This study examined the transverse relationship between the maxilla and mandible in children with mixed dentition. The study focused on the primary second molar and the permanent first molar in relation to the anteroposterior skeletal patterns using cone-beam computed tomography (CBCT). A total of 102 patients from the Pediatric Dentistry Department at Pusan Dental Hospital were classified into three skeletal groups (Class I, Ⅱ, Ⅲ) based on the ANB angle (angle formed by A-point-nasion-B-point). CBCT scans were analyzed to assess the transverse dimensions of basal bone and dento-alveolar measurements. The results showed that Class Ⅲ patients exhibited a significantly narrower maxillary basal bone compared with Class I and Ⅱ patients. The mandibular basal width was not significantly different between the classes. For primary second molars, Class Ⅲ patients showed significantly narrower maxillary alveolar bone width at the root bifurcation level (51.7 ± 2.5 mm, p < 0.05) compared with Class I and II patients. For permanent first molars, the maxillary occlusal fossa distance was smallest in Class II (45.4 ± 2.4 mm, p < 0.05), and was significantly different from Class I and Class Ⅲ. Maxillary first molar inclination was more lingually inclined in Class Ⅱ patients (99.0 ± 4.2°, p < 0.05) compared with Class Ⅲ patients, whereas Class Ⅲ patients exhibited more buccal inclination. This study highlights the correlation between transverse discrepancies and anteroposterior skeletal classifications, with Class Ⅲ showing a narrower maxillary base and Class Ⅱ patients presenting greater lingual compensation. These findings may aid pediatric dentists in diagnosing transverse relationships in mixed dentition.

This study aimed to investigate the dental utilization status, satisfaction with dental treatment, and the need for improvement among pediatric patients with rare diseases in Korea. A survey was conducted from June 2023 to May 2024 among caregivers of patients with rare diseases who visited the pediatric dentistry departments of eight dental institutions. The questionnaire for this study was divided into two sections: 126 caregivers participated in the dental utilization survey, while 91 caregivers completed the survey on satisfaction with dental treatment. Many caregivers believed that the patient’s poor oral health could impact overall health and reported positive functional and psychological changes following dental treatment. However, dental care for these patients presents challenges due to insufficient oral care information, specialized dentists, specialized dental facilities, and insurance coverage. Caregivers identified the need for an increase in specialized dental facilities as the highest priority (42.9%), with many emphasizing the necessity for expanded insurance coverage (38.9%). Notably, caregivers of patients who had undergone dental caries treatment advocated for broader insurance coverage (p = 0.0141), particularly for prosthetic (p = 0.0330) and restorative treatments (p = 0.0129). Furthermore, caregivers of patients with congenital disorders reported a significant economic burden associated with orthodontic treatment (p = 0.0405). Additionally, caregivers emphasized the need for an increase in specialized dentists (33.3%) and improved collaboration with pediatricians (25.4%). This study underscores the critical necessity for tailored policies and comprehensive support systems that reflect the current needs of the dental care system for pediatric patients with rare diseases.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study examined the transverse relationship between the maxilla and mandible in children with mixed dentition. The study focused on the primary second molar and the permanent first molar in relation to the anteroposterior skeletal patterns using cone-beam computed tomography (CBCT). A total of 102 patients from the Pediatric Dentistry Department at Pusan Dental Hospital were classified into three skeletal groups (Class I, Ⅱ, Ⅲ) based on the ANB angle (angle formed by A-point-nasion-B-point). CBCT scans were analyzed to assess the transverse dimensions of basal bone and dento-alveolar measurements. The results showed that Class Ⅲ patients exhibited a significantly narrower maxillary basal bone compared with Class I and Ⅱ patients. The mandibular basal width was not significantly different between the classes. For primary second molars, Class Ⅲ patients showed significantly narrower maxillary alveolar bone width at the root bifurcation level (51.7 ± 2.5 mm, p < 0.05) compared with Class I and II patients. For permanent first molars, the maxillary occlusal fossa distance was smallest in Class II (45.4 ± 2.4 mm, p < 0.05), and was significantly different from Class I and Class Ⅲ. Maxillary first molar inclination was more lingually inclined in Class Ⅱ patients (99.0 ± 4.2°, p < 0.05) compared with Class Ⅲ patients, whereas Class Ⅲ patients exhibited more buccal inclination. This study highlights the correlation between transverse discrepancies and anteroposterior skeletal classifications, with Class Ⅲ showing a narrower maxillary base and Class Ⅱ patients presenting greater lingual compensation. These findings may aid pediatric dentists in diagnosing transverse relationships in mixed dentition.

