Search Results (577)

Amphiphilic statistical copolymers are valuable synthetic macromolecules for the formation of small, well-defined nanoassemblies able to be utilized as nanocarriers for drug and/or gene delivery applications. In this work, the synthesis of amphiphilic linear statistical copolymers of the poly(benzyl methacrylate-co-dimethylaminoethyl methacrylate) [P(BzMA-co-DMAEMA)] type is described in three different comonomer compositions. Their synthesis was realized through a one-pot reversible addition-fragmentation chain transfer (RAFT) solution polymerization scheme. Further quaternization of the amine groups of DMAEMA with methyl iodide (CH₃I) resulted in cationic amphiphilic statistical copolymers. Macromolecular characterization was performed using size exclusion chromatography (SEC) and spectroscopic techniques (¹H-NMR and ATR-FTIR). The aggregation properties of the copolymers in aqueous media were studied via dynamic light scattering (DLS) and electrophoretic light scattering (ELS). Bimodal size distributions were determined in some cases. The BzMA to DMAEMA ratio determined aggregate size, with the copolymer of lower hydrophobic BzMA content producing smaller nanoparticles. Cryogenic transmission electron microscopy (cryo-TEM) showed the presence of spherical assemblies resulting from aggregation of primary micelles in the case of higher BzMA content. The copolymer aggregates experience dissociation at high salt concentration, and the pH-responsiveness of the amine precursors results in the formation of multifunctional potential nanocarriers. Full article

Quercetin (QE), a flavonol-type polyphenol, and oat β-glucan (OβG), a soluble dietary fiber, are natural active ingredients with the potential to reduce the risk of diabetes. OβG slows starch digestion by modifying chyme viscosity, while QE inhibits digestive enzyme activity. This study aimed to explore the formation mechanism and structural characteristics of QE-OβG complexes, as well as their functional properties in terms of viscosity and amylase inhibitory activities. It was found that QE and OβG formed stable non-covalent complexes via hydrogen bonding and hydrophobic interactions. At a mass ratio of 0.6, the binding capacity was relatively high with a moderate aggregation degree, representing a balanced interaction state. Changes in turbidity and particle size indicated that different environmental factors (pH, temperature, ionic strength) exert differential effects on the aggregation behavior of the complex. In addition, the complex exhibited a unique fibrous-block morphology, enhanced thermal stability, improved starch system viscoelasticity, and stronger mixed-type reversible α-amylase inhibition (IC₅₀ = 2.629 mg/mL). This study clarifies the interaction mechanism between QE and OβG, provides a reliable theoretical basis for the development of novel hypoglycemic foods, and offers new insights into multi-component regulation strategies for slow-digestion food design. Full article

Cancer is the second leading cause of death worldwide. Mutations in the TP53 gene lead to a loss of tumor suppressor function and an oncogenic gain of function for the protein, resulting in a more invasive, metastatic, and chemoresistant phenotype. Diverse structural studies have demonstrated that mutant p53 core domain unfolding is not irreversible. Thus, reactivation toward its wild-type-like conformation or inactivation of its mutant p53 capacities may restore the expression of genes in its tumor suppressor pathways, resulting in enhanced responses to current therapies. Resveratrol (3,4′,5-trihydroxy-trans-stilbene) is a phytoalexin naturally found in more than 70 plant species that has widely proven antiproliferative and pro-apoptotic properties, as well as a capacity to reverse multidrug resistance in various cancer types. Interestingly, it has recently been demonstrated that resveratrol directly interacts with the p53 core domain and reduces mutant p53 aberrant aggregation. In this context, our study aims to elucidate whether resveratrol may induce antiproliferative and pro-apoptotic pathways regardless of a mutant background. We observed that resveratrol has an antiproliferative effect in cancer cells, independent of p53 status, and leads to apoptosis after 48 h of treatment. Resveratrol also induces the expression of p53 tumor suppressor target genes, which are involved in cell cycle arrest and apoptosis. Even though the previous effects are more significant in cells expressing wild-type p53, resveratrol drastically sensitizes all cancer cell lines, regardless of p53 status, to cisplatin treatment, making it a promising enhancer compound to overcome chemoresistance associated with p53. Full article

