Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Background/Aims: Adiponectin, a hormone primarily produced by adipocytes, typically shows an inverse relationship with body mass index (BMI). However, some studies have reported a positive correlation between the two. Thus, this study aimed to examine the relationship between adiponectin level and BMI in diabetic patients, focusing on the impact of past obesity on current adiponectin levels. Methods: We conducted an observational study analyzing data from 323 diabetic patients at Kyungpook National University Hospital. Based on past and current BMIs, participants were categorized into never-obese (nn, n = 106), previously obese (on, n = 43), and persistently obese (oo, n = 73) groups based on a BMI threshold of 25 kg/m2. Adiponectin level and BMI were key variables. Kaplan–Meier analysis assessed their impact on all-cause mortality up to August 2023, with survival differences based on adiponectin quartiles and follow-up starting from patient enrollment (2010–2015). Results: The analysis revealed a significant inverse correlation between adiponectin level and past maximum BMI. The on group exhibited approximately 10% lower adiponectin levels compared to the nn group. This association remained significant after adjusting for current BMI, age, and sex, highlighting the lasting influence of previous obesity on adiponectin levels. Furthermore, survival analysis indicated that patients in the lowest adiponectin quartile had reduced survival, with a statistically significant trend (p = 0.062). Conclusions Findings of this study suggest that lower adiponectin levels, potentially reflecting past obesity, are associated with decreased survival in diabetic patients, underscoring a critical role of adiponectin in long-term health outcomes.

Evaluating cell metabolism is crucial during pluripotent stem cell (PSC) differentiation and somatic cell reprogramming as it affects cell fate. As cultured stem cells are heterogeneous, a comparative analysis of relative metabolism using existing metabolic analysis methods is difficult, resulting in inaccuracies. In this study, we measured human PSC basal metabolic levels using a Seahorse analyzer. We used fibroblasts, human induced PSCs, and human embryonic stem cells to monitor changes in basal metabolic levels according to cell number and determine the number of cells suitable for analysis. We evaluated normalization methods using glucose and selected the most suitable for the metabolic analysis of heterogeneous PSCs during the reprogramming stage. The response of fibroblasts to glucose increased with starvation time, with oxygen consumption rate and extracellular acidification rate responding most effectively to glucose 4 hours after starvation and declining after 5 hours of starvation. Fibroblasts and PSCs achieved appropriate responses to glucose without damaging their metabolism 2∼4 and 2∼3 hours after starvation, respectively. We developed a novel method for comparing basal metabolic rates of fibroblasts and PSCs, focusing on quantitative analysis of glycolysis and oxidative phosphorylation using glucose without enzyme inhibitors. This protocol enables efficient comparison of energy metabolism among cell types, including undifferentiated PSCs, differentiated cells, and cells undergoing cellular reprogramming, and addresses critical issues, such as differences in basal metabolic levels and sensitivity to normalization, providing valuable insights into cellular energetics.

Purpose: In the present study, we determined the prevalence of obstructive meibomian gland dysfunction (MGD), hyposecretory MGD, grossly normal MG, and hypersecretory MGD in patients with dry eye syndrome using lipid layer thickness (LLT) and MG dropout. Methods: Eighty-eight patients with dry eye syndrome were included in the study. Patients were categorized into four groups according to the LLT and weighted total meiboscore. The proportion of patients in each group was calculated. The age, sex, Ocular Surface Disease Index, LLT, Schirmer, tear film breakup time, cornea stain, weighted total meiboscore, expressibility, and quality of meibum were compared between the four groups. Results: Fifteen eyes (17.0%) had obstructive MGD, two eyes (2.3%) had hyposecretory MGD, 40 eyes (45.5%) had grossly normal MG, and 17 eyes (19.3%) had hypersecretory MGD. The obstructive MGD group was younger than the grossly normal MG group. In obstructive MGD, the ratio of men to women was higher than that of the other groups. However, Ocular Surface Disease Index, Schirmer, tear film breakup time, and corneal stain did not show statistically significant differences between the four groups. The meibum expressibility of the hyposecretoy MGD group was worse than those of the other groups. The meibum expressibility of the hyposecretoy MGD group was poor than those of the obstructive and hypersecretory MGD group. Conclusions This categorization was expected to help determine the best treatment method for dry eye syndrome, according to the MG status.

Several cases of cardiac arrhythmia after coronavirus disease 2019 (COVID-19) vaccination have been reported in adults. However, the Centers for Disease Control and Prevention do not list cardiac arrhythmias as a possible side effect of the COVID-19 vaccines. A previously healthy 18-year-old man presented at the Soonchunhyang University Bucheon Hospital with complaints of palpitations, acute chest tightness, and dyspnea. Two days before presentation, he had received the COVID-19 vaccine, BNT162b2 (Comirnaty, Pfizer-BioNTech; Pfizer, New York, NY, USA). His vital signs were stable; however, physical examination revealed irregular heartbeats without a cardiac murmur. A 12-lead electrocardiography showed atrial fibrillation. The patient received several medications for 6 months, without improvement. Eventually normal sinus rhythm was restored with cardioversion. The patient has remained asymptomatic for 1 year. We report the case of an adolescent with atrial fibrillation after receiving a messenger RNA COVID-19 vaccine. Atrial fibrillation should be considered a cardiovascular side effect of the COVID-19 vaccine in adolescents.

Purpose: This retrospective study aimed to clarify the relation between nutritional index and length of hospital stay in elderly patients undergoing pancreatic cancer surgery, and to identify factors affecting the length of hospital stay. Methods: Total 102 patients aged over 65 years who underwent pancreaticoduodenectomy were retrospectively enrolled from January 1, 2010 to September 30, 2020. All patients were subjected to nutritional screening using Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI). Results: The GNRI average was 95. 66±6.95, with 67.6% of patients having a low GNRI score (malnutrition group). The average regarding PNI was 45.46±5.65, with 54.9% of patients having a low PNI (malnutrition group). The average total length of hospital stay was 23.12±10.69 days. Total length of hospital stay according to the nutritional indexes of the subjects was longer in the low GNRI (t=-2.09, p=.039) and low PNI (t=-2.29, p=.024) groups. Conclusion Poorer preoperative nutritional status increased total length of hospital stay in elderly patients with pancreatic cancer. Assessment of nutritional status of patients using GNRI and PNI is a good strategy for evaluating elderly patients at high risk of having to stay in hospital for more extended periods of time.