3D Model Research Articles

Minimal Detectable Bone Fracture Gaps in CT Images and Digital Three-Dimensional (3D) Radii Models.

Knowledge of the minimal detectable bone fracture gap is essential in three-dimensional (3D) models, particularly in pre-operative planning of osteosynthesis to avoid overlooking gaps. In this study, defined incisions and bony displacements ranging from 100 to 400 µm were created in diaphyseal radii in 20 paired forearm specimens and verified with light microscopy. The specimens were scanned utilizing different computed tomography (CT) technologies/scanners, specimen positionings, scan protocols, image segmentations, and processing protocols. Inter- and intra-operator variabilities were reported as coefficient kappa. In CT images, fracture gaps of 100 µm and bone lamellae of 300 µm and 400 µm width were identified at a rate of 80 to 100%, respectively, independent of the investigated settings. In contrast, only 400µm incisions and bony displacements were visible in digital 3D models, with detection rates dependent on CT technology, image segmentation, and post-processing algorithm. 3D bone models based on state-of-the-art CT imaging can reliably visualize clinically relevant bone fracture gap sizes. However, verification of fractures to be surgically addressed should be verified with the original CT image series.

Impact of Cyclic Strain on Elastin Synthesis in a 3D Human Myometrial Culture Model.

The synthesis and assembly of mature, organized elastic fibers remains a limitation to the clinical use of many engineered tissue replacements. There is a critical need for a more in-depth understanding of elastogenesis regulation for the advancement of methods to induce and guide production of elastic matrix structures in engineered tissues that meet the structural and functional requirements of native tissue. The dramatic increase in elastic fibers through normal pregnancy has led us to explore the potential role of mechanical stretch in combination with pregnancy levels of the steroid hormones 17β-estradiol and progesterone on elastic fiber production by human uterine myometrial smooth muscle cells in a three-dimensional (3D) culture model. Opposed to a single strain regimen, we sought to better understand how the amplitude and frequency parameters of cyclic strain influence elastic fiber production in these myometrial tissue constructs (MTC). Mechanical stretch was applied to MTC at a range of strain amplitudes (5%, 10%, and 15% at 0.5 Hz frequency) and frequencies (0.1 Hz, 0.5 Hz, 1 Hz, and constant 0 Hz at 10% amplitude), with and without pregnancy-level hormones, for 6 days. MTC were assessed for cell proliferation, matrix elastin protein content, and expression of the main elastic fiber genes, tropoelastin (ELN) and fibrillin-1 (FBN1). Significant increases in elastin protein and ELN and FBN1 mRNA were produced from samples subjected to a 0.5 Hz, 10% strain regimen, as well as samples stretched at higher amplitude (15%, 0.5 Hz) and higher frequency (1 Hz, 10%); however, no significant effects because of third-trimester mimetic hormone treatment were determined. These results establish that a minimum level of strain is required to stimulate the synthesis of elastic fiber components in our culture model and show this response can be similarly enhanced by increasing either the amplitude or frequency parameter of applied strain. Further, our results demonstrate strain alone is sufficient to stimulate elastic fiber production and suggest hormones may not be a significant factor in regulating elastin synthesis. This 3D culture model will provide a useful tool to further investigate mechanisms underlying pregnancy-induced de novo elastic fiber synthesis and assembly by uterine smooth muscle cells.

Disassembling the components of virtual clothing presentation: exploring their impact on consumers' perception and purchase intention

PurposeVirtual clothing presentation has a visual 3D effort and allows consumers to interact. Currently, most scholars make virtual clothing presentations as a whole or focus on one element to study its impact on consumers’ purchase intentions. This study disassembles the components of virtual clothing presentation in Taobao and explores how each component (virtual clothing, virtual model, presentation space, presentation technology and system quality) affects consumers’ purchase intention, which can provide clothing companies recommendations for developing it and help improve consumers’ online shopping experience.Design/methodology/approachThis study created the parts of a virtual clothing presentation and took advantage of Taobao’s 3D interactive module to simulate a shopping scenario. Participants experienced a 3D interactive virtual clothing presentation in which they could change clothing colors, show actual clothing sizes, try different model poses, switch presentation backgrounds and unfold clothing structure through interactive buttons. Then they were randomly assigned to view two kinds of images and videos of experiment clothing (real images and videos vs virtual ones), respectively. Hypotheses were tested using SEM and applying SmartPLS 4.FindingsThe results demonstrated that five components of virtual clothing presentation have different degrees of influence on consumers’ purchase intention through different consumer perceptions (perceived usefulness, ease of use and enjoyment). It is necessary to consider the design of the virtual clothing presentation in those five dimensions for different needs. In addition, it is feasible to replace images and animated videos of real clothing with virtual ones in Taobao.Originality/valueDifferent types of virtual clothing presentations can lead to various results in terms of diverse impacts. This study disassembles and researches each component of a virtual clothing presentation. Overall, this study could provide guidance and suggestions for clothing companies to develop and design or invest in virtual clothing presentations.

