Frontiers in Biomedical Technologies
Volume:10 Issue: 3, Summer 2023

Mathematical simulating and computer modeling of cells in organs help to better understand cells' interactions and tissues' functions. The purpose of this paper was to model and simulate the excitable membrane of gastric cells. In this simulation, the current physiological functional descriptions of the gastric cells have been used, and at the same time, the electrophysiological characteristics of similar cells in the gastrointestinal tract have also been considered.

To obtain a mathematical model for the stomach Smooth Muscle Cells (SMCs), the properties and electrophysiological parameters from the SMCs in the colon were used in the simulation of the stomach SMCs. Using the sensitivity analysis method, the effective parameters and values for simulating the electrophysiological behavior of the excitable gastric cell membrane were obtained for different phases of slow-wave (such as Depolarization, Spike, Plateau, Repolarization, and Rest). Also, the Action Potential Duration (APDs) method in four modes of 10, 20, 50, and 90 percent of APDs was used to evaluate the estimation of the effect of sensitivity analysis on the slow-wave of the studied cells.

The findings showed that the greatest effect of the stimulation current parameters was on the slow-wave duration and frequency. In addition, the greatest effect of ion channel parameters was observed on the plateau_phase in the slow-wave. Based on these methods, the resulting slow-wave pattern and its frequency (2.8 cycles per min) were in line with the experimental observations for gastric SMCs.

The mathematical model obtained from the model of colon SMCs accurately represented the electrophysiological behavior of the stomach cells.

Absorbed dose enhancement due to the presence of high atomic number nanoparticles (NP)s has been estimated and modeled by Monte Carlo (MC) simulation methods. In the current study, two MC codes of MCNPX and EGSnrc codes were compared by calculation of secondary electron energy spectra and nano-scaled dose values around four types of spherical NPs.

The MC model was composed of a spherical nanoparticle with a diameter of 50 nm and mono-energetic sources of photons with energies of 30,60, and 100 keV. The secondary electrons emitted from the nanoparticle were scored on the nanoparticle surface and the delivered dose to water around the nanoparticle was tallied using concentric shells with a thickness of 25 nm. Four different elements were used as materials of NPs, including Gold, Bismuth, Gadolinium, and Hafnium.

Our results showed a considerable difference in the number of emitted electrons per incident photon between the two codes. There were also discrepancies between the two codes in the energy spectra of secondary electrons. Calculated radial dose values around NPs in nano-scale had a similar pattern for both codes. However, significant differences existed for some elements.

It can be concluded that the results of nano-scaled MC modeling for nanoparticle-based radiation therapy are dependent on the code type and its algorithm for electron transport as well as exploited cross-section libraries.

Radiology examinations are growing significantly every year. Analysis of the CT scan reports can highlight defects and is a good way to develop safety in healthcare. This study aimed to evaluate the rate of normal head Computed Tomography (CT) scans at a hospital radiology department in Shahroud and estimate the cancer risk associated with these normal CT scans.

In total, the data of 400 patients referred to the emergency radiology center of Imam Hossein hospital in Shahroud from November 23 to December 10, 2021, were collected. CT scan reports were categorized into three groups according to the interpretation of the radiologist. The BEIR VII model was used to estimate the radiation cancer risk.

Among the 400 patients, 248 (62%) were males and the average age of the patients was 49.05 ± 22.60 years. CT scans in 270 (67.5%) cases were reported normal. The average age of the patients with normal, and abnormal CT scans were 41.86 ± 20.27, and 63.03 ± 20.27 years, respectively and the difference was significant (p-value <0.001). The average effective dose was obtained 1.72±0.09, 1.31±0.11, and 0.87±0.09 mSv for different age groups of 1-5, 5-10, >10-year-old. The average risks of all solid cancers were 7.82 cases per 100,000 patients, while the average risk of leukemia was 0.71 cases per 100,000 patients.

A large percentage of CT examinations are normal in our country which leads to many public health issues in the future years. Therefore, efforts should be made to establish predictor clinical factors to reduce unnecessary radiology examinations.

This study aimed to investigate the effect of the patients’ setup errors on dosimetric and radiobiologic parameters for left-sided Whole-Breast Irradiation (WBI) in three different radiotherapy techniques, including Intensity-Modulated Radiation Therapy (IMRT), Field-In-Field (FIF), and Conventional Wedge (CW).

