Search Results (11,456)

Brown algae of the Cystoseira genus are recognized as valuable sources of bioactive compounds, including polysaccharides. Within the framework of current restoration efforts regarding damaged Ericaria amentacea populations in the Mediterranean Sea, the valorization of apices derived from ex situ cultivation waste represents a sustainable opportunity for industrial and biomedical applications. In this study, sodium alginate (SA) was extracted from E. amentacea apex by-products using a hydrothermal–alkaline method and subsequently chemically characterized. FTIR analysis showed O-H, C-H, and COO- stretching compatible with commercial alginates, while 1H-NMR spectroscopy indicated high β-D-mannuronic acid content, with an M/G ratio of 2.33. The extracted SA displayed a molecular weight of 1 × 10⁴ g/mol and a polydispersity index of 3.5. The bioactive properties of the SA extract were investigated in chemico and in vitro. SA exhibited remarkable antioxidant activity, showing significant DPPH and nitric oxide-radical-scavenging capacity. Furthermore, SA demonstrated a strong anti-inflammatory effect in LPS-stimulated macrophages through modulation of several inflammatory mediators (i.e., IL-6, IL-8/CXCL5, MCP-1, and TNF-α). In particular, SA promoted a striking iNOS gene expression inhibition, which, paired with its direct NO-scavenging ability, paves the way for future pharmacological use of E. amentacea derivatives, particularly if sustainably obtained from restoration activity waste. Full article

Human–machine shared control has been widely adopted to enhance driving performance and facilitate smooth transitions between manual and fully autonomous driving. However, existing authority allocation strategies often neglect real-time assessment of scenario complexity and driver workload. To address this gap, we leverage non-invasive eye-tracking devices and the 3D virtual driving simulator Car Learning to Act (CARLA) to collect multimodal data—including physiological measures and vehicle dynamics—for the real-time classification of scenario complexity and cognitive workload. Feature importance is quantified using the SHAP (SHapley Additive exPlanations) values derived from Random Forest classifiers, enabling robust feature selection. Building upon a Hidden Markov Model (HMM) for workload inference and a Model Predictive Control (MPC) framework, we propose a novel human–machine shared control architecture with adaptive authority allocation. Human-in-the-loop validation experiments under both high- and low-workload conditions demonstrate that the proposed strategy significantly improves driving safety, stability, and overall performance. Notably, under high-workload scenarios, it achieves substantially greater reductions in Time to Collision (TTC) and Time to Lane Crossing (TLC) compared to low-workload conditions. Moreover, the adaptive approach yields lower controller load than alternative authority allocation methods, thereby minimizing human–machine conflict. Full article

Background: Due to chronic venous insufficiency, venous leg ulcers (VLUs) develop as chronic wounds characterized by impaired healing, persistent inflammation, and endothelial dysfunction. Nitrosative stress, mitochondrial damage, and tissue apoptosis caused by excess nitric oxide (NO) produced by iNOS in macrophages and fibroblasts are contributing factors in the chronic wound environment; therefore, pharmacological modulation of iNOS presents an attractive mechanistic target in chronic wound pathophysiology. Methods: Herein, we present the use of a structure-based computational strategy to assess the inhibition of tavaborole, a boron-based antifungal agent, against iNOS using human iNOS crystal structure (PDB ID: iNOS) by molecular docking using AutoDock 4.2, 500 ns simulation of molecular dynamics (MD), with equilibration within ~50 ns and analyses over full trajectory and binding free energy calculations through the MM-PBSA approach. Results: Docking studies showed favorable binding of tavaborole (–6.1 kcal/mol) in the catalytic domain, which stabilizes contacts with several key residues (CYS200, PRO350, PHE369, GLY371, TRP372, TYR373, and GLU377). MD trajectories for 1 ns showed stable structural configurations with negligible deviations (RMSD ≈ 0.44 ± 0.10 nm) and hydrogen bonding, and MM-PBSA analysis confirmed energetically favorable complex formation (ΔG_binding ≈ 18.38 ± 63.24 kJ/mol) similar to the control systems (L-arginine and 1400W). Conclusions: Taken together, these computational findings indicate that tavaborole can stably occupy the iNOS active site and interact with key catalytic residues, providing a mechanistic basis for further in vitro and ex vivo validation of its potential as an iNOS inhibitor to reduce nitrosative stress and restore endothelial homeostasis in venous leg ulcers, rather than direct therapeutic proof. Full article

