Long-range Correlated Glucose Fluctuations in Diabetes

Blood urea nitrogen may serve as a predictive indicator of retained placenta in dairy cows

Retained placentae (RP) results in significant economic losses to dairy farmers. In Experiment 1, to screen biochemical indicators of RP, 21 cows with RP and 21 cows with no retained placenta (NRP) were selected as a control group, and blood was collected at -7 d, 0 h (parturition) and 12 h. Serum biochemical indicators were ascertained. Results indicate serum concentrations of phosphorus (P) and blood urea nitrogen (BUN) in cows of the RP group were markedly greater than in cows of the NRP group at -7 d (P < 0.01). In Experiment 2, to evaluate predictive indicators for RP, 34 cows with RP and 34 cows with NRP were selected, and there was blood sampling at -15 d, -10 d, -7 d, -4 d, and -1 d. Serum P, BUN, and total protein (TP) were evaluated. Associations of values among the three indicators and occurrence of RP were analyzed using binary logistic regression. Results indicate there was a negative correlation between only the values for BUN and RP (P = 0.016). In Experiment 3, to test hypothesis that relatively greater concentrations of BUN effects immune function in placental tissues, four cows were selected, placentae were collected at 0 and 12 h, and hematoxylin-eosin (HE) staining was performed. Results indicated that the extent of inflammatory cell infiltration and vascular proliferation were less at the 12 than 0-hour timepoint. Taken together, BUN at -7 d may serve as a predictive indicator of RP in cows.

Dynamic properties of glucose complexity during the course of critical illness: a pilot study

Methods to control the blood glucose (BG) levels of patients in intensive care units (ICU) improve the outcomes. The development of continuous BG levels monitoring devices has also permitted to optimize these processes. Recently it was shown that a complexity loss of the BG signal is linked to poor clinical outcomes. Thus, it becomes essential to decipher this relation to design efficient BG level control methods. In previous studies the BG signal complexity was calculated as a single index for the whole ICU stay. Although, these approaches did not grasp the potential variability of the BG signal complexity. Therefore, we setup this pilot study using a continuous monitoring of central venous BG levels in ten critically ill patients (EIRUS platform, Maquet Critical CARE AB, Solna, Sweden). Data were processed and the complexity was assessed by the detrended fluctuation analysis and multiscale entropy (MSE) methods. Finally, recordings were split into 24 h overlapping intervals and a MSE analysis was applied to each of them. The MSE analysis on time intervals revealed an entropy variation and allowed periodic BG signal complexity assessments. To highlight differences of MSE between each time interval we calculated the MSE complexity index defined as the area under the curve. This new approach could pave the way to future studies exploring new strategies aimed at restoring blood glucose complexity during the ICU stay.

Chikusetsu saponin IVa protects pancreatic β cell against intermittent high glucose-induced injury by activating Wnt/β-catenin/TCF7L2 pathway

Islet β cell mass reduction induced by glucose fluctuation is crucial for the development and progression of T2DM. Chikusetsu saponin IVa (CHS) had protective effects against DM and related injuries. Here we aimed to investigate the role of CHS in β cell injuries and its possible mechanism involved. Isolated rat islets, βTC3 cells and T2DM mice were used in this study. The results showed that CHS restored the secretion activity, promoted β cell survival by increasing β cell proliferation and decreasing apoptosis which induced by intermittent high glucose (IHG). In vivo, CHS protected β cell apoptosis to normalize blood glucose and improve insulin sensitivity in DM mice. Further studies showed that CHS activated Wnt3a signaling, inhibited HBP1, promoted β-catenin nuclear translocation, enhanced expressions of TCF7L2, GIPR and GLP-1R, inhibited p53, p27 and p21. The protective effect of CHS was remarkably suppressed by siRNAs against TCF7L2 or XAV-939 (a Wnt/β-catenin antagonist) in vitro and in β-catenin^-/- mice. In conclusion, we identified a novel role of CHS in protecting β cell survival and regeneration by mechanisms involving the activation of Wnt3a/β-catenin/TCF7L2 signaling. Our results indicated the potential value of CHS as a possible intervention drug for T2DM.

