Search Results (212)

In this study, the influence of the electrochemical oxidation process on Ti-Grad 23 alloy (Ti6Al4V ELI) in 1 M H₃PO₄, under applied voltages between 200 and 275 V, at a constant time of 1 min, is analyzed. The structural, morphological, and wettability properties of the TiO₂ anodic layers obtained were investigated by X-ray diffraction (XRD), energy dispersive electron microscopy (SEM-EDS), contact angle measurements, and chemical corrosion. XRD analysis showed the development and intensification of anatase and brookite phases, with increased crystallite size after electrochemical oxidation. SEM/EDS characterization confirmed the formation of an inhomogeneous porous TiO₂ layer, with pore diameters ranging from 98 to 139 nm and a significant increase in oxygen content. Contact angle measurements demonstrate enhanced hydrophilicity for all oxidized samples, with progressively lower values as the applied voltage increased. Chemical corrosion tests in Ringer solution and Ringer + 40 g/L H₂O₂ indicated that oxidized surfaces maintain structural stability in physiological media, whereas exposure to oxidizing environments induces partial pore closure and crack formation due to localized corrosion. The optimal anodizing condition was identified at 200 V for 1 min, yielding a uniform distribution of pores and improved morpho-functional characteristics suitable for biomedical applications. The optimal electrochemical oxidation conditions were identified at 200 V for 1 min, ensuring a uniform pore distribution. Full article

Chronic kidney disease (CKD) impacts more than 850 million people globally, yet existing machine learning methodologies for risk stratification encounter substantial challenges: computationally intensive hyperparameter tuning, model opacity that conflicts with clinical interpretability standards, and class imbalance leading to systematic prediction bias. We constructed an integrated architecture that combines XGBoost with Optuna-driven Bayesian optimization, evaluated against 19 competing hyperparameter tuning approaches and tested on CKD patients using dual-paradigm statistical validation. The architecture delivered 93.43% accuracy, 93.13% F1-score, and 97.59% ROC-AUC—representing gains of 6.22 percentage points beyond conventional XGBoost and 7.0–26.8 percentage points compared to 20 baseline algorithms. Tree-structured Parzen Estimator optimization necessitated merely 50 trials compared to 540 for grid search and 1069 for FLAML, whereas Boruta feature selection accomplished 54.2% dimensionality reduction with no performance compromise. Over 30 independent replications, the model exhibited remarkable stability (cross-validation standard deviation: 0.0121, generalization gap: −1.13%) alongside convergent evidence between frequentist and Bayesian paradigms (all p < 0.001, mean CI-credible interval divergence < 0.001, effect sizes d = 0.665–5.433). Four separate explainability techniques (SHAP, LIME, accumulated local effects, Eli5) consistently identified CKD stage and albumin-creatinine ratio as principal predictors, aligning with KDIGO clinical guidelines. Clinical utility evaluation demonstrated 98.4% positive case detection at 50% screening threshold alongside near-optimal calibration (mean absolute error: 0.138), while structural equation modeling revealed hyperuricemia (β = −3.19, p < 0.01) as the most potent modifiable risk factor. This dual-validated architecture demonstrates that streamlined hyperparameter optimization combined with convergent multi-method interpretability enables precise CKD risk stratification with clinical guideline alignment, supporting evidence-informed screening protocols. Full article

Real-world decision-making often involves uncertainty, incomplete data, and the need to evaluate alternatives based on both quantitative and qualitative criteria. To address these challenges, this study presents FAS-XAI, a unified methodological framework that integrates fuzzy clustering and explainable artificial intelligence (XAI). FAS-XAI supports interpretable, data-driven decision-making by combining three key components: fuzzy clustering to uncover latent behavioral profiles under ambiguity, supervised prediction models to estimate decision outcomes, and expert-guided interpretation to contextualize results and enhance transparency. The framework ensures both global and local interpretability through SHAP, LIME, and ELI5, placing human reasoning and transparency at the center of intelligent decision systems. To demonstrate its applicability, FAS-XAI is applied to a real-world B2B customer service dataset from a global ERP software distributor. Customer engagement is modeled using the RFID approach (Recency, Frequency, Importance, Duration), with Fuzzy C-Means employed to identify overlapping customer profiles and XGBoost models predicting attrition risk with explainable outputs. This case study illustrates the coherence, interpretability, and operational value of the FAS-XAI methodology in managing customer relationships and supporting strategic decision-making. Finally, the study reflects additional applications across education, physics, and industry, positioning FAS-XAI as a general-purpose, human-centered framework for transparent, explainable, and adaptive decision-making across domains. Full article

