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31 pages, 10959 KB

Open AccessArticle

Pro-Apoptotic and Anti-EMT Activity of Wild Ginseng Adventitious Root Extract in MDA-MB-231 TNBC Cells: Association with GSK-3β/β-Catenin Signaling

by Chang-Eui Hong, Ducdat Le, Mina Lee and Su-Yun Lyu

Pharmaceuticals 2026, 19(2), 216; https://doi.org/10.3390/ph19020216 (registering DOI) - 26 Jan 2026

Abstract

Background/Objectives: Triple-negative breast cancer (TNBC) lacks targeted therapies and has a poor prognosis. Wild ginseng (Panax ginseng) is traditionally valued for its medicinal properties, but its scarcity limits therapeutic application. Adventitious root culture technology provides a sustainable source of wild [...] Read more.

Background/Objectives: Triple-negative breast cancer (TNBC) lacks targeted therapies and has a poor prognosis. Wild ginseng (Panax ginseng) is traditionally valued for its medicinal properties, but its scarcity limits therapeutic application. Adventitious root culture technology provides a sustainable source of wild ginseng-derived bioactive compounds. This study investigated the anticancer effects of wild ginseng adventitious root extract (WGAR) on MDA-MB-231 TNBC cells and elucidated the underlying molecular mechanisms. Methods: WGAR was prepared from cultured adventitious roots of 100-year-old wild ginseng, and its chemical composition was analyzed by LC-MS/MS. Anticancer effects were evaluated using MTT assay, acridine orange/propidium iodide (AO/PI) staining, Matrigel invasion assay, Western blot analysis, and proteome profiler array. Molecular docking was performed to predict interactions between WGAR constituents and target proteins poly (ADP-ribose) polymerase (PARP)-1 and β-catenin. Results: LC-MS/MS analysis tentatively identified 17 compounds, including ginsenosides (Rg3, Rh1, Rf) and terpenoids (ursolic acid). WGAR reduced cell viability with an IC50 of 79 μg/mL at 48 h, inducing 51.2% cell death. WGAR activated the intrinsic apoptotic pathway through sequential caspase-9 and caspase-3 activation, followed by PARP cleavage, and was associated with changes in epithelial–mesenchymal transition (EMT)-related markers (reduced N-cadherin, Slug, and β-catenin) alongside decreased inhibitory Ser9 phosphorylation of GSK-3β. Proteome array analysis revealed suppression of ECM remodeling proteins (tenascin C, u-PA) and inflammatory mediators (IL-6, CXCL8). Molecular docking predicted that selected WGAR constituents, particularly terpenoid-type compounds, may potentially interact with PARP-1 and β-catenin; however, these in silico findings are hypothesis-generating and require experimental validation. Conclusions: WGAR exerts multi-target anticancer effects on TNBC cells through apoptosis induction and EMT suppression associated with modulation of GSK-3β/β-catenin signaling, suggesting its potential as a source of therapeutic agents for TNBC. Full article

(This article belongs to the Special Issue Exploring the Anticancer and Immunomodulatory Mechanisms of Phytochemicals and Natural Bioactive Compounds)

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15 pages, 8213 KB

Open AccessArticle

Discrete Element Modeling of Near-Surface Fault Rupture Evolution Along the Milun Fault in Taiwan

by Xiao-Fei Guo, Yosuke Aoki and Jiang-Hai Li

Appl. Sci. 2026, 16(3), 1265; https://doi.org/10.3390/app16031265 (registering DOI) - 26 Jan 2026

Abstract

Understanding the shallow rupture mechanisms on coseismic faults and assessing the influence of fault area propagation is essential for disaster prevention. Since 2000, Hualien and nearby areas in eastern Taiwan have experienced frequent earthquakes, making it a good area to study the evolution [...] Read more.

Understanding the shallow rupture mechanisms on coseismic faults and assessing the influence of fault area propagation is essential for disaster prevention. Since 2000, Hualien and nearby areas in eastern Taiwan have experienced frequent earthquakes, making it a good area to study the evolution of fault rupture. This study proposes a two-dimensional dynamic discrete element model to simulate the shallow rupture behavior of the Milun Fault. Results indicate that the rupture process proceeds through multiple evolutionary stages, with fractures propagating upward from depth but failing to fully break through to the surface, resulting instead in surface cracking without complete rupture. The second deviatoric stress invariant serves as an effective indicator of stress accumulation and release during rupture progression. For the preferred model, the modeled vertical uplift near the fault reached 0.6 m, consistent with field observations reporting a maximum coseismic uplift of approximately 0.585 m along the Milun Fault. Given the scarcity of near-fault observational constraints, the simulation represents a physically plausible scenario rather than a unique reconstruction. The integration of stress evolution, crack propagation, and near-field displacement provides new insight into the mechanical processes governing shallow thrust fault rupture and can be applied to similar fault systems exhibiting near-surface deformation. Full article

(This article belongs to the Section Earth Sciences)

23 pages, 7127 KB

Open AccessArticle

Spatiotemporal Dynamics and Evaluation of Groundwater and Salt in the Karamay Irrigation District

by Gang Chen, Feihu Yin, Zhenhua Wang, Yungang Bai, Shijie Cai, Zhaotong Shen, Ming Zheng, Biao Cao, Zhenlin Lu and Meng Li

Agriculture 2026, 16(3), 310; https://doi.org/10.3390/agriculture16030310 (registering DOI) - 26 Jan 2026

Abstract

Inland depression irrigation districts in the arid regions of Xinjiang, owing to the absence of natural drainage conditions, exhibit unique groundwater-salt dynamics and face prominent risks of soil salinization, thus necessitating clarification of their water-salt transport mechanisms to ensure sustainable agricultural development. This [...] Read more.

Inland depression irrigation districts in the arid regions of Xinjiang, owing to the absence of natural drainage conditions, exhibit unique groundwater-salt dynamics and face prominent risks of soil salinization, thus necessitating clarification of their water-salt transport mechanisms to ensure sustainable agricultural development. This study takes the Karamay Agricultural Comprehensive Development Zone as the research subject. The study examines the distribution characteristics of soil salinity, groundwater depth, and Total Dissolved Solids (TDS) of groundwater across diverse soil textures, elucidates the correlative relationships between groundwater dynamics and soil salinity, and forecasts the evolutionary trajectory of groundwater levels within the irrigation district. The findings reveal that groundwater depth in silty soil regions (3.24–3.11 m) substantially exceeds that in silty clay regions (2.43–2.61 m), whereas TDS of groundwater demonstrates marginally elevated concentrations in silty clay areas (19.05–16.78 g L⁻¹) compared to silty soil zones (18.18–16.29 g L⁻¹). Soil salinity exhibits pronounced surface accumulation phenomena and considerable inter-annual seasonal variations: manifesting a “spring-peak, summer-trough” pattern in 2023, which inversely transitioned to a “summer-peak, spring-trough” configuration in 2024, with salinity hotspots predominantly concentrated in silty clay distribution zones. A significant sigmoid functional relationship emerges between soil salinity and groundwater depth (R² = 0.73–0.77), establishing critical depth thresholds of 2.44 m for silty soil and 2.72 m for silty clay, beneath which the risk of secondary salinization escalates dramatically. The XGBoost model demonstrates robust predictive capability for groundwater levels (R² = 0.8545, MAE = 0.4428, RMSE = 0.5174), with feature importance analysis identifying agricultural irrigation as the predominant influencing factor. Model projections indicate that mean groundwater depths across the irrigation district will decline to 2.91 m, 2.76 m, 2.62 m, and 2.36 m over the ensuing 1, 3, 5, and 10 years, respectively. Within a decade, 73.33% of silty soil regions and 92.31% of silty clay regions will experience groundwater levels below critical thresholds, subjecting the irrigation district to severe secondary salinization threats. Consequently, comprehensive mitigation strategies encompassing precision irrigation management and enhanced drainage infrastructure are imperative. Full article

