Trends in Analytical Chemistry最新文献

Optical spectroscopy has gained increasing significance over time, offering an impressive revival of this analytical approach for qualitative and quantitative applications. This resurgence spans from homemade test kits to official high-throughput methods employing automatic analyzers in pharmacopoeias and forensic science. This primary methodology is once again poised to provide suitable solutions to contemporary analytical problems through the new possibilities offered by the digital revolution and biocompatible materials, fostering the development of self-standing biosensing and wearable analytical devices. This review begins with the principles of optical-based analysis, rooted in the classical correlation among analyte structural features, well-established chemical reactions, and optical properties. It concludes with applicative examples of assays built under the emerging field of metabolite-based assays, incorporating natural derivatizing molecules and metabolite-derived nanomaterials. Data suggest that a comprehensive exploration of the colorimetric research field, integrated with next-generation technologies, could lead to significant improvements in pharmaceutical analysis and molecular clinical diagnosis.

Hydrogen peroxide (H₂O₂) is a critically important, vital biomarker and hence a highly relevant analyte in a broad range of bioanalytical applications. The most recent trends furthering the ability of its reliable, reproducible, and sensitive quantification include the development of non-biological enzyme mimics, the investigation of smartphone cameras as transducers and detectors, and the continued development of semi-reversible and reversible detection strategies. While the non-biological catalysts offer stability-related advantages over enzymes while providing equally good limits of detection, critical questions regarding toxicity, persistence, (bio)accumulation, and overall environmental footprint need to be answered. In the case of heavy metal-based strategies a replacement by non-toxic, renewable alternatives should be an obvious research need. Signal recording has seen a dramatic change toward smartphones, with their ever-improving computing and image-acquisition abilities. Yet, with the sheer number of different camera and phone models progress can be difficult to assess, as reproducibility and comparability of results and experimental set-ups are too often elusive. In the area of semi-reversible sensors flow injection analysis (FIA) coupled with chemiluminescence (CL) remains the most advanced system. In the case of fully reversible sensors, research points toward oxygen-based sensing to be the most reliable. Analyzing publications from 2018 to 2024, it is not surprising that the important analytical figures of merit of low limits of detection (LODs), broad quantitation ranges, faster response and regeneration times combined with novel (reversible) probes continue to be and should remain central focus of future developments.

Metabolomics offers a unique approach to study biological systems. Liquid chromatography coupled to mass spectrometry serves as a powerful analytical tool to analyze complex mixtures of metabolites. However, successful metabolomic analysis relies on sample preparation. While untargeted analysis traditionally favors non-selective procedures like liquid-liquid extraction (LLE), these methods can compromise analytical performance due to limited analyte enrichment and potential matrix interferences. Solid-phase extraction (SPE) has emerged as a well-established and versatile technique for this purpose, offering advantages over other traditional methods like LLE. This review explores the applications of SPE and solid-phase microextraction (SPME) in LC-MS-based metabolomics. We discuss various modes of SPE, ranging from conventional flow-through cartridges and plates to approaches involving the dispersion of sorbent in a sample, as well as sorbents, their properties, and the diverse geometries of support materials employed in SPME. This review underscores the potential of emerging extraction protocols to further accelerate metabolomics research.

Metabolomics and lipidomics are rapidly growing fields, leading to novel discoveries and advancing the understanding of biological processes at the molecular level. However, designing a proper workflow and choosing from countless options can be challenging, especially for beginners in the field. To address this challenge, we provide a comprehensive overview of metabolomics and lipidomics tools and a step-by-step guide that includes “tips and tricks” based on current metabolomics and lipidomics analysis approaches. We include power analysis, sample collection and preparation, separation and detection of metabolites using primarily liquid chromatography–mass spectrometry (LC–MS), processing of raw instrumental files, quality control, statistical analysis, and data sharing. This guide offers practical insights applicable to diverse research areas, covering all the essential steps in metabolomic and lipidomic profiling.

Food quality and safety (FQS) are crucial aspects of everyone's life and health. With the rapidly advancing field of analytical sciences, there is a growing demand for intuitive, accurate, and swift control of FQS. In recent years, artificial intelligence (AI) has emerged as a great opportunity, offering unparalleled opportunities for extracting information and making decisions from complex or large datasets in areas like chromatography, mass spectrometry, and spectroscopy for the identification of FQS indicators. This review provides a comprehensive overview of AI-based technology's general algorithms for FQS indicator analysis. Additionally, it surveys AI-based methods that are at the forefront of analytical techniques and hold significant potential for enhancing the smart control of FQS indicators. Finally, we highlight key challenges and offer recommendations to accelerate progress towards intelligent FQS control.