Laser-driven ion acceleration in dense, hydrogen-rich media can be significantly enhanced by embedding metallic nanoantennas that support localized surface plasmon (LSP) resonances. Using large-scale particle-in-cell (PIC) simulations with the EPOCH code, we investigate how nanoantenna geometry and laser pulse parameters influence proton acceleration in gold-doped polymer targets. The study covers dipole, crossed, and advanced 3D-cross antenna configurations under laser intensities of 10¹⁷–10¹⁹ W/cm² and pulse durations from 2.5 to 500 fs, corresponding to experimental conditions at the ELI laser facility. Results show that the dipole antennas exhibit resonance-limited proton energies of ~0.12 MeV, with optimal acceleration at the intensities 4 × 10¹⁷–1 × 10¹⁸ W/cm² and pulse durations around 100–150 fs. This energy is higher by roughly three orders of magnitude than the proton energy for the same field and same polymer without dopes: ~1–2 × 10⁻⁴ MeV. Crossed antennas achieve higher energies (~0.2 MeV) due to dual-mode plasmonic coupling that sustains local fields longer. Advanced 3D and Yagi-like geometries further enhance field localization, yielding proton energies up to 0.4 MeV and larger high-energy proton populations. For dipole antennas, experimental data from ELI exists and our results agree with it. We find that moderate pulses preserve plasmonic resonance for longer and improve energy transfer efficiency, while overly intense pulses disrupt the resonance early. These findings reveal that plasmonic field enhancement and its lifetime govern energy transfer efficiency in laser–matter interaction. Crossed and 3D geometries with optimized spacing enable multimode resonance and sequential proton acceleration, overcoming the saturation limitations of simple dipoles. The results establish clear design principles for tailoring nanoantenna geometry and pulse characteristics to optimize compact, high-energy proton sources for inertial confinement fusion and high-energy-density applications. Full article

This review examines the role of differential forms, Pfaffian systems, and hypersurfaces in general relativity. These mathematical constructions provide the essential tools for general relativity, in which the curvature of spacetime—described by the Einstein field equations—is most elegantly formulated using the Cartan calculus of differential forms. Another important subject in this discussion is the notion of conformal geometry, where the relevant invariants of a metric are characterized by Élie Cartan’s normal conformal connection. The previous analysis is then used to develop the null surface formulation (NSF) of general relativity, a radical framework that postulates the structure of light cones rather than the metric itself as the fundamental gravitational variable. Defined by a central Pfaffian system, this formulation allows the entire spacetime geometry to be reconstructed from a single scalar function, Z, whose level surfaces are null. Full article

The influence of electron beam melting (EBM) scan speed on the corrosion, nano-biotribological, and cellular adhesion properties of Ti-6Al-4V-ELI (extra low interstitials) was systematically investigated. Specimens were fabricated using five different scanning speeds, and tribological performance was assessed via reciprocating dry wear tests, while corrosion behaviour was evaluated through monitoring the open circuit potential and anodic potentiodynamic polarization tests in Ringer’s solution. Human fibroblasts from the FN1 cell line were used to assess cell adhesion. Specimens produced using scanning speeds of 4530 mm·s⁻¹ and 4983 mm·s⁻¹ exhibited increased passive current densities, indicating reduced corrosion protection, although all surfaces maintained the passive film characteristic. Tribological behaviour was strongly dependent on scan speed, with wear rate and penetration depth increasing at higher speeds; notably, an intermediate scan speed produced a surface with minimal wear and penetration depth despite a wide wear track, suggesting enhanced resistance to tribological degradation. Fibroblast cultures demonstrated robust adhesion and spindle-shaped morphology across all samples, with the disk produced using a scanning speed of 4983 mm·s⁻¹ showing the highest surface coverage, highlighting the role of EBM process parameters in modulating surface properties relevant to cell–biomaterial interactions. These findings underscore the critical influence of scan speed on the multifunctional performance of Ti-6Al-4V-ELI for biomedical applications. Full article

