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Impaired insulin secretory capacity is associated with high glycemic variability in patients with type 2 diabetes (T2DM). However, there are no existing reports on the association between insulin secretory capacity and time in range (TIR). This retrospective study involved 330 T2DM admitted for diabetes education who underwent intermittently scanned continuous glucose monitoring (isCGM) and had their fasting serum C-peptide immunoreactivity (S-CPR) measured within 5 days of admission. The baseline characteristics were as follows: age, 60.2 years; glycated hemoglobin (HbA1c), 9.2%; S-CPR, 2.2 ng/mL; S-CPR index (S-CPR [ng/mL]/fasting plasma glucose [mg/dL] × 100), 1.6; and TIR, 60.3%. TIR correlated significantly with the S-CPR index, which was confirmed by multivariate analysis that included various factors such as HbA1c. Receiver operating characteristic (ROC) analysis showed that 1.88 was the optimal S-CPR index level to predict TIR ≥ 70%. In addition to HbA1c and biguanide use, the S-CPR index was a significant factor associated with TIR > 70%. S-CPR index values of ≥ 1.88 also correlated significantly with TIR > 70%. In conclusion, insulin secretory capacity is associated with TIR in Japanese T2DM, suggesting that the S-CPR index might be a potentially useful biomarker insulin secretory capacity, in association with TIR. Trial registration UMIN0000254333.

Viscoelastic coagulation tests have been increasingly used for hemostasis management in cardiac surgery. The ClotPro system is a novel viscoelastic device based on principles of rotational thromboelastometry. We aimed to compare ClotPro with ROTEM and plasma coagulation assays in cardiopulmonary bypass (CPB) patients. Blood samples were collected from 25 CPB patients at (1) baseline, (2) start of CPB, (3) end of CPB, and (4) end of surgery. The EX-test, IN-test, HI-test, FIB-test parameters on ClotPro were compared with corresponding ROTEM assay (EXTEM, INTEM, HEPTEM, and FIBTEM). Standard plasma coagulation assays and endogenous thrombin generation (TG) were simultaneously evaluated. Pearson correlation analyses showed moderate correlations between clotting times (CTs) (r = 0.63–0.67; p < 0.001, respectively), and strong correlations with maximal clot firmness (MCF) (r = 0.93–0.98; p < 0.001, respectively) between ClotPro and ROTEM. EX-test and IN-test MCF parameters were interchangeable with acceptable percentage errors (EX-test MCF: 7.3%, IN-test MCF: 8.3%), but FIB-test MCF (27.0%) and CT results were not (EX-test CT: 44.7%, IN-test CT: 31.4%). The correlations of PT/INR or peak TG with EX-test CTs were higher than with EXTEM CTs (PT/INR: r = 0.80 and 0.41, peak TG: 0.43 and 0.18, respectively). FIB-test MCF has strong correlation with plasma fibrinogen and factor XIII level (r = 0.84 and 0.66, respectively). ROC analyses showed that ClotPro was capable of emulating well-established ROTEM thresholds (area under curves: 0.83–1.00). ClotPro demonstrated strong correlations in MCF parameters of ROTEM in CPB patients. It may be reasonable to modify ROTEM-based transfusion algorithm pertaining to MCF parameters to establish cut-off values for ClotPro device.

The red blood cell distribution width–albumin ratio (RAR) is a prognostic factor for adverse outcomes in various populations. However, whether RAR is associated with renal outcomes remains unclear. Therefore, we aimed to investigate the impact of RAR on the prognosis in patients with chronic kidney disease (CKD). We conducted a retrospective cohort study using 997 CKD patients who were enrolled in the Fukushima Cohort Study. Patients were categorized into tertiles (T1-3) according to the baseline RAR. The associations of RAR with end-stage kidney disease (ESKD) were assessed using Kaplan–Meier curves and multivariable cox regression analyses. Receiver operating characteristic (ROC) curves were performed to test whether significant differences were present between red cell distribution width (RDW) and RAR. The median age was 66, 57% were men, the median eGFR was 47.8 ml/min/1.73 m 2 , and the median value of RAR was 3.5. The higher RAR group showed an increased risk for ESKD in the Kaplan–Meier curve analysis. Compared to the lowest RAR group, higher RAR groups had a higher risk of ESKD (hazard ratio [HR] 1.37, 95% CI 0.68–2.78 and 2.92, 95% CI 1.44–5.94) for T2 and T3 groups, respectively. ROC curve analysis proved that the discriminating ability of RAR for ESKD was superior to RDW. A higher RAR value was associated with worse renal outcomes in patients with CKD. RAR could be a convenient and useful prognostic marker for renal prognosis.

