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Detection of the COVID 19 virus is possible through the reverse transcription-polymerase chain reaction (RT-PCR) kits and computed tomography (CT) images of the lungs. Diagnosis via CT images provides a faster diagnosis than the RT-PCR method does. In addition to low false-negative rate, CT is also used for prognosis in determining the severity of the disease and the proposed treatment method. In this study, we estimated a probability density function (PDF) to examine the infections caused by the virus. We collected 232 chest CT of suspected patients and had them labeled by two radiologists in 6 classes, including a healthy class and 5 classes of different infection severity. To segment the lung lobes, we used a pre-trained U-Net model with an average Dice similarity coefficient (DSC) greater than 0.96. First, we extracted the PDF to grade the infection of each lobe and selected five specific thresholds as feature vectors. We then assigned this feature vector to a support vector machine (SVM) model and made the final prediction of the infection severity. Using the T-Test statistics, we calculated the

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. In more than 90% of all CRC patients, the master oncogenic Ras-Wnt signaling axis is over-activated. MicroRNAs (miRNAs) are potential novel diagnostic and prognostic biomarkers as well as therapeutic targets for several cancers including lung, breast, gastric, and colorectal cancers. Oncogenic or tumor suppressor miRNAs modulate tumor cells proliferation, cell cycle progression, angiogenesis, invasion, and metastasis through regulating oncogenic pathways including Wnt/β-catenin signaling. This review summarizes the current knowledge about the role of Wnt/β-catenin signaling regulatory miRNAs in the pathogenesis of colorectal cancer for a better understanding and hence a better management of this disease.

Background There is controversial evidence about the effect of cerebellar low-frequency stimulation in patients with essential tremor (ET). Objectives In this study we assessed safety and effectiveness of 1 Hz (low-frequency) cerebellar repetitive transcranial magnetic stimulation (rTMS) on tremor severity in patients with essential tremor in a sham-controlled crossover trial. Methods A total of 23 patients assigned into two groups to receive either sham (n = 10) or rTMS (n = 13) treatment, with crossing over after a two-month washout period. Intervention consisted of 900 pulses of 1 Hz rTMS at 90% resting motor threshold or the same protocol of sham stimulation over each cerebellar hemisphere for 5 consecutive days. Tremor severity was assessed by Fahn-Tolosa-Marin (FTM) scale at baseline and at days 5, 12 and 30 after intervention. The FTM consists of 3 subscales including tremor severity rating, performance of motor tasks, and functional disability. Carry-over and treatment effects were analyzed using independent samples t-test. Results There was no significant improvement in the total FTM scores in rTMS compared to the sham stimulation on day 5 (p = 0.132), day 12 (p = 0.574), or day 30 (p = 0.382). Similarly, FTM subscales, including tremor severity rating, motor tasks, and functional disability did not improve significantly after rTMS treatment. Mild headache and local pain were the most frequent adverse events. Conclusion Although cerebellar rTMS seems to have acceptable safety when used in ET patients, this study could not prove any efficacy for it in reduction of tremor in these patients. Larger studies are needed to evaluate efficacy of this therapeutic intervention and to provide evidence about the optimal stimulation parameters.

This paper focuses on using response surface methodology (RSM) and artificial neural network (ANN) to optimize the diameter of Gum tragacanth (GT)/poly(vinyl alcohol) (PVA) nanofibers. However, producing curcumin-loaded GT/PVA nanofibers with using these optimized conditions is another aim. RSM methodology based on four variables (voltage, feed rate, distance between nozzle and collector, and solution concentration) with three levels and ANN technique were compared for modeling the average diameter of nanofibers. In the RSM method, the individual and interaction effects between the parameters on the average diameter of nanofibers were determined using Box-Behnken design (BBD). Data sets of input–output patterns were used for training the multilayer perceptron (MP) neural networks trained with back-propagation algorithm for modeling purpose. Experimental results for both ANN and RSM techniques showed agreement with the predicted fiber diameter. High-regression coefficient between the variables and the response displayed that the performance of RSM for minimizing diameter of nanofibers was better than ANN. Based on response surface model, optimum conditions (polymer concentration of 4.2% (w/v), distance between the capillary and collector 20 cm, applied voltage of 20 kV and flow rate of 0.5 mL/h) were obtained for producing GT/PVA nanofibers with minimized diameter. Then curcumin-loaded GT/PVA nanofibers were produced with acquired optimum condition and the effect of curcumin concentration (3 and 5% (w/v)) on the morphology, diameter and biological properties of nanofibers was investigated.