The detection of exoplanets in space-based photometry relies on identifying periodic transit signatures in stellar light curves. The Kepler Threshold Crossing Events (TCE) catalog collects all periodic dimming signals detected by the pipeline, while the Kepler Objects of Interest (KOI) catalog provides vetted dispositions (CONFIRMED, CANDIDATE, FALSE POSITIVE). However, the pathway from raw TCE detections to KOI classifications remains ambiguous in many borderline cases. We introduce FAS-XAI, a framework that integrates Fuzzy C-Means (FCM) clustering, supervised learning, and explainable AI (XAI) to improve transparency in exoplanet candidate classification. FCM applied to TCE parameters (period, duration, depth, and SNR) reveals three meaningful regimes in the transit-signal space and quantifies ambiguity through fuzzy memberships. Linking these clusters to KOI dispositions highlights a progressive consolidation of confirmed planets within the high-SNR, medium-duration regime. A supervised XGBoost classifier trained on KOI labels and augmented with fuzzy memberships achieves strong performance (Accuracy = 0.73, Macro F1 = 0.69, ROC–AUC = 0.855), clearly separating CONFIRMED and FALSE POSITIVE objects while appropriately reflecting the transitional nature of CANDIDATES. SHAP, LIME, and ELI5 provide consistent global and local attributions, identifying period, duration, depth, SNR, and fuzzy ambiguity as the key explanatory features. Finally, stellar parameters from Kepler DR25 validate the physical plausibility of the detected regimes, demonstrating that FAS-XAI captures astrophysically meaningful patterns rather than purely statistical structures. Overall, the framework illustrates how fuzzy logic and explainable AI can jointly enhance the interpretability and scientific rigor of exoplanet vetting pipelines. Full article

Moss in container seedling nurseries competes with seedlings for water and nutrients while blocking light, thereby inhibiting growth. This study aimed to address this issue by evaluating the moss control efficacy of 11 chemical compounds, including terpinyl acetate (TA), limonene, and Hinoki essential oil (HEO). The plate experiment results led to the selection of 6 substances (TA, limonene, HEO, pine leaf extract, baking soda, pelargonic acid) that stably controlled both Polytrichum commune Hedw. and Marchantia. Polymorpha L. When TA, limonene, and HEO were combined with surfactants, moss control rates increased and showed stable performance. In the container seedling experiment, TA, limonene, and HEO demonstrated high moss control effects while exhibiting low growth inhibition. When these three substances were combined with surfactants, the electrolyte leakage index (ELI) decreased, indicating minimal cell membrane damage. Additionally, TA treatment maintained stable soil physicochemical properties with no significant changes in pH or nutrient levels. Microscopic analysis of moss cells showed cell wall deformation and expansion of intercellular spaces in the three substance treatment groups. Future verification of long-term effectiveness, expansion of application targets, and assessment of economic feasibility could lead to the development of eco-friendly moss removal agents for improving container seedling quality. Full article

Nicotinamide N-methyltransferase (NNMT) enzyme catalyzes the N-methylation of nicotinamide and its overexpression has been reported in many neoplasms, favoring traits featuring an aggressive tumor cell phenotype. Our recent data demonstrated that NNMT upregulation in osteosarcoma (OS) and Merkel cell carcinoma (MCC) led to a significant increase in cell proliferation and migration ability, together with a reduction in sensitivity to chemotherapeutic treatment. Based on these findings, we investigated the impact of small molecule NNMT inhibitors 5-amino-1-methyl quinolinium (5-AMQ), 6-methoxynicotinamide (6MeONa) and Eli Lilly’s pyrimidine 5-carboxamide (EL-1) on U-2 OS and Saos-2 OS cell lines and MCC13 and MCC26 MCC cell lines. Following incubation of the cells with these compounds, cell viability, reactive oxygen species (ROS) production and apoptosis induction were evaluated. Cells were then subjected to combined treatment with inhibitors and cisplatin (CDDP), and viability and ROS levels were further analyzed. Our results clearly illustrate that cells treated with NNMT inhibitors underwent significant reductions in viability, increased ROS production and activation of apoptotic pathways. Given the association of NNMT with cancer aggressiveness, inhibiting its catalytic activity might present a novel strategy for counteracting cancer growth and chemoresistance, providing the rationale for an effective anti-cancer therapy based on the use of specific NNMT inhibitors. Full article

