The concept of a digital or virtual patient represents a paradigm shift in implant dentistry, transforming treatment planning into a data-driven, prosthetically guided, and patient-specific workflow. This article outlines the comprehensive process of constructing a digital patient by integrating multiple datasets: cone-beam computed tomography (CBCT) for volumetric bone representation, intraoral surface scans for dental and soft tissue geometry, facial scans for esthetic harmony, and jaw-motion tracking data for functional analysis. These datasets are merged through precise registration protocols using fiducial markers and AI-assisted alignment to create an accurate three-dimensional model reflecting both anatomical and functional dynamics. The resulting virtual patient enables prosthetically driven implant positioning, real-time occlusal simulations, and seamless communication between the surgical, prosthetic, and laboratory teams. Moreover, advances in artificial intelligence, cloud computing, and blockchain-based data security promise to expand the digital patient’s role from static documentation to a dynamic, continuously updated virtual twin. This integrated workflow enhances surgical precision, esthetic predictability, and clinical efficiency, marking a significant step toward fully digitized, personalized implant rehabilitation.

Accurate modeling of thermochemical conversion of carbonaceous particles is essential for predicting solid conversion behavior in high temperature industrial reactors. Numerical efficient 0D or 1D particle models are widely used in large-scale CFD simulations. They typically rely on simplifying assumptions regarding intra-particle heat and mass transfer and chemistry. In contrast, fully resolved 3D multi-region particle models capture detailed transport and reaction phenomena but are computationally expensive. In this study, we compare a 1D particle-resolved Lagrangian model with a detailed 3D multi-region model implemented in OpenFOAM to assess their predictive capabilities under realistic conditions. Three particle sizes and three conversion temperature profiles were analyzed. The comparison focuses on the temporal evolution of the conversion and the intra-particle states at 50% devolatilization and 50% burnout. The results indicate that the 1D and 3D model predict similar mean temperature profiles for most cases, while the mean conversion profiles differ. The results indicate that the 1D model results are biased by the employed sequential thermochemical conversion model for high temperature cases. Some of the differences might be also caused by the slightly inconsistent model settings between the 1D and 3D models. The more complex 3D model requires additional parameters and the devolatilization model from the 1D model is not supported by the 3D modeling framework. • Introduction of a 3D detailed particle model • Comparison of 1D and 3D particle models under realistic conversion conditions • Multi-scale evaluation of thermally thick particle behavior in 1D and 3D frameworks

Assessing the precision of 3D human model for forensic biomechanics application.

Visualizing intracellular and extracellular cell-mineral interactions in a three-dimensional breast tumor model.

Three-dimensional finite element (FE) models derived from Computed Tomography (CT) images predict hip fractures better than areal bone mineral density measurements from Dual-energy X-ray Absorptiometry (DXA). Yet, these results have not justified the adoption of CT in clinical practice, and only 2D DXA images are clinically available. Statistical shape and appearance models can be used to reconstruct three-dimensional FE models from 2D DXA images. While ex vivo validations have been performed on 3D reconstructed DXA-based FE models, it is not clear how well 3D reconstructed DXA-based FE models can predict fractures compared to CT-based models. The aim of this study was thus to evaluate the ability of one such methodology, namely DXA2FEM, to predict fractures in a clinical cohort of pair-matched fractured and control subjects, for whom both DXA and CT images were available. 3D FE models of the femur were built from both DXA and CT, and FE simulations were run reproducing a sideways fall in 28 different femoral configurations. An absolute risk of fracture (ARF0) was then computed based on the FE-predicted femoral strength values. DXA- and CT-derived models were compared with respect to geometry, density distribution, and FE-predicted proximal femoral strength. DXA-derived 3D FE models had an average point-to-surface distance of -2mm from CT-based models, whereas the Young's moduli were 29% higher. ARF0 by CT reported statistically significantly better diagnostic accuracy (0.83, 95% CI 0.75 to 0.91) than standard hip DXA (0.69, 95% CI 0.6 to 0.8) or FRAX (0.69, 95% CI 0.57 to 0.81). The diagnostic accuracy of ARF0 by DXA was between ARF0 by CT and standard hip DXA/FRAX (0.74, 95% CI 0.62 to 0.86), albeit neither difference was statistically significant in the analysed cohort.

