Background : Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical tool in metabolomics, but it is often hindered by the high cost and technical complexity of the machines, limiting its clinical and point-of-care applications. Recent advances in benchtop NMR technology have sought to overcome these barriers by providing more compact, affordable, and user-friendly instruments. This systematic review aims to assess the potential of benchtop NMR in clinical metabolomics, highlighting its practical advantages, current applications, and technological challenges relative to high-field systems. Methods: For this systematic review we searched Web of Science and PubMed databases to identify studies employing benchtop NMR spectroscopy in clinical and biomedical applications. The review focuses on works that evaluated metabolic profiling in human and animal disease contexts, compared benchtop and high-field performance, and utilized advanced data analysis methods, including multivariate and machine learning approaches. Results: Among the 74 records identified, 15 research articles were eligible, including 11 studies involving human biospecimens and 4 studies concerning animal samples. The selected works were published between 2018 and 2025. These studies demonstrated the potential clinical utility of low-field NMR in differentiating disease states such as tuberculosis, type 2 diabetes, neonatal sepsis, and chronic kidney disease, achieving diagnostic accuracies comparable to high-field instruments. Conclusions: Although limited by lower sensitivity and spectral resolution, benchtop NMR represents a significant step toward the democratization of NMR-based metabolomics. Continued hardware development, improved pulse sequences, and the integration of artificial intelligence for spectral processing and modeling are expected to enhance its analytical power and accelerate its clinical adoption.

Phytodepuration occurs in the plant-mediated remediation processes exploited to remove pollutants from wastewater, and Phragmites australis is one of the most used plants. This goal is achieved using constructed wetlands (CW), which are engineered systems designed to mimic the natural processes of pollutants removal. The aim of this work was to characterize the bacterial communities associated to P. australis, soils, and permeates of the CW of Calice (Prato, Italy), to evaluate the possible effect of wastewaters on the CW bacterial communities, through a next-generation sequencing-based approach. A total of 122 samples were collected from different tissues of P. australis (i.e., roots, aerial parts, and stem), soil (i.e., rhizospheric and bulk soil), and permeates, and analyzed. All samples were collected during five sampling campaigns, with the first one performed before the activation of the plant. Obtained results highlighted a specific microbiota of P. australis, conserved among the different plant tissues and during time, showing a lower alpha diversity than the other samples and not influenced by the more complex and variable environmental (soils and permeates) bacterial communities. These data suggest that P. australis is able to select and maintain a defined microbiota, a capacity that could allow the plant to survive in hostile environments, such as that of CW.

Background/Objectives: Astrocytes play a critical role in maintaining brain homeostasis and are increasingly recognized as active contributors to neurodegenerative processes. Metabolic dysfunction in astrocytes has been implicated in the onset and progression of Alzheimer’s disease (AD), yet the underlying metabolic alterations remain poorly characterized. Methods: We used an optimized protocol for untargeted metabolomic profiling of both intracellular and extracellular compartments of primary human astrocytes derived from AD patients and healthy subjects (HS) using ¹H nuclear magnetic resonance (NMR) spectroscopy. Cells were treated with oligomeric Aβ_1-42 to model pathological conditions. Results: Aβ_1-42 treatment induced intracellular metabolic alterations in both AD and HS astrocytes, including a consistent reduction in phosphocreatine, potentially indicating impaired energy-buffering capacity. Notably, a decrease in β-alanine was observed only in AD astrocytes, suggesting alterations in carnosine-related antioxidant defence. Analysis of conditioned media revealed differential responses between groups: AD astrocytes showed increased extracellular levels of 2-oxoglutarate, citrate, and glycine, whereas HS astrocytes exhibited reduced extracellular levels of leucine and isoleucine, suggesting distinct adaptive metabolic responses to Aβ-induced stress. However, none of these differences remained statistically significant after correction for multiple testing. Conclusions: These findings suggest that NMR-based metabolomics can detect subtle metabolic shifts in human astrocyte models of AD and HS exposed to amiloidogenic challenge. Given the limited sample size and the exploratory design adopted, the results should be interpreted as preliminary and require validation in larger, better-matched cohorts. Nevertheless, this study provides a methodological framework and generates biologically plausible hypotheses regarding astrocyte metabolic responses relevant to AD pathophysiology.