Purpose: Human breast milk (HBM) contains immune components that produced and delivered from the mother along with nutrients necessary for the baby. MicroRNA (miRNA) is a small noncoding RNA molecule, that is used as an ideal biomarker for diagnosis and prognosis of various diseases and are more abundant in HBM. We analyzed and compared the immune components and miRNAs of HBM. Methods: HBM were collected from 20 healthy breastfeeding mothers. We measured the amount of lactoferrin, lysozyme, and immunoglobulin A (IgA) and extracted the miRNAs from each breast milk samples. Next, the top 5 and bottom 5 expressed miRNAs were compared and analyzed based on the amounts of the 3 immune components. Results: The mean levels and ranges of lactoferrin, lysozyme, and IgA were 6.33 (2.24–14.77)×106 ng/mL, 9.90 (1.42–17.59)×107 pg/mL, and 6.64 (0.48–20.01)×105 ng/mL, respectively. The miRNAs concentration per 1 mL of skim milk was 40.54 (14.95–110.01) ng/μL. Comparing the bottom 5 and top 5 groups of each immune component, 19 miRNAs were significantly upregulated (6, 9, and 4 targeting lactoferrin, lysozyme, and IgA, respectively) and 21 were significantly downregulated (4, 9, and 8 targeting lactoferrin, lysozyme, and IgA, respectively). There were no miRNAs that were expressed significantly higher or lower in common to all 3 components.However, 2 and 3 miRNAs were commonly overexpressed and underexpressed, in the top 5 groups of lysozyme and IgA concentrations. Conclusion We identified the immune components and miRNAs in breast milk and found that each individual has different ingredients.

Purpose: Human breast milk (HBM) contains immune components that produced and delivered from the mother along with nutrients necessary for the baby. MicroRNA (miRNA) is a small noncoding RNA molecule, that is used as an ideal biomarker for diagnosis and prognosis of various diseases and are more abundant in HBM. We analyzed and compared the immune components and miRNAs of HBM. Methods: HBM were collected from 20 healthy breastfeeding mothers. We measured the amount of lactoferrin, lysozyme, and immunoglobulin A (IgA) and extracted the miRNAs from each breast milk samples. Next, the top 5 and bottom 5 expressed miRNAs were compared and analyzed based on the amounts of the 3 immune components. Results: The mean levels and ranges of lactoferrin, lysozyme, and IgA were 6.33 (2.24–14.77)×106 ng/mL, 9.90 (1.42–17.59)×107 pg/mL, and 6.64 (0.48–20.01)×105 ng/mL, respectively. The miRNAs concentration per 1 mL of skim milk was 40.54 (14.95–110.01) ng/μL. Comparing the bottom 5 and top 5 groups of each immune component, 19 miRNAs were significantly upregulated (6, 9, and 4 targeting lactoferrin, lysozyme, and IgA, respectively) and 21 were significantly downregulated (4, 9, and 8 targeting lactoferrin, lysozyme, and IgA, respectively). There were no miRNAs that were expressed significantly higher or lower in common to all 3 components.However, 2 and 3 miRNAs were commonly overexpressed and underexpressed, in the top 5 groups of lysozyme and IgA concentrations. Conclusion We identified the immune components and miRNAs in breast milk and found that each individual has different ingredients.

Purpose: Human breast milk (HBM) contains immune components that produced and delivered from the mother along with nutrients necessary for the baby. MicroRNA (miRNA) is a small noncoding RNA molecule, that is used as an ideal biomarker for diagnosis and prognosis of various diseases and are more abundant in HBM. We analyzed and compared the immune components and miRNAs of HBM. Methods: HBM were collected from 20 healthy breastfeeding mothers. We measured the amount of lactoferrin, lysozyme, and immunoglobulin A (IgA) and extracted the miRNAs from each breast milk samples. Next, the top 5 and bottom 5 expressed miRNAs were compared and analyzed based on the amounts of the 3 immune components. Results: The mean levels and ranges of lactoferrin, lysozyme, and IgA were 6.33 (2.24–14.77)×106 ng/mL, 9.90 (1.42–17.59)×107 pg/mL, and 6.64 (0.48–20.01)×105 ng/mL, respectively. The miRNAs concentration per 1 mL of skim milk was 40.54 (14.95–110.01) ng/μL. Comparing the bottom 5 and top 5 groups of each immune component, 19 miRNAs were significantly upregulated (6, 9, and 4 targeting lactoferrin, lysozyme, and IgA, respectively) and 21 were significantly downregulated (4, 9, and 8 targeting lactoferrin, lysozyme, and IgA, respectively). There were no miRNAs that were expressed significantly higher or lower in common to all 3 components.However, 2 and 3 miRNAs were commonly overexpressed and underexpressed, in the top 5 groups of lysozyme and IgA concentrations. Conclusion We identified the immune components and miRNAs in breast milk and found that each individual has different ingredients.

