Exploring green organic solvents is a global demand. Most of the currently used solvents pose some concerns regarding environmental sustainability and occupational health risks. In this work, propylene glycol was employed for the first time as a green solvent for mobile phase preparation in the reversed phase chromatographic separation of a mixture of two antioxidants, glutathione and ascorbic acid. The slight viscosity of propylene glycol was manipulated by using water as a co-fluidizing agent to facilitate pumping. Method optimization was performed using factorial design experimental Expert 13® Software (Minneapolis, MN, USA) to achieve the maximum resolution and the minimum run time. The reported method was properly validated according to the International Conference on Harmonization criteria at the linearity range of 1–500 µg/mL, with acceptable accuracy and precision for both drugs. The method was effectively applied for the quantification of both drugs in their commercial pharmaceutical formulation. The proposed method was assessed for environmental and operator safety by means of global tools like AGREE and MoGAPI and has proved high degrees of greenness. Propylene glycol has several benign properties, such as low volatility, less toxicity, compatibility with UV detectors and very low flammability, that will soon assemble it as a promising alternative for the conventionally used solvents.

Quality control of herbal medicinal products (HMPs) is challenging due to their multicomponent composition. For most HMPs, chemical reference standards (CRSs) required for traditional chromatographic and spectral analyses are unavailable. According to USP and Ph. Eur., an exception is valerian tincture, for which highly specific CRSs have been developed. The aim of this study was to use principal component analysis (PCA) and the novel two-dimensional diffuse laser scattering (2D-DLS) method to identify HMPs and their aqueous-ethanolic extracts according to their botanical genera without relying on specific marker compounds. Spectral data were compiled into an extensive library covering a wide wavelength range—from 0.02 nm to 15,000 nm. PCA of the spectral data (UV spectrophotometry, fluorimetry, FTIR spectroscopy, and X-ray diffraction) enabled clustering of samples by individual botanical genera. The most significant information for sample differentiation was provided by wavenumbers of 1400, 1180, and 931 cm−1 in the IR spectra and wavelengths of 450 nm and 672 nm in the UV and fluorescence spectra, respectively. During model cross-validation, all “blind samples” were correctly classified by botanical genus, achieving a non-error rate (NER) of 100%. Furthermore, the unique 2D-DLS method was used to rapidly identify tinctures without opening the glass bottles.

Alterations in the expression of the Klotho gene have been associated with chronic kidney disease (CKD), and its potential as an early diagnostic biomarker is currently under active investigation. In this work, we report the development of a highly sensitive, label-free electrochemical DNA-based biosensor for the detection of a 100 mer DNA fragment corresponding to a partial region of Klotho mRNA. The proposed bioplatform integrates mixed self-assembled monolayers (SAMs) and gold nanoparticles for efficient DNA immobilization within a sandwich-type configuration, coupled with impedimetric detection. Different SAM architectures were evaluated by cyclic voltammetry and electrochemical impedance spectroscopy, with the binary monolayer composed of 1-hexadecanethiol (HDT) and the capture probe (CP) exhibiting the best analytical performance. The use of gold nanoparticle-modified screen-printed carbon electrodes (AuNPs–SPCEs) resulted in a 1.4-fold increase in the signal-to-noise ratio compared to screen-printed gold electrodes. Additionally, the incorporation of a blocking step using bovine serum albumin (BSA–HDT–CP–AuNPs–SPCE) enhanced the sensitivity by 1.6-fold compared to the unblocked system. The genosensor displayed a linear response in the concentration range of 3 × 10−10 to 7.5 × 10−8 M, achieving a detection limit of 0.09 nM. Relative standard deviations below 7.5% were obtained for different Klotho concentrations, confirming high intra-assay and intermediary precision. Selectivity assays demonstrated negligible signals for non-complementary sequences, while recovery experiments in spiked human serum samples yielded satisfactory values between 96.5% and 103.4%.

