Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimers disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The time orientation and 3-word recall score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.The publication costs, design of the study, data management and writing the manuscript for this article were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538), Korea Ministry of Health & Welfare, and from the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Korean Government (MSIP; No. 2014M3C7A1064752)

Differences in Clinical Features According to Boryoung and Karp Genotypes of Orientia tsutsugamushi

Scrub typhus is an infectious disease caused by Orientia tsutsugamushi. The differences in virulence of O. tsutsugamushi prototypes in humans are still unknown. We investigated whether there are any differences in the clinical features of the Boryoung and Karp genotypes.Patients infected with O. tsutsugamushi, as Boryoung and Karp clusters, who had visited 6 different hospitals in southwestern Korea were prospectively compared for clinical features, complications, laboratory parameters, and treatment responses. Infected patients in the Boryoung cluster had significantly more generalized weakness, eschars, skin rashes, conjunctival injection, high albumin levels, and greater ESR and fibrinogen levels compared to the Karp cluster. The treatment response to current antibiotics was significantly slower in the Karp cluster as compared to the Boryoung cluster.The frequency of occurrence of eschars and rashes may depend on the genotype of O. tsutsugamushi

Standardization of the methods and reference materials used to assess virus content in varicella vaccines

BACKGROUND: In Korea, every vaccine lot is tested by the National Center for Lot Release (NCLR) in accordance with the national lot release procedures to ensure the safety and efficacy of vaccines. These quality tests examine the virus content in varicella vaccines via plaque assays (either the agar overlay method [AOM] or plaque staining method [PSM]), according to the procedures suggested by the Korean Reference Material for the Varicella Vaccine (KRMVV) or the manufacturer’s standard in-house protocol. AIM: To standardize the virus content tests, viral titers in the KRMVV were measured using the PSM at four participating laboratories in a collaborative study. With the aim of developing a standardized method using the KRMVV as a positive control, we compared the ability of the two test methods, AOM and PSM, to accurately and reproducibly determine the virus content of two commercial varicella vaccines. RESULTS: The results showed that the standardized method (PSM) was more suitable for quality control analysis of the varicella vaccine. CONCLUSION: Use of a standardized method (PSM) according to the Korean reference material will improve the reliability and objectivity of lot release testing

Clinical Characteristics of a Nationwide Hospital-based Registry of Mild-to-Moderate Alzheimer's Disease Patients in Korea: A CREDOS (Clinical Research Center for Dementia of South Korea) Study

With rapid population aging, the socioeconomic burden caused by dementia care is snowballing. Although a few community-based studies of Alzheimer's disease (AD) have been performed in Korea, there has never been a nationwide hospital-based study thereof. We aimed to identify the demographics and clinical characteristics of mild-to-moderate AD patients from the Clinical Research Center for Dementia of Korea (CREDOS) registry. A total of 1,786 patients were consecutively included from September 2005 to June 2010. Each patient underwent comprehensive neurological examination, interview for caregivers, laboratory investigations, neuropsychological tests, and brain MRI. The mean age was 74.0 yr and the female percentage 67.0%. The mean period of education was 7.1 yr and the frequency of early-onset AD (< 65 yr old) was 18.8%. Among the vascular risk factors, hypertension (48.9%) and diabetes mellitus (22.3%) were the most frequent. The mean score of the Korean version of Mini-Mental State Examination (K-MMSE) was 19.2 and the mean sum of box scores of Clinical Dementia Rating (CDR-SB) 5.1. Based on the well-structured, nationwide, and hospital-based registry, this study provides the unique clinical characteristics of AD and emphasizes the importance of vascular factors in AD in Korea

Sublingual Immunization with M2-Based Vaccine Induces Broad Protective Immunity against Influenza

The ectodomain of matrix protein 2 (M2e) of influenza A virus is a rationale target antigen candidate for the development of a universal vaccine against influenza as M2e undergoes little sequence variation amongst human influenza A strains. Vaccine-induced M2e-specific antibodies (Abs) have been shown to display significant cross-protective activity in animal models. M2e-based vaccine constructs have been shown to be more protective when administered by the intranasal (i.n.) route than after parenteral injection. However, i.n. administration of vaccines poses rare but serious safety issues associated with retrograde passage of inhaled antigens and adjuvants through the olfactory epithelium. In this study, we examined whether the sublingual (s.l.) route could serve as a safe and effective alternative mucosal delivery route for administering a prototype M2e-based vaccine. The mechanism whereby s.l. immunization with M2e vaccine candidate induces broad protection against infection with different influenza virus subtypes was explored.A recombinant M2 protein with three tandem copies of the M2e (3M2eC) was expressed in Escherichia coli. Parenteral immunizations of mice with 3M2eC induced high levels of M2e-specific serum Abs but failed to provide complete protection against lethal challenge with influenza virus. In contrast, s.l. immunization with 3M2eC was superior for inducing protection in mice. In the latter animals, protection was associated with specific Ab responses in the lungs.The results demonstrate that s.l. immunization with 3M2eC vaccine induced airway mucosal immune responses along with broad cross-protective immunity to influenza. These findings may contribute to the understanding of the M2-based vaccine approach to control epidemic and pandemic influenza infections

