Search Results (227)

Background: Nutritional status and lifestyle factors are increasingly recognized as relevant modulators of women’s reproductive health. However, data remain limited on the relationship between body composition, dietary habits, and menstrual cycle characteristics in apparently healthy young women. This study aimed to assess nutritional status, body composition, and lifestyle behaviors in young women and to explore their associations with menstrual cycle regularity. Methods: This cross-sectional study included 49 apparently healthy women aged 19–30 years. Anthropometric measurements and body composition were assessed using bioelectrical impedance analysis. Dietary habits were evaluated through a simplified food frequency questionnaire, and adherence to the Mediterranean diet was assessed using the PREDIMED score. Physical activity was estimated using MET values based on the Compendium of Physical Activities. Menstrual cycle characteristics were collected via questionnaire. Group comparisons were performed between women with regular and irregular menstrual cycles. Results: The sample was predominantly normal-weight (mean BMI 22.36 ± 4.26 kg/m²). Anthropometric and bioelectrical impedance parameters did not differ significantly between women with regular and irregular cycles. Women with irregular cycles showed higher resistance and extracellular water and lower phase angle and body cell mass, although differences were not statistically significant. A significant association was found for meat consumption, which was lower in women with irregular cycles (p = 0.007). No associations were observed for other dietary variables, physical activity, or meal frequency. Conclusions: Menstrual regularity in young women was not associated with major anthropometric differences but may be linked to subtle aspects of nutritional status and dietary habits. Lower meat consumption emerged as a potential dietary factor associated with menstrual irregularity. Although associations were modest, these findings support the relevance of nutritional and lifestyle factors in menstrual health. Larger longitudinal studies are needed to clarify these relationships. Full article

Flexible conductive hydrogels hold great promise in wearable electronics and biomonitoring applications, yet their practical use is constrained by issues such as poor low-temperature tolerance, susceptibility to dehydration, and limited multifunctional sensing capabilities. This study successfully synthesized a dual-conductive lithium-ion and calcium-ion hydrogel based on acrylamide/gelatin via a simplified low-temperature one-pot polymerization method. At 60 °C, mixing acrylamide, gelatin, lithium chloride, and calcium chloride within 40 min constructed a network structure featuring covalent bonds, ionic bonds, and hydrogen bonds. The resulting material exhibited exceptional extensibility with a break elongation of 1408.5% and tensile strength of 134.2 kPa while maintaining strong adhesion to nine different substrates. It retained flexibility at −20 °C and demonstrated minimal mass loss (3% of initial value) after 10 days of aging. As a sensor, this hydrogel reliably responds to pressure, temperature, large-amplitude body movements, and subtle physiological signals like pulse and vocal cord vibrations. In animal simulation monitoring, its electrical resistance signals increased linearly with model body weight and remained stable between −20 °C and 20 °C. These results demonstrate the hydrogel’s broad application potential in wearable sensing, ecological monitoring, and smart agriculture. Full article

Background: Gait with external load is an inherent element of military tasks, and the mass of equipment carried by soldiers has systematically increased over recent decades. Depending on the nature of the operation, soldiers may carry loads ranging from several to several dozen kilograms, which may affect gait biomechanics and increase the risk of overload injuries. The aim of this study was to evaluate changes in the spatiotemporal gait parameters of Special Forces Operators depending on the mass and type of the carried external load. Methods: The study included 34 active Special Forces Operators (age: 36.47 ± 5.63 years; height: 180.39 ± 5.72 cm; body mass: 85.92 ± 8.54 kg). Gait analysis was performed using an h/p/cosmos gaitway 3D + 1D treadmill equipped with an integrated pressure platform enabling ground reaction force (GRF) measurement. Participants performed gait trials at a speed of 5.5 km/h under four load conditions: 0 kg, 7 kg, 20 kg, and 27 kg. For each condition, 30 s measurement series were recorded, enabling analysis of a stable locomotion pattern and detection of gait phase events. Results: Statistically significant differences were demonstrated for the following parameters: stance phase, load response, single support, pre-swing, swing phase, double stance, foot rotation, step time, stride length, step width, cycle time, and cadence. The greatest changes were observed between unloaded gait and the condition with a helmet and vest. External load mainly caused prolongation of phases related to support and shortening of the swing phase and single support. Conclusions: Military load significantly modifies the temporal structure of gait in Special Forces Operators even at a constant, relatively low speed. The use of an instrumented treadmill with an integrated pressure platform and GRF measurement, as well as the registration of a large number of gait cycles, enabled the detection of subtle differences in spatiotemporal parameters and reliable assessment of stability and dynamic asymmetry under controlled laboratory conditions. Full article