Background/Objectives: Spaceflight presents a combination of physical and psychosocial stressors that may impact biological aging and health. Understanding how spaceflight influences molecular aging processes is essential as commercial and professional space travel continue to expand. Methods: We analyzed publicly available DNA methylation data to evaluate longitudinal changes in 10 epigenetic aging biomarkers, 6 leukocyte proportion estimates, and 109 DNA methylation-derived protein scores in two astronauts participating in Axiom Space’s AX1 17-day low Earth orbit mission. We calculated mean values for all biomarkers across three timepoints: two weeks before spaceflight (T0), 24 h after spaceflight (T1), and three months after spaceflight (T2). Using the mean values, we next calculated the fold change from baseline for all biomarkers. Because the sample size precluded statistical testing, we identified the top 5% of absolute fold changes to highlight the largest shifts across candidate biomarkers. Results: Across epigenetic clocks, MiAge showed the greatest T0–T1 decrease (−4.26-fold), and DNAmFitAge showed the greatest T0–T2 increase (2.47-fold). NK cells exhibited the largest T0–T1 change, decreasing by 49% (−0.49-fold). B cells exhibited the largest T0–T2 change, decreasing by 11% (−0.11-fold). Proteins meeting a predefined top 5% fold change from baseline criterion at both T1 and T2, included BMP1, CLEC11A, CXCL11, FAP, and LTF. Enrichment analysis indicated involvement of serine-type endopeptidase activity, molecular function activator activity, and cell aggregation pathways. Conclusions: These findings suggest that spaceflight influences methylation-derived biomarkers of aging and immunity even in short-duration missions. These results, though exploratory, contribute to emerging efforts to characterize molecular resilience and vulnerability in human spaceflight. Full article

We analyze parameter identifiability in a Marchuk-type immune-response model using longitudinal whole-blood transcriptomic signatures from the influenza challenge. Latent states are extracted from curated gene signatures derived from nine symptomatic and eight asymptomatic subjects. The governing delay differential equations are cast in a linear-in-parameters form; derivatives are estimated by smoothing splines, coefficients are fit by ridge regression, and the delay $\tau$ is selected by grid search. We find that the parameters governing viral and innate dynamics are consistently identifiable, with low relative error, and are highly determined, whereas adaptive-immunity and tissue-damage parameters are poorly constrained by transcriptomics alone. Introducing a small additive background term and tissue dependence markedly reduces residual variance and stabilizes estimates. Symptomatic patients exhibit a characteristic regulatory delay near 21 h. These results show that aggregated transcriptomic time series can reliably identify some subsystems of classical immune models, but that adaptive immunity and damage dynamics require explicit structural extensions or additional data modalities. The study provides a practical identification pipeline and concrete guidance on model extensions needed for transcriptomic-driven mechanistic inference. Full article

For the environment and the daily life of urban settlements, in the context of contemporary challenges, severe meteorological events rank second worldwide. Therefore, these events tend to become a real threat to human society and to specific economic activities. The main objective of this study is to analyze the spatio-temporal evolution of severe meteorological events in urban environments and to assess their relationship with atmospheric circulation regimes and urban thermal conditions. The analysis focuses on five types of severe events (significant atmospheric precipitation, hail, strong winds, tornadic structures, and cloud-to-ground lightning) recorded in 11 cities located in the historical region of Muntenia, Romania, over the period 2014–2024. The methodological framework is based on three complementary components. First, a new database was developed by integrating information from multiple sources, including the National Meteorological Administration (ANM), the European Severe Storms Laboratory (ESSL), international databases, and validated media reports, with spatio-temporal filtering and aggregation into synoptic episodes. Second, atmospheric circulation regimes were identified using ECMWF ERA5 reanalysis data, based on geopotential height anomalies at the 500 hPa level, allowing the classification of large-scale synoptic patterns. Third, urban thermal conditions were assessed using the ECMWF CERRA regional reanalysis dataset, which provides high-resolution air temperature data, enabling the analysis of urban–peri-urban thermal contrasts and the estimation of the urban heat island effect. The results highlight a total of 997 severe meteorological events, of which 253 (25.6%) were recorded in the analyzed urban areas, 85 (15.9%) in other towns, and 583 (58.5%) in rural areas. The analysis reveals pronounced interannual and intraseasonal variability, as well as distinct spatial clustering patterns, particularly in urban and peri-urban zones. Among the circulation regimes, the Zonal Regime exhibits the highest event rate, suggesting increased favorability for severe weather occurrence, while other regimes show weaker or even inhibitory effects. In addition, most severe events were associated with positive urban–peri-urban temperature contrasts, indicating an active contribution of the urban heat island effect. By combining observational data, synoptic-scale analysis, and urban-scale thermal assessment, this study provides an integrated regional perspective on severe meteorological events and contributes to the enrichment of data sources in the region, while improving the understanding of their dynamics in urban environments affected by data limitations. Full article