Wear simulation of UHMWPE against the different counterface roughness in reciprocating unidirectional sliding motion

Wear simulations of UHMWPE can economically and conveniently predict the performance of wear resistant bushings used for sealing or other reciprocating unidirectional sliding motion. In this study, pin on plate tribological experiments and microscopic analysis was done to obtained the wear profiles, wear volume and wear mechanism of UHMWPE against the counterface with different surface roughness of which Ra range is 0.03 ~ 2 μm. Meanwhile, the 3D wear simulation model of the pin on plate tribological experiments was established to discuss the adaptability of the energy and Archard wear model by analyzing the difference of wear profiles and wear volume between the experiment and simulation. The results indicate that with an increase in the counterface roughness, the wear simulation of UHMWPE estimated by the energy model were more accurate in reciprocating unidirectional sliding motion.

Development of performance analysis model with numerical and dynamic energy modeling for an integrated PVT-HP system

This study delivers a comprehensive numerical analysis of an integrated photovoltaic/thermal-heat pump (PVT-HP) system, underscored by an innovative three-dimensional thermal energy storage (TES) model. Addressing the limitations of conventional one-dimensional TES models, which struggled with accurately simulating horizontal flows and the fluid state at various facility inlets, this research marks a significant advancement. Our development of a 3D TES model optimizes finite elements to reduce computation time and enhance accuracy, vital for precise energy analysis in buildings and air conditioning systems. The integration of this model with a network model allows for detailed analysis of flow rate changes and their impacts on heat transfer, crucial for the integrated PVT-HP system. Key findings include a 30 % increase in the temperature difference between the top and bottom layers of the TES when the flow rate is reduced from 50 LPM to 20 LPM, and a 1 % decrease in the heat pump's coefficient of performance (COP) with a 10 LPM reduction in flow rate. The study emphasizes that managing the flow rate is key to optimizing temperature gradients and system efficiency. Strategic adjustments in flow rate significantly affect thermal storage and transfer capabilities, proving essential in system performance. This research offers vital insights into optimizing PVT-HP systems, focusing on the importance of flow rate control in improving temperature management and overall system performance.

Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI

A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m2, CKD stage G4–5); 172 with moderate renal dysfunction (30 ≤ eGFR < 60 mL/min/1.73 m2, CKD stage G3a/b); and 76 with mild renal dysfunction (eGFR ≥ 60 mL/min/1.73 m2, CKD stage G1–2) participated in this study. The model was applied to the right, left, and both kidneys, as well as to each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for the bilateral kidney models than for the unilateral kidney models. Our deep learning approach using kidney MRI can be applied to classify patients with CKD based on the severity of kidney disease.

Three-dimensional artistic design method of ceramic products based on recurrent neural network technology

Three-dimensional digital technology has made breakthroughs and shown unique advantages in all walks of life. On the basis of practicality, the three-dimensional artistic design of ceramic products gradually adds some aesthetic, artistic design elements, which brings beautiful enjoyment to people’s lives and makes people’s lives colorful. This paper presents a three-dimensional artistic design method for ceramic products based on RNN (recurrent neural network) technology. With the establishment of the 3D YOLOv3 framework, the new model training is faster and more stable, the convergence speed of the loss function is faster, and the reconstructed 3D model is more accurate. After training for a certain number of times, the network gradually becomes stable, the accuracy rate is kept at 95%, and the loss function value is reduced below 0.2. The accuracy of the network model and the precision of semantic segmentation are improved. The semantic segmentation and object recognition under 3D scene reconstruction studied in this paper have certain theoretical value and high feasibility.