Hollow hydrogels are promising for flexible electronics and bioengineering, yet their fabrication is limited by sacrificial templates, specialized equipment, and complex engineering processes. Herein, a facile wet-spinning strategy is developed to fabricate sodium alginate (SA) hollow hydrogels. Extruding SA/CaCO₃ precursor suspension into an acidic coagulation bath induces simultaneous ionic cross-linking and in situ CO₂ generation, driving the self-formation of hollow tubular architectures with tunable morphologies, mechanical performance, macroscopic architecture, and functional properties. Moreover, the introduction of secondary cross-linking enhances the SA hydrogels’ water retention and resistance to freezing conditions. Utilizing their intrinsic ionic conductivity, the hollow hydrogels demonstrate outstanding sensing performance, enabling reliable detection of both large-amplitude limb motions and subtle muscle activity in the human body. Furthermore, hollow hydrogel tubes with diverse geometries can be readily fabricated by simply modifying the spinning mold, thereby broadening their potential applications. In vitro cytotoxicity assessments further confirm that the SA hollow hydrogels exhibit excellent biocompatibility with minimal cytotoxicity, satisfying the fundamental criteria for bioengineering applications. The combination of a simple yet controllable fabrication strategy with the intrinsic multifunctionality of the SA hollow tubes confers substantial potential for their deployment in bioengineering and flexible electronic applications. Full article

In the era of Industry 4.0, artificial intelligence technology is experiencing rapid development, and the integration of artificial intelligence (AI) with flexible sensors has emerged as a transformative approach for human motion and posture sensing. This paper explores the advancements in AI-enhanced flexible sensors, focusing on the application of flexible sensors on various parts of the human body. Flexible sensors, due to their conformability and sensitivity, are ideal for capturing the dynamic and subtle movements of the human body. AI algorithms, particularly machine learning and deep learning techniques are employed to process the complex data streams from these sensors, enabling the accurate recognition and prediction of various human postures and motions. The combination of these technologies overcomes the limitations of traditional sensing systems, offering higher precision, adaptability, and real-time feedback. It can be applied to healthcare for rehabilitation monitoring, sports for performance enhancement, and human–computer interaction for intuitive control. This review also discusses the challenges such as sensor reliability, data privacy, and power management. The future outlook emphasizes more sophisticated AI models and deeper technology integration, promising a seamless integration into everyday life for enhanced human–machine interaction and health monitoring. Full article

Background: The Index of Cardiac Electrophysiological Balance (ICEB) has emerged as a electrocardiographic marker reflecting the equilibrium between ventricular depolarization and repolarization. Although obesity is known to alter cardiac electrophysiology, the combined influence of body mass index (BMI) and objective nutritional status on ICEB and its heart rate-corrected form (ICEBc) remains insufficiently defined. This study aimed to investigate the associations between BMI categories, nutritional status, and cardiac electrophysiological balance. Methods: This cross-sectional study included 591 adult patients classified as normal-weight, overweight, or obese according to BMI. Electrophysiological assessment of ICEB (QT/QRS) and ICEBc (QTc/QRS) values was calculated from standard 12-lead electrocardiogram recordings. Participants’ nutritional status was analyzed using validated clinical indices such as the Prognostic Nutritional Index (PNI), Controlling Nutritional Status (CONUT), Geriatric Nutritional Risk Index (GNRI) and Hemoglobin–Albumin–Lymphocyte–Platelet (HALP) score. Results: According to the results, both ICEB and ICEBc showed significant differences among BMI categories (p < 0.001). ICEB/ICEBc exhibited a non-linear distribution. The ICEB/ICEBc values were found to be minimum in the normal weight group at 4.22 ± 0.54/4.87 ± 0.66 and maximum in the obese group at 4.27 ± 0.51/4.99 ± 0.59. The ICEB/ICEBc value closest to the optimal physiological limits was found in the overweight group at 4.04 ± 0.53/4.59 ± 0.58. Higher ICEBc quartiles were accompanied by increased GNRI (120.9 ± 13.7, 129 ± 15.1, 130.5 ± 16.3, 131.8 ± 17.6, p < 0.001)and decreased HALP scores (59.7 ± 24.4, 56.1 ± 25.3, 55.2 ± 25.9, 51.1 ± 19.4, p: 0.025). Conclusion: The association between BMI and cardiac electrophysiological balance is non-linear and appears to be modulated by nutritional and inflammatory status. ICEBc may represent a more sensitive marker than ICEB for detecting subtle electrophysiological alterations related to obesity. Full article

