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Recent Articles

17 pages, 738 KiB

Open AccessArticle

Chemical Composition, Enantiomeric Distribution and Antimicrobial, Antioxidant and Antienzymatic Activities of Essential Oil from Leaves of Citrus x limonia

by Eduardo Valarezo, Laura Toledo-Ruiz, Wolter Coque-Saetama, Alfredo Caraguay-Martínez, Ximena Jaramillo-Fierro, Nixon Cumbicus and Miguel Angel Meneses

Molecules 2025, 30(4), 937; https://doi.org/10.3390/molecules30040937 (registering DOI) - 18 Feb 2025

Abstract

Citrus x limonia is an aromatic species belonging to the Rutaceae family. In the present study, the chemical composition, enantiomeric distribution, and biological activity of the essential oil isolated from leaves of Citrus x limonia were determined. The essential oil was extracted through hydrodistillation. The chemical composition of the essential oil was determined by gas chromatography (GC) coupled to a flame ionization detector (GC-FID), and a mass spectrometer detector (GC-MS) using a nonpolar column. The enantiomeric distribution was performed using two enantioselective chromatographic columns. Antimicrobial activity was determined using the broth microdilution method. The antimicrobial activity was tested against eight bacteria and two fungi. The antioxidant activity was determined through ABTS and DPPH methods. The spectrophotometric method was used to determine anticholinesterase activity. In the essential oil, forty-three compounds were identified. These compounds represent 99.13% of the total composition. Monoterpene hydrocarbons were the most representative group in number of compounds (fourteen) and in terms of relative abundance (65.67%). The main constituent is found to be limonene (25.37 ± 0.80%), β-pinene (23.29 ± 0.15%) and sabinene (8.35 ± 0.10%). Six pairs of enantiomers were identified in the essential oil from fruits of Citrus x limonia. The essential oil showed moderate antibacterial activity against Gram-positive cocci Enterococcus faecalis, and Gram-positive bacillus Lysteria monocytogenes with a MIC of 1000 μg/mL. The oil exhibited strong antifungal activity against fungi Aspergillus niger, and yeasts Candida albicans with a MIC of 250 and 500 μg/mL, respectively. The antioxidant activity of essential oil was weak in ABTS method with a SC₅₀ of 9.12 mg/mL. Additionally, the essential oil presented moderate anticholinesterase activity with an IC₅₀ of 71.02 ± 1.02 µg/mL. Full article

(This article belongs to the Special Issue Chemical Composition and Bioactivities of Essential Oils, 3rd Edition)

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14 pages, 692 KiB

Open AccessSystematic Review

Fibromyalgia, Depression, and Autoimmune Disorders: An Interconnected Web of Inflammation

by Stefania Sedda, Maria Piera L. Cadoni, Serenella Medici, Elena Aiello, Gian Luca Erre, Alessandra Matilde Nivoli, Ciriaco Carru and Donatella Coradduzza

Biomedicines 2025, 13(2), 503; https://doi.org/10.3390/biomedicines13020503 (registering DOI) - 18 Feb 2025

Abstract

Background: Fibromyalgia, depression, and autoimmune diseases represent a triad of interconnected conditions characterized by overlapping biological pathways, including chronic inflammation, immune dysregulation, and neurochemical imbalances. Understanding their shared mechanisms offers opportunities for innovative therapeutic approaches. Objective: This systematic review explores the common inflammatory- and immune-related pathways among these conditions, emphasizing their implications for biomarker development and novel therapeutic strategies. Methods: Following PRISMA guidelines, a comprehensive literature search was conducted in databases including PubMed, Scopus, Web of Science, and the Cochrane Library. Studies examining the relationship between fibromyalgia, depression, and autoimmune diseases with a focus on immune responses, inflammatory biomarkers, and therapeutic interventions were included. The quality of the selected studies was assessed using the Cochrane Risk of Bias tool. Results: From the 255 identified studies, 12 met the inclusion criteria. Evidence supports the role of pro-inflammatory cytokines (e.g., IL-6, TNF-α) and neurochemical dysregulation (e.g., serotonin, dopamine) as key factors in the pathophysiology of these conditions. Pilot studies highlight the potential of immune-modulating therapies, including low-dose IL-2 and anti-inflammatory agents such as N-acetylcysteine and minocycline, in alleviating both physical and psychological symptoms. Emerging biomarkers, including cytokine profiles and platelet serotonin activity, show promise for personalized treatment approaches. Conclusions: The shared inflammatory pathways linking fibromyalgia, depression, and autoimmune diseases underscore the need for integrated therapeutic strategies. Although pilot studies provide preliminary insights, validation through large-scale, multicenter trials is essential. Future research should focus on standardizing methodologies and leveraging biomarker-driven precision medicine to improve outcomes for patients with these complex, multifactorial conditions. Full article

