In this study, the development of an ultrasound method for extraction of phenolic compounds from barley waste using acidic deep eutectic solvents (UAE-DES) was investigated. Optimization of the extraction parameters, which include extraction time, temperature, and ultrasound power (UP), was performed using the One-Factor-at-a-Time (OFAT) experimental design, followed by HPLC-PDA for determination of total quantified phenolic content (TQPC). In addition, the influence of water addition on TQPC was evaluated. The Maximum TQPC obtained was 5.78 mg/g using ChCl: formic acid at a molar ratio (1:2) and optimal conditions of (70 °C, 30 min, 80% UP, 10% water), and 4.67 mg/g, using ChCl: tartaric acid at a molar ratio (1:2) and optimal conditions of (70 °C, 25 min, 100% UP, and 20% water). The obtained TQPC was 5- and 4-fold higher in comparison with 70% methanol and 70% ethanol extraction. LC–MS-qTOF analysis of DES extracts revealed diverse phenolic compounds, while the concentration range of compounds obtained was as follows: ferulic acid (0.86–2.47 mg/g), catechin (0.12–2.16 mg/g), p-coumaric acid (0.12–0.32 mg/g), naringenin (0.54–0.86 mg/g), and apigenin (0.15–0.91 mg/g). SEM analysis confirmed enhanced accessibility of lignocellulose in DES-treated samples. The sustainability of UAE-DES extraction was assessed using AGREE, AGREEprep, CACI, BAGI, and CaFRI green tools. The grade assessment of each tool resulted in scores: 0.63 for AGREE, 0.57 for AGREEprep, 65 for CACI, 82.5 for BAGI, and 72 for CaFRI, indicating a greener extraction performance of UAE-DES in comparison with 70% methanol and 70% ethanol extraction.
IntroductionMercuric ions (Hg2+) are among the most hazardous heavy metal pollutants, posing severe threats to the human reproductive and central nervous systems even at trace concentrations. Although various fluorescent probes for Hg2+ have been reported, most rely on a “turn-off” (fluorescence quenching) mechanism, which often suffers from low sensitivity and susceptibility to interference.MethodsNovel nitrogen-doped fluorescent carbon dots (FL-CDs) were synthesized for the first time via a one-pot hydrothermal method, using natural senna leaf as a green carbon source, and m-phenylenediamine as both the nitrogen dopant and functional monomer.ResultsThis unique precursor combination endows the as-prepared FL-CDs with excellent optical properties. The obtained FL-CDs are spherical with an average size of 2.19 nm, exhibit bright green fluorescence at 518 nm, and possess a high quantum yield of 23.54%. Strikingly, in contrast to the common quenching effect of most heavy metal sensors, the fluorescence of FL-CDs was significantly enhanced upon Hg2+ addition, achieving a desirable “turn-on” response. The probe exhibited exceptional selectivity toward Hg2+ over other metal ions, with a detection limit of 10.65 μmol/L.DiscussionThis work not only introduces a new biomass precursor for the fabrication of carbon dots but also provides a simple, sensitive, and sustainable “turn-on” sensing platform for trace Hg2+ detection. The proposed strategy offers a promising alternative for environmental monitoring and food safety analysis, and also contributes to the rational design of advanced functional materials derived from natural resources.
IntroductionMicro- and nanoplastics (MNPs) are pervasive in the environment and are increasingly being detected in human tissues, including placenta, yet their effects on pregnancy outcome remain poorly understood.MethodsThis study utilized pyrolysis gas chromatography x cyclic ion mobility mass spectrometry (Py-GCxcIMS) to overcome lipid interference and improve quantification of MNPs in human placentas from forty-six participants. Polyethylene (PE), polypropylene (PP), and polystyrene (PS) were targeted for analysis.ResultsMNPs were detected in 26% of placental tissue samples (24/92) and in 41% of participants (19/46), with total polymer concentrations ranging from 0.1 to 12.3 μg/g (mean total of 0.5 μg/g). The variability in microplastic concentrations across the different placental regions highlights the organ’s heterogeneous nature.DiscussionPolypropylene was the most frequently detected, while polystyrene showed the highest mean concentration. Although no direct link to birth outcomes was found, the exploratory analysis suggested sex-specific association in complicated pregnancies (p = 0.071 for males) underscores the need for expanded cohort studies. These results provide evidence of MNP presence in human placental tissue, emphasizing the importance of larger human cohort studies and robust analytical methods to better understand the potential impact MNPs have on pregnancy and fetal health.
In modern scientific and industrial environments, processes are increasingly monitored through dense networks of sensors generating high-dimensional and often, continuous data streams. Process Analytical Technology (PAT), originally developed in the pharmaceutical industry but now widely applied across biotechnology, food production, environmental monitoring, cultural heritage preservation, and healthcare, provides an empowering framework with which to link real-time measurements to critical quality attributes and process parameters, enabling optimal process understanding, control, and optimization. Despite continuing, impressive advances in sensor technology and chemometric modelling, a persistent misconception is that data quantity alone ensures representativity and model reliability. While data quality is important, remaining a critical success factor for PAT, material heterogeneity, sensor placement, sampling frequency, and process sampling interface design together determine how well observed process data variability and the collected data reflect the true system variability without being unduly compromised by the total measurement system errors and uncertainties. This article emphasizes the central role of the Theory of Sampling (TOS) in ensuring representative increment, sample and data acquisition, illustrating the most common sampling pitfalls including over-reliance on data augmentation, poor field-of-view selection, and neglect of temporal dynamics and demonstrates how these factors impact chemometric models across diverse applications. Emerging approaches, such as automated adaptive sampling and digital twins, offer potential to optimize data collection, but their effectiveness still relies fundamentally on informative primary sensors, which must be TOS-compliant, no exceptions. Through article reviews and examples including Raman and near infrared datasets from materials like rocks, coffee, and beer fermentation, we highlight practical strategies for integrating sampling design with sensor deployment. Overall, this study emphasizes the critical need to prioritize representative sampling, as advanced sensor technology and powerful data modelling cannot alone compensate for systematic measurement system bias, thereby ensuring reliable, interpretable, and actionable process insights.
IntroductionBispecific therapeutic fusion proteins require analytical methods capable of detecting and resolving process- and product-related impurities while remaining practical to implement and validate. Such methods are essential for supporting both process development and good manufacturing practice (GMP) -compliant testing.MethodsA sodium dodecyl sulfate capillary gel electrophoresis (CE-SDS) method was developed to separate structurally similar protein species based on differences in the number of N-linked glycosylation sites. The approach leverages glycosylation-dependent electrophoretic mobility to resolve heterodimeric and related molecular species.ResultsThe CE-SDS method effectively separated bispecific protein variants that differed in glycosylation, enabling discrimination between the desired bispecific product and associated impurities. This was confirmed by comparing native and deglycosylated Fc-fusion protein. The method was successfully applied to inform process development decisions aimed at enriching the target bispecific protein and was demonstrated to be suitable for GMP release and stability testing by verifying ICH criteria for method validation.DiscussionThis analytical strategy provides a robust and broadly applicable means of separating heterodimeric and bispecific glycoproteins based on glycosylation differences. The method can be readily extended to other fusion proteins, provided sufficient glycosylation asymmetry exists between constituent polypeptide chains, making it a valuable tool for both development and manufacturing control.