Background: The implant–abutment interface has been thoroughly examined due to its impact on the success of implant healing and longevity. Removing the abutment is advantageous, but it changes the biomechanics of the implant fixture and restoration. This in vitro three-dimensional finite element analytical (FEA) study aims to evaluate the distribution of von Mises stress (VMS) in abutment-free and three additional implant abutment connections composed of various titanium alloys. Materials and methods: A three-dimensional implant-supported single-crown prosthesis model was digitally generated on the mandibular section using a combination of microcomputed tomography imaging (microCT), a computer-assisted designing (CAD) program (SolidWorks), Analysis of Systems (ANSYS), and a 3D digital scan (Visual Computing Lab). Four digital models [A (BioHorizons), B (Straumann AG), C abutment-free (Matrix), and D (TRI)] representing three different functional biomaterials [wrought Ti-6Al-4Va ELI, Roxolid (85% Ti, 15% Zr), and Ti-6Al-4V ELI] were subjected to simulated static/cyclic static loading in axial/oblique directions after being restored with highly translucent monolithic zirconia restoration. The stresses generated on the implant fixture, abutment, crown, screw, cortical, and cancellous bones were measured. Results: The highest VMSs were generated by the abutment-free (Model C, Matrix) implant system on the implant fixture [static (32.36 Mpa), cyclic static (83.34 Mpa)], screw [static (16.85 Mpa), cyclic static (30.33 Mpa), oblique (57.46 Mpa)], and cortical bone [static (26.55), cyclic static (108.99 Mpa), oblique (47.8 Mpa)]. The lowest VMSs in the implant fixture, abutment, screw, and crown were associated with the binary alloy Roxolid [83–87% Ti and 13–17% Zr]. Conclusions: Abutment-free implant systems generate twice the stress on cortical bone than other abutment implant systems while producing the highest stresses on the fixture and screw, therefore demanding further clinical investigations. Roxolid, a binary alloy of titanium and zirconia, showed the least overall stresses in different loadings and directions. Full article

Over the past decade, cellular immunotherapy has emerged as a transformative strategy for non-small cell lung cancer (NSCLC), with dendritic-cell (DC) vaccines, T-cell vaccines, and natural killer (NK)-cell therapies demonstrating distinct mechanisms and clinical potential. DC vaccines capitalize on antigen presentation to prime tumor-specific T-cell responses, showing excellent safety profiles limited mainly to injection-site reactions and flu-like symptoms. While monotherapy has shown limited efficacy, combinations with checkpoint inhibitors or chemotherapy enhance immune activation and survival outcomes. Recent innovations, including neoantigen-loaded, mRNA-electroporated, and exosome-pulsed DCs, demonstrate improved immunogenicity and personalized approaches. T-cell vaccines, designed to activate cytotoxic CD8+ T-cell responses, have been tested across multiple platforms, including peptide-based (MAGE-A3), viral vector (TG4010/MUC1), and mRNA (CV9201/92) formulations. While the phase III MAGRIT trial presented no disease-free survival (DFS) benefit with adjuvant MAGE-A3 vaccination, the TG4010 vaccine improved progression-free survival (PFS; HR 0.66) and overall survival (OS; HR 0.67) in MUC1-positive NSCLC when combined with chemotherapy. Current strategies focus on personalized neoantigen vaccines and KRAS-targeted approaches (e.g., ELI-002), with ongoing phase III trials evaluating their potential in resectable NSCLC. NK-cell therapies have also shown promise, with early trials establishing the feasibility of autologous and allogeneic infusions, while engineered CAR-NK cells enhance tumor-specific targeting. Combination strategies with checkpoint inhibitors significantly improve response rates and PFS, revealing synergies between innate and adaptive immunity. Recent advances include cytokine-enhanced, memory-like NK cells to overcome immunosuppression and “off-the-shelf” products for broader clinical use. Together, these cellular immunotherapies represent a versatile and evolving frontier in NSCLC treatment, with ongoing research optimizing combinations, delivery platforms, and patient selection to maximize therapeutic benefit. Full article

This work presents a non-destructive methodology to estimate the residual porosity and mechanical properties of titanium foams produced via Hot Isostatic Pressing (HIP) followed by solid-state foaming (SSF). Pulsed laser-spot thermography was employed to measure thermal diffusivity in compact and foamed Ti6Al4V-ELI samples derived from powders of different granulometries. A power-law correlation between thermal diffusivity and porosity was used to estimate post-foaming porosity, which was then used to predict elastic modulus, yield strength, and ultimate tensile strength. Results highlight the potential of thermal diffusivity as a reliable indicator of structural performance, offering a rapid and fully non-destructive route for evaluating metallic foams in biomedical and aerospace applications. Full article

