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In a rapid increase in cases of diabetes mellitus worldwide, there has been interested in the use of plant-derived polyphenols as nutraceuticals to prevent the onset and progression of diabetes mellitus and its associated complications. Aspalathus linearis, commonly known as rooibos, is a rich source of uncommon glycosylated plant polyphenols with various critical health-promoting properties, including the prevention and treatment of diabetes mellitus (DM). This study aimed to examine these effects by meta-analyzing the current evidence in diabetic rodent models. Peer-reviewed studies written in English from two databases, PubMed and Embase, were searched up to 28 February 2018. Studies reporting blood glucose levels in diabetic rodents with and without receiving rooibos extracts or their major phenolic compounds are included. Twelve studies enrolling 88 diabetic rodents treated with rooibos extracts or their polyphenols and 85 diabetic control males reported blood glucose levels. The pooled effect size was −0.89 (95% CI: −1.44 to −0.35) with a substantial heterogeneity (I2 = 67.0%). This effect was likely to be modified by type of rooibos extracts and their polyphenols and treatment period. Blood glucose levels were significantly lower in diabetic rodent models treated with the phenolic compound rich in rooibos extracts, PPAG.

Aim: The aim of the present study was undertaken to correlate the glucose levels in saliva and blood of diabetic and healthy nondiabetic individuals and to determine the efficacy of saliva as a diagnostic tool. Setting and Design: This was a case-control study. Materials and Methods: Forty-five patients previously diagnosed with diabetes mellitus and 45 healthy controls were included in the study. The patients and controls were asked to come to the clinic in the morning, after 8-10 h fasting. At that time, 5 ml of venous blood and unstimulated saliva was collected from both the groups, and 2 h after meal, again, venous blood and unstimulated saliva were collected. The saliva and sera from blood samples were subjected to glucose estimation. Saliva was collected in sterilized vials, and blood was collected in test tubes. Glucose estimation was done by oxidase-peroxidase method. Statistical Analysis: Pearson's correlation coefficient, Student's t-test and paired t-test were used for statistical analysis. Results: Correlation coefficient values show that there is a significant positive correlation between fasting blood and fasting salivary glucose levels and postprandial blood and postprandial salivary glucose levels. Conclusion: Salivary glucose level estimation can be used as a potential indicator in screening, diagnosis and monitoring of diabetes mellitus. Furthermore, it is an easy and noninvasive method.

Elevated 1‐h plasma glucose (1h‐PG; ≥155 mg/dL) during an oral glucose tolerance test is a risk factor for type 2 diabetes. However, the metabolic characteristics of non‐obese Asians with elevated 1h‐PG are unknown. Thus, we studied 59 non‐obese Japanese men with normal glucose tolerance. We divided study participants into the Low 1h‐PG group (<155 mg/dL) and the High 1h‐PG group (≥155 mg/dL). We compared the metabolic characteristics of the groups, including tissue‐specific insulin sensitivity measured using a two‐step hyperinsulinemic‐euglycemic clamp. Insulinogenic index and adiponectin levels were significantly lower in the High 1h‐PG group than in the Low 1h‐PG group. Other characteristics, including insulin sensitivity, adiposity and ectopic fat accumulation, were similar between the groups. In conclusion, non‐obese Japanese men with high 1h‐PG have impaired early‐phase insulin secretion and lower adiponectin levels. Insulin resistance and abnormal fat distribution were not evident in this population. Characteristics of non‐obese Asians with elevated 1‐h plasma glucose are unknown. Individuals with elevated 1‐h plasma glucose have lower insulinogenic index and adiponectin. Insulin sensitivity was similar between the low and high 1‐h plasma glucose groups.

The diabetes is a disease that can become a serious disorder for a lifetime. It kills more than a million people every year. This disease can affect anyone. Diabetes occurs when the body is unable to process all the sugar (glucose) in the bloodstream; its complications can move to heart issues, caress, vision loss, and kidney stoppage and leg amputation problems. Many people with diabetes inject their body daily and feel that their work is done. Diabetes is an incurable disease because of poor health. The diabetes be able to be divided keen on2 types. The type-1 diabetes is hereditary. It is not easy to cure. People with type 2 diabetes can greatly reduce their risk of developing diabetes by following a proper, proper lifestyle. In addition it helps reduce the risk of diabetes. The proposed model of managing diabetics explains this disease as a specific lifestyle. The existence of an effective system for the treatment of diabetes, according to the tasks currently set out, provides for the achievement of goals. The proposed edge based machine learning approach was achieved 85% of results compared with the Blood glucose level prediction, Adaptive multivariable closed-loop control, neural model of blood glucose level and Detecting Undiagnosed Diabetes.

