Chlorpromazine inhibits EAG1 channels by altering the coupling between the PAS, CNBH and pore domains.

EAG1 depolarization-activated potassium selective channels are important targets for treatment of cancer and neurological disorders. EAG1 channels are formed by a tetrameric subunit assembly with each subunit containing an N-terminal Per-Arnt-Sim (PAS) domain and C-terminal cyclic nucleotide-binding homology (CNBH) domain. The PAS and CNBH domains from adjacent subunits interact and form an intracellular tetrameric ring that regulates the EAG1 channel gating, including the movement of the voltage sensor domain (VSD) from closed to open states. Small molecule ligands can inhibit EAG1 channels by binding to their PAS domains. However, the allosteric pathways of this inhibition are not known. Here we show that chlorpromazine, a PAS domain small molecule binder, alters interactions between the PAS and CNBH domains and decreases the coupling between the intracellular tetrameric ring and the pore of the channel, while having little effect on the coupling between the PAS and VSD domains. In addition, chlorpromazine binding to the PAS domain did not alter Cole-Moore shift characteristic of EAG1 channels, further indicating that chlorpromazine has no effect on VSD movement from the deep closed to opened states. Our study provides a framework for understanding global pathways of EAG1 channel regulation by small molecule PAS domain binders.

Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.

Acute lymphoblastic leukemia (ALL) is a life-threatening disease that commonly affects children and is classified into three subtypes: L1, L2, and L3. Traditionally, ALL is diagnosed through morphological analysis, involving the examination of blood and bone marrow smears by pathologists. However, this manual process is time-consuming, laborious, and prone to errors. Moreover, the significant morphological similarity between ALL and various lymphocyte subtypes, such as normal, atypic, and reactive lymphocytes, further complicates the feature extraction and detection process. The aim of this study is to develop an accurate and efficient automatic system to distinguish ALL cells from these similar lymphocyte subtypes without the need for direct feature extraction. First, the contrast of microscopic images is enhanced using histogram equalization, which improves the visibility of important features. Next, a fuzzy C-means clustering algorithm is employed to segment cell nuclei, as they play a crucial role in ALL diagnosis. Finally, a novel convolutional neural network (CNN) with three convolutional layers is utilized to classify the segmented nuclei into six distinct classes. The CNN is trained on a labeled dataset, allowing it to learn the distinguishing features of each class. To evaluate the performance of the proposed model, quantitative metrics are employed, and a comparison is made with three well-known deep networks: VGG-16, DenseNet, and Xception. The results demonstrate that the proposed model outperforms these networks, achieving an approximate accuracy of 97%. Moreover, the model's performance surpasses that of other studies focused on 6-class classification in the context of ALL diagnosis. RESEARCH HIGHLIGHTS: Deep neural networks eliminate the requirement for feature extraction in ALL classification The proposed convolutional neural network achieves an impressive accuracy of approximately 97% in classifying six ALL and lymphocyte subtypes.

Evaluating dose distributions of high dose rate 60Co brachytherapy in an asymmetric tumor: A comparison of different designs of vaginal cylindrical applicators.

The aim of this study is to evaluate organ-at-risk (OAR) doses obtained from different designs of intracavitary cylinder applicators during high-dose-rate (HDR) brachytherapy of an asymmetric vaginal tumor. Dose distributions around five cylinder applicators were obtained using the Geant4 toolkit. Three of these applicators are commercially available: single-channel, multi-channel, and shielded. Additionally, two proposed sub-configurations were evaluated: (I) a combination of the multichannel applicator with a central shield and (II) a dynamically modulated cylinder (DMC). The dose distributions of the proposed applicators were compared to those of the single-channel cylinder applicator. The results showed that using a cylindrical applicator with a higher degree of freedom in plan optimization can improve OAR, sparing up to 60% for the rectum and 20% for the bladder. In conclusion, this work suggests using a new design of a cylindrical applicator to enhance the therapeutic ratio of brachytherapy for asymmetric and irregularly shaped vaginal tumors.

Investigation of TG-43 Dosimetric Parameters for 192Ir Brachytherapy Source Using GATE Monte Carlo Code.

