Search Results (3,569)

This study considers citrus rootstocks as autonomous biological entities and examines whether, and to what extent, they differently regulate plant–water relations and biomass allocation as well as how such physiological variations translate into differences in vegetative vigor. To address these questions, four citrus genotypes—Sour Orange (SO), Volkamer Lemon (VL), Swingle Citrumelo (CTR), and Troyer Citrange (TC)—were compared with respect to their morphological traits, biomass distribution, and hydraulic properties. These four rootstocks were selected as they represent contrasting genetic backgrounds and well-documented differences in vigor, stress tolerance, and hydraulic behavior, providing an effective model for assessing intrinsic physiological variability. The findings reveal pronounced rootstock-specific differences in water acquisition, transport, and utilization, with direct implications for the hydraulic architecture, leaf water status, and partitioning of biomass between above- and belowground organs. CTR exhibited a highly integrated hydraulic strategy, characterized by elevated conductance across both aerial and root systems and accompanied by greater biomass allocation to the canopy and absorptive roots, resulting in an enhanced overall vigor. SO and VL displayed an intermediate physiological performance, whereas TC demonstrated a restricted hydraulic transport capacity, which is associated with lower biomass allocation, reduced leaf water potential, and diminished vigor. By assessing rootstocks independently of scion influences, this work demonstrates that variations between citrus rootstocks cannot be explained solely by morphological traits but instead reflect contrasting physiological strategies governing the coordinated management of water and carbon resources. These results highlight the rootstock as a central determinant of hydraulic functioning, biomass partitioning, and plant vigor and provide a conceptual basis for selecting rootstocks that are better suited to water-limited environments. Full article

Regenerative medicine is increasingly leveraging the synergies between bioinspired conductive biomaterials and 3D/4D bioprinting to replicate the native electroactive and hierarchical microenvironments essential for functional tissue restoration. However, a critical gap remains in the intelligent integration of these technologies to achieve dynamic, responsive tissue regeneration. This review introduces a “bioinspired material–printing–function” triad framework to systematically synthesize recent advances in: (1) tunable conductive materials (polymers, carbon-based systems, metals, MXenes) designed to mimic the electrophysiological properties of native tissues; (2) advanced 3D/4D printing technologies (vat photopolymerization, extrusion, inkjet, and emerging modalities) enabling the fabrication of biomimetic architectures; and (3) functional applications in neural, cardiac, and musculoskeletal tissue engineering. We highlight how bioinspired conductive scaffolds enhance electrophysiological behaviors—emulating natural processes such as promoting axon regeneration cardiomyocyte synchronization, and osteogenic mineralization. Crucially, we identify multi-material 4D bioprinting as a transformative bioinspired approach to overcome conductivity–degradation trade-offs and enable shape-adaptive, smart scaffolds that dynamically respond to physiological cues, mirroring the adaptive nature of living tissues. This work provides the first roadmap toward intelligent electroactive regeneration, shifting the paradigm from static implants to dynamic, biomimetic bioelectronic microenvironments. Future translation will require leveraging AI-driven bioinspired design and organ-on-a-chip validation to address challenges in vascularization, biosafety, and clinical scalability. Full article

Biofilms formed by Staphylococcus aureus on medical devices and tissue surfaces are a major contributor to persistent infections due to their resistance to antibiotics. Hydrodynamic forces in physiological and device-associated environments significantly influence biofilm development, yet the dynamics of detachment and regrowth under flow remain poorly quantified. In this study, biofilm surface coverage was measured in microfluidic flow assays across combinations of shear rates and nutrient concentrations. A computational workflow was used to segment biofilm trajectories into three kinetic phases—growth, exodus, and regrowth—based on surface coverage dynamics. Each phase was modeled using parametric functions, and fitted parameters were interpolated across experimental conditions to reconstruct biofilm lifecycles throughout the flow–nutrient conditions. The analysis revealed that intermediate shear rates triggered early detachment events while suppressing subsequent regrowth, whereas lower and higher shear regimes favored biofilm persistence. The resulting model enables quantitative comparison of condition-specific biofilm behaviors and identifies key thresholds in mechanical and nutritional inputs that modulate biofilm stability. These findings establish a phase-resolved framework for studying S. aureus biofilms under hydrodynamic stress and support future development of targeted strategies to control biofilm progression in clinical and engineered systems. Full article

