The impact of testosterone, tibolone and black cohosh on purified mammary and placental 17β-hydroxysteroid dehydrogenase type 1

Abstract Context: Mammary and placental 17β-hydroxysteroid dehydrogenase type 1 (17βHSD1). Objective: To assess the impact of testosterone, tibolone, and black cohosh on purified mammary and placental 17βHSD1. Materials and methods: 17βHSD1 was purified from human mammary gland and placenta by column chromatography, its activity was monitored by a radioactive activity assay, and the degree of purification was determined by gel electrophoresis. Photometric cofactor transformation analysis was performed to assess 17βHSD1 activity without or in presence of testosterone, tibolone and black cohosh. Results: 17βHSD1 from both sources displayed a comparable basal activity. Testosterone and tibolone metabolites inhibited purified mammary and placental 17βHSD1 activity to a different extent, whereas black cohosh had no impact. Discussion: Studies on purified enzymes reveal the individual action of drugs on local regulatory mechanisms thus helping to develop more targeted therapeutic intervention. Conclusion: Testosterone, tibolone and black cohosh display a beneficial effect on local mammary estrogen metabolism by not affecting or decreasing local estradiol exposure.

Hepatic and intramyocellular glycogen stores in adults with type 1 diabetes and healthy controls.

Glycogen levels in liver and skeletal muscle assessed non-invasively using magnetic resonance spectroscopy after a 48-h pre-study period including a standardized diet and withdrawal from exercise did not differ between individuals with well-controlled Type 1 DM and matched healthy controls.

Exercise-associated glucose metabolism in individuals with type 1 diabetes mellitus.

PURPOSE OF REVIEW The primary focus of this review is threefold: first, to summarize available knowledge on exercise-associated glucose metabolism in individuals with type 1 diabetes mellitus (T1DM); second, to elucidate physiological mechanisms predisposing to glycemic variations in patients in T1DM; and third, to describe novel approaches derived from physiological perceptions applicable to stabilize exercise-related glycemia in individuals with T1DM. RECENT FINDINGS Recent studies corroborate the concept that despite partial differences in counter-regulatory mechanisms individuals with T1DM do not fundamentally differ in their glucose response to exercise when compared with healthy individuals if studies are performed under standardized conditions with insulin and glucose levels held close to physiological ranges. Novel approaches derived from a better understanding of exercise-associated glucose metabolism (e.g., the concept of intermittent high-intensity exercise) may provide alternative ways to master the challenges imposed by exercise to individuals with T1DM. SUMMARY Exercise still imposes high demands on patients with T1DM and increases risks for hypoglycemia and hyperglycemia. Deeper insight into the associated metabolic pathways has revealed novel options to stabilize exercise-associated glucose levels in these patients.

Metabolic and hormonal response to intermittent high-intensity and continuous moderate intensity exercise in individuals with type 1 diabetes: a randomised crossover study.

AIMS/HYPOTHESIS To investigate exercise-related fuel metabolism in intermittent high-intensity (IHE) and continuous moderate intensity (CONT) exercise in individuals with type 1 diabetes mellitus. METHODS In a prospective randomised open-label cross-over trial twelve male individuals with well-controlled type 1 diabetes underwent a 90 min iso-energetic cycling session at 50% maximal oxygen consumption ([Formula: see text]), with (IHE) or without (CONT) interspersed 10 s sprints every 10 min without insulin adaptation. Euglycaemia was maintained using oral (13)C-labelled glucose. (13)C Magnetic resonance spectroscopy (MRS) served to quantify hepatocellular and intramyocellular glycogen. Measurements of glucose kinetics (stable isotopes), hormones and metabolites complemented the investigation. RESULTS Glucose and insulin levels were comparable between interventions. Exogenous glucose requirements during the last 30 min of exercise were significantly lower in IHE (p = 0.02). Hepatic glucose output did not differ significantly between interventions, but glucose disposal was significantly lower in IHE (p < 0.05). There was no significant difference in glycogen consumption. Growth hormone, catecholamine and lactate levels were significantly higher in IHE (p < 0.05). CONCLUSIONS/INTERPRETATION IHE in individuals with type 1 diabetes without insulin adaptation reduced exogenous glucose requirements compared with CONT. The difference was not related to increased hepatic glucose output, nor to enhanced muscle glycogen utilisation, but to decreased glucose uptake. The lower glucose disposal in IHE implies a shift towards consumption of alternative substrates. These findings indicate a high flexibility of exercise-related fuel metabolism in type 1 diabetes, and point towards a novel and potentially beneficial role of IHE in these individuals. TRIAL REGISTRATION ClinicalTrials.gov NCT02068638 FUNDING: Swiss National Science Foundation (grant number 320030_149321/) and R&A Scherbarth Foundation (Switzerland).

