How Will Nanomedicine Revolutionize Future Dentistry and Periodontal Therapy?

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(2), P. 592 - 592

Published: Jan. 12, 2025

Periodontitis is a prevalent inflammatory disease affecting the supporting structures of teeth, leading to gum recession, tooth loss, and systemic health complications. Traditional diagnostic methods treatments, such as clinical evaluation scaling, often fall short in early detection targeted therapy, particularly complex or advanced cases. Recent advancements nanomedicine offer promising solutions for improving both diagnosis treatment periodontitis. Nanoparticles, liposomes, quantum dots, nanorods, have demonstrated potential enhancing accuracy by enabling more precise periodontal pathogens biomarkers at molecular level. Furthermore, nanotechnology-based therapies, including drug delivery systems antimicrobial agents, localized controlled release therapeutic efficacy reducing side effects compared conventional treatments. This study reviews current applications periodontitis, highlighting its revolutionize care detection, times, outcomes.

Language: Английский

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Harnessing Natural Polymers and Nanoparticles: Synergistic Scaffold Design for Improved Wound Healing

Hybrid Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100381 - 100381

Published: Jan. 1, 2025

Language: Английский

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Regeneration of Bone Tissue Using Nanofibers Made from Electrospun Polycaprolactone (PCL) and a Hydrogel Composed of Alginate (Alg/PCL)

Regenerative Engineering and Translational Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

Language: Английский

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Novel Estimation of Nanofiber Diameter from SEM Images Using Deep Feature Embeddings and Machine Learning Models

Advanced Theory and Simulations, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Accurate nanofiber diameter estimation is crucial for optimizing their functionality in materials science. Traditional measurement methods from Scanning Electron Microscopy (SEM) images are often labor‐intensive and subjective. This study proposes a machine learning‐based approach using deep feature embeddings to predict average diameters directly SEM images. Eight learning models—Linear Regression (LR), k‐Nearest Neighbors (kNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Neural Network (NN), Gradient Boosting (GB), AdaBoost—are evaluated 5‐fold 10‐fold cross‐validation. Performance assessed via Mean Squared Error (MSE), Root (RMSE), Absolute (MAE), Percentage (MAPE), R 2 . The kNN model consistently outperformed others across three datasets: smooth nanofibers, beaded combined set. It achieves the lowest error metrics highest (0.950) while demonstrating strong generalization morphologies. among first integrate with direct prediction, providing reliable alternative traditional methods.

Language: Английский

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Scaffold for Tissue Engineering Design Fabrication and Applications

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 335 - 366

Published: April 25, 2025

Recently, Tissue engineering (TE) has been rapidly growing field in biomedical field, it provides the solutions to problem such as immunological rejection and a shortage of available donors. TE scaffolds encourage cell adhesion, proliferation, differentiation by simulating extracellular matrix with three-dimensional matrices. Current, advancements artificial intelligence (AI) nanotechnology have improved design, pore size, mechanical properties. However, lack ability vascularization, immune compatibility, scalability. In order address this issue, surface-functionalized anti-inflammatory cytokines IL-10 that can increase integration, less rejection, long-term performance. Therefore, is considered combination AI scaffold design will enhance bioactivity, strength, cellular behavior modeling. Regenerative medicine poised for revolution due significant scaffold-based TE.

Language: Английский

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Embracing the future: The application of regenerative biomaterials in the spinal disorders

Biomedical Technology, Journal Year: 2024, Volume and Issue: 9, P. 100068 - 100068

Published: Dec. 25, 2024

Language: Английский

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Electrospun-based nanofibers as ROS-scavenging scaffolds for accelerated wound healing: a narrative review

International Journal of Polymeric Materials, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 33

Published: Dec. 16, 2024

This review delves into the efficacy of electrospun nanofibers as structures capable neutralizing Reactive Oxygen Species (ROS), thereby aiding in acceleration wound repair. ROS occupy a dual position cellular dynamics, being indispensable for intracellular communication, yet they potentially exacerbate oxidative stress which can stall healing trajectory. The method electrospinning synthesizes distinguished by their expansive surface area relative to volume and notable porosity, rendering them optimally suited medical endeavors, particularly frameworks that bolster recuperation. analysis elucidates diverse roles these play, from enhancing clot formation combating microbial invasion mitigating inflammation, fostering proliferation, facilitating angiogenesis—each pivotal component effective mending wounds.

Language: Английский

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