Search Results (1,306)

This study examines the contrast in the nonlinear dynamics of Thrinax radiata Lodd. ex Schult. & Schult. f. Seed germplasm explored by optical and electrical signals. By integrating chaotic attractors for the modulation of the optical and electrical measurements, the research ensures high sensitivity monitoring of seed germplasm dynamics. Reflectance measurements and electrical responses were analyzed across different laser pulse energies using Newton–Leipnik and Rössler chaotic attractors for signal characterization. The optical attractor captured laser-induced changes in reflectance, highlighting nonlinear thermal effects, while the electrical attractor, through a custom-designed circuit, revealed electromagnetic interactions within the seed. Results showed that increasing laser energy amplified voltage magnitudes in both systems, demonstrating their sensitivity to energy inputs and distinct energy-dependent chaotic patterns. Fractional calculus, specifically the Caputo fractional derivative, was applied for modeling temperature distribution within the seeds during irradiation. Simulations revealed heat transfer about 1 °C in central regions, closely correlating with observed changes in chaotic attractor morphology. This interdisciplinary approach emphasizes the unique strengths of each method: optical attractors effectively analyze photoinduced thermal effects, while electrical attractors offer complementary insights into bioelectrical properties. Together, these techniques provide a realistic framework for studying seed germplasm dynamics, advancing knowledge of their responses to external perturbations. The findings pave the way for future applications and highlight the potential of chaos theory for early detection of structural and bioelectrical changes induced by external energy inputs, thereby contributing to sample protection. Our results provide quantitative dynamical descriptors of laser-evoked seed responses that establish a tractable framework for future studies linking these metrics to physiological outcomes. Full article

Background/Objectives: Weight gain after kidney transplantation is frequent but heterogeneous, often accompanied by changes in body composition that influence long-term outcomes. This study analysed one-year changes in body compartments and their demographic and clinical determinants. Methods: A prospective cohort of 112 adult kidney recipients transplanted between September 2020 and June 2022 at a Spanish tertiary hospital was followed. Body weight, muscle mass, fat mass, visceral fat and total body water were assessed by multi-frequency bioelectrical impedance at discharge, and at 3, 6 and 12 months. Associations with sociodemographic, clinical and comorbidity variables were examined using repeated-measures ANOVA and comparative tests. Results: At 12 months, mean weight gain was 3.6 ± 6.5 kg (5.1%). Increases were greater in men, younger patients, non-dialysis candidates, those with previous transplantation and living donor grafts. Muscle mass rose during the first three months and then stabilised, with greater gains in men and haemodialysis patients. Fat mass decreased initially and then increased, particularly in women, younger recipients and living donor transplants. Visceral fat progressively increased after three months, with higher levels in men and older patients. Total body water declined in women, younger recipients and first transplant patients. Patients with new-onset diabetes gained less weight, while smokers gained more. Conclusions: Post-transplant body composition is shaped by sex, age, BMI, comorbidities and donor type. Monitoring compartments beyond body weight may allow early detection of adverse metabolic trajectories. Tailored nutritional and lifestyle interventions are needed to optimise long-term outcomes. Full article

Plant Microbial Fuel Cells (PMFCs) represent a promising technology that uses electroactive bacteria to convert the chemical energy in organic matter into electrical energy. The addition of carbon pellet on electrodes may increase the specific surface area for colonization via bacteria. Use of nutrients such as urea could enhance plant growth. Our study aims to address the following questions: (1) Does carbon pellet layering affect the electrical performance of PMFCs? (2) Does urea treatment of the plants used to feed the PMFCs affect the electrical performance? A new prototype of PMFC has been tested: the plant pot is on the top, drainage water percolates to the tub below, containing the Microbial Fuel Cells (MFCs). To evaluate the best layering setup, two groups of MFCs were constructed: a “Double layer” group (with carbon pellet both on the cathode and on the anode), and a “Single layer” group (with graphite only on the cathode). All MFCs were plant-fed by Spathiphyllum lanceifolium L leachate. After one year, each of the previous two sets has been divided into two subsets: one wetted with percolate from plants fertilized with urea, and the other with percolate from unfertilized plants. Open circuit voltage (mV), short circuit peak current, and short circuit current after 5 s (mA) produced values that were measured on a weekly basis. PMFCs characterized by a “Single layer” group performed better than the “Double layer” group most times, in terms of higher and steadier values for voltage and calculated power. Undesirable results regarding urea treatment suggest the use of less concentrated urea solution. The treatment may provide consistency but appears to limit voltage and peak values, particularly in the “Double layer” configuration. Full article

