Comparison of effective radiation doses from X-ray, CT, and PET/CT in pediatric patients with neuroblastoma using a dose monitoring program

PURPOSE:We aimed to evaluate the use of a dose monitoring program for calculating and comparing the diagnostic radiation doses in pediatric patients with neuroblastoma.METHODS:We retrospectively reviewed diagnostic and therapeutic imaging studies performed on pediatric patients with neuroblastoma from 2003 to 2014. We calculated the mean effective dose per exam for X-ray, conventional computed tomography (CT), and CT of positron emission tomography/computed tomography (PET/CT) from the data collected using a dose monitoring program (DoseTrack group) since October 2012. Using the data, we estimated the cumulative dose per person and the relative dose from each modality in all patients (Total group). The effective dose from PET was manually calculated for all patients.RESULTS:We included 63 patients with a mean age of 3.2±3.5 years; 28 had a history of radiation therapy, with a mean irradiated dose of 31.9±23.2 Gy. The mean effective dose per exam was 0.04±0.19 mSv for X-ray, 1.09±1.11 mSv for CT, and 8.35±7.45 mSv for CT of PET/CT in 31 patients of the DoseTrack group. The mean estimated cumulative dose per patient in the Total group was 3.43±2.86 mSv from X-ray (8.5%), 7.66±6.09 mSv from CT (19.1%), 18.35±13.52 mSv from CT of PET/CT (45.7%), and 10.71±10.05 mSv from PET (26.7%).CONCLUSION:CT of PET/CT contributed nearly half of the total cumulative dose in pediatric patients with neuroblastoma. The radiation dose from X-ray was not negligible because of the large number of X-ray images. A dose monitoring program can be useful for calculating radiation doses in patients with cancer

DiGeorge syndrome who developed lymphoproliferative mediastinal mass

DiGeorge syndrome is an immunodeficient disease associated with abnormal development of 3rd and 4th pharyngeal pouches. As a hemizygous deletion of chromosome 22q11.2 occurs, various clinical phenotypes are shown with a broad spectrum. Conotruncal cardiac anomalies, hypoplastic thymus, and hypocalcemia are the classic triad of DiGeorge syndrome. As this syndrome is characterized by hypoplastic or aplastic thymus, there are missing thymic shadow on their plain chest x-ray. Immunodeficient patients are traditionally known to be at an increased risk for malignancy, especially lymphoma. We experienced a 7-year-old DiGeorge syndrome patient with mediastinal mass shadow on her plain chest x-ray. She visited Severance Children's Hospital hospital with recurrent pneumonia, and throughout her repeated chest x-ray, there was a mass like shadow on anterior mediastinal area. We did full evaluation including chest computed tomography, chest ultrasonography, and chest magnetic resonance imaging. To rule out malignancy, video assisted thoracoscopic surgery was done. Final diagnosis of the mass which was thought to be malignancy, was lymphoproliferative lesion

Purification and characterization of angiotensin-1 converting enzyme (ACE)-inhibitory peptide from the jellyfish, Nemopilema nomurai

The Nemopilema nomurai hydrolysate was produced by the reaction of papain, and an angiotensin-Ι converting enzyme (ACE)-inhibitory peptide was purified by using the molecular cut-offs membrane filter, the gel filtration chromatography with Sephadex LH-20 and the reverse phase chromatographic method using C18 and C12 columns. Purification yield of the active peptide was estimated to be 0.2 ± 0.1%, starting from the lyophilized jellyfish. The infrared (IR), proton nuclear magnetic resonance spectroscopy (1H NMR), carbon nuclear magnetic resonance (13C NMR) and mass spectrometry (MS) spectrometer analyses elucidated that the structure of the purified peptide is tyrosine-isoleucine (Tyr-Ile). The inhibitory concentration at 50% (IC50) and Ki values were calculated to be 2.0 ± 0.3 μg/ml and 3.3 ± 0.3 μM, respectively, which acts as a competitive inhibitor to ACE.Keywords: Angiotensin-Ι converting enzyme, Jellyfish, Nemopilema nomurai, Papain hydrolysate, Tyrosine-IsoleucineAfrican Journal of Biotechnology Vol. 12(15), pp. 1888-189