Waste orange peels (WOP) are a major orange processing residue, and they may be a rich source of precious bioactive polyphenols. Amongst the various WOP constituents, hesperidin holds a prominent position as the most abundant polyphenolic metabolite, with proven biological properties. The current work was performed to provide detailed information on the effect of various acid catalysts to assist hesperidin recovery, using an ethanol organosolv treatment. The treatment developed was first examined by comparing inorganic (HCl) and natural organic (oxalic, citric) acids for their influence on process performance, extraction kinetics, and severity. Following this, optimization was accomplished through response surface methodology, and the extracts produced were investigated with respect to their polyphenolic composition and antioxidant characteristics. The HCl-catalyzed treatment, carried out with 70% ethanol/2% HCl, was proven the most efficacious, giving a total polyphenol yield of 30.7 mg gallic acid equivalents per g of dry mass, and it was shown that the treatment yield was related to severity, obeying a power model. Liquid chromatography–tandem mass spectrometry analysis of the extract generated under optimized conditions (170 min, 80 °C) revealed that hesperidin was extensively hydrolyzed into hesperetin 7-O-glucoside and aglycone (hesperetin). Such an effect was very limited with the oxalic acid-catalyzed treatment, whereas citric acid did not affect the original polyphenolic composition. Overall, the HCl-catalyzed treatment was of significantly higher performance, providing a total flavanone yield of 21.22 mg per g dry mass. The results of this investigation may be of value in adjusting treatment settings for (i) increased flavonoid recovery from WOP and (ii) producing extracts enriched in hesperidin and/or its hydrolysis derivatives. Such practical recommendations may assist the establishment of WOP valorization processes in an integrated biorefinery prospect.

A probabilistic–deterministic design of experiments (PDDoE) approach was employed to optimize laser-induced breakdown spectroscopy (LIBS) parameters for the quantitative determination of minor components in lead-based alloys. The PDDoE optimization identified 18 J laser pump lamp energy, 1 µs delay, and 1 µs exposure as optimal conditions, minimizing spectral dispersion (5–8%) and ensuring stable plasma formation. The acquired spectra were subsequently processed in an R-based automated workflow, where Linear, Lasso, and Ridge regression models were used to establish quantitative relationships between normalized line intensities and atomic absorption spectroscopy (AAS) reference data. The resulting models demonstrated high accuracy (R2 = 0.97 for Sn, 0.985 for Sb, 0.982 for Bi, 0.919 for As, and 0.905 for Ag), with prediction errors (RMSE) below 10% and limits of quantification (LOQ) under 0.05 wt.%. Principal component analysis (PCA) applied to 43 historical (19th–20th century) and technogenic samples (19th–20th century) allowed us to isolate clusters of Pb–Sb alloys corresponding to secondary accumulator materials, alongside a diffuse group of nearly pure Pb specimens containing variable minor impurities. The combined PDDoE–LIBS–R analytical framework provides a reproducible, non-destructive, and chemometrically validated methodology for the quantitative characterization and classification of archeological and industrial lead alloys.

Volatile organic compounds (VOCs) emitted from human skin are promising biomarkers for non-invasive health assessment and disease diagnosis. However, efficient collection and sensitive analytical methods for skin VOCs remain challenging. We developed a method for measuring ethanol, acetaldehyde, and acetone from palmar skin using glass cup aqueous sampling followed by headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Compounds were extracted using a carboxen/polydimethylsiloxane fiber by HS-SPME and separated using a DB-1 capillary column within 5 min. The HS-SPME/GC-MS method showed linearity (5–1000 ng/mL, r ≥ 0.990) with detection limits of 0.56, 1.01, and 0.15 ng/mL for ethanol, acetaldehyde, and acetone, respectively. Intra-day and inter-day precision were ≤9.3% and ≤9.7%, with accuracy ranged of 94–110%. Five-minute palm contact with water caused VOC release to increase linearly, and samples remained stable for 24 h at −20 °C. Following ingestion of a 500 mL alcoholic beverage (5% ethanol), ethanol and acetaldehyde emissions peaked at 95 and 24 ng/cm2/min after 1 h, while acetone gradually increased to 1.3 ng/cm2/min after 6 h. This simple, rapid method enables practical assessment of skin VOCs for health monitoring and environmental exposure evaluation.

