Effects of Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032 on Overweight and the Gut Microbiota in Humans: Randomized,Double-Blinded,Placebo-Controlled Clinical Trial

Obesity and overweight are closely related to diet, and the gut microbiota play an important role in body weight and human health. The aim of this study was to explore how Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032 supplementation alleviate obesity by modulating the human gut microbiome. A randomized, double-blind, placebo-controlled study was conducted on 72 individuals with overweight. Over a 12-week period, probiotic groups consumed 1 × 10¹⁰ colony-forming units of HY7601 and KY1032, whereas the placebo group consumed the same product without probiotics. After treatment, the probiotic group displayed a reduction in body weight (p < 0.001), visceral fat mass (p < 0.025), and waist circumference (p < 0.007), and an increase in adiponectin (p < 0.046), compared with the placebo group. Additionally, HY7601 and KY1032 supplementation modulated bacterial gut microbiota characteristics and beta diversity by increasing Bifidobacteriaceae and Akkermansiaceae and decreasing Prevotellaceae and Selenomonadaceae. In summary, HY7601 and KY1032 probiotics exert anti-obesity effects by regulating the gut microbiota; hence, they have therapeutic potential for preventing or alleviating obesity and living with overweight.     

Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants

PurposeThe aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants.Materials and MethodsOf 10425 VLBW infants registered in the Korean Neonatal Network between 2013 and 2017, 7954 infants were included. PGF was defined as a decrease in Z score >1.28 at discharge, compared to that at birth. Six metrics [area under the receiver operating characteristic curve (AUROC), accuracy, precision, sensitivity, specificity, and F1 score] were obtained at five time points (at birth, 7 days, 14 days, 28 days after birth, and at discharge). Machine learning models were built using four different techniques [extreme gradient boosting (XGB), random forest, support vector machine, and convolutional neural network] to compare against the conventional multiple logistic regression (MLR) model.ResultsThe XGB algorithm showed the best performance with all six metrics across the board. When compared with MLR, XGB showed a significantly higher AUROC (p=0.03) for Day 7, which was the primary performance metric. Using optimal cut-off points, for Day 7, XGB still showed better performances in terms of AUROC (0.74), accuracy (0.68), and F1 score (0.67). AUROC values seemed to increase slightly from birth to 7 days after birth with significance, almost reaching a plateau after 7 days after birth.ConclusionWe have shown the possibility of predicting PGF through machine learning algorithms, especially XGB. Such models may help neonatologists in the early diagnosis of high-risk infants for PGF for early intervention.     

Machine Learning Model for Classifying the Results of Fetal Cardiotocography Conducted in High-Risk Pregnancies

PurposeFetal well-being is usually assessed via fetal heart rate (FHR) monitoring during the antepartum period. However, the interpretation of FHR is a complex and subjective process with low reliability. This study developed a machine learning model that can classify fetal cardiotocography results as normal or abnormal.Materials and MethodsIn total, 17492 fetal cardiotocography results were obtained from Ajou University Hospital and 100 fetal cardiotocography results from Czech Technical University and University Hospital in Brno. Board-certified physicians then reviewed the fetal cardiotocography results and labeled 1456 of them as gold-standard; these results were used to train and validate the model. The remaining results were used to validate the clinical effectiveness of the model with the actual outcome.ResultsIn a test dataset, our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 and area under the precision-recall curve (AUPRC) of 0.73 in an internal validation dataset. An average AUROC of 0.73 and average AUPRC of 0.40 were achieved in the external validation dataset. Fetus abnormality score, as calculated from the continuous fetal cardiotocography results, was significantly associated with actual clinical outcomes [intrauterine growth restriction: odds ratio, 3.626 (p=0.031); Apgar score 1 min: odds ratio, 9.523 (p<0.001), Apgar score 5 min: odds ratio, 11.49 (p=0.001), and fetal distress: odds ratio, 23.09 (p<0.001)].ConclusionThe machine learning model developed in this study showed precision in classifying FHR signals. This suggests that the model can be applied to medical devices as a screening tool for monitoring fetal status.     