Artificial intelligence (AI) is emerging as a valuable complementary tool in small-molecule drug discovery, augmenting traditional methodologies rather than replacing them. This review examines the evolution of AI from early rule-based systems to advanced deep learning, generative models, diffusion models, and autonomous agentic AI systems, highlighting their applications in target identification, hit discovery, lead optimization, and safety prediction. We present both successes and failures to provide a balanced perspective. Notable achievements include baricitinib (BenevolentAI/Eli Lilly, an existing drug repurposed through AI-assisted analysis for COVID-19 and rheumatoid arthritis), halicin (MIT, preclinical antibiotic), DSP-1181 (Exscientia, discontinued after Phase I), and ISM001-055/rentosertib (Insilico Medicine, positive Phase IIa results). However, several AI-assisted compounds have also faced challenges in clinical development. DSP-1181 was discontinued after Phase I, despite a favorable safety profile, highlighting that the acceleration of discovery timelines by AI does not guarantee clinical success. Despite progress, challenges such as data quality, model interpretability, regulatory hurdles, and ethical concerns persist. We provide practical insights for integrating AI into drug discovery workflows, emphasizing hybrid human-AI approaches and the emergence of agentic AI systems that can autonomously navigate discovery pipelines. A critical evaluation of current limitations and future opportunities reveals that while AI offers significant potential as a complementary technology, realistic expectations and careful implementation are crucial for delivering innovative therapeutics. Full article

Background: Mandibular defects caused by trauma or tumor resection pose significant challenges in both functional and aesthetic reconstruction. Additive manufacturing (AM) technologies offer promising solutions for surgical planning and personalized treatment. Objectives: This review aims to evaluate current trends in the application of AM technologies for mandibular resection and reconstruction, with a particular focus on material selection, clinical integration, and technology-specific advantages. Methods: A structured literature review was performed using PubMed, Scopus, Web of Science, and Google Scholar. Studies published between January 2020 and May 2025 were screened using the following inclusion criteria: original peer-reviewed English-language research involving AM in mandibular surgery. The exclusion criteria included review articles, non-English sources, and non-mandibular studies. A total of 77 studies met the inclusion criteria and were analyzed in this review. Results: Based on the literature review conducted from 2020 to 2025, the most common restorative methods for the mandible using additively manufactured models include reconstruction with a titanium surgical plate bent to the curvature of the edges and angle of the mandible or a personalized titanium or PEEK surgical plate made directly based on the patient’s diagnosis. Implants made of Ti-6AL-4V ELI and bioceramic scaffolds are also used in the reconstruction process. They are developed based on patient diagnostic data and effectively replace the loss of mandibular bone structure. In addition, based on models and surgical guides created using additive manufacturing techniques, the performance of autogenous grafts from the fibula or iliac crest has improved significantly when used with a titanium implant plate. Conclusions: Additive manufacturing supports highly personalized and accurate mandibular reconstruction. The advantages of these methods include a reduced overall duration of procedures, a lower health risk for patients due to less reliance on general anesthesia, a near perfect match between the implant and the remaining hard tissues, and satisfactory aesthetic outcomes. However, success depends on the appropriate selection AM technology and material, particularly in load-bearing applications. Full article

Sequential drought and heat stress pose a growing threat to forest ecosystems in the context of climate change, yet systematic evaluation methods for woody plants remain limited. This study aimed to develop a comprehensive screening platform for identifying woody plant species tolerant to sequential drought and heat stress among 27 native species growing in Korea. A sequential stress protocol was applied: drought stress for 2 weeks, followed by high-temperature exposure at 45 °C. Physiological indicators, including relative water content (RWC) and electrolyte leakage index (ELI), were used for preliminary screening, supported by phenotypic observations, Evans blue staining for cell death, and DAB staining to assess oxidative stress and recovery ability. The results revealed clear differences among species. Chamaecyparis obtusa, Quercus glauca, and Q. myrsinaefolia exhibited strong tolerance, maintaining high RWC and low ELI values, while Albizia julibrissin was highly susceptible, showing severe membrane damage and low survival. DAB staining successfully distinguished tolerance levels based on oxidative recovery. Additional species such as Camellia sinensis, Q. acuta, Q. phillyraeoides, Q. salicina, and Ternstroemia japonica showed varied responses: Q. phillyraeoides demonstrated high tolerance, T. japonica showed moderate tolerance, and Q. salicina was relatively sensitive. The integrated screening system effectively differentiated tolerant species through multiscale analysis—physiological, cellular, and morphological—demonstrating its robustness and applicability. This study provides a practical and reproducible framework for evaluating sequential drought and heat stress in trees and offers valuable resources for urban forestry, reforestation, and climate-resilient species selection. Full article