High-resolution mass spectrometry (HRMS) enables non-targeted detection of drugs and metabolites in complex matrices. Phase II metabolites—especially glucuronides—are often the only detectable biomarkers in late or postmortem samples but are underrepresented in commercial libraries. This work pursued the prediction of phase II-glucuronide conjugates in diluted urine samples by non-targeted/targeted LC-HRMS workflows. A simply “dilute-and-shoot” qualitative UHPLC-HRMS/MS method (Q Exactive HF, ddMS2) was integrated with Compound Discoverer® software for data processing. The workflow incorporated predictive strategies such as exact mass suspect lists, Structured Query Language (SQL)-based filters, compound-class and diagnostic neutral-loss rules (including the characteristic loss of 176.0321 Da for glucuronides) and MS/MS confirmation using both in-house and public spectral libraries. An additional part of the application’s performance assessment involved its validation for diluted urine sample. A qualitative validated method for more than two hundred drugs in urine samples was performed, including the method’s selectivity/specificity, limit of identification, matrix effects, and potential carryover. Most analytes fulfilled the qualitative acceptance criteria, with more than 60% successfully identified at a concentration of at least 2.5 ng/mL. Matrix effects were within acceptable limits for most compounds, and no severe ion suppression was observed. A non-targeted workflow was applied to real forensic samples (n = 16), allowing a reduction of approximately 66,800 detected features to 225 glucuronide candidates, while a targeted workflow based on exact mass lists yielded 31 high-confidence identifications. Characteristic neutral losses and diagnostic fragment ions led to the tentative identification of some glucuronide phase II metabolites such as mirtazapine–glucuronide, morphine-6–glucuronide, and glucuronide conjugates of benzodiazepines and synthetic opioids. In conclusion, the integration of biotransformation knowledge with HRMS-based predictive filtering allows for the efficient and hydrolysis-free detection of glucuronide metabolites, thereby extending detection windows and enhancing toxicological interpretation in complex forensic scenarios. This adaptable and library-independent workflow also facilitates retrospective data mining, making it suitable for the identification of emerging substances and newly characterized metabolites.

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%.

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.

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants that tend to accumulate in solid matrices such as sewage sludge, raising concerns regarding their fate and potential ecological risks. This study aimed to develop and validate a robust analytical method for the accurate determination of PFAS in dehydrated sludge. A liquid chromatography–tandem mass spectrometry (LC–MS/MS) method was optimized for 28 PFAS, including perfluoroalkyl carboxylic acids (PFCAs) and sulfonic acids (PFSAs). Solid–liquid extraction with basic methanol was followed by cleanup using a cartridge packed with ferrite and sodium sulfate to remove moisture and particulate interferences. Chromatographic separation was performed with an Avantor® ACE® PFAS Delay column coupled to an Agilent triple quadrupole MS operating in negative electrospray ionization mode. The method achieved excellent sensitivity (MDL < 0.02 µg/g dry weight for most compounds), satisfactory precision (RSD < 15%), and recoveries between 80–118%. Optimization of mobile phase additives, gradient conditions, and MS parameters enhanced chromatographic resolution and signal-to-noise ratio. The validated method demonstrates high reliability for PFAS determination in complex solid matrices and can be applied as a valuable tool for environmental monitoring and risk assessment of sludge management practices.

In modern circular-economy value chains, wood is frequently processed into fines, chips, or powders—forms in which anatomical features are no longer visible, rendering traditional visual identification methods ineffective. This study introduces a rapid, non-destructive attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy approach, combined with chemometric modeling, to address this challenge by enabling both the classification and compositional profiling of processed wood fractions. Using full-spectrum ATR-FTIR data, partial least squares discriminant analysis (PLS-DA) models achieved high-accuracy classification of wood by type, species, and provenance, with sensitivity and specificity reaching up to 1.00. In addition, PLS and backward interval BiPLS models predicted total lignin, acid-soluble lignin, and extractives with strong performance (R2 > 0.90, RPD > 2). Interval selection further enhanced prediction accuracy by reducing RMSEP by up to 30%, improving model stability for real-world application. By replacing slow, reagent-intensive wet chemistry with a rapid, green, and scalable technique, the presented methodology provides a valuable tool for authentication, quality control, and resource optimization when dealing with mechanically processed or recycled wood.