Classification of glucose records from patients at diabetes risk using a combined permutation entropy algorithm

BACKGROUND AND OBJECTIVES

The adoption in clinical practice of electronic portable blood or interstitial glucose monitors has enabled the collection, storage, and sharing of massive amounts of glucose level readings. This availability of data opened the door to the application of a multitude of mathematical methods to extract clinical information not discernible with conventional visual inspection. The objective of this study is to assess the capability of Permutation Entropy (PE) to find differences between glucose records of healthy and potentially diabetic subjects.

METHODS

PE is a mathematical method based on the relative frequency analysis of ordinal patterns in time series that has gained a lot of attention in the last years due to its simplicity, robustness, and performance. We study in this paper the applicability of this method to glucose records of subjects at risk of diabetes in order to assess the predictability value of this metric in this context.

RESULTS

PE, along with some of its derivatives, was able to find significant differences between diabetic and non-diabetic patients from records acquired up to 3 years before the diagnosis. The quantitative results for PE were 3.5878 ± 0.3916 for the nondiabetic class, and 3.1564 ± 0.4166 for the diabetic class. With a classification accuracy higher than 70%, and by means of a Cox regression model, PE demonstrated that it is a very promising candidate as a risk stratification tool for continuous glucose monitoring.

CONCLUSION

PE can be considered as a prospective tool for the early diagnosis of the glucoregulatory system.

Glucose time series complexity as a predictor of type 2 diabetes

BACKGROUND

Complexity analysis of glucose profile may provide valuable information about the gluco-regulatory system. We hypothesized that a complexity metric (detrended fluctuation analysis, DFA) may have a prognostic value for the development of type 2 diabetes in patients at risk.

METHODS

A total of 206 patients with any of the following risk factors (1) essential hypertension, (2) obesity or (3) a first-degree relative with a diagnosis of diabetes were included in a survival analysis study for a diagnosis of new onset type 2 diabetes. At inclusion, a glucometry by means of a Continuous Glucose Monitoring System was performed, and DFA was calculated for a 24-h glucose time series. Patients were then followed up every 6 months, controlling for the development of diabetes.

RESULTS

In a median follow-up of 18 months, there were 18 new cases of diabetes (58.5 cases/1000 patient-years). DFA was a significant predictor for the development of diabetes, with ten events in the highest quartile versus one in the lowest (log-rank test chi2 = 9, df = 1, p = 0.003), even after adjusting for other relevant clinical and biochemical variables. In a Cox model, the risk of diabetes development increased 2.8 times for every 0.1 DFA units. In a multivariate analysis, only fasting glucose, HbA_1c and DFA emerged as significant factors.

CONCLUSIONS

Detrended fluctuation analysis significantly performed as a harbinger of type 2 diabetes development in a high-risk population. Complexity analysis may help in targeting patients who could be candidates for intensified treatment. Copyright © 2016 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd.

Delay in the Detrended Fluctuation Analysis Crossover Point as a Risk Factor for Type 2 Diabetes Mellitus

Detrended Fluctuation Analysis (DFA) measures the complexity of a glucose time series obtained by means of a Continuous Glucose Monitoring System (CGMS) and has proven to be a sensitive marker of glucoregulatory dysfunction. Furthermore, some authors have observed a crossover point in the DFA, signalling a change of dynamics, arguably dependent on the beta-insular function. We investigate whether the characteristics of this crossover point have any influence on the risk of developing type 2 diabetes mellitus (T2DM). To this end we recruited 206 patients at increased risk of T2DM (because of obesity, essential hypertension, or a first-degree relative with T2DM). A CGMS time series was obtained, from which the DFA and the crossover point were calculated. Patients were then followed up every 6 months for a mean of 17.5 months, controlling for the appearance of T2DM diagnostic criteria. The time to crossover point was a significant predictor risk of developing T2DM, even after adjusting for other variables. The angle of the crossover was not predictive by itself but became significantly protective when the model also considered the crossover point. In summary, both a delay and a blunting of the crossover point predict the development of T2DM.