Computed Tomography (CT) images of 10 female patients with early-stage left-sided breast cancer were used to simulate different radiotherapy techniques (IMRT, FIF, and CW). The dosimetric parameters; Conformity Index (CI), Homogeneity Index (HI), the dose received by at least 95% (D95%) of Planning Tumor Volume (PTV), the volume of lung and heart that respectively received at least 20% (V20%) and 40% (V40%) of the prescribed dose, as well as, the radiobiologic parameters, including Tumor Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) were assessed for setup errors in patients. The setup errors were assessed by shifting the isocenters and gantry angles of the treatment plans.

The D95% of the PTV for an isocenter misplacement plan in the posterior direction decreased by 66.99 (IMRT), 71.86 (CW), and 68.25% (FIF). The TCP of the PTV was reduced by 26.66, 39.16, and 36.97% for IMRT, CW, and FIF techniques, respectively. Increasing gantry angle by a ±10 degree caused a 43%, 41%, and 41% decrease in the D95% of IMRT, FIF, and CW techniques, respectively. The TCP values decreased about 18% in all three techniques with a ±10 degree gantry angle shift; however, the NTCP values of the heart and lungs increased for all three methods. The CI and HI values had significantly more changes with increasing setup errors in the IMRT than in the two techniques.

The radiobiologic parameters in IMRT were less sensitive to setup errors compared to FIF and CW techniques. The radiobiological parameters can help estimate the setup errors along with physical parameters during breast radiotherapy.

Multiple Sclerosis (MS) is an acute, autoimmune, and inflammatory disease in the central nervous system. This study investigated the effect of sagittal Short Tau Inversion Recovery (STIR) and T2-W Fluid Attenuated Inversion Recovery (FLAIR) sequences rather than sagittal T2-W as complementary sequences in patients with cervical spinal cord lesions and suspected MS.

This cross-sectional study was performed on all individuals referred to the Shahid Ghazi MRI center in Sanandaj for six months. Sixty patients with a cervical spine MRI request that were suspected of having MS were examined. The number of MS plaques in the sagittal T2-W FSE, sagittal STIR, and sagittal T2-W FLAIR were recorded separately. A comparison between routine sequences and sequence supplementation has been made for characterizing MS plaque in the spine.

Results showed that the greatest agreement was related to sagittal STIR, and sagittal FLAIR (Cohen’s kappa = 0.56). Whereas the least agreement values were from sagittal T2-W and sagittal FLAIR, STIR and FLAIR, T2-W and FLAIR, T2-W and STIR (Cohen’s kappa = 0.20, 0.33, 0.48, 0.55), respectively. Sagittal STIR and sagittal FLAIR were excellent predictors for MS plaques diagnosis due to the area under the ROC curve = 0.56; sensitivity (95% CI) = [0.85 (0.73426 to 0.929044)] and specificity (95% CI) = [0.46 (0.336699 to 0.600035)].

Results show that FLAIR T2-W images in sagittal sequence are appropriate for detecting lesions around spinal cord lesions. Furthermore, using thresholds obtained via statistical analysis, plaques in the cervical spinal cord can be identified in sagittal STIR images.

Alzheimer's Disease (AD) is in the dementia group and is one of the most prevalent neurodegenerative disorders. Between existing characteristics, White Matter (WM) is a known marker for AD tracking, and WM segmentation in MRI based on clustering can be used to decrease the volume of data. Many algorithms have been developed to predict AD, but most concentrate on the distinction of AD from Cognitive Normal (CN). In this study, we provided a new, simple, and efficient methodology for classifying patients into AD and MCI patients and evaluated the effect of the view dimension of Fuzzy C Means (FCM) in prediction with ensemble classifiers.

We proposed our methodology in three steps; first, segmentation of WM from T1 MRI with FCM according to two specific viewpoints (3D and 2D). In the second, two groups of features are extracted: approximate coefficients of Discrete Wavelet Transform (DWT) and statistical (mean, variance, skewness) features. In the final step, an ensemble classifier that is constructed with three classifiers, K-Nearest Neighbor (KNN), Decision Tree (DT), and Linear Discriminant Analysis (LDA), was used.

The proposed method has been evaluated by using 1280 slices (samples) from 64 patients with MCI (32) and AD (32) of the ADNI dataset. The best performance is for the 3D viewpoint, and the accuracy, precision, and f1-score achieved from the methodology are 94.22%, 94.45%, and 94.21%, respectively, by using a ten-fold Cross-Validation (CV) strategy.

