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Objectives@#This study aimed to develop a machine learning model for diagnosing schizophrenia (SZ) and bipolar disorder (BD) based on diffusion tensor imaging (DTI) data. @*Methods@#We used 3T-magnetic resonance imaging to examine SZ, BD, healthy control (HC) subjects (aged 20-50 years, n=65 in each group). Applying Support Vector Machine (SVM) to fractional anisotropy (FA) values, we built classification models of SZ and HC, BD and HC, and SZ and BD. Features of white matter (WM) tracts were selected through recursive feature elimination, and 5-fold cross validation was performed. @*Results@#The SVM models classified SZ and BD from HC with a mean accuracy of 83.5% and 75.4%, respectively. The SZ-BD classification model archived 75.0% accuracy. These classification models used FA values in 15-18 WM tracts as features, including the retrolenticular part of the internal capsule, superior corona radiata, cingulum, and superior fronto-occipital fasciculus. @*Conclusions@#This study presented a preliminary machine learning model to diagnose SZ and BD based on DTI data. Our findings also suggest that there might be a specific pattern of abnormalities in WM integrity that can differentiate the two psychotic disorders.
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Striatal changes in the pathogenesis of Alzheimer’s disease (AD) is not fully understood yet. We compared structural and functional image differences in the striatum between patients with early onset AD (EOAD) and late onset AD (LOAD) to investigate whether EOAD harbors autosomal dominant AD like imaging findings. The clinical, neuropsychological and neuroimaging biomarkers of 77 probable AD patients and 107 elderly subjects with normal cognition (NC) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI)-2 dataset were analyzed. Enrolled each subject completed a 3-Tesla MRI, baseline 18F-FDG-PET, and baseline 18F-AV-45 (Florbetapir) amyloid PET studies. AD patients were divided into two groups based on the onset age of clinical symptoms (EOAD <65 yrs; LOAD ≥65 yrs). A standardized uptake value ratio of the striatum and subcortical structures was obtained from both amyloid and FDG-PET scans. Structural MR imaging analysis was conducted using a parametric boundary description protocol, SPHARM-PDM. Of the 77 AD patients, 18 were EOAD and 59 were LOAD. Except for age of symptom onset, there were no statistically significant differences between the groups in demographics and detailed neuropsychological test results. 18F-AV-45 amyloid PET showed marked β-amyloid accumulation in the bilateral caudate nucleus and left pallidum in the EOAD group. Intriguingly, the caudate nucleus and putamen showed maintained glucose metabolism in the EOAD group compared to the LOAD group. Our image findings in the striatum of EOAD patients suggest that sporadic EOAD may share some pathophysiological changes noted in autosomal dominant AD.
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Objectives@#This study aimed to investigate suicidal behaviors and the related psychopathology across the different stages of schizophrenia. @*Methods@#We recruited 131 patients with schizophrenia and categorized them into two groups, according to the duration of illness (DI) as follows: ≤10 years (n=39) and >10 years (n=92). Psychopathology and suicidality were assessed using the 18-item Brief Psychiatric Rating Scale (BPRS-18) and the suicidality module from the Mini-International Neuropsychiatric Interview, respectively. @*Results@#One-quarter of the patients with a DI ≤10 years and nearly one-sixth of the patients with a DI >10 years experienced suicidal behaviors in the previous month. Suicidality scores were significantly associated with the “affect” factor scores of the BPRS-18 in patients with a DI ≤10 years (β=0.55, p=0.003) and with the “resistance” factor scores in patients with a DI of >10 years (β=0.29, p=0.006). @*Conclusion@#The present study demonstrated that psychopathological factors were differentially associated with suicidality in patients with schizophrenia according to the illness stage. Our findings suggest that for effective suicide prevention, different approaches are required for the management of each stage of schizophrenia.
