Sepsis is a syndrome characterized by systemic inflammatory responses to a severe infection. Acute hyper-inflammatory reactions in the acute phase of sepsis have been considered as a primary reason for organ dysfunction and mortality, and advances in emergency intervention and improved intensive care management have reduced mortalities in the early phase. However it has been recognized that increased deaths in the late phase still maintain sepsis mortality high worldwide. Patients recovered from early severe illness are unable to control immune system with sepsis-induced immunosuppression such as immunological tolerance, exhaustion and apoptosis, which make them vulnerable to nosocomial and opportunistic infections ultimately leading to threat to life. Based on strategies to reverse immunosuppression, recent developments in sepsis therapy are focused on molecules having immune enhancing activities. These efforts are focused on defining and revising the immunocompromised status associated with long-term mortality.
Apoptosis ; Critical Care ; Emergencies ; Humans ; Immune System ; Immunosuppression* ; Immunotherapy ; Mortality ; Opportunistic Infections ; Precision Medicine ; Sepsis* ; Theranostic Nanomedicine

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

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.

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.

In this study, we developed MobileNurseTM; a prototype of mobile nursing information system using PDA. MobileNurseTM is designed to communicate with hospital information system(HIS) via mobile support station(MSS) which interchanges and stores clinical data. MobileNurseTM consists of 3 components. The first component is medical order checking module. It enables nurses to retrieve patients' information such as physicians' orders and test results at anywhere or anytime. The second component is nursing recording module which helps nurses to record the results of their practices at bedside. On the autosynchronization of MSS and PDA, the data in PDA and MSS can be interchanged and updated respectively. The last component is nursing unit care planing module. It is helpful for retrieving the nursing care plans of patients that are expected to be done, such as patients' discharge, consultation, or transfer. With use of PDA in clinical environment, nurses can spend more time on caring for patients by reducing time-consuming, redundant paperwork. It is promising that this 'point-of-care system enables nurses to improve the quality of nursing care.
Humans ; Information Systems* ; Nursing Care ; Nursing Records ; Nursing* ; Patient Care Planning

This study explores whether the National Health Information Database (NHID) can be used to monitor health status of entire population in Korea. We calculated the crude mortality rate and life expectancy (LE) at birth across the national, provincial, and municipal levels using the NHID eligibility database from 2004 to 2015, and compared the results with the corresponding values obtained from the Korean Statistical Information Service (KOSIS) of Statistics Korea. The study results showed that the ratio of crude mortality rate between the two data was 0.99. The absolute difference between the LE of the two data was not more than 0.5 years, and did not exceed 0.3 years in gender specific results. The concordance correlation coefficients (CCC) between the crude mortality rates from NHID and the rates from KOSIS ranged 0.997–0.999 among the municipalities. For LE, the CCC between the NHID and KOSIS across the municipalities were 0.990 in 2004–2009 and 0.985 in 2010–2015 among men, and 0.952 in 2004–2009 and 0.914 in 2010–2015 among women, respectively. Overall, the NHID was a good source for monitoring mortality and LE across national, provincial, and municipal levels with the population representativeness of entire Korean population. The results of this study indicate that NHID may well contribute to the national health promotion policy as a part of the health and health equity monitoring system.
Female ; Health Equity ; Health Promotion ; Humans ; Information Services ; Korea* ; Life Expectancy* ; Male ; Mortality* ; National Health Programs* ; Parturition

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.

BACKGROUND: We compared age-standardized overweight prevalence and their income gaps at the level of district in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: We analyzed 39,093,653 subjects in the NHSD and 926,580 individuals in the CHS between 2009 and 2014. For the comparison of body mass index (BMI) distributions, data from 26,100 subjects in the Korea National Health and Nutrition Examination Survey (KNHANES) were also analyzed. We calculated the age-standardized overweight prevalence and its interquintile income gap at the district level. We examined the magnitudes of the between-period correlation for age-standardized overweight prevalence. The differences in overweight prevalence and its income gap between the NHSD and the CHS were also investigated. RESULTS: The age-adjusted mean BMI from the CHS was lower than those from the NHSD and the KNHANES. The magnitudes of the between-period correlation for overweight prevalence were greater in the NHSD compared to the CHS. We found that the district-level overweight prevalence in the NHSD were higher in all districts of Korea than in the CHS. The correlation coefficients for income gaps in overweight prevalence between the two databases were relatively low. In addition, when using the NHSD, the district-level income inequalities in overweight were clearer especially among women than the inequalities using the CHS. CONCLUSION: The relatively large sample size for each district and measured anthropometric data in the NHSD are more likely to contribute to valid and reliable measurement of overweight inequality at the district level in Korea.
Body Mass Index ; Female ; Health Surveys ; Humans ; Korea ; Mass Screening ; Nutrition Surveys ; Overweight ; Prevalence ; Republic of Korea ; Sample Size ; Socioeconomic Factors

BACKGROUND: We compared age-standardized prevalence of cigarette smoking and their income gaps at the district-level in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: Between 2009 and 2014, 39,049,485 subjects participating in the NHSD and 989,292 participants in the CHS were analyzed. The age-standardized prevalence of smoking and their interquintile income differences were calculated for 245 districts of Korea. We examined between-period correlations for the age-standardized smoking prevalence at the district-level and investigated the district-level differences in smoking prevalence and income gaps between the two databases. RESULTS: The between-period correlation coefficients of smoking prevalence for both genders were 0.92–0.97 in NHSD and 0.58–0.69 in CHS, respectively. When using NHSD, we found significant income gaps in all districts for men and 244 districts for women. However, when CHS was analyzed, only 167 and 173 districts for men and women, respectively, showed significant income gaps. While correlation coefficients of district-level smoking prevalence from two databases were 0.87 for men and 0.85 for women, a relatively weak correlation between income gaps from the two databases was found. CONCLUSION: Based on two databases, income gaps in smoking prevalence were evident for nearly all districts of Korea. Because of the large sample size for each district, NHSD may provide stable district-level smoking prevalence and its income gap and thus should be considered as a valuable data source for monitoring district-level smoking prevalence and its socioeconomic inequality.
Female ; Health Surveys ; Humans ; Information Storage and Retrieval ; Korea ; Male ; Mass Screening ; Prevalence ; Sample Size ; Smoke ; Smoking ; Socioeconomic Factors