Background: Sepsis-associated liver injury (SALI) is a serious complication of sepsis that increases the risk of organ dysfunction and mortality; however, early identification of high-risk patients remains difficult due to nonspecific clinical features and complex pathophysiology. This study aimed to develop machine learning (ML) models to predict 28-day mortality in SALI patients within the first 24 h of intensive care unit (ICU) admission. Methods: A total of 1157 patients were included, comprising 826 from the MIMIC-IV (v2.2) database, 225 from MIMIC-III (v1.4), and 106 from eICU (v2.0). Data from MIMIC-IV were split into training and internal validation sets (7:3), while MIMIC-III and eICU served as external validation cohorts. Thirty clinically relevant features were selected. Eight ML models were evaluated using AUROC, accuracy, precision, recall, F1-score, and specificity. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) enhanced interpretability. Results: XGBoost model achieved the best performance, with an AUROC of 0.8556 (95% CI: 0.807–0.898), accuracy of 0.7702, recall of 0.8469, and specificity of 0.7200. SHAP identified lactate, blood urea nitrogen, heart rate, hemoglobin, and diastolic blood pressure as key predictors, while LIME provided patient-level interpretability. Conclusions: The XGBoost-based model may facilitate early mortality risk stratification and support clinical decision-making for SALI patients in ICU settings. Full article

The Campos Rupestres, ancient and nutrient-poor mountaintop ecosystems in Brazil, harbor exceptional biodiversity and endemism but face severe threats from mining and urban expansion. Native grasses (Poaceae), represented by nearly 300 documented species—many of them poorly studied—are fundamental elements of these ecosystems. They provide critical ecological services, including soil stabilization, enhancing carbon storage and nutrient cycling, regulating water availability, and resilience to disturbances. This review synthesizes current knowledge on the diversity, functions, and propagation of Campos Rupestres grasses, with emphasis on their potential in ecological restoration. Despite their ecological importance, large-scale use of native grasses remains incipient, constrained by limited knowledge of reproductive biology, low seed viability, and scarce commercial seed availability. Advances in propagation include seedling and plug production, vegetative propagation, and rescue/reintroduction strategies, which have shown promising results in post-mining restoration. However, reliance on seed collection from natural populations risks depleting already limited genetic resources, highlighting the need for ex situ production systems. Expanding research on taxonomy, ecology, and cost-effective propagation methods, alongside supportive policy and market development, is crucial for integrating native grasses as cornerstone species in restoration programs. Bridging these gaps will enhance biodiversity conservation and restoration in one of the world’s most threatened megadiverse systems. Full article

Background/Objectives: Effective removal of organic tissue extruded beyond the apex is crucial in regenerative endodontics, particularly in teeth with immature apices; therefore, this study aims to compare the efficacy of standard needle irrigation (SNI), ultrasonic irrigation (UI), photon-induced photoacoustic streaming (PIPS), and shock wave-enhanced emission photoacoustic streaming (SWEEPS) techniques in dissolving periapical tissue in a simulated model. Methods: Sixty single-rooted human premolars and sixty bovine palatal mucosa specimens were used. A custom model was created by placing mucosal tissue in contact with the apical area. Specimens were divided into four groups (n = 15) according to the irrigation method: SNI, UI, PIPS, and SWEEPS. Each canal received 15 mL of 2% NaOCl. Tissue samples were weighed before and after treatment. One-way ANOVA and Tukey’s post hoc test were used for statistical analysis (p < 0.05). Results: UI showed significantly less tissue dissolution than the other methods (p < 0.05). SNI, PIPS, and SWEEPS showed no significant differences (p > 0.05). Conclusions: All methods led to tissue loss, but UI was significantly less effective. SNI, PIPS, and SWEEPS performed similarly. Full article

This study aimed to develop a non-invasive blood glucose estimation method by integrating wearable multimodal signals, including photoplethysmography (PPG), electrodermal activity (EDA), and skin temperature (ST), with food log–derived nutritional features, and to validate its clinical reliability. We analyzed data from 16 adults who underwent continuous glucose monitoring (CGM) while multimodal physiological signals were collected over 8–10 consecutive days, yielding more over 20,000 paired samples. Features from food logs and physiological signals were extracted, followed by feature selection using Boruta and minimum Redundancy Maximum Relevance (mRMR). Five machine learning models were trained and evaluated using five-fold cross-validation. Food log features alone demonstrated stronger predictive power than unimodal physiological signals. The fusion of nutritional, physiological, and temporal features achieved the best accuracy using LightGBM, reducing the RMSE to 12.9 mg/dL, with a MARD of 7.9%, a MAE of 8.82 mg/dL, and R² of 0.69. SHapley Additive exPlanations (SHAP) analysis revealed that 24-h carbohydrate and sugar intake, time since last meal, and short-term EDA features were the most influential predictors. By integrating multimodal wearable and dietary information, the proposed framework significantly enhances non-invasive glucose estimation. The interpretable LightGBM model demonstrates promising clinical utility for continuous monitoring and early dysglycemia management. Full article