(This article belongs to the Section Agricultural Water Management)

11 pages, 273 KB

Open AccessArticle

Lie Symmetries and Similarity Solutions for a Shallow-Water Model with Bed Elevation in Lagrange Variables

by Andronikos Paliathanasis, Genly Leon and Peter G. L. Leach

Mathematics 2026, 14(3), 433; https://doi.org/10.3390/math14030433 (registering DOI) - 26 Jan 2026

Abstract

We investigate the Lagrange formulation for the one-dimensional Saint Venant–Exner system. The system describes shallow-water equations with a bed evolution, for which the bedload sediment flux depends on the velocity,

Q (t, x) = A_{g} u^{m}, m \geq 1

[...] Read more.

We investigate the Lagrange formulation for the one-dimensional Saint Venant–Exner system. The system describes shallow-water equations with a bed evolution, for which the bedload sediment flux depends on the velocity,

Q (t, x) = A_{g} u^{m}, m \geq 1

. In terms of the Lagrange variables, the nonlinear hyperbolic system is reduced to one master third-order nonlinear partial differential equation. We employ Lie’s theory and find the Lie symmetry algebra of this equation. It was found that for an arbitrary parameter m, the master equation possesses four Lie symmetries. However, for

m = 3

, there exists an additional symmetry vector. We calculate a one-dimensional optimal system for the Lie algebra of the equation. We apply the latter for the derivation of invariant functions. The invariants are used to reduce the number of the independent variables and write the master equation into an ordinary differential equation. The latter provides similarity solutions. Finally, we show that the traveling-wave reductions lead to nonlinear maximally symmetric equations which can be linearized. The analytic solution in this case is expressed in closed-form algebraic form. Full article

(This article belongs to the Special Issue Symmetry Methods for Differential Equations)

28 pages, 877 KB

Open AccessArticle

SFD-ADNet: Spatial–Frequency Dual-Domain Adaptive Deformation for Point Cloud Data Augmentation

by Jiacheng Bao, Lingjun Kong and Wenju Wang

J. Imaging 2026, 12(2), 58; https://doi.org/10.3390/jimaging12020058 (registering DOI) - 26 Jan 2026

Abstract

Existing 3D point cloud enhancement methods typically rely on artificially designed geometric transformations or local blending strategies, which are prone to introducing illogical deformations, struggle to preserve global structure, and exhibit insufficient adaptability to diverse degradation patterns. To address these limitations, this paper [...] Read more.

Existing 3D point cloud enhancement methods typically rely on artificially designed geometric transformations or local blending strategies, which are prone to introducing illogical deformations, struggle to preserve global structure, and exhibit insufficient adaptability to diverse degradation patterns. To address these limitations, this paper proposes SFD-ADNet—an adaptive deformation framework based on a dual spatial–frequency domain. It achieves 3D point cloud augmentation by explicitly learning deformation parameters rather than applying predefined perturbations. By jointly modeling spatial structural dependencies and spectral features, SFD-ADNet generates augmented samples that are both structurally aware and task-relevant. In the spatial domain, a hierarchical sequence encoder coupled with a bidirectional Mamba-based deformation predictor captures long-range geometric dependencies and local structural variations, enabling adaptive position-aware deformation control. In the frequency domain, a multi-scale dual-channel mechanism based on adaptive Chebyshev polynomials separates low-frequency structural components from high-frequency details, allowing the model to suppress noise-sensitive distortions while preserving the global geometric skeleton. The two deformation predictions dynamically fuse to balance structural fidelity and sample diversity. Extensive experiments conducted on ModelNet40-C and ScanObjectNN-C involved synthetic CAD models and real-world scanned point clouds under diverse perturbation conditions. SFD-ADNet, as a universal augmentation module, reduces the mCE metrics of PointNet++ and different backbone networks by over 20%. Experiments demonstrate that SFD-ADNet achieves state-of-the-art robustness while preserving critical geometric structures. Furthermore, models enhanced by SFD-ADNet demonstrate consistently improved robustness against diverse point cloud attacks, validating the efficacy of adaptive space-frequency deformation in robust point cloud learning. Full article

(This article belongs to the Special Issue 3D Image Processing: Progress and Challenges)

37 pages, 1319 KB

Open AccessReview

Late-Onset Depression in an Aging World: A Multidimensional Perspective on Risks, Mechanisms, and Treatment

by Antonio Maria D’Onofrio, Gaspare Filippo Ferrajoli, Lodovico Maria Balzoni, Marco Massetti, Andrea Zanzarri, Giuseppe Marano, Marianna Mazza, Alexia Koukopoulos, Georgios D. Kotzalidis, Lorenzo Moccia, Alessio Simonetti, Delfina Janiri, Marco Di Nicola, Gabriele Sani and Giovanni Camardese

Geriatrics 2026, 11(1), 13; https://doi.org/10.3390/geriatrics11010013 (registering DOI) - 26 Jan 2026

Abstract

Background: Late-onset depression (LOD) represents a distinct clinical and biological phenotype emerging in the context of global population ageing. This study aims to synthesize current evidence on the epidemiology, risk factors, mechanistic pathways, and therapeutic approaches of LOD, integrating biological, psychological, and social [...] Read more.