To investigate the efficacy and safety of Mixed Reality (MR)-Assisted Thoracic Endovascular Aortic Repair (TEVAR). We retrospectively analyzed 46 patients with aortic dissection who underwent TEVAR. In the Control Group, Computed Tomography Angiography (CTA) was performed on the thoracic and abdominal aorta, after which surgery was performed based on traditional 2D imaging data. In the observation group, the Star Map HoloLens Image System was used for data processing and 3D modeling, and preoperative analysis and intraoperative path guidance were conducted with the MR Microsoft HoloLens Headset. The communication time, satisfaction, and anxiety after communication, as well as the operation duration, intraoperative blood loss, postoperative complications, and rehabilitation of these two groups were analyzed. This study aimed to evaluate the perioperative outcomes of MR-guided stent placement. A total of 46 patients were equally divided into the MR group and control group (n = 23 each), with data analyzed via non-parametric tests. Compared with the control group, the MR group exhibited significantly shorter operation duration (70.91 ± 8.533 vs. 77.48 ± 8.474 min, Z = -2.785, p = 0.005), fewer fluoroscopy times (3.74 ± 1.214 vs. 5.61 ± 1.530, Z = -3.813, p < 0.001), and less stent adjustments (1.65 ± 1.152 vs. 2.91 ± 1.411, Z = -2.765, p = 0.006), suggesting MR guidance may optimize perioperative efficiency. Multimodal MR has an important auxiliary role in patient education, surgical planning, and accurate positioning of the surgical approach.

Statins are widely prescribed to those with atherosclerosis to lower cholesterol and reduce cardiovascular risk, but their influence on plaque calcification remains unclear. While clinical data associate statin use with increased calcium scores and reduced cardiovascular events, their effect on rupture-prone microcalcifications has not been clinically assessed due to imaging limitations. In vitro studies report conflicting outcomes on statin-induced calcification in various cell types. To address this gap, we investigated the impact of atorvastatin on calcification across multiple plaque-relevant cell types using both monolayer cultures and a tissue-engineered 3D plaque model. Human mesenchymal stromal cells (MSCs) were isolated from iliac crest bone chips and differentiated into smooth muscle (mSMCs) cells using TGF-β1, while human vena saphena cells (HVSCs) were obtained from bypass surgery material. Monolayer cultures of MSCs, mSMCs, and HVSCs were exposed to calcifying medium with or without atorvastatin (0.1-1 μM) for 2 weeks. For the 3D model, cells were embedded in fibrin gels, cultured to form a collagenous matrix for 2 weeks, then calcified for an additional 2 weeks with or without atorvastatin (1-10 μM). In both monolayer and the 3D model, atorvastatin inhibited calcification in MSCs, while it induced calcification in mSMCs. For HVSCs, atorvastatin reduced calcification in 2D monolayer cultures, while it had no visible effect in 3D. This study highlights the cell type-specific effects of atorvastatin on calcification, underscoring the need to consider cellular heterogeneity when evaluating its impact on plaque stability.

The APOL1 gene variants G1 and G2 are associated with an increased risk of APOL1-mediated kidney disease. A recently identified variant, p.N264K (M1), mitigates this risk of renal damage by abolishing APOL1-G2's associated cytotoxicity. However, the molecular and structural basis of this protective effect remains incompletely understood. In this study, we first show that both the cytotoxic G2 and the nontoxic M1-G2 exhibit similar intracellular localization, surface expression, and turnover kinetics. Moreover, N-glycosylation assays indicated no differences in topology, and 3D models demonstrated that both cytotoxic G2 and nontoxic APOL1 M1-G2 span the membrane four times, forming a potential ion channel. Interestingly, molecular dynamics analyses of a computational APOL1 3D model further revealed that in case of M1, the lysine at position 264 occludes this channel, thereby preventing ion pore activity of APOL1. These findings provide, for the first time, a mechanistic explanation for the nontoxic behavior of the APOL1 M1-G2 variant. Additional 3D analyses suggest that the C-terminal region may contribute to APOL1 multimerization, potentially influencing ion flux and cytotoxicity.