Type 2 Diabetes Mellitus (T2DM) is a costly, lifestyle-related disorder, its management is very critical and challenging hence lifestyle intervention may a cornerstone in the reversal and management of T2DM. This study designed to assess the impact of lifestyle intervention holistic (LIH) Model on blood glucose levels (BGL), Health-Related Quality of Life (HRQOL), and medical treatment cost in T2DM patients. This prospective, quasi-experimental study was conducted among 224 T2DM patients in Delhi Diabetes Research Center (DDRC), New Delhi. The study participants were allocated into two groups-Lifestyle Intervention Counseling (LIC) group received lifestyle-based counseling through the LIH model while the Usual-care group received only standard treatment. Study outcomes were assessed at baseline, 3rd, 6th, and 12th month and data were analyzed through SPSS. Study results revealed that LIC participants had decreased in fasting blood glucose 0.26 mg dL-1 (-4.37 to 4.89), blood glucose postprandial -70.16 mg dL-1 (-85.15 to - 55.16), HbA1C -2.82% (-5.26 to - 0.37), medicine cost (p < 0.004), hospitalization cost (p < 0.011), and cost of surgery (p < 0.0005). A significant improvement also observed in HRQOL and adherence towards a holistic model in LIC group. The study concludes that lifestyle-based counseling and its adherence was cost-effective and significantly improves BGL, HRQoL, and medical treatment in T2DM patients.

The current study was aimed to evaluate the antidiabetic effect of grape seed extract (GSE) on Alloxan (120mg/kg of body weight) induced diabetes in mice as well as characterize the chemical composition and phytochemical content of grape seeds from three grape cultivars (Ahmer, Halawani, and Kamali) grown in Iraq as well as pomace. Ahmer gave the highest values for crude fat14.84±0.2 and phytochemicals (tannins, saponin, alkaloids, flavonoids, phenol, and anthocyanin) as compared to other cultivars. phytochemical analysis using High-performance liquid chromatography (HPLC) revealed that the highest concentration of proanthocyanidins polymers (catechine, procyanidin, and epicatechine) was recorded in Ahmer seed extract which were (796, 170, 244) µg/g, respectively, while the lowest amounts were in pomace 489, 99, and 143 µg/g, respectively using HPLC. Oral administration of grape seed natural extract (600 mg/kg/day) reduced the level of glucose in mice which was highly statistically significant (p <0.01) compared with the diabetic control mice (untreated), which was 206.83±6.7 and 349±27.50 mg/dl, respectively.

Our study was focused on identification and correction of early hyperglycaemia, with the aim to reduce the risk of developing post-transplant diabetes mellitus (PTDM) and its associated complications. In a single centre, the prospective study included adult kidney transplant recipients without diabetes mellitus whose pre-transplant glucometabolic data did not show signs of diabetes mellitus. Starting from the first day after kidney transplantation, patients were closely monitored for hyperglycaemia; glucose level measurements were started to obtain pre-prandial levels. If the blood glucose level exceeded 11.1 mmol/l, hyperglycaemia was corrected with short-acting insulin. A total of 14 patients completed a three-month follow-up. During the first post-transplant week, the blood glucose level exceeded 11.1 mmol/l in nine patients (63.9%). From those patients five (55.5%) did not develop PTDM. None of the patients who did not need insulin treatment developed PTDM. Higher pre-lunch glucose levels increased the risk of developing PTDM (p = 0.006). Patients with diabetes required a two times higher insulin dosage than other patients during the first post-transplantation week. We found that hyperglycaemia is a common problem in the early post-transplant period. Early recognition and correction of inpatient hyperglycaemia was associated with reduction of the prevalence of PTDM in more than a half of the patients in the studied group at three months post transplant.

Aims/hypothesisWe determined whether the time of day of exercise training (morning vs evening) would modulate the effects of consumption of a high-fat diet (HFD) on glycaemic control, whole-body health markers and serum metabolomics.MethodsIn this three-armed parallel-group randomised trial undertaken at a university in Melbourne, Australia, overweight/obese men consumed an HFD (65% of energy from fat) for 11 consecutive days. Participants were recruited via social media and community advertisements. Eligibility criteria for participation were male sex, age 30–45 years, BMI 27.0–35.0 kg/m2 and sedentary lifestyle. The main exclusion criteria were known CVD or type 2 diabetes, taking prescription medications, and shift-work. After 5 days, participants were allocated using a computer random generator to either exercise in the morning (06:30 hours), exercise in the evening (18:30 hours) or no exercise for the subsequent 5 days. Participants and researchers were not blinded to group assignment. Changes in serum metabolites, circulating lipids, cardiorespiratory fitness, BP, and glycaemic control (from continuous glucose monitoring) were compared between groups.ResultsTwenty-five participants were randomised (morning exercise n = 9; evening exercise n = 8; no exercise n = 8) and 24 participants completed the study and were included in analyses (n = 8 per group). Five days of HFD induced marked perturbations in serum metabolites related to lipid and amino acid metabolism. Exercise training had a smaller impact than the HFD on changes in circulating metabolites, and only exercise undertaken in the evening was able to partly reverse some of the HFD-induced changes in metabolomic profiles. Twenty-four-hour glucose concentrations were lower after 5 days of HFD compared with the participants’ habitual diet (5.3 ± 0.4 vs 5.6 ± 0.4 mmol/l, p = 0.001). There were no significant changes in 24 h glucose concentrations for either exercise group but lower nocturnal glucose levels were observed in participants who trained in the evening, compared with when they consumed the HFD alone (4.9 ± 0.4 vs 5.3 ± 0.3 mmol/l, p = 0.04). Compared with the no-exercise group, peak oxygen uptake improved after both morning (estimated effect 1.3 ml min−1 kg−1 [95% CI 0.5, 2.0], p = 0.003) and evening exercise (estimated effect 1.4 ml min−1 kg−1 [95% CI 0.6, 2.2], p = 0.001). Fasting blood glucose, insulin, cholesterol, triacylglycerol and LDL-cholesterol concentrations decreased only in participants allocated to evening exercise training. There were no unintended or adverse effects.Conclusions/interpretationA short-term HFD in overweight/obese men induced substantial alterations in lipid- and amino acid-related serum metabolites. Improvements in cardiorespiratory fitness were similar regardless of the time of day of exercise training. However, improvements in glycaemic control and partial reversal of HFD-induced changes in metabolic profiles were only observed when participants exercise trained in the evening.Trial registrationanzctr.org.au registration no. ACTRN12617000304336.FundingThis study was funded by the Novo Nordisk Foundation (NNF14OC0011493).