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Methodological and physiological test-retest reliability of (13) C-MRS glycogen measurements in liver and in skeletal muscle of patients with type 1 diabetes and matched healthy controls.

Glycogen is a major substrate in energy metabolism and particularly important to prevent hypoglycemia in pathologies of glucose homeostasis such as type 1 diabetes mellitus (T1DM). (13) C-MRS is increasingly used to determine glycogen in skeletal muscle and liver non-invasively; however, the low signal-to-noise ratio leads to long acquisition times, particularly when glycogen levels are determined before and after interventions. In order to ease the requirements for the subjects and to avoid systematic effects of the lengthy examination, we evaluated if a standardized preparation period would allow us to shift the baseline (pre-intervention) experiments to a preceding day. Based on natural abundance (13) C-MRS on a clinical 3 T MR system the present study investigated the test-retest reliability of glycogen measurements in patients with T1DM and matched controls (n = 10 each group) in quadriceps muscle and liver. Prior to the MR examination, participants followed a standardized diet and avoided strenuous exercise for two days. The average coefficient of variation (CV) of myocellular glycogen levels was 9.7% in patients with T1DM compared with 6.6% in controls after a 2 week period, while hepatic glycogen variability was 13.3% in patients with T1DM and 14.6% in controls. For comparison, a single-session test-retest variability in four healthy volunteers resulted in 9.5% for skeletal muscle and 14.3% for liver. Glycogen levels in muscle and liver were not statistically different between test and retest, except for hepatic glycogen, which decreased in T1DM patients in the retest examination, but without an increase of the group distribution. Since the CVs of glycogen levels determined in a "single session" versus "within weeks" are comparable, we conclude that the major source of uncertainty is the methodological error and that physiological variations can be minimized by a pre-study standardization. For hepatic glycogen examinations, familiarization sessions (MR and potentially strenuous interventions) are recommended. Copyright © 2016 John Wiley & Sons, Ltd.

Age Related Differences in Individual Quality of Life Domains in Youth with Type 1 Diabetes.

BACKGROUND: Investigating individual, as opposed to predetermined, quality of life domains may yield important information about quality of life. This study investigated the individual quality of life domains nominated by youth with type 1 diabetes. METHODS: Eighty young people attending a diabetes summer camp completed the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting interview, which allows respondents to nominate and evaluate their own quality of life domains. RESULTS: The most frequently nominated life domains were 'family', 'friends', 'diabetes', 'school', and 'health' respectively; ranked in terms of importance, domains were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'; ranked in order of satisfaction, domains were 'camp', 'religion', 'pets', and 'family' and 'a special person' were tied for fifth. Respondent age was significantly positively associated with the importance of 'friends', and a significantly negatively associated with the importance of 'family'. Nearly all respondents nominated a quality of life domain relating to physical status, however, the specific physical status domain and the rationale for its nomination varied. Some respondents nominated 'diabetes' as a domain and emphasized diabetes 'self-care behaviors' in order to avoid negative health consequences such as hospitalization. Other respondents nominated 'health' and focused more generally on 'living well with diabetes'. In an ANOVA with physical status domain as the independent variable and age as the dependent variable, participants who nominated 'diabetes' were younger (M = 12.9 years) than those who nominated 'health' (M = 15.9 years). In a second ANOVA, with rationale for nomination the physical status domain as the independent variable, and age as the dependent variable, those who emphasized 'self care behaviors' were younger (M = 11.8 years) than those who emphasized 'living well with diabetes' (M = 14.6 years). These differences are discussed in terms of cognitive development and in relation to the decline in self-care and glycemic control often observed during adolescence. CONCLUSIONS: Respondents nominated many non-diabetes life domains, underscoring that QOL is multidimensional. Subtle changes in conceptualization of diabetes and health with increasing age may reflect cognitive development or disease adjustment, and speak to the need for special attention to adolescents. Understanding individual quality of life domains can help clinicians motivate their young patients with diabetes for self-care. Future research should employ a larger, more diverse sample, and use longitudinal designs.

