Cutaneous dermatophyte infections, dermatophytosis, are common worldwide, affecting various age groups and body parts. Despite advancements in antifungal therapies, the prevalence of dermatophytosis continues to increase, posing significant challenges for diagnosis and treatment. This review provides an overview of the prevalence, clinical features, and diagnostic methods for dermatophytosis in Korea. A comprehensive review of domestic reports and research on dermatophytosis in Korea was conducted using data from KoreaMed.This study covers the various clinical presentations, age distributions, seasonal trends, and types of dermatophytes identified in different body areas. Dermatophytosis in Korea have shown changing patterns in terms of prevalence and causative species. Trichophyton rubrum remains the most common causative organism, with varying presentations depending on the site of infection, such as tinea pedis, tinea corporis, tinea capitis, tinea faciei, and onychomycosis. Diagnostic practices largely depend on the potassium hydroxide smear test, which has limited sensitivity, particularly for onychomycosis. Recent trends indicate an increase in the incidence of dermatophytosis among older adults, which may be linked to underlying health conditions and lifestyle changes. Dermatophytosis in Korea exhibit diverse clinical manifestations influenced by factors such as patient age, body site, and seasonal variation. Improved diagnostic methods are needed to enhance the accuracy and guide appropriate treatment, especially with the emergence of antifungal-resistant strains. This review aims to provide a better understanding of the current state of dermatophytosis in Korea and contribute to more effective management and prevention strategies.

Cutaneous dermatophyte infections, dermatophytosis, are common worldwide, affecting various age groups and body parts. Despite advancements in antifungal therapies, the prevalence of dermatophytosis continues to increase, posing significant challenges for diagnosis and treatment. This review provides an overview of the prevalence, clinical features, and diagnostic methods for dermatophytosis in Korea. A comprehensive review of domestic reports and research on dermatophytosis in Korea was conducted using data from KoreaMed.This study covers the various clinical presentations, age distributions, seasonal trends, and types of dermatophytes identified in different body areas. Dermatophytosis in Korea have shown changing patterns in terms of prevalence and causative species. Trichophyton rubrum remains the most common causative organism, with varying presentations depending on the site of infection, such as tinea pedis, tinea corporis, tinea capitis, tinea faciei, and onychomycosis. Diagnostic practices largely depend on the potassium hydroxide smear test, which has limited sensitivity, particularly for onychomycosis. Recent trends indicate an increase in the incidence of dermatophytosis among older adults, which may be linked to underlying health conditions and lifestyle changes. Dermatophytosis in Korea exhibit diverse clinical manifestations influenced by factors such as patient age, body site, and seasonal variation. Improved diagnostic methods are needed to enhance the accuracy and guide appropriate treatment, especially with the emergence of antifungal-resistant strains. This review aims to provide a better understanding of the current state of dermatophytosis in Korea and contribute to more effective management and prevention strategies.

Cutaneous dermatophyte infections, dermatophytosis, are common worldwide, affecting various age groups and body parts. Despite advancements in antifungal therapies, the prevalence of dermatophytosis continues to increase, posing significant challenges for diagnosis and treatment. This review provides an overview of the prevalence, clinical features, and diagnostic methods for dermatophytosis in Korea. A comprehensive review of domestic reports and research on dermatophytosis in Korea was conducted using data from KoreaMed.This study covers the various clinical presentations, age distributions, seasonal trends, and types of dermatophytes identified in different body areas. Dermatophytosis in Korea have shown changing patterns in terms of prevalence and causative species. Trichophyton rubrum remains the most common causative organism, with varying presentations depending on the site of infection, such as tinea pedis, tinea corporis, tinea capitis, tinea faciei, and onychomycosis. Diagnostic practices largely depend on the potassium hydroxide smear test, which has limited sensitivity, particularly for onychomycosis. Recent trends indicate an increase in the incidence of dermatophytosis among older adults, which may be linked to underlying health conditions and lifestyle changes. Dermatophytosis in Korea exhibit diverse clinical manifestations influenced by factors such as patient age, body site, and seasonal variation. Improved diagnostic methods are needed to enhance the accuracy and guide appropriate treatment, especially with the emergence of antifungal-resistant strains. This review aims to provide a better understanding of the current state of dermatophytosis in Korea and contribute to more effective management and prevention strategies.

