ASSESSMENT OF INCRETINS IN ORAL GLUCOSE AND LIPID TOLERANCE
TESTS MAY BE INDICATIVE IN THE DIAGNOSIS OF METABOLIC
SYNDROME AGGRAVATION

Metabolic syndrome (MS), leading to diabetes mellitus type 2 (T2DM) is nowadays one of the most common disorders. That is why so many studies have been introduced about its pathomechanism, modern prophylactic, diagnostic and therapeutic algorithms to stop the progression (1-3).

The incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) have many different properties - from the appetite control to the regulation of the visceral sensivity in lower bowel (4). The support of incretins activity has been one of the promising physiological tools against T2DM development (5-7). Their most important effect - the activation of insulin secretion by pancreatic b cells, was described to be tightly dependent on the presence of meal in gut lumen (8, 9). Thus the incretin axis activation depending on the degree of metabolic disorders (by metabolically healthy but obese patients, in metabolic syndrome and in patients with already developed T2DM) was compared in many clinical studies (10-12).

Besides the potent insulinotropic effect, GIP also exerts glucagonotropic and adipogenic effects (13). In vitro and the animal studies revealed that this hormone modify lipid metabolism and promote triglyceride (lipid droplets) deposition, not only in adipose tissue (disappearing proinflammatory free fatty acids from circulation), but also in the muscles and liver (unwanted effect promoting nonalcoholic fatty liver disease (NAFLD) (14).

Obesity is characterized by the chronic low-grade inflammation resulting from activation of macrophages and immune cells (Th-1) and overproduction of pro-inflammatory cytokines (MPC-1, interleukin-8, TNF-α endothelial injury (free radicals, selectins, integrins) markers which contribute to cardiovascular complications of diabetes (15, 16). Recent observation on human adipocytes revealed, that GIP induces prolipolytic as well as proinflammatory response activating the protein kinase A - nuclear factor-κB - interleukin-1 (PKA - NF-κB - IL-1) pathway signaling and impairs insulin sensitivity (17). Moreover, inhibition of GIP signaling protects against diet-induced obesity and insulin resistance (18, 19). Thus GIP appears to be important modulator of lipid metabolism and its complications.

Since the obesity-associated low grade inflammation of adipose tissue is related to insulin resistance, the several known markers of such process including macrophage chemotactic protein (MPC1), endothelial injury (sE-selectin), leptin/adipokin ratio (20) and the others such as visfatin which may serve as a marker of the degree of inflammation and related disease activity were measured during the functional tests: OGTT and OLTT to follow which will be more indicative for progress of MS complications.

The aim of the study was to compare the release of incretins at fasting and postprandial period induced by functional oral glucose as well as lipid load with the early inflammation and endothelial injury markers level in healthy controls and patients with MS.

MATERIALS AND METHODS

Patients

This Project was approved by the local Bioethical Committee. Participants were elected from patients of Out-patients Clinics: the Clinic of Endocrinology UJ CM and the Clinic of Obesity and Lipid Disorder Treatment at the Department of Biochemistry UJ CM in Cracow.

Among 50 participants with MS selected in accordance to IDF criteria (1), there were 22 women and 28 men aged from 25 to 73 years (53.39 ± 11.86), with BMI above 30 kg/m2. The T1DM and T2DM or pharmacologic treatment of glucose tolerance disorders or dyslipidemia were factors disqualifying from attendance in this study. Also volunteers with diseases that could affect the metabolism of glucose and lipids (pregnancy, thyroid disease, kidney disease, and other chronic diseases etc.) were excluded.

The control group (C) consisted of 20 healthy volunteers with a BMI in the range of 19 to 26.9 kg/m2, adjusted in terms of age and gender to the MS group. Finally, only 18 people from group C completed the study protocol (11 women and 7 men) aged from 28 to 62 years (43.5 ±11.53).

The percentage of the fat tissue in the body was measured by bioimpedance (Maltron Body Fat Analyzer BF-905). All patients enrolled into this study were asked to follow an isocaloric diet with low amount of antioxidative vitamins, polyunsaturated fatty acids and alcohol for 2 weeks. The diet instructions have been presented to each patient by dietician.

After two weeks of the diet standardization, venous blood samples were drawn after a 12 hours of overnight fasting for analysis of basal value of plasma total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides, glutathione peroxidase activity, interleukin-6, soluble adhesion molecules E-selectin (sE-selectin), monocyte chemoattractant protein 1 (MCP-1), leptin, adiponectin and visfatin.