Protection of pancreatic β-cells against glucotoxicity by short-term treatment with GLP-1

Glucagon-like peptide-1 (GLP-1) reduces pancreatic β-cell apoptosis in type 2 diabetes. Glucotoxiciy is a main cause of β-cell apoptosis in type 2 diabetes. The aims of this study were to investigate the anti-apoptotic mechanisms of GLP-1 against glucotoxicity and whether physiological short-term treatment with GLP-1 can protect β-cells from glucotoxicity-induced apoptosis. GLP-1 treatment for only 30 min alleviated high glucose-induced β-cell apoptosis. The effect of GLP-1 was related with phosphoinositide 3-kinase (PI3K)/AKT-S473 phosphorylation. The increase in pAKT-S473 led to suppression of FoxO-1. GLP-1-induced AKT-S473 activation and FoxO-1 suppression were abolished by the selective inactivation of mTOR complex (mTORC) 2 using small interfering RNA directed towards the rapamycin-insensitive companion of mTOR. The protective effect of GLP-1 on β-cell apoptosis was also abolished by the selective inactivation of mTORC2. Hence, the protective effect of GLP-1 against glucotoxicity may be mediated by FoxO-1 suppression through the PI3K/mTORC2/AKT-S473 phosphorylation. This report provides evidence that short-term treatment with GLP-1 is beneficial to protect against glucotoxicity-induced β-cell apoptosis.

Glucose series complexity at the threshold of diabetes

BACKGROUND

One of the earliest signs of dysfunction in a complex system is the simplification of its output. A well-accepted method to measure this phenomenon is detrended fluctuation analysis (DFA). Herein, we evaluated the usefulness of DFA at the threshold of type 2 diabetes mellitus (T2DM).

METHODS

We report on the clinical and glucometric characteristics of a sample of 103 patients at increased risk of developing T2DM. All patients had HbA1c levels 5%-6.4% and met at least one of the following criteria: body mass index (BMI) > 30 kg/m2, essential hypertension or a first-degree relative with T2DM. For each patient, a 24-h glucose time series was obtained, and the clinical and glucometric variables were compared.

RESULTS

There was a significant correlation between the number of National Cholesterol Education Program--Adult Treatment Panel (ATP III) metabolic syndrome (MS)-defining criteria and DFA (ρ = 0.231, P = 0.019), and DFA differed significantly between patients meeting or not the ATP III definition of MS (1.443 vs. 1.399, respectively; P = 0.018). The DFA was not correlated with HbA1c. Depending on how it was calculated, the area under the log(Fn)∼log(n) curve correlated with HbA1c levels or the number of MS criteria. Conventional variability metrics (mean amplitude of glycemic excursions) did not differ between patients complying or not with the definition of MS.

CONCLUSIONS

Complexity analysis is capable of detecting differences in variables related to the risk of developing T2DM and could be a useful tool to study the initial phases of glucoregulatory dysfunction leading to T2DM.

Dynamical glucometry: use of multiscale entropy analysis in diabetes

Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.

Glucose series complexity in hypertensive patients

Nonlinear methods have been applied to the analysis of biological signals. Complexity analysis of glucose time series may be a useful tool for the study of the initial phases of glucoregulatory dysfunction. This observational, cross-sectional study was performed in patients with essential hypertension. Glucose complexity was measured with detrended fluctuation analysis (DFA), and glucose variability was measured by the mean amplitudes of glycemic excursion (MAGE). We included 91 patients with a mean age of 59 ± 10 years. We found significant correlations for the number of metabolic syndrome (MS)-defining criteria with DFA (r = 0.233, P = .026) and MAGE (r = 0.396, P < .0001). DFA differed significantly between patients who complied with MS and those who did not (1.44 vs. 1.39, P = .018). The MAGE (f = 5.3, P = .006), diastolic blood pressures (f = 4.1, P = .018), and homeostasis model assessment indices (f = 4.2, P = .018) differed between the DFA tertiles. Multivariate analysis revealed that the only independent determinants of the DFA values were MAGE (β coefficient = 0.002, 95% confidence interval: 0.001-0.004, P = .001) and abdominal circumference (β coefficient = 0.002, 95% confidence interval: 0.000015-0.004, P = .048). In our population, DFA was associated with MS and a number of MS criteria. Complexity analysis seemed to be capable of detecting differences in variables that are arguably related to the risk of the development of type 2 diabetes.