Morphological Features of the Vertebrobasilar System Predict Ischemic Stroke Risk in Spontaneous Vertebral Artery Dissection.

The vertebral artery's morphological characteristics are crucial in spontaneous vertebral artery dissection (sVAD). We aimed to investigate morphologic features related to ischemic stroke (IS) and develop a novel prediction model. Out of 126 patients, 93 were finally analyzed. We constructed 3D models and morphological analyses. Patients were randomly classified into training and validation cohorts (3:1 ratio). Variables selected by LASSO - including five morphological features and five clinical characteristics - were used to develop prediction model in the training cohort. The model exhibited a high area under the curve (AUC) of 0.944 (95%CI, 0.862-0.984), with internal validation confirming its consistency (AUC = 0.818, 95%CI, 0.597-0.948). Decision curve analysis (DCA) indicated clinical usefulness. Morphological features significantly contribute to risk stratification in sVAD patients. Our novel developed model, combining interdisciplinary parameters, is clinically useful for predicting IS risk. Further validation and in-depth research into the hemodynamics related to sVAD are necessary.

3D technologies in STEAM education

The article presents the application of 3D technologies in STEAM education through a conducted scientific research, highlighting the role of 3D modeling and 3D printing as an innovative approach in achieving an interdisciplinary learning model. The research included the following stages: preparation for designing a detailed 3D steam locomotive model; analysis of process difficulties; giving students and lecturers the opportunity to perform a specific modeling task, using basic primitives from solid geometry, as well as a questionnaire to analyze and evaluate the skills and knowledge of the participants in the 3D modeling field. In this context, the preparation process of a 3D steam locomotive model for educational purposes, using Autodesk 3ds Max software, is presented, and the 3D printing technology FDM is examined. We issued a challenge to the participants in the research to design a non-complex 3D model, using unfamiliar 3D modeling software Blender, within a limited time. The questionnaire covered topics in education, science, art, STEAM, and 3D modeling. The goal is to showcase the role of the integration of 3D technologies in educational environments with the idea of developing key skills and knowledge in learners.

Evaluation of the Transfemoral Bone-Implant Interface Properties Using Vibration Analysis.

Evaluating the bone-implant interface (BII) properties of osseointegrated transfemoral (TFA) implants is important for early failure detection and prescribing loads during rehabilitation. The objective of this work is to derive and validate a 1D finite element (FE) model of the Osseointegrated Prosthetic Limb (OPL) TFA system that can: (1) model its dynamic behaviour and (2) extract the BII properties. The model was validated by: (1) comparing the 1D FE formulation to the analytical and 3D FE solutions for a simplifiedcylinder, (2) comparing the vibration modes of the actual TFA geometry using 1D and 3D FE models, and (3) evaluating the BII properties for three extreme conditions (LOW, INTERMEDIATE, and HIGH) generated using 3D FE and experimental (where the implant was embedded, using different adhesives, in synthetic femurs) signals for additional validation. The modes predicted by the 1D FE model converged to the analytical and the 3D FE solutions for the cylinder. The 1D model also matched the 3D FE solution with a maximum frequency difference of 2.02% for the TFA geometry. Finally, the 1D model extracted the BII stiffness and the system's damping properties for the three conditions generated using the 3DFE simulations and the experimental INTERMEDIATE and HIGH signals. The agreement between the 1D FE and the 3D FE solutions for the TFA geometry indicates that the 1D model captures the system's dynamic behaviour. Distinguishing between the different BII conditions demonstrates the 1D model's potential usefor the non-invasive clinical evaluation of the TFA BII properties.

Weakly guiding approximation of a three-dimensional waveguide model for extreme ultraviolet lithography simulation

A three-dimensional (3D) waveguide model is applied in extreme ultraviolet (EUV) lithography simulations. The 3D waveguide model is equivalent to rigorous coupled-wave analysis, but fewer field components are used to solve Maxwell’s equations. The 3D waveguide model uses two components of vector potential, A x and A y , corresponding to the two polarizations. The electric field of the A x polarization is approximately parallel to the x axis, and the electric field of the A y polarization is approximately parallel to the y axis. The 3D waveguide model solves a coupled vector wave equation for two polarizations. The refractive index of conventional EUV absorbers is close to that of vacuum. The weakly guiding approximation in optical fiber theory is applied to the 3D waveguide model. The coupled vector wave equations for the two polarizations are decoupled into two independent scalar wave equations. Maxwell’s equations are simplified to a set of scalar wave equations. The weakly guiding approximation reduces the computation time to solve the equations. The computation time required to solve the weakly guiding approximation is about 1/5 of the time to solve the original 3D waveguide model.