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Objective@#This study used network analyses to examine network structures reflecting interactions between specific domains of social functioning in schizophrenia (SZ) and bipolar disorder (BD). @*Methods@#We used the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) to assess six domains of social functioning (‘cognition’, ‘mobility’, ‘self-care’, ‘getting along’, ‘life activities’, and ‘participation’) in 143 patients with SZ, 81 patients with BD, and 106 healthy subjects. We constructed regularized partial correlation networks, estimated network centrality and edge strength, tested network stability, and compared SZ and BD network structures. @*Results@#Patients with SZ showed a significantly higher level of functional disability than patients with BD. In the networks we constructed, ‘cognition’ was the most central domain of social functioning in both SZ and BD. The ‘cognition’ domain was primarily associated with the ‘getting along’ domain in the SZ network and the ‘life activities’ domain in the BD network. We found no significant group-level differences in network structures for SZ vs. BD. @*Conclusion@#Our results suggest that cognition may play a pivotal role in social functioning in both SZ and BD. In addition, domains of social functioning in SZ and BD have similar network structures despite the higher level of disability in SZ compared to BD.
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Objective@#More recently, attention has turned to the linkage between childhood trauma and emotional dysregulation, but the evidence in bipolar disorder (BD) is limited. To determine neurobiological relationships between childhood trauma, current anxiety, and impulsivity, we investigated cortical volumetric correlates of these clinical factors in BD. @*Methods@#We studied 36 patients with DSM-5 BD and 29 healthy controls. Childhood trauma, coexisting anxiety, and impulsivity were evaluated with the Korean version-Childhood Trauma Questionnaire (CTQ), the Korean version-Beck Anxiety Inventory (BAI), and the Korean version-Barratt Impulsiveness Scale (BIS). Voxel-based morphometry (VBM) was used to assess gray matter volume (GMV) alterations on the brain magnetic resonance imaging (MRI). Partial correlation analyses were conducted to examine associations between the GMV and each scale in the BD group. @*Results@#Childhood trauma, anxiety, and impulsivity were interrelated in BD. BD patients revealed significant inverse correlations between the GMV in the right precentral gyrus and CTQ scores (r=-0.609, p<0.0003); between the GMV in the left middle frontal gyrus and BAI scores (r=-0.363, p=0.044). Moreover, patients showed similar tendency of negative correlations between the GMV in the right precentral gyrus and BIS scores; between the GMV in the left middle frontal gyrus and CTQ scores. @*Conclusion@#The present study provides evidence for a neural basis between childhood trauma and affect regulations in BD. The GMV alterations in multiple frontal lobe areas may represent neurobiological markers for anticipating the course of BD.
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OBJECTIVE: We aimed to develop predictive models to identify suicide attempters among individuals with suicide ideation using a machine learning algorithm. METHODS: Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 5,773 subjects who reported experiencing suicide ideation and had answered a survey question about suicide attempts. Then, we performed resampling with the Synthetic Minority Over-sampling TEchnique (SMOTE) to obtain data corresponding to 1,324 suicide attempters and 1,330 non-suicide attempters. We randomly assigned the samples to a training set (n=1,858) and a test set (n=796). In the training set, random forest models were trained with features selected through recursive feature elimination with 10-fold cross validation. Subsequently, the fitted model was used to predict suicide attempters in the test set. RESULTS: In the test set, the prediction model achieved very good performance [area under receiver operating characteristic curve (AUC)=0.947] with an accuracy of 88.9%. CONCLUSION: Our results suggest that a machine learning approach can enable the prediction of individuals at high risk of suicide through the integrated analysis of various suicide risk factors.
Тема - темы
Forests , Korea , Machine Learning , Risk Factors , ROC Curve , SuicideРеферат
OBJECTIVES: This study examined the functional disabilities of patients with chronic schizophrenia using WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) and its related factors. METHODS: The subjects consisted of 86 patients with schizophrenia with more than 10 years' duration of illness and 40 healthy volunteers. The functional disabilities and psychopathology were evaluated using the WHODAS 2.0 and 18-items Brief Psychiatric Rating Scale (BPRS-18), respectively. This study analyzed the six sub-domains ('cognition', 'mobility', 'self-care', 'getting along', 'life activities', and 'participation') of WHODAS 2.0 and the four sub-scales ('positive symptoms', 'negative symptoms', 'affect', and 'resistance') of BPRS-18. RESULTS: Patients with chronic schizophrenia experienced severe functional disabilities across all six sub-domains of WHODAS 2.0 compared to healthy people. Hierarchical regression showed that 'negative symptoms' explained the disabilities in the WHODAS 2.0 sub-domains of 'cognition' (p<0.05), 'self-care' (p<0.05), 'getting along' (p<0.01), and 'life activities' (p<0.05). 'Positive symptoms' and 'affect' explained the disabilities in 'cognition' (p<0.01 and p<0.05, respectively) and 'participation' (p<0.05 and p<0.01, respectively). 'Resistance' was found to be a predictor of 'getting along' disabilities (p<0.01). CONCLUSION: Negative symptoms mainly accounted for the multiple domains of functional disabilities in the WHODAS 2.0 but residual positive and affective symptoms could also deteriorate the cognition and social participation of patients with chronic schizophrenia.