Background: Sarcopenia and low muscle mass are prevalent and prognostically relevant in patients with lung cancer, yet their diagnosis remains challenging in routine clinical practice. Opportunistic assessment using computed tomography (CT) has emerged as a valuable tool for body composition evaluation. We aimed to assess the utility of thoracic CT at T12 and T4 levels in identifying sarcopenia and low muscle mass and explore their correlation with morphofunctional tools such as bioelectrical impedance vector analysis (BIVA), nutritional ultrasound (NU), and functional performance tests. Methods: In this prospective observational study, 80 patients with lung cancer were evaluated at diagnosis. Body composition was assessed using BIVA-, NU-, and CT-derived parameters at T12 and T4 levels. Functional status was measured using the Timed Up and Go (TUG) and 30-Second Chair Stand Test. Sarcopenia was defined according to EWGSOP2 criteria. Results: Sarcopenia was identified in 20% of patients. CT-derived indices at T12CT demonstrated better diagnostic performance than T4CT. For detecting low muscle mass, the optimal SMI cut-off values were SMI_T12CT < 31.98 cm²/m² and SMI_T4CT < 59.05 cm²/m² in men and SMI_T12CT < 28.23 cm²/m² and SMI_T4CT < 41.69 cm²/m² in women. For sarcopenia diagnosis, the values were SMI_T12CT < 24.78 cm²/m² and SMI_T4CT < 57.23 cm²/m² in men and SMI_T12CT < 21.24 cm²/m² and SMI_T4CT < 49.35 cm²/m² in women. A combined model including SMI_T12CT, RF_CSA, and the 30 s squat test showed high diagnostic accuracy (AUC = 0.826). In multivariable analysis, lower SMA_T12CT was independently associated with risk of sarcopenia (OR = 0.96, 95% CI: 0.92–0.99, p = 0.022), as were older age (OR = 1.23, 95% CI: 1.07–1.47, p = 0.010) and fewer repetitions in the 30 s squat test (OR = 0.78, 95% CI: 0.63–0.91, p = 0.007). Conclusions: CT-derived body composition assessment, particularly at the T12 level, shows good correlation with morphofunctional tools and may offer a reliable and timely alternative for identifying sarcopenia and low muscle mass in patients with lung cancer. Full article

Cognition is often modeled in terms of abstract reasoning and neural computation, yet a growing body of theoretical and experimental work suggests that the roots of cognition lie in fundamental embodied regulatory processes. This article presents a theory of cognition grounded in sensing, feeling, and affect—capacities that precede neural systems and are observable in even the simplest living organisms. Based on the info-computational framework, this entry outlines how cognition and proto-subjectivity co-emerge in biological systems. Embodied appraisal—the system’s ability to evaluate internal and external conditions in terms of valence (positive/negative; good/bad)—and the capacity to regulate accordingly are described as mutually constitutive processes observable at the cellular level. This concept reframes cognition not as abstract symbolic reasoning but as value-sensitive, embodied information dynamics resulting from self-regulating engagement with the environment that spans scales from unicellular organisms to complex animals. In this context, information is physically instantiated, and computation is the dynamic, self-modifying process by which organisms regulate and organize themselves. Cognition thus emerges from the dynamic coupling of sensing, internal evaluation, and adaptive morphological (material shape-based) activity. Grounded in findings from developmental biology, bioelectric signaling, morphological computation, and basal cognition, this account situates intelligence as an affect-driven regulatory capacity intrinsic to biological life. While focused on biological systems, this framework also offers conceptual insights for developing more adaptive and embodied forms of artificial intelligence. Future experiments with minimal living systems or synthetic agents may help operationalize and test the proposed mechanisms of proto-subjectivity and affect regulation. Full article