Purpose: According to the revised Task Group number 43 recommendations, a brachytherapy source must be validated against a similar or identical source before its clinical application. The purpose of this investigation is to verify the dosimetric data of the high dose rate (HDR) BEBIG 192Ir source (Ir2.A85-2). Materials and Methods: The HDR 192Ir encapsulated seed was simulated and its main dosimetric data were calculated using Geant4 Application for Tomographic Emission (GATE) simulation code. Cubic cells were used for the calculation of dose rate constant and radial dose function while for anisotropy function ring cells were used. DoseActors were simulated and attached to the respective cells to obtain the required data. Results: The dose rate constant was obtained as 1.098 ± 0.003 cGy.h - 1.U - 1, differing by 1.0% from the reference value reported by Granero et al. Similarly, the calculated values for radial dose and anisotropy functions presented good agreement with the results obtained by Granero et al. Conclusion: The results of this study suggest that the GATE Monte Carlo code is a valid toolkit for benchmarking brachytherapy sources and can be used for brachytherapy simulation-based studies and verification of brachytherapy treatment planning systems.

Molecular mechanism of EAG1 channel inhibition by imipramine binding to the PAS domain.

Ether-a-go-go (EAG) channels are key regulators of neuronal excitability and tumorigenesis. EAG channels contain an N-terminal Per-Arnt-Sim (PAS) domain that can regulate currents from EAG channels by binding small molecules. The molecular mechanism of this regulation is not clear. Using surface plasmon resonance and electrophysiology we show that a small molecule ligand imipramine can bind to the PAS domain of EAG1 channels and inhibit EAG1 currents via this binding. We further used a combination of molecular dynamics (MD) simulations, electrophysiology, and mutagenesis to investigate the molecular mechanism of EAG1 current inhibition by imipramine binding to the PAS domain. We found that Tyr71, located at the entrance to the PAS domain cavity, serves as a "gatekeeper" limiting access of imipramine to the cavity. MD simulations indicate that the hydrophobic electrostatic profile of the cavity facilitates imipramine binding and in silico mutations of hydrophobic cavity-lining residues to negatively charged glutamates decreased imipramine binding. Probing the PAS domain cavity-lining residues with site-directed mutagenesis, guided by MD simulations, identified D39 and R84 as residues essential for the EAG1 channel inhibition by imipramine binding to the PAS domain. Taken together, our study identified specific residues in the PAS domain that could increase or decrease EAG1 current inhibition by imipramine binding to the PAS domain. These findings should further the understanding of molecular mechanisms of EAG1 channel regulation by ligands and facilitate the development of therapeutic agents targeting these channels.

Lactobacillus casei condition medium downregulates miR-21 relative expression in HT-29 colorectal cancer cell line.

Previous research has demonstrated promising outcomes regarding the advantageous impact of probiotics in both cancer prevention and treatment. Nevertheless, the precise molecular mechanisms underpinning these effects remain elusive. Recent investigations have proposed a potential involvement of micro ribonucleic acids (miRNAs) in mediating the favorable influence of probiotics on cancerous cells. This study was designed to evaluate the effect of Lactobacillus casei condition medium on miR-21 relative expression in HT-29 colorectal cancer cells. Lactobacillus casei condition medium mixed with RPMI in different proportions (1:1, 1:3, and 1:7) and utilized to treat HT-29 cells for 24 and 48 h. Subsequently, percentage of early and late apoptotic cells were identified using a flow cytometry instrument. A real-time polymerase chain reaction was carried out to determine the relative expression of miR-21. Our findings revealed that L. casei condition medium induces apoptosis in a time- and dose-dependent manner in HT-29 cells. Furthermore, we found a significantly downregulated miR-21 after treatment with high doses of L. casei condition medium after 48 h. Overall, our results provide valuable insights into a potential mechanism through which L. casei condition medium mediates its apoptotic effect in colorectal cancer cells through downregulation of miR-21. However, further investigations are required to unravel its therapeutic, diagnostic, and treatment monitoring potential.

Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study.