Understanding the hydration dynamics of montmorillonite clay minerals is critical for predicting their behavior in geotechnical and environmental applications. However, prior ESEM studies have employed separate measurement techniques and lack synchronized multi-scale observations linking microscale aggregate morphology to nanoscale interlayer spacing, with kinetic timescales for clay equilibration remaining unknown. This study employs in situ environmental scanning electron microscopy (ESEM) combined with synchronized X-ray diffraction (XRD) to directly observe and quantify the hydration and dehydration processes of montmorillonite SWy-1 under controlled pressure and temperature conditions on the same sample. ESEM enabled direct visualization of water–clay interactions by precisely controlling chamber pressure (4–5.3 Torr), while synchronized XRD measured basal spacing (d₀₀₁) changes. Key findings reveal: single water-layer hydration (1W) produces ~19% aggregate swelling and two-layer hydration (2W) yields ~32% swelling; rapid dehydration occurs within 3 min with complete equilibration by 15 min; hydration exhibits steeper pressure dependency (slope = 2.7249) compared to dehydration (slope = 1.6702), indicating thermodynamically driven water uptake but kinetically limited desorption; and water-adsorption isotherms exhibited type-H3 hysteresis. This dual-scale integration establishes practical timescales for clay equilibration and provides critical mechanistic insights for predicting clay behavior in geotechnical engineering and engineered barrier design. Full article

Diabetic peripheral neuropathy (DPN) is a common and debilitating complication of diabetes mellitus which affects individuals with both type 1 and type 2 diabetes mellitus (T2DM), presenting with sensory loss, pain, and progressive nerve dysfunction. DPN pathogenesis is multifactorial: chronic hyperglycemia activates the polyol, hexosamine, and protein kinase C (PKC) pathways, increases advanced glycation end-products, and drives oxidative stress, mitochondrial dysfunction, inflammation, and impaired neurotrophic signaling. In addition to hyperglycemia-driven mechanisms, dyslipidemia and microvascular insufficiency exacerbate neural ischemia and metabolic stress. Recent mechanistic, animal, and associative human studies further implicate amyloidogenic toxicity, particularly from human islet amyloid polypeptide (hIAPP), as a plausible contributory factor in peripheral nerve degeneration in T2DM, linking protein misfolding and aggregation to axonal damage and demyelination in DPN. Despite increased understanding of these mechanisms, current treatments remain mainly symptomatic. Emerging therapeutic strategies, including antioxidants, anti-inflammatory agents, modulators of mitochondrial function, amyloid oligomer modulators, neurotrophic enhancers, and regenerative approaches such as stem cells and gene-based therapies, offer potential to modify disease progression. The strength of evidence across these methods varies, ranging from mechanistic and animal studies to early human research and, in some cases, randomized clinical trials. Therefore, although several candidates show potential to alter the disease, few have demonstrated consistent benefits on objective measures of nerve structure or function in large clinical trials. This review summarizes the key mechanisms driving DPN in T2DM and highlights promising therapeutic innovations poised for clinical translation. Full article