Evaluating liver steatosis and fibrosis is important for patients with non-alcoholic fatty liver disease. Although liver biopsy and pathological assessment is the gold standard for these conditions, this technique has several disadvantages. The evaluation of steatosis and fibrosis using ultrasound B-mode imaging is qualitative and subjective. The liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) determined using FibroScan are the evidence-based non-invasive measures of liver fibrosis and steatosis, respectively. The LSM and CAP measurements are carried out simultaneously, and the median values of more than ten valid measurements are used to quantify liver fibrosis and steatosis. Here, we demonstrate that the reliability of the LSM depends on the interquartile range to median ratio (IQR/Med), but CAP values do not depend on IQR/Med. In addition, the LSM is affected by inflammation, congestion, and cholestasis in addition to fibrosis, while CAP values are affected by the body mass index in addition to steatosis. We also show that the M probe provides higher LSM values but lower CAP values than the XL probe in the same population. However, there was no statistically significant difference between the diagnostic accuracies of the two probes. These findings are important to understand the reliability of FibroScan measurements and the factors influencing measurement values for all patients.

BackgroundLiver cirrhosis induces marked metabolic disorders, protein-energy malnutrition, and sarcopenia. The objective of the study reported here was to investigate the effects of dietary branched-chain amino acids (BCAAs) on systemic glucose metabolism, skeletal muscle, and prognosis of patients with liver cirrhosis.MethodsJapanese patients with liver cirrhosis (n = 21) were enrolled into a longitudinal study in which their diets were supplemented with BCAAs. We evaluated glucose metabolism and analyzed the skeletal muscle area index (SAI) and intramuscular adipose tissue content (IMAC) using computed tomography.ResultsAfter 48 weeks of supplementation with BCAAs, there were no changes in glucose metabolism and skeletal muscle findings. In patients with ameliorated hypoalbuminemia, IMAC was significantly decreased and SAI was preserved concomitant with decreasing 90- and 120-min post-challenge plasma glucose levels (P < 0.01 each). In patients without increased albumin levels, IMAC was significantly increased and the SAI was significantly decreased (P < 0.01 each). Liver-related event-free survival rates for 72 months were 63.6% in patients with decreased IMAC and 20.0% in patients with increased IMAC.ConclusionsAmelioration of hypoalbuminemia associated with BCAA supplementation correlated with decreased fat accumulation in skeletal muscle, maintenance of skeletal muscle mass, and improved glucose sensitivity, all factors which may contribute to improving the survival of patients with liver cirrhosis.

Ensemble learning helps improve machine learning results by combining several models and allows the production of better predictive performance compared to a single model. It also benefits and accelerates the researches in quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR). With the growing number of ensemble learning models such as random forest, the effectiveness of QSAR/QSPR will be limited by the machine’s inability to interpret the predictions to researchers. In fact, many implementations of ensemble learning models are able to quantify the overall magnitude of each feature. For example, feature importance allows us to assess the relative importance of features and to interpret the predictions. However, different ensemble learning methods or implementations may lead to different feature selections for interpretation. In this paper, we compared the predictability and interpretability of four typical well-established ensemble learning models (Random forest, extreme randomized trees, adaptive boosting and gradient boosting) for regression and binary classification modeling tasks. Then, the blending methods were built by summarizing four different ensemble learning methods. The blending method led to better performance and a unification interpretation by summarizing individual predictions from different learning models. The important features of two case studies which gave us some valuable information to compound properties were discussed in detail in this report. QSPR modeling with interpretable machine learning techniques can move the chemical design forward to work more efficiently, confirm hypothesis and establish knowledge for better results.

Real-world data comparing the effectiveness of various glucagon-like peptide 1 receptor agonists (GLP-1 RAs) in type 2 diabetes mellitus (T2DM) are limited. We investigated the clinical effectiveness of liraglutide and dulaglutide in Japanese T2DM in a real-world setting. This retrospective study included 179 patients with T2DM who were treated with GLP-1 RA for at least 12 months (liraglutide, n = 97; dulaglutide, n = 82). We used stabilized propensity score-based inverse probability of treatment weighting (IPTW) to reduce selection bias and confounding by observed covariates. Changes in glycated hemoglobin (HbA1c) at the end of the 12-month treatment were evaluated. After adjustment by stabilized propensity score-based IPTW, no significant differences were observed in patient characteristics between the liraglutide and dulaglutide groups. HbA1c was significantly lower at 12 months in both groups (liraglutide, 8.9 to 7.4%; dulaglutide, 8.7 to 7.5%). Multivariate linear regression analysis showed no differences in the extent of changes in HbA1c at 12 months between the two agents. High baseline HbA1c, the addition of GLP-1 RA treatment modality, and in-hospital initiation of GLP-1 RA treatment were identified as significant contributing factors to HbA1c reduction. The effects of liraglutide and dulaglutide on lowering HbA1c levels at 12 months were comparable in a real-world setting.