This study aimed to investigate the diagnostic performance of machine learning-based radiomics analysis to diagnose coronary artery disease status and risk from rest/stress Myocardial Perfusion Imaging (MPI) single-photon emission computed tomography (SPECT). A total of 395 patients suspicious of coronary artery disease who underwent 2-day stress-rest protocol MPI SPECT were enrolled in this study. The left ventricle myocardium, excluding the cardiac cavity, was manually delineated on rest and stress images to define a volume of interest. Added to clinical features (age, sex, family history, diabetes status, smoking, and ejection fraction), a total of 118 radiomics features, were extracted from rest and stress MPI SPECT images to establish different feature sets, including Rest-, Stress-, Delta-, and Combined-radiomics (all together) feature sets. The data were randomly divided into 80% and 20% subsets for training and testing, respectively. The performance of classifiers built from combinations of three feature selections, and nine machine learning algorithms was evaluated for two different diagnostic tasks, including 1) normal/abnormal (no CAD vs. CAD) classification, and 2) low-risk/high-risk CAD classification. Different metrics, including the area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE), were reported for models' evaluation. Overall, models built on the Stress feature set (compared to other feature sets), and models to diagnose the second task (compared to task 1 models) revealed better performance. The Stress-mRMR-KNN (feature set-feature selection-classifier) reached the highest performance for task 1 with AUC, ACC, SEN, and SPE equal to 0.61, 0.63, 0.64, and 0.6, respectively. The Stress-Boruta-GB model achieved the highest performance for task 2 with AUC, ACC, SEN, and SPE of 0.79, 0.76, 0.75, and 0.76, respectively. Diabetes status from the clinical feature family, and dependence count non-uniformity normalized, from the NGLDM family, which is representative of non-uniformity in the region of interest were the most frequently selected features from stress feature set for CAD risk classification. This study revealed promising results for CAD risk classification using machine learning models built on MPI SPECT radiomics. The proposed models are helpful to alleviate the labor-intensive MPI SPECT interpretation process regarding CAD status and can potentially expedite the diagnostic process.

Long Non-Coding RNA Signatures in Lymphopoiesis and Lymphoid Malignancies.

Lymphoid cells play a critical role in the immune system, which includes three subgroups of T, B, and NK cells. Recognition of the complexity of the human genetics transcriptome in lymphopoiesis has revolutionized our understanding of the regulatory potential of RNA in normal lymphopoiesis and lymphoid malignancies. Long non-coding RNAs (lncRNAs) are a class of RNA molecules greater than 200 nucleotides in length. LncRNAs have recently attracted much attention due to their critical roles in various biological processes, including gene regulation, chromatin organization, and cell cycle control. LncRNAs can also be used for cell differentiation and cell fate, as their expression patterns are often specific to particular cell types or developmental stages. Additionally, lncRNAs have been implicated in lymphoid differentiation, such as regulating T-cell and B-cell development, and their expression has been linked to immune-associated diseases such as leukemia and lymphoma. In addition, lncRNAs have been investigated as potential biomarkers for diagnosis, prognosis, and therapeutic response to disease management. In this review, we provide an overview of the current knowledge about the regulatory role of lncRNAs in physiopathology processes during normal lymphopoiesis and lymphoid leukemia.

Conformational Fluctuations in ß2-Microglubulin Using Markov State Modeling and Molecular Dynamics.

Conformational dynamics in proteins can give rise to aggregation prone states during folding, and these kinetically stable states could form oligomers and aggregates. In this study, we investigate the intermediate states and near-folded states of ß2-microglobulin and their physico-chemical properties using molecular dynamics and Markov state modeling. Analysis of hundreds of microseconds simulation show the importance of the edge strands in the misfolded states that give rise to a high exposure of hydrophobic residues in the core of the protein that could initiate oligomerization and aggregate formation. Our study sheds light on the first step of aggregation of ß2m monomers and gave a better picture of the landscape of protein misfolding and aggregation.

Automatic Diagnosis of Stage of COVID-19 Patients using an Ensemble of Transfer Learning with Convolutional Neural Networks Based on Computed Tomography Images.