Human motivation is governed by a long-memory cognitive process in which the depth of temporal integration—how far into the past the system draws upon accumulated experience—is not fixed, but dynamically compressed under cognitive stress. Despite extensive empirical evidence that acute stress impairs working memory and narrows temporal integration in decision-making, no existing mathematical framework has formally coupled the memory depth of the governing operator to a physiologically grounded stress indicator. To address this gap, we propose a stress-adaptive variable-order fractional model for motivational intensity $M\left(t\right)$, in which the Caputo fractional order $\alpha \left(t\right)$ varies inversely with an aggregated stress indicator $\sigma \left(t\right)$ through the Hill-type coupling $\alpha \left(t\right)={\alpha }_{min}+({\alpha }_{max}-{\alpha }_{min})C/(C+\sigma \left(t\right))$, thereby encoding the empirically documented shift from deep integrative to shallow heuristic processing as cognitive load increases. Rather than deriving the model by algebraic manipulation of a differential equation, we formulate it directly as a causally consistent type-III Volterra integral equation, in which the memory kernel is evaluated at the history time s, ensuring that the weight assigned to each past state reflects the memory depth that was physiologically active when that state was experienced. Well-posedness is established rigorously via the Banach fixed-point theorem with explicit contraction constants, uniform boundedness and non-negativity of solutions are derived through the fractional Gronwall inequality, and numerical solutions are computed using an Adams–Bashforth–Moulton predictor–corrector scheme adapted to the variable-order kernel. Five numerical experiments demonstrate that stress-induced variation in $\alpha \left(t\right)$ produces qualitatively richer dynamics compared with the tested constant-order baselines: the proposed model achieves a steeper peak decline rate (0.48 versus 0.19–0.45), a larger burnout gap (3.15 versus 1.92–2.81), and faster recovery to ninety percent of peak motivation (4.2 versus 3.9–7.3 time units), while the empirically observed numerical convergence approaches $O\left(h^2\right)$ for sufficiently small step sizes. The framework offers a principled phenomenological substrate for memory-adaptive cognitive modelling, with direct implications for stress-aware intelligent tutoring systems that are capable of inferring $\alpha \left(t\right)$ in real time from biometric signals such as heart rate variability or galvanic skin response, and adjusting instructional complexity accordingly. Empirical calibration against learning-analytics and psychophysiological datasets, together with stochastic extensions for probabilistic burnout-risk prediction, are identified as immediate priorities for future research. Full article

The extensive use of agrochemicals and plastic materials has led to the accumulation of persistent pollutants in agricultural soils, raising concerns about agroecosystems through posing potential risks to soil and environmental health. This review synthesizes recent knowledge on these pollutant sources, including their distribution, fate, transformation pathways, and detection methods, as well as their impacts on soil physicochemical properties, microbial populations, plants, and ecosystems. Existing findings indicate that agrochemicals and micro-nano plastics (MPs-NPs) can significantly impede the stability of soil aggregation, increase soil water holding capacity (WHC) and porosity, reduce bulk density and infiltration, alter soil structure, and affect soil pH, cation exchange capacity (CEC), electrical conductivity (EC), and nutrient retention capacity. Moreover, exposure to these pollutants alters soil microbial communities, enzymatic activity, nitrification and denitrification processes, and arbuscular mycorrhizal fungi (AMF), thereby affecting carbon pools and fluxes as well as nutrient cycling. However, the magnitude and direction of these effects are strongly influenced by soil type, pollutant class, concentration, and physicochemical properties. Furthermore, terrestrial and aquatic ecosystems are negatively affected due to the presence of such persistent pollutants by impairing their physiological processes. Despite these findings, mechanistic understanding remains limited due to a lack of long-term field investigation and proper detection methods, particularly regarding NPs. A comprehensive understanding of agrochemical and MP-NP interactions is essential for developing sustainable soil management strategies and agroecosystems. Future studies should address the development of standardized NP detection methods and the conducting of long-term field studies to elucidate MP-NP and agrochemical interactions, soil impacts, and crop uptake mechanisms. Full article

