Secondary-metabolites fingerprinting of Argania spinosa kernels using liquid chromatography-mass spectrometry and chemometrics, for metabolite identification and quantification as well as for geographic classification.

Argan (Argania spinosa L.) fruit kernels' composition has been poorly studied and received less research intensity than the resulting Argan oil. The Moroccan Argan kernels contain a wealth of metabolites and can be investigated for nutritional and health aspects as well as for economic benefits. Ultra-Performance Liquid Chromatography Mass Spectrometry (UPLC-MS) was employed to trace the geographical origin of Argan kernels based on secondary-metabolite profiles. One-hundred and twenty Argan fruit kernels from five regions ('Agadir', 'Ait-Baha' 'Essaouira', 'Tiznit' and 'Taroudant') were studied. Characterization and quantification of 36 secondary metabolites (33 polyphenolic and 3 non-phenolic) were achieved. Those metabolites are highly influenced by the geographic origin. Then, the untargeted UPLC-MS fingerprint was decomposed by metabolomic data handling tools, such as multivariate curve resolution alternating least squares (MCR-ALS) and XCMS. The two resulting data matrices were pretreated and prepared separately by chemometric tools and then two data fusion strategies (low- and mid-levels) were applied on them. The four data sets were comparatively investigated. Principal component analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Soft Independent Modeling of Class Analogies (SIMCA) were used to classify samples. The exploration or classification models demonstrated a good ability to discriminate and classify the samples in the geographical-origin based classes. Summarized, the developed fingerprints and their metabolomics-based data handling successfully allowed geographical traceability evaluation of Moroccan Argan kernels.

Feasibility study on exhaled-breath analysis by untargeted Selected-Ion Flow-Tube Mass Spectrometry in children with cystic fibrosis, asthma, and healthy controls: Comparison of data pretreatment and classification techniques.

Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS) has been applied in a clinical context as diagnostic tool for breath samples using target biomarkers. Exhaled breath sampling is non-invasive and therefore much more patient friendly compared to bronchoscopy, which is the golden standard for evaluating airway inflammation. In the actual pilot study, 55 exhaled breath samples of children with asthma, cystic-fibrosis and healthy individuals were included. Rather than focusing on the analysis of target biomarkers or on the identification of biomarkers, different data analysis strategies, including a variety of pretreatment, classification and discrimination techniques, are evaluated regarding their capacity to distinguish the three classes based on subtle differences in their full scan SIFT-MS spectra. Proper data-analysis strategies are required because these full scan spectra contain much external, i.e. unwanted, variation. Each SIFT-MS analysis generates three spectra resulting from ion-molecule reactions of analyte molecules with H3O+, NO+ and O2+. Models were built with Linear Discriminant Analysis, Quadratic Discriminant Analysis, Soft Independent Modelling by Class Analogy, Partial Least Squares - Discriminant Analysis, K-Nearest Neighbours, and Classification and Regression Trees. Perfect models, concerning overall sensitivity and specificity (100% for both) were found using Direct Orthogonal Signal Correction (DOSC) pretreatment. Given the uncertainty related to the classification models associated with DOSC pretreatments (i.e. good classification found also for random classes), other models are built applying other preprocessing approaches. A Partial Least Squares - Discriminant Analysis model with a combined pre-processing method considering single value imputation results in 100% sensitivity and specificity for calibration, but was less good predictive. Pareto scaling prior to Quadratic Discriminant Analysis resulted in 41/55 correctly classified samples for calibration and 34/55 for cross-validation. In future, the uncertainty with DOSC and the applicability of the promising preprocessing methods and models must be further studied applying a larger representative data set with a more extensive number of samples for each class. Nevertheless, this pilot study showed already some potential for the untargeted SIFT-MS application as a rapid pattern-recognition technique, useful in the diagnosis of clinical breath samples.

Four Pistacia atlantica subspecies (atlantica, cabulica, kurdica and mutica): A review of their botany, ethnobotany, phytochemistry and pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Pistacia atlantica (wild pistachio) belongs to the Anacardiaceae family, and growing from the Mediterranean basin to central Asia, especially in Iran, Turkey, Iraq and Saudi Arabia where it is extensively used in traditional medicine for a wide range of ailments related to relieving upper abdominal discomfort and pain, dyspepsia and peptic ulcer. OBJECTIVE: Despite the diverse biological activities of P. atlantica, there is no current review summarizing medicinal properties of its subspecies, including cabulica, kurdica and mutica. Thus, this paper aims to explore the current understanding of the chemical, pharmacological, and biochemical properties of the extracts and the main active constituents found in each subspecies of this plant. METHODS: Peer-reviewed articles, using "Pistacia atlantica" as search term (″all fields″), were retrieved from Scifinder, Pubmed, Science direct, Wiley, Springer, ACS, Scielo, Web of Science and other web search instruments (Google Scholar, Yahoo search). Papers published until July 2020 are considered. In addition, various books were consulted that contained botanical and ethnopharmacological information. The information provided in this review is based on peer-reviewed papers in English and French. RESULTS: Phytochemical studies have shown the presence of numerous valuable compounds, including volatile compounds, flavonoids, phenolic compounds, fatty acids, tocopherols and phytosterols. P. atlantica contains also minerals and trace elements, like iron, lead, copper, potassium, sodium and calcium; fatty acids, like oleic, linoleic, and palmitic acid; fat-soluble vitamins, such as α, ß, γ and δ tocopherols; phytosterols, like betasitosterol, stigmasterol, campesterol and Δ5-avenasterol. Crude extracts and isolated compounds from P. atlantica show a wide range of pharmacological properties, such as antimicrobial, antifungal, anti-inflammatory, analgesic, antinociceptive, wound healing, anticancer, cytotoxic, anticholinesterase, antidiabetic, hepatoprotective, urease inhibition, antihypertension, nipple fissure healing, antileishmanial and antiplasmodial activities. However, there are no reports summarizing the P. atlantica bioactivity, its therapeutic value, and the roles played by each of the numerous phytoconstituents. CONCLUSION: Many traditional uses of P. atlantica and its subspecies have now been confirmed by pharmacologic research. Systematic phytochemical investigation of the P. atlantica subspecies and the pharmacological properties, especially the mechanisms of action and toxicology, to illustrate their ethnomedicinal use, to explore the therapeutic potential and support further health-care product development, will undoubtedly be the focus of further research. Therefore, detailed and extensive studies and clinical evaluation of P. atlantica subspecies should be carried out in future for the safety approval of therapeutic applications.