Introduction: Unhealthy eating habits combined with low levels of physical activity and cardiorespiratory fitness pose a serious threat to the health of young people. The aim of this research was to determine the relationship between selected components of body composition, the occurrence of eating disorders, and cardiorespiratory fitness (CRF) and physical activity levels among university students. Material and Methods: This study was conducted among 254 students at a university in Poland. It included the measurements of body height, body composition analysis using bioelectrical impedance analysis (BIA), and assessment of cardiorespiratory fitness (CRF). This research also employed the My Eating Habits (MEH) questionnaire and the short version of the International Physical Activity Questionnaire (IPAQ-SF). Results: Based on body fat percentage (BF%), nearly one-fifth (19.69%) of participants were classified as obese. According to the body mass index (BMI), over one-third had excess body weight (overweight 24.02%, obesity 10.24%), while 6.7% were underweight. Eating disorders were significantly more prevalent in women (p = 0.0002). A significant relationship was observed between eating disorders and BMI, muscle mass (MM%), skeletal muscle mass (SMM%), body fat (BF%), and visceral fat (VFATL). Higher BMI, BF%, and VFATL were associated with a greater risk of developing eating disorders. Emotional overeating was significantly less common among individuals with normal body weight compared to those who were underweight or overweight. No statistically significant associations were found between students’ physical activity levels and eating habits. However, cardiorespiratory fitness (CRF) was significantly negatively correlated with the presence of eating disorders. Conclusions: Understanding the relationship between components of body composition, eating disorders, physical activity levels, and cardiorespiratory fitness is crucial for designing effective interventions that promote a healthier lifestyle and psychological well-being among university students. Full article

This study tested whether classic and specific bioelectrical impedance vector analysis (BIVA) parameters could explain metabolic and mechanical performance in endurance-trained trail runners. Fifteen males ($\dot{\mathrm{V}}$O₂max 61.04 ± 6.91 mL·kg⁻¹·min⁻¹) completed a 60-min treadmill protocol at 70% $\dot{\mathrm{V}}$O₂max across randomized slopes (−7% to +7%), with continuous gas-exchange, heart-rate, and running-power recording; whole-body BIVA was obtained immediately pre- and post-exercise. Post-test, impedance and resistance increased (+2.73%, +2.84%), while reactance (Xc) and phase angle decreased (−2.36%, −4.91%); all were significant and mirrored by both classic and specific indices, consistent with acute fluid loss and altered cellular status. After Benjamini–Hochberg adjustment, baseline Xc/height correlated inversely with $\dot{\mathrm{V}}$CO₂peak and $\dot{\mathrm{V}}$CO₂mean, whereas exercise-induced changes in ΔXc/height and ΔXcspecific correlated positively with both metabolic variables and mean power. Stepwise regression retained ΔXc/h or ΔXcspecific as the only BIVA predictors for $\dot{\mathrm{V}}$CO₂peak, $\dot{\mathrm{V}}$CO₂mean, and mean power output, explaining ~31–36% and ~22–23% of the variance, respectively; classic and specific approaches performed similarly. No bioelectrical variable predicted $\dot{\mathrm{V}}$O₂max. These preliminary findings suggest that acute reactance shifts may provide a modest yet sensitive, non-invasive index of exercise-induced physiological responses, warranting confirmation in larger and more diverse cohorts. Full article