Background: Diagnosis of the stage of COVID-19 patients using the chest computed tomography (CT) can help the physician in making decisions on the length of time required for hospitalization and adequate selection of patient care. This diagnosis requires very expert radiologists who are not available everywhere and is also tedious and subjective. The aim of this study is to propose an advanced machine learning system to diagnose the stages of COVID-19 patients including normal, early, progressive, peak, and absorption stages based on lung CT images, using an automatic deep transfer learning ensemble. Methods: Different strategies of deep transfer learning were used which were based on pretrained convolutional neural networks (CNNs). Pretrained CNNs were fine-tuned on the chest CT images, and then, the extracted features were classified by a softmax layer. Finally, we built an ensemble method based on majority voting of the best deep transfer learning outputs to further improve the recognition performance. Results: The experimental results from 689 cases indicate that the ensemble of three deep transfer learning outputs based on EfficientNetB4, InceptionResV3, and NasNetlarge has the highest results in diagnosing the stage of COVID-19 with an accuracy of 91.66%. Conclusion: The proposed method can be used for the classification of the stage of COVID-19 disease with good accuracy to help the physician in making decisions on patient care.

Optimization and synthesis of a novel sorbent composite based on magnetic chitosan-amine-functionalized bimetallic MOF for the simultaneous dispersive solid-phase microextraction of four aflatoxins in real water, herbal distillate, and food samples.

Aflatoxins (AFs), an important category of pollutants, are formed in many foods and adversely affect human health. Therefore, their determination is critical to ensuring human food health. An efficient dispersive solid-phase microextraction technique was developed as a simple and straightforward sample preparation technique for determination of four aflatoxins using a high-performance liquid chromatography (HPLC) fluorescence detector. A novel efficient, green sorbent for extracting AFs was synthesized based on hydrothermal and chemical strategies. The amounts of three sorbent components were optimized using a mixture design (simplex lattice design), including 14 experiments. The optimal amount of amino-bimetallic Fe/Ni-MIL-53 nanospheres, chitosan, and magnetic Fe3O4 nanoparticles as sorbent components was 0.87, 0.67, and 0.47 g, respectively. Also, various factors affecting the process of AF determination were studied and optimized in two successive experimental designs, including the definitive screening design and the Box-Behnken design. Under optimal conditions, the linear ranges for measuring aflatoxin B1, aflatoxin B2, aflatoxin G1, and aflatoxin G2 were 0.05-82.6, 0.07-86.4, 0.08-85.7, and 0.07-89.5 ng mL-1, respectively. The relative standard deviations under inter-day and intra-day conditions for measuring AFs at three analyte concentrations were determined in triplicate analysis and were in the ranges of 3.7-4.6% and 4.9-6.1% for water sample analysis, respectively. The qualitative detection limits for determining AFs were between 0.01 and 0.05 ng mL-1. The pre-concentration factor of the method for measuring AFs ranged from 739.7 to 802.1. The proposed method was used for determining AFs in several real samples, including herbal distillate, black tea, corn, and real water samples. The relative recovery and standard deviation were 87.8-97.8% and 4.10-6.82%, respectively.

Effect of cetrimonium carrier micelles on bacterial membranes and extracellular DNA, an in silico study.

Microorganisms do not live as dispersed single cells but rather they form aggregates with extracellular polymeric substances at interfaces. Biofilms are considered efficient life forms because they shield bacteria from biocides and collect dilute nutrients. This is a big concern in industry since the microorganisms can colonize a wide range of surfaces, accelerating material deterioration, colonizing medical devices, contaminating ultrapure drinking water, increasing energy costs and creating focus of infection. Conventional biocides that target a specific component of the bacteria are not effective in the presence of biofilms. Efficient biofilm inhibitors are based on a multitarget approach interacting with the bacteria and the biofilm matrix. Their rationale design requires a thorough understanding of inhibitory mechanisms that are still largely lacking today. Herein we uncover via molecular modelling the inhibition mechanism of cetrimonium 4-OH cinnamate (CTA-4OHcinn). Simulations show that CTA-4OH micelles can disrupt symmetric and asymmetric bilayers, representative of inner and outer bacterial membranes, following three stages: adsorption, assimilation, and defect formation. The main driving force for micellar attack is electrostatic interactions. In addition to disrupting the bilayers, the micelles work as carriers facilitating the trapping of 4OH cinnamate anions within the bilayer upper leaflet and overcoming electrostatic repulsion. The micelles also interact with extracellular DNA (e-DNA), which is one of the main components of biofilms. It is observed that CTA-4OHcinn forms spherical micelles on the DNA backbone; which hinders their ability to pack. This is demonstrated by modelling the DNA along the hbb histone-like protein, showing that in the presence of CTA-4OHcinn, DNA does not pack properly around hbb. The abilities of CTA-4OHcinn to cause cell death through membrane disruption and to disperse a mature, multi-species biofilm are also confirmed experimentally.

