OBJECTIVES: Neurocognitive dysfunction may provide a marker of underlying neuropathology and disease vulnerability in bipolar disorder. The aim of this study was to identify the differences and the profiles of cognitive deficits in euthymic bipolar patients and first-degree relatives of bipolar probands. METHODS: Twenty four unaffected first-degree relatives of probands with bipolar I disorder (BD) were included in the study as an equal number of remitted BD patients and healthy controls who were matched on age, sex, years of education, and general intelligence. Cognitive assessments were performed using the Digit Span Test, Continuous Performance Test, Rey Auditory & verbal Learning Test, Complex Figure Test, Verbal Fluency Test, Wisconsin Card Sorting Test, and Finger Tapping Test. The effect of subsyndromal symptomatology was controlled. RESULTS: Patients showed significantly worse performance than healthy control subjects in several measures of attention, working memory, verbal learning and memory, visual memory (delayed recall), and verbal fluency (category). Relatives showed significant impairment in working memory. No differences were observed in sustained attention, cognitive flexibility, and psychomotor performance. CONCLUSION: Findings of our study suggest that the deficit in working memory could be a potential endophenotypic marker of genetic vulnerability to BD. Verbal learning and memory impair ment appears to be more related to the fully developed BD.
Bipolar Disorder ; Endophenotypes ; Fingers ; Humans ; Intelligence ; Memory ; Memory, Short-Term ; Pliability ; Verbal Learning ; Wisconsin

Background: Milk consumption is associated with bone mineral density (BMD), but reports are limited in terms of participant age, sex, and number of study subjects. We investigated the association between milk consumption and BMD in South Korean adults (≥20 years). Methods: We analyzed men and women aged ≥20 years who participated in the Korean National Health and Nutrition Examination Survey, 2008–2011. We used linear regression to calculate the mean BMD and 95% confidence interval (CI) based on the frequency of milk consumption. Multivariate logistic regression analysis was used to estimate the odds ratios (ORs) and 95% CI for T-scores ≤-2.5 (osteoporosis) in both men aged ≥50 years and postmenopausal women. Results: In total 8,539 subjects were studied. Drinking milk more than once a day was associated with higher BMD in the total femur and femoral neck in men aged <50 years and lumbar spine in men aged ≥50 years, compared to less than once a week. It was also associated with lower ORs for osteoporosis of the femoral neck and lumbar spine in men aged ≥50 years (OR, 0.35; 95% CI, 0.125–0.979 and OR, 0.34; 95% CI, 0.143–0.804, respectively). In postmenopausal women who consumed milk 2–6 times weekly, higher BMD and lower OR for osteoporosis were observed in the total femur (OR, 0.23; 95% CI, 0.055–0.958). Conclusion This study suggests that frequent milk consumption could potentially reduce osteoporosis incidence in South Korean adults. Further prospective study is necessary to elucidate the effect of milk consumption on BMD.

Background: Milk consumption is associated with bone mineral density (BMD), but reports are limited in terms of participant age, sex, and number of study subjects. We investigated the association between milk consumption and BMD in South Korean adults (≥20 years). Methods: We analyzed men and women aged ≥20 years who participated in the Korean National Health and Nutrition Examination Survey, 2008–2011. We used linear regression to calculate the mean BMD and 95% confidence interval (CI) based on the frequency of milk consumption. Multivariate logistic regression analysis was used to estimate the odds ratios (ORs) and 95% CI for T-scores ≤-2.5 (osteoporosis) in both men aged ≥50 years and postmenopausal women. Results: In total 8,539 subjects were studied. Drinking milk more than once a day was associated with higher BMD in the total femur and femoral neck in men aged <50 years and lumbar spine in men aged ≥50 years, compared to less than once a week. It was also associated with lower ORs for osteoporosis of the femoral neck and lumbar spine in men aged ≥50 years (OR, 0.35; 95% CI, 0.125–0.979 and OR, 0.34; 95% CI, 0.143–0.804, respectively). In postmenopausal women who consumed milk 2–6 times weekly, higher BMD and lower OR for osteoporosis were observed in the total femur (OR, 0.23; 95% CI, 0.055–0.958). Conclusion This study suggests that frequent milk consumption could potentially reduce osteoporosis incidence in South Korean adults. Further prospective study is necessary to elucidate the effect of milk consumption on BMD.

