Choi, Miyoung;Yu, Su-Yeon;Cheong, Chelim;Choe, Young June;Choi, Soo-Han
Pediatric Infection and Vaccine
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v.29
no.1
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pp.28-36
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2022
Purpose: To evaluate the efficacy and safety of coronavirus disease 2019 (COVID-19) vaccines in children aged 5-11 years, a rapid systematic review was conducted on published clinical trials of COVID-19 vaccines and studies that analyzed real-world data on adverse events after COVID-19 vaccination. Methods: A systematic search was conducted on medical literature in international (Ovid-MEDLINE) and pre-published literature databases (medRxiv), followed by handsearching up to January 4, 2022. We used terms including COVID-19, severe acute respiratory syndrome coronavirus 2, and vaccines, and the certainty of evidence was graded using the GRADE approach. Results: A total of 1,675 studies were identified, of which five were finally selected. Among the five studies, four consisted of data from clinical trials of each of the four types of COVID-19 vaccines (BNT162b2, mRNA-1273, CoronaVac, and BBIBP-CorV). The remaining study consisted of real-world data on the safety of the BNT162b2 vaccine in children aged 5-11 years. This systematic review identified that COVID-19 vaccines in recipients aged 5-11 years produced a favorable immune response, and were vaccines were effective against COVID-19. The safety findings for the BNT162b2 vaccine in children and early adolescents aged 5-11 years were similar to those data noted in the clinical trial. Conclusions: There is limited data on COVID-19 vaccines in children aged 5-11 years. Consequently continuous and comprehensive monitoring is necessary for the evaluation of the safety and effectiveness of the COVID-19 vaccines.
Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.
Karaman, M. Muge;Zhou, Christopher Y.;Zhang, Jiaxuan;Zhong, Zheng;Wang, Kezhou;Zhu, Wenzhen
Investigative Magnetic Resonance Imaging
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v.26
no.2
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pp.104-116
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2022
The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm2) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (Dm) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean Dm, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for Dm, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.
Purpose: The traditional ethical study only suggests a blurred insight on the research using medical big data, especially in this rapid-changing and demanding environment which is called "4th Industry Revolution." Current institutional/ethical issues in big data research need to approach with the thoughtful insight of past ethical study reflecting the understanding of present conditions of this study. This study aims to examine the ethical issues that are emerging in recent health care big data research. So, this study aims to survey the public perceptions on of health care big data as part of the process of public discourse and the acceptance of the utility and provision of big data research as a subject of health care information. In addition, the emerging ethical challenges and how to comply with ethical principles in accordance with principles of the Belmont report will be discussed. Methods: Survey was conducted from June 3th August to 6th September 2020. The online survey was conducted through voluntary participation through Internet users. A total of 319 people who completed the survey (±5.49%P [95% confidence level] were analyzed. Results: In the area of the public's perspective, the survey showed that the medical information is useful for new medical development, but it is also necessary to obtain consents from subjects in order to use that medical information for various research purposes. In addition, many people were more concerned about the possibility of re-identifying personal information in medical big data. Therefore, they mentioned the necessity of transparency and privacy protection in the use of medical information. Conclusion: Big data on medical care is a core resource for the development of medicine directly related to human life, and it is necessary to open up medical data in order to realize the public good. But the ethical principles should not be overlooked. The right to self-determination must be guaranteed by means of clear, diverse consent or withdrawal of subjects, and processed in a lawful, fair and transparent manner in the processing of personal information. In addition, scientific and ethical validity of medical big data research is indispensable. Such ethical healthcare data is the only key that will lead to innovation in the future.
Journal of Dental Rehabilitation and Applied Science
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v.38
no.3
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pp.138-149
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2022
The clinical applicability of ceramics can be increased by analyzing the causes of fractures after fracture testing of dental ceramics. Fractography to analyze the cause of fracture of dental ceramics is being widely applied with the development of imaging technologies such as scanning electron microscopy. Setting the experimental conditions is important for accurate interpretation. The fractured specimens should be stored and cleaned to avoid contamination, and metal pretreatment is required for better observation. Depending on the type of fracture, there are dimple rupture, cleavage, and decohesive rupture mainly observed in metals, and fatigue fractures and conchoidal fractures observed in ceramics. In order to reproduce fatigue fracture in the laboratory, which is the main cause of fracture of ceramics, a dynamic loading for observing slow crack growth is essential, and the load conditions and number of loads must be appropriately set. A typical characteristic of a fracture surface of ceramic is a hackle, and the causes of fracture vary depending on the shape of hackle. Fractography is a useful method for in-depth understanding of fractures of dental ceramics, so it is necessary to follow the exact experimental procedure and interpret the results with caution.
Human sparganosis is a food-borne parasitic disease caused by the plerocercoids of Spirometra species. Clinical diagnosis of sparganosis is crucial for effective treatment, thus it is important to identify sensitive and specific antigens of plerocercoids. The aim of the current study was to identify and characterize the immunogenic proteins of Spirometra erinaceieuropaei plerocercoids that were recognized by patient sera. Crude soluble extract of the plerocercoids were separated using 2-dimensional gel electrophoresis coupled with immunoblot and mass spectrometry analysis. Based on immunoblotting patterns and mass spectrometry results, 8 antigenic proteins were identified from the plerocercoid. Among the proteins, cysteine protease protein might be developed as an antigen for diagnosis of sparganosis.