This study aimed to investigate the dental utilization status, satisfaction with dental treatment, and the need for improvement among pediatric patients with rare diseases in Korea. A survey was conducted from June 2023 to May 2024 among caregivers of patients with rare diseases who visited the pediatric dentistry departments of eight dental institutions. The questionnaire for this study was divided into two sections: 126 caregivers participated in the dental utilization survey, while 91 caregivers completed the survey on satisfaction with dental treatment. Many caregivers believed that the patient’s poor oral health could impact overall health and reported positive functional and psychological changes following dental treatment. However, dental care for these patients presents challenges due to insufficient oral care information, specialized dentists, specialized dental facilities, and insurance coverage. Caregivers identified the need for an increase in specialized dental facilities as the highest priority (42.9%), with many emphasizing the necessity for expanded insurance coverage (38.9%). Notably, caregivers of patients who had undergone dental caries treatment advocated for broader insurance coverage (p = 0.0141), particularly for prosthetic (p = 0.0330) and restorative treatments (p = 0.0129). Furthermore, caregivers of patients with congenital disorders reported a significant economic burden associated with orthodontic treatment (p = 0.0405). Additionally, caregivers emphasized the need for an increase in specialized dentists (33.3%) and improved collaboration with pediatricians (25.4%). This study underscores the critical necessity for tailored policies and comprehensive support systems that reflect the current needs of the dental care system for pediatric patients with rare diseases.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

This study examined the transverse relationship between the maxilla and mandible in children with mixed dentition. The study focused on the primary second molar and the permanent first molar in relation to the anteroposterior skeletal patterns using cone-beam computed tomography (CBCT). A total of 102 patients from the Pediatric Dentistry Department at Pusan Dental Hospital were classified into three skeletal groups (Class I, Ⅱ, Ⅲ) based on the ANB angle (angle formed by A-point-nasion-B-point). CBCT scans were analyzed to assess the transverse dimensions of basal bone and dento-alveolar measurements. The results showed that Class Ⅲ patients exhibited a significantly narrower maxillary basal bone compared with Class I and Ⅱ patients. The mandibular basal width was not significantly different between the classes. For primary second molars, Class Ⅲ patients showed significantly narrower maxillary alveolar bone width at the root bifurcation level (51.7 ± 2.5 mm, p < 0.05) compared with Class I and II patients. For permanent first molars, the maxillary occlusal fossa distance was smallest in Class II (45.4 ± 2.4 mm, p < 0.05), and was significantly different from Class I and Class Ⅲ. Maxillary first molar inclination was more lingually inclined in Class Ⅱ patients (99.0 ± 4.2°, p < 0.05) compared with Class Ⅲ patients, whereas Class Ⅲ patients exhibited more buccal inclination. This study highlights the correlation between transverse discrepancies and anteroposterior skeletal classifications, with Class Ⅲ showing a narrower maxillary base and Class Ⅱ patients presenting greater lingual compensation. These findings may aid pediatric dentists in diagnosing transverse relationships in mixed dentition.

This study aimed to investigate the dental utilization status, satisfaction with dental treatment, and the need for improvement among pediatric patients with rare diseases in Korea. A survey was conducted from June 2023 to May 2024 among caregivers of patients with rare diseases who visited the pediatric dentistry departments of eight dental institutions. The questionnaire for this study was divided into two sections: 126 caregivers participated in the dental utilization survey, while 91 caregivers completed the survey on satisfaction with dental treatment. Many caregivers believed that the patient’s poor oral health could impact overall health and reported positive functional and psychological changes following dental treatment. However, dental care for these patients presents challenges due to insufficient oral care information, specialized dentists, specialized dental facilities, and insurance coverage. Caregivers identified the need for an increase in specialized dental facilities as the highest priority (42.9%), with many emphasizing the necessity for expanded insurance coverage (38.9%). Notably, caregivers of patients who had undergone dental caries treatment advocated for broader insurance coverage (p = 0.0141), particularly for prosthetic (p = 0.0330) and restorative treatments (p = 0.0129). Furthermore, caregivers of patients with congenital disorders reported a significant economic burden associated with orthodontic treatment (p = 0.0405). Additionally, caregivers emphasized the need for an increase in specialized dentists (33.3%) and improved collaboration with pediatricians (25.4%). This study underscores the critical necessity for tailored policies and comprehensive support systems that reflect the current needs of the dental care system for pediatric patients with rare diseases.

Background/Aims: Pancreatic cancer poses significant challenges due to its tendency for late-stage diagnosis and high mortality rates. Cryoablation, a technique used to treat various types of cancer, has shown potential in enhancing the prognosis of pancreatic cancer when combined with other therapies. However, its implementation is often limited by the need for lengthy procedures and specialized equipment. This study aims to develop a cryoablation needle optimized for endoscopic ultrasonography to simplify its application in treating pancreatic cancer. Methods: The study involved conducting cryoablation experiments on swine liver tissue. It utilized cryo-needles to evaluate the extent of cell death across various temperatures and durations of cryoablation. Results: The cryoablation system, which employed liquid carbon dioxide, achieved rapid cooling, reaching temperatures below –60 °C within 30 seconds and maintained the cryoablation process for 200 seconds. These conditions resulted in necrosis of the liver tissue. Notable cellular changes were observed up to 15 mm away from the cryoablation needle. Conclusions This experimental study successfully demonstrated the efficacy of using a cryo-needle for cryoablation in swine liver tissue. Further trials involving pancreatic tissue are expected to verify its effectiveness, underscoring the importance of continued research to establish its role as a complementary therapy in pancreatic cancer treatment.