Search Results (737)

This review explores the transformative potentials of artificial intelligence (AI) in promoting healthspan and longevity. Healthspan focuses on enhancing quality of life free from chronic conditions, while longevity defines current lifespan limits within a particular species and encompasses biological aging at multiple levels. AI methodologies—including machine learning, deep learning, natural language processing, robotics, and data analytics—offer unprecedented tools to analyze complex biological data, accelerate biomarker discovery, optimize therapeutic interventions, and personalize medicine. Notably, AI has facilitated breakthroughs in identifying accurate biomarkers of biological age, developing precision medicine approaches, accelerating drug discovery, and enhancing genomic editing technologies such as CRISPR. Further, AI-based analysis of endogenous cytoprotection, especially the activity of molecules such as heme oxygenase, with particular application to hemolytic diseases. AI-driven robotics and automated monitoring systems significantly improve elderly care, lifestyle interventions, and clinical trials, demonstrating considerable potential to extend both healthspan and lifespan. However, the integration of AI into longevity research poses ethical and societal challenges, including concerns over privacy, equitable access, and broader implications of extended human lifespans. Strategic interdisciplinary collaboration, transparent AI methodologies, standardized data frameworks, and equitable policy approaches are essential to responsibly harness AI’s full potential in transforming longevity science and improving human health. Full article

Depression is one of the most prevalent mental health conditions in middle and late adulthood, contributing substantially to morbidity, mortality, and reduced quality of life. However, limited research has examined the mechanisms linking genetic predisposition and early protective environments to long-term mental health trajectories. Guided by a life course health development perspective, this study investigated how depression polygenic scores (G) and protective childhood family environments (E) interplay to shape depressive symptom trajectories from mid- to late adulthood. We analyzed longitudinal data of 14 waves from the Health and Retirement Study (1994–2020; N = 4817), estimating linear mixed-effects models of depressive symptoms using the validated CES-D scale. Early protective environments were measured by indicators of family structure stability, non-abusive and substance-free parenting, positive parent–child relationships, and parental support. Results showed that genetic predisposition and protective family environments jointly influence depression trajectories across the life course. Specifically, individuals with both low genetic risk and high environmental protection had the lowest depressive symptoms over time. Importantly, when only one favorable factor was present, protective family environments offered a stronger lifelong benefit than low genetic risk. These findings extend prior research by demonstrating that supportive childhood environments can mitigate genetic vulnerability, shaping healthier long-term mental health trajectories. This work underscores the need for early family-based interventions to reduce depression risk, enhance resilience, and promote longevity. Full article

Despite the extensive cultivation of Moringa trees in tropical regions, understanding of accession-specific performance across diverse agroecological zones remains inadequate. Thus, this study evaluated the growth, adaptability, and leaf yield performance of 12 Moringa accessions (11 M. oleifera and 1 M. stenopetala) over three years in a subtropical climate (Pretoria, South Africa). Seeds were planted in seedling trays in the glasshouse at the University of Pretoria’s experimental farm. Vigorous seedlings were transplanted to the field at the Roodeplaat experimental site of the Agricultural Research Council two months after establishment, following a randomized complete block design (RCBD). Data were measured on establishment (emergence, survival), growth and yield parameters, and monitored plant health via leaf greenness, vigour, chlorosis, and pest and disease incidence. Accessions exhibited substantial variation for most traits, except for stem diameter. Moringa stenopetala showed the highest initial emergence rate but later displayed lower survival rates than most M. oleifera accessions. Survival rates, morphological features (plant height, canopy diameter, and branching), visual scores for leaf greenness and plant vigour, and leaf yield (fresh and dry) varied considerably among the accessions. Moringa oleifera A2 consistently performed well, exhibiting vigorous growth, the maximum survival rate (78%), and fresh leaf production (6206 kg ha⁻¹). Accessions A3 and A8 showed intermediate yield and longevity, indicating potential for cultivation or breeding. Conversely, M. oleifera A10 and M. stenopetala markedly underperformed in most traits, limiting their cultivation potential. Based on multi-year performance, A2 is suggested for large-scale cultivation due to its vigour, yield, and stress tolerance, while A3 and A8 hold breeding potential. The study emphasizes the critical role of genetic variation and selection in enhancing Moringa productivity under subtropical environments. Future work should focus on genetic characterization and agronomic practices optimization of superior accessions. Full article

