Current Analytical Chemistry - Volume 20, Issue 1, 2024

Sarcosine is currently identified as a potential biomarker for prostate cancer. It is n-methyl derivative of glycine, which is naturally present in muscle and body tissues. Studies indicate that a delay in the treatment of prostate cancer is often due to its diagnosis not being possible at earlier stages. Also, plasma and urine samples with increased sarcosine concentration exhibit a higher probability of this cancer development, therefore; it is safe to proceed with them as biomarkers. Correspondingly, a sarcosine biosensor can be used for early detection of this cancer. Driven by this, in this review, we have discussed various types of biosensors for the detection of sarcosine. The review includes an overview of biosensors with their working principle, and discussion of the methodologies used, starting from conventional chromatographic methods to exclusive nanotechnology-based biosensors. This imbibes various techniques involved in the detection of sarcosine from urine and blood samples. We also critically evaluated the different reports for sarcosine detection based on materials used, techniques employed, limit of detection (LOD), linear range, sensitivity, and cost. We believe that this review retains its novelty in providing a vision of existing advancements with intricate details of their features, thus enabling the further development of biosensors for prostate cancer.

Background: Detection and identification of a wide range of drugs, including small peptides, corticosteroids, selective androgen receptor modulators (SARMs), and quaternary ammonium drugs (QADs), are imperative across several domains, particularly in anti-doping analysis, given the potential misuse of these substances in animal sports, there is an urgent demand for an allencompassing screening method to effectively identify these compounds. Objective: To develop a robust and sensitive high-resolution method for simultaneous screening of small peptides, corticosteroids, SARMs, and QADs using liquid chromatography accurate mass spectrometry in post-race urine samples. This method integrates a streamlined single-stage extraction approach, significantly enhancing efficiency and adaptability for screening drugs across various classes. Methods: The method development and validation involved a comprehensive solid-phase extraction protocol, which included a sequential elution for corticosteroids, small peptides, SARMs, and QADs. Chromatographic separation was achieved using a reverse-phase C18 column, and the analysis was performed using liquid chromatography - high-resolution accurate mass spectrometry. Results: The developed method was validated using a selection of drugs representing each class. The method exhibited robustness and sensitivity, enabling the simultaneous screening of the specified drug classes. The flexibility inherent in the proposed extraction and analysis method allows for seamless integration of new drug candidates eliminating the need for method redevelopment. Conclusion: A versatile and effective screening method was successfully developed and validated for the simultaneous detection of small peptides, corticosteroids, SARMs, and QADs. The method's ability for retrospective analysis of emerging drugs using full scan HRMS enhances its utility. This method holds great promise across various fields where accurate and comprehensive drug screening is imperative.

Background: Selective serotonin reuptake inhibitors (SSRIs) are mostly prescribed for the treatment of depression. This study describes the microscale in-microwell formation of blue-colored N-vinylamino-naphthoquinone derivatives of SSRIs upon their reaction with 2,3-dichloro-1,4- naphthoquinone (DCNQ) and acetaldehyde. The reaction was subsequently utilized as a basis for the development of a new simple and sensitive microwell spectrophotometric method (MW-SPM) for the quality control of pharmaceutical formulations of four SSRIs. These SSRIs are fluoxetine (FLU), sertraline (SER), paroxetine (PAR), and reboxetine (REB). Methods: The MW-SPM procedure was performed in 96-microwell transparent plates, and the microplate reader was employed to measure the absorbances of the reaction products at their peak absorbance wavelength of 580 nm. The best conditions for the method were determined. Results: The relations showed good linearity (correlation coefficients were ≥0.9992) in the concentration range of 5 – 600 μg/mL. The limits of detection ranged from 5.20 to 15.58 μg/mL. The precision was deemed acceptable since all cases' relative standard deviation (RSD) values remained below 2.21%. Recovery experiments were conducted to confirm the accuracy of the method, yielding recovery values of at least 97.8%. The MW-SPM method was effectively utilized to analyze SSRIs in both their bulk and pharmaceutical dosage forms, exhibiting acceptable accuracy and precision. The recovery values ranged from 99.4% to 101.0% (with a margin of error of ± 0.5% to 1.6%). The results were comparable with those of the pre-validated reported methods. Four different metric tools evaluated the greenness of the proposed method, and the results proved that the method fulfills the requirements of green analytical approaches. Furthermore, the ability to handle numerous microvolume samples simultaneously in the described method provides it with a high-throughput characteristic. Conclusion: The proposed MW-SPM represents a valuable tool for an efficient analysis of SSRIs in pharmaceutical quality control units.

