Bio-medical materials and engineering最新文献

BackgroundThe skin serves as a critical barrier, safeguarding the body against external threats including bacteria, viruses, and ultraviolet (UV) radiation. Compromised skin integrity can result in pain, hinder daily activities, and elevate the risk of infections. Clinically, dressings are the conventional treatment for skin injuries. However, these often necessitate frequent replacements and may exacerbate wound trauma during removal. Therefore, there is growing interest in developing innovative dressings such as hydrogels, which are celebrated for their softness, adaptability, permeability, and capacity to sustain a moist wound environment. Guar gum, a galactomannan polysaccharide extensively utilized in the food and biomedical sectors, forms highly viscous, biocompatible hydrogels that are promising for medical applications including capsules and wound dressings. Nonetheless, the mechanical strength and antimicrobial properties of guar gum hydrogels require enhancements for optimal medical efficacy.ObjectiveThis study explores the fortification of guar gum (GG) hydrogels with tannic acid (TA) and citric acid (CA), which are known for their antibacterial, anti-inflammatory, and antioxidant properties, to develop injectable, antimicrobial hydrogel dressings.MethodsEmploying a one-pot synthesis method, this research aimed to create dressings for treating skin injuries in murine models. The hydrogels were characterized using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FT-IR), assessed for antibacterial efficacy against Staphylococcus aureus, and evaluated for biocompatibility and therapeutic effectiveness in mice with full-thickness skin injuries.ResultsThe results demonstrated successful cross-linking, structural stability, and significant enhancement in wound healing, indicating the potential of these GG-CA-TA hydrogel dressings to broaden the scope of guar gum applications in clinical skin restoration.ConclusionIn this study, a kind of Guar gum hydrogel was successfully synthesized by one-pot method, which has great potential in clinical skin repair.

BackgroundA representative method for compensating for tooth loss is implant placement. Dental implants consist of a crown, an abutment, and an artificial tooth root, and are made of various materials. Proper care is essential for the long-term use of implants, and negligence in care can lead to inflammation around the implant. The most representative inflammation that occurs around implants is peri-implantitis, and various laser treatments are being studied recently to eliminate it.ObjectiveIn this study, the effect of implant materials on temperature rise within inflamed tissue was analyzed both theoretically and numerically in removal of peri-implantitis using photothermal therapy.MethodsThe temperature distribution in tissue for various artificial root materials, laser irradiation angles, and intensities was calculated, and degree of tissue death was determined using the Arrhenius damage integral. Furthermore, percentage of tissue death was analyzed using the Arrhenius thermal damage ratio and the normal tissue Arrhenius thermal damage ratio to identify trends in the results based on treatment conditions.ResultsConsequently, with regard to materials used for artificial tooth roots, the prevailing trend in treatment indicates that zirconia is the most effective material, followed by Ti-6Al-4V, titanium, and tantalum. The efficacy of laser irradiation increases as the angle approaches vertical.ConclusionThe findings indicate that increasing laser power and reducing the irradiation angle are beneficial when focusing solely on inflammation.

Background: The restoration of collagen and elastin in human dermal fibroblasts plays a crucial role in anti-aging and skin rejuvenation therapies. Numerous studies have examined the effects of various antioxidants on skin health, but there is limited research comparing their combined effects on collagen and elastin synthesis in human dermal fibroblasts. Objective: The objective of this study was to evaluate the individual and combined effects of N-acetylcysteine (NAC), Coenzyme Q10 (CoQ10), Niacinamide (NIAC), Gamma Cyclodextrin (GAMMA), Retinol (RET), Epigallocatechin Gallate (EGCG), and Ellagic Acid (ELA) on collagen type I and elastin synthesis in human dermal fibroblasts (HDFs). Methods: Human dermal fibroblasts were treated with individual and combined antioxidants. The expression of collagen type I and elastin was measured using mRNA analysis, immunofluorescence staining, and matrix protein assays. The study focused on the effects of EGCG in combination with other antioxidants like RET, CoQ10, and NAC to identify synergistic effects. Results: The combination of EGCG + RET and EGCG + CoQ10 showed the most significant increase in both elastin and collagen type I synthesis, surpassing the effects of individual antioxidants. EGCG demonstrated the highest fold change in elastin mRNA expression, while the combination treatments notably enhanced the extracellular matrix restoration in HDFs. Conclusion: The combination of EGCG with CoQ10, Retinol, or NAC presents a promising strategy for enhancing skin elasticity and firmness by promoting both elastin and collagen synthesis. These findings suggest that antioxidant combinations can be developed for effective anti-aging skincare formulations.

