A Glucose-Only Model to Extract Physiological Information from Postprandial Glucose Profiles in Subjects with Normal Glucose Tolerance.

BACKGROUND: Current mathematical models of postprandial glucose metabolism in people with normal and impaired glucose tolerance rely on insulin measurements and are therefore not applicable in clinical practice. This research aims to develop a model that only requires glucose data for parameter estimation while also providing useful information on insulin sensitivity, insulin dynamics and the meal-related glucose appearance (GA). METHODS: The proposed glucose-only model (GOM) is based on the oral minimal model (OMM) of glucose dynamics and substitutes the insulin dynamics with a novel function dependant on glucose levels and GA. A Bayesian method and glucose data from 22 subjects with normal glucose tolerance are utilised for parameter estimation. To validate the results of the GOM, a comparison to the results of the OMM, obtained by using glucose and insulin data from the same subjects is carried out. RESULTS: The proposed GOM describes the glucose dynamics with comparable precision to the OMM with an RMSE of 5.1 ± 2.3 mg/dL and 5.3 ± 2.4 mg/dL, respectively and contains a parameter that is significantly correlated to the insulin sensitivity estimated by the OMM (r = 0.7) Furthermore, the dynamic properties of the time profiles of GA and insulin dynamics inferred by the GOM show high similarity to the corresponding results of the OMM. CONCLUSIONS: The proposed GOM can be used to extract useful physiological information on glucose metabolism in subjects with normal glucose tolerance. The model can be further developed for clinical applications to patients with impaired glucose tolerance under the use of continuous glucose monitoring data.

Bayesian parameter estimation in the oral minimal model of glucose dynamics from non-fasting conditions using a new function of glucose appearance.

BACKGROUND AND OBJECTIVE: The oral minimal model (OMM) of glucose dynamics is a prominent method for assessing postprandial glucose metabolism. The model yields estimates of insulin sensitivity and the meal-related appearance of glucose from insulin and glucose data after an oral glucose challenge. Despite its success, the OMM approach has several weaknesses that this paper addresses. METHODS: A novel procedure introducing three methodological adaptations to the OMM approach is proposed. These are: (1) the use of a fully Bayesian and efficient method for parameter estimation, (2) the model identification from non-fasting conditions using a generalised model formulation and (3) the introduction of a novel function to represent the meal-related glucose appearance based on two superimposed components utilising a modified structure of the log-normal distribution. The proposed modelling procedure is applied to glucose and insulin data from subjects with normal glucose tolerance consuming three consecutive meals in intervals of four hours. RESULTS: It is shown that the glucose effectiveness parameter of the OMM is, contrary to previous results, structurally globally identifiable. In comparison to results from existing studies that use the conventional identification procedure, the proposed approach yields an equivalent level of model fit and a similar precision of insulin sensitivity estimates. Furthermore, the new procedure shows no deterioration of model fit when data from non-fasting conditions are used. In comparison to the conventional, piecewise linear function of glucose appearance, the novel log-normally based function provides an improved model fit in the first 30 min of the response and thus a more realistic estimation of glucose appearance during this period. The identification procedure is implemented in freely accesible MATLAB and Python software packages. CONCLUSIONS: We propose an improved and freely available method for the identification of the OMM which could become the future standardard for the oral minimal modelling method of glucose dynamics.

A Minimal Model Approach for the Description of Postprandial Glucose Responses from Glucose Sensor Data in Diabetes Mellitus.

Modelling of the gluco-regulatory system in response to an oral glucose tolerance test (OGTT) has been the subject of research for decades. This paper presents an adaptation to the well-established oral minimal model that is identifiable from glucose data only and is able to capture the dynamics of glucose following both OGTT and mixed meal consumption. The model is in the form of low-dimensional differential equations with a recently introduced input function consisting of Gaussian shaped components. It was identified from glucose data recorded from six subjects without diabetes, prediabetes and type 2 diabetes under controlled conditions. The inferred parameters of the model are shown to have physiological meaning and produce realistic steady state behavior. This model may be useful in the development of clinical advisory tools for the treatment and prevention of non-insulin dependent type 2 diabetes mellitus.

Metabolic phenotype of male obesity-related secondary hypogonadism pre-replacement and post-replacement therapy with intra-muscular testosterone undecanoate therapy.