Background: The current study presents a method for the simultaneous quantification of atractylenolide I, II, and III, together with syringin, syringaresinol-4-O-β-D-glucoside and caffeine in Atractylode macrocephala (AM) rhizomes. Contents of the metabolites, in combination with the metabolomics approach, were used to discriminate AM rhizomes, which were processed by different methods. Methods: An HPLC Agilent 1100 system with a Thermo Hypersil BDS C18 column (L × I.D. 250 mm × 4.6 mm, 5.0 µm particle size) was used for the quantification of the compounds in the AM samples. The detection wavelengths were set up at 220 nm and 280 nm, respectively. A gradient of acetonitrile and water was utilized as the mobile phase. From the quantification results, the process AM rhizomes were discriminated using multivariate statistical methods, such as Principle component analysis and Hierarchical clustering analysis. Results: The contents of atractylenolide I, II, and III, syringin, syringaresinol-4-O-β-D-glucoside, and caffeine in the AM samples were simultaneously quantified. The linear range of each reference compound was selected from 5 to 100 μg/mL, the linearity with R² values varied from 0.9990 to 0.9997, the limits of quantification (LOD) ranged from 0.1 to 0.9 μg/mL, LOQ ranged from 0.2 to 2.6 μg/mL, while the intra- and inter-day recovery distributed between 96.0% and 104.8% indicated the precision and accuracy of the quantification method. These satisfied the criteria FDA standards for bioanalytical method validation. Multivariate statistical results revealed that atractylenolide I was the marker of the alcohol presoaking samples, syringaresinol-4-O-β-D-glucoside, and atractylenolide III were representative compounds for the terra stirring AM rhizomes Conclusion: For the first time, six investigated bioactive compounds in Atractylodes macrocephala were simultaneously quantified using the HPLC-DAD method. About 30 samples in four types of processed rhizomes of A. macrocephala were discriminated using the quantification results in combination with multivariate statistical methods. These results revealed a promising method for discrimination and quality assurance of products from processed AM rhizomes.

Background: Brown coals are recognized as promising sources of rare earth elements (REEs). Rare earths are present in both the mineral and organic parts of brown coal. Objectives: This study was conducted to investigate the influence of preliminary mechanical activation in the process of sample preparation prior to analyzing the concentrations of rare earth elements in brown coal samples of various origins and compositions. Methods: Four coal samples from different deposits in Russia were selected for the study. Samples were treated with mechanical activation, without reagents, or mechanochemical activation, with humic acids added externally as reagents. X-ray phase analysis was carried out with the selected samples. The quantities of rare-earth elements present in the samples were studied by the method of high-sensitivity inductively coupled plasma mass spectrometry (ICP-MS). Results: It was found that the mechanical activation of coal before dissolution in a mixture of nitric and hydrofluoric acids leads to an increase in the determined concentration of rare earth elements. For this study, the expediency of using only nitric acid as an optimal solvent for the elemental analysis of coal samples was shown. The total concentration of all REE after dissolution of nitric acid and mechanochemical activation with humic acid reached 2456 g/t in Vanchin coal, 968 g/t in Azeysky coal, and 24 g/t and 150 g/t in Itatsky and Spetsugli coals, respectively. Conclusion: Mechanical activation and mechanochemical treatment can greatly help to facilitate sample preparation of natural objects, such as coals for elemental analysis, but in some cases, only a change of solvent is sufficient. When developing technology for concentrating rare earth elements from coal involving grinding, it is necessary to take into account the fact that mechanical activation of coal changes its tendency to dissolve, which may affect the results of the analysis and should be taken into account during experiments.

Introduction: This paper first introduces the use of computer-simulated single-band synchronous fluorescence (SF) obtained from experimental excitation and emission fluorescence spectra of a pure compound in solution. The simulation produces a single narrow band with a peak wavelength that identifies the compound. Methods: The method is used to show single peak identification of benzene, chlorobenzene, benzoic acid, phthalic acid, and mellitic acid in water solutions. Synchronous fluorescence spectroscopy (SFS) is a variant of fluorescence technique in which excitation and emission scans are simultaneously acquired and multiplied with a predetermined wavelength difference (Δλ) between the two. Commercial instruments have this option to get the SFS signals. Results: In response to the Δλ selected, the result will be an SFS signal producing a series of peaks that could be assigned to compounds. Instead of running the same experiment with different Δλ values to identify the compounds, our simulation program determines a specific Δλ value that generates a narrow SF band with a distinctive peak wavelength for identification purposes. Conclusion: Finally, binary mixtures of chlorobenzene with each compound in water are prepared. The SFS of the solution is acquired and compared with the SFS bands of the components for identification purposes. With the commercial lamp fluorimeter employed, the limits of detection are obtained at the ng/g concentration level with fluorescence emission. Possible limits of detection at lower concentrations are discussed using a laser source. The presence of these molecules in astrochemical studies is discussed.