Background: Most Obstructive Sleep Apnoea (OSA) treatments use cross-sectional examination of the Upper Airways (UA) to determine decreasing gap and UA length. Surgery is detrimental to all OSA patients, stressing the need for better assessment. Objective: This study integrates Computational Fluid Dynamics (CFD) with physical model validation to improve OSA prediction and turbulence model accuracy and dependability. Methods: The k-omega SST turbulence model is used to analyse OSA using CFD. SLS is used to build a physical model of the UA for CFD simulations. The UA's physical model is then compared to the OSA-recommended CFD turbulence model to verify simulation-physical reality coherence. Result: The average UA pressure differential decreases considerably after mandibular advancement surgery. The Turbulent Kinetic Energy (TKE) increases after surgery, indicating more turbulence. Cross-validation of the physical model confirms the OSA CFD turbulence simulation's validity. Conclusion: The study concludes that matching UA simulations with physical models improves OSA assessments. CFD with established physical models is a reliable method for assessing OSA therapy, especially surgical operations. The post-surgery increase in TKE needs more study to determine its effects on OSA treatment outcomes.

BackgroundTo alleviate the workload of medical staff and provide personalized care for hepatitis patients, this study focuses on developing a hepatitis care robot.ObjectiveThe objective of this study is to integrate the RP-lidarA1 sensor into a hepatitis care robot to achieve high-precision environmental perception, mapping, and navigation, thereby improving healthcare services.MethodsThe RP-lidarA1 sensor was utilized for environmental scanning, and the MPU6050 chip was used to collect attitude data. An improved RBPF-SLAM algorithm was employed for high-precision map construction. For positioning and navigation, a combination of the A* algorithm and Dynamic Window Approach (DWA) algorithm was used to optimize path planning and obstacle avoidance.ResultsSimulation experiments demonstrated that the improved algorithm reduced the number of particles to 50 in a 140 m² area and shortened the map construction time to 1200 s. The A* algorithm effectively planned optimal paths, while the DWA algorithm improved navigation efficiency. Satisfaction surveys indicated that 92.4% of hepatitis patients and 81.8% of nurses were highly satisfied with the robot's performance.ConclusionsThe hepatitis care robot integrating the RP-lidarA1 sensor showed excellent performance in autonomous navigation, map construction, and obstacle avoidance, significantly enhancing the quality and efficiency of medical services.

BackgroundLung cancer is a leading cause of cancer-related deaths worldwide, making early diagnosis crucial for improving treatment success and survival rates. Traditional diagnostic methods, such as biopsy and manual CT image interpretation, are time-consuming and prone to variability, highlighting the need for more efficient and accurate tools. Advances in deep learning offer promising solutions by enabling faster and more objective medical image analysis.ObjectiveThis study aims to classify benign, malignant, and normal lung CT images using advanced deep learning techniques, including a specially developed CNN model, to improve diagnostic accuracy.MethodsA dataset of 1097 lung CT images was balanced using GANs and preprocessed with techniques like histogram equalization and noise reduction. The data was split into 70% training and 30% testing sets. Models including VGG19, AlexNet, InceptionV3, ResNet50, and a custom-designed CNN were trained. Additionally, Faster R-CNN-based region proposal methods were integrated to enhance detection performance.ResultsThe custom CNN model achieved the highest accuracy at 99%, surpassing other architectures like VGG19, which reached 97%. The Faster R-CNN integration further improved sensitivity and classification precision.ConclusionThe results demonstrate the effectiveness of GAN-supported deep learning models for lung cancer classification, highlighting their potential clinical applications for early detection and diagnosis.