Chemical contaminants are increasingly detected in freshwater environments, yet the physiological and molecular responses of many non-model freshwater invertebrates to acute chemical stress remain poorly understood. In this study, we investigated the physiological and transcriptomic responses of the freshwater hydrozoan Craspedacusta sowerbii to two widespread aquatic pollutants: the antibiotic sulfamethoxazole (20 μM) and the heavy metal salt CdSO₄ (10 μM). Morphological and behavioral observations showed that sulfamethoxazole exposure led to reduced motility and body shrinkage, whereas cadmium exposure caused rapid loss of movement and complete mortality within 24 h. RNA sequencing revealed distinct transcriptional response patterns to the two stressors. Sulfamethoxazole exposure primarily induced the up-regulation of genes associated with oxidative stress, apoptosis, immune responses, and signaling pathways, suggesting an active but limited stress-adaptation response. In contrast, cadmium exposure resulted in extensive down-regulation of genes involved in metabolic pathways, cell cycle regulation, fatty acid metabolism, and anti-aging processes, suggesting severe disruption of core metabolic processes. Comparative pathway analyses identified both shared stress-related responses and pollutant-specific transcriptional signatures, with cadmium exerting markedly stronger inhibitory effects at both physiological and molecular levels. These results reveal clear thresholds of stress tolerance and response failure in C. sowerbii under chemical pollution, and highlight its ecological sensitivity to water quality deterioration. Together, these findings provide mechanistic insight into acute pollutant-induced stress responses in a freshwater Cnidarian and offer a useful reference for understanding how freshwater invertebrates respond to short-term chemical disturbances. Full article

This study investigated whether Whole blood viscosity (WBV) varies with age in clinically healthy Beagle dogs and Korean Shorthair cats and examined the hematologic and biochemical variables associated with WBV. WBV was measured across multiple shear rates using a scanning capillary viscometry; complete blood count (CBC) and serum chemistry profiles were also evaluated. Both species demonstrated characteristic shear-thinning behavior. WBV showed a strong association with red blood cell count (RBC), hematocrit (HCT), and hemoglobin (Hb) in both species, with additional association with serum proteins and cholesterol in dogs. No significant relationship between WBV and age was identified at any shear rate, and principal component analysis (PCA) revealed no age-related clustering in the viscosity profiles. These findings indicated that WBV does not exhibit meaningful age-dependent trends in healthy companion animals. This suggests that, in a clinical setting, deviations in normal WBV are more likely to influence underlying physiological or pathological factors than normal aging. Full article

Laboratory mice are the most widely used model organisms in biomedical and behavioral research, yet growing concerns regarding reproducibility and translational validity have highlighted the substantial influence of housing and husbandry conditions on experimental outcomes. Although domestication is often assumed to have rendered laboratory mice fully adapted to artificial environments, evidence from ethology indicates that many core behavioral and physiological needs remain conserved. As a result, standard laboratory housing may generate chronic stress, alter behavior, and introduce systematic bias into experimental data. This narrative review critically examines how ethological constraints persisting after domestication interact with key environmental factors, social housing, environmental enrichment, ambient temperature, and lighting regimes to shape welfare and experimental validity in laboratory mice. Rather than providing an exhaustive overview of mouse behavior, the review adopts a problem-oriented and solution-focused approach, highlighting specific welfare-related mechanisms that can distort behavioral and physiological readouts. Particular attention is given to social isolation and aggression in male mice, the role of nesting material in mitigating thermal stress, and the effects of circadian disruption under standard and reversed light–dark cycles. By integrating ethological theory with laboratory animal welfare research, this review argues that housing conditions should be regarded as integral components of experimental design rather than secondary technical variables. Addressing welfare-related bias through evidence-based refinement strategies is essential for improving reproducibility, enhancing data interpretability, and strengthening the scientific validity of mouse-based research. Full article