Background: Late-onset depression (LOD) represents a distinct clinical and biological phenotype emerging in the context of global population ageing. This study aims to synthesize current evidence on the epidemiology, risk factors, mechanistic pathways, and therapeutic approaches of LOD, integrating biological, psychological, and social dimensions. Methods: This narrative review synthesizes recent evidence across epidemiology, clinical symptomatology, neurobiology, and treatment. Where conceptually appropriate or empirically overlapping, we incorporate findings from the broader late-life depression (LLD) literature. Results: LOD emerges (as a distinct clinical and biological entity in later life) as a clinically and biologically meaningful presentation of depression in later life, representing a minority of depressive cases. It is defined by prominent apathy, psychomotor slowing, and cognitive impairment, and is closely linked to frailty, medical comorbidity, and heightened dementia risk. Pathophysiological mechanisms converge on vascular, inflammatory, oxidative, and neuroplasticity pathways, while psychosocial adversity further shapes onset and course. Treatment prioritizes efficacy and tolerability amid multiple morbidity; SSRIs and SNRIs are first-line, with pro-dopaminergic or dual-action agents addressing anhedonia and apathy, and neuromodulation or augmentation strategies reserved for resistance. Integrative approaches combining pharmacotherapy, psychotherapy, and lifestyle interventions are essential to optimize outcomes in aging populations. Conclusions: Late-onset depression (is a distinct, biologically and psychosocially driven disorder) represents a biologically and psychosocially enriched subtype in its own within the spectrum of late-life depression, requiring integrated, personalized care. Addressing neurovascular mechanisms, psychosocial adversity, and prevention through coordinated geriatric and psychiatric strategies may improve outcomes in aging populations. Full article

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26 pages, 458 KB

Open AccessArticle

Creating Value for the Montepulciano D’Abruzzo PDO Chain: A Pilot Study of Supply Chain Traceability Using Multi-Elemental and Chemometrics Analysis of Wine and Soil

by Mattia Rapa, Stefania Supino, Marco Ferrante, Ilia Rodushkin and Marcelo Enrique Conti

Appl. Sci. 2026, 16(3), 1266; https://doi.org/10.3390/app16031266 (registering DOI) - 26 Jan 2026

Abstract

This study aims to enhance the value of the Montepulciano d’Abruzzo PDO supply chain by integrating multi-elemental and isotopic profiling with chemometric analysis. The objective is to establish a pilot study for origin authentication, supporting strategic, managerial, and regulatory decision-making for stakeholders in [...] Read more.

This study aims to enhance the value of the Montepulciano d’Abruzzo PDO supply chain by integrating multi-elemental and isotopic profiling with chemometric analysis. The objective is to establish a pilot study for origin authentication, supporting strategic, managerial, and regulatory decision-making for stakeholders in the wine sector. Wine and soil samples from producers in the Abruzzo region were analyzed for 63 elements and selected isotopic ratios using HR-ICP-MS and MC-ICP-MS. Exploratory data analysis, including PCA and clustering, was employed to investigate intrinsic data structure. Variable selection techniques identified the most discriminant markers, and multiple classification models were tested to assess producer-level differentiation. The combined elemental and isotopic dataset showed strong intrinsic structure. Four variables—Mo, ²⁰⁸Pb/²⁰⁶Pb, P, and ⁸⁷Sr/⁸⁶Sr—emerged as key discriminants. Quadratic Discriminant Analysis and Artificial Neural Networks achieved 100% accuracy in classifying samples by producer. The results demonstrate that integrating multi-elemental and isotopic data with chemometric tools offers a pilot approach to authenticate wine origin and enhance transparency across the PDO supply chain. Beyond scientific innovation, this study provides a pilot decision support model that can strengthen competitive differentiation, regulatory compliance, and sustainable territorial development, highlighting opportunities for digital transformation in PDO management. Full article

(This article belongs to the Section Chemical and Molecular Sciences)

31 pages, 2717 KB

Open AccessArticle

Quality Assessment and Prediction of Peanut Storage Life Based on Deep Learning

by Yipeng Zhou, Xingchen Sun, Wenjing Yan, Mingwen Bi, Yiwen Shao and Kexin Chen

Foods 2026, 15(3), 446; https://doi.org/10.3390/foods15030446 (registering DOI) - 26 Jan 2026

Abstract

As a globally significant oilseed and food crop, peanuts exhibit significant quality changes influenced by storage conditions. This study monitored six key quality indicators—including fatty acid content, carbonyl content, peroxide value, acid value, phenylacetaldehyde and moisture content—in peanut samples stored for 30 weeks [...] Read more.

As a globally significant oilseed and food crop, peanuts exhibit significant quality changes influenced by storage conditions. This study monitored six key quality indicators—including fatty acid content, carbonyl content, peroxide value, acid value, phenylacetaldehyde and moisture content—in peanut samples stored for 30 weeks under varying temperature and humidity conditions. A Deep Clustering Network (DCN) was employed for quality grading, yielding superior results compared to Deep Empirical Correlation (DEC) and K-Means++ clustering methods, thereby establishing effective quality grading standards. Building upon this, a D-SCSformer time series prediction model was constructed to forecast quality indicators. Through dimensionality-segmented embedding and statistical feature fusion, it achieved strong predictive performance (MSE = 0.2012, MAE = 0.2884, RMSE = 0.4387, and R² = 0.9998), reducing MSE by 57.9%, MAE by 35.4%, and RMSE by 34.1%, while improving R² from 0.9996 to 0.9998 compared to the mainstream Crossformer model. This study provides technical support and a decision-making basis for temperature and humidity regulation and shelf-life management during peanut storage. Full article

(This article belongs to the Special Issue Using Artificial Intelligence and Big Data Analytics to Improve Food Safety)

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19 pages, 7234 KB

Open AccessArticle

Increased Sensitivity of Alpine Grasslands to Climate Change on the Tibetan Plateau

by Zhuanjia Xu, Lanhui Li, Binghua Zhang, Shuimei Fu, Wei Liu, Yanran Luo, Hui Li, Xiaoling Zhu and Fuliang Deng

Land 2026, 15(2), 215; https://doi.org/10.3390/land15020215 (registering DOI) - 26 Jan 2026

Abstract

Accurately quantifying the sensitivity of alpine vegetation to climate change is a key prerequisite for formulating regional climate change adaptation policies. The sensitivity of the fragile alpine grasslands on the Tibetan Plateau to climate change has received widespread attention. However, the spatiotemporal dynamics [...] Read more.

Accurately quantifying the sensitivity of alpine vegetation to climate change is a key prerequisite for formulating regional climate change adaptation policies. The sensitivity of the fragile alpine grasslands on the Tibetan Plateau to climate change has received widespread attention. However, the spatiotemporal dynamics and driving mechanisms of this sensitivity are still unclear under continuous warming and wetting. This study, based on MODIS_NDVI and meteorological data from 2000 to 2023, constructed a dynamic Vegetation Sensitivity Index (VSI) framework and integrated Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models with Shapley Additive exPlanations (SHAP) attribution analysis to reveal the spatiotemporal evolution characteristics and driving mechanisms of vegetation sensitivity on the Tibetan Plateau. The results show that (1) the VSI of alpine grasslands exhibited a spatial pattern of higher values in the southwest and lower values in the northeast, with an overall upward trend. Specifically, 56.31% of the region showed an increase in the VSI, with the upward trend being more pronounced in the northern plateau. (2) The dominant role of different climate factors varied regionally; vegetation sensitivity to precipitation increased in the northern plateau, and temperature sensitivity decreased in the central plateau, while sensitivity to solar radiation significantly increased in the central plateau. (3) SHAP attribution analysis indicated that elevation was the core factor driving VSI differentiation, showing a higher sensitivity at higher elevations, with lower growth rates. These findings reveal the dynamic evolution of vegetation sensitivity under the warming and wetting climate trend and its elevation-regulated mechanism, providing important scientific insights for regional ecological adaptation management. Full article

21 pages, 4553 KB

Open AccessArticle

Removal Dynamics of Water Droplets in the Orientated Gas Flow Channel of Proton Exchange Membrane Fuel Cells

by Dan Wang, Song Yang, Ping Sun, Xiqing Cheng, Huili Dou, Wei Dong, Zezhou Guo and Xia Sheng

Energies 2026, 19(3), 645; https://doi.org/10.3390/en19030645 (registering DOI) - 26 Jan 2026

Abstract

Understanding the dynamic characteristics of droplets in the orientated flow channels of Proton Exchange Membrane Fuel Cells (PEMFCs) is crucial for their effective heat and water management and bipolar plate design. Therefore, the transient transport dynamics of liquid water within orientated gas flow [...] Read more.