A Cost-Affordable Methodology of 3D Printing of Bone Fractures Using DICOM Files in Traumatology.

Three-dimensional (3D) printing has gained popularity across various domains but remains less integrated into medical surgery due to its complexity. Existing literature primarily discusses specific applications, with limited detailed guidance on the entire process. The methodological details of converting Computed Tomography (CT) images into 3D models are often found in amateur 3D printing forums rather than scientific literature. To address this gap, we present a comprehensive methodology for converting CT images of bone fractures into 3D-printed models. This involves transferring files in Digital Imaging and Communications in Medicine (DICOM) format to stereolithography format, processing the 3D model, and preparing it for printing. Our methodology outlines step-by-step guidelines, time estimates, and software recommendations, prioritizing free open-source tools. We also share our practical experience and outcomes, including the successful creation of 72 models for surgical planning, patient education, and teaching. Although there are challenges associated with utilizing 3D printing in surgery, such as the requirement for specialized expertise and equipment, the advantages in surgical planning, patient education, and improved outcomes are evident. Further studies are warranted to refine and standardize these methodologies for broader adoption in medical practice.

Surgical treatment of torticollis secondary to the presence of a congenital paracondylar process: illustrative case.

A paracondylar process is an abnormal bony exostosis arising from the skull base lateral to the occipital condyle and extending inferiorly toward the transverse process of the atlas. Paracondylar processes are typically identified incidentally and vary in size from a small protuberance to an elongated process. The authors present the first pediatric case of torticollis secondary to a congenital paracondylar process successfully treated with resection of the paracondylar process and sternocleidomastoid release. Cadaveric dissection, three-dimensional models, intraoperative imaging guidance, and multidisciplinary collaboration were paramount to a successful surgical outcome. https://thejns.org/doi/10.3171/CASE2447.

A 3D Pancreatic Cancer Model with Integrated Optical Sensors for Noninvasive Metabolism Monitoring and Drug Screening.

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heterogeneity that meaningfully impacts disease biology and treatment resistance. The dynamic crosstalk between cancer cells and the dense stromal compartment leads to spatially and temporally heterogeneous metabolic alterations, such as acidic pH that contributes to drug resistance in PDAC. Thus, monitoring the extracellular pH metabolic fluctuations within the TME is crucial to predict and to quantify anticancer drug efficacy. Here,a simple and reliable alginate-based 3D PDAC model embedding ratiometric optical pH sensors and cocultures of tumor (AsPC-1) and stromal cells for simultaneously monitoring metabolic pH variations and quantify drug response is presented. By means of time-lapse confocal laser scanning microscopy (CLSM) coupled with a fully automated computational analysis, the extracellular pH metabolic variations are monitored and quantified over time during drug testing with gemcitabine, folfirinox, and paclitaxel, commonly used in PDAC therapy. In particular, the extracellular acidification is more pronounced after drugs treatment, resulting in increased antitumor effect correlated with apoptotic cell death. These findings highlight the importance of studying the influence of cellular metabolic mechanisms on tumor response to therapy in 3D tumor models, this being crucial for the development of personalized medicine approaches.

Cancer organoids 2.0: modelling the complexity of the tumour immune microenvironment.

The development of neoplasia involves a complex and continuous interplay between malignantly transformed cells and the tumour microenvironment (TME). Cancer immunotherapies targeting the immune TME have been increasingly validated in clinical trials but response rates vary substantially between tumour histologies and are often transient, idiosyncratic and confounded by resistance. Faithful experimental models of the patient-specific tumourimmune microenvironment, capable of recapitulating tumour biology and immunotherapy effects, would greatly improve patient selection, target identification and definition of resistance mechanisms for immuno-oncology therapeutics. In this Review, we discuss currently available and rapidly evolving 3D tumour organoid models that capture important immune features of the TME. We highlight diverse opportunities for organoid-based investigations of tumour immunity, drug development and precision medicine.