Integrating 3D Point Cloud analysis for potentially unstable rock blocks characterization: a method for assessing size and shape distribution

The sella turcica is a depression located on the sphenoid bone at the base of the skull that houses the pituitary gland. The morphological characteristics of this region provide important insights into growth and development, endocrine system functions and the evaluation of various pathologies. This study aimed to evaluate morphological differences in the sella turcica between male and female Romanov sheep using three-dimensional geometric morphometric methods. A total of 20 Romanov sheep specimens (10 males and 10 females) were analysed. Thirteen anatomical landmarks were identified on three-dimensional models and processed using the software 3D Slicer. The resulting landmark coordinates were statistically analysed using PAST to test sexual shape differences. Shape variations were mainly associated with differences in the depth and contour of the fossa hypophysialis and the rostral and caudal clinoid processes. Male specimens exhibited a deeper and longer sella turcica, whereas female specimens showed a wider and shallower morphology. Statistical analysis revealed that these sexual shape differences were significant (p < 0.001). Geometric morphometric analysis demonstrated that the sella turcica exhibits marked sex-related shape variations. These anatomical differences may provide valuable reference data for clinical, zooarchaeological, forensic and anthropological studies aimed at identifying sex-related morphological traits.

This study presents a multi-step approach to design and evaluate the cooling architecture of an actively cooled probe nacelle suitable for high-temperature supersonic flows. First, a 1D heat transfer model was used to determine the coolant pressure required for thermal protection of the nacelle at supersonic conditions. It incorporates conductive-convective heat transfer, effusion cooling, leading-edge effects, and high-speed boundary layer effects. A parametric analysis identified a minimum coolant pressure of 2.4 bar to satisfy the temperature limits of the nacelle at the most severe conditions of M 1 = 6 , T 01 = 1700 K . 3D RANS simulations were utilized to assess the accuracy of the 1D model giving average deviations in adiabatic cooling effectiveness and heat transfer coefficient below 6% and 15% respectively. Finally, the cooling performance of the nacelle was assessed in a transonic open jet. Cooling effectiveness was measured with high-resolution infrared thermography, and heat flux was measured with high-frequency Atomic Layer Thermopiles (ALTP). Uncertainties in cooling effectiveness and heat transfer coefficient were evaluated through Taylor propagation and Monte Carlo simulations, respectively. Oil-flow visualization was conducted to compare the surface flow behavior in the effusion cooled face between simulations and experiments, while Schlieren was used to compare the bow shock location and shape. A comprehensive comparison is conducted involving analytical models, simulations and experiments that validate the proposed methodology. • First unified 1D 3D experimental methodology for supersonic cooled-probe design. • Actively cooled probe enables optical tests from transonic to Mach 6 and 1700 K. • IR, thermopile, schlieren, and oil tests link heat flux, cooling, and flow topology. • 1D and 3D models agree within 15% for HTC and 7% for cooling effectiveness.

Continuous evolving humanoid for advanced cellular models.

Thermokinetic parameters of vitamin C and total carotenoids in carrot: Prediction and validation of their retention via 3D finite element modelling

Advances in rodent oligodendrocyte precursor cells isolation and culture: From traditional methods to modern approaches.

Detecting deepfake videos remains a challenging task, especially in scenarios involving unknown manipulation methods or unseen data distributions. Most existing video deepfake detection methods rely on high-level semantic features, which often lead to overfitting of facial identity information and poor transferability. In this work, we explore a novel perspective by modeling videos through 3D differential operations along temporal and spatial dimensions. To exploit the spatial–temporal variation information of the video content, the proposed approach decomposes videos into single-axis 1D differential signals, which are then transformed into 2D representations for efficient learning. This procedure enables the use of lightweight 2D CNNs while retaining directional forgery cues. Our experiments, aimed at analyzing whether these differential signals capture discriminative patterns useful for distinguishing real from fake content, show that the proposed method achieves strong intra-dataset performance and reveals complementary information across dimensions. These findings suggest that differential signals could potentially support generalization when integrated into broader detection frameworks. • We propose 3D Differential Decomposition modeling for deepfake video detection. • Multi-directional and multi-order differential operation are considered. • Optimization for differential order selection and fusion strategy are explored.