We have developed mold matrices that can be employed to distinguish between enantiomers (D- and L-glucose) and structural isomers (n- and iso-stearic acid) in matrix-assisted laser desorption/ionization mass spectrometry. Utilizing a temperature-responsive polymer, a molecular structure recognition film was created around metal or semiconductor particles, such as silver (Ag) or cadmium telluride (CdTe), forming the core. Molecules that fit the template structure were selectively ionized. To elucidate the properties of the mold matrix, the relationship between molecular recognition rate and peak intensity of analyte ion was investigated by varying polymer film thickness around the core. The relationship between molecular recognition rate and hydrophobicity of the template molecule was also examined. It was found that increasing the amount of polymer forming the molecular recognition film improved the molecular recognition rate. However, the peak intensity of the analyte ion decreased. It was also found that using highly hydrophobic molecules as template molecules resulted in high molecular recognition rates. In addition, a water-splitting photocatalyst was synthesized and utilized to fabricate the mold matrix. It was applicable to both positive and negative ion generation while recognizing the molecular structure of the analyte.

Estrogens are cholesterol-derived hormones, with four endogenous estrogens being presented in the scientific literature, namely, estradiol, estrone, estriol, and estetrol. In this study, we aim to obtain a complete thermoanalytical profile for the three most important endogenous estrogens: estradiol, estriol, and estrone. To achieve this, the TG/DTG were registered in non-isothermal conditions at five different heating rates (β = 2, 4, 6, 8, and 10 °C min−1). To describe the mechanisms of the degradation processes, a complex kinetic analysis was performed by applying a preliminary method (ASTM E698), two isoconversional methods (Flynn–Wall–Ozawa and Friedman), and the non-parametric kinetic method. The results indicate that estradiol undergoes a single-step degradation process, while estriol and estrone present a complex degradation process. The determination of the shelf life of pharmaceutical products represents a critical factor in ensuring their safety and efficacy. This parameter can be estimated from the activation energy derived from non-isothermal experiments through the application of the Arrhenius equation and appropriate kinetic models.

Nuts such as pecans, almonds, peanuts, pistachios, and walnuts are nutrient-dense foods rich in unsaturated fatty acids and antioxidant compounds. Their regular consumption has been linked to significant health benefits, including reduced risks of cardiovascular disease, diabetes, and high cholesterol. With increasing global demand, ensuring the quality of nuts before they reach consumers is critical. Conventional quality assessment methods dominate the industry but are often subjective, destructive, time-intensive, environmentally burdensome, and laborious. Therefore, there is an urgent need for rapid, non-destructive, and objective alternatives capable of meeting modern quality standards. In this systematic review, we summarize traditional approaches for evaluating nut quality parameters and introduce hyperspectral imaging as a novel technique with promising applications. We examine its use in detecting nut adulteration, assessing chemical composition, identifying defects, and evaluating other quality traits. Limitations of hyperspectral imaging in industrial settings are also discussed, along with potential solutions and future directions. Given the relatively limited research area, approximately 44 relevant studies were critically reviewed. This work provides valuable insights for researchers and industry stakeholders developing innovative technologies for nut quality assessment.

The study evaluated the effect of moderate heating temperatures on physical, mechanical, and spectral properties of bulk flaxseeds and pressed oils. The samples of bulk flaxseeds were measured at 60 mm pressing height and subjected to pretreatment temperatures between 40 °C and 60 °C at 5 °C intervals at a constant heating time of 30 min. The uniaxial compression process, comprising a pressing chamber of a diameter of 60 mm with a plunger, was used for extracting the oil under a load of 300 kN and a speed of 5 mm/min. Prior to the oil extraction, the moisture content of the flaxseeds samples was determined to be 8.15 ± 0.07% d.b., and that of oil content was 40.32 ± 0.02%. Based on the results obtained, porosity, density, oil yield, and oil expression efficiency significantly correlated positively (p-value < 0.05) with the increase in heating temperatures. However, kinematic and dynamic viscosities, compressive stress, deformation energy, and hardness did not significantly correlate (p-value > 0.05) with heating temperature. The study revealed that heating temperatures increased oil yield from 11.54% to 24.18% and oil expression efficiency from 28.62% to 59.96% with the corresponding deformation energy of 0.698 ± 0.011 kJ at 60 °C. The findings suggest that mild thermal pretreatment of flaxseeds improves oil recovery with minimal energy requirement under the linear compression process.