Cho, Eun-Jung;Choi, Ae Ran;Ryu, Ji Hyeong;Yun, So Jeong;Lee, Woochang;Chun, Sail;Min, Won-Ki;Oh, Eun-Jee
Laboratory Medicine and Quality Assurance
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v.40
no.2
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pp.51-69
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2018
As part of the immunoserology program of the Korean Association of External Quality Assessment Service, we organized two trials on the external quality assessment of hepatitis viral markers in 2016 and 2017. The hepatitis viral antigens and antibodies program consisted of 10 test items. We delivered two and three types of pooled sera specimens to 965 and 965 institutions for the first and second trials of external proficiency testing in 2016, respectively. The number of participating laboratories was 915 (94.8%) and 913 (95.0%) in the first and second trials in 2016, respectively. We also delivered three kinds of pooled sera specimens to 936 and 1,015 institutions for the first and second trials of external proficiency testing in 2017, respectively. The number of participating laboratories was 920 (98.3%) and 996 (98.1%) in the first and second trials in 2017, respectively. The most commonly tested items were hepatitis B surface antigen, followed by the antibodies to hepatitis B surface antigen, anti-hepatitis C virus, hepatitis B envelope antigen, antibodies to hepatitis B envelope antigen, anti-hepatitis A virus and antibodies to hepatitis B core antigen. The most frequently used methods for detecting viral markers were the chemiluminescence immunoassay and the electrochemiluminescence immunoassay, but they yielded a few-false positive results due to the matrix effect. The immunochromatographic assay yielded false-negative results for anti-hepatitis A virus due to low sensitivity. Continuous improvement in the quality of viral hepatitis testing through participation in the survey seems necessary.
Hee-kyu Choi;Yu Rim Kim;Soon Young Hwang;Yeounsu Chu;Pyoungbeom Kim;Hyuk Je Lee
Korean Journal of Environmental Biology
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v.41
no.4
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pp.637-656
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2023
River estuaries are dynamic and productive ecosystems with high regional biodiversity. Environmental DNA (eDNA) has become a useful approach to assessing biodiversity in aquatic ecosystems. This study was conducted to investigate fish community characteristics and species diversity in two river estuary ecosystems, the Taehwa River and Changwon Stream. We further compared conventional and eDNA metabarcoding analyses of the fish communities. The conventional survey was performed in May, July, and October 2022, while the eDNA analysis was conducted only in May. We observed various fish species with different life histories, including carp, goby, and marine fish. We also found that migratory fish, such as dace Tribolodon hakonensis, sweetfish Plecoglossus altivelis, and eel Auguilla japonica, occurred in the Taehwa River, suggesting high river connectivity. Marine fish species were predominant in the Changwon Stream, as this river is located close to the sea. The diversity indices showed that the Taehwa River generally had higher species richness, evenness, and diversity values than the Changwon Stream. A total of 9-19 species were detected in the conventional survey for the three sites, whereas 11-18 species were found from eDNA analysis. The findings indicate that the sensitivity of eDNA was similar to or higher than that of the conventional method. Our study findings suggest the efficiency and efficacy of eDNA-based fish community monitoring, although with some shortcomings in applying the genetic marker to Korean fish, including no clear-cut distinction for Korean endemic species and/or genetically closely related species groups.
Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$$Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.
A total of 197 fecal specimens was prepared for quantitative examination of helminth eggs by modified Kato's cellophane thick smear (M.C.T.S.) and Stoll's dilution egg counting technique (D.E,C.T.). The comparative effectiveness of two techniques was evaluated and conversion function was deduced. The average time required for the microscopic examination on one slide by M.C.T.S. was 12.6 minutes and that of D.E.C.T. was 14.6 minutes. M.C.T.S. showed lower false negative rate than D.E.C.T in light worm burden cases. Functions to convert the counts obtained by M.C.T.S. to E.P.G. by Stoll's dilution egg counting technique were $47.86{\times}10^{0.87{\;}logM.C.T.S.},{\;}$ in A. lumbricoides, $41.69{\times}10^{0.82{\;}logM.C.T.S.}$ in T. trichiura and $63.10{\times}10^{0.85{\;}logM.C.T.S.}$ in C. sinensis. It was suggested M.C.T.S. be better than D.E.C.T. for the quantitative examination of intestinal helminthiases such as A. lumbricoides, T. trichiura, and C. sinensis infections even in the cases with low worm burden.