Understanding the dynamic characteristics of droplets in the orientated flow channels of Proton Exchange Membrane Fuel Cells (PEMFCs) is crucial for their effective heat and water management and bipolar plate design. Therefore, the transient transport dynamics of liquid water within orientated gas flow channels (OGFCs) of PEMFCs are investigated, and a two-phase model based on the volume of fluid (VOF) method is established in the current study. Moreover, the impacts of the size of droplets and the geometrical parameters of baffles on the removal dynamics of liquid water are examined. The results show that baffles effectively promote droplet breakup and accelerate their detachment from the Gas Diffusion Layer (GDL) surface by increasing flow instability and local shear forces. The morphology of water is altered by the high velocity of gaseous flow, which can break up into several smaller droplets and distribute them on the surface of GDL by the gas flow. The shape of the liquid water film changes from a regular cuboid to a big droplet due to the surface tension of the liquid water droplets and the hydrophobicity of the GDL surfaces. Increasing the baffle height can reduce the time needed for the removal of droplets. With the increase in L1* from 0.25 to 0.75, the drainage time decreases slightly; however, for L1* increasing from 0.75 to 1.25, the drainage time remains almost the same. The impacts of different leeward lengths, L2*, on the water coverage ratio and pressure drop are minor. Full article

(This article belongs to the Section A5: Hydrogen Energy)

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35 pages, 1699 KB

Open AccessReview

Will AI Replace Physicians in the Near Future? AI Adoption Barriers in Medicine

by Rafał Obuchowicz, Adam Piórkowski, Karolina Nurzyńska, Barbara Obuchowicz, Michał Strzelecki and Marzena Bielecka

Diagnostics 2026, 16(3), 396; https://doi.org/10.3390/diagnostics16030396 (registering DOI) - 26 Jan 2026

Abstract

Objectives: This study aims to evaluate whether contemporary artificial intelligence (AI), including convolutional neural networks (CNNs) for medical imaging and large language models (LLMs) for language processing, could replace physicians in the near future and to identify the principal clinical, technical, and [...] Read more.

Objectives: This study aims to evaluate whether contemporary artificial intelligence (AI), including convolutional neural networks (CNNs) for medical imaging and large language models (LLMs) for language processing, could replace physicians in the near future and to identify the principal clinical, technical, and regulatory barriers. Methods: A narrative review is conducted on the scientific literature addressing AI performance and reproducibility in medical imaging, LLM competence in medical knowledge assessment and patient communication, limitations in out-of-distribution generalization, absence of physical examination and sensory inputs, and current regulatory and legal frameworks, particularly within the European Union. Results: AI systems demonstrate high accuracy and reproducibility in narrowly defined tasks, such as image interpretation, lesion measurement, triage, documentation support, and written communication. These capabilities reduce interobserver variability and support workflow efficiency. However, major obstacles to physician replacement persist, including limited generalization beyond training distributions, inability to perform physical examination or procedural tasks, susceptibility of LLMs to hallucinations and overconfidence, unresolved issues of legal liability at higher levels of autonomy, and the continued requirement for clinician oversight. Conclusions: In the foreseeable future, AI will augment rather than replace physicians. The most realistic trajectory involves automation of well-defined tasks under human supervision, while clinical integration, physical examination, procedural performance, ethical judgment, and accountability remain physician-dependent. Future adoption should prioritize robust clinical validation, uncertainty management, escalation pathways to clinicians, and clear regulatory and legal frameworks. Full article

(This article belongs to the Topic Machine Learning and Deep Learning in Medical Imaging)

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33 pages, 654 KB

Open AccessReview

Vascular Sociology: Integrating Vascular Surgery and Medical Sociology for a Comprehensive Understanding of Vascular Health

by Davide Costa and Raffaele Serra

J. Vasc. Dis. 2026, 5(1), 5; https://doi.org/10.3390/jvd5010005 (registering DOI) - 26 Jan 2026

Abstract

Vascular diseases remain a major global health burden despite remarkable technological advances in vascular surgery and endovascular therapies. Conditions such as peripheral arterial disease, abdominal aortic aneurysm, carotid stenosis, chronic venous disease, diabetic vasculopathies, and vascular chronic ulcers are not only biological entities [...] Read more.

Vascular diseases remain a major global health burden despite remarkable technological advances in vascular surgery and endovascular therapies. Conditions such as peripheral arterial disease, abdominal aortic aneurysm, carotid stenosis, chronic venous disease, diabetic vasculopathies, and vascular chronic ulcers are not only biological entities but are deeply shaped by social structures, cultural norms, and economic inequalities. This article introduces Vascular Sociology as an interdisciplinary field that integrates vascular surgery with medical sociology to provide a more comprehensive understanding of vascular health and disease. Drawing on classical and contemporary sociological theory, including concepts such as social determinants of health, embodiment, illness narratives, and the disease–illness–sickness triad, the article argues that vascular pathology reflects cumulative social exposures across the life course. Socially patterned behaviors, work conditions, food environments, healthcare access, gender norms, and geographic inequalities profoundly influence disease onset, progression, treatment decisions, and outcomes. The paper highlights how surgical success is contingent not only on technical excellence but also on patients’ social contexts, including health literacy, trust in institutions, caregiving resources, and the capacity to adhere to long-term follow-up and rehabilitation. By outlining conceptual foundations, epidemiological evidence, and mixed-methods research strategies, the article positions Vascular Sociology as a framework capable of bridging biomedical knowledge with lived experience. This approach expands the definition of vascular outcomes to include social reintegration, identity transformation, and equity of care, ultimately aiming to improve patient-centered practice, reduce disparities, and inform more socially responsive vascular health policies. Full article

(This article belongs to the Section Peripheral Vascular Diseases)

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29 pages, 3654 KB

Open AccessArticle

Direct Cytoplasmic Transcription and Trimeric RBD Design Synergize to Enhance DNA Vaccine Potency Against SARS-CoV-2

by Yunju Nam, Sang Chul Shin, Sang Won Cho and Hyung Jun Ahn

Pharmaceutics 2026, 18(2), 164; https://doi.org/10.3390/pharmaceutics18020164 (registering DOI) - 26 Jan 2026

Abstract

Background/Objectives: The emergence of immune-evasive SARS-CoV-2 variants highlights the need for adaptable vaccine strategies. Trimeric receptor-binding domain (tRBD) antigens offer structural and immunological advantages over monomeric RBDs, but DNA vaccine efficacy has been limited by inefficient antigen expression, particularly in non-dividing antigen-presenting cells. [...] Read more.