Background: In elite football, understanding how age impacts players’ physical performance is essential for optimizing training, career longevity, and team management. Objectives: This study aimed to compare variations in physical capabilities of professional football players by chronological age and identify peak performance ages. Methods: Data from 5203 match performances across 351 official games were analyzed, involving 98 male players aged 18–39 years. Physical capacities (speed, explosive actions, and endurance) were assessed using the Catapult VECTOR7 system. Results: showed that players over 32 years experienced declines in high-intensity and explosive actions, while endurance remained relatively stable with age. Peak performance occurred around 25.7 years for speed, 24.8 years for endurance, and 26 years for explosiveness. Conclusions: Overall, players aged 17–26 years demonstrated the highest physical performance, with notable declines observed in older age groups. Full article

Background: The adhesion between artificial teeth and denture bases is crucial for the longevity of complete dentures. This in vitro study evaluated the shear bond strength (SBS) and failure modes between artificial teeth and denture base resins produced with conventional, milled, and 3D-printed techniques. Materials: A total of 105 specimens were fabricated and assigned to 7 groups (n = 15) combining conventional, milled, or printed denture bases with conventional, milled, or printed teeth. SBS was tested using a universal testing machine, and failure modes were classified as adhesive, cohesive, or mixed. Data were analyzed with one-way ANOVA and Tukey’s post hoc test (α = 0.05). Results: SBS significantly varied among groups (p < 0.001). The conventional base–conventional tooth group (CB-CT) showed the highest bond strength (14.9 ± 3.69 MPa), while the printed base–milled tooth group (PB-MT) had the lowest (6.58 ± 3.41 MPa). Milled base groups showed intermediate values (11.7–12.4 MPa). Conclusions: Bond strength between denture teeth and denture bases depends on the fabrication workflow. Conventional heat-cured PMMA bases exhibited the most reliable adhesion, while milled bases demonstrated satisfactory performance with optimized bonding. Printed bases showed reduced and variable adhesion, suggesting the need for improved bonding protocols before their widespread clinical application in definitive prostheses. Full article

In this paper, Distribution of Relaxation Time (DRT) analysis is presented as a powerful tool for understanding the aging mechanisms in lithium-ion batteries, with a focus on its application to estimating the State of Health (SOH). A novel parameter, the characteristic relaxation time, derived from DRT analysis, is introduced to enhance SOH estimation. By analyzing the ratio of the central relaxation time (τ) between the charge transfer and diffusion peaks, the battery status can be determined without the need for historical data. Experimental data from lithium-ion batteries, including 18650 cells and LR2032 coin cells, were examined until the end of their life. Nyquist and DRT plots across various frequency ranges revealed consistent aging trends, particularly in the charge transfer and diffusion processes. These processes appeared as shifting and merging peaks in the DRT plots, signifying progressive degradation. A polynomial equation fitted to the τ ratio graph achieved a high accuracy (Adj. R² = 0.9994), enabling reliable battery lifespan prediction. Validation with a Samsung Galaxy S9+ battery demonstrated that the method could estimate its remaining life, predicting a total lifespan of approximately 2100 cycles (compared to 1000 cycles already completed). These results confirm that SOH estimation is feasible without prior data and highlight the potential of DRT analysis for accurate and quantitative prediction of battery longevity. Full article