Melatonin prevents pancreatic β-cell loss due to glucotoxicity: the relationship between oxidative stress and endoplasmic reticulum stress

Prolonged hyperglycemia results in pancreatic β-cell dysfunction and apoptosis, referred to as glucotoxicity. Although both oxidative and endoplasmic reticulum (ER) stresses have been implicated as major causative mechanisms of β-cell glucotoxicity, the reciprocal importance between the two remains to be elucidated. The aim of this study was to evaluate the differential effect of oxidative stress and ER stress on β-cell glucotoxicity, by employing melatonin which has free radical-scavenging and antioxidant properties. As expected, in β-cells exposed to prolonged high glucose levels, cell viability and glucose-stimulated insulin secretion (GSIS) were significantly impaired. Melatonin treatment markedly attenuated cellular apoptosis by scavenging reactive oxygen species via its plasmalemmal receptor-independent increase in antioxidant enzyme activity. However, treatments with antioxidants alone were insufficient to recover the impaired GSIS. Interestingly, 4-phenylbutyric acid (4-PBA), a chemical chaperone that attenuate ER stress by stabilizing protein structure, alleviated the impaired GSIS, but not apoptosis, suggesting that glucotoxicity induces oxidative and ER stress independently. We found that cotreatment of glucotoxic β-cells with melatonin and 4-PBA dramatically improved both their survival and insulin secretion. Taken together, these results suggest that ER stress may be the more critical mechanism for prolonged high-glucose-induced GSIS impairment, whereas oxidative stress appears to be more critical for the impaired β-cell viability. Therefore, combinatorial therapy of melatonin with an ER stress modifier may help recover pancreatic β-cells under glucotoxic conditions in type 2 diabetes.

A Review of Theoretical Perspectives in Cognitive Science on the Presence of 1/f Scaling in Coordinated Physiological and Cognitive Processes

Time series of human performances present fluctuations around a mean value. These fluctuations are typically considered as insignificant, and attributable to random noise. Over recent decades, it became clear that temporal fluctuations possess interesting properties, however, one of which the property of fractal 1/f scaling. 1/f scaling indicates that a measured process extends over a wide range of timescales, suggesting an assembly over multiple scales simultaneously. This paper reviews neurological, physiological, and cognitive studies that corroborate the claim that 1/f scaling is most clearly present in healthy, well-coordinated activities. Prominent hypotheses about the origins of 1/f scaling are confronted with these reviewed studies. It is concluded that 1/f scaling in living systems appears to reflect their genuine complex nature, rather than constituting a coincidental side-effect. The consequences of fractal dynamics extending from the small spatial and temporal scales (e.g., neurons) to the larger scales of human behavior and cognition, are vast, and impact the way in which relevant research questions may be approached. Rather than focusing on specialized isolable subsystems, using additive linear methodologies, nonlinear dynamics, more elegantly so, imply a complex systems methodology, thereby exploiting, rather than rejecting, mathematical concepts that enable describing large sets of natural phenomena.

Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence

Hyperglycemia, hypoglycemia, preexisting diabetes, and glycemic variability each may affect hospital outcomes. Observational findings derived from randomized trials or retrospective studies suggest that independent of hypoglycemia and hyperglycemia, a relationship exists between variability and hospital outcomes. A review of studies conducted in diverse hospital populations is reported here, showing a relationship between measures of variability and nonglycemic outcomes, including ICU and hospital mortality and length of stay. "Glycemic variability" has an intuitive meaning, understood as a propensity of a single patient to develop repeated episodes of excursions of BG over a relatively short period of time that exceed the amplitude expected in normal physiology. It is proposed that each of 3 dimensions of variability should be separately studied: (1) magnitude of glycemic excursions during intervals of relative stability of the moving average of BG, (2) frequency with which a critical magnitude of excursion is exceeded, and (3) presence or absence of fine tuning. Multiple hospital studies have found that the standard deviation (SD) of the data set of blood glucose values (BG) of individual patients predicts outcomes. An appropriate refinement would be to report the "Reverse-transformed group mean of the SD of the logarithmically transformed BG data set of each patient," with confidence intervals. In logarithmic space, group means of the SD of BGs of each patient may be compared, using an appropriate parametric test. Upon reverse transformation, the upper and lower bounds of the confidence intervals become asymmetric about the reverse-transformed group mean of the SD. There is a need to understand what patterns of dispersion of BG over time are captured by SD as a predictor of outcomes. Among the causes of high SD, a subgroup may consist of patients having frequent oscillations of BG. Another subgroup may consist of patients experiencing a major change of overall glycemia during the timeframe of data collection. Appropriate metrics should be developed to recognize both variability in the sense of recurrent large oscillations of BG, and separately to recognize any time-dependent change of overall glycemia during hospitalization. Especially in relation to uncontrolled diabetes, there is a need to know whether rapid correction of chronic hyperglycemia adversely affects hospital outcomes. We have some understanding of how to control or prevent change of overall glycemia, and less understanding of how to control variability. Each may be associated with outcomes, and each may be detected by a high SD, but it remains uncertain whether intervention to prevent either pattern of changing glycemia would affect outcomes.

Characterization of detrended fluctuation analysis in the context of glycemic time series

There is a growing interest in the analysis of hyperglycemia and its relationship with other pathologies. The level of glucose in blood is regulated by the flux/reflux and controlled by hyperglycemia hormones and hypoglycemic insulin. Glycemic profiles are characterized by a nonlinear and nonstationary behavior but also influenced by circadian rhythms and patient daily routine which introduce quasi-periodic trends into them. This type of signals are commonly analyzed by Detrended Fluctuation Analysis (DFA) which states that the control system in charge of regulating the glucose level usually holds a long-range negative correlation. But there is an inconsistency about the windowing lengths, as no standard or rules are set. This work studies the influence of the windowing length sequence, and shows that there is a need for selecting the optimal values in order to obtain a good differentiation between different groups, and these values are somehow determined by signal characteristics.

Glucose exposure pattern determines glucagon-like peptide 1 receptor expression and signaling through endoplasmic reticulum stress in rat insulinoma cells

Repeated fluctuation in plasma glucose levels, as well as chronic hyperglycemia, is an important phenomenon frequently observed in diabetic patients. Recently, several studies have reported that glucose fluctuation, compared to chronic hyperglycemia, mediates more adverse effects due to induced oxidative and/or endoplasmic reticulum (ER) stress. In type 2 diabetes, stimulation of insulin secretion by glucagon-like peptide-1 (GLP-1) has been found to be reduced, and the results of recent studies have shown that the expression of the GLP-1 receptor (GLP-1R) is reduced by chronic hyperglycemia. However, GLP-1R signaling in glucose fluctuation has not been elucidated clearly. In this study, we hypothesized that intermittent high glucose (IHG) conditions also reduced GLP-1-mediated cellular signaling via reduction in GLP-1R expression. To evaluate this hypothesis, rat insulinoma cells (INS-1) were exposed for 72 h to either sustained high glucose (SHG) conditions (30 mM glucose) or IHG conditions (11 and 30 mM glucose, alternating every 12h). In comparison to both the SHG and control groups, IHG conditions induced a more significant impairment of insulin release and calcium influx in response to 1nM GLP-1 treatment. In addition, the activity of caspase 3/7 as well as the gene expression of binding protein (Bip) and C/EBP homologous protein (CHOP), molecular markers of ER stress, was significantly higher in IHG-treated cells than in SHG-treated cells. Interestingly, the expression level of GLP-1R was significantly lower under IHG conditions than under SHG conditions. Collectively, these findings indicated that glucose fluctuation reduces GLP-1R expression through ER stress more profoundly than sustained hyperglycemia, which may contribute to the diminished response of GLP-1.

