Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease that culminates in respiratory failure and death due to irreversible scarring of the distal lung. While initially considered a chronic inflammatory disorder, the aberrant function of the alveolar epithelium is now acknowledged as playing a central role in the pathophysiology of IPF. This study aimed to investigate the regenerative capacity of alveolar type 2 (AT2) cells using IPF-derived alveolar organoids and to examine the effects of disease progression on this capacity. Methods: Lung tissues from three pneumothorax patients and six IPF patients (early and advanced stages) were obtained through video-assisted thoracoscopic surgery and lung transplantation. HTII-280+ cells were isolated from CD31-CD45-epithelial cell adhesion molecule (EpCAM)+ cells in the distal lungs of IPF and pneumothorax patients using fluorescence-activated cell sorting (FACS) and resuspended in 48-well plates to establish IPF-derived alveolar organoids. Immunostaining was used to verify the presence of AT2 cells. Results: FACS sorting yielded approximately 1% of AT2 cells in early IPF tissue, and the number decreased as the disease progressed, in contrast to 2.7% in pneumothorax. Additionally, the cultured organoids in the IPF groups were smaller and less numerous compared to those from pneumothorax patients. The colony forming efficiency decreased as the disease advanced. Immunostaining results showed that the IPF organoids expressed less surfactant protein C (SFTPC) compared to the pneumothorax group and contained keratin 5+ (KRT5+) cells. Conclusion This study confirmed that the regenerative capacity of AT2 cells in IPF decreases as the disease progresses, with IPF-derived AT2 cells inherently exhibiting functional abnormalities and altered differentiation plasticity.

Background: F-18 Fluorodeoxyglucose positron emission tomography (F-18 FDG PET), which can cover the body from the skull base to the thigh in one scan, is beneficial for evaluating distant metastasis. F-18 FDG PET has interested policymakers because of its relatively high cost. This study investigated the effect of the F-18 FDG PET reimbursement criteria amendment on healthcare behavior in breast cancer using an interrupted time series (ITS) analysis. Methods: We retrospectively analyzed the inpatient and outpatient data from Korea’s Health Insurance Review and Assessment Service (HIRA) from January 1, 2013 to December 31, 2018. ITS analysis was performed for the number of each medical imaging modality and the total medical imaging cost of the breast cancer patients. Results: The annual number of breast cancer patients has been increasing steadily since 2013. The trend of F-18 FDG PET increased before the reimbursement criteria was amended, but intensely decreased immediately thereafter. The chest and abdomen computed tomography scans showed a statistically significant increase immediately after the amendment and kept steadily increasing. A change in the total medical imaging cost for the breast cancer patient claimed every month showed an increasing trend before the amendment (β = 5,475, standard error [SE] = 1,992, P = 0.008) and rapid change immediately after (β = −103,317, SE = 16,152, P < 0.001). However, there was no significant change in the total medical imaging cost at the long-term follow-up (β = −912, SE = 1,981, P = 0.647). Conclusion Restriction of health insurance coverage for cancer may affect healthcare behaviors. To compensate for it, the policymakers must consider this and anticipate the impact following implementation.

Mast cells integrate innate and adaptive immunity and are implicated in pathophysiological conditions, including allergy, asthma, and anaphylaxis. Cross-linking of the high-affinity IgE receptor (FcεRI) initiates diverse signal transduction pathways and induces release of proinflammatory mediators by mast cells. In this study, we demonstrated that hyperactivation of mechanistic target of rapamycin (mTOR) signaling using the mTOR activator MHY1485 suppresses FcεRI-mediated mast cell degranulation and cytokine secretion. MHY1485 treatment increased ribosomal protein S6 kinase (S6K) and eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) phosphorylation, which are downstream targets of mTOR complex 1 (mTORC1), but decreased phosphorylation of Akt on mTOR complex 2 (mTORC2) target site serine 473. In addition, this activator decreased β-hexosaminidase, IL-6, and tumor necrosis factor α (TNF-α) release in murine bone marrow-derived mast cells (BMMCs) after FcεRI stimulation. Furthermore, MHY1485-treated BMMCs showed significantly decreased proliferation when cultured with IL-3. These findings suggested hyperactivation of mTORC1 as a therapeutic strategy for mast cell-related diseases.
Adaptive Immunity ; Anaphylaxis ; Asthma ; Cell Degranulation ; Cell Proliferation ; Hypersensitivity ; Immunoglobulin E ; Interleukin-3 ; Interleukin-6 ; Mast Cells* ; Peptide Initiation Factors ; Phosphorylation ; Ribosomal Protein S6 Kinases ; Serine ; Signal Transduction ; Sirolimus ; Tumor Necrosis Factor-alpha