Excessive energy consumption of communication protocols in IoT/IIoT systems constitutes one of the key constraints for the operational longevity of remote sensor nodes, where radio transmission often incurs higher energy costs than data acquisition or local computation. Previous studies have remained fragmented, typically focusing on selected technologies or specific layers of the communication stack, which has hindered the development of comparable quantitative metrics across protocols. The aim of this study is to design and validate a unified evaluation framework enabling consistent assessment of both wired and wireless protocols in terms of energy efficiency, reliability, and maintenance costs. The proposed approach employs three complementary research methods: laboratory measurements on physical hardware, profiling of SBC devices, and simulations conducted in the COOJA/Powertrace environment. A Unified Comparative Method was developed, incorporating bilinear interpolation and weighted normalization, with its robustness confirmed by a Spearman rank correlation coefficient exceeding 0.9. The analysis demonstrates that MQTT-SN and CoAP (non-confirmable mode) exhibit the highest energy efficiency, whereas HTTP/3 and AMQP incur the greatest energy overhead. Results are consolidated in the ICoPEP matrix, which links protocol characteristics to four representative RS-IoT scenarios: unmanned aerial vehicles (UAVs), ocean buoys, meteorological stations, and urban sensor networks. The framework provides well-grounded engineering guidelines that may extend node lifetime by up to 35% through the adoption of lightweight protocol stacks and optimized sampling intervals. The principal contribution of this work is the development of a reproducible, technology-agnostic tool for comparative assessment of IoT/IIoT communication protocols. The proposed framework addresses a significant research gap in the literature and establishes a foundation for further research into the design of highly energy-efficient and reliable IoT/IIoT infrastructures, supporting scalable and long-term deployments in diverse application environments. Full article

It has been proven that marital status affects health outcomes, with marriage often linked to greater longevity and wellbeing. However, while married individuals generally exhibit higher life expectancy, the ordering among other marital statuses (never married, divorced, widowed) can vary by gender and socio-cultural context. This study examines the evolving relationship between marital status and life expectancy in Greece over a 30-year period (1991–2021). Utilizing Hellenic Statistical Authority (ELSTAT) data specifically commissioned for this research, it constructs life tables by marital status, incorporating, for the first time in Greece, life tables for those in civil partnerships for 2021. While life expectancy improved across all marital statuses, married individuals consistently had the highest longevity, whereas those in civil partnerships are expected to live less than married individuals. Furthermore, widowers experienced a substantial increase in life expectancy, while by 2021, divorced males had the lowest life expectancy among men and divorced females showed the highest mortality rates at older ages among women. The relative position of never-married individuals improved over the period. Never-married women generally outlived never-married men, with this gap widening for the divorced. The most compelling finding is that the difference in mortality among family status categories appears to have diminished over time in Greece. Full article

Wireless sensor networks (WSNs) are key enablers of efficient communication in the Internet of Things (IoT) ecosystem. These networks comprise numerous sensor nodes that collaboratively collect and transmit data, requiring adaptive and energy-efficient management. However, high node density and resource limitations introduce challenges such as control overhead, packet collisions, interference, and energy inefficiency. To mitigate these issues, this paper adopts the Hybrid Wireless Mesh Protocol (HWMP), standardized under IEEE 802.11s for wireless mesh networks (WMNs), as the routing protocol in WSNs. HWMP’s hybrid design combining reactive and proactive routing is well-suited for dynamic and mobile environments, making it applicable to WSNs operating under similar conditions. Building on this foundation, we propose a community-aware topology control mechanism that constructs a Connected Dominating Set (CDS) to serve as the network’s energy-efficient backbone. Node selection is guided by centrality metrics and detected community structures to enhance routing efficiency and network longevity. The mechanism is evaluated across six mobility scenarios characterized by realistic movement patterns. Comparative results show that incorporating community structure significantly improves routing performance and reduces energy consumption, validating the approach’s effectiveness in real-world WSN deployments. Full article