Breast cancer, a prevalent global malignancy in women, demands accurate tissue alteration detection for effective diagnosis and treatment. Histology, pivotal in diagnosis, faces challenges like time, limited tissue, and lacking comprehensive three-dimensional views. This review explores X-ray microtomography virtual histology as a complementary tool to address histology's limitations. Particularly, phase-contrast techniques offer non-destructive, high-resolution 3D imaging, surpassing traditional histology constraints. Phase-contrast microtomography provides valuable insights into breast tissue alterations, aiding early cancer detection and enhancing diagnostic precision. The role of synchrotron facilities and alternative validation approaches for clinical settings are discussed. Another significant aspect covered in this review is the global shortage of pathologists, which poses a major challenge in the timely and accurate diagnosis of breast cancer. Phase-contrast microtomography can support pathologists by offering digital imaging capabilities, which enable remote consultation and reduce the dependency on physical tissue sections.

Phosphate metabolites (PMs) are endogenous substances that contain phosphate groups, constituting over half of the small molecules in the body. They play crucial roles in various biological processes. However, the qualitative and quantitative analysis of PMs in biological matrices remains challenging. To elucidate the current status of detection methodologies, this review summarizes existing studies on the extraction and analysis of PMs. Emphasis is placed on the chemical derivatization-based mass spectrometry (CD-MS) strategy, with a detailed examination of the types of CD reagents and the reactive groups in PMs. Additionally, emerging methods potentially applicable to PM analysis are reviewed. Finally, we discuss the challenges and future perspectives in this field. This comprehensive review aims to enhance the understanding of PM analysis, thereby facilitating their exploration in health and disease contexts.

Both organic and inorganic pollutants seriously impact the environment, human health, and ecosystems. Carbon quantum dots (CQDs) and their composites have emerged as promising materials for addressing these environmental issues due to their adaptability, efficiency, and environmentally friendly nature. This study aims to discuss the most recent developments in CQDs-based nanomaterials, focusing on their distinctive structures, synthesis methodologies, characterizations, and applications in environmental science as pollutants extractors and sensors. It studies the potential of nanomaterials based on CQDs for identifying and absorbing contaminants, focusing on their effectiveness in detecting and absorbing hazardous organic chemicals and heavy metals from different environments. The key results include the recognition of distinctive surface characteristics of CQDs-based nanomaterials, which facilitate effective interactions with various pollutants. This enhances their effectiveness in sensor applications and as constituents of extraction materials. This review emphasizes the potential of CQDs-based nanomaterials to transform pollution detection and extraction practices by providing an extensive overview of their utility in environmental science.

Bee pollen is a food supplement that is receiving increasing attention for its nutraceutical and therapeutic properties. However, several uncertainties on the safety of this beekeeping product still exist. The present work addressed this issue through the critical evaluation of 61 studies, published over the 2014–2024 period, and focused on the analysis of pesticides and mycotoxins in bee pollen. A comprehensive examination of the analytical procedures employed for the analysis of these contaminants was performed. Overall, 358 pesticides and 7 mycotoxins were found in bee pollen, with certain compounds being globally distributed and frequently encountered. An overview of the existing European regulations concerning pesticide and mycotoxin levels in food was presented, emphasizing the exclusion of bee pollen from the list of monitored commodities. The findings of the reviewed studies revealed the necessity of gathering more data on bee pollen's contamination and consumption, in order to finally perform reliable risk assessments.

The Mid-Infrared (MIR) spectral regime has gained interest in biosensor research due to the unique excitation of specific molecular vibrational, rovibrational, and rotational modes of biomarkers and biological molecules, offering inherent selectivity for biomarker detection, which is a key asset for biomedical applications. This review focuses on the role of mid-infrared sensing technologies in biomedicine, emphasizing the crucial requirement for accurate detection and real-time monitoring of biological processes in early disease diagnosis and monitoring of disease progression. Highlighted examples provide insight into the effectiveness of MIR optical biosensors for addressing key biomarkers, underscoring their potential impact in areas including but not limited to personalized medicine and clinical research. Furthermore, we discuss how recently designed and implemented microstructures enhance the sensitivity within these application scenarios. These advancements will be complemented by technical challenges inherent to this evolving field, addressing further sensitivity enhancement, device miniaturization, and system integration, along with advanced data analysis. Future strategies discussed in this review contextualize the convergence of MIR sensing, biomedicine, and the integration of artificial intelligence for comprehensive data analysis and interpretation.