Cutaneous dermatophyte infections, dermatophytosis, are common worldwide, affecting various age groups and body parts. Despite advancements in antifungal therapies, the prevalence of dermatophytosis continues to increase, posing significant challenges for diagnosis and treatment. This review provides an overview of the prevalence, clinical features, and diagnostic methods for dermatophytosis in Korea. A comprehensive review of domestic reports and research on dermatophytosis in Korea was conducted using data from KoreaMed.This study covers the various clinical presentations, age distributions, seasonal trends, and types of dermatophytes identified in different body areas. Dermatophytosis in Korea have shown changing patterns in terms of prevalence and causative species. Trichophyton rubrum remains the most common causative organism, with varying presentations depending on the site of infection, such as tinea pedis, tinea corporis, tinea capitis, tinea faciei, and onychomycosis. Diagnostic practices largely depend on the potassium hydroxide smear test, which has limited sensitivity, particularly for onychomycosis. Recent trends indicate an increase in the incidence of dermatophytosis among older adults, which may be linked to underlying health conditions and lifestyle changes. Dermatophytosis in Korea exhibit diverse clinical manifestations influenced by factors such as patient age, body site, and seasonal variation. Improved diagnostic methods are needed to enhance the accuracy and guide appropriate treatment, especially with the emergence of antifungal-resistant strains. This review aims to provide a better understanding of the current state of dermatophytosis in Korea and contribute to more effective management and prevention strategies.

Cutaneous dermatophyte infections, dermatophytosis, are common worldwide, affecting various age groups and body parts. Despite advancements in antifungal therapies, the prevalence of dermatophytosis continues to increase, posing significant challenges for diagnosis and treatment. This review provides an overview of the prevalence, clinical features, and diagnostic methods for dermatophytosis in Korea. A comprehensive review of domestic reports and research on dermatophytosis in Korea was conducted using data from KoreaMed.This study covers the various clinical presentations, age distributions, seasonal trends, and types of dermatophytes identified in different body areas. Dermatophytosis in Korea have shown changing patterns in terms of prevalence and causative species. Trichophyton rubrum remains the most common causative organism, with varying presentations depending on the site of infection, such as tinea pedis, tinea corporis, tinea capitis, tinea faciei, and onychomycosis. Diagnostic practices largely depend on the potassium hydroxide smear test, which has limited sensitivity, particularly for onychomycosis. Recent trends indicate an increase in the incidence of dermatophytosis among older adults, which may be linked to underlying health conditions and lifestyle changes. Dermatophytosis in Korea exhibit diverse clinical manifestations influenced by factors such as patient age, body site, and seasonal variation. Improved diagnostic methods are needed to enhance the accuracy and guide appropriate treatment, especially with the emergence of antifungal-resistant strains. This review aims to provide a better understanding of the current state of dermatophytosis in Korea and contribute to more effective management and prevention strategies.

Objective: The loudness dependence of the auditory evoked potential (LDAEP) is a reliable indicator that is inversely related to central serotonergic activity, and recent studies have suggested an association between LDAEP and suicidal ideation. This study investigated differences in LDAEP between patients with major depressive disorder and high suicidality and those with major depressive disorder and low suicidality compared to healthy controls. Methods: This study included 67 participants: 23 patients with major depressive disorder with high suicidality (9 males, mean age 29.3 ± 15.7 years, total score of SSI-BECK ≥ 15), 22 patients with major depressive disorder with low suicidality (9 males, mean age 42.2 ± 14.4 years, total score of SSI-BECK ≤ 14), and 22 healthy controls (11 males, mean age 31.6 ± 8.7 years). Participants completed the following assessments: Patient Health Questionnaire-9, Beck Depression Inventory-II, Beck Scale for Suicidal ideation, State Anxiety Scale of the State-Trait Anxiety Inventory, Beck Anxiety Inventory, and LDAEP (measured at electrode Cz). Results: There were no sex-related differences among groups (p = 0.821). The high-suicidality group exhibited significantly higher LDAEP compared to the low-suicidality group (0.82 ± 0.79 vs. 0.26 ± 0.36, p = 0.014). No significant differences were found between the control and high-suicidality (p = 0.281) or the control and low-suicidality groups (p = 0.236). Conclusion LDAEP was applied to demonstrate the association between serotonergic activity and suicidal ideation and suicide risk in major depression and may be a candidate of biological marker for preventing suicide in this study.

Objective: The loudness dependence of the auditory evoked potential (LDAEP) is a reliable indicator that is inversely related to central serotonergic activity, and recent studies have suggested an association between LDAEP and suicidal ideation. This study investigated differences in LDAEP between patients with major depressive disorder and high suicidality and those with major depressive disorder and low suicidality compared to healthy controls. Methods: This study included 67 participants: 23 patients with major depressive disorder with high suicidality (9 males, mean age 29.3 ± 15.7 years, total score of SSI-BECK ≥ 15), 22 patients with major depressive disorder with low suicidality (9 males, mean age 42.2 ± 14.4 years, total score of SSI-BECK ≤ 14), and 22 healthy controls (11 males, mean age 31.6 ± 8.7 years). Participants completed the following assessments: Patient Health Questionnaire-9, Beck Depression Inventory-II, Beck Scale for Suicidal ideation, State Anxiety Scale of the State-Trait Anxiety Inventory, Beck Anxiety Inventory, and LDAEP (measured at electrode Cz). Results: There were no sex-related differences among groups (p = 0.821). The high-suicidality group exhibited significantly higher LDAEP compared to the low-suicidality group (0.82 ± 0.79 vs. 0.26 ± 0.36, p = 0.014). No significant differences were found between the control and high-suicidality (p = 0.281) or the control and low-suicidality groups (p = 0.236). Conclusion LDAEP was applied to demonstrate the association between serotonergic activity and suicidal ideation and suicide risk in major depression and may be a candidate of biological marker for preventing suicide in this study.