Intermittent high glucose enhances apoptosis in INS-1 cells

To investigate the effect of intermittent high glucose (IHG) and sustained high glucose (SHG) on inducing β-cell apoptosis and the potential involved mechanisms, INS-1 beta cells were incubated for 72 h in the medium containing different glucose concentrations: control (5.5 mmol/L), SHG (33.3 mmol/L), and IHG (5.5 mmol/L and 33.3 mmol/L glucose alternating every 12 h). Cell viability, apoptosis rate, and oxidative-stress markers were determined. The results showed that the apoptosis induced by IHG was more obvious than that by SHG. Simultaneously, the intracellular level of oxidative stress was more significantly increased in INS-1 cells exposed to IHG. These findings suggest that intermittent high glucose could be more deleterious to β-cell than a constant high concentration of glucose, this may be due to the aggravation of oxidative stress triggered by intermittent high glucose.

Detrended fluctuation analysis is considered to be useful as a new indicator for short-term glucose complexity

BACKGROUND

This study clarified whether detrended fluctuation analysis (DFA) can evaluate how to advance the loss of complexity from impaired glucose tolerance (IGT) through mild diabetes mellitus (DM) to overt DM.

METHODS

Continuous glucose monitoring (CGM) was done during a 48-h interval for 59 subjects from multiple centers. Subjects were divided according to CGM data into those with impaired glucose tolerance (IGT) (n = 20), mild DM (n = 13), and overt DM (n = 26). The short-term (α1) and long-term (α2) range exponentials by DFA were compared among the three groups.

RESULTS

The value of α1 within 1h was significantly lower in the IGT group than in either of the other two groups (IGT vs. mild DM vs. overt DM, 1.53 ± 0.22 vs. 1.71 ± 0.17 vs. 1.77 ± 0.13, P<0.0001), and α1 within 2h differed significantly among the three groups (1.49 ± 0.13 vs. 1.57 ± 0.10 vs. 1.72 ± 0.10, P<0.0001). The α1 within 3h was significantly higher in overt DM than in either of the other two groups but did not change between IGT and mild DM (1.44 ± 0.12 vs. 1.52 ± 0.11 vs. 1.67 ± 0.09, P<0.0001). All short-term exponents decreased gradually but significantly as the window widened in all groups (P<0.0001). The α2 over 1h was significantly higher in overt DM but was unchanged in IGT and mild DM (1.22 ± 0.11 vs. 1.27 ± 0.12 vs. 1.36 ± 0.13, P = 0.0010). The α2 over 3h did not differ among the three groups.

CONCLUSIONS

Progressive loss of complexity in the glycemic profile occurred from the short-term range and spread to the long-term range concomitantly with the progression of the DM state.

Differences in complexity of glycemic profile in survivors and nonsurvivors in an intensive care unit: a pilot study

OBJECTIVE

To investigate glycemic dynamics and its relation with mortality in critically ill patients. We searched for differences in complexity of the glycemic profile between survivors and nonsurvivors in patients admitted to a multidisciplinary intensive care unit.

DESIGN

Prospective, observational study, convenience sample.

SETTINGS

Multidisciplinary intensive care unit of a teaching hospital in Madrid, Spain.

PATIENTS

A convenience sample of 42 patients, aged 29 to 86 yrs, admitted to an intensive care unit with an Acute Physiology and Chronic Health Evaluation II score of >or=14 and with an anticipated intensive care unit stay of >72 hrs.