Background/Objectives: The emergence of immune-evasive SARS-CoV-2 variants highlights the need for adaptable vaccine strategies. Trimeric receptor-binding domain (tRBD) antigens offer structural and immunological advantages over monomeric RBDs, but DNA vaccine efficacy has been limited by inefficient antigen expression, particularly in non-dividing antigen-presenting cells. Although cytoplasmic transcription–based DNA platforms have been developed to overcome nuclear entry barriers, their utility for antigen structure–function optimization remains underexplored. This study evaluated whether integrating a rationally designed trimeric RBD with a T7-driven cytoplasmic transcription system could enhance immunogenic performance. Methods: A DNA vaccine encoding a tandem trimeric SARS-CoV-2 RBD was delivered using a T7 RNA polymerase-driven cytoplasmic transcription system. In vitro antigen expression was assessed following Lipofectamine 3000-mediated transfection. In vivo, mice were immunized with the SM-102-based Rpol/tRBD/LNP formulation, and immunogenicity was assessed by antigen-specific antibody titers, serum neutralizing activity, and T-cell response profiling, together with basic safety/tolerability evaluations. Results: The T7-driven cytoplasmic transcription system markedly increased antigen mRNA and protein expression compared with conventional plasmid delivery. Rpol/tRBD vaccination induced higher anti-RBD IgG titers, enhanced neutralizing antibody activity, and robust CD8⁺ T cell responses relative to monomeric RBD and plasmid-based trimeric RBD vaccines. Immune responses were Th1-skewed and accompanied by germinal center activation without excessive inflammatory cytokine induction, body-weight loss, or hepatic and renal toxicity. Conclusions: This study demonstrates that integrating rational trimeric antigen engineering with direct cytoplasmic transcription enables balanced and well-tolerated immune activation in a DNA vaccine context. The T7 autogene-based platform provides a flexible framework for antigen structure–function optimization and supports the development of next-generation DNA vaccines targeting rapidly evolving viral pathogens. Full article

(This article belongs to the Special Issue Cutting-Edge Approaches to Smart Pharmaceutics and Vaccine Development)

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16 pages, 3559 KB

Open AccessArticle

How Does Food Accessibility Shape the City Food Landscape? Socio-Economic Inequalities in the Metropolitan Region of Rome

by Davide Marino, Daniela Bernaschi and Francesca Benedetta Felici

Land 2026, 15(2), 214; https://doi.org/10.3390/land15020214 (registering DOI) - 26 Jan 2026

Abstract

Food insecurity is not merely an outcome of individual deprivation but a place-based expression of how urban food systems operate within unequal socio-spatial contexts. Using the Drivers–Pressures–State–Impacts–Responses (DPSIR) framework as a policy-relevant analytical lens, this study examines the Metropolitan Region of Rome to [...] Read more.

Food insecurity is not merely an outcome of individual deprivation but a place-based expression of how urban food systems operate within unequal socio-spatial contexts. Using the Drivers–Pressures–State–Impacts–Responses (DPSIR) framework as a policy-relevant analytical lens, this study examines the Metropolitan Region of Rome to show how structural inequalities and uneven food infrastructures shape exposure to food-related risks. The results show that vulnerability is amplified by food price inflation, the rising cost of a healthy diet, and spatial gaps in retail provision—captured through the combined presence of food deserts and food blackouts—disproportionately affecting peripheral municipalities. State indicators, including the Food Insecurity Experience Scale (FIES), the Food Affordability Index (FAI), and the spatial distribution of FEAD beneficiaries, reveal a markedly uneven geography of food poverty, mirroring a higher prevalence of overweight, obesity, and diabetes. These spatial configurations point to obesogenic environments in which constrained affordability and limited accessibility restrict the capacity to maintain healthy diets, generating hidden social and health costs that disproportionately burden peripheral areas. Overall, food insecurity in Rome follows a pronounced centre–periphery gradient rooted in structural and institutional arrangements rather than incidental variation. Addressing this condition requires place-based, justice-oriented interventions that strengthen food infrastructures, improve coordination across governance scales, and place food security at the core of an integrated metropolitan Food Policy. Full article

31 pages, 5186 KB

Open AccessArticle

Simulating Daily Evapotranspiration of Summer Soybean in the North China Plain Using Four Machine Learning Models

by Liyuan Han, Fukui Gao, Shenghua Dong, Yinping Song, Hao Liu and Ni Song

Agronomy 2026, 16(3), 315; https://doi.org/10.3390/agronomy16030315 (registering DOI) - 26 Jan 2026

Abstract

Accurate estimation of crop evapotranspiration (ET) is essential for achieving efficient agricultural water use in the North China Plain. Although machine learning techniques have demonstrated considerable potential for ET simulation, a systematic evaluation of model-architecture suitability and hyperparameter optimization strategies specifically for summer [...] Read more.

Accurate estimation of crop evapotranspiration (ET) is essential for achieving efficient agricultural water use in the North China Plain. Although machine learning techniques have demonstrated considerable potential for ET simulation, a systematic evaluation of model-architecture suitability and hyperparameter optimization strategies specifically for summer soybean ET estimation in this region is still lacking. To address this gap, we systematically compared several machine learning architectures and their hyperparameter optimization schemes to develop a high-accuracy daily ET model for summer soybean in the North China Plain. Synchronous observations from a large-scale weighing lysimeter and an automatic weather station were first used to characterize the day-to-day dynamics of soybean ET and to identify the key driving variables. Four algorithms—support vector regression (SVR), Random Forest (RF), extreme gradient boosting (XGBoost), and a stacking ensemble—were then trained for ET simulation, while Particle Swarm Optimization (PSO), Genetic Algorithms (GAs), and Randomized Grid Search (RGS) were employed for hyperparameter tuning. Results show that solar radiation (R_S), maximum air temperature (T_max), and leaf area index (LAI) are the dominant drivers of ET. The Stacking-PSO-F3 combination, forced with Rs, T_max, LAI, maximum relative humidity (RH_max), and minimum relative humidity (RH_min), achieved the highest accuracy, yielding R² values of 0.948 on the test set and 0.900 in interannual validation, thereby demonstrating excellent precision, stability, and generalizability. The proposed model provides a robust technical tool for precision irrigation and regional water resource optimization. Full article

(This article belongs to the Special Issue Water and Fertilizer Regulation Theory and Technology in Crops)

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22 pages, 645 KB

Open AccessArticle

Pathogenic and Clinical Relevance of Serum IL-17A and TNF-α in Systemic Lupus Erythematosus

by Patricia Richter, Luana Andreea Macovei, Ciprian Rezus, Alexandra Maria Burlui and Elena Rezus

Int. J. Mol. Sci. 2026, 27(3), 1244; https://doi.org/10.3390/ijms27031244 (registering DOI) - 26 Jan 2026

Abstract

Cytokines IL-17A and TNF-α have been implicated in the dysregulated immune responses that characterize SLE, with potential relevance to specific organ involvement. This study aimed to assess their serum levels in SLE patients and to explore potential correlations with clinical, biological, and immunological [...] Read more.