Background and aim: Traditional marker-based optical motion capture systems are costly, time-consuming to operate, and constrained by laboratory environments, limiting their broader adoption in clinical practice and naturalistic settings. Markerless motion capture based on a sums-of-Gaussians (SoG) body model is a potential alternative; however, its metrological properties for kinematic assessment during walking and slow running remain insufficiently validated. Using a conventional marker-based Vicon system as the reference, this study evaluated the reliability and concurrent validity of an SoG-based markerless system (MocapGS) for bilateral lower-limb joint range of motion (ROM) during gait. Methods: Thirty-six healthy adults completed self-selected-pace speed walking and slow running tasks while both systems synchronously acquired bilateral lower-limb kinematics. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), SEM percentage (SEM%), minimal detectable change (MDC), MDC percentage (MDC%), and root mean square error (RMSE) were used to assess reliability. Concurrent validity was evaluated using the Pearson correlation coefficient, paired-sample t-tests, and the concordance correlation coefficient (CCC) to compare the ROM. Results: Vicon showed moderate-to-high reliability for ROM in most joints across both tasks. By contrast, the MocapGS achieved acceptable ICC values mainly for the sagittal-plane ROM at the hip and knee. The CCC analysis showed no significant agreement between the two systems. Bland–Altman plots showed systematic biases with spatially heterogeneous random errors. During walking, MocapGS systematically overestimated ROM relative to Vicon at several joint axes; the widest limits of agreement (LOA) occurred at the left knee X-axis and right hip Z-axis. During running, overestimation was consistent across all bilateral joints at the X-axis and the right hip at the Y-axis, while the widest LOA were found at the bilateral hip X-axes. These specific discrepancies highlighted the joint–axis combinations with the greatest measurement variance. In walking, the test–retest reliability of the knee flexion–extension ROM measured by the MocapGS approached that of Vicon; however, the SEM% and MDC% were generally larger for MocapGS than for Vicon. The RMSE exceeded 5 degrees for ROM in most joint planes, especially in the frontal and transverse planes and at distal joints; errors increased further during slow running. Conclusions: MocapGS may be used for coarse monitoring of large-magnitude changes in sagittal-plane kinematics during gait; however, it is currently unlikely to replace Vicon for clinical decision-making or detecting subtle gait changes, and its outputs should be interpreted with caution, particularly for ankle kinematics and non-sagittal-plane motion. Full article

This article examines the theoretical and practical frameworks surrounding liminal states of consciousness—specifically lucid dreaming and out-of-body experiences (OBEs)—within Indian religious and philosophical traditions. Through a comparative analysis of Vedāntic, Yogic, Buddhist, and Jain systems, the article argues that these states are not merely anomalous psychological events but deliberately cultivated “architectures of liminality” designed to investigate the nature of self, consciousness, and reality. Methodologically, this article offers a comparative analysis of models and categories of liminal consciousness across Indian traditions, critically engaging relevant neurophenomenological frameworks and incorporating a small set of representative first-person exemplars. The results reveal a spectrum of interpretations: from the mind-only projection model of Buddhist dream yoga to the subtle-material interaction model of Jain karmic ontology, and from the embodied cognition framework of modern neuroscience to the disembodied consciousness theories of classical Indian systems. The study concludes that a comprehensive understanding of liminal consciousness must integrate first-person phenomenological reports with the soteriological, ritual, and metaphysical contexts that structure their interpretation, thereby challenging reductionist approaches in contemporary consciousness studies. Full article

A spatial awareness is a fundamental aspect of dance, reflecting deep philosophical ideas and aesthetic values across different cultures. While existing studies often focus on theatrical or biomechanical analyses, few explore how material cultural artifacts, such as pottery and porcelain figurines, reveal spatial differences in dance. This study addresses this gap by comparing Chinese pottery figurines from the Neolithic to Tang dynasties with Western Meissen porcelain dancers from the 18th century onward, applying a three-dimensional framework of “Movement Scheduling Space—kinetic space—expressive space.” Drawing on Confucian principles of “Harmony between Heaven and Humanity” and Christian notions of transcendence, the research examines how cultural traditions shape the spatial expression in dance. The findings show that Chinese dance emphasizes inward, upper-body movements extending from two-dimensional to one-dimensional space, reflecting a centripetal, earthly orientation. In contrast, Western dance expands from two-dimensional to three-dimensional space, emphasizing outward, lower-body movements symbolizing transcendental aspirations. Additionally, Chinese dance focuses on subtle hand gestures, while Western dance highlights expressive foot movements. By integrating artifact-based analysis with cultural and philosophical interpretation, this study offers a fresh approach to comparative dance philosophy, providing valuable insights for the reinterpretation of traditional aesthetics in modern choreography. Full article