To address the issues of high energy consumption and unstable construction quality caused by high-temperature heating during the preparation of traditional hot-mixed/grouted semi-flexible pavement (SFP) mixtures, a cold-mixed integrated (CMI) process was proposed. In addition, the material composition of the mixtures was optimized. The effects of the preparation process and binder type on the high- and low-temperature performance, water stability, and fatigue performance were then analyzed. Furthermore, the microstructural characteristics of the semi-flexible mixture were also investigated. The results indicated that the CMI process facilitated the formation and uniform distribution of calcium silicate hydrate (C-S-H), enhanced the binder’s ability to encapsulate aggregates and fill skeletal voids, significantly reduced the mixture’s void ratio, and improved its pavement performance. The proposed procedure was a means of enhancing high-temperature stability and fatigue life (an increase of 80% and 200 times compared to the hot-mixed/grouted (HMG) process, and 5 times and 300 times compared to AC-13, respectively). Compared with the HMG process, the CMI process offered greater advantages in enhancing the high-temperature stability and fatigue resistance of the mixture, particularly when using SBS-modified asphalt, where fatigue performance exhibited an order-of-magnitude improvement. Furthermore, while SBS modification could improve the road performance of SFP materials, mixtures prepared with SBS-modified emulsified asphalt demonstrated more significant enhancements in high-temperature stability and fatigue resistance, approximately 2 times and 10 times higher than SBS-modified mixtures, respectively. The addition of styrene–acrylic emulsion (SAE) could further enhance the low-temperature crack resistance by approximately 7%. The research results can provide a reference for the development and application of preparation processes for semi-flexible mixtures. Full article

Large-scale and widely distributed air-conditioning (AC) loads can be aggregated into load-type Virtual Power Plants (VPPs) to participate in peak-shaving ancillary services, thereby improving the allocation of demand-side electricity resources. However, current AC aggregation methods primarily focus on meeting peak-shaving instructions and generally employ fixed incentive pricing and proportional capacity allocation, making it difficult to balance user revenue and satisfaction and thereby constraining the flexibility of VPP demand-side regulation. This paper proposes a unified incentive-based demand response scheduling framework for both fixed- and variable-frequency AC loads across industrial, commercial, and residential scenarios. Based on the Equivalent Thermal Parameter model, AC loads are classified into curtailable and shiftable types, with their adjustable boundaries characterized by a Time-of-Use (TOU) elasticity-based interaction willingness model and a fuzzy load transfer rate model, respectively. A three-objective optimization model is established to maximize user revenue while minimizing user dissatisfaction and scheduling error, with incentive pricing and capacity allocation jointly optimized via Non-dominated Sorting Genetic Algorithm III (NSGA-III). Case studies are conducted on a load-type VPP covering three scenarios, namely a large industrial zone, a commercial zone, and a residential zone, under weekday and non-weekday TOU tariffs and three representative 1 h peak-shaving periods. Compared with a fixed-pricing benchmark, the proposed strategy increases total user revenue by 9.4% to 11.4% and reduces weighted average dissatisfaction by 0.27 to 1.92%. The case study results demonstrate that the proposed method can improve the trade-off between user revenue and satisfaction. Full article

Dissolved silicic acid (Si) in groundwater can reduce the As-removal performance of adsorbents used for treating contaminated water. However, its effects on Mg-based adsorbents remain largely unexplored. In this study, As-removal tests were conducted under various test conditions to evaluate the suitability of Mg-based adsorbents (MgO, Mg(OH)₂, and MgCO₃) for the purification of As-contaminated water in the presence of Si. As-removal performance varied significantly depending on the Mg-based adsorbent type and dosage (W_Ad0/V), As valence, and the initial As and Si (C_Si0) concentrations. In some cases, As removal improved at relatively low C_Si0; however, overall performance decreased with increasing C_Si0 for all Mg-based adsorbents. Moreover, compared with Mg(OH)_2, the performance of MgO and MgCO₃ was more strongly affected by Si. This inhibition is attributed to competition between Si and As for adsorption sites on the adsorbent surface. Furthermore, for MgO and MgCO₃, the amount of As removed by coprecipitation with secondarily generated Mg(OH)₂ aggregates was inferred to decrease with increasing C_Si0, because higher C_Si0 lowered the solution pH. Overall, MgO and Mg(OH)₂ can function effectively as adsorbents for As treatment when W_Ad0/V is appropriately selected, considering the range of Si concentrations typically found in groundwater. Full article

