Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Tumor microenvironment is intrinsically hypoxic with abundant hypoxia-inducible factors-1α (HIF-1α), a primary regulator of the cellular response to hypoxia and various stresses imposed on the tumor cells. HIF-1α increases radioresistance and chemoresistance by reducing DNA damage, increasing repair of DNA damage, enhancing glycolysis that increases antioxidant capacity of tumors cells, and promoting angiogenesis. In addition, HIF-1α markedly enhances drug efflux, leading to multidrug resistance. Radiotherapy and certain chemotherapy drugs evoke profound anti-tumor immunity by inducing immunologic cell death that release tumor-associated antigens together with numerous pro-immunological factors, leading to priming of cytotoxic CD8+ T cells and enhancing the cytotoxicity of macrophages and natural killer cells. Radiotherapy and chemotherapy of tumors significantly increase HIF-1α activity in tumor cells. Unfortunately, HIF-1α effectively promotes various immune suppressive pathways including secretion of immune suppressive cytokines, activation of myeloid-derived suppressor cells, activation of regulatory T cells, inhibition of T cells priming and activity, and upregulation of immune checkpoints. Consequently, the anti-tumor immunity elevated by radiotherapy and chemotherapy is counterbalanced or masked by the potent immune suppression promoted by HIF-1α. Effective inhibition of HIF-1α may significantly increase the efficacy of radiotherapy and chemotherapy by increasing radiosensitivity and chemosensitivity of tumor cells and also by upregulating anti-tumor immunity.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Tumor microenvironment is intrinsically hypoxic with abundant hypoxia-inducible factors-1α (HIF-1α), a primary regulator of the cellular response to hypoxia and various stresses imposed on the tumor cells. HIF-1α increases radioresistance and chemoresistance by reducing DNA damage, increasing repair of DNA damage, enhancing glycolysis that increases antioxidant capacity of tumors cells, and promoting angiogenesis. In addition, HIF-1α markedly enhances drug efflux, leading to multidrug resistance. Radiotherapy and certain chemotherapy drugs evoke profound anti-tumor immunity by inducing immunologic cell death that release tumor-associated antigens together with numerous pro-immunological factors, leading to priming of cytotoxic CD8+ T cells and enhancing the cytotoxicity of macrophages and natural killer cells. Radiotherapy and chemotherapy of tumors significantly increase HIF-1α activity in tumor cells. Unfortunately, HIF-1α effectively promotes various immune suppressive pathways including secretion of immune suppressive cytokines, activation of myeloid-derived suppressor cells, activation of regulatory T cells, inhibition of T cells priming and activity, and upregulation of immune checkpoints. Consequently, the anti-tumor immunity elevated by radiotherapy and chemotherapy is counterbalanced or masked by the potent immune suppression promoted by HIF-1α. Effective inhibition of HIF-1α may significantly increase the efficacy of radiotherapy and chemotherapy by increasing radiosensitivity and chemosensitivity of tumor cells and also by upregulating anti-tumor immunity.

Purpose: It is well known that the majority of the extranodal marginal zone lymphomas of mucosa-associated lymphoid tissues (MALT lymphomas) are associated with microbiota, e.g., gastric MALT lymphoma with Helicobacter pylori. In general, they are very sensitive to low-dose radiotherapy and chemotherapeutic agents. The microbiota profile is not clearly elucidated in bronchus-associated lymphoid tissue (BALT) lymphoma, a rare type of MALT lymphoma in the lung. Thus, this study aimed to clarify the intratumor microbiome in BALT lymphoma using the third-generation next-generation sequencing (NGS) method. Materials and Methods: DNAs were extracted from 12 formalin-fixed paraffin-embedded (FFPE) tumor tissues obtained from BALT lymphoma patients diagnosed between 1990 and 2016. 16S rRNA gene was amplified by polymerase chain reaction. Amplicons were sequenced using a Nanopore platform. Next-generation sequencing analysis was performed to assess microbial profiles. For comparison, FFPE specimens from nine non-cancerous lung tissues were also analyzed. Results: Specific bacterial families including Burkholderiaceae, Bacillaceae, and Microbacteriaceae were associated with BALT lymphoma by a linear discriminant analysis effect size approach. Although the number of specimens was limited, BALT lymphomas exhibited significantly higher microbial abundance and diversity with distinct microbial composition patterns and correlation networks than non-cancerous lung tissues. Conclusion This study provides the first insight into intratumor microbiome in BALT lymphoma using the third-generation NGS method. A distinct microbial composition suggests the presence of a unique tumor microenvironment of BALT lymphoma.

Tumor microenvironment is intrinsically hypoxic with abundant hypoxia-inducible factors-1α (HIF-1α), a primary regulator of the cellular response to hypoxia and various stresses imposed on the tumor cells. HIF-1α increases radioresistance and chemoresistance by reducing DNA damage, increasing repair of DNA damage, enhancing glycolysis that increases antioxidant capacity of tumors cells, and promoting angiogenesis. In addition, HIF-1α markedly enhances drug efflux, leading to multidrug resistance. Radiotherapy and certain chemotherapy drugs evoke profound anti-tumor immunity by inducing immunologic cell death that release tumor-associated antigens together with numerous pro-immunological factors, leading to priming of cytotoxic CD8+ T cells and enhancing the cytotoxicity of macrophages and natural killer cells. Radiotherapy and chemotherapy of tumors significantly increase HIF-1α activity in tumor cells. Unfortunately, HIF-1α effectively promotes various immune suppressive pathways including secretion of immune suppressive cytokines, activation of myeloid-derived suppressor cells, activation of regulatory T cells, inhibition of T cells priming and activity, and upregulation of immune checkpoints. Consequently, the anti-tumor immunity elevated by radiotherapy and chemotherapy is counterbalanced or masked by the potent immune suppression promoted by HIF-1α. Effective inhibition of HIF-1α may significantly increase the efficacy of radiotherapy and chemotherapy by increasing radiosensitivity and chemosensitivity of tumor cells and also by upregulating anti-tumor immunity.

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.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Objective: Classification guides the surgical approach and predicts prognosis. However, existing classifications of spinal schwannomas often result in a high ‘unclassified’ rate. Here, we aim to develop a new comprehensive classification for spinal schwannomas based on their presumed origin. We compared the new classification with the existing classifications regarding the rate of ‘unclassified’. Finally, we assessed the surgical strategies, outcomes, and complications according to each type of the new classification. Methods: A new classification with 9 types was created by analyzing the anatomy of spinal nerves and the origin of significant tumor portions and cystic components in preoperative magnetic resonance images. A total of 482 patients with spinal schwannomas were analyzed to compare our new classification with the existing classifications. We defined ‘unclassified’ as the inability to classify a patient with spinal schwannoma using the classification criteria. Surgical approaches and outcomes were also aligned with our new classification. Results: Our classification uniquely reported no ‘unclassified’ cases, indicating full applicability. Also, the classification has demonstrated usefulness in predicting the surgical outcome with the approach planned. Gross total removal rates reached 88.0% overall, with type 1 and type 2 tumors at 95.3% and 96.0% respectively. The approach varied with tumor type, with laminectomy predominantly used for types 1, 2, and 9, and facetectomy with posterior fixation used for type 3 tumors. Conclusion The new classification for spinal schwannomas based on presumed origin is applicable to all spinal schwannomas. It could help plan a surgical approach and predict its outcome, compared with existing classifications.