Effects of Asthma Medication Type on Asthma Exacerbation in a Real-World Setting

PurposeCurrently, there are multiple options for the pharmacological treatment of asthma. This study aimed to compare the effects of different asthma medications on exacerbation in a real-world setting.Materials and MethodsWe retrospectively reviewed electronic medical records of asthma patients who visited the hospital from November 1, 2016 to October 31, 2019. The number of asthma exacerbations requiring administration of systemic steroids was the primary outcome. A time-varying Cox regression analysis was used to reflect the real-world setting: variable usage times, discontinuation, and switching of medication.ResultsAmong 937 patients with asthma, 228 (24.3%) experienced asthma exacerbation during the study period. Asthma exacerbation was observed in patients using short-acting β₂-agonists (SABA) alone (50.4% vs. 28.6%, p<0.001) as well as in patients not using inhaled corticosteroids (ICS) (58.8% vs. 40.3%, p<0.001), long-acting β₂-agonists (LABA) (54.8% vs. 36.1%, p<0.001), and leukotriene receptor antagonists (71.5% vs. 50.8%, p<0.001). A time-varying Cox regression analysis of asthma exacerbations according to the duration of asthma medication showed that SABA alone increased the risk of asthma exacerbation [hazard ratio (HR), 1.834; 95% confidence interval (CI), 1.299–2.588; p=0.001], whereas ICS-LABA decreased the risk (HR, 0.733; 95% CI, 0.538–0.997; p=0.048). However, in the subgroup analysis according to medication type, specific ingredients showed no significant differences.ConclusionIn the real world, asthma medications affect asthma exacerbation variably according to the medication type.     

Advanced parental age is an independent risk factor for term low birth weight and macrosomia

We aimed to investigate association between parental age and the risks of term low birth weight and macrosomia.This was a retrospective cohort study using a national database including 2,245,785 term singleton live births with complete parental age data. Old parental age was defined as 35 years or older. Odd ratios (OR) for term low birth weight and macrosomia were analyzed using univariate and multivariate logistic regression analysis.Neonatal sex, maternal occupation, parity, nationality, age, and paternal age were significant factors of term low birth weight and macrosomia, in univariate analysis. In multivariate analysis, old maternal age (≥35 years old) showed increased odds of term low birth weight and macrosomia (aOR = 1.122, 95% CI: 1.083 –1.162; and aOR = 1.166, 95% CI: 1.143 – 1.189, respectively). Similarly, old paternal age (≥35 years old) showed increased odds of term low birth weight and macrosomia (aOR = 1.090, 95% CI: 1.058 –1.122; and aOR = 1.101, 95% CI: 1.083 – 1.119, respectively). Maternal education that lasted more than 12 years had reduced odds of term low birth weight and macrosomia (OR = 0.817, 95% CI: 0.792 –0.842; and OR = 0.894, 95% CI: 0.879 – 0.91, respectively). Paternal education that lasted more than 12 years also had reduced odds of term low birth weight and macrosomia (OR = 0.865, 95% CI: 0.84 –0.892; and OR = 0.897, 95% CI: 0.881 – 0.913, respectively).This study suggests that not only maternal age but also paternal age are significantly associated with term low birth weight and macrosomia. In addition, parental education levels are also associated with term low birth weight and macrosomia.     

Clinical Characteristics and Risk Factors for Mortality in Critical Coronavirus Disease 2019 Patients 50 Years of Age or Younger During the Delta Wave: Comparison With Patients > 50 Years in Korea

BackgroundNumerous patients around the globe are dying from coronavirus disease 2019 (COVID-19). While age is a known risk factor, risk analysis in the young generation is lacking. The present study aimed to evaluate the clinical features and mortality risk factors in younger patients (≤ 50 years) with a critical case of COVID-19 in comparison with those among older patients (> 50 years) in Korea.MethodsWe analyzed the data of adult patients only in critical condition (requiring high flow nasal cannula oxygen therapy or higher respiratory support) hospitalized with PCR-confirmed COVID-19 at 11 hospitals in Korea from July 1, 2021 to November 30, 2021 when the delta variant was a dominant strain. Patients’ electronic medical records were reviewed to identify clinical characteristics.ResultsDuring the study period, 448 patients were enrolled. One hundred and forty-two were aged 50 years or younger (the younger group), while 306 were above 50 years of age (the older group). The most common pre-existing conditions in the younger group were diabetes mellitus and hypertension, and 69.7% of the patients had a body mass index (BMI) > 25 kg/m². Of 142 younger patients, 31 of 142 patients (21.8%, 19 women) did not have these pre-existing conditions. The overall case fatality rate among severity cases was 21.0%, and it differed according to age: 5.6% (n = 8/142) in the younger group, 28.1% in the older group, and 38% in the ≥ 65 years group. Age (odds ratio [OR], 7.902; 95% confidence interval [CI], 2.754–18.181), mechanical ventilation therapy (OR, 17.233; 95% CI, 8.439–35.192), highest creatinine > 1.5 mg/dL (OR, 17.631; 95% CI, 8.321–37.357), and combined blood stream infection (OR, 7.092; 95% CI, 1.061–18.181) were identified as independent predictors of mortality in total patients. Similar patterns were observed in age-specific analyses, but most results were statistically insignificant in multivariate analysis due to the low number of deaths in the younger group. The full vaccination rate was very low among study population (13.6%), and only three patients were fully vaccinated, with none of the patients who died having been fully vaccinated in the younger group. Seven of eight patients who died had a pre-existing condition or were obese (BMI > 25 kg/m²), and the one remaining patient died from a secondary infection.ConclusionAbout 22% of the patients in the young critical group did not have an underlying disease or obesity, but the rate of obesity (BMI > 25 kg/m²) was high, with a fatality rate of 5.6%. The full vaccination rate was extremely low compared to the general population of the same age group, showing that non-vaccination has a grave impact on the progression of COVID-19 to a critical condition. The findings of this study highlight the need for measures to prevent critical progression of COVID-19, such as vaccinations and targeting young adults especially having risk factors.     

