Sarcopenia has been defined as a progressive and generalized loss of muscle mass that can be observed after the age of 40 years, with a rate of deterioration of about 8% every ten years up to 70 ...years, and 15-25% thereafter ....
Mathematical modeling in the field of glucose metabolism has a longstanding tradition. The use of models is motivated by several reasons. Models have been used for calculating parameters of ...physiological interest from experimental data indirectly, to provide an unambiguous quantitative representation of pathophysiological mechanisms, to determine indices of clinical usefulness from simple experimental tests. With the growing societal impact of type 2 diabetes, which involves the disturbance of the glucose homeostasis system, development and use of models in this area have increased. Following the approaches of physiological and clinical investigation, the focus of the models has spanned from representations of whole body processes to those of cells, i.e., from
to
research. Model-based approaches for linking
to
research have been proposed, as well as multiscale models merging the two areas. The success and impact of models has been variable. Two kinds of models have received remarkable interest: those widely used in clinical applications, e.g., for the assessment of insulin sensitivity and β-cell function and some models representing specific aspects of the glucose homeostasis system, which have become iconic for their efficacy in describing clearly and compactly key physiological processes, such as insulin secretion from the pancreatic β cells. Models are inevitably simplified and approximate representations of a physiological system. Key to their success is an appropriate balance between adherence to reality, comprehensibility, interpretative value and practical usefulness. This has been achieved with a variety of approaches. Although many models concerning the glucose homeostasis system have been proposed, research in this area still needs to address numerous issues and tackle new opportunities. The mathematical representation of the glucose homeostasis processes is only partial, also because some mechanisms are still only partially understood. For
research, mathematical models still need to develop their potential. This review illustrates the problems, approaches and contribution of mathematical modeling to the physiological and clinical investigation of glucose homeostasis and diabetes, focusing on the most relevant and stimulating models.
The aim of this study was to test the effect of a plant-based dietary intervention on beta-cell function in overweight adults with no history of diabetes. Participants (
= 75) were randomized to ...follow a low-fat plant-based diet (
= 38) or to make no diet changes (
= 37) for 16 weeks. At baseline and 16 weeks, beta-cell function was quantified with a mathematical model. Using a standard meal test, insulin secretory rate was calculated by C-peptide deconvolution. The Homeostasis Model Assessment (HOMA-IR) index was used to assess insulin resistance while fasting. A marked increase in meal-stimulated insulin secretion was observed in the intervention group compared with controls (interaction between group and time, Gxt,
< 0.001). HOMA-IR index fell significantly (
< 0.001) in the intervention group (treatment effect -1.0 (95% CI, -1.2 to -0.8); Gxt,
= 0.004). Changes in HOMA-IR correlated positively with changes in body mass index (BMI) and visceral fat volume (
= 0.34;
= 0.009 and
= 0.42;
= 0.001, respectively). The latter remained significant after adjustment for changes in BMI (
= 0.41;
= 0.002). Changes in glucose-induced insulin secretion correlated negatively with BMI changes (
= -0.25;
= 0.04), but not with changes in visceral fat. Beta-cell function and insulin sensitivity were significantly improved through a low-fat plant-based diet in overweight adults.
Epidemiological studies have shown that increased circulating branched-chain amino acids (BCAAs) are associated with insulin resistance and type 2 diabetes (T2D). This may result from altered energy ...metabolism or dietary habits.
We hypothesized that a lower intake of BCAAs improves tissue-specific insulin sensitivity.
This randomized, placebo-controlled, double-blinded, crossover trial examined well-controlled T2D patients receiving isocaloric diets (protein: 1 g/kg body weight) for 4 wk. Protein requirements were covered by commercially available food supplemented ≤60% by an AA mixture either containing all AAs or lacking BCAAs. The dietary intervention ensured sufficient BCAA supply above the recommended minimum daily intake. The patients underwent the mixed meal tolerance test (MMT), hyperinsulinemic-euglycemic clamps (HECs), and skeletal muscle and white adipose tissue biopsies to assess insulin signaling.