This prospective study determined the effects of hypoglycemic stimulation on vascular endothelial function in non-diabetic patients using reactive hyperemia peripheral arterial tonometry (RH-PAT). The study included non-diabetic patients who were hospitalized for an insulin tolerance test (ITT) for the diagnosis of hypoadrenocorticism or hypopituitarism. Vascular endothelial function was assessed using the reactive hyperemia index (RHI) measured by the RH-PAT. We also measured the levels of anterior pituitary hormone, adrenaline, noradrenaline, and dopamine at the time of hypoglycemia. The primary endpoint was a change in the RHI at 120 min after insulin administration. The study included 27 patients. ITT was associated with significant increases in systolic blood pressure, pulse rate, and the blood levels of adrenocorticotropic hormone, cortisol, growth hormone, adrenaline, noradrenaline, and dopamine. RHI significantly decreased after ITT from 2.24 ± 0.51 to 1.71 ± 0.42. A significant inverse correlation was observed between the change in RHI and change in adrenaline (r = − 0.670, p = 0.012). We concluded that hypoglycemic stimulation altered vascular endothelial function, as measured by RH-PAT, even in patients free of glucose intolerance. The observed deterioration in vascular endothelial function correlated with increases in catecholamine levels during hypoglycemia. Trial registration: UMIN000033244.

To elucidate the mechanisms of rapid progression of serous ovarian cancer, gene expression profiles from 43 ovarian cancer tissues comprising eight early stage and 35 advanced stage tissues were carried out using oligonucleotide microarrays of 18 716 genes. By non‐negative matrix factorization analysis using 178 genes, which were extracted as stage‐specific genes, 35 advanced stage cases were classified into two subclasses with superior (n = 17) and poor (n = 18) outcome evaluated by progression‐free survival (log rank test, P = 0.03). Of the 178 stage‐specific genes, 112 genes were identified as showing different expression between the two subclasses. Of the 48 genes selected for biological function by gene ontology analysis or Ingenuity Pathway Analysis, five genes (ZEB2, CDH1, LTBP2, COL16A1, and ACTA2) were extracted as candidates for prognostic factors associated with progression‐free survival. The relationship between high ZEB2 or low CDH1 expression and shorter progression‐free survival was validated by real‐time RT‐PCR experiments of 37 independent advanced stage cancer samples. ZEB2 expression was negatively correlated with CDH1 expression in advanced stage samples, whereas ZEB2 knockdown in ovarian adenocarcinoma SKOV3 cells resulted in an increase in CDH1 expression. Multivariate analysis showed that high ZEB2 expression was independently associated with poor prognosis. Furthermore, the prognostic effect of E‐cadherin encoded by CDH1 was verified using immunohistochemical analysis of an independent advanced stage cancer samples set (n = 74). These findings suggest that the expression of epithelial–mesenchymal transition‐related genes such as ZEB2 and CDH1 may play important roles in the invasion process of advanced stage serous ovarian cancer. (Cancer Sci 2009)

Periodontal disease is an inflammatory disease caused by pathogenic oral microorganisms that leads to the destruction of alveolar bone and connective tissues around the teeth. Although many studies have shown that periodontal disease is a risk factor for systemic diseases, such as type 2 diabetes and cardiovascular diseases, the relationship between nonalcoholic fatty liver disease (NAFLD) and periodontal disease has not yet been clarified. Thus, the purpose of this review was to reveal the relationship between NAFLD and periodontal disease based on epidemiological studies, basic research, and immunology. Many cross-sectional and prospective epidemiological studies have indicated that periodontal disease is a risk factor for NAFLD. An in vivo animal model revealed that infection with periodontopathic bacteria accelerates the progression of NAFLD accompanied by enhanced steatosis. Moreover, the detection of periodontopathic bacteria in the liver may demonstrate that the bacteria have a direct impact on NAFLD. Furthermore, Porphyromonas gingivalis lipopolysaccharide induces inflammation and accumulation of intracellular lipids in hepatocytes. Th17 may be a key molecule for explaining the relationship between periodontal disease and NAFLD. In this review, we attempted to establish that oral health is essential for systemic health, especially in patients with NAFLD.