Background/Objectives: National Football League (NFL) American football players are exposed to osteoarthritis risk factors of obesity and high joint loads. We sought to examine the association between total body mass (TBM), lean body mass (LBM), body fat percentage (BF%), and normalized compressive knee joint reaction forces (JRFcomp), peak knee adductor moments (KAM), and vertical ground reaction forces (vGRF) in NFL draft-eligible players during a high-speed run. Methods: A total of 125 participants ran a single trial at 5.5–6.5 m/s for 5 s on an instrumented treadmill. Bilateral vGRF and knee joint kinetics were calculated using inverse dynamics. Body composition was assessed using bioelectrical impedance. Results: LBM demonstrated significant moderate associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.60, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.20, p = 0.026; right, r(123) = −0.30, p < 0.001) and JRFcomp (left, r(123) = −0.39, p = 0.020; right, r(123) = −0.38, p = 0.015), respectively. TBM showed significant moderate negative associations with vGRF (left, r(123) = −0.56, p < 0.001; right, r(123) = −0.61, p < 0.001) and low-to-negligible associations with KAM (left, r(123) = −0.21, p = 0.021; right, r(123) = −0.28, p = 0.002) and JRFcomp (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.37, p < 0.001), respectively. BF% showed significant low-to-negligible negative associations with JRFcomp (left, r(123) = −0.21, p < 0.001; right, r(123) = −0.22, p < 0.001) and vGRF (left, r(123) = −0.39, p < 0.001; right, r(123) = −0.41, p < 0.001), respectively, and no significant associations with KAM, p > 0.05. The heavier group exhibited significantly lower normalized JRFcomp, and vGRF, p < 0.05. Conclusions: Heavier, but not fatter, players attenuate knee loads. Dampening may be a short-term protective strategy for joints of heavier players. Full article

(1) Background: Low back pain (LBP) is the most prevalent cause of disability worldwide, yet current assessment relies mainly on subjective questionnaires, underscoring the need for objective and interpretable biomarkers. Bioelectrical impedance parameter (BIP), quantified by resistance (R), impedance magnitude (Z), and phase angle (PA), reflects tissue hydration and cellular integrity and may provide physiological correlates of pain; (2) Methods: This cross-sectional study used lumbar BIP and demographic characteristics from 83 participants (38 with lumbar BIP and 45 normal controls). We applied Extreme Gradient Boosting (XGBoost), a regularized tree-based machine learning (ML) algorithm, with stratified five-fold cross-validation. Model interpretability was ensured using SHapley Additive exPlanations (SHAP), which provide global importance rankings and local feature attributions. Outcomes included classification of LBP versus healthy status and regression-based prediction of pain scales: the Visual Analog Scale (VAS), Oswestry Disability Index (ODI), and Roland–Morris Disability Questionnaire (RMDQ); (3) Results: The classifier achieved high discrimination (ROC–AUC = 0.996 ± 0.009, sensitivity = 0.950 ± 0.068, specificity = 0.977 ± 0.049). Pain prediction showed best performance for VAS (R² = 0.70 ± 0.14; mean absolute error = 1.23 ± 0.27), with weaker performance for ODI and RMDQ; (4) Conclusions: These findings suggest that explainable ML models applied to BIP could discriminate between LBP and healthy groups and could estimate pain intensity, providing an objective complement to subjective assessments. Full article

Background: Bioelectrical impedance analysis (BIA) is a widely used field technique for assessing body composition in football. However, its reliance on population-specific regression equations limits its accuracy. Objective: This scoping review aimed to map the scientific literature on BIA applications in professional and semi-professional football, highlighting uses, limitations, and research opportunities. Methods: A comprehensive search was conducted in the scientific databases PubMed, EMBASE, Web of Science, and SPORTDiscus. Identified studies involved the use of BIA in professional and semi-professional football players (≥16 years) in the context of routine training and competition. Results: From 14,624 records, 39 studies met the inclusion criteria and were included. Three main applications were identified: (1) quantitative body composition assessment, (2) qualitative/semi-quantitative analysis (e.g., bioelectrical impedance vector analysis (BIVA)), and (3) muscle health and injury monitoring. Seven specific research areas emerged, including hydration monitoring, cross-method validation of body composition analyses, development of predictive models, sport phenotype identification, tracking training adaptations, performance/load assessment via phase angle, and localized BIA for injury diagnosis and recovery. Conclusions: While quantitative BIA estimates may lack individual-level precision, raw parameter analyses may offer valuable insights into hydration, cellular integrity, and muscle injury status, yet further research is needed to fully realize these applications. Full article

