Analytical Approach for Detection of Ergosterol in Mushrooms Based on Modification Free Electrochemical Sensor in Organic Solvents

Voltammetry of 7-dehydrocholesterol as a new and useful tool for Smith-Lemli-Opitz syndrome diagnosis

7-Dehydrocholesterol is an essential biomarker of Smith-Lemli-Opitz syndrome, a congenital autosomal recessive disorder. This study shows for the first time that electrochemical oxidation of 7-dehydrocholesterol can be used for its voltammetric determination. Two classes of supporting electrolytes in acetonitrile and a mixture of acetonitrile-water were used: inorganic acids known to promote structural changes of steroids and indifferent electrolytes. Oxidation of 7-dehydrocholesterol at ca +0.8 V (vs. Ag/AgNO₃ in acetonitrile) in 0.1 mol L^-1 NaClO₄ in acetonitrile is useful for its voltammetric detection using common bare electrode materials. Detection limits for 7-dehydrocholesterol lie in the low micromolar range for all the working electrodes, including boron-doped diamond (0.4 μmol L^-1) and disposable thin-film platinum electrodes (0.5 μmol L^-1), which are advantageous because of the low volumes of studied solutions. After Bligh-Dyer extraction, quantification of 7-dehydrocholesterol concentration (boron-doped diamond) or concentration range (thin-film platinum) is easily attainable in artificial serum. The mere knowledge of the concentration range provides clinically valuable information, as 7-dehydrocholesterol levels are employed for SLOS diagnosis as a binary criterion (elevated, tens to hundreds μmol L^-1 in symptomatic/non-elevated, typically bellow 1 μmol L^-1 in healthy individuals in plasma). Moreover, it is shown that 7-dehydrocholesterol (provitamin D₃) and cholecalciferol (vitamin D₃) can be oxidized in 0.1 mol L^-1 HClO₄ in acetonitrile. Under these conditions, their voltammetric response changes dramatically, and their oxidation potential difference transiently increases from 0.08 V to 0.25 V, which should facilitate their simultaneous voltammetric determination. This work constitutes a foundation for a reliable and straightforward method for Smith-Lemli-Opitz syndrome diagnosis and monitoring 7-dehydrocholesterol's biotransformation to cholecalciferol.

Effects of boron-containing compounds in the fungal kingdom

BACKGROUND

The number of known boron-containing compounds (BCCs) is increasing due to their identification in nature and innovative synthesis procedures. Their effects on the fungal kingdom are interesting, and some of their mechanisms of action have recently been elucidated.

METHODS

In this review, scientific reports from relevant chemistry and biomedical databases were collected and analyzed.

RESULTS

It is notable that several BCC actions in fungi induce social and economic benefits for humans. In fact, boric acid was traditionally used for multiple purposes, but some novel synthetic BCCs are effective antifungal agents, particularly in their action against pathogen species, and some were recently approved for use in humans. Moreover, most reports testing BCCs in fungal species suggest a limiting effect of these compounds on some vital reactions.

CONCLUSIONS

New BCCs have been synthesized and tested for innovative technological and biomedical emerging applications, and new interest is developing for discovering new strategic compounds that can act as environmental or wood protectors, as well as antimycotic agents that let us improve food acquisition and control some human infections.

A Review on Recent Advances in the Applications of Boron-Doped Diamond Electrochemical Sensors in Food Analysis

The usage of boron-doped diamond (BDD) material has found to be very attractive in modern electroanalytical methods and received massive consideration as perspective electrochemical sensor due to its outstanding (electro)chemical properties. These generally known facilities include large potential window, low background currents, ability to withstand extreme potentials and strong tendency to resist fouling compared to conventional carbon-based electrodes. As evidence of superiority of this material, couple of reviews describing the overview of various applications of BDD electrodes in the field of analytical and material chemistry has been reported in scientific literature during last decade. However, herein proposed review predominantly focuses on the most recent developments (from 2009 to 2020) dealing with the application of BDD as an advanced and environmental-friendly sensor platform in food analysis. The main method characteristics of analysis of various organic food components with different chemical properties, including additives, flavor and aroma components, phenolic compounds, flavonoids and pesticides in food matrices are described in more details. The importance of BDD surface termination, presence of sp² content and boron doping level on electrochemical sensing is discussed. Apart from this, a special attention is paid to the evaluation of main analytical characteristics of the BDD electrochemical sensor in single- and multi-analyte detection mode in food analysis. The recent achievements in the utilizing of BDD electrodes in amperometric detection coupled to flow injection analysis, batch injection analysis, and high-performance liquid chromatography are also commented. Moreover, actual trends in sample preparation techniques prior to electrochemical sensing in food analysis are referred.