Non-alcoholic fatty liver disease (NAFLD) is closely linked to metabolic syndrome and circadian rhythm disruption, yet the mechanisms by which lifestyle interventions restore circadian organization remain incompletely understood. In this study, we employed a stringent 3 h time-restricted feeding (TRF) regimen in a mouse model of high-fat diet (HFD)-induced metabolic dysfunction. TRF markedly improved metabolic outcomes, including lipid accumulation, glucose tolerance, and behavioral and physiological rhythms. Importantly, through transcriptomic profiling using RNA sequencing, we found that TRF induced circadian rhythmicity in previously arrhythmic hepatic genes. This approach revealed that TRF promotes transcriptional synchronization within key metabolic pathways. Genes involved in autophagy, fatty acid metabolism, and protein catabolism exhibited coherent peak expression at defined time windows, suggesting that TRF temporally restructures gene networks to enhance metabolic efficiency. This intra-pathway synchronization likely minimizes energy waste and enables cells to execute specialized functions in a temporally optimized manner. Together, our findings identify temporal reorganization of metabolic pathways as a mechanistic basis for the benefits of TRF, providing new insight into circadian-based strategies for managing metabolic disease. Full article

Wearable sensors generate continuous physiological and behavioral data at a population scale, yet wellness prediction remains limited by noisy measurements, irregular sampling, and subjective outcomes. We introduce HybridSense, a unified framework that integrates raw wearable signals and their statistical descriptors with large language model–based reasoning to produce accurate and interpretable estimates of stress, fatigue, readiness, and sleep quality. Using the PMData dataset, minute-level heart rate and activity logs are transformed into daily statistical features, whose relevance is ranked using a Random Forest model. These features, together with short waveform segments, are embedded into structured prompts and evaluated across seven prompting strategies using three large language model families: OpenAI 4o-mini, Gemini 2.0 Flash, and DeepSeek Chat. Bootstrap analyses demonstrate robust, task-dependent performance. Zero-shot prompting performs best for fatigue and stress, while few-shot prompting improves sleep-quality estimation. HybridSense further enhances readiness prediction by combining high-level descriptors with waveform context, and self-consistency and tree-of-thought prompting stabilize predictions for highly variable targets. All evaluated models exhibit low inference cost and practical latency. These results suggest that prompt-driven large language model reasoning, when paired with interpretable signal features, offers a scalable and transparent approach to wellness prediction from consumer wearable data. Full article

Background: Prolonged sitting has been associated with adverse cardiovascular and neuromuscular responses; however, the temporal onset of these acute physiological changes remains unclear. This study aimed to determine the acute effects of prolonged sitting on blood flow, blood pressure, and muscle activity. Methods: A non-controlled clinical trial was conducted with 21 healthy adults (22.5 ± 1.60 years), both male and female. Participants remained seated continuously for three hours, with data collected every 20 min, including infrared thermography, blood pressure, and electromyographic activity. Skin temperature was measured using infrared thermography on the calf region of both legs, and the mean temperature was analyzed. Systolic and diastolic blood pressure were measured using an oscillometric device, and mean arterial pressure was subsequently calculated. Muscle activity was assessed through surface electromyography, using median frequency and root mean square values. Statistical analysis was performed using the Friedman test and the Durbin–Conover post hoc test, along with a subjective trend analysis of each variable over time. Results: A significant reduction was observed in both calf skin temperature and median frequency after 60 min of uninterrupted sitting (p < 0.05). Mean and systolic blood pressure exhibited an increasing trend after 160 min (p < 0.05). Conclusions: The exposure–response data from this study may contribute to the planning of future interventions aimed at refining recommendations for breaking up prolonged sitting periods. Full article