This research introduces a novel synthetic method for introducing highly luminescent silver nanoclusters (AgNCs). The technique relies on coffee Arabica seed extraction (CSE), which is the focus of this study. Our developed and manufactured ecologically friendly approach has enhanced the selectivity of AgNCs for Hg(II) ions. The coffee extract was employed in the synthesis process to stabilize and enhance the quantity of AgNCs generated. Various advanced techniques were used to characterize the AgNCs precisely in their prepared condition concerning size, surface modification, and composition. The fluorescence quenching of the AgNCs was the mechanism via which the CSE-AgNCs reacted to the principal metal ions in the experiment. Using this sensing methodology, a very accurate and selective sensing method is provided for Hg(II) in the dynamic range of 0.117 µM to 1.4 µM, with a limit of detection (LOD) equal to 35.21 nM. Comparative research was conducted to determine how selective CSE-AgNCs are for Hg(II) ions compared to other ions. Consequently, a notable degree of selectivity of AgNCs towards these Hg(II) metal ions was achieved, allowing the sensitive detection of Hg(II) metal ions, even their interfering metal ions, in the environment. AgNCs can detect Hg(II) at acceptable values within the nanomolar range. Based on their characteristics, Hg(II) ions were detected in real samples using CSE-AgNCs.

Tropaeolum majus L. is an edible plant known for its therapeutic and medicinal effects, as it possesses bioactive compounds (polyphenols, glucosinolates, fatty acids) and has various biological activities, which makes it interesting and makes it the research objective of this work. The aim of this study was to extract the phenolic compounds present in the T. majus plant by maceration and ultrasound-assisted extraction techniques using two solvents: 80% ethanol and water. In vitro digestion was performed to see how stable the phenolic components are after digestion. An LC-MS/MS instrument was used to identify and quantify the phenolic components. The highest extraction yield for the T. majus extract was obtained when 80% ethanol was used as the solvent after ultrasound-assisted extraction (32.63 ± 2.28 mg/0.5 g fresh material), while the opposite was true for the T. majus extract when water was used as the solvent and maceration as the technique (21.00 ± 3.26 mg/0.5 g fresh material). However, water extracted more phenolic components for identification. In general, the major compounds before in vitro digestion with commercial enzymes and with 80% ethanol and water as the solvents were p-hydroxybenzoic acid, protocatechuic acid, p-coumaric acid, caffeic acid and chlorogenic acid. After in vitro digestion using both solvents and extraction procedures, the stable phenolic compounds were p-hydroxybenzoic acid (>67%) and p-coumaric acid (>35%). Caffeic acid and quinic acid were not detected after digestion. The stability of certain phenolic components could influence the use of such extracts as dietary supplements with beneficial effects on human health, making them interesting for the general population.

This study investigated the effect of surface treatments on the electrochemical performance of 3D-printed electrodes for versatile applications. The conductive filament was obtained from a mixture of polylactic acid (PLA) and carbon black (CB) at a 7:3 ratio (PLA/CB) dispersed in acetic acid and dichloroethane (3:1) medium. The treatments used were HNO3, NaOH, DMF (immersion for 30, 30, and 15 min, respectively), and electrochemical activation (amperometry 150 s, 1.8 V). In general, the treatments allow greater exposure of the conductive material and active sites present on the sensor surface. This was confirmed using cyclic voltammetry and electrochemical impedance spectroscopy. The analyses were conducted with a 0.10 M KCl solution containing the redox pair ferricyanide/ferrocyanide 5.00 mmol L−1. Based on the results obtained, the electroactive area, kinetic constant and resistance to electron transfer were determined for each treatment. The treatment in basic medium stood out as the treatment that was most appropriate for the device used in this work. The device was also tested for its potential in the analysis of acetaminophen, demonstrating satisfactory results permitting the application of 3D-SBasic in the analysis of acetaminophen.

Serial crystallography (SX) determines the crystal structures of target molecules at room temperature with minimal radiation damage. During SX data collection, the stable delivery of many microcrystals to the X-ray interaction point is crucial for efficient sample consumption and effective beamtime usage. Most microcrystal delivery techniques for SX require sophisticated devices or specialized techniques, which can be challenging for data collection. This review introduces a straightforward method that delivers microcrystal samples in SX experiments using a commercially available syringe and syringe pump. This method does not require specialized skills for sample delivery and can be tested in the laboratory prior to SX data collection at the beamline. Advantages and disadvantages of this method are also discussed, along with various application cases. This straightforward sample delivery approach is concluded to facilitate efficient SX data collection.

The development of screen-printed electrochemical sensors represents a rapidly expanding research field with great potential for applications in the rapid and sensitive determination of drugs in complex matrices. This work presents a review of the state-of-the-art examples of this technology, focusing on its application in real matrices such as water, pharmaceutical formulations, and biological fluids. We discuss the main materials used in developing conductive inks, highlighting their properties and influence on sensor performance. The characterization of materials and sensors is crucial to ensure the reproducibility and reliability of results. Additionally, we address the challenges associated with the application of these sensors in complex matrices, such as interferences from other components and the need for sample pretreatment. Finally, we present future perspectives for developing screen-printed electrochemical sensors, with an emphasis on new technologies and materials that can improve the sensitivity, selectivity, and stability of these devices.