Application of 3D bioprinting technology apply to assessing Dangguiniantongtang (DGNT) decoctions in arthritis

The aim of this study was to develop a three-dimensional (3D) cell model in order to evaluate the effectiveness of a traditional Chinese medicine decoction in the treatment of arthritis. Chondrocytes (ATDC5) and osteoblasts (MC3T3-E1) were 3D printed separately using methacryloyl gelatin (GelMA) hydrogel bioinks to mimic the natural 3D cell environment. Both cell types showed good biocompatibility in GelMA. Lipopolysaccharide (LPS) was added to the cell models to create inflammation models, which resulted in increased expression of inflammatory factors IL-1β, TNF-α, iNOS, and IL-6, and decreased expression of cell functional genes such as Collagen II (COLII), transcription factor SOX-9 (Sox9), Aggrecan, alkaline phosphatase (ALP), RUNX family transcription factor 2 (Runx2), Collagen I (COLI), Osteopontin (OPN), and bone morphogenetic protein-2 (BMP-2). The created inflammation model was then used to evaluate the effectiveness of Dangguiniantongtang (DGNT) decoctions. The results showed that DGNT reduced the expression of inflammatory factors and increased the expression of functional genes in the cell model. In summary, this study established a 3D cell model to assess the effectiveness of traditional Chinese medicine (TCM) decoctions, characterized the gene expression profile of the inflammatory state model, and provided a practical reference for future research on TCM efficacy evaluation for arthritis treatment.

Hypoxia-Responsive Prodrug of ATR Inhibitor, AZD6738, Selectively Eradicates Treatment-Resistant Cancer Cells.

Targeted therapy remains the future of anti-cancer drug development, owing to the lack of specificity of current treatments which lead to damage in healthy normal tissues. ATR inhibitors have in recent times demonstrated promising clinical potential, and are currently being evaluated in the clinic. However, despite the considerable optimism for clinical success of these inhibitors, reports of associated normal tissues toxicities remain a concern and can compromise their utility. Here, ICT10336 is reported, a newly developed hypoxia-responsive prodrug of ATR inhibitor, AZD6738, which is hypoxia-activated and specifically releases AZD6738 only in hypoxic conditions, in vitro. This hypoxia-selective release of AZD6738 inhibited ATR activation (T1989 and S428 phosphorylation) and subsequently abrogated HIF1a-mediated adaptation of hypoxic cancers cells, thus selectively inducing cell death in 2D and 3D cancer models. Importantly, in normal tissues, ICT10336 is demonstrated to be metabolically stable and less toxic to normal cells than its active parent agent, AZD6738. In addition, ICT10336 exhibited a superior and efficient multicellular penetration ability in 3D tumor models, and selectively eradicated cells at the hypoxic core compared to AZD6738. In summary, the preclinical data demonstrate a new strategy of tumor-targeted delivery of ATR inhibitors with significant potential of enhancing the therapeutic index.

An Inverse Modeling Approach for Retrieving High-Resolution Surface Fluxes of Greenhouse Gases from Measurements of Their Concentrations in the Atmospheric Boundary Layer

This study explores the potential of using Unmanned Aircraft Vehicles (UAVs) as a measurement platform for estimating greenhouse gas (GHG) fluxes over complex terrain. We proposed and tested an inverse modeling approach for retrieving GHG fluxes based on two-level measurements of GHG concentrations and airflow properties over complex terrain with high spatial resolution. Our approach is based on a three-dimensional hydrodynamic model capable of determining the airflow parameters that affect the spatial distribution of GHG concentrations within the atmospheric boundary layer. The model is primarily designed to solve the forward problem of calculating the steady-state distribution of GHG concentrations and fluxes at different levels over an inhomogeneous land surface within the model domain. The inverse problem deals with determining the unknown surface GHG fluxes by minimizing the difference between measured and modeled GHG concentrations at two selected levels above the land surface. Several numerical experiments were conducted using surrogate data that mimicked UAV observations of varying accuracies and density of GHG concentration measurements to test the robustness of the approach. Our primary modeling target was a 6 km2 forested area in the foothills of the Greater Caucasus Mountains in Russia, characterized by complex topography and mosaic vegetation. The numerical experiments show that the proposed inverse modeling approach can effectively solve the inverse problem, with the resulting flux distribution having the same spatial pattern as the required flux. However, the approach tends to overestimate the mean value of the required flux over the domain, with the maximum errors in flux estimation associated with areas of maximum steepness in the surface topography. The accuracy of flux estimates improves as the number of points and the accuracy of the concentration measurements increase. Therefore, the density of UAV measurements should be adjusted according to the complexity of the terrain to improve the accuracy of the modeling results.