Body size is a key trait influencing life history and ecological adaptation, and sexual size dimorphism (SSD) reflects divergent selective pressures acting on males and females. In morphologically conserved insect groups such as Cassidinae leaf beetles, the external similarity between sexes often impedes accurate dimorphism assessment. To address this, we conducted a systematic morphometric study of ten Cassidinae species from the Nanling Mountains—the largest east–west mountain system in southern China—where we definitively assigned sex via genital dissection. We measured body weight, body length, body width, length–width ratio, and corresponding wing traits. Across all species, SSD was consistently female biased, with statistically significant but subtle differences in most traits; body weight exhibited the greatest relative disparity. While this pattern aligns with the fecundity advantage hypothesis, direct fecundity data were not collected. Crucially, interspecific allometric analyses revealed that the scaling of male and female body sizes was statistically indistinguishable from that of isometry, providing no significant support for Rensch’s rule in this female-biased system. Our findings offer foundational insights into SSD evolution in cryptically dimorphic, herbivorous beetles and highlight the need for phylogenetically informed studies across broader geographic and taxonomic scales. Full article

Peroxisome-proliferator–activated receptor delta (PPARδ) regulates metabolic, mitochondrial, and inflammatory pathways implicated in neurodegeneration, making it an attractive therapeutic target for amyotrophic lateral sclerosis (ALS). In this study, we evaluated two PPARδ agonists, KD3010 and T3D-959, in two established ALS/FTD mouse models: an AAV-mediated C9orf72 G4C2-repeat expansion model (C9-149R) and the TDP-43^Q331K transgenic model. Drug treatment was initiated prior to the emergence of key disease features and continued for 9–10 months. Comprehensive behavioral, neuropathological, and biomarker analyses revealed marked differences between the two models. C9-149R mice exhibited reduced body weight and subtle behavioral alterations without robust motor deficits, whereas TDP-43^Q331K mice developed pronounced, progressive motor and cognitive impairments accompanied by a ~7-fold elevation in plasma neurofilament light chain (NfL). Despite effective target engagement—particularly for T3D-959—neither PPARδ agonist improved motor performance, cognitive behavior, neuroanatomical measures, plasma NfL levels, or disease-associated molecular phenotypes in either model. Prolonged KD3010 treatment resulted in loss of target engagement, consistent with drug tolerance, while T3D-959 sustained PPARδ activation without therapeutic benefit. Together, these findings demonstrate that PPARδ agonism is insufficient to modify disease progression in these ALS/FTD mouse models and underscore the importance of publishing well-powered negative preclinical studies to refine therapeutic strategies for ALS. Full article

On-load tap changers (OLTCs) are critical components of power transformers. In recent years, condition monitoring technologies for OLTCs based on vibration signals have attracted increasing research interest. However, practical applications still face several challenges, including background noise interference, insufficient characterization of transient signals, signal complexity, difficulty in detecting subtle anomalies, and ambiguous associations between fault modes and signal features. To address these issues, this paper proposes an OLTC acoustic fingerprint feature recognition method based on multidimensional phase-space trajectory analysis. First, an OLTC fault simulation platform was established, in which typical mechanical faults—such as fastener loosening, contact wear, and insufficient spring energy storage—were physically simulated. Corresponding vibration signals were then acquired under different operating conditions. Considering the independence of vibration characteristics at different locations of the distribution transformer, a blind source separation method based on endpoint detection was employed to separate OLTC vibration signals from the operational noise of the transformer body. Given the nonlinear and chaotic characteristics of OLTC vibration signals, phase-space reconstruction was introduced for signal analysis. Based on the reconstructed phase space, characteristic patterns and geometric feature parameters corresponding to different mechanical states of the OLTC were extracted. Furthermore, a two-dimensional membership function was constructed using the phase-space trajectories, and fuzzy inference based on predefined fuzzy rules was applied to compute representative feature parameters. A feature parameter database was subsequently established to enable OLTC condition identification. Experimental results demonstrate that the proposed diagnostic model can effectively classify and identify OLTC fault conditions using vibration signals, achieving an average classification accuracy exceeding 91.25%. The proposed method provides an effective non-intrusive approach for online monitoring and mechanical fault diagnosis of OLTCs without interrupting normal transformer operation. Full article

Background: Effects on insulin sensitivity and postprandial glycemia through enzyme inhibition and regulation of glucose transport have been extensively researched; however, the role of sugarcane (poly)phenols remain underexplored. Methods: In a randomized, placebo-controlled, single-blinded crossover study, 12 healthy participants consumed a bread-based meal containing 50 g of carbohydrates, supplemented with either 0.5% or 5% liquid PRSE or sugar-balanced controls. Glucose and plasma insulin levels were assessed over 180 min. The extract was evaluated for its inhibitory effect on human α-amylases (salivary and pancreatic) and α-glucosidases (sucrase, maltase, and isomaltase) utilizing solid PRSE. Results: The postprandial glucose and insulin responses to bread sandwiches in healthy volunteers remained unchanged by both PRSE dosages. High-dose treatment reduced the Matsuda index by 9.8%, perhaps due to a subtle alteration in whole-body insulin sensitivity. Low-dose intervention postponed the insulin peak by 30 min without altering HOMA-IR. In vitro, PRSE diminished sucrase activity by 67% (IC₅₀ = 425.8 ± 18.7 µg/mL) and lowered maltase and isomaltase activity by 40% (IC₂₅ = 876.3 ± 131 and 960.6 ± 95.2 µg/mL, respectively). It enhanced the activity of human salivary and pancreatic α-amylases. Conclusion: In healthy people, acute PRSE supplementation had a minor impact on postprandial glucose and insulin levels. Low-dose PRSE postponed the insulin peak, whereas high-dose PRSE reduced Matsuda index potentially via α-amylase activation, suggesting a modest alteration in whole-body insulin sensitivity without significantly changing the glucose or insulin response. In vitro, PRSE exhibited modest inhibition of human α-glucosidases. Full article

The clinical success of chimeric antigen receptor (CAR) T-cell therapies has revolutionized oncology, yet the high costs and logistical complexities of ex vivo manufacturing remain significant barriers to global patient access. In vivo cell therapy, which involves the direct injection of lentiviral vectors (LVVs) to engineer cells within the patient’s body, offers a promising, cost-effective alternative. However, transitioning from ex vivo to in vivo applications necessitates a fundamental shift in LVV biomanufacturing to ensure safety and efficacy. This paper examines the critical bottlenecks in the current LVV production landscape. In upstream processing, we explore LVV particle assembly and maturation mechanisms, the effect of transgene size on LVV functional titers and the formation of non-functional byproducts, including empty and partially formed LVV particles and extracellular vesicles (EVs). These impurities pose severe risks of immunotoxicity and insertional mutagenesis when delivered in vivo. In downstream processing, we highlight the challenges of purifying labile LVV particles, emphasizing the need for rapid, high-resolution separation techniques like continuous processing to maintain functional titers. Furthermore, we address the limitations of current analytical assays, which often fail to distinguish mature, functional LVVs from structurally similar but inactive contaminants. We conclude that the future of in vivo lentiviral therapy depends on developing novel purification strategies based on subtle biophysical differences—such as surface charge and capsid morphology—and implementing robust, high-throughput analytics to ensure delivery of high-purity, potent therapeutic viral vectors. Full article

This dataset presents a real-world lipidomics resource for developing and benchmarking quality control methods, batch effect detection algorithms, and data validation workflows. The data originates from a cross-sectional clinical study of psoriatic arthritis (PsA) patients (n = 81) and healthy controls (n = 26), matched for age, sex, and body mass index, which was collected at a tertiary university rheumatology center. Subtle laboratory irregularities were detected only through advanced unsupervised analysis, after passing conventional quality control and standard analytical methods. Blood samples were processed using standardized protocols and analyzed using high-resolution and tandem mass spectrometry platforms. Both targeted and untargeted lipid assays captured lipids of several classes (including carnitines, ceramides, glycerophospholipids, sphingolipids, glycerolipids, fatty acids, sterols and esters, endocannabinoids). The dataset is organized into four comma-separated value (CSV) files: (1) Box–Cox-transformed and imputed lipidomics values; (2) outlier-cleaned and imputed values on the original scale; (3) metadata including clinical classifications, biological sex, and batch information for all assay types and control sample processing dates; and (4) a variable-level description file (readme.csv). The 292 lipid variables are named according to LIPID MAPS classification and standardized nomenclature. Complete batch documentation and FAIR-compliant data structure make this dataset valuable for testing the robustness of analytical pipelines and quality control in lipidomics and related omics fields. This unique dataset does not compete with larger lipidomics quality control datasets for comparisons of results but provides a unique, real-life lipidomics dataset displaying traces of the laboratory sample processing schedule, which can be used to challenge quality control frameworks. Full article