Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.

The circadian rhythm for mood (CRM) is a digital therapeutic, which aims to prevent mood episode and improve clinical course in patients with major mood disorders. Developed on the circadian rhythm hypothesis of mood disorder, CRM predicts the impending risk of mood episode with its built-in algorithm, utilizing wearable devices data and daily self-reports, and provides personalized feedback. In a pilot study of the CRM, the users experienced less frequent and shorter duration of mood episodes than the non-users. To investigate the efficacy of the upgraded CRM, a double-blind, randomized, sham-controlled, parallel-group trial is designed. Patients aged between 19 and 70, diagnosed with bipolar I disorder, bipolar II disorder, or major depressive disorder, in a euthymic state for more than two months, can participate. During this 12-month trial, participants are assessed for episode recurrence every three months, and the efficacy of the CRM as a potential digital therapeutic is evaluated. Trial registration: ClinicalTrials.gov Identifier: NCT05400785.

Background/Aims: We evaluated the role of next-generation sequencing (NGS)-based disease monitoring for elderly patients diagnosed with acute myeloid leukemia (AML) who received decitabine therapy. Methods: A total of 123 patients aged > 65 years with AML who received decitabine were eligible. We analyzed the dynamics of variant allele frequency (VAF) in 49 available follow-up samples after the fourth cycle of decitabine. The 58.6% VAF clearance (Δ, [VAF at diagnosis − VAF at follow-up] × 100 / VAF at diagnosis) was the optimal cut-off for predicting overall survival (OS). Results: The overall response rate was 34.1% (eight patients with complete remission [CR], six of CR with incomplete hematologic recovery, 22 with partial responses, and six with morphologic leukemia-free status). Responders (n = 42) had significantly better OS compared with non-responders (n = 42) (median, 15.3 months vs. 6.5 months; p < 0.001). Of the 49 patients available for follow-up targeted NGS analysis, 44 had trackable gene mutations. The median OS of patients with ΔVAF ≥ 58.6% (n=24) was significantly better than that of patients with ΔVAF < 58.6% (n = 19) (20.5 months vs. 9.8 months, p = 0.010). Moreover, responders with ΔVAF ≥ 58.6% (n = 20) had a significantly longer median OS compared with responders with VAF < 58.6% (n = 11) (22.5 months vs. 9.8 months, p = 0.004). Conclusions This study suggested that combining ΔVAF ≥ 58.6%, a molecular response, with morphologic and hematologic responses can more accurately predict OS in elderly AML patients after decitabine therapy.

In children and adolescents, dental age estimation is performed with the development of the teeth. Various statistical analysis methods have been used to determine the relationship between age and dental maturity and develop an accurate method of age calculation. This study attempted to apply a neural network model for the statistical analysis of dental age estimation in children and evaluated its applicability. This study used 1196 panoramic radiographs of patients aged 3–16 years, and 996 and 200 were randomly classified into training and test sets, respectively. The dental maturity of the mandibular left teeth was evaluated using Demirjian's method, the neural network model using the backpropagation algorithm was derived using training sets, and the errors were evaluated using 100 radiographs of each male and female as test sets. In addition, multiple linear regression analysis was conducted on the same training set, and the error was calculated by applying it to the test set and comparing it with the error of the neural network model. In the neural network model, the mean absolute error (MAE) and root mean squared error (RMSE) were 0.589 and 0.783 in male subjects and 0.529 and 0.760 in female subjects, respectively. In the multiple linear regression model, the MAE and RMSE were 0.600 and 0.748 in male subjects and 0.566 and 0.789 in female subjects, respectively. When applying the neural network model to the statistical analysis of the dental developmental stage, the results were as accurate as those of conventional statistical analysis methods. This study’s approach is expected to be useful for estimating the ages of children.

Given that tooth loss is a degenerative change, the number of residual teeth may be used to specify a particular age range as a marker for age estimation. This study examined changes in the number of teeth with age using a nationwide oral survey database and derived the age distribution of the Korean population according to the number of teeth. Data on the number of teeth and age were extracted from the oral examination data of the Korean National Health and Nutrition Examination Survey (KNHANES) from 2016 to 2018. Statistical analyses of a complex sample survey were performed using weighted values. The distribution range of the number of teeth by age was broad. The proportion of young people decreased progressively as the number of remaining teeth decreased. In contrast, the proportion of those from the older age group decreased slightly as the number of teeth increased. The number of teeth was subdivided into groups of four, age was categorized into 5-year intervals, and the distribution of age groups by the number of teeth was analyzed. We attempted to determine the age group threshold at approximately 95th percentile for age. In summary, we found that if there were ≤4, 5-12, and 13-20 residual teeth, the estimated age was ≥60, ≥55, and ≥50 years, respectively, with an approximately 95% probability. When many teeth are lost and it is difficult to apply conventional dental age estimation methods, our method may assist in narrowing the age range, although it is not an accurate age determination method.