The Effect of Acetyl-L-Carnitine (ALCAR) on Peripheral Nerve Regeneration in Animal Models: A Systematic Review.

Peripheral neuropathies caused by the peripheral nervous system (PNS) damage can occur due to trauma and other disorders. They present as altered sensation, weakness, autonomic symptoms, and debilitating pain syndrome with a wide range of clinical signs. Acetyl-L-Carnitine (ALCAR) is a biological compound with essential roles in mitochondrial oxidative metabolism and anti-oxidant effects that protects mitochondria from oxidative damage and inhibits apoptosis caused by mitochondrial damage. This study is a systematic review and meta-analysis of the effects of ALCAR on peripheral nerve injuries. This review examines studies on treating traumatic peripheral neuropathies in which ALCAR is administered to rats with sciatic nerve injury with an appropriate control group. The articles were divided based on the mode of ALCAR administration. If one method was used in more than one article, their results were entered in the "Revman5.4" software and were meta-analyzed. Studies were selected from 1994 to 2018 on rats with varying physical injuries to their sciatic nerves. In one study, ALCAR was provided to rats in their drinking water, while in other studies, ALCAR was injected intra-peritoneally. Different mechanisms of ALCAR actions have been suggested in this study, but the underpinnings of the neuroprotective effects of ALCAR are still unclear. Further studies are mandatory to clarify the actual mechanisms of the neuroprotective activity of ALCAR. Based on the results of existing studies, ALCAR effectively increases the tolerance threshold of thermal and mechanical stimuli, reduces latency, and reduces apoptosis; finally, adjusting the dose and duration of administration may increase the dose and duration axon diameter.

Developments of Microextraction (Extraction) Procedures for Sample Preparation of Antidepressants in Biological and Water Samples, a Review.

Antidepressants are an important class of drugs to treat various types of depression. The determination of antidepressants is crucial in biological samples to control adverse effects in humans and study pharmacokinetics and bioavailability. Direct measurement of antidepressants in biological and water samples is a considerable challenge for analysts due to their low concentration, the high matrix effects of real samples, and the presence of metabolites of these drugs in biological samples. The challenge leads to using sample preparation processes as a critical step in determining antidepressants. Extraction and microextraction procedures have been widely utilized as sample preparation procedures for these drugs. The purposes of extraction or microextraction methods for antidepressant medications are to preconcentrate the analyte, reduce the matrix effects, increase the selectivity of the procedures, and convert the sample to a suitable format for introducing it into detection systems. In the review, the various extraction and microextraction methods of these drugs in biological, real water, and wastewater samples were investigated. The theory of each technique was briefly addressed to understand the features and factors affecting each method. The extraction and microextraction methods were classified based on their application for antidepressants, and the advantages and disadvantages of each technique were reviewed. The new developments to overcome the limitations of each procedure were discussed. The investigation indicated the number of applications of liquid-phase microextraction for extracting antidepressants has been almost equal to that of solid-phase microextraction.

Incidence risk assessment of secondary cancer due to radiotherapy of women with rectal cancer using BEIR VII, EPA, and ICRP models.