The experimental evaluation shows that WM segmentation increases the performance of the ensemble classifier, and moreover the 3D view FCM is better than the 2D view. According to the results, the proposed methodology has comparable performance for the detection of MCI from AD. The low computational cost algorithm and the three classifiers for generalization can be used in practical application by physicians in pre-clinical.

The anatomical and physiological processes of the human body are pictured in radiology using different modalities. Magnetic Resonance Imaging (MRI) supports capturing the images of organs using magnetic field gradients. The quality of MR images is generally affected by various noises such as Gaussian, speckle, salt and pepper, Rayleigh, Rican etc. Removal of these noises from the MR images is essential for further diagnostic procedures.

In this article, Gaussian noise, speckle noise, and salt and pepper noise are added to the MR uterus image for which different filters are applied to remove the noise for precise identification of endometrial carcinoma.

The different filters incorporated for the additive noise removal process are the bilateral filter, Non-Local Means (NLM) filter, anisotropic diffusion filter, and Convolution Neural Network (CNN). The efficiency of the filter is calculated by evaluating the response of the filter by gradually increasing the noise intensity of the MR images.

Further, peak Signal-to-Noise Ratio (SNR), structural similarity index measure, image quality index and computational cost parameters are computed and analyzed.

Memory and learning have particular importance due to their ubiquitous nature in everyday life and the high prevalence of related complaints. The present study aimed to provide normative data for one of the most widely used tests of verbal memory and learning in Iran and to assess the effect of demographic variables of age, gender, and education on its various measures.

The study was conducted as part of the Iranian Brain Imaging Database (IBID) project. The sample consisted of 300 normal individuals in the age range of 20 to 70 years, with an equal number of participants in each age decade (#60). The sample was classified by five decades, including 20-30-year-olds, 31-40-year-olds, 41-50-year-olds, 51-60-year-olds, and 61-70-year-olds. Each age decade was divided equally between the genders. The Rey Auditory Verbal Learning Test (RAVLT), which was defined in terms of 10 scores on learning, recall, and recognition, was used to assess verbal learning and memory.

The correlation matrix among the variables shows that all three variables of age, gender, and education had a significant correlation with most RAVLT measures. Among the three demographic variables, age had the strongest correlation with most RAVLT scores. Three-way Analysis of Variance (ANOVA) showed that the effect of age and gender on memory and learning measures was significant. On the other hand, the effect of education on some measures was statistically significant. In addition, the mean and standard deviation of 10 RAVLT measures classified by gender and education years in the five age groups are provided.

The findings show that while increasing age, verbal memory, and learning performance decline, women outperform men, and education affects some indicators of learning and memory. These findings emphasize the importance of using age-, gender- and education-related normative data in clinical, educational, and research settings.

This study aimed to evaluate the effect of samarium-153-EDTMP (153Sm-EDTMP) on pain relief bone metastases of Breast Cancer (BC) and Prostate Cancer (PC) patients.

Thirty patients aged 40-77 years (62.6±10.2 years) with intractable metastatic bone pain were included in the current study. A checklist of patient information and a standard questionnaire for the assessment of pain and quality of life were completed before and after four and eight week’s palliative treatment with 37 MBq/kg of 153Sm-EDTMP. To analyse the data, parametric and non-parametric tests were used in SPSS software.

Twelve females with BC (40%) and 18 males with PC (60%) were included. Four and eight weeks after palliative treatment of 153Sm-EDTMP, the mean pain score reduction and quality of life were statistically increased compared to before the intervention (P-value < 0.05). Notably, the amount of pain reduction in the fourth week was more than in the eighth week; however, the quality of life was better in the eighth week, without significant variation (P-value <0.05). In addition, there was no statistically significant relationship between pain reduction and the type of primary diseases, BC, and PC (P-value >0.05).

The injection of 153Sm-EDTMP had therapeutic efficacy for bone pain palliation in patients with diffuse bone metastases at the end of the 4th and 8th week post-infusion.

In this study, a controlled release drug delivery system loaded with piroxicam and methadone was synthesized and used subcutaneously in rat with experimental tibial defect and healing were assessed histopathologically.

For this purpose 100 adult female rats were were randomly divided into five equal groups; group control, chitosan group, piroxicam group, methadone group, and piroxicam-methadone group. The morphological structure of the synthesized drug systems was studied by scanning electron microscope. In addition, the structure of the hydrogels was investigated by fourier transform infrared spectroscopy and while releasing the hydrogels gelation time, the release of piroxicam and methadone from the hydrogels were evaluated in vitro.  

