Search Results (185)

Bone integrity is maintained through continuous remodeling, orchestrated by the coordinated actions of osteocytes, osteoblasts, and osteoclasts. Once considered passive bystanders, osteocytes are now recognized as central regulators of this process, mediating biochemical signaling and mechanotransduction. Malfunctioning osteocytes contribute to serious skeletal disorders such as osteoporosis. Mesenchymal stromal cells (MSCs), multipotent stem cells capable of differentiating into osteoblasts, have emerged as promising agents for bone regeneration, primarily through the paracrine effects of their secreted exosomes. MSC-derived exosomes are nanoscale vesicles enriched with proteins, lipids, and nucleic acids that promote intercellular communication, osteoblast proliferation and differentiation, and angiogenesis. Notably, they deliver osteoinductive microRNAs (miRNAs) that influence osteogenic markers and support bone tissue repair. In vivo investigations validate their capacity to enhance bone regeneration, increase bone volume, and improve biomechanical strength. Additionally, MSC-derived exosomes regulate the immune response, creating pro-osteogenic and pro-angiogenic factors, boosting their therapeutic efficacy. Due to their cell-free characteristics, MSC-derived exosomes offer benefits such as diminished immunogenicity and minimal risk of off-target effects. These properties position them as promising and innovative approaches for bone regeneration, integrating immunomodulatory effects with tissue-specific regenerative capabilities. Full article

Traditional 2D optical markers degrade quickly in underwater applications due to sediment accumulation and marine biofouling, becoming undetectable within weeks. This paper presents a Three-Dimensional Binary Marker, a novel passive fiducial marker designed for underwater Long-Term Deployment. The Three-Dimensional Binary Marker addresses the 2D-markers limitation through a 3D design that enhances resilience and maintains contrast for computer vision detection over extended periods. The proposed solution has been validated through simulation, water tank testing, and long-term sea trials for 5 months. In each stage, the marker was compared based on detection per visible frame and the detection distance. In conclusion, the design demonstrated superior performance compared to standard 2D markers. The proposed Three-Dimensional Binary Marker provides compatibility with widely used fiducial markers, such as ArUco and AprilTag, allowing quick adaptation for users. In terms of fabrication, the Three-Dimensional Binary Marker uses additive manufacturing, offering a low-cost and scalable solution for underwater localization tasks. The proposed marker improved the deployment time of fiducial markers from a couple of days to sixty days and with a range up to seven meters, providing robustness and reliability. As the marker survivability and detection range depend on its size, it is still a valuable innovation for Autonomous Underwater Vehicles, as well as for inspection, maintenance, and monitoring tasks in marine robotics and offshore infrastructure applications. Full article

Background: In just twenty years, three dangerous human coronaviruses—SARS-CoV, MERS-CoV, and SARS-CoV-2 have exposed critical gaps in early detection of emerging viral threats. Current diagnostics remain pathogen-focused, often missing the earliest phase of infection. A virus-agnostic, host-based diagnostic capable of detecting responses to viral intrusion is urgently needed. Methods: We hypothesized that the lungs act as biomechanical instruments, with infection altering tissue tension, wave propagation, and flow dynamics in ways detectable through subaudible vibroacoustic signals. In a matched case–control study, we enrolled 19 RT-PCR-confirmed COVID-19 inpatients and 16 matched controls across two Johns Hopkins hospitals. Multimodal data were collected, including passive vibroacoustic auscultation, lung ultrasound, peak expiratory flow, and laboratory markers. Machine learning models were trained to identify host-response biosignatures from anterior chest recordings. Results: 19 COVID-19 inpatients and 16 matched controls (mean BMI 32.4 kg/m², mean age 48.6 years) were successfully enrolled to the study. The top-performing, unoptimized, vibroacoustic-only model achieved an AUC of 0.84 (95% CI: 0.67–0.92). The host-covariate optimized model achieved an AUC of 1.0 (95% CI: 0.94–1.0), with 100% sensitivity (95% CI: 82–100%) and 99.6% specificity (95% CI: 85–100%). Vibroacoustic data from the anterior chest alone reliably distinguished COVID-19 cases from controls. Conclusions: This proof-of-concept study demonstrates that passive, noninvasive vibroacoustic biosignatures can detect host response to viral infection in a hospitalized population and supports further testing of this modality in broader populations. These findings support the development of scalable, host-based diagnostics to enable early, agnostic detection of future pandemic threats (ClinicalTrials.gov number: NCT04556149). Full article