Cytokines IL-17A and TNF-α have been implicated in the dysregulated immune responses that characterize SLE, with potential relevance to specific organ involvement. This study aimed to assess their serum levels in SLE patients and to explore potential correlations with clinical, biological, and immunological features, as well as with disease activity and damage scores. We conducted a cross-sectional analysis of 88 SLE patients diagnosed according to the 2012 SLICC classification criteria and 87 controls matched by sex and age. Serum IL-17A and TNF-α levels were quantified using ELISA. Clinical and laboratory data were collected, including SLEDAI for disease activity and the SLICC/ACR Damage Index for cumulative organ damage. No significant differences were observed in serum IL-17A levels between SLE patients and healthy controls, whereas serum TNF-α levels differed significantly between the two groups. Serum IL-17A levels were significantly associated with cutaneous involvement (p = 0.036) and the inflammatory syndrome (p = 0.049). TNF-α levels were also significantly elevated in patients with cutaneous manifestations (p = 0.050). A positive correlation was observed between TNF-α levels and cumulative organ damage, as assessed by the SLICC/ACR Damage Index (r = 0.36, p < 0.001; R² = 0.13), and levels were particularly higher in patients with malignancies (p = 0.032). A positive correlation was observed between IL-17A and TNF-α levels. No significant associations were found between serum levels of IL-17A or TNF-α and demographic factors, disease activity (SLEDAI), immunological and biological markers. Both IL-17A and TNF-α were significantly associated with cutaneous involvement in SLE patients, supporting their implication in skin-related inflammatory processes. IL-17A was additionally linked to the presence of an inflammatory syndrome. TNF-α levels correlated with cumulative organ damage and were elevated in patients with malignancies, suggesting that patients with higher TNF-α accumulated significantly more irreversible organ damage over time. No meaningful associations were observed between cytokine levels and demographic characteristics, disease duration, treatment or global SLE activity. Full article

(This article belongs to the Special Issue Autoimmune Diseases: From Pathogenesis to Treatment and Prognostic Markers)

25 pages, 18096 KB

Open AccessArticle

Evaluation of the Drug–Polymer Compatibility and Dissolution Behaviour of Fenbendazole–Soluplus^® Solid Dispersions Prepared by Hot-Melt Extrusion

by Amirhossein Karimi, Gilberto S. N. Bezerra, Clement L. Higginbotham and John G. Lyons

Polymers 2026, 18(3), 333; https://doi.org/10.3390/polym18030333 (registering DOI) - 26 Jan 2026

Abstract

Fenbendazole is an important anti-parasitic medicine widely used in the veterinary field and has recently been considered as a possible anti-cancer agent in humans by some researchers. Fenbendazole encounters challenges in its usage due to its limited aqueous solubility, which consequently impacts its [...] Read more.

Fenbendazole is an important anti-parasitic medicine widely used in the veterinary field and has recently been considered as a possible anti-cancer agent in humans by some researchers. Fenbendazole encounters challenges in its usage due to its limited aqueous solubility, which consequently impacts its therapeutic efficacy. In this work, an in vitro mechanistic investigation was conducted to evaluate the compatibility, amorphization behaviour and dissolution profile of fenbendazole dispersed in Soluplus^® using the solid dispersion approach via hot-melt extrusion. Three different fenbendazole/Soluplus^® ratios were formulated and characterised through systematic experimentation. Powder X-Ray Diffraction (PXRD), Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray (EDX) and Fourier Transform Infrared Spectroscopy (FTIR) were employed for thermal, physical, chemical and morphological analyses. The solubility of the drug formulation during a dissolution test was investigated using Ultraviolet–Visible (UV–Vis) spectrophotometric measurements. In vitro dissolution testing in acidic and neutral media was employed as a controlled environment to compare dissolution behaviour among different loadings. The extrudates demonstrated markedly enhanced apparent solubility compared to neat fenbendazole, with the 5% formulation showing the highest dissolution rate (approximately 85% after 48 h). This improvement can be attributed to better wetting properties and drug dispersion within the Soluplus^® matrix. This innovative strategy holds promise in surmounting fenbendazole’s solubility limitations, presenting a comprehensive solution to enhance its therapeutic effectiveness. Full article

(This article belongs to the Section Smart and Functional Polymers)

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21 pages, 9165 KB

Open AccessArticle

MSMC: Multi-Scale Embedding and Meta-Contrastive Learning for Few-Shot Fine-Grained SAR Target Classification

by Bowen Chen, Minjia Yang, Yue Wang and Xueru Bai

Remote Sens. 2026, 18(3), 415; https://doi.org/10.3390/rs18030415 (registering DOI) - 26 Jan 2026

Abstract

Constrained by observation conditions and high inter-class similarity, effective feature extraction and classification of synthetic aperture radar (SAR) targets in few-shot scenarios remains a persistent challenge. To address this issue, this article proposes a few-shot fine-grained SAR target classification method based on multi-scale [...] Read more.

Constrained by observation conditions and high inter-class similarity, effective feature extraction and classification of synthetic aperture radar (SAR) targets in few-shot scenarios remains a persistent challenge. To address this issue, this article proposes a few-shot fine-grained SAR target classification method based on multi-scale embedding network and meta-contrastive learning (MSMC). Specifically, the MSMC integrates two complementary training pipelines; the first employs metric-based meta-learning to facilitate few-shot classification, while the second adopts an auxiliary training strategy to enhance feature diversity through contrastive learning. Furthermore, a shared multi-scale embedding network (MSEN) is designed to extract discriminative multi-scale features via adaptive candidate region generation and joint multi-scale embedding. The experimental results on the MSTAR dataset demonstrate that the proposed method achieves superior few-shot fine-grained classification performance compared to existing methods. Full article

(This article belongs to the Section AI Remote Sensing)

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21 pages, 2403 KB

Open AccessArticle

Blockchain-Enabled Data Supply Chain Governance: An Evolutionary Game Model Based on Prospect Theory

by Jie Zhang and Jian Yang

Mathematics 2026, 14(3), 432; https://doi.org/10.3390/math14030432 (registering DOI) - 26 Jan 2026

Abstract

With the continuous expansion of data trading, the data supply chain system has gradually developed and improved. However, frequent security issues during the data transaction process have seriously hindered the development of the digital economy. As a key link in the data supply [...] Read more.