The impact of nutrition intervention on glycemic control in a pediatric type 1 diabetes mellitus population

Aim: The goal of this study was to evaluate the change in hemoglobin A1C and glycemic control after nutrition intervention among a population of type 1 diabetic pediatric patients. Methods: Data was collected from all type 1 diabetic patients who were scheduled for a consultation with the diabetes/endocrine RD from January 2006 through December 2006. Two groups were compared, those who kept their RD appointment and those who did not keep their appointment. The main outcome measure was HgbA1C. An independent samples t-test compared the two groups with respect to change in HbgA1C before and after the most recent scheduled appointment with the RD. Baseline characteristics were used as covariates and analyzed and controlled for using analysis of covariance (ANCOVA). Results: There was no difference in HgbA1c after either attending an RD appointment or not having attended an RD appointment. Those who arrived for and attended their RD appointment and those who did not arrive for and attend their RD appointment, had statistically different HgbA1C's before their scheduled appointment as well as after the RD appointment. However, the two groups were not equal at the beginning of the study period. Discussion: A study design with inclusion criteria of a specified range of HgbA1C values within which the study subjects needed to fall, would have potentially eliminated the difference between the two groups at the beginning of the study period. Conducting either another retrospective study that controlled for the initial HgbA1C value or conducting a prospective study that designated a range of HgbA1C values would be worth investigating to evaluate the impact of medical nutrition therapy intervention and the role of the RD in diabetes management. It is an interesting finding that there was a significant difference in the initial HgbA1c for those who came to the RD appointment compared to those who did not come. The fact that in this study those who did not arrive for their RD appointment had worse control of their diabetes suggests that this is a high-risk group. Targeting diabetes education toward this group of patients may prove to be beneficial. ^

Diabetic nephropathy in African-Americans with type 1 diabetes: The new Jersey 725 study

Diabetic nephropathy is the most common cause of end-stage renal disease (ESRD) in the United States. African-Americans and patients with type 1 diabetes (T1D) are at increased risk. We studied the rate and factors that influenced progression of glomerular filtration rate (GFR) in 401 African-American T1D patients who were followed for 6 years through the observational cohort New Jersey 725 study. Patients with ESRD and/or GFR<20 ml/min were excluded. The mean (SD) baseline GFR was 106.8 (27.04) ml/min and it decreased by 13.8 (mean, SD 32.2) ml/min during the 6-year period (2.3 ml/min/year). In patients with baseline macroproteinuria, GFR decreased by 31.8 (39.0) ml/min (5.3 ml/min/year) compared to 8.2 (mean, SD 27.6) ml/min (1.3 ml/min/year) in patients without it (p<0.00001). Six-year GFR fell to <20 ml/min in 5.25% of all patients, but in 16.8% of macroproteinuric patients.^ A model including baseline GFR, proteinuria category and hypertension category, explained 35% of the 6-year GFR variability (p<0.0001). After adjustment for other variables in the model, 6-year GFR was 24.9 ml/min lower in macroproteinuric patients than in those without proteinuria (p=0.0001), and 12.6 ml/min lower in patients with treated but uncontrolled hypertension compared to normotensive patients (p=0.003). In this sample of patients, with an elevated mean glycosylated hemoglobin of 12.4%, glycemic control did not independently influence GFR deterioration, nor did BMI, cholesterol, gender, age at diabetes onset or socioeconomic level.^ Taken together, our findings suggest that proteinuria and hypertension are the most important factors associated with GFR deterioration in African-American T1D patients.^

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

Personalized rule-based closed-loop control algorithm for type 1 diabetes

Type 1 diabetes-mellitus implies a life-threatening absolute insulin deficiency. Artificial pancreas (CGM sensor, insulin pump and control algorithm) is promising to outperform current open-loop therapies.