Abstract Context Sleep disruption is associated with worse glucose metabolic control and altered gut microbiota in animal models. Objective We aimed to evaluate the possible links among rapid eye movement (REM) sleep duration, continuous glucose levels, and gut microbiota composition. Methods This observational, prospective, real-life, cross-sectional case-control study included 118 (60 with obesity), middle-aged (39.1-54.8 years) healthy volunteers recruited at a tertiary hospital. Glucose variability and REM sleep duration were assessed by 10-day continuous glucose monitoring (CGM) (Dexcom G6) and wrist actigraphy (Fitbit Charge 3), respectively. The coefficient of variation (CV), interquartile range (IQR), and SD of glucose variability was assessed and the percentage of time in range (% TIR), at 126-139 mg/dL (TIR2), and 140-199 mg/dL (TIR3) were calculated. Shotgun metagenomics sequencing was applied to study gut microbiota taxonomy and functionality. Results Increased glycemic variability (SD, CV, and IQR) was observed among subjects with obesity in parallel to increased % TIR2 and % TIR3. REM sleep duration was independently associated with % TIR3 (β = −.339; P < .001) and glucose variability (SD, β = −.350; P < .001). Microbial taxa from the Christensenellaceae family (Firmicutes phylum) were positively associated with REM sleep and negatively with CGM levels, while bacteria from Enterobacteriacea family and bacterial functions involved in iron metabolism showed opposite associations. Conclusion Decreased REM sleep duration was independently associated with a worse glucose profile. The associations of species from Christensenellaceae and Enterobacteriaceae families with REM sleep duration and continuous glucose values suggest an integrated picture of metabolic health.

Aims/hypothesisExercise is recommended for the treatment and prevention of type 2 diabetes. However, the most effective time of day to achieve beneficial effects on health remains unknown. We aimed to determine whether exercise training at two distinct times of day would have differing effects on 24 h blood glucose levels in men with type 2 diabetes.MethodsEleven men with type 2 diabetes underwent a randomised crossover trial. Inclusion criteria were 45–68 years of age and BMI between 23 and 33 kg/m2. Exclusion criteria were insulin treatment and presence of another systemic illness. Researchers were not blinded to the group assignment. The trial involved 2 weeks of either morning or afternoon high-intensity interval training (HIIT) (three sessions/week), followed by a 2 week wash-out period and a subsequent period of the opposite training regimen. Continuous glucose monitor (CGM)-based data were obtained.ResultsMorning HIIT increased CGM-based glucose concentration (6.9 ± 0.4 mmol/l; mean ± SEM for the exercise days during week 1) compared with either the pre-training period (6.4 ± 0.3 mmol/l) or afternoon HIIT (6.2 ± 0.3 mmol/l for the exercise days during week 1). Conversely, afternoon HIIT reduced the CGM-based glucose concentration compared with either the pre-training period or morning HIIT. Afternoon HIIT was associated with elevated thyroid-stimulating hormone (TSH; 1.9 ± 0.2 mU/l) and reduced T4 (15.8 ± 0.7 pmol/l) concentrations compared with pre-training (1.4 ± 0.2 mU/l for TSH; 16.8 ± 0.6 pmol/l for T4). TSH was also elevated after morning HIIT (1.7 ± 0.2 mU/l), whereas T4 concentrations were unaltered.Conclusions/interpretationAfternoon HIIT was more efficacious than morning HIIT at improving blood glucose in men with type 2 diabetes. Strikingly, morning HIIT had an acute, deleterious effect, increasing blood glucose. However, studies of longer training regimens are warranted to establish the persistence of this adverse effect. Our data highlight the importance of optimising the timing of exercise when prescribing it as treatment for type 2 diabetes.