Purpose: Human breast milk (HBM) contains immune components that produced and delivered from the mother along with nutrients necessary for the baby. MicroRNA (miRNA) is a small noncoding RNA molecule, that is used as an ideal biomarker for diagnosis and prognosis of various diseases and are more abundant in HBM. We analyzed and compared the immune components and miRNAs of HBM. Methods: HBM were collected from 20 healthy breastfeeding mothers. We measured the amount of lactoferrin, lysozyme, and immunoglobulin A (IgA) and extracted the miRNAs from each breast milk samples. Next, the top 5 and bottom 5 expressed miRNAs were compared and analyzed based on the amounts of the 3 immune components. Results: The mean levels and ranges of lactoferrin, lysozyme, and IgA were 6.33 (2.24–14.77)×106 ng/mL, 9.90 (1.42–17.59)×107 pg/mL, and 6.64 (0.48–20.01)×105 ng/mL, respectively. The miRNAs concentration per 1 mL of skim milk was 40.54 (14.95–110.01) ng/μL. Comparing the bottom 5 and top 5 groups of each immune component, 19 miRNAs were significantly upregulated (6, 9, and 4 targeting lactoferrin, lysozyme, and IgA, respectively) and 21 were significantly downregulated (4, 9, and 8 targeting lactoferrin, lysozyme, and IgA, respectively). There were no miRNAs that were expressed significantly higher or lower in common to all 3 components.However, 2 and 3 miRNAs were commonly overexpressed and underexpressed, in the top 5 groups of lysozyme and IgA concentrations. Conclusion We identified the immune components and miRNAs in breast milk and found that each individual has different ingredients.

Purpose: Human breast milk (HBM) contains immune components that produced and delivered from the mother along with nutrients necessary for the baby. MicroRNA (miRNA) is a small noncoding RNA molecule, that is used as an ideal biomarker for diagnosis and prognosis of various diseases and are more abundant in HBM. We analyzed and compared the immune components and miRNAs of HBM. Methods: HBM were collected from 20 healthy breastfeeding mothers. We measured the amount of lactoferrin, lysozyme, and immunoglobulin A (IgA) and extracted the miRNAs from each breast milk samples. Next, the top 5 and bottom 5 expressed miRNAs were compared and analyzed based on the amounts of the 3 immune components. Results: The mean levels and ranges of lactoferrin, lysozyme, and IgA were 6.33 (2.24–14.77)×106 ng/mL, 9.90 (1.42–17.59)×107 pg/mL, and 6.64 (0.48–20.01)×105 ng/mL, respectively. The miRNAs concentration per 1 mL of skim milk was 40.54 (14.95–110.01) ng/μL. Comparing the bottom 5 and top 5 groups of each immune component, 19 miRNAs were significantly upregulated (6, 9, and 4 targeting lactoferrin, lysozyme, and IgA, respectively) and 21 were significantly downregulated (4, 9, and 8 targeting lactoferrin, lysozyme, and IgA, respectively). There were no miRNAs that were expressed significantly higher or lower in common to all 3 components.However, 2 and 3 miRNAs were commonly overexpressed and underexpressed, in the top 5 groups of lysozyme and IgA concentrations. Conclusion We identified the immune components and miRNAs in breast milk and found that each individual has different ingredients.

Novel strategies are required to reduce the risk of developing diabetes and/or clinical outcomes and complications of diabetes. In this regard, the role of the circadian system may be a potential candidate for the prevention of diabetes. We reviewed evidence from animal, clinical, and epidemiological studies linking the circadian system to various aspects of the pathophysiology and clinical outcomes of diabetes. The circadian clock governs genetic, metabolic, hormonal, and behavioral signals in anticipation of cyclic 24-hour events through interactions between a “central clock” in the suprachiasmatic nucleus and “peripheral clocks” in the whole body. Currently, circadian rhythmicity in humans can be subjectively or objectively assessed by measuring melatonin and glucocorticoid levels, core body temperature, peripheral blood, oral mucosa, hair follicles, rest-activity cycles, sleep diaries, and circadian chronotypes. In this review, we summarized various circadian misalignments, such as altered light-dark, sleep-wake, rest-activity, fasting-feeding, shift work, evening chronotype, and social jetlag, as well as mutations in clock genes that could contribute to the development of diabetes and poor glycemic status in patients with diabetes. Targeting critical components of the circadian system could deliver potential candidates for the treatment and prevention of type 2 diabetes mellitus in the future.