Тема - темы
Humans , Affective Symptoms , Appointments and Schedules , Brief Psychiatric Rating Scale , Cognition , Disability Evaluation , Global Health , Healthy Volunteers , Psychopathology , Schizophrenia , Social Participation , World Health OrganizationРеферат
OBJECTIVE: In this study, we aimed to develop a model predicting individuals with suicide ideation within a general population using a machine learning algorithm. METHODS: Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 11,628 individuals via random down-sampling. This included 5,814 suicide ideators and the same number of non-suicide ideators. We randomly assigned the subjects to a training set (n=10,466) and a test set (n=1,162). In the training set, a random forest model was trained with 15 features selected with recursive feature elimination via 10-fold cross validation. Subsequently, the fitted model was used to predict suicide ideators in the test set and among the total of 35,116 subjects. All analyses were conducted in R. RESULTS: The prediction model achieved a good performance [area under receiver operating characteristic curve (AUC)=0.85] in the test set and predicted suicide ideators among the total samples with an accuracy of 0.821, sensitivity of 0.836, and specificity of 0.807. CONCLUSION: This study shows the possibility that a machine learning approach can enable screening for suicide risk in the general population. Further work is warranted to increase the accuracy of prediction.
Тема - темы
Forests , Korea , Machine Learning , Mass Screening , ROC Curve , Sensitivity and Specificity , SuicideРеферат
Internet addiction (IA) has become a widespread and problematic phenomenon as smart devices pervade society. Moreover, internet gaming disorder leads to increases in social expenditures for both individuals and nations alike. Although the prevention and treatment of IA are getting more important, the diagnosis of IA remains problematic. Understanding the neurobiological mechanism of behavioral addictions is essential for the development of specific and effective treatments. Although there are many databases related to other addictions, a database for IA has not been developed yet. In addition, bioinformatics databases, especially genetic databases, require a high level of security and should be designed based on medical information standards. In this respect, our study proposes the OAuth standard protocol for database access authorization. The proposed IA Bioinformatics (IABio) database system is based on internet user authentication, which is a guideline for medical information standards, and uses OAuth 2.0 for access control technology. This study designed and developed the system requirements and configuration. The OAuth 2.0 protocol is expected to establish the security of personal medical information and be applied to genomic research on IA.
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Humans , Computational Biology , Databases, Genetic , Diagnosis , Health Expenditures , InternetРеферат
OBJECTIVES: The purpose of this study was to assess the accuracy of Root ZX (J. Morita Corp.) according to the location of major foramen and open apex. MATERIALS AND METHODS: 81 mandibular premolars with mature apices were selected. After access preparation, 27 teeth were instrumented to simulate open apices. 54 teeth were classified according to location of major foramen under surgical microscope (x16). The file was fixed at the location of apical constriction by Root ZX using glass ionomer cement. The apical 4 mm of the apex was exposed and photo was taken and the distance from file tip to the major foramen was measured by calibrating metal ruler on graph paper. The results were statistically analyzed using ANOVA and Scheffe test at p < 0.05 level. RESULTS: Mean distance from file tip to major foramen was 0.308 mm in Tip foramen group (I), 0.519 mm in Lateral foramen group (II) and 0.932 mm in open apex group (III). Root ZX located apical constriction accurately within +/- 0.5 mm in group I of 85.71%, in group II of 59.09%, and in group III of 33.33%. There was a statistically significant difference between group I and III (p < 0.05). CONCLUSION: Root ZX located apical constriction accurately regardless of location of major foramen. However, Root ZX couldn't find it in open apex. Clinicians have to use a combination of methods to determine an appropriate working length at open apex. It may be more successful than relying on just electronic apex locator.