Purpose: This study examined the factors that may affect the growth status of preterm infants. Methods: This study included 91 preterm infants born at <37 weeks of gestation (22.9-36.9 weeks of gestation), including 48 (52.7%) males and 43 (47.3%) females. Diet-related data were collected through parental questionnaires, and growth-related data, such as height and weight, were collected through the hospital medical records. Results: No significant difference in weight and growth was observed between early and late preterm infants. On the other hand, smaller averages of all weight z-score (recent weight at 40 weeks of gestation) included lower birth weight, height, and head circumference. On the other hand, infants' birth weight, height, and head circumference in the weight z-score of <0 (<50% in the age-weight growth chart) was smaller than those in the weight z-score of ≥0. Furthermore, neonatal intensive care unit (NICU) hospitalization period and NICU discharge were shorter with growth cessation age in weight z-score of <0. The weight growth velocity was associated with gestational age, birth weight, and medical treatment in the NICU. Thus, parents of preterm infants with low growth rates prefer more community care services for their children. Conclusion: Birth weight, age of preterm infants, and medical treatment in the NICU were factors related to early birth weight growth. Following NICU discharge, poor intake and intake issues were associated with poor growth after 40 weeks of gestation. Therefore, monitoring the growth of preterm infants requires continuous active involvement and supports for growth-promoting factors after NICU discharge.
Background: In vitro culture of preantral follicles is a promising technology for fertility preservation. Objectives: This study aims to investigate an optimized three-dimensional (3D) fetal bovine serum (FBS)-free preantral follicle culture system having a simple and easy operation. Methods: The isolated follicles from mouse ovaries were randomly divided in an ultra-low attachment 96-well plates supplement with FBS or bovine serum albumin (BSA) culture or encapsulated with an alginate supplement with FBS or BSA culture. Meanwhile, estradiol (E2) concentration was assessed through enzyme-linked immunosorbent assay of culture supernatants. The diameter of follicular growth was measured, and the lumen of the follicle was photographed. Spindle microtubules of oocytes were detected via immunofluorescence. The ability of oocytes to fertilize was assessed using in vitro fertilization. Results: The diameters were larger for the growing secondary follicles cultured in ultra-low attachment 96-well plates than in the alginate gel on days 6, 8, and 10 (p < 0.05). Meanwhile, the E2 concentration in the BSA-supplemented medium was significantly higher in the alginate gel than in the other three groups on days 6 and 8 (p < 0.05), and the oocytes in the FBS-free system could complete meiosis and fertilization in vitro. Conclusions: The present study furnishes insights into the mature oocytes obtained from the 3D culture of the preantral follicle by using ultra-low attachment 96-well plate with an FBS-free system in vitro and supports the clinical practices to achieve competent, mature oocytes for in vitro fertilization.
Objective : The purpose of this study was to investigate the educational status, knowledge, awareness, and readiness for dysphagia therapy among university occupational therapy students. Methods : One hundred and five online questionnaires completed by senior-year students at an occupational therapy university were analyzed. The questionnaire assessed the educational status, knowledge, awareness, and readiness for dysphagia therapy. Descriptive statistics and differences between those with and without practical experience were analyzed. The relationships among educational status, knowledge, and readiness were analyzed. Results : Independent opening of the dysphagia therapy class (69.5%) and experience in dysphagia practice were high (79.0%). Dysphagia education and knowledge in university and practice were moderate and item scores were higher for university education. Knowledge of adult dysphagia therapy was higher than that of pediatric dysphagia therapy. Scores on awareness, knowledge, and readiness for dysphagia therapy were significantly higher among students with practical experience. Conclusion : Education and knowledge of dysphagia therapy were moderate. Knowledge and readiness in adults are higher than in children. Systematic dysphagia therapy education in university and associated practices are needed to enhance the specialty of dysphagia therapy.
Jihyun Mun;Sunhee Kim;Myeong Ju Kim;Jiwon Ryu;Sejoong Kim;Minhwa Chung
Phonetics and Speech Sciences
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v.14
no.4
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pp.45-56
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2022
This paper proposes an optimal methodology for automatically diagnosing and predicting the severity of the chronic kidney disease (CKD) using patients' utterances. In patients with CKD, the voice changes due to the weakening of respiratory and laryngeal muscles and vocal fold edema. Previous studies have phonetically analyzed the voices of patients with CKD, but no studies have been conducted to classify the voices of patients. In this paper, the utterances of patients with CKD were classified using the variety of utterance types (sustained vowel, sentence, general sentence), the feature sets [handcrafted features, extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), CNN extracted features], and the classifiers (SVM, XGBoost). Total of 1,523 utterances which are 3 hours, 26 minutes, and 25 seconds long, are used. F1-score of 0.93 for automatically diagnosing a disease, 0.89 for a 3-classes problem, and 0.84 for a 5-classes problem were achieved. The highest performance was obtained when the combination of general sentence utterances, handcrafted feature set, and XGBoost was used. The result suggests that a general sentence utterance that can reflect all speakers' speech characteristics and an appropriate feature set extracted from there are adequate for the automatic classification of CKD patients' utterances.
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