Objective: To explore the quality of life and mental health status of adolescents in Zhengzhou, and to compare with HongKong and Taiwan. Methods: A total of 6 401 students from 12 primary and secondary schools in Zhengzhou City. A total of 3 642 students from HongKong and 1 547 students from Taiwan were selected by cluster sampling. And Padiatric Quality of Life Inventory Version 4.0, Self-Esteem Scale, General Self-efficacy Scale, Depression Anxiety Stress Scale and self-made general situation questionnaire were used to conduct questionnaire survey. Results: The total score of quality of life and the scores of each dimension in Zhengzhou were significantly higher than those in HongKong, while self-esteem and anxiety were lower than those of Taiwan adolescents（P<0.05). In addition to self-esteem, anxiety and stress, the scores of quality of life and mental health of adolescents of different grades and genders in Zhengzhou were statistically different(t=13.53，20.71，10.92，20.26，14.68，-16.03，21.26；6.16，3.81，-2.22，-0.33，8.76，4.16，2.71，P<0.01). The quality of life of adolescents in HongKong and Taiwan in different grades and genders were basically the same as those in Zhengzhou, and the differences of depression and stress scores in grades were the same as those in Zhengzhou. Conclusion The overall quality of life and mental health of adolescents in Zhengzhou is better than that in Hong Kong and Taiwan. It is necessary to explore the relationship between the quality of life and mental health of adolescents in order to improve their quality of life.

Objectives: ZZThe aim was to find effective vectorization and classification models to predict a psychiatric diagnosis from text-basedmedical records. Methods: ZZElectronic medical records (n = 494) of present illness were collected retrospectively in inpatient admission notes withthree diagnoses of major depressive disorder, type 1 bipolar disorder, and schizophrenia. Data were split into 400 training data and 94 independentvalidation data. Data were vectorized by two different models such as term frequency-inverse document frequency (TF-IDF)and Doc2vec. Machine learning models for classification including stochastic gradient descent, logistic regression, support vectorclassification, and deep learning (DL) were applied to predict three psychiatric diagnoses. Five-fold cross-validation was used to find aneffective model. Metrics such as accuracy, precision, recall, and F1-score were measured for comparison between the models. Results: ZZFive-fold cross-validation in training data showed DL model with Doc2vec was the most effective model to predict the diagnosis(accuracy = 0.87, F1-score = 0.87). However, these metrics have been reduced in independent test data set with final workingDL models (accuracy = 0.79, F1-score = 0.79), while the model of logistic regression and support vector machine with Doc2vec showedslightly better performance (accuracy = 0.80, F1-score = 0.80) than the DL models with Doc2vec and others with TF-IDF. Conclusions ZZThe current results suggest that the vectorization may have more impact on the performance of classification thanthe machine learning model. However, data set had a number of limitations including small sample size, imbalance among the category,and its generalizability. With this regard, the need for research with multi-sites and large samples is suggested to improve the machinelearning models.

Objectives: ZZThe aim was to find effective vectorization and classification models to predict a psychiatric diagnosis from text-basedmedical records. Methods: ZZElectronic medical records (n = 494) of present illness were collected retrospectively in inpatient admission notes withthree diagnoses of major depressive disorder, type 1 bipolar disorder, and schizophrenia. Data were split into 400 training data and 94 independentvalidation data. Data were vectorized by two different models such as term frequency-inverse document frequency (TF-IDF)and Doc2vec. Machine learning models for classification including stochastic gradient descent, logistic regression, support vectorclassification, and deep learning (DL) were applied to predict three psychiatric diagnoses. Five-fold cross-validation was used to find aneffective model. Metrics such as accuracy, precision, recall, and F1-score were measured for comparison between the models. Results: ZZFive-fold cross-validation in training data showed DL model with Doc2vec was the most effective model to predict the diagnosis(accuracy = 0.87, F1-score = 0.87). However, these metrics have been reduced in independent test data set with final workingDL models (accuracy = 0.79, F1-score = 0.79), while the model of logistic regression and support vector machine with Doc2vec showedslightly better performance (accuracy = 0.80, F1-score = 0.80) than the DL models with Doc2vec and others with TF-IDF. Conclusions ZZThe current results suggest that the vectorization may have more impact on the performance of classification thanthe machine learning model. However, data set had a number of limitations including small sample size, imbalance among the category,and its generalizability. With this regard, the need for research with multi-sites and large samples is suggested to improve the machinelearning models.