Objective: Maxillofacial silicone elastomers represent a standard material in maxillofacial prosthetic applications due to their excellent biocompatibility and aesthetic properties. However, their long-term performance is limited by color degradation and susceptibility to fungal colonization. Incorporating nanoparticles into silicone matrices has emerged as a potential solution to enhance durability and hygiene. This study aimed to evaluate the effect of zinc oxide (ZnO) and titanium dioxide (TiO₂) nanoparticles used individually and in combination to evaluate the color stability and antifungal activity of pigmented maxillofacial silicone elastomers. Material and Methods: Fifty specimens were fabricated for each test and divided into five groups: Group (A) control (pigmented silicone only, no nanoparticles), Group (B) ZnO (1.5 wt%), Group (C) TiO₂ (2.5 wt%), and two combinations: Group(D1) (0.75 wt% ZnO + 1.25 wt% TiO₂) and Group (D2)(0.5 wt% ZnO + 0.83 wt% TiO₂) ratios. Color stability was assessed before and after 500 h of artificial aging using CIELAB-ΔE values and visual scoring. Antifungal activity was evaluated against Candida albicans using the disk diffusion method. Attenuated Total Reflectance with Fourier Transform Infrared Spectroscopy (ATR-FTIR), Scanning electron microscopy (SEM) along side with Energy-dispersive X-ray spectroscopy (EDS) were applied for Specimen characterization. Data were analyzed with one-way ANOVA and Tukey’s post hoc test (α = 0.05). Results: The dual-nanoparticle group with 0.75% ZnO and 1.25% TiO₂ demonstrated the best color stability (ΔE = 0.86 ± 0.50) and strongest antifungal activity (inhibition zone: 7.8 ± 3.8 mm) compared to the control (ΔE = 2.31 ± 0.62; no inhibition). Single-nanoparticle groups showed moderate improvements. A significant Association (r = 0.89, p < 0.01) was found between nanoparticle dispersion and material performance. Conclusions: Incorporating ZnO and TiO₂ nanoparticles into maxillofacial silicone elastomers significantly enhances color stability and antifungal efficacy. The combined formulation showed a synergistic effect, offering promising potential for improving the longevity and hygiene of maxillofacial prostheses. Full article

Underwater crack detection is critical for ensuring the safety and longevity of submerged infrastructures, yet it remains challenging due to water-induced image degradation, limited labeled data, and the poor generalization of existing models. This paper proposes a novel deep learning framework that integrates physical priors and uncertainty modeling to address these challenges. Our approach introduces a physics-guided enhancement module that leverages underwater light propagation models, and a dual-branch segmentation network that combines semantic and geometry-aware curvature features to precisely delineate irregular crack boundaries. Additionally, an uncertainty-aware Transformer module quantifies prediction confidence, reducing the number of overconfident errors in ambiguous regions. Experiments on a self-collected dataset demonstrate State-of-the-Art performance, achieving 81.2% mIoU and 83.9% Dice scores, with superior robustness in turbid water and uneven lighting. The proposed method introduces a novel synergy of physical priors and uncertainty-aware learning, advancing underwater infrastructure inspection beyond the current data-driven approaches. Our framework offers significant improvements in accuracy, robustness, and interpretability, particularly in challenging conditions like turbid water and non-uniform lighting. Full article

Recurrence of the original glomerular disease (GN) poses a significant threat to kidney transplant function and longevity. The probability and severity of this recurrence vary, with C3 glomerulopathy and certain forms of FSGS exhibiting particularly high rates. Kidney transplant GN recurrence risk hinges on the characteristics of the initial GN, recipient/donor genetics, recipient age, donor type, end-stage kidney disease (ESRD) progression rate, and proteinuria levels. Standard immunosuppression has limited efficacy in preventing primary disease recurrence; however, agent selection and induction therapy can influence the risk for specific GNs. Diagnosing recurrent GN involves a comprehensive approach, including clinical evaluation, laboratory tests (such as proteinuria, hematuria, and specific biomarkers like anti-PLA2R for membranous nephropathy or complement for C3G), and, critically, an allograft biopsy analyzed with light, immunofluorescence, and electron microscopy. Treatment strategies are evolving towards targeted therapies, such as rituximab for antibody-mediated GN and complement inhibitors for C3G, moving away from broad immunosuppression. This narrative literature review provides practical monitoring algorithms for post-transplant settings, synthesizing information on the incidence, predictors, diagnostic strategies, and therapeutic options for various glomerular disease subtypes. The methodology involved searching MEDLINE, Embase, and Cochrane databases from 1996 to 2025, prioritizing systematic reviews, cohort studies, registries, and interventional reports. Eligibility criteria included adult transplant recipients and English-language reports on recurrent glomerular disease outcomes, excluding most single-patient case reports. Limitations include potential selection bias, omission of relevant studies, and the absence of a formal risk-of-bias assessment or meta-analysis. The evidence base is heterogeneous, with inconsistent outcome reporting and scarce randomized controlled trials. Future efforts should focus on developing predictive biomarkers, standardizing diagnostic and response criteria, conducting multicenter prospective cohorts and pragmatic trials, and creating shared registries with harmonized data. Full article