Background: Radiotherapy has a significant side effect known as radiation-induced secondary cancer. This study aims to evaluate the dose and secondary cancer risk for women with rectal cancer treated with three-dimensional conformal radiation therapy (3D-CRT) to the organs at risk (OARs) and some sensitive organs using different types of radiation-induced cancer risk prediction models, including Biological Effects of Ionizing Radiation (BEIRVII), Environmental Protection Agency (EPA) and International Commission on Radiological Protection (ICRP), and compare the results of the different models for same organs. Materials and methods: Thirty female patients with rectal cancer were considered and dose calculations were based on the PCRT-3D treatment planning system, while the radiotherapy of the patients had been performed using Shinva linear accelerator with a total dose of 45 Gy at 25 fractions. Planning target volume (PTV), OARs, and some sensitive organs were contoured, three models were used to evaluate secondary cancer risk (SCR) using the excess relative risk (ERR) and excess absolute risk (EAR). Results: The bladder presents the highest risk, in terms of ERR, and the femur head and uterus in terms of EAR from the three models (BEIR VII, EPA, and ICRP). Conclusion: Based on the obtained results, radiotherapy of rectal cancer is relatively higher for the bladder and femur head, compared to the risk for other organs, the kidney risk is significantly lower. It was observed that the SCR from the ICRP model was higher compared to BEIR VII and EPA models.

Comparison of PRIMO Monte Carlo code and Eclipse treatment planning system in calculation of dosimetric parameters in brain cancer radiotherapy.

Background: It is important to evaluate the dose calculated by treatment planning systems (TPSs) and dose distribution in tumor and organs at risk (OARs). The aim of this study is to compare dose calculated by the PRIMO Monte Carlo code and Eclipse TPS in radiotherapy of brain cancer patients. Materials and methods: PRIMO simulation code was used to simulate a Varian Clinac 600C linac. The simulations were validated for the linac by comparison of the simulation and measured results. In the case of brain cancer patients, the dosimetric parameters obtained by the PRIMO code were compared with those calculated by Eclipse TPS. Gamma function analysis with 3%, 3 mm criteria was utilized to compare the dose distributions. The evaluations were based on the dosimetric parameters for the planning target volume (PTV) and OAR including D min, D mean, and D max, homogeneity index (HI), and conformity index (CI). Results: The gamma function analysis showed a 98% agreement between the results obtained by the PRIMO code and measurement for the percent depth dose (PDD) and dose profiles. The corresponding value in comparing the dosimetric parameters from PRIMO code and Eclipse TPS for the brain patients was 94%, on average. The results of the PRIMO simulation were in good agreement with the measured data and Eclipse TPS calculations. Conclusions: Based on the results of this study, the PRIMO code can be utilized to simulate a medical linac with good accuracy and to evaluate the accuracy of treatment plans for patients with brain cancer.

Assessment of Field-in-Field, 3-Field, and 4-Field Treatment Planning Methods for Radiotherapy of Gastro-Esophageal Junction Cancer.

Background: Gastro-esophageal (GE) junction cancer is the fastest-growing tumor, particularly in the United States (US). Objective: This study aimed to compare dosimetric and radiobiological factors among field-in-field (FIF), three-field (3F), and four-field box (4FB) radiotherapy planning techniques for gastro-esophageal junction cancer. Material and Methods: In this experimental study, thirty patients with GE junction cancer were evaluated, and three planning techniques (field-in-field (FIF), three-field (3F), and four-field box (4FB)) were performed for each patient for a 6-MV photon beam. Dose distribution in the target volume, the monitor units (MUs) required, and the dose delivered to organs at risk (OARs) were compared for these techniques using the paired-sample t-test. Results: A significant difference was measured between the FIF and 3F techniques with respect to conformity index (CI), dose homogeneity index (HI), and tumor control probability (TCP) for the target organ, as well as the Dmean for the heart, kidneys, and liver. For the spinal cord, the FIF technique showed a slight reduction in the maximum dose compared to the other two techniques. In addition, the V20 Gy of the lungs and the normal tissue complication probability (NTCP) of all OARs were reduced with FIF method. Conclusion: The FIF technique showed better performance for treating patients with gastro-esophageal junction tumors, in terms of dose homogeneity in the target, conformity of the radiation field with the target volume, TCP, less dose to healthy organs, and fewer MU.

Intensity-modulated brachytherapy for vaginal cancer.

