Frontiers in Biomedical Technologies
Volume:9 Issue: 2, Spring 2022

Sodium Valproate (VPA) is one of the first-generation Antiepileptic Drugs (AEDs) which mediates epileptic activities by releasing stimulators of Gamma-Aminobutyric Acid (GABA) and is greatly used to treat partial and generalized seizures. Lamotrigine )LTG( is commonly used as AEDs that are widely utilized in first-line monotherapy or in combination with other AEDs. Our specific goal was to compare these two AEDs with different molecular mechanisms on both cortical and subcortical brain structures, along with cognitive performance and dysfunctions.

We conducted a retrospective study comparing LTG with sodium VPA, both administrated as monotherapy. Twenty patients with a confirmed generalized-epilepsy tonic-clonic seizure who had been treated at least 6 months with LTG (n=8) and Sodium VPA (n=12) were retrospectively recruited. We also included 12 age, gender, and education-matched Healthy Controls (HC). We evaluated cognitive performances. All participants underwent a Magnetic Resonance Imaging (MRI) scanner and T1-weighted MR images were acquired. Voxel-based morphometric alterations in the brain cortex, as well as subcortical structures, were inspected using Statistical Parametric Mapping (SPM) software.

The cognitive performance was revealed inferior in patients on Sodium VPA. Poor performance was associated with significant volume reduction in insula bilaterally, and subcortical structures of thalamus, cerebellum, and hippocampus compared to the HC. Comparing patients on LTG to HC revealed significant volume reduction in the anterior cingulate cortex in concordance with slight cognitive dysfunctions.

These findings suggested that different molecular mechanisms of Antiepileptic Drugs (AEDs) may affect brain structures and cognition with different severity levels, presumably with more adverse effects induced by GABA mediations from sodium VPA.

For over three decades, various researchers have aimed to construct a model of breast cancer. Most of them have used an infrared thermal model to stimulate breast cancer, but in this study, a novel estimation methodology is presented to detect the breast cancer tumor using the surface measurement obtained by Passive Acoustic Thermometer (PAT). PAT is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature.

This article uses a simulation framework for breast tissue simulation and tumor detection using the PAT methodologies in different scenarios. This framework supports the generation of acoustic radiation, tissue modelling, signal processing, parameter estimation, and temperature reconstruction processes. The proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Using the proposed framework, PAT has been evaluated in breast cancer detection.

According to the results, obtained from the temperature estimation in scenario 3, the sub-band estimation method, which is utilized in practical experiments in this field, shows different errors in each sub-band, making it difficult to select the true estimation. Therefore, a novel formulation is proposed that provides only one estimated temperature for breast tissue with a reasonable error (1.28 degrees) for tumor detection.

The results show that it is possible to use this framework to evaluate the PAT in different scenarios for tumor detection. In fact, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiments.

Although MATLAB is a powerful math program, its virtual reality (VR) toolbox is limited for those who engage in the modelling of human body systems. The integration of Poser software with MATLAB is provided in this study for designing and developing human bodies in VR.

First, a human entire body model was created in the Poser environment. The prototype is then loaded into MATLAB Simulink.

Two-Link Arm powered by Six Muscles (TLASM), a well-known model of human arm movements in the horizontal plane, is simulated to test the efficiency of the virtual model. TLASM was presented in this team's prior work.

Despite the fact that only one limb of the human virtual platform body has been tested, it can easily be applied to other limbs.

Cancer radionuclide therapy is an effective, beneficial, and crucial method of cancer treatment that uses unsealed radioactivated radionuclides sources that are attached to a targeting vector to deliver therapeutic radiation doses from the ionizing radiation source to specific disease sites either for curative intent or for disease control and palliation for the patient pain decreasing. For this aim, Monte Carlo N–Particle 5 (MCNP5) MC computational code was employed for simulations and calculations as well as radiation transport.