With the continuous expansion of data trading, the data supply chain system has gradually developed and improved. However, frequent security issues during the data transaction process have seriously hindered the development of the digital economy. As a key link in the data supply chain, the data trading market needs to use blockchain technology to achieve full-chain supervision of the data supply chain, which has become a top priority. Based on prospect theory, this paper constructs an evolutionary game model composed of data suppliers, consumers and data trading markets at all levels. The main factors affecting the system game strategy are discussed. The results show that: (1) The development of the data supply chain system can be divided into three stages, and blockchain technology plays a key role in realizing full-chain supervision of the data transaction process. The costs of blockchain adoption, market rewards, and penalties significantly affect the behavior of all parties. (2) The behavior of data suppliers has strong negative externalities and affects other participants. In addition, the larger the size of the data transaction, the lower the probability of breach by the data provider. (3) Adopting blockchain technology and implementing effective incentives can promote the development of the data supply chain. Full article

(This article belongs to the Special Issue Dynamic Analysis and Decision-Making in Complex Networks)

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20 pages, 1784 KB

Open AccessArticle

Does Urban Digital Infrastructure Bring Skill-Biased Technological Change? Evidence from China

by Min Song, Lingzhi Shi and Xinyu Liu

Systems 2026, 14(2), 124; https://doi.org/10.3390/systems14020124 (registering DOI) - 26 Jan 2026

Abstract

The technological attributes of urban digital infrastructure (UDI) are transforming labor skill structures in the market, thereby altering changes in skill premiums. This study investigates the relationship between UDI and skill premiums by developing a theoretical model that incorporates both digital and material [...] Read more.

The technological attributes of urban digital infrastructure (UDI) are transforming labor skill structures in the market, thereby altering changes in skill premiums. This study investigates the relationship between UDI and skill premiums by developing a theoretical model that incorporates both digital and material capital. Using data from the China Labor Force Dynamic Survey and urban statistics, we examine the underlying mechanisms. The findings indicate that UDI exhibits skill-biased technological attributes, thereby increasing the skill premium. UDI development raises the demand for high-skilled labor across both skill-intensive and non-skill-intensive industries, altering the labor skill structure and consequently elevating the skill premium. This effect stems from the complementarity between UDI-related digital capital and high-skilled labor. Compared to material capital, deepening digital capital enables high-skilled labor to contribute more significantly to output. Full article

(This article belongs to the Section Systems Practice in Social Science)

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27 pages, 1234 KB

Open AccessSystematic Review

A Systematic and Thematic Review of Greenwashing in the Tourism and Hospitality Industry

by Merve Onur, Aykut Göktuğ Soylu, Bülent Yorgancı and Reha Kılıçhan

Sustainability 2026, 18(3), 1255; https://doi.org/10.3390/su18031255 (registering DOI) - 26 Jan 2026

Abstract

In recent years, greenwashing has been seen as a critical issue in the tourism and hospitality sector. This study is structured to systematically examine the literature on greenwashing in the tourism and hospitality industry and to establish a study identity. The study is [...] Read more.

In recent years, greenwashing has been seen as a critical issue in the tourism and hospitality sector. This study is structured to systematically examine the literature on greenwashing in the tourism and hospitality industry and to establish a study identity. The study is based on the evaluation of 42 qualified articles from the WoS and Scopus databases using the SLR method, in harmony with the PRISMA protocol. As a result of the analyses, the research was classified into seven thematic headings: consumer perception and behavioral responses; employee behavior and internal effects; corporate communication and marketing strategies; strategic corporate social responsibility; critical approaches; greenhushing; and conceptual framework development. According to these findings, extensive study has been focused on consumer perceptions and behavioral responses, yet lacks information on environmentally friendly practices, employee behavior, and organizational structures. This study is important because it connects these different views, offering a practical model that works for both researchers and professionals. While the agricultural and retail dimensions have been well-documented, this study distinguishes itself by situating the analysis within the unique framework of tourism and hospitality. Full article

(This article belongs to the Special Issue Sustainable Tourism Management and Marketing)

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18 pages, 5170 KB

Open AccessArticle

Two-Dimensional Digital Electromagnetic Micro-Conveyance Device

by Célien Bergeron, Gabriel Géron, Laurent Petit, Erwan Dupont, Nicolas Piton and Christine Prelle

Actuators 2026, 15(2), 75; https://doi.org/10.3390/act15020075 - 26 Jan 2026

Abstract

This paper presents a 2D micro-conveyance device based on a 3 × 3 electromagnetic digital actuator array. This device allows the conveyed object to be moved between several discrete positions distributed in the xy-plane through a collaborative actuation of the digital actuators. Each [...] Read more.

This paper presents a 2D micro-conveyance device based on a 3 × 3 electromagnetic digital actuator array. This device allows the conveyed object to be moved between several discrete positions distributed in the xy-plane through a collaborative actuation of the digital actuators. Each digital actuator includes a mobile permanent magnet placed in a square cavity and can be moved between four discrete positions. An analytical model of the digital actuators was proposed and used to design the conveyance device. Then, a prototype was built using rapid prototyping techniques and was experimentally characterized. The reachable workspace of the conveyance device is 56 mm × 56 mm in the xy-plane, and the proposed architecture enables the workspace to be easily enlarged by adding elementary modules. The distance between two discrete positions is 4 mm, and the positioning repeatability was measured as 5.5 µm. The maximum conveyance velocity and transportable mass were found to be up to 16 mm.s⁻¹ and 15 g, respectively. Full article

(This article belongs to the Special Issue AI, Designing, Sensing, Instrumentation, Diagnosis, Controlling, and Integration of Actuators in Digital Manufacturing—2nd Edition)

11 pages, 4271 KB

Open AccessArticle

A Low-Power High-Precision Discrete-Time Delta–Sigma Modulator for Battery Management System

by Ying Li and Wenyuan Li

Electronics 2026, 15(3), 535; https://doi.org/10.3390/electronics15030535 - 26 Jan 2026

Abstract

This paper presents a low-power high-precision Discrete-Time Delta–Sigma (DT-DS) analog-to-digital converter (ADC) for a Battery Management System (BMS), which is critical for monitoring key battery parameters such as voltage, current, and temperature. This design employs a second-order Cascade of Integrators FeedForward (CIFF) architecture [...] Read more.

This paper presents a low-power high-precision Discrete-Time Delta–Sigma (DT-DS) analog-to-digital converter (ADC) for a Battery Management System (BMS), which is critical for monitoring key battery parameters such as voltage, current, and temperature. This design employs a second-order Cascade of Integrators FeedForward (CIFF) architecture using a hybrid chopping technique to effectively suppress 1/f noise and offset. Fabricated in a 180 nm Bipolar-CMOS-DMOS (BCD) process, the ADC achieves a peak signal-to-noise ratio (SNR) of 91.2 dB and a peak signal-to-noise-and-distortion ratio (SNDR) of 90.6 dB within a 600 Hz bandwidth, while consuming only 35 µA from a 1.8 V supply. This corresponds to a figure-of-merit (FoM) of 160.4 dB, calculated based on the SNDR, bandwidth, and power dissipation. Full article

(This article belongs to the Special Issue Feature Papers in Electrical and Autonomous Vehicles, Volume 2)

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20 pages, 9590 KB

Open AccessArticle

Computer-Guided Flapless Immediate Function Dental Implants for Full-Arch Rehabilitations Using the All-on-4 Concept: A 12-Year Clinical and 10-Year Radiographic Retrospective Study

by Miguel de Araújo Nobre, Armando Lopes, Carolina Antunes and Francisco Salvado

Prosthesis 2026, 8(2), 13; https://doi.org/10.3390/prosthesis8020013 - 26 Jan 2026

Abstract

Background/Objectives: Implant-supported rehabilitations using the All-on-4 concept represent a viable treatment option for completely edentulous patients. The guided surgery software allows for the performance of a flapless computer-guided surgery with similar results to those achieved through a flap surgery. This study aimed to [...] Read more.