Background: Right heart failure (RHF) in dogs is marked by pathological fluid redistribution and extracellular fluid (ECF) accumulation, which intensifies cardiac work-load and disrupts systemic homeostasis. This study aimed to validate the clinical utility of phase angle (PhA), a key biomarker derived from bioelectrical impedance analysis (BIA), as a non-invasive and real-time indicator of fluid distribution abnormalities in canine RHF. PhA reflects cellular integrity and fluid balance, making it a promising tool for detecting ECF accumulation, one of the hallmark features of RHF. Additionally, the study assessed the feasibility and clinical applicability of the InBody M20 device in veterinary cardiology, supporting its potential role in monitoring and managing fluid-related complications in dogs with RHF. Methods: A total of 110 canine patients presenting to the Tokyo University of Agriculture and Technology Veterinary Hospital were enrolled and categorized into three groups: right-sided heart failure (RHF), left-sided heart failure (LHF), and healthy controls. Phase angle (PhA) was measured using the InBody M20 device, and plasma osmolality (OSM) was also assessed. Additionally, the effects of body weight and age on PhA values were analyzed to account for potential confounding factors. Results: Dogs in the RHF group exhibited significantly lower phase angle (PhA) values and higher plasma osmolality (OSM) compared to those in the LHF and control groups. A strong positive correlation was observed between PhA and OSM (r = 0.9211, p < 0.0001). Additionally, PhA measured at 5 kHz demonstrated a significant negative correlation with body weight (r = –0.4536, p = 0.0007), while PhA at 50 kHz showed a significant negative correlation with age (r = –0.3219, p = 0.0176). Conclusions: PhA is a reliable and non-invasive biomarker for assessing extracellular fluid accumulation and diagnosing right heart failure in dogs. Its strong correlation with plasma osmolality, as well as its associations with body weight and age, highlights its clinical relevance for comprehensive fluid status evaluation. The findings support the feasibility and applicability of using the InBody M20 device in veterinary cardiology to monitor and manage fluid-related complications in canine patients. Full article

Sarcopenia, a progressive age-related loss of skeletal muscle mass, strength, and function, is a major contributor to disability, reduced quality of life, and mortality in older adults. While current diagnostic approaches, such as dual-energy X-ray absorptiometry (DXA), bioelectrical impedance analysis (BIA), magnetic resonance imaging (MRI), and computed tomography (CT), are widely used to assess muscle mass, they have limitations in detecting early qualitative changes in muscle architecture and composition. Shear Wave Elastography (SWE), an ultrasound-based technique that quantifies tissue stiffness, has emerged as a promising tool to evaluate both muscle quantity and quality in a non-invasive, portable, and reproducible manner. Studies suggest that SWE can detect alterations in muscle mechanical properties associated with sarcopenia, providing complementary information to traditional morphometric assessments. Preliminary evidence indicates its good reproducibility, feasibility in various clinical settings, and potential for integration into routine evaluations. This narrative review summarizes current evidence on the use of SWE for the assessment of sarcopenia across diverse populations. Full article

Electric fields (EFs) have emerged as effective, non-chemical tools for modulating microbial populations in complex matrices such as wastewater. This review consolidates current advances on EF-induced alterations in microbial structures and functions, focusing on both vegetative cells and spores. Key parameters affected include membrane thickness, transmembrane potential, electrical conductivity, and dielectric permittivity, with downstream impacts on ion homeostasis, metabolic activity, and viability. Such bioelectrical modifications underpin EF-based detection methods—particularly impedance spectroscopy and dielectrophoresis—which enable rapid, label-free, in situ microbial monitoring. Beyond detection, EFs can induce sublethal or lethal effects, enabling selective inactivation without chemical input. This review addresses the influence of field type (DC, AC, pulsed), intensity, and exposure duration, alongside limitations such as species-specific variability, heterogeneous environmental conditions, and challenges in achieving uniform field distribution. Emerging research highlights the integration of EF-based platforms with biosensors, machine learning, and real-time analytics for enhanced environmental surveillance. By linking microbiological mechanisms with engineering solutions, EF technologies present significant potential for sustainable water quality management. Their multidisciplinary applicability positions them as promising components of next-generation wastewater monitoring and treatment systems, supporting global efforts toward efficient, adaptive, and environmentally benign microbial control strategies. Full article