A green liquid chromatography method for rapid determination of ergosterol in edible fungi based on matrix solid-phase dispersion extraction and a core-shell column

Developing a green analytical method for the analysis of components in food samples is an important research aspect of liquid chromatography (LC). The traditional LC method usually consumes a lot of toxic solvent for sample extraction and LC separation. In the current study, a green analytical method for the rapid determination of ergosterol in edible fungi was established. The sample was extracted and purified by matrix solid-phase dispersion (MSPD) with a green solution (ethanol and water). The LC separation was performed using a Poroshell 120 SB-C18 (4.6 × 30 mm, 2.7 μm) column with a green mobile phase (94% ethanol) at a flow rate of 1.0 mL min-1. The detection wavelength was set at 283 nm. The calibration curve of ergosterol showed good linearity (R = 0.9999) within the test range (4.21-25.27 μg mL-1). The RSD of precision was less than 2.0% and the recovery was 100.4% (RSD = 3.23%). The developed method was successfully applied to quantitative analysis of ergosterol in six edible fungi and the contents of ergosterol were in the range of 1.68-4.02 mg g-1. Only 11.5 mL ethanol water solution was used in the sample extraction and LC separation in the newly developed method, and no toxic organic solvents were used. The total analysis time was less than 15.5 min, about 12-14 min for sample extraction and 1.5 min for LC analysis. This method was environmentally friendly and time-saving, which is helpful to improve the quality evaluation of edible fungi.

New method for rapid identification and quantification of fungal biomass using ergosterol autofluorescence

This research reports on the development of a method to identify and quantify fungal biomass based on ergosterol autofluorescence using excitation-emission matrix (EEM) measurements. In the first stage of this work, several ergosterol extraction methods were evaluated by APCI-MS, where the ultrasound-assisted procedure showed the best results. Following an experimental design, various quantities of the dried mycelium of the fungus Schizophyllum commune were mixed with the starchy solid residue (BBR) from the babassu (Orbignya sp.) oil industry, and these samples were subjected to several ergosterol extraction methods. The EEM spectral data of the samples were subjected to Principal Component Analysis (PCA), which showed the possibility to qualitatively evaluate the presence of ergosterol in the samples by ergosterol autofluorescence without the addition of any reagent. In order to assess the feasibility of quantifying fungal biomass using ergosterol autofluorescence, the EEM spectral data and known amounts of fungal biomass were modeled using partial least squares (PLS) regression and a procedure of backward selection of predictors (AutoPLS) was applied to select the Excitation-Emission wavelength pairs that provide the lowest prediction error. The results revealed that the amount of fungal biomass in samples containing interfering substances (BBR) can be accurately predicted with R²CV = 0.939, R²P = 0.936, RPDcv = 4.07, RPDp = 4.06, RMSECV = 0.0731 and RMSEP = 0.0797. In order to obtain an easy-to-understand equation that expresses the relationship between fungal biomass and fluorescence intensity, multiple linear regression (MLR) was applied to the VIP variables selected by the AutoPLS method. The MLR model selected only 2 variables and showed a very good performance, with R²CV = 0.862, R²P = 0.809, RPDcv = 2.18, RPDp = 2.35, RMSECV = 0.137 and RMSEP = 0.138. This study demonstrated that ergosterol autofluorescence can be successfully used to quantify fungal biomass even when mixed with agroindustrial residues, in this case BBR.