50nm 90Y radionuclide nanosphere was modelled coated by a 10nm coating layer with some non-toxic high and low Z materials. Physical interactions, such as β-ray and the simulated coating materials were studied and radiological parameters were scored by the used MC code. Attenuation of β-ray, and production of the bremsstrahlung X-ray photons and other phenomena were simulated by the code and analyzed. MC code estimated the effect of the simulated coating materials, such as Gold, Platinum, Gaddolonium, Silver, and Epoxy-Resin on the radiation characteristics around the modelled nano-radionuclide per 2nm from the radiation source surface to 1µm distance. Produced bremsstrahlung X-ray by the source coating material and tissue atoms, emitted β-particle number, flux over the surfaces (per 2nm), radiation fluence of photon and β- ray, deposited energy per gr of the cell medium, and average dose to the cells around the 500nm and 1µm distance from the radionuclide source surface also was derived.

Our results showed that coating the radionuclide with the materials especially high Z (Gold and Platinum) materials may produce a dual emitter radiation source, X-ray photon and β- ray and is capable of killing the cancer cells more than the source with not-coated source.

Our conclusion was that coating the β- ray emitter radionuclides, especially high-energy β- ray, enhances its therapeutical capability with X-ray and β- ray emission. The studied coated sources in our study were performed as a dual radiation source; produced X-ray and β-ray, which increases the therapeutic efficiency of the source.

Attention Deficit Hyperactivity Disorder (ADHD) is now recognized as the most common childhood behavioral disorder. This disorder causes school problems and social incompatibility. Thus an accurate diagnosis can help diminish such problems. In this paper, we propose a brain connectomics approach based on eyes-open resting state Magnetoencephalography (rs-MEG) to diagnose subjects with ADHD from Healthy Controls (HC).

We used the eyes-open rs-MEG signals recorded from 25 subjects with ADHD and 25 HC. We calculated Coherence (COH) between the MEG sensors in the conventional frequency bands (i.e., delta, theta, alpha, beta, and gamma), selected the most discriminative COH measures by the Neighborhood Component Analysis (NCA), and fed them to three classifiers, including Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel, K-Nearest Neighbors (KNN), and Decision Tree to classify ADHD and HC.

We achieved the best average accuracy of 91.1% for a single-band classifier based on the COH in the delta-band as an input feature of the SVM. However, when we integrated the COH values of all frequency bands as input features, the average accuracy was slightly improved to 92.7% using the SVM classifier.

Our results demonstrate the capability of a functional connectomics approach based on rs-MEG for the diagnosis of ADHD. It is noteworthy that, to the best of our knowledge, COH has not yet been used to diagnose ADHD using rs-MEG data. Furthermore, there is no study on diagnosing ADHD using eyes-open rs-MEG. Thus, a novelty of our proposed method is to use COH and eyes-open rs-MEG data to diagnose ADHD. Moreover, our proposed method showed promising results compared with previous rs-MEG studies for the diagnosis of ADHD.

Ionizing radiation-absorbed doses is a crucial concern in Cone-Beam Computed Tomography (CBCT) and panoramic radiography. This study aimed to evaluate and compare the Entrance Skin Doses (ESD) of thyroid and parotid gland regions in CBCT and panoramic radiography in Yazd province, Iran.

In this cross-sectional study, 332 patients were included, who were then divided into two age groups (adult and pediatric) and underwent dental CBCT and panoramic radiography. Twelve Thermoluminescence Dosimeters (TLD- GR200) were used for each patient to measure the ESD of thyroid and parotid glands. The differences between the ESD values in CBCT and panoramic examinations as well as between the adults and children groups were evaluated by one-way ANOVA and Man-Whitney tests.

The mean and Standard Deviation (SD) values of ESD in panoramic imaging were equal to 61 ± 4 and 290 ± 12 µGy for the thyroid and parotid glands of the adult groups, respectively. Notably, these values for CBCT were significantly higher (P<0.01), as 377 ± 139 and 1554 ± 177 µGy, respectively. Moreover, the mean ESD values in the panoramic examination were 41 ± 3 and 190 ± 16 µGy for thyroid and parotid glands for the children group, while they were 350 ± 120 and 990 ± 107 µGy in CBCT (P<0.01), respectively. The ESD values in the parotid gland were approximately 3.4 (2.8-4.1) and 4.7 (4.6-4.8) times greater than those for CBCT and panoramic examinations, respectively.