BackgroundThe utilization of bioceramics for medical implants necessitates the incorporation of antibacterial properties to mitigate post-surgical inflammation of bone tissue.ObjectiveIn this research, Zn²⁺ ions were introduced as an antibacterial agent into carbonate-hydroxyapatite-based honeycomb Scaffold bioceramics (CHA/HCB), with varying doping concentrations, to investigate the impact of Zn²⁺ on the antibacterial activity of CHA/HCB against Staphylococcus aureus and Pseudomonas aeruginosa.MethodsCHA was synthesized from abalone shells through the co-precipitation method, followed by the fabrication of a CHA-based scaffold with HCB using the porogen leaching technique. Subsequently, the Zn ion doping process was executed through the ion exchange method, using concentrations of 0.05 M, 0.1 M, 0.15 M, and 0.2 M. The samples were characterized using XRF and antibacterial test.ResultsThe XRF results revealed that the Ca/P ratio of CHA/HCB was within the range of 1.48-1.85, indicating a declining trend with the introduction of Zn²⁺ as a dopant. Nevertheless, these results remained within acceptable ranges, ensuring compatibility with bone tissue. In terms of antibacterial activity, the measured inhibition zone diameters increased alongside the increase of Zn concentration. The zone diameters ranged from 14.3 to 22.0 mm against Staphylococcus aureus and 13.7 to 21.4 mm against Pseudomonas aeruginosa.ConclusionThe findings suggest that Zn doping in CHA/HCB bioceramics has a potential an antibacterial agent in CHA scaffolds as well as potential for practical applications, particularly in reducing the risk of postoperative infection in bone tissue implantation.

BackgroundThe success of dental restorations depends on achieving adequate surface integrity. However, grinding and polishing are generally ineffective because of the special physical and chemical compositions and properties of the composites. Polyurea resin is an elastomer with high elasticity, abrasion resistance, heat resistance, and toughness. When it is used as a bond, grinding wheels with high grain grip strength can be fabricated.ObjectiveWe fabricated a mounted wheel with a polyurea resin as the bond and used it to polish a composite resin and porcelain under clinical polishing conditions. The effects of the approach on the polished surface roughness and morphology were evaluated with respect to the type of mounted wheel, initial surface roughness, abrasive particle size, and polishing time.MethodsThis study fabricates a mounted wheel with polyurea resin as the bond and uses it to polish composite resin and porcelain under clinical polishing conditions. The effects of the approach on the polished surface roughness and morphology are evaluated against the type of mounted wheel, initial surface roughness, abrasive particle size, and polishing time.ResultsAmong single-crystal diamond, siliconcon carbide (GC), and alumina (WA) abrasive grains, diamond abrasive grains produced the best finish for most tested resin composites. However, WA abrasive grains are effective for polishing Estenia (it has the highest filler content). The polishing performance of the porcelain varied with the initial surface roughness and abrasive particle diameter.ConclusionThis study provides guidance for improving and developing mounted wheels for clinical applications.

BackgroundThe differences in bony alignment of the lower extremities during gait compared to standing remain unclear.ObjectiveThis study aimed to evaluate three-dimentional (3D) lower extremity alignment in healthy elderly individuals during the stance phase of gait and compare it with static standing alignment.MethodsThirty-four knees (9 females, 8 males; mean age 73.2 years) were assessed using single-plane X-ray fluoroscopy and a 3D to two-dimensional (2D) image matching technique. Alignment during stance phase and standing was evaluated in a world coordinate system, using the direction of gravity and frontal X-ray (aligned with the gait direction) as references.ResultsCompared to standing, the femur (3.5°), tibia (3.2°) and tibial joint line relative to the floor (3.3°) exhibited increased lateral inclination during stance phase (p < 0.01). In the transverse plane, the femur showed a significant increase in external rotation during stance phase (5.0°, p < 0.01) compared to standing, with no significant difference in tibial rotation.ConclusionLower extremity alignment significantly differs between static standing and gait, making it challenging to accurately infer the alignment during gait from standing assessments. This approach offers a practical means for assessing functional lower extremity alignment, potentially improving clinical outcomes in realignment surgeries.