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Abstract Serial CA125 and second line transvaginal ultrasound (TVS) screening in the UKCTOCS indicated a shift towards detection of earlier stage ovarian cancer (OvCa), but did not yield a significant mortality reduction. There remains a need to establish additional biomarkers that can complement CA125 for even earlier and at a larger proportion of new cases. Using a cohort of plasma samples from 219 OvCa cases (59 stage I/II and 160 stage III/IV) and 409 female controls and a novel Sensitivity Maximization At A Given Specificity (SMAGS) method, we developed a blood-based metabolite-based test consisting of 7 metabolites together with CA125 for detection of OvCa. At a 98.5% specificity cutpoint, the metabolite test achieved sensitivity of 86.2% for detection of early-stage OvCa and was able to capture 64% of the cases with low CA125 levels (

In-Seon Lee,1 Da-Eun Yoon,1 Seoyoung Lee,2 Jae-Hwan Kang,3,4 Younbyoung Chae,1 Hi-Joon Park,1 Junsuk Kim5 1College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea; 2Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway; 3Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea; 4Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea; 5School of Information Convergence, Kwangwoon University, Seoul, Republic of KoreaCorrespondence: Junsuk Kim, School of Information Convergence, Kwangwoon University, 20 Kwangwoon-ro, Seoul, 01897, Republic of Korea, Tel +82-2-940-8477, Email junsuk.kim@kw.ac.kr Hi-Joon Park, College of Korean Medicine, Kyung Hee University, 26 Kyunghee-daero, Seoul, 02447, Republic of Korea, Tel +82-2-961-9435, Email acufind@khu.ac.krPurpose: Only a few studies have focused on the brain mechanisms underlying the itch processing in AD patients, and a neural biomarker has never been studied in AD patients. We aimed to develop a deep learning model-based neural signature which can extract the relevant temporal dynamics, discriminate between AD and healthy control (HC), and between AD patients who responded well to acupuncture treatment and those who did not.Patients and Methods: We recruited 41 AD patients (22 male, age mean ± SD: 24.34 ± 5.29) and 40 HCs (20 male, age mean ± SD: 26.4 ± 5.32), and measured resting-state functional MRI signals. After preprocessing, 38 functional regions of interest were applied to the functional MRI signals. A long short-term memory (LSTM) was used to extract the relevant temporal dynamics for classification and train the prediction model. Bootstrapping and 4-fold cross-validation were used to examine the significance of the models.Results: For the identification of AD patients and HC, we found that the supplementary motor area (SMA), posterior cingulate cortex (PCC), temporal pole, precuneus, and dorsolateral prefrontal cortex showed significantly greater prediction accuracy than the chance level. For the identification of high and low responder to acupuncture treatment, we found that the lingual-parahippocampal-fusiform gyrus, SMA, frontal gyrus, PCC and precuneus, paracentral lobule, and primary motor and somatosensory cortex showed significantly greater prediction accuracy than the chance level.Conclusion: We developed and evaluated a deep learning model-based neural biomarker that can distinguish between AD and HC as well as between AD patients who respond well and those who respond less to acupuncture. Using the intrinsic neurological abnormalities, it is possible to diagnose AD patients and provide personalized treatment regimens.Keywords: Atopic Dermatitis, deep learning, functional MRI, biomarkers, personalized medicine

Minyoung Hong,* In-Seon Lee,* Dha-Hyun Choi, Younbyoung Chae Acupuncture & Meridian Science Research Center, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea*These authors contributed equally to this workCorrespondence: Younbyoung Chae Email ybchae@khu.ac.krObjective: Despite the many medical benefits, cupping therapy can be difficult for some patients due to unpleasant marks on the skin. As patients are afraid of the potential painful sensation from cupping therapy, the skin reactions might produce vigilance for treatment as pain-related information. We investigated whether individuals show negative emotions and attentional bias toward pain-related residual marks from cupping therapy on the body using an eye-tracking method.Methods: Fifty pain-free volunteers were presented with four different kinds of visual stimulation, such as the back or face region and with or without cupping marks on the skin. A cupping and a control image were presented on one screen with one image on the left side of the screen and the other on the right (locations of the images were counterbalanced across participants). The eye movements of the participants were measured while they viewed the pictures. They completed the Empathy Quotient questionnaire before the experiment and evaluated the unpleasantness level to each image during the task.Results: Images of the back and face with cupping marks were rated significantly more unpleasant and showed a significant attentional bias (significantly longer percentage fixation time) than the control images (attentional bias score: Back + cupping: 48.1 ± 2.8%; Back: − 0.7 ± 3.4%; Face + cupping: 34.5 ± 2.5%; Face: − 2.2 ± 2.9%). Individuals with greater empathy exhibited significantly higher unpleasantness (r = 0.323, p < 0.05) and less attentional bias (r = − 0.279, p < 0.05) to the images with cupping marks.Conclusion: The skin reactions caused by cupping therapy evoked negative emotional responses as well as attentional bias to the reaction sites. Our findings suggest that the emotional and attentional responses to cupping therapy might reflect potential reluctance to this therapy.Keywords: attentional bias, cupping, emotion, empathy, eye-tracking