Objective: This study aimed to evaluate the effects of cold-water immersion (CWI) on post-training recovery in Kung Fu athletes. Methods: In a 3-week crossover design, 16 Kung Fu athletes (22.00 ± 5.95 years, 76.90 ± 9.74 kg) were divided into two conditions: CWI and passive recovery as a control (CON) measure. Through the study, muscle damage markers (creatine kinase [CK], lactate dehydrogenase [LDH], aspartate aminotransferase [AST] and alanine aminotransferase [ALT]), physical performance tests (upper limbs power, SJ and CMJ), skin temperature (from lower and upper limbs), and skin temperature asymmetries were measured. Results: CWI resulted in a higher reduction of CK concentration than CON 24 h after the intervention (−21.32%; p < 0.001). The SJ height 24 h after the intervention was higher in the CWI than in the CON (p < 0.001). Both CWI and CON resulted in skin temperature returning to baseline levels 24 h after intervention. Conclusions: CWI was effective in restoring muscle power, reducing muscle damage and reducing body temperature (BT) in Kung Fu athletes. Cold water recovery showed better muscle power and strength 24 and 48 h after training when compared to the passive method. CK and skin temperature were better 24 h after cold water recovery. Full article

Cognitive problems are associated with impaired learning ability and memory dysfunction. Neuroinflammation has been identified as an important factor in the progression of anxiety and depressive disorders. Zingerone is a phenolic alkanone derived from ginger (Zingiber officinale Roscoe), which is known for its antioxidant and anti-inflammatory properties. A number of studies have investigated the effect of zingerone on neuroinflammation and cognitive impairment. However, this evidence has not been systematically reviewed. This study sought to systematically review the effect of zingerone on neuroinflammation and neurobehavioural changes associated with memory and learning impairment and anxiety-like and depressive-like behaviours. A systematic review was conducted using pre-defined search criteria on Google Scholar, Scopus and Web of Science. The records obtained were screened based on inclusion criteria, and data was extracted from the included studies. Out of the 482 studies that were identified, only 9 studies met the inclusion criteria. Neuroinflammatory markers such as interleukin 1β (IL-1β), interleukin 6 (IL-6), tumour necrosis factor-alpha (TNF-α) and ionized calcium binding adaptor molecule (IBA-1), as well as behavioural parameters including Morris water maze, Y-Maze, recognition test, passive avoidance test, elevated plus maze, sucrose preference test and forced swimming test were measured. Zingerone exhibited anti-neuroinflammatory effects by improving IL-1β, IL-6 and TNF-α levels. However, zingerone did not show any significant changes on activated microglia. The anti-neuroinflammatory mechanisms of zingerone were linked to the inhibition of nuclear factor kappa B (NF-kB) activation and the NOD-like receptor family, pyrin domain-containing 3 (NLRP3) inflammasome, as well as the reduction in neuronal nitric oxide synthase (nNOS). The anxiolytic and anti-depressive effects of zingerone were also associated with an improvement in cortical cholinergic transmission, the mitigation of oxidative stress and the upregulation of neurotransmitters such as serotonin and dopamine. This review provides scientific evidence on the cognitive enhancing and neuroprotective mechanisms of zingerone, which may be beneficial for future experimental investigations. Full article