Background/Objectives: Implant-supported rehabilitations using the All-on-4 concept represent a viable treatment option for completely edentulous patients. The guided surgery software allows for the performance of a flapless computer-guided surgery with similar results to those achieved through a flap surgery. This study aimed to evaluate the long-term outcomes of complete edentulous implant-supported rehabilitations using an All-on-4 arrangement, following a computer-guided protocol. Methods: A total of 111 patients (68 females, 43 males) with an average age of 60.9 years ± 9.67 years were treated. The primary outcome measures were implant and prosthetic survival. Secondary outcome measures were marginal bone loss (MBL) and the incidence of mechanical and biological complications. Results: Thirty-nine patients were lost to follow-up. Thirty-seven implants and five prostheses failed, rendering a 92.5% implant cumulative survival rate and a 96.2% prosthetic survival rate at 12 years. The average MBL per implant was 1.19 ± 1.16 mm, with 1.26 ± 1.33 mm for axial implants and 1.12 ± 0.95 mm for tilted implants at 10 years. The incidence rate of mechanical complications at the patient level was 90.1% for provisional prostheses and 55.9% for definitive prostheses. The rate of biological complications was 14.3% at the implant level. Conclusions: Full-arch rehabilitations following an All-on-4 implant arrangement and assisted by a computer-guided protocol may be a viable alternative for patients with edentulism/hopeless teeth in the long term. Full article

(This article belongs to the Collection Oral Implantology: Current Aspects and Future Perspectives)

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20 pages, 17775 KB

Open AccessArticle

Structural, Swelling, and In Vitro Digestion Behavior of DEGDA-Crosslinked Semi-IPN Dextran/Inulin Hydrogels

by Tamara Erceg, Miloš Radosavljević, Ružica Tomičić, Vladimir Pavlović, Milorad Miljić, Aleksandra Cvetanović Kljakić and Aleksandra Torbica

Gels 2026, 12(2), 103; https://doi.org/10.3390/gels12020103 - 26 Jan 2026

Abstract

In this study, semi-interpenetrating polymer network (semi-IPN) hydrogels based on methacrylated dextran and native inulin were designed as biodegradable carriers for the colon-specific delivery of uracil as a model antitumor compound. The hydrogels were synthesized via free-radical polymerization, using diethylene glycol diacrylate (DEGDA) [...] Read more.

In this study, semi-interpenetrating polymer network (semi-IPN) hydrogels based on methacrylated dextran and native inulin were designed as biodegradable carriers for the colon-specific delivery of uracil as a model antitumor compound. The hydrogels were synthesized via free-radical polymerization, using diethylene glycol diacrylate (DEGDA) as a crosslinking agent at varying concentrations (5, 7.5, and 10 wt%), and their structural, thermal, and biological properties were systematically evaluated. Fourier transform infrared spectroscopy (FTIR) confirmed successful crosslinking and physical incorporation of uracil through hydrogen bonding. Concurrently, differential scanning calorimetry (DSC) revealed an increase in glass transition temperature (T_g) with increasing crosslinking density (149, 153, and 156 °C, respectively). Swelling studies demonstrated relaxation-controlled, first-order swelling kinetics under physiological conditions (pH 7.4, 37 °C) and high gel fraction values (84.75, 91.34, and 94.90%, respectively), indicating stable network formation. SEM analysis revealed that the hydrogel morphology strongly depended on crosslinking density and drug incorporation, with increasing crosslinker content leading to a more compact and wrinkled structure. Uracil loading further modified the microstructure, promoting the formation of discrete crystalline domains within the semi-IPN hydrogels, indicative of physical drug entrapment. All formulations exhibited high encapsulation efficiencies (>86%), which increased with increasing crosslinker content, consistent with the observed gel fraction values. Simulated in vitro gastrointestinal digestion showed negligible drug release under gastric conditions and controlled release in the intestinal phase, primarily governed by crosslinking density. Antimicrobial assessment against Escherichia coli and Staphylococcus epidermidis, used as an initial or indirect indicator of cytotoxic potential, revealed no inhibitory activity, suggesting low biological reactivity at the screening level. Overall, the results indicate that DEGDA-crosslinked dextran/inulin semi-interpenetrating (semi-IPN) hydrogels represent promising carriers for colon-targeted antitumor drug delivery. Full article

(This article belongs to the Special Issue Biopolymer Hydrogels: Synthesis, Properties and Applications)

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15 pages, 3676 KB

Open AccessArticle

Emulsion Quality and Functional Properties of Natural Emulsion Systems with Xanthan Gum as a Stabilizer and Carrier of Compounds Based on Enzymatically Modified Mutton Tallow and Hemp Oil

by Małgorzata Kowalska, Magdalena Wozniak, Anna Zbikowska, Jerzy Szakiel and Paweł Turek

Molecules 2026, 31(3), 431; https://doi.org/10.3390/molecules31030431 - 26 Jan 2026

Abstract

The aging population and increasing prevalence of oxidative stress-related diseases underscore the need for functional food and pharmaceutical formulations enriched with bioactive compounds. This study aimed to design sustainable emulsion systems incorporating enzymatically modified fats with enhanced functional and bioactive properties. Enzymatic interesterification [...] Read more.

The aging population and increasing prevalence of oxidative stress-related diseases underscore the need for functional food and pharmaceutical formulations enriched with bioactive compounds. This study aimed to design sustainable emulsion systems incorporating enzymatically modified fats with enhanced functional and bioactive properties. Enzymatic interesterification was employed as an environmentally friendly alternative to chemical catalysis, enabling the transformation of natural lipids without generating undesirable trans isomers. The lipid phase was formulated from blends of hemp oil, a plant-derived source rich in polyunsaturated fatty acids with documented antioxidant potential, and mutton tallow, in an effort to valorize meat industry by-products. Systematic evaluation of emulsion stability, viscosity, and textural properties was conducted using Turbiscan analysis and texture profile analysis. The results demonstrated that xanthan gum concentration was the primary determinant of structural stability, physicochemical stability, and structural integrity of the emulsion systems. Formulation no. 38 (0.8% w/w xanthan gum) was identified as the statistically most stable system based on Turbiscan Stability Index values (TSI = 1.4). Although emulsions containing 1.0% w/w xanthan gum exhibited similarly low TSI values and slightly smaller final droplet diameters, formulation E38 showed the smallest increase in droplet size during storage (<1 µm), indicating superior resistance to structural changes over time. Fat composition showed minimal influence on emulsion behavior, suggesting that lipid selection should prioritize nutritional and bioactive value. These findings indicate that emulsions based on enzymatically modified fats and stabilized with natural polysaccharides can serve as physically stable systems with potential applicability in food, cosmeceutical, and pharmaceutical formulations intended for bioactive compound delivery. Full article

(This article belongs to the Section Food Chemistry)

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