In-Seon Lee,1 Hyangsook Lee,1,2 Yi-Hung Chen,3 Younbyoung Chae1 1Acupuncture & Meridian Science Research Center, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea; 2Korean Medicine Convergence Research Center, Kyung Hee University, Seoul, Republic of Korea; 3Chinese Medicine Research Center, China Medical University, Taichung, Taiwan, R.O.C.Correspondence: Younbyoung ChaeAcupuncture & Meridian Science Research Center, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul, Republic of KoreaEmail ybchae@khu.ac.krObjective: A bibliometric approach using quantitative analytical methods was applied to explore the development of research investigating acupuncture for the treatment of pain. This study also evaluated the current status of acupuncture analgesia with a visualization analysis of journal articles.Methods: Articles on acupuncture for pain control that were published from 2000 to 2019 were retrieved from the Web of Science database. Extracted records were analyzed in terms of year of publication, country, journal, research area, authors, and organizational affiliations. The VOSviewer program was used to visualize trends in research on acupuncture for pain control.Results: Analyses of 4595 original and review articles revealed that the total number of publications has continually increased over the last 20 years. The country producing the most articles in this field was the United States, followed by China and South Korea. A network analysis based on the cooccurrence of keywords revealed the following three major types of studies: clinical studies, pain management studies, and mechanism studies.Conclusion: The present study evaluated research on acupuncture for pain control using bibliometric methods and revealed current trends in acupuncture analgesia research, as well as potential future hot spots of research in this field.Keywords: acupuncture, analgesia, bibliometric analysis, pain, network analysis

Cartilage thermoforming is an emerging surgical technology which uses heat to accelerate stress relaxation in mechanically deformed tissue specimens. Heat induced shape change in cartilage is associated with complex thermo mechanical behavior of which the mechanisms are still a subject of debate. Differential scanning calorimetry (DSC) was used to characterize the threshold temperatures and enthalpies in cartilage as a function of water content. The DSC identified two enthalpic events in porcine nasal septal cartilage, which depend on the water content. The change in the water content of cartilage impacts the interactions between matrix macromolecules and water molecules, which may be associated with a bound-free water transformation (reversible process) and a denaturation of cartilage (irreversible process).

Ye-Seul Lee,1 Won-Mo Jung,1 Hyunchul Jang,2 Sanghyun Kim,2 Sun-Yong Chung,3 Younbyoung Chae1 1Acupuncture and Meridian Science Research Center, College of Korean Medicine, Kyung Hee University, Seoul, 2Mibyeong Research Center, Korean Institute of Oriental Medicine, Daejeon, 3Department of Neuropsychiatry, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea Objectives: Recently, there has been increasing interest in preventing and managing diseases both inside and outside medical institutions, and these concerns have supported the development of the individual Personal Health Record (PHR). Thus, the current study created a mobile platform called “Mind Mirror” to evaluate psychological and physical conditions and investigated whether PHRs would be a useful tool for assessment of the dynamic relationship between the emotional and physical conditions of an individual.Methods: Mind Mirror was used to collect 30 days of observational data about emotional valence and the physical states of pain and fatigue from 20 healthy participants, and these data were used to analyze the dynamic relationship between emotional and physical conditions. Additionally, based on the cross-correlations between these three parameters, a multilevel multivariate regression model (mixed linear model [MLM]) was implemented.Results: The strongest cross-correlation between emotional and physical conditions was at lag 0, which implies that emotion and body condition changed concurrently. In the MLM, emotional valence was negatively associated with fatigue (β =-0.233, P