Background: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea.For rapid triage, we studied machine learning-based triage systems composed of a speech recognition model and natural language processing-based classification. Methods: We simulated 762 triage cases that consisted of 18 classes with six types of the main symptom (chest pain, dyspnea, fever, stroke, abdominal pain, and headache) and three levels of KTAS. In addition, we recorded conversations between emergency patients and clinicians during the simulation. We used speech recognition models to transcribe the conversation. Bidirectional Encoder Representation from Transformers (BERT), support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) were used for KTAS and symptom classification. Additionally, we evaluated the Shapley Additive exPlanations (SHAP) values of features to interpret the classifiers. Results: The character error rate of the speech recognition model was reduced to 25.21% through transfer learning. With auto-transcribed scripts, support vector machine (area under the receiver operating characteristic curve [AUROC], 0.86; 95% confidence interval [CI], 0.81–0.9), KNN (AUROC, 0.89; 95% CI, 0.85–0.93), RF (AUROC, 0.86; 95% CI, 0.82–0.9) and BERT (AUROC, 0.82; 95% CI, 0.75–0.87) achieved excellent classification performance.Based on SHAP, we found “stress”, “pain score point”, “fever”, “breath”, “head” and “chest” were the important vocabularies for determining KTAS and symptoms. Conclusion We demonstrated the potential of an automatic KTAS classification system using speech recognition models, machine learning and BERT-based classifiers.

Background: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea.For rapid triage, we studied machine learning-based triage systems composed of a speech recognition model and natural language processing-based classification. Methods: We simulated 762 triage cases that consisted of 18 classes with six types of the main symptom (chest pain, dyspnea, fever, stroke, abdominal pain, and headache) and three levels of KTAS. In addition, we recorded conversations between emergency patients and clinicians during the simulation. We used speech recognition models to transcribe the conversation. Bidirectional Encoder Representation from Transformers (BERT), support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) were used for KTAS and symptom classification. Additionally, we evaluated the Shapley Additive exPlanations (SHAP) values of features to interpret the classifiers. Results: The character error rate of the speech recognition model was reduced to 25.21% through transfer learning. With auto-transcribed scripts, support vector machine (area under the receiver operating characteristic curve [AUROC], 0.86; 95% confidence interval [CI], 0.81–0.9), KNN (AUROC, 0.89; 95% CI, 0.85–0.93), RF (AUROC, 0.86; 95% CI, 0.82–0.9) and BERT (AUROC, 0.82; 95% CI, 0.75–0.87) achieved excellent classification performance.Based on SHAP, we found “stress”, “pain score point”, “fever”, “breath”, “head” and “chest” were the important vocabularies for determining KTAS and symptoms. Conclusion We demonstrated the potential of an automatic KTAS classification system using speech recognition models, machine learning and BERT-based classifiers.