A new potential anti-cancer beta-carboline derivative decreases the expression levels of key proteins involved in glioma aggressiveness: A proteomic investigation.

Gliomas remain highly fatal due to their high resistance to current therapies. Deregulation of protein synthesis contributes to cancer onset and progression and is a source of rising interest for new drugs. CM16, a harmine derivative with predicted high blood-brain barrier penetration, exerts antiproliferative effects partly through translation inhibition. We evaluated herein how CM16 alters the proteome of glioma cells. The analysis of the gel-free LC/MS and auto-MS/MS data showed that CM16 induces time- and concentration-dependent significant changes in the total ion current chromatograms. In addition, we observed spontaneous clustering of the samples according to their treatment condition and their proper classification by unsupervised and supervised analyses, respectively. A two-dimensional gel-based approach analysis allowed us to identify that treatment with CM16 may downregulate four key proteins involved in glioma aggressiveness and associated with poor patient survival (HspB1, BTF3, PGAM1, and cofilin), while it may upregulate galectin-1 and Ebp1. Consistently with the protein synthesis inhibition properties of CM16, HspB1, Ebp1, and BTF3 exert known roles in protein synthesis. In conclusion, the downregulation of HspB1, BTF3, PGAM1 and cofilin bring new insights in CM16 antiproliferative effects, further supporting CM16 as an interesting protein synthesis inhibitor to combat glioma.

LC-method development for the quantification of neuromedin-like peptides. Emphasis on column choice and mobile phase composition.

In this study, the separation of four neuromedin-like peptides is investigated on four different core-shell stationary phases. Moreover, the effect of the mobile phase composition, i.e. organic modifier (acetonitrile and methanol) and additive (trifluoroacetic acid, formic acid, acetic acid, ammonium formate and ammonium acetate) on the chromatographic performance is studied. An improvement in chromatographic performance is observed when using the ammonium salt instead of its corresponding acid as additive, except for the column containing a positively charged surface (C18+). In general, the RP-Amide column provided the highest separation power with different mobile phases. However, for the neuromedin-like peptides of interest, the C18+ column in combination with a mobile phase containing methanol as organic modifier and acetic acid as additive provided narrower and higher peaks. A three-factor, three-level design is applied to further optimize the method in terms of increased peak height and reduced solvent consumption, without loss in resolution. The optimized method was subsequently used to assess the in vitro microdialysis recovery of the peptides of interest. Recovery values between 4 and 8% were obtained using a perfusion flow rate of 2µL/min.

Development and validation of an ion-exchange chromatography method for heparin and its impurities in heparin products.

An anion-exchange liquid chromatography method for the determination of heparin and its impurities (dermatan sulfate and oversulfated chondroitin sulfate) was developed using chemometric-assisted optimization, including multivariate experimental design and response surface methodology. The separation of heparin, dermatan sulfate, and oversulfated chondroitin sulfate (Rs above 2.0) was achieved on a Dionex RF IC IonPac AS22 column with a gradient elution of 10-70% of 2.5 M sodium chloride and 20 mM Tris phosphate buffer (pH 2.1) at a flow rate of 0.6 mL/min and UV detection at 215 nm. Method validation shows good linearity (r > 0.99), acceptable precision (%relative standard deviations <11.4%) and trueness (%recovery of 92.3-103.9%) for all analytes. The limits of detection for dermatan sulfate and oversulfated chondroitin sulfate are equivalent to 0.11% w/w (10.5 µg/mL) and 0.07% w/w (7.2 µg/mL), while the limits of quantification are 0.32% w/w (31.5 µg/mL) and 0.22% w/w (22.0 µg/mL) relative to heparin, respectively. The method is specific for heparin, dermatan sulfate, and oversulfated chondroitin sulfate without interference from mobile phase and sample matrices and could be used for accurate quantitation the drug and its impurities in a single run. Applications of the method reveal contents of heparin between 90.3 and 97.8%. Dermatan sulfate and oversulfated chondroitin sulfate were not detected in any of the real-life samples.