Double-pipe heat exchangers (DPHEs) are vital in industrial applications, and improving their performance is crucial for sustainability. This study uses three-dimensional Computational Fluid Dynamics (CFD) simulations to investigate the impact of passive flow modifications, specifically geometrically spaced and perforated ring inserts, on heat transfer and pressure drop in a DPHE. The research involved developing a 3D numerical model whose accuracy was ensured through a comprehensive mesh independence study and rigorous validation against established empirical correlations and experimental data. Subsequent simulations explored the influence of geometric spacing ( G -factor) and the number of perforations per ring. Results demonstrated that for unperforated rings P = 0 , uniform spacing maximised heat transfer, reaching a Nusselt number of 177.4 at a Reynolds number of 12,000. In contrast, strongly biased configurations exhibited superior overall performance by balancing thermal enhancement with hydraulic losses. These biased cases achieved a Performance Evaluation Criterion (PEC) of 1.065, equivalent to a 6.5% improvement compared with the uniform arrangement. The introduction of perforations significantly altered performance; a four-hole configuration with G = 1 . 00 consistently achieved the highest heat transfer and overall performance, with the Nusselt number rising to 195.8 and the PEC reaching 1.176, indicating an optimal balance between fluid mixing and flow resistance. By comparison, increasing the number of perforations further to eight reduced the pressure drop from 171 . 9 Pa for solid rings to 132 . 0 Pa , but had a less pronounced positive impact on heat transfer performance. For this configuration, the Nusselt number remained close to that of the unperforated case. Analysis of both turbulent kinetic energy (TKE) and velocity vector fields provided critical insights into the underlying mechanisms, illustrating how ring geometry and perforations disrupt boundary layers and generate beneficial turbulence. Furthermore, regression-based multivariate correlations for both the Nusselt number and friction factor were formulated as functions of Reynolds number, G -factor, and porosity. Validation against the full set of 75 CFD simulation cases demonstrated high accuracy, with 96% of the correlation-predicted Nusselt numbers deviating by less than ± 5 % from the corresponding CFD results, and the equivalent friction factor values deviating by less than ± 10 % . • Non-uniform ring spacing significantly affects DPHE thermo-hydraulic behaviour. • Four-hole perforated rings provide the best heat-transfer and pressure balance. • Strongly biased ring spacing yields higher overall PEC than weakly biased layouts. • CFD reveals mixing patterns driven by combined spacing and perforation effects. • Correlations predict Nusselt number and friction factor for 75 DPHE cases.

Lumican-mediated fibroblast differentiation in skin fibrosis.

Basement strike-slip fault controls on parallel and evenly-spaced Riedel shears and ore bodies – insights from 3D discrete element modeling

DivineTree: All-in-one 3D tree modeling with diverse and fused visual guidance

Clay's solid-fluid phase transition, a key cause of geohazards like landslides and debris flows, remains notoriously difficult to model due to its coupled frictional yielding and strain-rate-dependent fluidization. Its complexity poses a substantial challenge to constitutive modeling. For the first time, this study proposes a novel critical-state hydrodynamic model (CSHM), which efficiently captures clay's nonlinear solid-fluid phase transition by integrating quasi-static and viscous stress components in a unified framework. The quasi-static stress is described by a critical-state-based elastoplastic model, representing the solid-like behavior. In contrast, the viscous stress is described using a novel hydrodynamics-based rheological model that captures the fluid-like behavior by introducing a state variable termed “clay temperature”. The quasi-static component captures key aspects including nonlinear elasticity, stress dilatancy, and critical state, whereas the proposed viscous component describes shear-heating or shear-cooling rheology. Subsequently, extensive element simulations are employed to evaluate the new CSHM. Finally, validation against experimental data demonstrates that the CSHM accurately captures the clay's solid-to-fluid phase transition. The analyses reveal that: (i) While sand undergoes a shear-induced heating phase transition and is well described by the existing kinetic theory, clay exhibits shear-cooling, which our novel model accurately captures. (ii) Clay's phase transition is characterized by two transitional points (critical-state point and viscous-stress-dominant point) and three different regimes (solid-like, transitional, and fluid-like). (iii) Unlike the traditional HB model, a 2D model describing stress in the fluid-like state, the CSHM is a 3D full-range phase transition model that captures evolution from initial to critical state, and eventually fluid-like state. • Proposes critical-state hydrodynamic model for clay's solid-fluid phase transition. • CSHM integrates critical-state elastoplasticity (solid) and hydronhamics (fluid). • Proposes novel hydrodynamic model with ‘clay temperature’ for viscous stress. • Seamlessly bridges solid and fluid states via critical-state and clay temperature. • Comparison with experimental results confirm the model's accuracy.