After the BCAA− diet, BCAAs were reduced by 17% during fasting (P < 0.001), by 13% during HEC (P < 0.01), and by 62% during the MMT (P < 0.001). Under clamp conditions, whole-body and hepatic insulin sensitivity did not differ between diets. After the BCAA− diet, however, the oral glucose sensitivity index was 24% (P < 0.01) and circulating fibroblast-growth factor 21 was 21% higher (P < 0.05), whereas meal-derived insulin secretion was 28% lower (P < 0.05). Adipose tissue expression of the mechanistic target of rapamycin was 13% lower, whereas the mitochondrial respiratory control ratio was 1.7-fold higher (both P < 0.05). The fecal microbiome was enriched in Bacteroidetes but depleted of Firmicutes.
Short-term dietary reduction of BCAAs decreases postprandial insulin secretion and improves white adipose tissue metabolism and gut microbiome composition. Longer-term studies will be needed to evaluate the safety and metabolic efficacy in diabetes patients.
This trial was registered at clinicaltrials.gov as NCT03261362.
Diabetic foot syndrome is a multifactorial pathology with at least three main etiological factors, i.e., peripheral neuropathy, peripheral arterial disease, and infection. In addition to complexity, ...another distinctive trait of diabetic foot syndrome is its insidiousness, due to a frequent lack of early symptoms. In recent years, it has become clear that the prevalence of diabetic foot syndrome is increasing, and it is among the diabetes complications with a stronger impact on patient’s quality of life. Considering the complex nature of this syndrome, artificial intelligence (AI) methodologies appear adequate to address aspects such as timely screening for the identification of the risk for foot ulcers (or, even worse, for amputation), based on appropriate sensor technologies. In this review, we summarize the main findings of the pertinent studies in the field, paying attention to both the AI-based methodological aspects and the main physiological/clinical study outcomes. The analyzed studies show that AI application to data derived by different technologies provides promising results, but in our opinion future studies may benefit from inclusion of quantitative measures based on simple sensors, which are still scarcely exploited.
Sarcopenia is emerging as a severe complication in type 2 diabetes (T2DM). On the other hand, it has been documented that nutritional aspects, such as insufficient protein or total energy intake, ...increase sarcopenia risk. The analysis of body composition is a relevant approach to assess nutritional status, and different techniques are available. Among such techniques, bioelectrical impedance analysis (BIA) is particularly interesting, since it is non-invasive, simple, and less expensive than the other techniques. Therefore, we conducted a review study to analyze the studies using BIA for body composition analysis in T2DM patients with sarcopenia or at risk of catching it. Revised studies have provided important information concerning relationships between body composition parameters (mainly muscle mass) and other aspects of T2DM patients' conditions, including different comorbidities, and information on how to avoid muscle mass deterioration. Such relevant findings suggest that BIA can be considered appropriate for body composition analysis in T2DM complicated by sarcopenia/muscle loss. The wide size of the patients' cohort in many studies confirms that BIA is convenient for clinical applications. However, studies with a specific focus on the validation of BIA, in the peculiar population of patients with T2DM complicated by sarcopenia, should be considered.
The aim of this study was to develop a dynamic model-based approach to separately quantify the exogenous and endogenous contributions to total plasma insulin concentration and to apply it to assess ...the effects of inhaled-insulin administration on endogenous insulin secretion during a meal test. A three-step dynamic in-silico modeling approach was developed to estimate the two insulin contributions of total plasma insulin in a group of 21 healthy subjects who underwent two equivalent standardized meal tests on separate days, one of which preceded by inhalation of a Technosphere
Insulin dose (22U or 20U). In the 30-120 min test interval, the calculated endogenous insulin component showed a divergence in the time course between the test with and without inhaled insulin. Moreover, the supra-basal area-under-the-curve of endogenous insulin in the test with inhaled insulin was significantly lower than that in the test without (2.1 ± 1.7 × 10
pmol·min/L vs 4.2 ± 1.8 × 10
pmol·min/L, p < 0.01). The percentage of exogenous insulin reaching the plasma, relative to the inhaled dose, was 42 ± 21%. The proposed in-silico approach separates exogenous and endogenous insulin contributions to total plasma insulin, provides individual bioavailability estimates, and can be used to assess the effect of inhaled insulin on endogenous insulin secretion during a meal.