OBJECTIVES: This study aimed to identify the differences and the profiles of cognitive deficits in remitted patients with schizophrenia and first-degree relatives of schizophrenic probands. METHODS: A total of 26 remitted states of schizophrenia patients were included in the study and the same number of unaffected first-degree relatives of schizophrenic probands and healthy controls were matched for age, sex, years of education. Cognitive function of all participants was measured by using the Digit span test, the Continuous performance test, the Rey auditory & visual learning test, the Complex figure test, the Verbal fluency test, the Wisconsin card sorting test and the Finger tapping test. The effects of subsyndromal symptomatology and general intelligence score were controlled. RESULTS: Schizophrenia patients' group showed more significant impairment than other groups in verbal memory (learning, immediate recall, delayed recall), visual memory (copy, immediate recall, delayed recall) and cognitive flexibility domains. The family group and the patient group commonly performed significantly worse than healthy controls in working memory and verbal fluency (category) tests. There were no differences in sustained attention, psychomotor performance. CONCLUSIONS: Our research shows that the deficit in working memory and verbal fluency could be strong candidates of endophenotypic marker in schizophrenia.
Education ; Endophenotypes ; Fingers ; Humans ; Intelligence ; Learning ; Memory ; Memory, Short-Term ; Pliability ; Psychomotor Performance ; Schizophrenia* ; Wisconsin

OBJECTIVE: Schizophrenia and bipolar disorder are characterized by the presence of neurocognitive impairments on the psychosis continuum. The present study aimed to explore the shared and distinct endophenotypes between these disorders. METHODS: The study included 34 probands with remitted schizophrenia and 34 probands with euthymic bipolar disorder who had a history of psychotic symptoms that met the Diagnostic and Statistical Manual of Mental Disorders 4th edition (DSM-IV) criteria, unaffected first-degree relatives of probands (31 relatives of probands with schizophrenia and 29 relatives of probands with bipolar disorder), and 34 healthy controls. Cognitive assessments were performed using the digit span, continuous performance, Rey auditory and visual learning, complex figure, verbal fluency, Wisconsin card sorting, and finger tapping tests. RESULTS: Probands with schizophrenia showed the most generalized and severe cognitive deficits across cognitive domains (working memory, verbal learning and memory, visual memory, verbal fluency, and executive function). Some domains of cognitive function (working memory, verbal learning, and memory) were also impaired in probands with bipolar disorder, but to a lesser degree than in probands with schizophrenia. All probands and relatives showed a common deficit in working memory compared to healthy controls. Relatives of probands with schizophrenia also showed verbal fluency dysfunction. Cognitive performance of all relatives was intermediate to the performance of both patients and healthy controls. CONCLUSION: These findings suggest that a deficit in working memory could be a shared endophenotype of genetic vulnerability to schizophrenia and psychotic bipolar disorder, and verbal fluency could be a candidate endophenotype for schizophrenia specifically.
Bipolar Disorder* ; Cognition ; Diagnostic and Statistical Manual of Mental Disorders ; Endophenotypes* ; Fingers ; Humans ; Learning ; Memory ; Memory, Short-Term ; Psychotic Disorders ; Schizophrenia* ; Verbal Learning ; Wisconsin

Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of midbrain dopaminergic neurons, leading to motor symptoms. While current treatments provide limited relief, they don’t alter disease progression. Stem cell technology, involving patient-specific stem cell-derived neurons, offers a promising avenue for research and personalized regenerative therapies. This article reviews the potential of stem cell-based research in PD, summarizing ongoing efforts, their limitations, and introducing innovative research models. The integration of stem cell technology and advanced models promises to enhance our understanding and treatment strategies for PD.

Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of midbrain dopaminergic neurons, leading to motor symptoms. While current treatments provide limited relief, they don’t alter disease progression. Stem cell technology, involving patient-specific stem cell-derived neurons, offers a promising avenue for research and personalized regenerative therapies. This article reviews the potential of stem cell-based research in PD, summarizing ongoing efforts, their limitations, and introducing innovative research models. The integration of stem cell technology and advanced models promises to enhance our understanding and treatment strategies for PD.

Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of midbrain dopaminergic neurons, leading to motor symptoms. While current treatments provide limited relief, they don’t alter disease progression. Stem cell technology, involving patient-specific stem cell-derived neurons, offers a promising avenue for research and personalized regenerative therapies. This article reviews the potential of stem cell-based research in PD, summarizing ongoing efforts, their limitations, and introducing innovative research models. The integration of stem cell technology and advanced models promises to enhance our understanding and treatment strategies for PD.