In the realm of wearable technology, achieving robust continuous authentication requires balancing high security with the strict resource constraints of embedded platforms. Conventional machine learning approaches and deep learning-based biometrics often incur high computational costs, making them unsuitable for low-power edge devices. To address this challenge, we propose H-PPG, a lightweight authentication system that integrates photoplethysmography (PPG) and inertial measurement unit (IMU) signals for continuous user verification. Using Hyperdimensional Computing (HDC), a lightweight classification framework inspired by brain-like computing, H-PPG encodes user physiological and motion data into high-dimensional hypervectors that comprehensively represent individual identity, enabling robust, efficient and lightweight authentication. An adaptive learning process is employed to iteratively refine the user’s hypervector, allowing it to progressively capture discriminative information from physiological and behavioral samples. To further enhance identity representation, a dimension regeneration mechanism is introduced to maximize the information capacity of each dimension within the hypervector, ensuring that authentication accuracy is maintained under lightweight conditions. In addition, a user-defined security level scheme and an adaptive update strategy are proposed to ensure sustained authentication performance over prolonged usage. A wrist-worn prototype was developed to evaluate the effectiveness of the proposed approach and extensive experiments involving 15 participants were conducted under real-world conditions. The experimental results demonstrate that H-PPG achieves an average authentication accuracy of 93.5%. Compared to existing methods, H-PPG offers a lightweight and hardware-efficient solution suitable for resource-constrained wearable devices, highlighting its strong potential for integration into future smart wearable ecosystems. Full article

Pure titanium (Ti) and its alloys are the gold standard for dental implants because a stable titanium dioxide passive film provides excellent corrosion resistance in physiological environments. In this study, we aimed to examine electrochemical interactions between Ti and cobalt–chromium–molybdenum alloy (CoCrMo), and between a novel Ti–magnesium composite (BIACOM TiMg) and CoCrMo, when immersed in everyday solutions representing beverage or oral hygiene exposure. Test solutions included Coca-Cola^®, lemon juice, Elmex^® fluoride gel, Listerine^® Cool Mint, and Sensodyne^® fluoride paste. Immersion experiments paired Ti sticks with CoCrMo sticks and, separately, BIACOM TiMg with CoCrMo sticks, with three measurements per configuration. When galvanically coupled with CoCrMo, immersion in Coca-Cola produced galvanic potential differences of ~983 mV for the BIACOM TiMg-CoCrMo couple and 830 mV for the commercially pure grade 4 (CP4) Ti-CoCrMo couple, indicating significant electrochemical instability. Both materials showed significant potential increases in Elmex fluoride gel. Listerine Cool Mint and Sensodyne fluoride exposure produced electrochemical interactions exceeding 200 mV. Significant differences in corrosion stability were observed between CP4 Ti and BIACOM TiMg. These findings indicate that material pairing and electrolyte environment significantly influence galvanic behavior, with the Ti-Mg composite showing greater susceptibility than CP4 Ti, informing dental/biomedical material selection in oral environments. Full article

This study evaluates the feasibility of establishing a new strawberry cultivation zone in the Region of Florina, Northern Greece, as a strategy to support rural revitalization and agricultural diversification. Day-neutral strawberry genotypes were cultivated under net-house conditions at the University of Western Macedonia and assessed for physiological traits (SPAD index, chlorophyll fluorescence) and fruit quality (weight, color, firmness, °Brix, titratable acidity); while postharvest behavior was evaluated after seven days of cold storage. Statistical analysis identified genotypes with superior physiological performance and storability. Preliminary economic analysis suggests that their adoption could increase growers’ income by 20–30% compared to conventional varieties. The findings support the development of a strawberry production zone in Florina, with broader implications for sustainable agricultural intensification and rural development in underutilized European regions. Full article