Ramadan fasting substantially alters meal timing, sleep patterns, and daily activity, thereby increasing the risk of hypoglycaemia in adults with type 1 diabetes (T1D). Although continuous glucose monitoring (CGM) systems provide real-time alerts, these are largely reactive or limited to short prediction horizons, offering insufficient warning under fasting-related behavioural and circadian disruption. This study aims to evaluate whether behaviour-aware, temporally enriched recurrent deep learning models, leveraging multimodal CGM and wearable-derived signals, can forecast hypoglycaemia one hour ahead during Ramadan and the post-fasting period. In an observational, free-living cohort study conducted in Qatar, 33 adults with T1D were monitored using CGM and a wrist-worn wearable during Ramadan 2023 and the subsequent month. Multimodal data were aggregated into hourly features and organised into rolling 36 h sequences. In addition to physiological signals, explicit temporal and circadian proxy features were engineered, including cyclic time encodings, day–night indicators, and Ramadan-specific behavioural windows (e.g., pre-iftar, iftar, post-iftar, and fasting phases). Recurrent models, including LSTM and BiLSTM architectures, were trained using patient-wise, leak-free splits, with focal loss applied to address class imbalance. Model performance was evaluated on a held-out, naturally imbalanced test set using ROC AUC, precision–recall AUC, recall, and probability calibration, alongside cross-phase evaluation between Ramadan and post-fasting periods. Following quality control, 1164 participant-days were retained, with hypoglycaemia accounting for approximately 4% of hourly observations. Temporal feature enrichment and the use of a 36 h lookback window improved both discrimination and calibration, with performance stabilizing beyond this horizon. On the imbalanced test set, the best-performing multimodal model achieved an ROC AUC of 0.867 and a precision–recall AUC of 0.341, identifying 77% of next-hour hypoglycaemic events at a sensitivity-focused operating point (precision = 0.14). The selected BiLSTM model demonstrated good probability calibration (Brier score ≈ 0.03). Models trained using wearable-derived inputs alone achieved comparable discrimination and, in some configurations, higher precision–recall AUC than CGM-only baselines. Notably, models trained on the original imbalanced data outperformed resampled variants, suggesting that temporal and behavioural features provided sufficient discriminatory signal without requiring aggressive class balancing. Cross-phase evaluation indicated robust generalisation, particularly for the BiLSTM model. Overall, behaviour-aware, temporally enriched multimodal models can provide calibrated, hour-ahead hypoglycaemia risk estimates during Ramadan fasting in adults with T1D, enabling proactive intervention beyond reactive CGM alerts. Explicit modelling of circadian and behavioural dynamics enhances predictive performance under real-world class imbalance. Furthermore, integrating wearable-derived behavioural and physiological signals adds predictive value beyond CGM alone, supporting robustness across varying levels of contextual data availability. External validation and prospective clinical evaluation are required prior to deployment. Full article

Low-molecular-weight gelators (LMWGs) have attracted growing attention as versatile alternatives to conventional polymeric thickeners and gelators, owing to their ability to form three-dimensional fibrillar networks through non-covalent self-assembly and to undergo reversible sol–gel transitions in response to external stimuli. Among the various stimuli that can be exploited, pH represents a particularly attractive trigger given its direct relevance to biological and physiological environments. This review focuses on three categories of pH-responsive LMWGs that have shown notable progress over the past decade yet remain relatively underexplored in the literature. First, N-oxide-type hydrogelators are discussed, with emphasis on amide amine oxide-based surfactants and pyridine-N-oxide frameworks. The pH-dependent protonation of the N-oxide moiety modulates intermolecular hydrogen bonding, thereby governing self-assembly and gel formation. The structural versatility of these gelators enables rational tuning of aggregate morphology and confers clear pH and temperature responsiveness. Second, recent advances in phenylboronic acid-based LMWGs are highlighted. Although boronic acid derivatives have long been studied as dynamic crosslinking units in polymeric hydrogels, 3-isobutoxyphenylboronic acid was recently identified as the first example of phenylboronic acid functioning as an LMWG, in which gelation is driven primarily by hydrogen bonding and pH responsiveness is exploited for stimuli-triggered gel disruption rather than gel formation. Third, pH-responsive orthogonal self-assembly systems are reviewed. Representative examples include multicomponent hybrid hydrogels combining pH-activated LMWGs with polymer gelators for controlled drug release, pH-triggered self-sorting of two LMWGs without any polymeric component, and bio-based orthogonal hydrogels composed of a glucolipid LMWG and cellulose nanocrystals. For each system, both advantages and remaining limitations are critically assessed. Collectively, this review aims to provide a timely overview of emerging trends in pH-responsive LMWG research and to offer perspectives on the rational design of next-generation stimuli-responsive soft materials. Full article