The durability and safety of modern concrete architecture and infrastructure are critically impacted by early-stage surface cracks. Timely and appropriate identification and management of these cracks are therefore essential to enhance structural longevity and stability. This study utilizes computer vision technology to construct a large-scale database, comprising 106,998 concrete surface crack images from various research sources. Through data augmentation, the database is extended to 140,000 images to fully leverage the advantages of deep learning models. For concrete surface crack detection, this study proposed a lightweight convolutional neural network (CNN) model, achieving 92.27% accuracy, 94.98% recall, and a 92.39% F1 score. Notably, the model runs smoothly on lightweight office notebooks without GPUs. Additionally, an image stitching algorithm that seamlessly stitches multiple images was proposed to generate high-quality panoramic views of bridges. The image stitching algorithm demonstrates robustness when applied to multiple images, successfully achieving stitching without visible seams or errors, providing efficient and reliable technical support for bridge panorama generation. The research outcomes demonstrate significant practical value in bridge inspection, providing robust technical support for safe and efficient bridge inspection. Moreover, our findings offer valuable references for future research and applications in related fields. Full article

Mortality studies comparing married men to never-married or formerly married men have consistently found that married men have a noticeable mortality advantage. This paper takes a novel perspective—examining mortality outcomes from the perspective of married men only and comparing those who coreside with any parents, in-laws, or their spouse only. The analyses use CenSoc data set, consisting of the 1940 Full Count United States Census linked to the Social Security Administration Death Master Files and includes 1.7 million married men between the ages of 21 and 45 years old residing with their spouse, and who died between 1975 and 2005. The results show that married men who live with only a spouse but no parental generations have an older age at death, and being a household head has an additional advantage. Living with either or both of their parents is associated with a reduction in life of 4 months, or 2 months for those who live with their in-laws. The conclusion reached is that longevity is associated with the possible burden of living with one’s parents, coupled with the reasons that may have led to the particular living arrangement. The effect of coresidence is, in turn, filtered through expectations about intergenerational relationships and norms regarding coresidence. The coresidence experience can become part of a trajectory, leading to declines in longevity. Full article

Background: Spinal cord stimulation (SCS) is an established therapy for chronic neuropathic pain. Although rechargeable and non-rechargeable pulse generators (PGs) are widely used, their real-world battery life and the influence of lead type on energy efficiency remain underexplored. Objective: To evaluate PG battery longevity and compare the performance of surgical versus percutaneous leads in terms of energy efficiency. Methods: We conducted a retrospective study of 283 PGs implanted at Hospital Virgen de las Nieves (Granada, Spain) from 1996 to 2023. Data on patient demographics, pain etiology, lead type and placement, stimulation modality, and PG status were extracted. A competing risks analysis was used to assess PG shutdown and early explantation over time. Results: Of the PGs analyzed, 43.5% were non-rechargeable and 56.5% rechargeable. Rechargeable PGs showed significantly longer battery life (mean: 82.7 vs. 38.9 months, p < 0.05), with a lower probability of shutdown at 50, 100, and 150 months. No significant differences in battery longevity were observed regarding lead location, stimulation type, or pain etiology. A trend toward longer battery life was observed with percutaneous leads, although not statistically significant. Conclusions: Rechargeable PGs demonstrated superior longevity compared to non-rechargeable models and should be considered the preferred option in most cases. While both surgical and percutaneous leads are effective, percutaneous systems may offer improved battery efficiency. Further prospective studies are warranted to confirm these findings and assess cost-effectiveness. Full article