Background: Malignant struma ovarii (MSO) is a very rare disease in which thyroid cancer originates from the ovary. Because it is rare for endocrinologists to encounter patients with MSO, endocrinologists may have a limited understanding of the disease. Therefore, we analyzed and introduced its incidence and clinical course in a tertiary hospital in Korea. Methods: We retrospectively investigated the clinical data of 170 patients who underwent surgery for struma ovarii at the Department of Obstetrics and Gynecology of Samsung Medical Center from 1994 to May 2023. Results: Among 170 patients with struma ovarii, 15 (8.8%) were diagnosed with MSO. The median age of patients with MSO was 48 years (range, 30 to 74), and the median tumor size was 3.3 cm (range, 0.5 to 11.0). Papillary thyroid carcinoma (46.7%) was the most common subtypes followed by follicular thyroid carcinoma (26.7%). All patients were diagnosed after surgery, with no predictions from preoperative imaging. The surgical extent of gynecological surgery was variable. Four patients (26.7%) underwent thyroidectomy for thyroid cancer, while one underwent total thyroidectomy and radioactive iodine therapy for MSO with peritoneal metastasis. Except for one patient who underwent hemithyroidectomy, thyroid stimulating hormone suppression therapy was performed in four patients. Only 53% of MSO patients were consulted by an endocrinologist. With a median follow-up period of 33 months (range, 4 to 156), 11 patients remained disease-free, one experienced progression with peritoneal seeding, and the remaining one was in treatment. There have been no recurrences or deaths due to MSO. Conclusion An endocrinologist should be involved in establishing a therapeutic plan for MSO, for which the overall prognosis is generally favorable.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background/Aims: Acid-suppressive drugs, such as proton pump inhibitors (PPIs), are treatment options for functional dyspepsia (FD). However, the efficacy of potassium-competitive acid blockers (P-CABs) in treating FD has not yet been established. This prospective multicenter clinical trial-based study aimed to assess the efficacy and safety of tegoprazan as a P-CAB treatment in patients with FD. Methods: FD was diagnosed using the Rome IV criteria. All patients received tegoprazan 50 mg once daily for 8 weeks. Dyspeptic symptoms were assessed using a dyspepsia symptom questionnaire (5-point Likert scale, Nepean Dyspepsia Index-Korean [NDI-K], and gastroesophageal reflux disease–health-related quality of life [GERD-HRQL]). The main outcome was satisfactory symptom relief rates at 8 weeks. Results: In this study, from the initial screening of 209 patients, 173 were included in the per-protocol set analysis. Satisfactory symptom relief rates at 8 and 4 weeks were 86.7% and 74.6%, respectively. In addition, the NDI-K and GERD-HRQL scores significantly improved at 8 and 4 weeks compared with the baseline scores. The efficacy of tegoprazan was not influenced by the FD subtype or Helicobacter pylori status. In patients with overlapping FD and GERD, there was a greater improvement in the NDI-K and GERD-HRQL scores than in patients with FD symptoms only. No serious drug-related adverse events occurred during this study. Conclusion Tegoprazan (50 mg) administered once daily provided satisfactory symptom relief for FD.

Background: The use of immune checkpoint inhibitors (ICIs) in patients with advanced lung cancer is increasing. Despite ongoing studies to predict the efficacy of ICIs, its use in clinical practice remains difficult. Thus, we aimed to discover a predictive marker by analyzing blood cell characteristics and developing a scoring system for patients treated with ICIs. Methods: This was a prospective multicenter study in patients with advanced nonsmall cell lung cancer (NSCLC) who received ICIs as second-line treatment from June 2021 to November 2022. Blood cell parameters in routine blood samples were evaluated using an automated hematology analyzer. Immune checkpoint inhibitor score (IChIS) was calculated as the sum of neutrophil count score and immature granulocyte score. Results: A total of 143 patients from four institutions were included. The treatment response was as follows: partial response, 8.4%; stable disease, 37.1%; and progressive disease, 44.8%. Median progression-free survival and overall survival after ICI treatment was 3.0 and 8.3 months, respectively. Median progression-free survival in patients with an IChIS of 0 was 4.0 months, which was significantly longer than 1.9 months in patients with an IChIS of 1 and 1.0 month in those with an IChIS of 2 (p=0.001). The median overall survival in patients with an IChIS of 0 was 10.2 months, which was significantly longer than 6.8 and 1.8 months in patients with an IChIS of 1 and 2, respectively (p<0.001). Conclusion Baseline IChIS could be a potential biomarker for predicting survival benefit of immunotherapy in NSCLC.