AIM: To explore the metabolic phenotype of obesity-related secondary hypogonadism (SH) in men pre-replacement and post-replacement therapy with long-acting intramuscular (IM) testosterone undecanoate (TU). METHODS: A prospective observational pilot study on metabolic effects of TU IM in male obesity-related SH (hypogonadal [HG] group, n = 13), including baseline comparisons with controls (eugonadal [EG] group, n = 15). Half the subjects (n = 7 in each group) had type 2 diabetes mellitus (T2D). Baseline metabolic assessment on Human Metabolism Research Unit: fasting blood samples; BodPod (body composition), and; whole-body indirect calorimetry. The HG group was treated with TU IM therapy for 6-29 months (mean 14.8-months [SD 8.7]), and assessment at the Human Metabolism Research Unit repeated. T-test comparisons were performed between baseline and follow-up data (HG group), and between baseline data (HG and EG groups). Data reported as mean (SD). RESULTS: Overall, TU IM therapy resulted in a statistically significant improvement in HbA1C (9 mmol/mol, P = 0.03), with 52% improvement in HOMA%B. Improvement in glycaemic control was driven by the HG subgroup with T2D, with 18 mmol/mol [P = 0.02] improvement in HbA1C. Following TU IM therapy, there was a statistically significant reduction in fat mass (3.5 Kg, P = 0.03) and increase in lean body mass (2.9 kg, P = 0.03). Lipid profiles and energy expenditure were unchanged following TU IM therapy. Comparisons between baseline data for HG and EG groups were equivalent apart from differences in testosterone, SHBG and basal metabolic rate (BMR). CONCLUSION: In men with obesity-related SH (including a subgroup with T2D), TU IM therapy improved glycaemic control, beta cell function, and body composition.

Chemerin induces endothelial cell inflammation: activation of nuclear factor-kappa beta and monocyte-endothelial adhesion.

Chemerin, a chemoattractant protein, acts via a G-protein coupled chemokine receptor, i.e. Chemokine like Receptor 1/ChemR23; levels of which are elevated in pro-inflammatory states such as obesity and type 2 diabetes mellitus (T2DM). Obesity and T2DM patients are at high risk of developing cardiovascular disorders such as atherosclerosis. We have reported that chemerin induces human endothelial cell angiogenesis and since dysregulated angiogenesis and endothelial dysfunction are hallmarks of vascular disease; we sought to determine the effects of chemerin on monocyte-endothelial adhesion, and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), a critical pro-inflammatory transcription factor. Human endothelial cells were transfected with pNF-kappaB-Luc plasmid. Chemerin induced NF-κB activation via the MAPK and PI3K/Akt pathways. Western blot analyses and monocyte-endothelial adhesion assay showed that chemerin increased endothelial cell adhesion molecule expression and secretion, namely E-selectin (Endothelial Selectin), VCAM-1 (Vascular Cell Adhesion Molecule-1) and ICAM-1 (Intracellular Adhesion Molecule-1), leading to enhancement of monocyte-endothelial adhesion. Additionally, we showed a synergistic response of the pro-inflammatory mediator, Interleukin-1ß with chemerin induced effects. Chemerin plays an important role in endothelial inflammation, as it induces monocyte-endothelial adhesion, a critical step in the development of atherosclerosis.

Effects of supplemented isoenergetic diets varying in cereal fiber and protein content on the bile acid metabolic signature and relation to insulin resistance.

Bile acids (BA) are potent metabolic regulators influenced by diet. We studied effects of isoenergetic increases in the dietary protein and cereal-fiber contents on circulating BA and insulin resistance (IR) in overweight and obese adults. Randomized controlled nutritional intervention (18 weeks) in 72 non-diabetic participants (overweight/obese: 29/43) with at least one further metabolic risk factor. Participants were group-matched and allocated to four isoenergetic supplemented diets: control; high cereal fiber (HCF); high-protein (HP); or moderately increased cereal fiber and protein (MIX). Whole-body IR and insulin-mediated suppression of hepatic endogenous glucose production were measured using euglycaemic-hyperinsulinemic clamps with [6-62H2] glucose infusion. Circulating BA, metabolic biomarkers, and IR were measured at 0, 6, and 18 weeks. Under isoenergetic conditions, HP-intake worsened IR in obese participants after 6 weeks (M-value: 3.77 ± 0.58 vs. 3.07 ± 0.44 mg/kg/min, p = 0.038), with partial improvement back to baseline levels after 18 weeks (3.25 ± 0.45 mg/kg/min, p = 0.089). No deleterious effects of HP-intake on IR were observed in overweight participants. HCF-diet improved IR in overweight participants after 6 weeks (M-value 4.25 ± 0.35 vs. 4.81 ± 0.31 mg/kg/min, p = 0.016), but did not influence IR in obese participants. Control and MIX diets did not influence IR. HP-induced, but not HCF-induced changes in IR strongly correlated with changes of BA profiles. MIX-diet significantly increased most BA at 18 weeks in obese, but not in overweight participants. BA remained unchanged in controls. Pooled BA concentrations correlated with fasting fibroblast growth factor-19 (FGF-19) plasma levels (r = 0.37; p = 0.003). Higher milk protein intake was the only significant dietary predictor for raised total and primary BA in regression analyses (total BA, p = 0.017; primary BA, p = 0.011). Combined increased intake of dietary protein and cereal fibers markedly increased serum BA concentrations in obese, but not in overweight participants. Possible mechanisms explaining this effect may include compensatory increases of the BA pool in the insulin resistant, obese state; or defective BA transport.