Objectives: This study examined whether skeletal muscle mass mediates the relationship between sedentary behavior, physical activity, and cardiometabolic health, and if this relationship differs by genders. Methods: Secondary analysis was conducted using data from the 2022–2023 Korean National Health and Nutrition Examination Survey (n = 5956). Cardiometabolic abnormalities were defined as having one or more of the five metabolic syndrome (MS) criteria, while MS was defined as having three or more. Muscle mass relative to body weight was measured by bioelectrical impedance analysis. Sedentary time and recommended moderate-to-vigorous physical activity (MVPA) levels at work, for transportation, and for recreation (≥600 Mets), and strength training (≥2 times/week), were assessed using the Global Physical Activity Questionnaire. Results: Higher MVPA (p < 0.001) and less sedentary time (p < 0.01) were significantly correlated with greater muscle mass in middle-aged and elderly men and women. Mediation analyses, which controlled for MS risk factors, revealed gender differences. In men, the indirect effects of sedentary time, MVPA, and strength training on both cardiometabolic abnormalities (b = 0.007, CI [0.003, 0.013]; b = −0.066, CI [−0.110, −0.033]; b = −0.074, CI [−0.110, −0.033]) and MS (b = 0.007, CI [0.003, 0.011]; b = −0.060, CI [−0.095, −0.032]; b = −0.065, CI [−0.100, −0.035]) were significant, indicating mediation by muscle mass. In women, the indirect effects of these three behaviors on cardiometabolic abnormalities were also mediated by muscle mass (b = 0.003, CI [0.001, 0.006]; b = −0.014, CI [−0.031, −0.002]; b = −0.023, CI [−0.050, −0.003]). However, for MS, sedentary time (b = 0.057, p < 0.001) and MVPA (b = −0.222, p < 0.05) had only direct effects, with no mediation by muscle mass. Furthermore, strength training showed no significant effects. Conclusions: These findings suggest that promoting MVPA and strength training, while reducing sedentary time, can improve cardiometabolic health by increasing muscle mass, though the mediating role of muscle mass for MS differs by gender. Full article

Background/Objectives: Fetuin-A is a multifunctional glycoprotein involved in metabolic and inflammatory regulation. Although its role in insulin resistance, type 2 diabetes, and cardiovascular disease is well recognized, its relationship with pregnancy-related body mass changes remains unclear. This study aimed to explore associations between maternal BMI dynamics during and shortly after pregnancy and serum fetuin-A concentrations. Methods: Fifty-five healthy Caucasian women with term singleton pregnancies were enrolled. BMI was recorded at three time points: pre-pregnancy, before delivery, and 48 h postpartum. Based on ΔBMI (postpartum minus pre-pregnancy BMI), participants were divided into two groups: ΔBMI ≤ 1 kg/m² (n = 32) and ΔBMI > 1 kg/m² (n = 23). Serum fetuin-A levels were measured before delivery and postpartum using ELISA. Additional laboratory parameters and body composition were assessed postpartum via standard tests and bioelectrical impedance analysis (BIA). Results: No significant differences were found between groups in BMI at any single time point or in laboratory or BIA-derived parameters. However, all three BMI change indices (ΔBMI_gestational, ΔBMI_puerperal, and ΔBMI) differed significantly between groups. Fetuin-A concentrations did not differ significantly between groups. Importantly, fetuin-A levels decreased significantly after delivery in both groups, suggesting a potential role of the placenta in its regulation. A significant correlation was observed between pre-delivery fetuin-A and postpartum uric acid in Group ΔBMI > 1 kg/m² (p = 0.016), indicating a possible link in women with greater gestational weight gain. Conclusions: While fetuin-A was not directly associated with BMI changes, its peripartum dynamics and correlation with uric acid may reflect underlying metabolic-inflammation pathways. ΔBMI indices may offer a more individualized measure of weight dynamics in pregnancy research. Full article