(This article belongs to the Special Issue Molecular Research of Neurodegenerative and Psychiatric Diseases, 2nd Edition)

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13 pages, 3692 KiB

Open AccessArticle

Studies on Modification of Polyamide 6 Plastics for Hydrogen Storage

by Li Li, Jiawei Zhao, Xingguo Wang, Qingquan Yang, Xiang Wang and Hua Yin

Polymers 2025, 17(4), 523; https://doi.org/10.3390/polym17040523 (registering DOI) - 18 Feb 2025

Abstract

Polyamide 6 (PA6) can be used as the liner material of a type IV hydrogen storage tank, but its high hydrogen permeability and poor low-temperature toughness limit its application in related fields. In this work, PA6 composites were prepared by introducing graphene with different contents and a nano two-dimensional lamellar filler via the melt blending method, and the effects of the graphene content on the crystallization properties, mechanical properties, and hydrogen barrier properties of the composites were investigated. The results showed that composites containing 2.0 wt% graphene exhibited the best overall performance, and compared with PA6, the crystallization properties, normal-temperature impact strength and low-temperature impact strength of the composites were increased by 16.0%, 130.6% and 111.7%, respectively, and the helium permeability coefficient was decreased by 33.2%. Graphene enhances the crystallinity and lamellar thickness of the composites. Additionally, its two-dimensional lamellar structure can also increase the diffusion path of gas molecules, thereby improving the barrier properties of the composites. Full article

(This article belongs to the Section Polymer Composites and Nanocomposites)

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12 pages, 1273 KiB

Open AccessArticle

Leaf Water Storage Capacity Among Eight US Hardwood Tree Species: Differences in Seasonality and Methodology

by Natasha Scavotto, Courtney M. Siegert, Heather D. Alexander and J. Morgan Varner

Hydrology 2025, 12(2), 40; https://doi.org/10.3390/hydrology12020040 (registering DOI) - 18 Feb 2025

Abstract

Canopy hydrology and forest water inputs are directly linked to the physical properties of tree crowns (e.g., foliar and woody surfaces), which determine a tree’s capacity to intercept and retain incident rainfall. The changing forest structure, notably the decline of oak’s (Quercus) dominance and encroachment of non-oak species in much of the upland hardwood forests of the eastern United States, challenges our understanding of how species-level traits scale up to control the forest hydrologic budget. The objective of this study was to determine how the leaf water storage capacity varies across species and canopy layers, and how these relationships change throughout the growing season. We measured the leaf water storage capacity of overstory and midstory trees of native deciduous oaks (Q. alba, Q. falcata, Q. stellata) and non-oak species (Carya tomentosa, Acer rubrum, Ulmus alata, Liquidambar styraciflua, Nyssa sylvatica) using two methods (water displacement and rainfall simulation). Overstory Q. alba leaves retained 0.5 times less water per unit leaf area than other overstory species (p < 0.001) in the early growing season, while in the late growing season, C. tomentosa leaves had the lowest storage capacity (p = 0.024). Quercus falcata leaves displayed a minimal change in storage between seasons, while Q. alba and Q. stellata leaves had higher water storage in the late growing season. Midstory U. alata leaves had 3.5 times higher water storage capacity in the early growing season compared to all the other species (p < 0.001), but this difference diminished in the late growing season. Furthermore, the water storage capacities from the simulated rainfall experiments were up to two times higher than those in the water displacement experiments, particularly during the early growing season. These results underscore the complexity of leaf water storage dynamics, the methodology, and the implications for forest hydrology and species interactions. Broader efforts to understand species-level controls on canopy water portioning through leaf and other crown characteristics are necessary. Full article

(This article belongs to the Section Ecohydrology)

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19 pages, 3682 KiB

Open AccessArticle

Citizen Science to Investigate the Ecophysiological Responses of Mediterranean Shrubland Vegetation in an Urban Open-Air Laboratory

by Valerio Lazzeri, Francesca Bretzel, Graziella Rossini, Laura Pellegrino, Laura Marchetti, Rosella Panti, Enrica Talà, Antonio Martelli and Andrea Scartazza

Land 2025, 14(2), 423; https://doi.org/10.3390/land14020423 (registering DOI) - 18 Feb 2025