This study aimed to evaluate the dose modulation potential of static and dynamic steel-shielded applicators using the Geant4 Application for Emission Tomography (GATE) Monte Carlo code for the treatment of vaginal cancer. The GATE TOOLKIT (version 9.0) was used to simulate vaginal cancer intensity-modulated brachytherapy (IMBT) in a pelvic water-equivalent phantom. IMBT performance of a multichannel static and single-channel dynamic steel-shielded applicator was compared to that of a conventional multichannel Plexiglas applicator. DoseActors were defined to calculate the absorbed dose and attached to the voxelized target and organs at risk (OARs). 60Co and 192Ir high-dose-rate seeds were used as irradiation sources. Dynamic IMBT decreased the D2cc of the rectum and bladder by 28.67 and 28.11% using the 60Co source and by 40.00 and 36.34% using the 192Ir source, respectively. Static IMBT decreased the D2cc for the rectum and bladder by 11.69 and 9.29% using the 60Co source and by 22.21 and 17.71% using the 192Ir source, respectively. In contrast, absorbed dose parameters (D5, D90, and D100) for the target in the three techniques showed a mean relative variation of 0.96% (0.00-7.49%) for both sources. Static and dynamic IMBT using steel-shielded applicators provided relatively better OAR protection while maintaining similar target coverage in the treatment of vaginal cancer.

Detection of stage of lung changes in COVID-19 disease based on CT images: a radiomics approach.

The aim of this study is to classify patients suspected from COVID-19 to five stages as normal, early, progressive, peak, and absorption stages using radiomics approach based on lung computed tomography images. Lung CT scans of 683 people were evaluated. A set of statistical texture features was extracted from each CT image. The people were classified using the random forest algorithm as an ensemble method based on the decision trees outputs to five stages of COVID-19 disease. Proposed method attains the highest result with an accuracy of 93.55% (96.25% in normal, 74.39% in early, 100% in progressive, 82.19% in peak, and 96% in absorption stage) compared to the other three common classifiers. Radiomics method can be used for the classification of the stage of COVID-19 disease with good accuracy to help decide the length of time required to hospitalize patients, determine the type of treatment process required for patients in each category, and reduce the cost of care and treatment for hospitalized individuals.

The safety of a novel single-drape cover for sterile back tables in the operating room compared to the standard two-drape method: an experimental study.

BACKGROUND: Covering the prepared sterile back tables (PSBTs) during periods of nonuse and during active surgeries may decrease contamination of sterile surgical instruments that have direct contact to surgical wound. The Association of periOperative Registered Nurses (AORN) declared that an easy method for covering and removing the drape will ultimately be most effective (e.g. standard two-drape method). Hence, this study was designed to test the hypothesis that using a novel single-drape cover had more efficiency and safety in decreasing airborne bacteria-carrying particles (ABCPs) settling on the PSBTs during static and dynamic periods than the standard two-drape method. METHODS: This experimental study was conducted with using 918 agar plates to detect contamination of the PSBTs with ABCPs on two conditions (static and dynamic) at an academic medical center in Kashan, Iran, from September 25, 2021, to January 20, 2022. The contamination of PSBTs was evaluated by 6 agar settle plates (n = 918 in total) on each PSBT in static and dynamic operating room (OR) conditions. At each time-point, this set-up was repeated on two occasions else during data collection, establishing 81 PSBTs in total. Tested groups included the PSBTs covered with the standard two-drape method, the novel single-drape cover, or no cover. The plates were collected after 15, 30, 45, 60, 120, 180, 240 min and 24 h. The primary outcome measured was comparison of mean bioburden of ABCPs settling on covered PSBTs on two conditions by using agar settle plates. The secondary outcomes measured were to determine the role of covering in decreasing contamination of PSBTs and the estimation of time-dependent surgical instrument contamination in the uncovered PSBTs on two conditions by using agar settle plates. RESULTS: Covering the PSBTs during static and dynamic OR conditions lead to a significantly decreased bioburden of ABCPs on them (P < 0.05). No differences were seen between the standard two-drape method and the novel single-drape cover (P > 0.05). CONCLUSIONS: We found that there is no preference for using the novel single-drape cover than the standard two-drape method. Our results showed a significant decrease in bioburden of ABCPs on the PSBTs when those were covered during static and dynamic OR conditions, indicating the efficiency for covering the PSBTs during periods of nonuse and during active surgery.