Recently, compounds of plant origin have been the focus of increased scientific interest. Micromeria frivaldszkyana is a rare species endemic to Bulgaria, whose biological activity remains unknown. This article aims to evaluate the subchronic toxicity of Micromeria frivaldszkyana methanolic extract and its effect on cognition in rats. Following 90 days of oral administration, a histopathological evaluation of brain, kidney, and liver tissues was conducted. Additionally, serum levels of total bilirubin (TB), conjugated bilirubin (CB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), creatinine (CR), uric acid (UA), and urea (U) were measured. Cognitive function was studied after 7 d of treatment using activity cage test, along with tests for active memory, passive memory, anxiety, spatial and working memory, and explorative activity. The experiments showed no toxic effects of the extract in subchronic application. No adverse effects on brain function were observed after 14 days of treatment. While the extract increased the motor activity of the animals, it did not significantly improve the learning and memory processes. In conclusion, the methanolic extract of Micromeria frivaldszkyana in doses 250 and 500 mg/kg bw did not induce toxicity after 90-day treatment in rats. These doses did not significantly affect central nervous system (CNS) functions, although increased motor activity was observed after 14 days of treatment with the extract. Full article

This study analyses for the first time the genetic diversity, connectivity, and evolutionary dynamics of the small red scorpionfish (Scorpaena notata) in the Balearic Islands, using two mitochondrial DNA markers: Cytochrome c oxidase subunit I (COI) and the Control Region (CR). Nucleotide diversity of the COI gene was found to be low compared to other commercial fish species, suggesting that fishing may be impacting the population despite being a by-catch species. In contrast, the CR showed higher genetic variability. Demographic history analyses suggest that S. notata underwent a population expansion during the Pleistocene, possibly driven by sea-level changes. Genetic structure analyses (F_st and AMOVA) indicated genetic homogeneity and high connectivity among the Balearic Islands’ population, likely facilitated by its passive dispersion via pelagic eggs and larvae and the oceanographic conditions of the region. Our results suggest that the entire Balearic Islands could be considered as a unique Management Unit, although its potential relation to other nearby areas, such as the Iberian Peninsula, along with the analysis of additional genetic markers, should be addressed in future studies. Full article

Curved-spoke wheels have been proposed as an effective way to overcome stair-like obstacles with smooth, rotation-only motion. However, when the wheel’s contact point shifts, discontinuous changes in its radius of curvature cause abrupt drops in the robot’s linear speed, often leading to reduced payload stability and slip. As a result, maintaining reliable stair climbing becomes more difficult. At higher speeds, these sudden changes become stronger, further reducing dynamic stability. To address these issues, we propose a passive Compliant Spiral Torsional Suspension (C-STS) attached to the wheel’s drive axis. Through camera-based marker tracking, we analyzed wheel trajectories under various stiffness and speed conditions. In particular, we define the deceleration caused by the velocity drop during contact transitions as our dynamic stability metric and demonstrate that the C-STS significantly reduces this deceleration across low-, medium-, and high-speed climbing, based on comparisons both with and without the suspension. It also raises the average velocity, likely due to a brief release of stored elastic energy, and lowers the net torque requirement. Our findings show that the proposed C-STS greatly improves dynamic stability and suggest its potential for enhancing stair-climbing performance in curved-wheel-based robotic systems. Furthermore, our approach may extend to other reconfigurable wheels facing similar instabilities. Full article

Passive Dynamic Ankle–Foot Orthoses (PD-AFOs) are medical devices prescribed to individuals with foot drop, a condition characterized by weakness of the ankle dorsiflexor muscles. PD-AFOs can store and release energy during the stance phase of the gait cycle, while supporting the foot in the swing phase. This study aimed at estimating the energetics of a novel fiberglass-reinforced polyamide custom PD-AFO in a population of mild foot drop patients. Eight PD-AFOs were designed and 3D-printed via selective laser sintering for eight participants with a unilateral foot drop condition. Lower limb kinematics and AFO flexion/extension were recorded during comfortable walking speed via skin marker-based stereophotogrammetry. The stiffness of each AFO was measured via an ad hoc experimental setup. The elastic work performed by the PD-AFO during gait was calculated as the dot product of the calf-shell resisting moment and the rotation angle. The average maximum energy stored by the calf-shell across all PD-AFOs was 0.013 ± 0.005 J/kg. According to this study, 3D-printed custom PD-AFOs made with fiberglass-reinforced polyamide can store some elastic energy, which is released to the ankle during push-off. Further studies should be conducted to assess the effect of this energy return mechanism in improving the gait of individuals with deficits of the ankle plantarflexor muscles. Full article

