4-hydrazinobenzoic acid as a derivatizing agent for aldehyde analysis by HPLC-UV and CE-DAD.

Aldehydes are relevant analytes in a wide range of samples, in particular, food and beverages but also body fluids. Hydrazines can undergo nucleophilic addition with aldehydes or ketones giving origin to hydrazones (a group of stable imines) that can be suitably used in the identification of aldehydes. Herein, 4-hydrazinobenzoic acid (HBA) was, for the first time, used as the derivatizing agent in analytical methodologies using liquid chromatography aiming the determination of low-molecular aldehydes. The derivatization reaction was simultaneously performed along with the extraction process, using gas-diffusion microextraction (GDME), which resulted in a clean extract containing the HBA-aldehyde derivates. The corresponding formed imines were determined by both high-performance liquid chromatography (LC) with UV spectrophotometric detection (HPLC-UV) and capillary electrophoresis with diode array detection (CE-DAD). HBA showed to be a rather advantageous derivatization reagent due to its stability, relatively high solubility in water and other solvents, high selectivity and sensibility, reduced impurities, simple preparation steps and applicability to different separation and/or different detection techniques. Limits of detections (LODs) of the optimized methodologies (in terms of time and pH among other experimental variables) were all below 0.5 mg L-1, using both instrumental techniques. Furthermore, for the first time, the HBA-aldehyde derivatives were analyzed by LC with mass spectrometry (LC-MS), demonstrating the possibility of identification by MS of each compound. The developed methodologies were also successfully applied in the analysis of formaldehyde and acetaldehyde in several alcoholic beverages. This was also the first time GDME was combined with CE, showing that it can be a valuable sample preparation tool for electrophoresis, in particular by eliminating the interference of ions and inorganic constituents present in the samples.

Voltammetric determination of trace amounts of diacetyl at a mercury meniscus modified silver solid amalgam electrode following gas-diffusion microextraction.

A new approach was developed for the determination of trace amounts of diacetyl in food products using gas-diffusion microextraction (GDME) and subsequent detection by differential pulse voltammetry (DPV) at a mercury meniscus modified silver solid amalgam electrode (m-AgSAE). Diacetyl is a vicinal diketone responsible for the buttery aroma in many fermented foods and beverages. Its determination is important not only for evaluation of the final product quality (note of mention: health related concerns were associated with continuous diacetyl exposure) but also to monitor fermentation. GDME, a technique combining gas-diffusion and microextraction, particularly aimed to volatile and semi-volatile analytes, seemed the best way to selective extract diacetyl. A solution of 0.05% o-phenylenediamine (OPDA) prepared in a Britton-Robinson buffer (pH 5.0) was chosen as the extracting solution. This solution simultaneously extracts, pre-concentrates and derivatizes diacetyl to 2,3-dimethylquinoxaline (DMQ), enhancing the extraction selectivity and making the analyte electroactive. After finding the optimum conditions for the extraction process (10min at 60°C with 1.0mL of OPDA at pH 5.0), the DPV measurements at the m-AgSAE were conducted with a scan rate of 7mVs-1, a modulation amplitude of 50mV and a modulation time of 100ms. Under these conditions, the resulting DMQ could be easily measured at a potential of -0.6V vs. Ag|AgCl (3molL-1 KCl). The amalgam electrode keeps the advantages of classic mercury electrodes, like high sensitivity, while being environmentally friendly. The GDME/m-AgSAE produced suitable method features for the determination of low amounts of diacetyl (as DMQ) in alcoholic beverages, and in fact, to the best of our knowledge, the limit of quantification of 0.18µgL-1 is one of the lowest reported in literature.

Determination of ammonia nitrogen in solid and liquid high-complex matrices using one-step gas-diffusion microextraction and fluorimetric detection.

This paper introduces a new method for a one-step determination of ammonia nitrogen (NH3) in high complex solid and liquid samples from the agricultural and livestock sectors. To this end, we developed a simultaneous extraction and fluorimetric labeling of NH3, using gas diffusion microextraction (GDME), followed by the fluorescence measurement under 96-well microplate format. The GDME ensured a selective diffusion of NH3 through a commercial hydrophobic membrane, and confined the acceptor solution, which included the fluorimetric labeling reagent o-phthalaldehyde (OPA). The OPA-NH3 labeling reaction was optimized resorting to a full factorial experimental design, which showed that the reducing agent (Na2SO3) concentration was critical to achieve the highest sensitivity. A similar optimization approach for GDME showed that time and temperature significantly influenced the sensitivity of the assay, and also that the modifications in these two factors could be used to adjust the sensitivity according to the concentrations present in the samples. In our final conditions, it was possible to quantify NH3 in the range between 0.38 and 6.27mgL-1 using a 10min extraction at 25°C in different samples (e.g., corn and grass silages, feces, urine). The developed method showed a high repeatability and reproducibility (intraday and interday relative standard deviations values of 4.5% and 9.5%, respectively) and an adequate limit of detection (0.22mgL-1). This new methodology also highlighted the simplicity and versatility of GDME for the determination of volatile components of high-complex matrices, which will certainly drive future developments in the analysis of environmental and biological samples.

Gas-diffusion microextraction coupled with spectrophotometry for the determination of formaldehyde in cork agglomerates.

In this work, a simple methodology was developed for the extraction and determination of free formaldehyde content in cork agglomerate samples. For the first time, gas-diffusion microextraction was used for the extraction of volatile formaldehyde directly from samples, with simultaneous derivatization with acetylacetone (Hantzsch reaction). The absorbance of the coloured solution was read in a spectrophotometer at 412 nm. Different extraction parameters were studied and optimized (extraction temperature, sample mass, volume of acceptor solution, extraction time and concentration of derivatization reagent) by means of an asymmetric screening. The developed methodology proved to be a reliable tool for the determination of formaldehyde in cork agglomerates with the following suitable method features: low LOD (0.14 mg kg-1) and LOQ (0.47 mg kg-1), r 2 = 0.9994, and intraday and interday precision of 3.5 and 4.9%, respectively. The developed methodology was applied to the determination of formaldehyde in different cork agglomerate samples, and contents between 1.9 and 9.4 mg kg-1 were found. Furthermore, formaldehyde was also determined by the standard method EN 717-3 for comparison purposes; no significant differences between the results of both methods were observed. Graphical abstract Representation of the GDME system and its main components.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.

Computational Alanine Scanning Mutagenesis-An Improved Methodological Approach for Protein-DNA Complexes.

Proteins and protein-based complexes are the basis of many key systems in nature and have been the subject of intense research in the last decades, in an attempt to acquire comprehensive knowledge of reactions that take place in nature. Computational Alanine Scanning Mutagenesis approaches have been extensively used in the study of protein interfaces and in the determination of the most important residues for complex formation, the Hot-spots. However, as it is usually applied to the study of protein-protein interfaces, we tried to modify and apply it to the study of protein-DNA interfaces, which are also crucial in nature but have not been the subject of as much research. In this work, we carry out MD simulations of seven protein-DNA complexes and tested the influence of the variation of different parameters on the determination of the binding free energy terms (ΔΔGbinding) of 78 mutations: solvent representation, internal dielectric constant, Linear and Nonlinear Poisson-Boltzmann equation, Generalized Born model, simulation time, number of structures analyzed, number of MD trajectories, force field used, and energetic terms involved. Overall, this new approach gave an average error of 1.55 kcal/mol, and P, R, F1, accuracy, and specificity values of 0.78, 0.50, 0.61, 0.77, and 0.92, respectively. This improved computational alanine scanning mutagenesis approach may serve as a tool to explore the behavior of this important class of complexes.