Although CBCT provides supplementary diagnostic advantages, the thyroid and parotid glands’ doses are higher than panoramic radiography. Therefore, the risks and benefits of each method should be considered before their prescription.

Brain-Computer Interface (BCI) systems are a new channel of communication between human thoughts and machines without the aid of neuromuscular systems. Although BCI systems exhibit several advantages, they yet have a long road ahead to reach a flawless state. For example, error occurrence is one of the problems in these systems, leading to Error-Related Potentials (ErRP) in the brain signal. In this study, Electroencephalogram (EEG) signals in the condition of system error occurrence are investigated. Since local information on the EEG signal channels alone cannot reveal the secrets of the brain, functional connectivity was used as a feature in this research.

In this research, 32 channel EEG signals with a sampling frequency of 256 Hz were recorded from 18 participants while interacting with a BCI system which has an interaction error. Two types of stimulus were used, including visual and tactile ones. Moreover, the Inter-Stimulus-Interval (ISI) was changed during the task. After pre-processing, brain functional connectivity was calculated between all channel pairs in four groups (visual, tactile, combined visual-tactile (ISI=3.5), and combined visual-tactile (ISI=2)) using Magnitude-Squared Coherence (MSC) measure.

The results showed a significant difference in frontal-right temporal connectivity between correct and error classes in tactile stimulation, in visual stimulation significant differences in frontal-occipital connectivity, in visual-tactile (ISI=3.5) stimulation significant differences in left temporal-occipital connectivity (P-value< 0.001), and in visual-tactile (ISI=2) stimulation significant differences in central-occipital connectivity were seen (P-value< 0.01).

This study shows that using brain functional connectivity features along with local features can improve the performance of BCI systems.

Diffusion Magnetic Resonance Imaging (dMRI) has widely been used as a part of breast MRI protocols throughout the world, providing valuable information about breast tissue structures. This method has the potential to improve the characterization of benign and malignant breast lesions thereby guiding treatment decisions. DMRI as a non-contrast approach has certain benefits in comparison with the Dynamic Contrast Enhanced (DCE) method. Particularly, dMRI does not need intravenous contrast, which makes the imaging process faster and easier. Although there are still concerns about dMRI images quality, advances in the acquisition methods seem to be promising. More advanced dMRI strategies, such as Diffusion Tensor Imaging (DTI) and Intravoxel Incoherent Motion (IVIM), not only improve diagnosis accuracy, but also present new information about tissue perfusion. This review will present an overview of dMRI in the characterization of breast cancers.

Coronavirus disease (COVID-19) has killed a large number of people, threatening public health around the world. Many drugs and materials that have an antiviral therapeutic effect are still being tested, including silver nanoparticles.

It has been proven that Synthesis of silver Nanoparticles (Ag NPs) (Ag NPs) possess strong antifungal, antibacterial, anti-angiogenesis, and anti-inflammatory potential. Green synthesized of Ag NPs are a promising source of new antiviral agents considering the multiplicity of its mechanism and the multiple target areas in the virus. The Ag NPs or Ag+ ions, which are released from the Ag NPs, interact directly with some biological molecules of the viruses that contain phosphorous or sulfur, such as some proteins, Deoxyribonucleic Acid (DNA), and Ribonucleic Acid (RNA).

This reaction generates Reactive Oxygen Species (ROS), causing damage to the membranes in the virus. Metal nano-therapies such as Ag NPs are granted research consideration for COVID-19 treatment.

The biocompatibility achieved through green synthesis suggests its possible use not only in these specific coronavirus conditions but also in other types of virus infections without any risk of toxicity of these molecules.