Thyroid nodules are a common disease in clinical practice. Fine needle aspiration (FNA) is an accurate and safe method for the diagnosis of thyroid nodules. One of the limitations of FNA is the variable rate of unsatisfactory specimens, especially in small sized, deep seated or complex cystic nodules. To overcome this problem, ultrasound-guided FNA (US-FNA) has been widely used. In this study, the clinical usefulness of US-FNA cytology in thyroid nodules was investigated. Female to male ratio was 6.58:1. The incidence of nodules were 157 (43.1%) cases on the right, 130 (35.7%) cases on the left and 9 (2.5%) cases in isthmus. Total 139 cases (38.2%) belong to less than 1cm and 225 cases (61.8%) belong to more than 1cm. As for the echo type in the nodules, solid types were 255(70.1%), cystic type 39 (10.7%) cases, and the percentage of mixed type was 19.2%. The results show that US-FNA reduces the possibility of unsatisfactory cytologic specimens and the rate of false-negative diagnosis, and improves the diagnostic accuracy in investigation thyroid nodules.
Noroviruses (noroV) are the major cause of nonbacterial gastroenteritis in humans worldwide. Since noroV cannot yet be cultured in vitro and their diagnosis by electron microscopy requires at least $10^6$ viral particles/g of stool a variety of molecular detection techniques represent an important step towards the detection of noroV. In the present study, we have applied real-time nucleic acid sequence-based amplification (real-time NASBA) for simultaneous detection of NoroV genogroup I (GI) and genogroup II (GII) using standard viral RNA. For real-time NASBA assay which can detected noroV GI and GII, a selective region of the genes encoding the capsid protein was used to design primers and genotype-specific molecular beacon probes. The specificity of the real-time NASBA using newly designed primers and probes were confirmed using standard viral RNA of noroV GI and GII. To determine the sensitivity of this assay, serial 10-fold dilutions of standard viral RNA of noroV GI and GII were used for reverse transcription polymerase chain reaction (RT-PCR) and real-time NASBA. The results showed that while agarose gel electrophoresis could detect RT-PCR products with 10 pg of standard viral RNA, the real-time NASBA assay could detect 100 fg of standard viral RNA. These results suggested that the real-time NASBA assay has much higher sensitivity than conventional RT-PCR assay. This assay was expected that might detect the viral RNA in the specimens which could have been false negative by RT-PCR. There were needed to perform real-time NASBA with clinical specimens for evaluating accurate sensitivity and specificity of this assay.
Purpose: In children with acute leukemia, bone marrow genetic abnormalities (GA) have prognostic significance, and may be the basis for minimal residual disease monitoring. Since April 2007, we have used a multiplex reverse transcriptase-polymerase chain reaction tool (HemaVision) to detect of GA. Methods: In this study, we reviewed the results of HemaVision screening in 270 children with acute leukemia, newly diagnosed at The Catholic University of Korea from April 2007 to December 2011, and compared the results with those of fluorescence in situ hybridization (FISH), and G-band karyotyping. Results: Among the 270 children (153 males, 117 females), 187 acute lymphoblastic leukemia and 74 acute myeloid leukemia patients were identified. Overall, GA was detected in 230 patients (85.2%). HemaVision, FISH, and G-band karyotyping identified GA in 125 (46.3%), 126 (46.7%), and 215 patients (79.6%), respectively. TEL-AML1 (20.9%, 39/187) and AML1-ETO (27%, 20/74) were the most common GA in ALL and AML, respectively. Overall sensitivity of HemaVision was 98.4%, with false-negative results in 2 instances: 1 each for TEL-AML1 and MLL-AF4. An aggregate of diseases-specific FISH showed 100% sensitivity in detection of GA covered by HemaVision for actual probes utilized. G-band karyotype revealed GA other than those covered by HemaVison screening in 133 patients (49.3%). Except for hyperdiplody and hypodiploidy, recurrent GA as defined by the World Health Organizationthat were not screened by HemaVision, were absent in the karyotype. Conclusion: HemaVision, supported by an aggregate of FISH tests for important translocations, may allow for accurate diagnosis of GA in Korean children with acute leukemia.