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Acrylic Resins , Bicuspid , Constriction , Electronics , Electrons , Glass Ionomer Cements , Silicon Dioxide , Tooth , Tooth ApexРеферат
PURPOSE: The objective of this study was to investigate the differences of hippocampal volume and shape as well as the functional change between long life experienced taxi drivers and controls of Korean population. MATERIALS AND METHODS: Three-dimensional T1-weighted images and blood oxygen level dependent functional MRI(fMRI) were obtained from 8 subjects, consisting of 4 experienced (20-30 years) taxi drivers and 4 age-matched controls. The hippocampal volume and shape were analyzed with three-dimensional T1-weighted images. In addition, neuronal activities of brain were analyzed using a blood oxygen level dependent fMRI between the two groups. RESULTS: The hippocampal volume showed no statistically significant difference between the two groups (p > 0.05). The left hippocampi of the taxi drivers were slightly elongated with larger head and tail portions than those of the controls (p < 0.05, uncorrected). For the functional MRI, fusiform gyrus was specifically activated in taxi drivers, compared with the control group. CONCLUSION: The structural and functional changes of taxi driver's hippocampus indicate the functional differentiation as a result of occupational dependence on spatial navigation. In other words, the continuous usage of spatial navigation performance may diminish degeneration of hippocampus and the related brain regions.
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Brain , Head , Hippocampus , Magnetic Resonance Imaging , Neurons , Orientation , OxygenРеферат
OBJECTIVES: The purpose of this study was to evaluate the buccolingual curvature at the apical one third in type II mesial canals of mandibular molars using the radius and angle of curvature. MATERIALS AND METHODS: Total 100 mandibular molars were selected. Following an endodontic access in the teeth, their distal roots were removed. #15 H- or K-files (Dentsply Maillefer) were inserted into the mesiobuccal and mesiolingual canals of the teeth. Radiographs of the teeth were taken for the proximal view. Among them, type II canals were selected and divided into two subgroups, IIa and IIb. In type IIa, two separate canals merged into one canal before reaching the apex and in type IIb, two separate canals merged into one canal within the apical foramen. The radius and angle of curvature of specimens were examined. RESULTS: In type II, mean radius of curvature in mesiolingual and mesiobuccal canals were 2.82 mm and 3.58 mm, respectively. The radius of the curvature of mesiolingual canals were significantly smaller than that of mesiobuccal canals in type II, and especially in type IIa. However, there were no statistically significant differences in radius of curvature between mesiobuccal and mesiolingual canals in type IIb and there were no significant differences in angle of curvature between type IIa and IIb. CONCLUSION: In this study, type II mesial canals of mandibular molars showed severe curvature in the proximal view. Especially, mesiolingual canals of type IIa had more abrupt curvature than mesiobuccal canals at the apical one third.
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Molar , Radius , Tooth , Tooth ApexРеферат
Type II root canal was defined that two canals leave the chamber and merge to form a single canal at short of the apex. The aim of this study was to analyse the master apical file (MAF) size according to various instrumentation techniques in the type II root canal when each canal was enlarged to working length. Eighty mesial roots of molar with ISO #15 initial apical file (IAF) size in type II root canals were randomly divided into four experimental groups with 20 teeth each. According to enlarging instruments, four groups are: K-FLEXOFILE(R) (KF), engine-driven Ni-Ti PROTAPER(R) (PT), HERO Shaper(R) (HS), K3 (TM) (K3). All canals were enlarged to each working length with ISO #30 size: #30 in KF, F3 in PT, .04/30 in HS, and .06/30 in K3. The master apical file (MAF) size was confirmed by tactile sensation and universal testing machine (EZ test, Shimadzu Co., Kyoto, Japan). The mean MAF size was statistically compared using one-way ANOVA and Tukey HSD test at the 0.05 probability level. These results show that the MAF size was appeared one or two sizes larger than the final enlarging instrument when all canal in type II configuration were enlarged to each working length. Therefore, the clinician have to confirm the apical stop once more after instrumentation of type II root canal.