Climate change is intensifying drought frequency and severity, posing increasing challenges for tropical forest species whose growth and survival depend on water availability. Ochroma pyramidale (Cav. ex Lam.) Urb. (balsa) is a fast-growing pioneer tree that plays important ecological roles, and it is valued for its lightweight timber, yet little is known about its drought tolerance or intraspecific variation among populations. This study evaluated the morphophysiological responses of O. pyramidale seedlings from three provenances spanning a rainfall gradient (850–6275 mm year⁻¹) under controlled soil moisture levels. The experiment followed a completely randomized factorial design with two factors, provenance (high-, medium-, and low-rainfall origins) and soil moisture (100%, 50%, and 20% field capacity), with six replications per treatment (n = 54 total plants). Drought significantly affected growth, water status, and physiological variables. Seedlings maintained high relative water content and photosynthetic pigment concentration under moderate stress (50% field capacity) but showed marked declines at 20% field capacity. Soluble sugar accumulation increased with drought intensity, suggesting osmotic adjustment, while root proliferation was enhanced under moderate stress (50% FC), evidenced by significantly higher Total Root Length (TRL) and Number of Branch Points (NBP). Provenance effects were weak, with only the number of leaves differing significantly among provenances. These results demonstrate that O. pyramidale tolerates moderate drought through physiological adjustment and root plasticity, supporting its use in reforestation and restoration initiatives in water-limited tropical environments. Full article

Root-promoting treatments and media are critical for the clonal propagation of Western pine species, yet long-term data for sugar pine (Pinus lambertiana Dougl.) and ponderosa pine (Pinus ponderosa Dougl. ex C. Lawson) remain limited. This multi-year greenhouse study (2024–2025) used a split-plot greenhouse design to evaluate interactions among four rooting media and various root-promoting treatments, including commercial mixed microbial/biostimulant products and indole-3-butyric acid (IBA). Coconut coir consistently outperformed other media, achieving rooting rates of up to 80% when combined with specific commercial products like Mykos, Dynomyco, or Wildroot. Seasonal timing also proved crucial; winter propagation (January 2025) yielded poor results (<30%) regardless of treatment, consistent with the influence of physiological dormancy. While commercial mixed microbial/biostimulant products were associated with improved rooting, their effectiveness depended on the use of an appropriate substrate. The superior performance of coconut coir is consistent with its physical characteristics (e.g., aeration, water retention), although these properties were not directly measured. Full article

The fermentation process of oolong tea is a critical step in shaping its quality and flavor profile. In this study, the fermentation degree of Anxi Tieguanyin oolong tea was assessed using image and hyperspectral features. Machine learning algorithms, including Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU), were employed to develop models based on both single-source features and multi-source fused features. First, color and texture features were extracted from RGB images and then processed through Pearson correlation-based feature selection and Principal Component Analysis (PCA) for dimensionality reduction. For the hyperspectral data, preprocessing was conducted using Normalization (Nor) and Standard Normal Variate (SNV), followed by feature selection and dimensionality reduction with Competitive Adaptive Reweighted Sampling (CARS), Successive Projections Algorithm (SPA), and PCA. We then performed mid-level fusion on the two feature sets and selected the most relevant features using L1 regularization for the final modeling stage. Finally, SHapley Additive exPlanations (SHAP) analysis was conducted on the optimal models to reveal key features from both hyperspectral bands and image data. The results indicated that models based on single features achieved test set accuracies of 68.06% to 87.50%, while models based on data fusion achieved 77.78% to 94.44%. Specifically, the Pearson+Nor-SPA+L1+SVM fusion model achieved the highest accuracy of 94.44%. This demonstrates that data feature fusion enables a more comprehensive characterization of the fermentation process, significantly improving model accuracy. SHAP analysis revealed that the hyperspectral bands at 967, 942, 814, 784, 781, 503, 413, and 416 nm, along with the image features H_σ and H, played the most crucial roles in distinguishing tea fermentation stages. These findings provide a scientific basis for assessing the fermentation degree of Tieguanyin oolong tea and support the development of intelligent detection systems. Full article

Aging-associated facial hyperpigmentation is driven not only by enhanced melanogenesis but also by dermal senescence and deterioration of the dermal–epidermal junction. The purpose of this study was to evaluate whether monopolar radiofrequency (MRF) monotherapy can improve aging-related facial hyperpigmentation by simultaneously suppressing melanogenic signaling and restoring senescence-associated dermal alterations. We assumed that deep dermal heating induced by MRF would modulate fibroblast senescence and basement membrane integrity, thereby indirectly regulating melanocyte activity. In a retrospective review of 26 Asian women, MRF treatment significantly decreased multiple pigmentation parameters, including melanin level, hyperconcentration, and Hemi Melasma Area and Severity Index (hemi-MASI) scores, while concurrently reducing wrinkles, pores, and enhanced overall skin texture without inducing inflammation. Complementary ex vivo experiments using ultraviolet B (UVB)-irradiated human skin demonstrated that MRF markedly reduced pro-melanogenic markers (α-MSH, MC1R, MITF, TYR, TRP1/2), restored collagen type IV expression at the basement membrane, decreased senescence-associated genes (p16, p21), and upregulated protective heat shock proteins (HSP70/47). Together, these findings suggest that MRF improves aging-associated hyperpigmentation by both suppressing melanogenesis and rejuvenating the senescent dermal microenvironment. MRF may serve as an effective non-invasive treatment option for pigmentation disorders in aging skin. Full article

