a systemic acquired resistance inducer on secondary metabolites accumulation in the soft coral Sarcophyton ehrenbergi along with the symbiont zooxanthellae and if SA elicitation effect is extended to other coral species S. glaucum and Lobophyton pauciliforum.MethodsPost elicitation in the three corals and zooxanthella, metabolites were extracted and analyzed via UHPLC-MS coupled with chemometric tools.ResultsMultivariate data analysis of the UHPLC-MS data set revealed clear segregation of SA, amino-SA, and acetyl-SA elicited samples. An increased level ca. 6- and 8-fold of the diterpenes viz., sarcophytonolide I, sarcophine and a C28-sterol, was observed in SA and amino-SA groups, respectively. Post elicitation, the level of diepoxy-cembratriene increased 1.5-fold and 2.4-fold in 1 mM SA, and acetyl-SA (aspirin) treatment groups, respectively. S. glaucum and Lobophyton pauciliforum showed a 2-fold increase of diepoxy-cembratriene levels.ConclusionThese results suggest that SA could function as a general and somewhat selective diterpene inducing signaling molecule in soft corals. Structural consideration reveals initial structure–activity relationship (SAR) in SA derivatives that seem important for efficient diterpene and sterol elicitation.

Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little “arm twisting” in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.

SBA-15|Sn3, a mesoporous silica-based material (derivative of SBA-15) loaded with an organotin compound Ph3Sn(CH2)3OH (Sn3), possesses improved antitumor potential against the A2780 high-grade serous ovarian carcinoma cell line in comparison to Sn3. It is demonstrated that both the compound and the nanostructured material are internalized by the A2780 cells. A similar mode of action of Sn3 and SBA-15|Sn3 against the A2780 cell line was found. Explicitly, induction of apoptosis, caspase 2, 3, 8 and 9 activation, accumulation of cells in the hypodiploid phase as well as accumulation of ROS were observed. Interestingly, Sn3 loaded in the mesoporous silica-based material needed to reach a concentration 3.5 times lower than the IC50 value of the Sn3 compound, pointing out a higher effect of the SBA-15|Sn3 than Sn3 alone. Clonogenic potential, growth in 3D culture as well as mobility of cells were disturbed in the presence of SBA-15|Sn3. Such behavior could be associated with the suppression of p-38 MAPK. Less profound effect of Sn3 compared to SBA-15|Sn3 could be attributed to a different regulation of p-38 and STAT-3, which are mainly responsible for an appropriate cellular response to diverse stimuli or metastatic properties.

Correction for ‘Synthesis, cytotoxic and hydrolytic studies of titanium complexes anchored by a tripodal diamine bis(phenolate) ligand’ by Sónia Barroso et al., Dalton Trans., 2014, 43, 17422–17433.

Univariate hypotheses tests such as Student’s t test or variance analysis (ANOVA) can help to answer a variety of questions in metabolomics data analysis. The statistical power of these tests depends on the setup of the experiment, the experimental design and the analytical variance of the actual observations. In this paper, we demonstrate how a well-designed pilot study prior to an experiment with the aim to find differences between e.g. several genotypes, can help to determine the variance at multiple levels ranging from biological variance, sample preparation to instrumental variances. Next, we illustrate how these variances can be used to obtain several parameters (e.g. minimum statistically significant effect, number of required replicates and error probabilities) which influence the design of the actual study. In particular, we are going to sketch how technical replicates can improve the performance of a test, when they are correctly used in the statistical analysis, e.g. with a hierarchical model. Finally, we demonstrate the process of evaluating the trade-off between different experimental designs with different replication strategies. The choice of an experimental design beyond the gut feeling can be influenced by factors such as costs, sample availability and the accuracy of of the tests. We use metabolite profiles of the model plant Arabidopsis thaliana measured on an UPLC-ESI/QqTOF-MS as real-world dataset, but the approach is equally applicable to other sample types and measurement methods like NMR based metabolomics.

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