Standardization of the methods and reference materials used to assess virus content in varicella vaccines

Background: In Korea, every vaccine lot is tested by the National Center for Lot Release (NCLR) in accordance with the national lot release procedures to ensure the safety and efficacy of vaccines. These quality tests examine the virus content in varicella vaccines via plaque assays (either the agar overlay method [AOM] or plaque staining method [PSM]), according to the procedures suggested by the Korean Reference Material for the Varicella Vaccine (KRMVV) or the manufacturer&apos;s standard in-house protocol. Aim: To standardize the virus content tests, viral titers in the KRMVV were measured using the PSM at four participating laboratories in a collaborative study. With the aim of developing a standardized method using the KRMVV as a positive control, we compared the ability of the two test methods, AOM and PSM, to accurately and reproducibly determine the virus content of two commercial varicella vaccines. Results: The results showed that the standardized method (PSM) was more suitable for quality control analysis of the varicella vaccine. Conclusion: Use of a standardized method (PSM) according to the Korean reference material will improve the reliability and objectivity of lot release testing.Y

Standardization of the methods and reference materials used to assess virus content in varicella vaccines

Background In Korea, every vaccine lot is tested by the National Center for Lot Release (NCLR) in accordance with the national lot release procedures to ensure the safety and efficacy of vaccines. These quality tests examine the virus content in varicella vaccines via plaque assays (either the agar overlay method [AOM] or plaque staining method [PSM]), according to the procedures suggested by the Korean Reference Material for the Varicella Vaccine (KRMVV) or the manufacturers standard in-house protocol. Aim To standardize the virus content tests, viral titers in the KRMVV were measured using the PSM at four participating laboratories in a collaborative study. With the aim of developing a standardized method using the KRMVV as a positive control, we compared the ability of the two test methods, AOM and PSM, to accurately and reproducibly determine the virus content of two commercial varicella vaccines. Results The results showed that the standardized method (PSM) was more suitable for quality control analysis of the varicella vaccine. Conclusion Use of a standardized method (PSM) according to the Korean reference material will improve the reliability and objectivity of lot release testing

Position Classification of the Endotracheal Tube with Automatic Segmentation of the Trachea and the Tube on Plain Chest Radiography Using Deep Convolutional Neural Network

Background: This study aimed to develop an algorithm for multilabel classification according to the distance from carina to endotracheal tube (ETT) tip (absence, shallow &gt; 70 mm, 30 mm &le; proper &le; 70 mm, and deep position &lt; 30 mm) with the application of automatic segmentation of the trachea and the ETT on chest radiographs using deep convolutional neural network (CNN). Methods: This study was a retrospective study using plain chest radiographs. We segmented the trachea and the ETT on images and labeled the classification of the ETT position. We proposed models for the classification of the ETT position using EfficientNet B0 with the application of automatic segmentation using Mask R-CNN and ResNet50. Primary outcomes were favorable performance for automatic segmentation and four-label classification through five-fold validation with segmented images and a test with non-segmented images. Results: Of 1985 images, 596 images were manually segmented and consisted of 298 absence, 97 shallow, 100 proper, and 101 deep images according to the ETT position. In five-fold validations with segmented images, Dice coefficients [mean (SD)] between segmented and predicted masks were 0.841 (0.063) for the trachea and 0.893 (0.078) for the ETT, and the accuracy for four-label classification was 0.945 (0.017). In the test for classification with 1389 non-segmented images, overall values were 0.922 for accuracy, 0.843 for precision, 0.843 for sensitivity, 0.922 for specificity, and 0.843 for F1-score. Conclusions: Automatic segmentation of the ETT and trachea images and classification of the ETT position using deep CNN with plain chest radiographs could achieve good performance and improve the physician&rsquo;s performance in deciding the appropriateness of ETT depth