High-performance organic semiconductors for thin-film transistors based on 2,6-bis(2-thienylvinyl)anthracene

We have synthesized two novel organic semiconductors, which have a symmetrically substituted thienylvinylene anthracene backbone. They show good electrical performances on SiO2/Si, with high field-effect mobilities of up to 0.4 cm2 V-1 s-1, and can easily be synthesized in large quantities. In addition, the high mobility of such semiconductors can be achieved at low substrate deposition temperatures.This work was supported by grants (F0004030-2007-23, F0004071-2007-23) from the Information Display R&D Center, one of the 21st Century Frontier R&D Programs funded by the Ministry of Commerce, Industry, and Energy of the Korean Government, and Seoul R&BD

Management of Complex Regional Pain Syndrome Type 1 With Total Spinal Block

Complex regional pain syndrome (CRPS) is a painful and disabling disorder that can affect one or more extremities. Unfortunately, the knowledge concerning its natural history and mechanism is very limited and many current rationales in treatment of CRPS are mainly dependent on efficacy originated in other common conditions of neuropathic pain. Therefore, in this study, we present a case using a total spinal block (TSB) for the refractory pain management of a 16-year-old male CRPS patient, who suffered from constant stabbing and squeezing pain, with severe touch allodynia in the left upper extremity following an operation of chondroblastoma. After the TSB, the patient's continuous and spontaneous pain became mild and the allodynia disappeared and maintained decreased for 1 month

CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article

ACT-PRESTO: Rapid and consistent tissue clearing and labeling method for 3-dimensional (3D) imaging

Understanding the structural organization of organs and organisms at the cellular level is a fundamental challenge in biology. This task has been approached by reconstructing three-dimensional structure from images taken from serially sectioned tissues, which is not only labor-intensive and time-consuming but also error-prone. Recent advances in tissue clearing techniques allow visualization of cellular structures and neural networks inside of unsectioned whole tissues or the entire body. However, currently available protocols require long process times. Here, we present the rapid and highly reproducible ACT-PRESTO (active clarity technique-pressure related efficient and stable transfer of macromolecules into organs) method that clears tissues or the whole body within 1 day while preserving tissue architecture and protein-based signals derived from endogenous fluorescent proteins. Moreover, ACT-PRESTO is compatible with conventional immunolabeling methods and expedites antibody penetration into thick specimens by applying pressure. The speed and consistency of this method will allow high-content mapping and analysis of normal and pathological features in intact organs and bodies.1

Improving the Performance of Heterogeneous Network Systems in Machine Learning-based 5G Mobile Communication System

Mobile traffic, which has increased significantly with the emergence of Fourth generation longterm evolution (4G-LTE) communications and advances in video streaming services, is still currently increasing at an incredible pace. Fifth-generation (5G) mobile communication systems, which were developed to deal with such a drastic increase in mobile traffic, aim to achieve ultra-high-speed data transmission, low latency, and the accommodation of many more connected devices compared to 4G-LTE systems. 5G communication uses high-frequency bandwidth to implement these features, which leads to an inevitable drawback of a high path loss. In order to overcome this disadvantage, small cell technology was developed, and is defined as small, low-power base stations that can extend the network coverage and solve the shadow area problem. Although small cell technology has these advantages, different problems, such as the effects of interference due to the deployment of a large number of small cells and the differences in devices accessing the network, need to be solved. To do so, it is necessary to develop an algorithm for a service method. However, general algorithms have difficulties in responding to the diverse environment of mobile communication systems, such as sudden increase in traffic in certain areas or sudden changes in the mobile population, and machine learning technology has been applied to solve this problem. This study employs a machine learning algorithm to determine small cell connections. In addition, a 5G macro system, the application of small cells, and the application of machine learning algorithms are compared to determine the performance improvement in the machine learning algorithm. Moreover, Support Vector Machine (SVM), Logistic Regression and Decision Tree algorithm are employed to show a training method that uses basic training data and a small cell on-off method, and the performance enhancement is verified based on this method