Cryotherapy and radiofrequency (RF) treatments modulate tissue temperature to induce therapeutic effects; however, improper application can result in thermal injury. Traditional temperature-based monitoring methods rely on multiple thermal sensors whose accuracy strongly depends on their number and spatial positioning, often failing to detect early tissue crystallization. This study introduces a fractional order bioimpedance modelling framework for the early detection of tissue freezing during cryogenic and thermal medical treatments, with the feasibility and effectiveness of this approach having been reported in our prior publications. While bioimpedance spectroscopy itself is a well-est. The corresponablished technique in biomedical engineering, its novel application to predict and identify premature freezing events provides a new pathway for safe and efficient energy-based therapies. Fractional-order models derived from the Cole family accurately reproduce the complex electrical behavior of biological tissues using fewer parameters than classical integer-order models, thus reducing both hardware requirements and computational cost. Experimental impedance data from human abdominal, gluteal, and femoral regions were modelled to extract fractional parameters that serve as sensitive indicators of phase-transition onset. The results demonstrate that the proposed approach enables real-time identification of freezing-induced electrical transitions, offering a physiologically grounded alternative to conventional temperature-based monitoring. Furthermore, the fractional order bioimpedance method exhibits high reproducibility and selectivity, and its analytical figures of merit, including the limits of detection and quantification, support its use for reliable real-time tissue monitoring and early injury detection. Overall, the proposed fractional order bioimpedance framework enhances both safety and control precision in cryogenic and thermal medical applications. Full article

Seismic surveys introduce high levels of noise into the soundscape. Thus, a major concern is the effect of these noise levels on animal communication, especially for species with high hearing acuity, such as cetaceans. We evaluated the effects of airgun pulses of seismic surveys on the acoustic behavior of humpback whales (Megaptera novaeangliae) and pantropical spotted dolphins (Stenella attenuata) in the two most important basins for oil and gas off Brazil. We detect the presence of airgun pulses and measure sound pressure levels (SPL) to evaluate whether SPL changed the acoustic parameters of cetacean vocalizations. Airgun pulses increased the SPL by 17%. This changes acoustic parameters differently: whales reduced call frequency and duration, while dolphins increased these parameters. In both cases, responses may be related to physiological limitations in sound modulation of each species. This was the first report on the impacts of seismic surveys on cetaceans’ communications in Brazil and the first for the pantropical spotted dolphin on this topic in the world. Impacts vary with the frequency and duration of emissions, indicating species-specific acoustic responses that depend on airgun noise characteristics. Whales cannot make efficient adjustments at higher or lower frequencies, and dolphins cannot adjust at lower frequencies. These results are important for discussing the effects of airgun noise on cetacean communication. Full article

Background/Objectives: Emotional eating refers to the tendency to eat in response to emotions rather than physiological hunger and has been associated with changes in food choices and difficulties in dietary self-regulation. Whether emotional eating influences adherence to the Mediterranean diet remains unclear. This study aimed to examine the association between emotional eating and adherence to the Mediterranean diet. Methods: In this cross-sectional study, 245 adults completed the Emotional Eater Questionnaire (EEQ) and the MEDI-LITE questionnaire to assess adherence to the Mediterranean diet. Participants were classified into three emotional eating categories (NO EE, LEE, EE) and stratified by BMI (normal weight vs. overweight). Results: Higher EEQ scores were associated with greater disinhibition, stronger food preferences, and a higher sense of guilt in both BMI categories. However, adherence to the Mediterranean diet did not differ significantly across emotional eating groups, and overall MEDI-LITE scores were low in the entire sample. Correlations between emotional eating subscales and specific food groups were weak and did not show a consistent pattern. Conclusions: Emotional eating was associated with psychological and behavioral aspects of eating but was not related to adherence to the Mediterranean diet in this population. The uniformly low adherence to the Mediterranean diet may have attenuated potential associations. Further studies using more detailed dietary assessment tools and longitudinal designs are needed to clarify how emotional eating influences food choices over time. Full article