Metformin Prevents Tumor Cell Growth and Invasion of Human Hormone Receptor-Positive Breast Cancer (HR+ BC) Cells via FOXA1 Inhibition

Women with type 2 diabetes (T2D) have a higher risk of being diagnosed with breast cancer and have worse survival than non-diabetic women if they do develop breast cancer. However, more research is needed to elucidate the biological underpinnings of these relationships. Here, we found that forkhead box A1 (FOXA1), a forkhead family transcription factor, and metformin (1,1-dimethylbiguanide hydrochloride), a medication used to treat T2D, may impact hormone-receptor-positive (HR+) breast cancer (BC) tumor cell growth and metastasis. Indeed, fourteen diabetes-associated genes are highly expressed in only three HR+ breast cancer cell lines but not the other subtypes utilizing a 53,805 gene database obtained from NCBI GEO. Among the diabetes-related genes, FOXA1, MTA3, PAK4, FGFR3, and KIF22 were highly expressed in HR+ breast cancer from 4032 breast cancer patient tissue samples using the Breast Cancer Gene Expression Omnibus. Notably, elevated FOXA1 expression correlated with poorer overall survival in patients with estrogen-receptor-positive/progesterone-receptor-positive (ER+/PR+) breast cancer. Furthermore, experiments demonstrated that loss of the FOXA1 gene inhibited tumor proliferation and invasion in vitro using MCF-7 and T47D HR+ breast cancer cell lines. Metformin, an anti-diabetic medication, significantly suppressed tumor cell growth in MCF-7 cells. Additionally, either metformin treatment or FOXA1 gene deletion enhanced tamoxifen-induced tumor growth inhibition in HR+ breast cancer cell lines within an ex vivo three-dimensional (3D) organoid model. Therefore, the diabetes-related medicine metformin and FOXA1 gene inhibition might be a new treatment for patients with HR+ breast cancer when combined with tamoxifen, an endocrine therapy.

Effect of forefoot transverse arch stiffness on foot biomechanical response--based on finite element method

BackgroundThe plantar vault, comprising the transverse and longitudinal arches of the human foot, is essential for impact absorption, elastic energy storage, and propulsion. Recent research underscores the importance of the transverse arch, contributing over 40% to midfoot stiffness. This study aimed to quantify biomechanical responses in the ankle-foot complex by varying the stiffness of the deep metatarsal transverse ligament (DTML).MethodsUsing CT image reconstruction, we constructed a complex three-dimensional finite element model of the foot and ankle joint complex, accounting for geometric complexity and nonlinear characteristics. The focus of our study was to evaluate the effect of different forefoot transverse arch stiffness, that is, different Young’s modulus values of DTML (from 135 MPa to 405 MPa), on different biomechanical aspects of the foot and ankle complex. Notably, we analyzed their effects on plantar pressure distribution, metatarsal stress patterns, navicular subsidence, and plantar fascial strain.ResultsIncreasing the stiffness of the DTML has significant effects on foot biomechanics. Specifically, higher DTML stiffness leads to elevate von Mises stress in the 1st, 2nd, and 3rd metatarsals, while concurrently reducing plantar pressure by 14.2% when the Young’s modulus is doubled. This stiffening also impedes navicular bone subsidence and foot lengthening. Notably, a 100% increase in the Young’s modulus of DTML results in a 54.1% decrease in scaphoid subsidence and a 2.5% decrease in foot lengthening, which collectively contribute to a 33.1% enhancement in foot longitudinal stiffness. Additionally, doubling the Young’s modulus of DTML can reduce the strain stretch of the plantar fascia by 38.5%.ConclusionPreserving DTML integrity sustains the transverse arch, enhancing foot longitudinal stiffness and elastic responsiveness. These findings have implications for treating arch dysfunction and provide insights for shoe developers seeking to enhance propulsion.