Lee, Minji;Ahn, Eu-Ree;Kim, Da-Hye;Shin, Heejin;Jung, Ju Yeon;Lee, Sung-Jin;Chun, Byung-Won
Analytical Science and Technology
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v.31
no.5
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pp.201-207
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2018
Blood is a commonly found body fluid at crime scenes, and plays an important role in identifying suspects and in the reconstruction of crime scenes. Although serological detection of blood has been widely used in the field of forensic science, research on the detection of old bloodstains is scarce. This work aimed to compare various methods for the detection of old bloodstains and validate the reliability of their results. Four presumptive tests-Tetramethylbenzidine, $Bluestar^{(R)}$, Leucomalachite Green, Kastle-Meyer tests-and two confirmatory tests-Fecal Occult Blood (FOB) and Rapid Stain $Identification^{(TM)}-Blood$ ($RSID^{TM}-Blood$) tests-were compared. Bloodstain samples from post-mortem cases were collected on gauzes and then stored at room temperature for periods from 7 to 30 years. All the presumptive tests were positive, even for the 30-year-old sample. However, FOB and $RSID^{TM}-Blood$ provided false negative results for some samples stored for 17 years or more (1988 to 2001). The results indicate that FOB and $RSID^{TM}-Blood$ are not reliable for the detection of old bloodstains. These findings can be useful in the selection of an appropriate detection method for serological testing of old bloodstains. In addition, the information will be useful background knowledge when applied in the field of forensic practice.
Background: Cervical cancer continues to be a major problem in Bangladesh with approximately 18,000 new cases annually of which over 10,000 women die from it. Visual inspection of the cervix after 3-5% acetic acid (VIA) application is a simple and easy to learn method for cervical cancer screening, although cytology-based screening is more often applied in developed countries where it has successfully reduced the prevalence of cervical cancer. Objective: To compare the efficacy of VIA and cytology-based primary methods for cervical cancer screening in Bangladesh. Materials and Methods: This hospital based comparative study was conducted at the VIA centre and Colposcopy Clinic of Bangabandhu Sheikh Mujib Medical University (BSMMU) from October 2008 to October 2010. Results: Among 650 women, 74 (11.4%) were VIA+ve and 8 (1.2%) had abnormalities in their Pap smear reports. During colposcopy, 38 (7.7%) women had different grades of CIN and 4 (0.6%) had cervical cancer. The gold standard histology findings proved 20 women had CIN I, 14 had CIN II/II and 4 had cervical cancer. Among the 38 histology diagnosed abnormalities, VIA test could identify 30 abnormalities including two cervical cancers. However, Pap smear could detect only 8 cases of histological abnormalities (2 low grade and 6 had high grade lesion) and it missed all the cervical cancer cases. The sensitivity and specificity of VIA were 88.9% and 52.1%. The positive predictive value (PPV) and negative predictive value (NPV) were 41.0%, and 92.6% respectively. Moreover, the sensitivity, specificity, PPV and NPV of Pap smear were 33.3%, 95.8%, 75.0% and 79.3%, respectively. Conclusions: VIA test should be used as the primary screening tool even with its low sensitivity and specificity in low resource countries like Bangladesh. False positive results may be greater, but overtreatment can be minimized by colposcopy evaluation of the VIA positive women.
Park, Sung Jin;Kim, Young Jae;Park, Dong Kyun;Chung, Jun Won;Kim, Kwang Gi
Journal of Biomedical Engineering Research
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v.39
no.5
/
pp.213-219
/
2018
Stomach cancer is the most diagnosed cancer in Korea. When gastric cancer is detected early, the 5-year survival rate is as high as 90%. Gastroscopy is a very useful method for early diagnosis. But the false negative rate of gastric cancer in the gastroscopy was 4.6~25.8% due to the subjective judgment of the physician. Recently, the image classification performance of the image recognition field has been advanced by the convolutional neural network. Convolutional neural networks perform well when diverse and sufficient amounts of data are supported. However, medical data is not easy to access and it is difficult to gather enough high-quality data that includes expert annotations. So This paper evaluates the efficacy of transfer learning in gastroscopy classification and diagnosis. We obtained 787 endoscopic images of gastric endoscopy at Gil Medical Center, Gachon University. The number of normal images was 200, and the number of abnormal images was 587. The image size was reconstructed and normalized. In the case of the ResNet50 structure, the classification accuracy before and after applying the transfer learning was improved from 0.9 to 0.947, and the AUC was also improved from 0.94 to 0.98. In the case of the InceptionV3 structure, the classification accuracy before and after applying the transfer learning was improved from 0.862 to 0.924, and the AUC was also improved from 0.89 to 0.97. In the case of the VGG16 structure, the classification accuracy before and after applying the transfer learning was improved from 0.87 to 0.938, and the AUC was also improved from 0.89 to 0.98. The difference in the performance of the CNN model before and after transfer learning was statistically significant when confirmed by T-test (p < 0.05). As a result, transfer learning is judged to be an effective method of medical data that is difficult to collect good quality data.
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