Fimasartan Ameliorates Deteriorations in Glucose Metabolism in a High Glucose State by Regulating Skeletal Muscle and Liver Cells

PurposeSince diabetes and hypertension frequently occur together, it is thought that these conditions may have a common pathogenesis. This study was designed to evaluate the anti-diabetic function of the anti-hypertensive drug fimasartan on C2C12 mouse skeletal muscle and HepG2 human liver cells in a high glucose state.Materials and MethodsThe anti-diabetic effects and mechanism of fimasartan were identified using Western blot, glucose uptake tests, oxygen consumption rate (OCR) analysis, adenosine 5′-triphosphate (ATP) enzyme-linked immunosorbent assay (ELISA), and immunofluorescence staining for diabetic biomarkers in C2C12 cells. Protein biomarkers for glycogenolysis and glycogenesis were evaluated by Western blotting and ELISA in HepG2 cells.ResultsThe protein levels of phosphorylated 5′ adenosine monophosphate-activated protein kinase (p-AMPK), p-AKT, insulin receptor substrate-1 (IRS-1), and glucose transporter type 4 (Glut4) were elevated in C2C12 cells treated with fimasartan. These increases were reversed by peroxisome proliferator-activated receptor delta (PPARδ) antagonist. ATP, OCR, and glucose uptake were increased in cells treated with 200 µM fimasartan. Protein levels of glycogen phosphorylase, glucose synthase, phosphorylated glycogen synthase, and glycogen synthase kinase-3 (GSK-3) were decreased in HepG2 cells treated with fimasartan. However, these effects were reversed following the addition of the PPARδ antagonist GSK0660.ConclusionIn conclusion, fimasartan ameliorates deteriorations in glucose metabolism as a result of a high glucose state by regulating PPARδ in skeletal muscle and liver cells.     

Current Landscape and Future Perspectives of Abbreviated MRI for Hepatocellular Carcinoma Surveillance

While ultrasound (US) is considered an important tool for hepatocellular carcinoma (HCC) surveillance, it has limited sensitivity for detecting early-stage HCC. Abbreviated MRI (AMRI) has recently gained popularity owing to better sensitivity in its detection of early-stage HCC than US, while also minimizing the time and cost in comparison to complete contrast-enhanced MRI, as AMRI includes only a few essential sequences tailored for detecting HCC. Currently, three AMRI protocols exist, namely gadoxetic acid-enhanced hepatobiliary-phase AMRI, dynamic contrast-enhanced AMRI, and non-enhanced AMRI. In this study, we discussed the rationale and technical details of AMRI techniques for achieving optimal surveillance performance. The strengths, weaknesses, and current issues of each AMRI protocol were also elucidated. Moreover, we scrutinized previously performed AMRI studies regarding clinical and technical factors. Reporting and recall strategies were discussed while considering the differences in AMRI protocols. A risk-stratified approach for the target population should be taken to maximize the benefits of AMRI and the cost-effectiveness should be considered. In the era of multiple HCC surveillance tools, patients need to be fully informed about their choices for better adherence to a surveillance program.     

Inhibitory effects of the atypical antipsychotic,clozapine, on voltage-dependent K+ channels in rabbit coronary arterial smooth muscle cells

To investigate the adverse effects of clozapine on cardiovascular ion channels, we examined the inhibitory effect of clozapine on voltage-dependent K⁺ (Kv) channels in rabbit coronary arterial smooth muscle cells. Clozapine-induced inhibition of Kv channels occurred in a concentration-dependent manner with an half-inhibitory concentration value of 7.84 ± 4.86 µM and a Hill coefficient of 0.47 ± 0.06. Clozapine did not shift the steady-state activation or inactivation curves, suggesting that it inhibited Kv channels regardless of gating properties. Application of train pulses (1 and 2 Hz) progressively augmented the clozapine-induced inhibition of Kv channels in the presence of the drug. Furthermore, the recovery time constant from inactivation was increased in the presence of clozapine, suggesting that clozapine-induced inhibition of Kv channels is use (state)-dependent. Pretreatment of a Kv1.5 subtype inhibitor decreased the Kv current amplitudes, but additional application of clozapine did not further inhibit the Kv current. Pretreatment with Kv2.1 or Kv7 subtype inhibitors partially blocked the inhibitory effect of clozapine. Based on these results, we conclude that clozapine inhibits arterial Kv channels in a concentration- and use (state)-dependent manner. Kv1.5 is the major subtype involved in clozapine-induced inhibition of Kv channels, and Kv2.1 and Kv7 subtypes are partially involved.