 Histological results of the 3rd day of the study showed the lowest extent and severity of inflammation in the chitosan, piroxicam, and piroxicam-methadone groups, while on the 7th day, tissue inflammation and the extent of bleeding was lower in the piroxicam, methadone, and piroxicam-methadone groups than in the other groups. Evaluation of new bone formation on day 21 showed that the chitosan, piroxicam, and methadone groups had better repair than the other groups.

It seems that in the control group that did not receive any treatment intervention, following the experimental bone defect, the highest inflammatory response was observed in histological examination and finally the weakest bone repair. On the other hand, the presence of piroxicam, methadone and chitosan in the piroxicam-methadone group (all of which have anti-inflammatory effects) also seems to have a negative effect on repair.

The goal of this research was to investigate the bystander effect in the A-375 cell line under the spatially fractionated radiation therapy (GRID therapy technique). In GRID therapy, due to direct and indirect cell damage after high-dose radiation, evaluation of Radiation-Induced Bystander Effects (RIBE) is of the most importance for investigating the risk of therapy.

The potential role of RIBE was evaluated with different doses of 6 MeV electron radiation and different incubation times after irradiation using two methods; GRID therapy and medium transfer. Colony Formation Assay (CFA) and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) test were used to detect the mentioned effects. Alpha and beta parameters were calculated from the cell survival curve by the quadratic-linear model.

The result showed that the survival fraction significantly decreases by increasing the radiation dose for both bystander and irradiated cells. However, a decrease in the number of colony-forming cells caused by electron radiation greater than 4MeV to target cells was significantly increased compared with bystander cells (P < 0.05). While increasing the incubation time after exposure to an electron beam, it had no significant effect on cell survival fraction (P > 0.05). Furthermore, the RIBE level in non-target cells increased up to a dose of 4Gy, but decreased significantly at doses higher than 4Gy. This result in high doses confirmed that a negative feedback mechanism was responsible for reducing the RIBE response.

Based on the results, we can state there are classic radiation-induced bystander effects in A-375 monolayer exposed by GRID therapy and medium transfer technique, which can play an important role in pre-clinical and clinical studies.

The pathophysiological progression of traumatic spinal cord injury (SCI) includes primary and secondary injury. Secondary injury causes the destruction of the spinal cord tissue and neurological disorders. After primary mechanical damage, inflammation is the most important factor inducing astrogliosis and scar formation. The activation of inflammatory cells in the area of ​​damage causes the production of free radicals, all of which damage cell membranes. A significant level of oxygen free radical production is involved in the pathology of SCI; Therefore, limiting secondary damage is very important in the clinical treatment of acute traumatic spinal cord injury.

In this review article, the articles indexed in various databases were used. The collection of articles was evaluated without time constraints using keywords inducing traumatic spinal cord injury (SCI), inflammation, oxidative stress, chitosan, selenium nanoparticles.

Inflammation and oxygen free radicals play a key role in secondary damage after SCI. Therefore, as a new therapeutic approach, the use of - hydrogels based on chitosan has been considered in SCI. The biocompatibility and biological properties of chitosan have made it considered as a suitable material for nerve regeneration.

The use of reactive oxygen species scavengers, including metal nanoparticles, can control inflammation and oxidative stress in spinal cord injuries. Selenium nanoparticles treatment may reduce secondary damage in SCI by using its anti-inflammatory and antioxidant properties. Therefore, the use of selenium nanoparticles in the chitosan hydrogel bed can control the degeneration and functional improvement of the nerve tissue of the spinal cord.

Utilizing Electroencephalogram (EEG) is more than at any time in history, therefore we have introduced an open-source MATLAB function to provide simulated EEG which is as equivalent as viable to empirical EEG in a user-friendly way with ground truth that is not accessible in real EEG records. This function should be versatile due to the requirements such as the number and orientation of sources, various noises, mode of activation function, and different anatomical structures.

We indicate all phases, modes, and formulas which constitute EEGg, EEG generator. This function supports selecting main sources locations and orientation, choosing SNR with white Gaussian noise, electrode numbers, and mode of activation functions. Also, users have the option to use automatic or partly automatic, or fully automatic EEG construction in EEGg. This function is ready to use at https://github.com/Avayekta/EEG.

EEGg is designed with several parameters that users have chosen. Hence, users can choose different variables to inspect the time and frequency aspects of synthetic EEG.

EEGg is a multi-purpose and comprehensive function to mimic EEG but with ground-truth EEG data and adjustable parameters.