Repair and regeneration of disorders affecting cardiac and pulmonary tissues through tissue-engineering-based approaches is currently of particular interest. On this matter, different families of bioactive glasses (BGs) have recently been given much consideration with respect to treating refractory diseases of these tissues, such as myocardial infarction. The inherent properties of BGs, including their ability to bond to hard and soft tissues, to stimulate angiogenesis, and to elicit antimicrobial effects, along with their excellent biocompatibility, support these newly proposed strategies. Moreover, BGs can also act as a bioactive reinforcing phase to finely tune the mechanical properties of polymer-based constructs used to repair the damaged cardiac and pulmonary tissues. In the present study, we evaluated the potential of different forms of BGs, alone or in combination with other materials (e.g., polymers), in regards to repair and regenerate injured tissues of cardiac and pulmonary systems.

In this study, we simulated a Siemens E.CAM SPECT system using SIMIND Monte Carlo program to acquire its experimental characterization in terms of energy resolution, sensitivity, spatial resolution and imaging of phantoms using 99m Tc. The experimental and simulation data for SPECT imaging was acquired from a point source and Jaszczak phantom . Verification of the simulation was done by comparing two sets of images and related data obtained from the actual and simulated systems. Image quality was assessed by comparing image contrast and resolution. Simulated and measured energy spectra (with or without a collimator) and spatial resolution from point sources in air were compared. The resulted energy spectra present similar peaks for the gamma energy of 99m Tc at 140 KeV. FWHM for the simulation calculated to14.01 KeV and 13.80 KeV for experimental data, corresponding to energy resolution of 10.01and 9.86% compared to defined 9.9% for both systems, respectively. Sensitivities of the real and virtual gamma cameras were calculated to 85.11 and 85.39 cps/MBq, respectively. The energy spectra of both simulated and real gamma cameras were matched. Images obtained from Jaszczak phantom, experimentally and by simulation, showed similarity in contrast and resolution. SIMIND Monte Carlo could successfully simulate the Siemens E.CAM gamma camera. The results validate the use of the simulated system for further investigation, including modification, planning, and developing a SPECT system to improve the quality of images.

Background: Glutathione reductase is an important enzyme in oxidative metabolism that provides reduced glutathione from its oxidized form in the cells. The role of oxidative stress in tumor tissues has led us to investigate the gene expression and activity of this enzyme in tumor and adjacent resected margins of colorectal cancer tissues, one of the most common malignancies in humans. Methods: We conducted this study on 15 Iranian colorectal cancer patients. RNA was extracted from fresh colon tissues that included tumor and anatomically normal margin tissue. Expression of the glutathione reductase gene was determined using realtime PCR by the ΔΔCt relative quantification method. The gene expression results were standardized with glyceraldehyde 3-phosphate dehydrogenase as the endogenous reference gene. In addition, we measured enzyme activity of glutathione reductase with a commercial kit based on a colorimetric assay. Results: The tumor tissue had higher expression of glutathione reductase compared to the margin tissue (P=0.005). There was significantly greater glutathione reductase enzyme activity in the tumor tissue (116.9±34.31 nmol/min/ml) compared to the noncancerous adjacent tissues (76.7±36.85 nmol/min/ml; P=0.003). Conclusion: These data showed increased glutathione reductase expression and enzyme activity in colorectal tumor tissue. Given the key role of glutathione in synthesis of dNTPs for DNA repair with the glutaredoxin system, the increased glutathione reductase expression and activity might be a reflection of hyperactivity of this enzyme in DNA synthesis and the repair process in colorectal cancer cells.