Screening for malnutrition in patients with gastro-entero-pancreatic neuroendocrine tumours: a cross-sectional study.

OBJECTIVES: To investigate whether screening for malnutrition using the validated malnutrition universal screening tool (MUST) identifies specific characteristics of patients at risk, in patients with gastro-entero-pancreatic neuroendocrine tumours (GEP-NET). DESIGN: Cross-sectional study. SETTING: University Hospitals Coventry & Warwickshire NHS Trust; European Neuroendocrine Tumour Society Centre of Excellence. PARTICIPANTS: Patients with confirmed GEP-NET (n=161) of varying primary tumour sites, functioning status, grading, staging and treatment modalities. MAIN OUTCOME MEASURE: To identify disease and treatment-related characteristics of patients with GEP-NET who score using MUST, and should be directed to detailed nutritional assessment. RESULTS: MUST score was positive (≥1) in 14% of outpatients with GEP-NET. MUST-positive patients had lower faecal elastase concentrations compared to MUST-negative patients (244±37 vs 383±20 µg/g stool; p=0.018), and were more likely to be on treatment with long-acting somatostatin analogues (65 vs 38%, p=0.021). MUST-positive patients were also more likely to have rectal or unknown primary NET, whereas, frequencies of other GEP-NET including pancreatic NET were comparable between MUST-positive and MUST-negative patients. CONCLUSIONS: Given the frequency of patients identified at malnutrition risk using MUST in our relatively large and diverse GEP-NET cohort and the clinical implications of detecting malnutrition early, we recommend routine use of malnutrition screening in all patients with GEP-NET, and particularly in patients who are treated with long-acting somatostatin analogues.

Characterization of wrist-wearable activity measurement using whole body calorimetry in semi-free living conditions.

Physical activity (PA) is a significant factor in a number of health conditions and monitoring PA can play a significant role in the treatment of, or research into, these conditions. For longitudinal monitoring of PA, unobtrusive devices are often used and there is a need for the development of energy expenditure (EE) estimation techniques from single-device systems. This paper presents an experiment designed to characterize the relationship between a previously described technique, the activity score (AS) and EE obtained from whole-room indirect calorimetry. The study used 8 participants over a 24-hr period with interspersed exercise periods to observe physical movement with wearable devices and EE in 5 minute epochs. Results show that AS and EE are correlated with a Spearman's rank correlation coefficient of 0.775 with p <; 0.001.

Modulation of amino acid metabolic signatures by supplemented isoenergetic diets differing in protein and cereal fiber content.

CONTEXT: Amino-acid (AA) metabolic signatures differ in insulin-resistant (IR) obese vs normal-weight subjects, improve after weight loss, and seem to predict the risk of type 2 diabetes. It is unknown whether weight-maintaining dietary measures aimed at influencing IR alter AA signatures of high-risk subjects. SETTING AND DESIGN: In the randomized controlled Protein, Fiber and Metabolic Syndrome (ProFiMet) trial we investigated effects of four isoenergetic, moderately fat-reduced diets varying in protein and cereal-fiber contents on complete AA metabolic signatures in 76 group-matched overweight or obese high-risk subjects. We analyzed the relation of whole-body and hepatic IR with AA signatures, body fat composition and liver fat, after 0, 6, and 18 weeks of dietary intervention. Discrimination between diets was further enhanced by providing tailored dietary supplements for twice-daily consumption over 18 weeks in all groups. RESULTS: Baseline AA, including branched-chain signatures significantly related to IR, liver fat, and visceral fat mass. Isoenergetic variation of protein and cereal-fiber dietary contents, but not fat restriction, significantly influenced IR, whereas the relation of AA with IR changed with all diets. The tryptophan ratio was significantly suppressed in obese vs overweight participants, but increased after 6 weeks of high cereal-fiber intake to a nonobese phenotype. Modeling analyses revealed diet-induced alterations of complex AA profiles to relate to 70% and 62% of changes in whole-body and hepatic IR. CONCLUSIONS: We demonstrate that relatively short-term isoenergetic changes in the diet significantly alter the relation of AA signatures with IR, with possible implications on the determination and treatment of diabetes risk.

Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques.

We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6 ± 1.0 years, BMI 31.5 ± 0.4 kg/m(2); 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6-6(2)H(2)] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39-56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r(2) = 27-32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations.