An analytical strategy based on the combination of ultrasound assisted flat membrane liquid phase microextraction and a smartphone reader for trace determination of malondialdehyde

Rapid and reliable quantification of urinary malondialdehyde by HILIC-MS/MS: A derivatization-free breakthrough approach

BACKGROUND

The development of fast analytical methods is crucial for the research, discovery, and confirmation of crucial biomarkers. Furthermore, the implementation of fast analytical strategies contributes to efficient and time-effective procedures. In this sense, analysis of malondialdehyde (MDA) has become an important tool for understanding the role of oxidative stress in various diseases and for evaluating the efficacy of therapeutic interventions.

RESULTS

A rapid and robust liquid chromatography tandem mass spectrometry method (HPLC-MS/MS) has been developed to determine endogenous amounts of malondialdehyde (MDA) in human urine without any associated derivatization reaction. MDA was separated in 4 min through a Urea-HILIC column and was analyzed using a triple quadrupole mass spectrometer in negative electrospray ionization mode. With a 50-fold dilution as the only sample pretreatment after alkaline hydrolysis, no matrix effect was present, which allowed for a fast and simple quantification by means of an external standard calibration with a limit of detection of 0.20 ng mL-1. The whole methodology was validated by analyzing unspiked and spiked urine samples from ten healthy individuals and comparing with the results obtained by the standard addition method. MDA was detected in all cases, with natural concentrations varying from 0.11 ± 0.03 to 0.31 ± 0.03 mg g-1 creatinine. Accuracies were found to be satisfactory, ranging from 95 % to 101 %. The proposed method also exhibited good repeatability and reproducibility (RSD<15 %) for four quality control levels.

SIGNIFICANCE

The main significance of this method is the avoidance of a derivatization reaction for the determination of urinary MDA, this constituting a step forward when compared with previous literature. This breakthrough not only streamlines time analysis to less than 5 min per sample but also results in a more robust procedure. Consequently, the method here developed could be applied to subsequent future research involving the determination of MDA as a lipid peroxidation biomarker, where simple, rapid, and reliable methods could represent a significant improvement.

Ultrasound assisted membrane-assisted solvent extraction for the simultaneous assessment of some drugs involved in drug-facilitated sexual assaults by liquid chromatography-tandem mass spectrometry

A simple and highly efficient ultrasound assisted membrane-assisted solvent extraction (MASE) pre-treatment method for urine has been developed and validated for the simultaneous determination of twenty-two drugs involved in drug-facilitated sexual assaults (DFSAs) by liquid chromatography-tandem mass spectrometry. MASE was performed with 4.0 mL of urine (pH adjusted at 12), 400 μL of hexane as an organic solvent inside the polypropylene membrane, and ultrasonication (45 kHz, 120 W) for 10 min. A pre-concentration factor of 40 was achieved after evaporation (N2 stream) and re-dissolution in 100 µL of methanol. Analytes were separated using a Zorbax Eclipse Plus C18 column under gradient elution with aqueous 10 mM NH4HCO3 (pH 8.0) and methanol as mobile phases. Matrix-matched calibrations allowed the assessment of DFSA drugs of quite different octanol-water partition coefficients (Ko/w), from 1.32 101 for pregabalin to 2.45 105 for clomipramine (Log P values from 1.12 (pregabalin) to 5.39 (clomipramine)). The limit of detection (LOD) was between 0.0075 to 0.37 µg L-1, with analytical recoveries ranging from 73 to 103%, and relative standard deviations (RSDs) within the 2-20% range. The applicability of the method was demonstrated after analysing urine samples under forensic investigation.

Miniaturized on-chip electromembrane extraction with QR code-based red-green-blue analysis using a customized Android application for copper determination in environmental and food samples

A miniaturized on-chip electromembrane extraction device with QR code-based red-green-blue analysis was designed to determine copper in water, food, and soil. The acceptor droplet consisted of ascorbic acid as the reducing agent and bathocuproine as the chromogenic reagent. The formation of a yellowish-orange complex was a sign of copper in the sample. Then, the qualitative and quantitative analysis of the dried acceptor droplet was done by the customized Android app that was developed based on image analysis concepts. In this application, principal component analysis was performed on the data for the first time to reduce the three dimensions, red, green, and blue, to one dimension. The effective extraction parameters were optimized. The limit of detection and limit of quantification were 0.1 µg mL^-1. Intra- and inter-assay relative standard deviations ranged between 2.0 and 2.3 % and 3.1-3.7 %, respectively. The calibration range was studied between 0.1 and 25 µg mL^-1 (R² = 0.9814).

