Journal of Biomedical Physics and Engineering最新文献

Background: Degenerative Joint Disease (DJD) of the first Metacarpophalangeal (MCP) joint, can severely impair hand function due to pain, stiffness, and reduced range of motion. Anatomical variations in metacarpal head morphology may play a critical role in altering joint biomechanics and stress distribution, potentially accelerating cartilage wear and osteoarthritis progression.

Objective: This study aimed to evaluate the biomechanical impact of different first metacarpal head morphologies on stress distribution within the MCP joint under various positions using computer simulation.

Material and methods: In this computer simulation study, three-dimensional models of the thumb MCP joint were reconstructed from Computed Tomography (CT) scans of healthy subjects. The models were adjusted to represent flat, biplanar, and convex metacarpal head morphologies and were simulated in three positions: neutral, 20° flexion, and 20° extension. Computer simulation was performed using Analysis System (ANSYS) to calculate von Mises stress distributions. Descriptive statistics and one-way Analysis of Variance (ANOVA) were applied to compare stress values between groups.

Results: The flat metacarpal head exhibited the highest stress concentrations, peaking at 138 MPa in 20° extension. Biplanar morphology showed moderate stresses, while the convex shape demonstrated the lowest stress, with a maximum of 58 MPa. The analysis confirmed significant differences between groups (P-value=0.039). Stress increased notably in flexion and extension positions compared to neutral across all morphologies.

Conclusion: Metacarpal head morphology and joint positioning significantly influence MCP joint biomechanics. Flat and biplanar shapes increase stress concentration, potentially elevating DJD risk. Convex morphology offers better stress dispersion, indicating a biomechanical advantage.

Background: Nonalcoholic Fatty Liver Disease (NAFLD) as a prevalent condition can significantly have health implications. Early detection and accurate grading of NAFLD are essential for effective management and treatment of the disease.

Objective: The current study aimed to develop an advanced hybrid machine-learning model to classify NAFLD grades using ultrasound images.

Material and methods: In this analytical study, ultrasound images were obtained from 55 highly obese individuals, who had undergone bariatric surgery and used histological results from liver biopsies as a reference for NAFLD grading. The features were extracted from the ultrasound images using popular pretrained Convolutional Neural Network (CNN) models, including VGG19, MobileNet, Xception, Inception-V3, ResNet-101, DenseNet-121, and EfficientNet-B7. The fully connected layers were removed from the CNN models and also used the remaining structure as a feature extractor. The most relevant features were then selected using the minimum Redundancy Maximum Relevance (mRMR) method. We then used four classification algorithms: Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Multilayer Perceptron (MLP) neural network, and Random Forest (RF) classifiers, to categorize the ultrasound images into four groups based on liver fat level (healthy liver, low fat liver, moderate fat liver, and high-fat liver).

Results: Among the different CNN models and classification methods, EfficientNet-B7 and RF achieved the highest accuracy. The average accuracies of the LDA, MLP, SVM, and RF classifiers for the feature extraction method with EfficientNet-B7 were 88.48%, 93.15%, 95.47%, and 96.83%, respectively. The proposed automatic model can classify NAFLD grades with a remarkable accuracy of 96.83%.

Conclusion: The proposed automatic classification model using EfficientNet-B7 for feature extraction and a Random Forest classifier can improve NAFLD diagnosis, especially in regions, in which access to professional and experienced medical experts is limited.

The extensive usage of mobile phones across all age brackets, including children and teenagers, leads to significant exposure to Radiofrequency Electromagnetic Fields (RF-EMF). This exposure raises concerns about potential adverse effects on sleep. The current study aimed to explore the influence of mobile phone-emitted RF-EMFs on the duration and quality of sleep in a cohort of medical students. Participants alternated between sleeping with and without a mobile phone for two-week intervals, while their sleep patterns were monitored using smartwatches. The study results indicated no statistically significant disparities in sleep quality between sleeping with and without a mobile phone. However, exposure to radiofrequency electromagnetic fields had a notable impact on the minimum and average blood oxygen saturation levels.

Background: Long-duration space missions expose astronauts to hazardous radiation, including Galactic Cosmic Rays (GCRs) and Solar Particle Events (SPEs), producing secondary neutrons that penetrate spacecraft. Traditional aluminum shielding is inefficient and generates secondary particles, necessitating lightweight, multifunctional composites for effective radiation protection.

Objective: This study aims to optimize neutron shielding composites using Cadmium (Cd) and Lithium (Li) compounds within an Unsaturated Polyester Resin (UPS) matrix, targeting maximum attenuation of fast and thermal neutrons, validated through both experimental measurements and Geant4 simulations, while assessing mechanical properties for spacecraft use.

Material and methods: This study combined experimental and simulation methods. Seven composites, each with 90 weight percentage (wt%) UPS and 10 wt% Cd and Li compounds (LiOH or LiBr), were synthesized. Neutron attenuation was tested using a ²³⁹Pu-Be source, measuring thermal (<0.5 eV) and fast (>0.5 MeV) neutron fluxes. Mechanical properties were evaluated via nanoindentation, with Geant4 Monte Carlo simulations providing comparative data.

Results: The Cd₅_LiOH₅ composite achieved 92.35% thermal neutron attenuation (99.65% simulated) at 25 mm, while Cd₂.₅_LiOH₇.₅ exhibited 36.2% fast neutron attenuation (38.7% simulated) at 25 mm. Simulations demonstrated strong agreement with experiments across most composites, with relative differences generally below 10%, except for thin samples or materials with heterogeneous filler distribution. The Cd₂.₅_LiBr₇.₅ composite showed superior hardness (0.10 GPa) and modulus (0.7 GPa).