It has not been elucidated whether incretins affect insulin clearance in type 2 diabetes (T2D). We aimed exploring possible associations between insulin clearance and endogenously secreted or ...exogenously administered incretins in T2D patients. Twenty T2D patients were studied (16 males/4 females, 59 ± 2 years (mean ± standard error), BMI = 31 ± 1 kg/m
, HbA1c = 7.0 ± 0.1%). Patients were treated with metformin, sitagliptin, metformin/sitagliptin combination, and placebo (randomized order). On each treatment period, oral and isoglycemic intravenous glucose infusion tests were performed (OGTT, IIGI, respectively). We also studied twelve T2D patients (9 males/3 females, 61 ± 3 years, BMI = 30 ± 1 kg/m
, HbA1c = 7.3 ± 0.4%) that underwent infusion of GLP-1(7-36)-amide, GIP, GLP-1/GIP combination, and placebo. Plasma glucose, insulin, C-peptide, and incretins were measured. Insulin clearance was assessed as insulin secretion to insulin concentration ratio. In the first study, we found OGTT/IIGI insulin clearance ratio weakly inversely related to OGTT/IIGI total GIP and intact GLP-1 (R
= 0.13, p < 0.02). However, insulin clearance showed some differences between sitagliptin and metformin treatment (p < 0.02). In the second study we found no difference in insulin clearance following GLP-1 and/or GIP infusion (p > 0.5). Thus, our data suggest that in T2D there are no relevant incretin effects on insulin clearance. Conversely, different antidiabetic treatments may determine insulin clearance variations.
Diet modulates gut microbiota and plays an important role in human health. The aim of this study was to test the effect of a low-fat vegan diet on gut microbiota and its association with weight, body ...composition, and insulin resistance in overweight men and women. We enrolled 168 participants and randomly assigned them to a vegan (
= 84) or a control group (
= 84) for 16 weeks. Of these, 115 returned all gut microbiome samples. Gut microbiota composition was assessed using uBiome Explorer™ kits. Body composition was measured using dual energy X-ray absorptiometry. Insulin sensitivity was quantified with the predicted clamp-derived insulin sensitivity index from a standard meal test. Repeated measure ANOVA was used for statistical analysis. Body weight decreased in the vegan group (treatment effect -5.9 kg 95% CI, -7.0 to -4.9 kg;
< 0.001), mainly due to a reduction in fat mass (-3.9 kg 95% CI, -4.6 to -3.1 kg;
< 0.001) and in visceral fat (-240 cm
95% CI, -345 to -135 kg;
< 0.001). PREDIcted M, insulin sensitivity index (PREDIM) increased in the vegan group (treatment effect +0.83 95% CI, +0.48 to +1.2;
< 0.001). The relative abundance of Faecalibacterium prausnitzii increased in the vegan group (+5.1% 95% CI, +2.4 to +7.9%;
< 0.001) and correlated negatively with changes in weight (r = -0.24;
= 0.01), fat mass (r = -0.22;
= 0.02), and visceral fat (r = -0.20;
= 0.03). The relative abundance of Bacteroides fragilis decreased in both groups, but less in the vegan group, making the treatment effect positive (+18.9% 95% CI, +14.2 to +23.7%;
< 0.001), which correlated negatively with changes in weight (r = -0.44;
< 0.001), fat mass (r = -0.43;
< 0.001), and visceral fat (r = -0.28;
= 0.003) and positively with PREDIM (r = 0.36;
< 0.001), so a smaller reduction in Bacteroides fragilis was associated with a greater loss of body weight, fat mass, visceral fat, and a greater increase in insulin sensitivity. A low-fat vegan diet induced significant changes in gut microbiota, which were related to changes in weight, body composition, and insulin sensitivity in overweight adults, suggesting a potential use in clinical practice.
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