Digital biomarkers for fatigue monitoring in neurological disorders represent an innovative approach to bridge the gap between mechanistic understanding and clinical application. This perspective paper examines how smartphone-derived measures, analyzed through artificial intelligence methods, can transform fatigue assessment from subjective, episodic reporting to continuous, objective monitoring. The proposed framework for smartphone-based digital phenotyping captures passive data (movement patterns, device interactions, and sleep metrics) and active assessments (ecological momentary assessments, cognitive tests, and voice analysis). These digital biomarkers can be validated through a multimodal approach connecting them to neuroimaging markers, clinical assessments, performance measures, and patient-reported experiences. Building on the previous research on frontal–striatal metabolism in multiple sclerosis and Long-COVID-19 patients, digital biomarkers could enable early warning systems for fatigue episodes, objective treatment response monitoring, and personalized fatigue management strategies. Implementation considerations include privacy protection, equity concerns, and regulatory pathways. By integrating smartphone-derived digital biomarkers with AI analysis approaches, the future envisions fatigue in neurological disorders no longer as an invisible, subjective experience but rather as a quantifiable, treatable phenomenon with established neural correlates and effective interventions. This transformative approach has significant potential to enhance both clinical care and the research for millions affected by disabling fatigue symptoms. Full article

Beyond the genomic and proteomic analysis of bulk and single cancer cells, a new focus of cancer research is emerging that is based on the mechanical analysis of cancer cells. Therefore, several biophysical techniques have been developed and adapted. The characterization of cancer cells, like human cancer cell lines, started with their mechanical characterization at mostly a single timepoint. A universal hypothesis has been proposed that cancer cells need to be softer to migrate and invade tissues and subsequently metastasize in targeted organs. Thus, the softness of cancer cells has been suggested to serve as a universal physical marker for the malignancy of cancer types. However, it has turned out that there exists the opposite phenomenon, namely that stiffer cancer cells are more migratory and invasive and therefore lead to more metastases. These contradictory results question the universality of the role of softness of cancer cells in the malignant progression of cancers. Another problem is that the various biophysical techniques used can affect the mechanical properties of cancer cells, making it even more difficult to compare the results of different studies. Apart from the instrumentation, the culture and measurement conditions of the cancer cells can influence the mechanical measurements. The review highlights the main advances of the mechanical characterization of cancer cells, discusses the strength and weaknesses of the approaches, and questions whether the passive mechanical characterization of cancer cells is still state-of-the art. Besides the cell models, conditions and biophysical setups, the role of the microenvironment on the mechanical characteristics of cancer cells is presented and debated. Finally, combinatorial approaches to determine the malignant potential of tumors, such as the involvement of the ECM, the cells in a homogeneous or heterogeneous association, or biological multi-omics analyses, together with the dynamic-mechanical analysis of cancer cells, are highlighted as new frontiers of research. Full article

Background: Gait assessment is a complex task involving locomotion and balance control across all body segments, requiring a global analysis in the event of motor disorders. Among these are spinal disorders, where an understanding of spinal kinematics during walking is important to improve treatment decisions and outcomes. The technique of stereophotogrammetric motion analysis is currently the gold standard in this context. A new integrated protocol for whole-body kinematic gait analysis is proposed in this study, which takes into account the movements of the spine. Methods: A new protocol with 30 passive markers was developed to analyze gait. Of these markers, 22 implemented the Davis protocol for gait measurement, while the other 8 were placed onto the spine to record spinal movements. The protocol’s accuracy was assessed through comparisons of the constructive angles of a manikin replicating the human body and the angles measured with the optoelectronic system. An assessment of intra- and inter-operator repeatability and protocol usability was carried out by recruiting and applying the protocol in a population composed of ten subjects (mean age 17.36—SD 10.12) without any history of spine pathology. Results: The protocol was validated successfully. The validation accuracy was more than satisfactory: the measured RMSE was 1.2 ± 1° for the data collected with the optoelectronic system with respect to the manikin. The intra-operator repeatability was also good in the sagittal and frontal planes (average ICC > 0.867), and the inter-operator repeatability was moderate or good in all planes (average ICC > 0.77). The usability score obtained using the System Usability Scale was satisfactory (mean 74.75, SD 5.88). Conclusions: This study proposes a new protocol to assess total body kinematics, including the spine in its three main segments, during gait. The successful validation of this protocol in terms of reliability and usability allows for its subsequent clinical application. Full article

This study explores the biomechanical impact of an elliptical leaf spring (ELS) foot on individuals with unilateral below-knee amputation. The ELS-foot, constructed with carbon fiber leaf springs and an ethylene-vinyl acetate rocker bottom sole, aims to balance energy storge and dissipation for effective cushioning and energy management. Six participants were recruited and visited the laboratory twice within a 3-to-5-day interval. The ELS-foot is compared with their own prosthesis through various mobility and balance tests, including the Timed Up and Go test, Four Square Step Test, 10 m walk test, Berg Balance Test, eyes-closed standing test, Tandem Test, jumping and walking test, and a subjective evaluation. Passive-reflective markers are placed on the participants according to the plug-in full body model. An eight-camera motion capture system synced with two force plates mounted under a walkway is used for the gait analysis. The results show that participants move faster during the Four Square Step Test and demonstrate better balance during the eyes-closed standing test and Tandem Test and jump higher with the ELS-foot. The unique ELS-foot design mechanism and rocker bottom sole facilitates better energy transfer and stability, thus enhancing the postural stability. These findings offer valuable insights for future prosthetic technology advancements. Full article

Gastrodia elata, Polygonatum sibiricum, and Poria cocos are traditional Chinese herbs commonly used as both medicinal and food ingredients, traditionally believed to improve liver and kidney functions, replenish vital energy (qi) and blood, and mitigate stress-induced damage. These herbs are combined in the Compound Gastrodia elata Formula (CGEF), a functional food formulation. Amidst growing interest in functional foods, this study explores the cognitive-enhancing effects of CGEF, focusing on cognitive function improvement. Cognitive impairment was induced in ICR mice via chronic sleep restriction. Behavioral assessments including the Y-maze test, object recognition test, Morris water maze test, and Passive avoidance test, were conducted to evaluate CGEF’s effects. Serum levels of inflammatory markers and oxidative stress were quantified while in rat hippocampus tissue expressions of inflammatory, apoptotic, and neuroprotective-related protein markers were analyzed by Western blotting. Neurotransmitter concentrations in both the hippocampus and prefrontal cortex were determined by LC-MS/MS. CGEF significantly alleviated cognitive impairments across all behavioral tests. The underlying mechanisms likely involve a reduction in oxidative stress and peripheral inflammatory factors, and suppression of the TLR2/MyD88/NF-κB signaling cascade in the hippocampus, thereby mitigating neuroinflammation and neuronal apoptosis. Furthermore, CGEF modulated the PI3K/AKT/GSK3β signaling pathway, potentially contributing to neuronal integrity and synaptic plasticity maintenance. CGEF also restored neurotransmitter balance and regulated tryptophan metabolism, further alleviating cognitive deficits associated with sleep disruption. These findings suggest CGEF’s potential as a functional food for reversing cognitive impairments caused by chronic sleep restriction, primarily through its anti-inflammatory and neuroprotective effects. Full article

Loneliness is a global issue which is particularly prevalent among college students, where it poses risks to mental health and academic success. Chronic loneliness can manifest in two primary forms: social loneliness, which is defined by a lack of belonging or a social network, and emotional loneliness, which comes from the absence of deep, meaningful connections. Differentiating between these forms is crucial for designing personalized and targeted interventions. Passive sensing technology offers a promising, unobtrusive approach to detecting loneliness by using behavioural data collected from smartphones and wearables. This study investigates behavioural patterns associated with social and emotional loneliness using passively sensed data from a student population. Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. Using statistical analysis, machine learning, and SHAP-based feature importance methods, we identified significant differences in behaviours between socially and Emotionally Lonely students. Specifically, there were distinct differences in phone use and location-based features. Our machine learning analysis shows a strong ability to classify types of loneliness accurately. The XGBoost model achieved the highest accuracy (78.48%) in predicting loneliness. Feature importance analysis found the critical role of phone usage and location-based features in distinguishing between social and emotional loneliness. Full article