Abstract

Urban biodiversity is essential for enhancing liveability for both humans and wildlife by providing a range of ecosystem services. Therefore, it is crucial to raise awareness among citizens, particularly schoolchildren, about the significance of biodiversity in urban environments. To this end, an Open-Air Laboratory was established in an urban park of an Italian Mediterranean city (Livorno), where natural vegetation flourishes. This initiative engaged schoolchildren in experimental campaigns to collect ecophysiological data on local wild woody species. Specifically, the students were tasked with identifying various wild woody species and, under the guidance of researchers, recording specific leaf ecophysiological traits, such as leaf mass per area, leaf pigments, and chlorophyll fluorescence. The results, which highlighted seasonal variations in leaf ecophysiological traits and interspecific differences, were analysed in relation to the environmental conditions documented by the schoolchildren. This analysis revealed distinct plant strategies for coping with winter and summer stressful periods. The methodology employed in this project, which involved schoolchildren in research activities, not only fostered environmental awareness among young participants but also serves as a pilot model for public engagement in scientific research. Full article

(This article belongs to the Special Issue Urban and Peri-Urban Forests—Status, Ecosystem Services, and Future Perspectives)

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Abstract

Hydrogel network structures play a crucial role in determining mechanical properties and have broad applications in biomedical and industrial fields. Therefore, their rational design is essential. Herein, we developed a Schiff base-crosslinked hydrogel through the reaction of Tetra-armed polyethylene glycol with aldehyde end groups (Tetra-PEG-CHO) and bovine serum albumin (BSA) under alkaline conditions. In addition, the Tetra-PEG-BSA hydrogel showed a rapid gelation time of around 11 s, much faster than that of the GLU-BSA, HT-BSA, and GDL-BSA hydrogels. It had high optical transmittance (92.92% at 600 nm) and swelling ratios superior to the other gels in different solutions, maintaining structural integrity even in denaturing environments such as guanidine hydrochloride and SDS. Mechanical tests showed superior strain at break (84.12 ± 0.76%), rupture stress (28.64 ± 1.21 kPa), and energy dissipation ability (468.0 ± 34.9 kJ·m⁻³), surpassing all control group hydrogels. MTT cytotoxicity assays indicated that cell viability remained >80% at lower concentrations, confirming excellent biocompatibility. These findings suggest that Tetra-PEG-BSA hydrogels may serve as effective materials for drug delivery, tissue engineering, and 3D printing. Full article

27 pages, 5597 KiB

Open AccessArticle

Smart Organization of Imbalanced Traffic Datasets for Long-Term Traffic Forecasting

by Mustafa M. Kara, H. Irem Turkmen and M. Amac Guvensan

Sensors 2025, 25(4), 1225; https://doi.org/10.3390/s25041225 (registering DOI) - 18 Feb 2025

Abstract

Predicting traffic speed is an important issue, especially in urban regions. Precise long-term forecasts would enable individuals to conserve time and financial resources while diminishing air pollution. Despite extensive research on this subject, to our knowledge, no publications investigate or tackle the issue of imbalanced datasets in traffic speed prediction. Traffic speed data are often biased toward high numbers because low traffic speeds are infrequent. The temporal aspect of traffic carries two important factors for low-speed value. The daily population movement, captured by the time of day, and the weather data, recorded by month, are both considered in this study. Hour-wise Pattern Organization and Month-wise Pattern Organization techniques were devised, which organize the speed data using these two factors as a metric with a view to providing a superior representation of data characteristics that are in the minority. In addition to these two methods, a Speed-wise Pattern Organization strategy is proposed, which arranges train and test samples by setting boundaries on speed while taking the volatile nature of traffic into consideration. We evaluated these strategies using four popular model types: long short-term memory (LSTM), gated recurrent unit networks (GRUs), bi-directional LSTM, and convolutional neural networks (CNNs). GRU had the best performance, achieving a MAPE (Mean Absolute Percentage Error) of 13.51%, whereas LSTM demonstrated the lowest performance, with a MAPE of 13.74%. We validated their robustness through our studies and observed improvements in model accuracy across all categories. While the average improvement was approximately 4%, our methodologies demonstrated superior performance in low-traffic speed scenarios, augmenting model prediction accuracy by 11.2%. The presented methodologies in this study are applied in the pre-processing steps, allowing their application with various models and additional pre-processing procedures to attain comparable performance improvements. Full article

(This article belongs to the Section Navigation and Positioning)

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