INTERVENTIONS

A continuous glucose monitoring system was used to measure subcutaneous interstitial fluid glucose levels every 5 mins for 48 hrs during the first days of intensive care unit stay. A 24-hr period (n = 288 measurements) was used as time series for complexity analysis of the glycemic profile.

MEASUREMENTS

Complexity of the glycemic profile was evaluated by means of detrended fluctuation analysis. Other conventional measurements of variability (range, sd, and Mean Amplitude of Glycemic Excursions) were also calculated.

MAIN RESULTS

Ten patients died during their intensive care unit stay. Glycemic profile was significantly more complex (lower detrended fluctuation analysis) in survivors (mean detrended fluctuation analysis, 1.49; 95% confidence interval, 1.44-1.53) than in nonsurvivors (1.60; 95% confidence interval, 1.52-1.68). This difference persisted after accounting for the presence of diabetes. In a logistic regression model, the odds ratio for death was 2.18 for every 0.1 change in detrended fluctuation analysis.Age, gender, Simplified Acute Physiologic Score 3 or Acute Physiologic and Chronic Health Evaluation II scores failed to explain differences in survivorship. Conventional variability measurements did not differ between survivors and nonsurvivors.

CONCLUSIONS

Complexity of the glycemic profile of critically ill patients varies significantly between survivors and nonsurvivors. Loss of complexity in glycemia time series, evaluated by detrended fluctuation analysis, is associated with higher mortality.

Adiponectin reduces glucotoxicity-induced apoptosis of INS-1 rat insulin-secreting cells on a microfluidic chip

Diabetes mellitus is a metabolic disorder characterized by elevated blood sugar and progressive failure of insulin-producing beta-cells. Persistent hyperglycemia and blood sugar fluctuation are two general phenomena in diabetic patients, and both of them can result in an increased frequency of beta-cell apoptosis. Therefore, rescuing pancreatic beta-cells from glucotoxicity-induced beta-cell apoptosis is increasing viewed as a promising means for curing. The aim of this study was to investigate whether adiponectin, an important cytokine expressed in adipose tissue, has a potential for the application as the antiapoptotic strategy. INS-1 rat insulin-secreting cell line was used in this study as a model of pancreatic beta-cells, because INS-1 cells show the susceptibility to glucotoxicity, as seen in beta-cells. INS-1 cells were cultured on a novel microfluidic chip with persistent perfusion and subsequently exposed to sustained high glucose (SHG) (25 mmol/l) or intermittent high glucose (IHG) (11.1 and 25 mmol/l glucose alternating every 12 h) in the absence or presence of adiponectin for 72 h. Using this device, we showed that IHG induced more serious impairment in INS-1 cells than did SHG, and adiponectin partially rescued INS-1 cells from glucotoxicity-induced apoptosis, dysfunction and reduction of insulin gene expression. Simultaneously, the mRNA expression of AMP-activated protein kinase (AMPK), which is a signaling protein that acts to modulate glucose uptake in skeletal muscle, was restored in the presence of adiponectin. Based on the above evidence, we suggest that adiponectin could reduce glucotoxicity-induced apoptosis of beta-cells, at least in part, by transiently activating AMPK signaling pathway.

Involvement of chronic stresses in rat islet and INS-1 cell glucotoxicity induced by intermittent high glucose

In order to investigate the toxic effect of intermittent high glucose (IHG) and sustained high glucose (SHG) on rat pancreatic beta cell functions and the potential involved mechanisms, isolated rat islets and INS-1 beta cells were exposed to SHG (25 mmol/l) or IHG (11.1 and 25 mmol/l glucose alternating every 12 h) for 72 h. The results showed that IHG induced a more significant impairment of insulin release response in rat islets and INS-1 cell than SHG. Simultaneously, the intracellular levels of endoplasmic reticulum and oxidative stress were more markedly increased in islets and INS-1 cells exposed to IHG. However, there was no significant difference between reducing cell viability, insulin content and gene expression induced by SHG and IHG. Taken together, this study suggested the more serious toxic effect on rat pancreatic beta cell function induced by IHG treatment may be due to excessive activation of cellular stress.