Lifestyle is a critical aspect of diabetes management. We aimed to define a healthy lifestyle using objectively measured parameters obtained from a wearable activity tracker (Fitbit) in patients with type 2 diabetes. This prospective observational study included 24 patients (mean age, 46.8 years) with type 2 diabetes. Expectation–maximization clustering analysis produced two groups: A (n=9) and B (n=15). Group A had a higher daily step count, lower resting heart rate, longer sleep duration, and lower mean time differences in going to sleep and waking up than group B. A Shapley additive explanation summary analysis indicated that sleep-related factors were key elements for clustering. The mean hemoglobin A1c level was 0.3 percentage points lower at the end of follow-up in group A than in group B. Factors related to regular sleep patterns could be possible determinants of lifestyle clustering in patients with type 2 diabetes.

Anal gland/duct cyst (AGC) is rare and observed in only 0.05% of patients undergoing anal surgery. AGC is thought to be a retention cyst in the anal gland and arises when an obstruction of the anal duct causes fluid collection in the anal gland. We report a case of AGC in a 66-year-old woman without anal symptoms. Found by colonoscopy, the AGC was excised transanally. The histopathology of the specimen confirmed AGC. Colonoscopists should include AGC in the differential diagnosis of anal canal mass and rule out of malignancy. Excision is recommended for definitive diagnosis and treatment.

Objective: Evidence for the association between circadian rhythm delay and depression is accumulating. Genetic studies have shown that certain polymorphisms in circadian genes are potential genetic markers of diurnal preference. Along with circadian genes, there is a growing interest in other genetic effects on circadian rhythms. This study evaluated whether the HTR2A rs6311 (-1438C/T) polymorphism is associated with diurnal preference in a Korean population. Methods: A total of 510 healthy subjects were included in this study. All subjects were genotyped for the HTR2A rs6311 polymorphism and they completed the Korean version of the composite scale of morningness (CSM). Results: The C allele carriers (C/C+C/T) showed significantly higher CSM scores compared to C allele non-carriers (T/T) (t=2.22, p= 0.03), suggesting the existence of a morning chronotype tendency in C allele carriers. In other words, the T/T genotype may be associated with the evening chronotype. Conclusion These results suggest that the HTR2A rs6311 polymorphism may be associated with diurnal preference in a healthy Korean population. The absence of the C allele may be responsible for the increasing susceptibility to eveningness in the Korean population. Further studies on HTR2A polymorphisms that evaluate their interactions with various candidate genes and differences in phenotypic expression of polymorphisms according to ethnic groups are warranted to fully understand their association with diurnal preference.

Hidradenoma papilliferum is a rare benign cystic tumor that originates from apocrine glands or anogenital mammary glands. Here, we describe 2 cases of hidradenoma papilliferum of the anus. Two female patients aged 39 and 35 presented with perianal masses with hemorrhoids. The patients underwent hemorrhoidectomy and excision of the lesion. Histopathology confirmed the masses as hidradenoma papilliferum. The postoperative course was uneventful for both patients, and there were no recurrences after 18 and 12 months of follow-up, respectively. Proctologists should consider hidradenoma papilliferum in their differential diagnosis of benign anal tumors. Surgical excision is necessary for diagnosis and treatment of hidradenoma papilliferum.
Acrospiroma ; Anal Canal ; Apocrine Glands ; Diagnosis ; Diagnosis, Differential ; Female ; Follow-Up Studies ; Hemorrhoidectomy ; Hemorrhoids ; Humans ; Mammary Glands, Human ; Recurrence

OBJECTIVE: The biological rhythm is closely related to mood symptoms. The purpose of this study was to assess the differences in biological rhythms among subjects with mood disorder [bipolar I disorder (BD I), bipolar II disorder (BD II), major depressive disorder (MDD)] and healthy control subjects.METHODS: A total of 462 early-onset mood disorder subjects were recruited from nine hospitals. The controls subjects were recruited from the general population of South Korea. Subject groups and control subject were evaluated for the Korean language version of Biological Rhythms Interview of Assessment in Neuropsychiatry (K-BRIAN) at the initial evaluation.RESULTS: The mean K-BRIAN scores were 35.59 [standard deviation (SD)=13.37] for BD I, 43.05 (SD=11.85) for BD II, 43.55 (SD=12.22) for MDD, and 29.1 (SD=8.15) for the control group. In the case of mood disorders, biological rhythm disturbances were greater than that in the control group (p<0.05). A significant difference existed between BD I and BD II (BD I Bipolar Disorder ; Cohort Studies ; Depression ; Depressive Disorder, Major ; Korea ; Mood Disorders ; Neuropsychiatry ; Periodicity