Accurate biomass and carbon estimation in tropical plantation forests requires species-specific allometric models. Silver Oak (Grevillea robusta A. Cunn. ex R. Br.), cultivar “AVAONE,” is widely planted in northeastern Thailand, yet locally calibrated equations remain limited. This study developed species- and site-specific allometric models using destructive sampling of eight trees (n = 8) aged 2–9 years from a single plantation in Pak Chong District, Nakhon Ratchasima Province, without independent validation. Each tree was separated into stem, branches, leaves, and roots to determine fresh and dry biomass, and carbon concentrations were measured using a LECO CHN628 analyzer in an ISO/IEC 17025-accredited laboratory. Aboveground biomass increased from 17.49 kg at age 2 to 860.42 kg at age 9, with the most rapid gains occurring between ages 6 and 9. Tree height stabilized at approximately 19–20 m after age 7, while diameter continued to increase. Stems accounted for the largest proportion of dry biomass, followed by branches and roots. Carbon concentrations ranged from 45.561% to 48.704%, close to the IPCC default value of 47%. Power-law models based on D²H showed clear relationships with biomass, with R² values ranging from 0.7365 to 0.9372 for individual components and 0.8409 for aboveground biomass. These locally derived equations provide preliminary, site-specific relationships for estimating biomass and carbon stocks in Silver Oak AVAONE plantations and offer a baseline for future studies with expanded sampling and independent validation. Full article

This study focuses on the development of antibacterial polymer nanocomposites based on biologically synthesized silver nanoparticles (AgNPs) and polyvinyl alcohol (PVA) as the polymer matrix. Silver nanoparticles were produced using an aqueous extract from dried Lavandula angustifolia (lavender) leaves, which proved to be highly effective in reducing silver ions and stabilizing the resulting nanoparticles. The synthesized AgNPs were characterized by FTIR, UV-Vis, TEM, SEM, and DLS analyses. The nanoparticles were predominantly spherical, with more than 70% having diameters below 20 nm. Subsequently, AgNPs were incorporated into the PVA matrix via an ex situ approach to fabricate nanocomposite fibers and thin films. SEM analysis confirmed successful incorporation and uniform distribution of AgNPs within the polymer structures. The nanocomposites exhibited pronounced antibacterial activity against both Gram-positive (Staphylococcus aureus, Staphylococcus haemolyticus, Streptococcus uberis) and Gram-negative (Escherichia coli, Pseudomonas aeruginosa) bacteria, with nanofibers demonstrating superior performance compared to thin films. These findings highlight the potential of lavender-extract-mediated AgNPs as sustainable functional fillers for the fabrication of eco-friendly antibacterial materials applicable in biomedical and food packaging fields. Full article

Background: Approximately half of U.S. adults have ≥1 cardiovascular disease (CVD) risk factors. Exercise is universally recommended as a first-line lifestyle therapy to prevent and treat CVD. Objective: We will conduct a feasibility and pilot efficacy randomized controlled trial to test the usability and user satisfaction of an evidence-based digital health tool we developed for physicians—the Prioritizes Personalizes Prescribes EXercise algorithm (P3-EX)—to treat patients with CVD risk factors (ClinicalTrials.gov: NCT07238556). Methods: We will recruit 24 physicians who do not prescribe written exercise prescriptions (ExRx) from two local CT hospitals. Physicians will recruit two patients each (N = 48); both patients must have CVD risk factors. Each physician will deliver a P3-EX ExRx to one patient (n = 24) and the Physical Activity Vital Sign ExRx to the other patient (n = 24) in a random sequence crossover design. Physicians and patients will rate the feasibility and acceptability of each ExRx method using validated questionnaires. Patients will perform their ExRx for 12 weeks and complete an exercise diary to monitor exercise adherence with weekly virtual oversight by Research Assistants. Before and after the exercise intervention, we will measure patient CVD risk factors and physical activity levels via accelerometry. Results: This trial has received Institutional Review Board approval (E-HHC-2025-0198) and will begin in January 2026, with findings published in 2027. Conclusions: This protocol provides the scientific rationale and methodology to test P3-EX within a real-world clinical setting, to inform the feasibility of using P3-EX as a digital health support tool by physicians, and preliminary efficacy of P3-EX to improve patient cardiovascular health and physical activity levels. Full article