Conclusion: UPS-based composites with Cd and Li offer effective neutron shielding and enhanced mechanical properties, validated by Geant4 simulations. These materials are promising for radiation protection in deep space missions.

Background: Psychogenic Non-Epileptic Seizures (PNES), is a type of seizure that is caused by emotional factors. Symptoms of PNES are similar to epileptic seizures including disturbance in involuntary movement. Previous studies showed that neural activity altered in PNES detected through the resting-state functional Magnetic Resonance Imaging (rs-fMRI) thus this study was designed for a better understanding of PNES pathophysiology using the rs-fMRI technique.

Objective: This study was conducted to examine dynamic Functional Connectivity (dFC) in the brain networks between PNES and healthy control subjects.

Material and methods: In this experimental study, the rs-fMRI was collected from 16 PNES subjects and 16 healthy subjects. After surrogating data, the sliding window technique was used for dFC detection in nine brain networks which chosen from Stanford Findlab.

Results: Our results indicate that there were no differences in the presence or absence of dFC between the PNES group and the control group in the ventral Default Mode Network (vDMN), Language Network (LN), and Visuospatial Network (VSN). However, dFC was elevated in the PNES group in comparison to the normal control group within the Sensorimotor Network (SMN), Posterior Salience Network (PSN), and Anterior Salience Network (ASN).

Conclusion: The findings suggest that dFC analyses hold significant potential for uncovering abnormal patterns of brain network connections in the PNES. This offers a promising finding for a better comprehension of PNES.

Background: Sonodynamic Therapy (SDT) is increasingly recognized as an innovative, non-invasive cancer modality in which low-intensity Ultrasound (U) energizes sonosensitizers, provoking a burst of Reactive Oxygen Species (ROS) that culminate in apoptotic destruction of tumor cells.

Objective: Silver-bismuth oxide nanocomposites (AgB NCs) and their folic acid-functionalized counterparts (FAgB NCs) studied as sono-sensitizers for improving in treatment route of melanoma cancer.

Material and methods: In this experimental research, AgB NCs and FAgB NCs were synthesized via a green route using Rheum turkestanicum extract. Comprehensive physicochemical characterizations-including Field-Emission Scanning Electron Microscopy (FESEM), Energy-Dispersive X-ray spectroscopy (EDX), Ultraviolet visible spectrometer (UV-vis), Powder X-ray Diffraction (PXRD), and Fourier-Transform Infrared spectroscopy (FT-IR)-confirmed the successful formation and functionalization of the nanocomposites.

Results: (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (MTT) assays on C540 melanoma cells revealed dose-dependent cytotoxicity, with F-AgBi NCs exhibiting significantly lower IC₅₀ values compared to AgB NCs. Upon U exposure, nanocomposites induced substantial ROS generation, mitochondrial dysfunction, and increased apoptosis, as verified by flow cytometry. Moreover, the FAgB NCs effectively suppressed cell migration and inhibited spheroid formation in 3D cultures, indicating potent antitumor activity in both monolayer and 3D models.

Conclusion: These findings underscore the synergistic potential of folic acid-functionalized AgB nanocomposites as efficient sonosensitizers for targeted melanoma therapy. Their enhanced ROS-mediated cytotoxicity, combined with folate receptor-targeted delivery, supports their application in advanced nanomedicine and SDT-based cancer treatment.

The TR5500 Thermoluminescent Dosimeter (TLD) reader was specifically designed and developed for the automated and efficient readout of Thermoluminescent (TL) chips and pellets in Iran. In accordance with International Atomic Energy Agency (IAEA) requirements for dosimetry laboratories, implementing a comprehensive Quality Management System (QMS) is essential to ensure adherence to standard criteria. This study aimed to evaluate key characteristics of the reader, including response non-linearity, Coefficients of Variation (COV), readout stability over time, and the reproducibility of TLD measurements. LiF: Mg, Cu, P TLDs were exposed to a standard photon radiation field and subsequently read using the TR5500 reader. The characteristics were then calculated and compared against the relevant criteria outlined in International Electrotechnical Commission (IEC) and American Society for Testing and Materials (ASTM) standards, such as ASTM E668-10 and IEC 62387. The reader met the key international standard requirements and, in certain aspects, even surpassed them. The device exhibited excellent stability and reproducibility in readouts, confirming its robust reliability and long-term suitability for routine use in various accredited dosimetry laboratories.

Background: Diabetes is a global concern, with an estimated 2 million individuals expected to be affected by the condition by 2024. Non-invasive glucose monitoring devices can greatly enhance patient care and management.

Objective: This study aimed to develop an instrument capable of non-invasively measuring blood glucose levels using an infrared transmitter and receiver, with data processing performed by a dedicated processor.

Material and methods: This analytical study develops a glucometer that incorporates a power supply, a light source, a light detector, a sampler, and signal processing components to enable non-invasive glucose measurements. The instrument was calibrated using sugar solution samples with known glucose concentrations. It was then tested using serum samples from diabetic patients with accuracy, which was evaluated using Clarke's grid analysis.

Results: Testing of the designed glucometer revealed that 83% of the serum samples fell within zone A of Clarke's grid analysis, indicating high accuracy. The remaining 17% of samples were classified in zone B, with no samples falling in zones C, D, or E.

Conclusion: The developed glucometer demonstrated higher accuracy in measuring glucose concentrations above 200 mg/dl. Despite the use of serum samples in this experiment, 83% of the results were located in zone A leads to the capability of non-invasively measuring blood glucose levels. Further studies are required to validate the device's accuracy in a larger population and assess its utility in clinical practice.