Ultra-trace determination of cadmium in water and food samples by a thin-film microextraction using a supported liquid membrane combined with smartphone-based colorimetric detection

A mixture of n-octanol and dithizone was introduced as an effective and novel extraction agent in a thin-film microextraction technique for the pre-concentration of cadmium ions. The extraction agent was immobilized on small pieces of porous polypropylene flat membrane as a supported liquid membrane. The analyte extraction was performed by immersing the modified film in the sample solution, and via a complex formation between the immobilized dithizone on the film and cadmium ions. After the thin-film microextraction process, the colored cadmium-dithizone complex was directly measured by a smartphone colorimetric analysis. Under optimized conditions, the linear dynamic range, the limit of detection, and the limit of quantification were 0.5-300.0, 0.1, and 0.4 μg L^-1, respectively. The developed technique was successfully employed to quantify cadmium ions in water and food samples. The high relative recovery values (95.0-103.0%) along with relative standard deviations of less than 2.5% were obtained for the spiked samples.

Solid supports and supported liquid membranes for different liquid phase microextraction and electromembrane extraction configurations. A review

Liquid phase microextraction (LPME) and electromembrane microextraction (EME) can be considered as two of the most popular techniques in sample treatment today. Both techniques can be configurated as membrane-assisted techniques to carry out the extraction. These supports provide the required geometry and stability on the contact surface between two phases (donor and acceptor) and improve the reproducibility of sample treatment techniques. These solid support pore space, once is filled with organic solvents, act as a selective barrier acting as a supported liquid membrane (SLM). The SLM nature is a fundamental parameter, and its selection is critical to carry out successful extractions. There are numerous SLMs that have been successfully employed in a wide variety of application fields. The latter is due to the specificity of the selected organic solvents, which allows the extraction of compounds of a very different nature. In the last decade, solid supports and SLM have evolved towards "green" and environmentally friendly materials and solvents. In this review, solid supports implemented in LPME and EME will be discussed and summarized, as well as their applications. Moreover, the advances and modifications of the solid supports and the SLMs to improve the extraction efficiencies, recoveries and enrichment factors are discussed. Hollow fiber and flat membranes, including microfluidic systems, will be considered depending on the technique, configuration, or device used.

Musculoskeletal Ultrasound Image-Based Radiomics for the Diagnosis of Achilles Tendinopathy in Skiers

OBJECTIVES

Our study aimed to develop and validate an efficient ultrasound image-based radiomic model for determining the Achilles tendinopathy in skiers.

METHODS

A total of 88 feet of skiers clinically diagnosed with unilateral chronic Achilles tendinopathy and 51 healthy feet were included in our study. According to the time order of enrollment, the data were divided into a training set (n = 89) and a test set (n = 50). The regions of interest (ROIs) were segmented manually, and 833 radiomic features were extracted from red, green, blue color channels and grayscale of ROIs using Pyradiomics, respectively. Three feature selection and three machine learning modeling algorithms were implemented respectively, for determining the optimal radiomics pipeline. Finally, the area under the receiver operating characteristic curve (AUC), consistency analysis, and decision analysis were used to evaluate the diagnostic performance.

RESULTS

By comparing nine radiomics analysis strategies of three color channels and grayscale, the radiomic model under the green channel obtained the best diagnostic performance, using the Random Forest selection and Support Vector Machine modeling, which was selected as the final machine learning model. All the selected radiomic features were significantly associated with the Achilles tendinopathy (P < .05). The radiomic model had a training AUC of 0.98, a test AUC of 0.99, a sensitivity of 0.90, and a specificity of 1, which could bring sufficient clinical net benefits.

CONCLUSIONS

Ultrasound image-based radiomics achieved high diagnostic performance, which could be used as an intelligent auxiliary tool for the diagnosis of Achilles tendinopathy.