Functional oral tests and biochemical measurements

Participants underwent a 3-hour oral glucose tolerance test (WHO 1999) - OGTT (75 g glucose) (21) and (with a two-week distance period) an 8-hour oral lipid tolerance test - OLTT (modification of the Couderc R. study (22)), which contained 80 g of fat (75%), made up of 50% saturated, 40% monounsaturated and 10% polyunsaturated fatty acids. The composition of standard meal of OLTT is shown in Table 1.

Table 1. The composition of standard meal in OLTT.

*SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids.

Every 30 minutes of OGTT and every 2 hours of OLTT venous blood was sampled in accordance to the assay indications and blood concentration of incretins (GLP-1, GIP), glucose, insulin, triglycerides (TG) and free fatty acids (FFA) was measured. Plasma active forms of GLP-1 (7-36; 7-37 amide) and GIP (1-42; 3-42 amide) were estimated by highly specific immunoenzymetric assay (ELISA), Millipore Corporation, USA kits. For determination of GLP-1 serum level, the blood sample was collected to a special tube charged BDTMP700 comprising an inhibitor of the enzyme DPP-4. Immediately after sampling the contents of the tube was gently mixed 8 – 10 times and transported on ice to the laboratory in time 5 – 10 minutes. After centrifugation in a refrigerated centrifuge (4°C, for 10 minutes at 1000 ×g) serum was stored at –70°C until analysis begins (no more than 1 month). To determine GIP serum level, the blood samples were collected into the kit attached tubes with chemically inert clotting activator and catabolism prevention chemicals. After centrifugation, serum samples were stored at –70°C for no longer than one month before measurement.

Serum insulin was determined by immunoradioassay (IRMA). Glucose and lipid profile (total cholesterol, TG, HDL) were analyzed using standard laboratory biochemistry methods. LDL cholesterol concentration was calculated with Friedewald’s formula (23). Determination of FFA plasma concentration was performed using optimized enzymatic colorimetric method using a commercial kit from Roche. For assays, the fresh, not frozen serum samples were used. If necessary, the material was stored at +4°C for no longer than 7 days. Reading of the absorbance was performed on a microplate reader Multiskan RS from Lab-Systems at a wavelength of 540 nm. The linearity of this method is observed to a concentration of FFA - 1.5 mmol/l. Reference FFA value are in the range of 0.3 to 0.8 mmol/l was indicated.

Basing on the OGTT data, homeostasis model assessment of insulin resistance (HOMA-IR: (fasting serum insulin × fasting plasma glucose) / 22.5) (24) was calculated. In the first blood sample taken in the fasting state, the standard lipidogram (levels of total cholesterol and fractions of HDL, LDL) as well as concentrations of selected adipokines (leptin - IRMA; adiponectin and visfatin - Human Assay, Invitrogen, ELISA kits) were measured.

Incretins release in both tests was calculated as the area under curve - AUC. To compare differences between GIP and GLP-1 release dependent on meal load (the glucose-rich (OGTT) versus lipid-rich (OLTT)) for MS and C groups, the AUC was calculated with regard to various length of tests: AUC/3 hours in OGTT and AUC/8 hours in OLTT.

The high sensitivity quantitative sandwich immunoassay technique was used for determination of interleukin-6 plasma levels (Human IL-6 Quantikine HS ELISA, R&D Systems Europe, Ltd.). Intra-assay and inter-assay variability coefficients were 6% and 7% respectively. Plasma concentration of sE-Selectin was determined by quantitative ELISA (Human sE-Selectin/CD62E Quantikine ELISA, R&D Systems Europe, Ltd) with sensitivity 0.010 ng/ml. Intra-assay and inter-assay variability coefficients was 6% and 8% respectively. Plasma concentration of macrophage chemotaxic protein (MCP-1) was determined by quantitative ELISA (Human CCL2/ MCP1 Quantikine ELISA, R&D Systems Europe, Ltd) with sensitivity 1.7 pg/ml. Intra-assay and inter-assay variability coefficients was 5% and 6% respectively.

Activity of glutathione peroxidase (GPx) was determined according to Paglia & Valentines method. The decrease in NADPH absorbance measured at 340 nm during the oxidation of NADPH to NADP+ is indicative of GPx activity (25).

Statistical analysis

Statistical analysis was performed by the computer program STATISTICA 10 PL. The characteristics of the population was prepared using descriptive statistics. Quantitative data are presented as the arithmetic mean and standard deviation (S.D.), minimum and maximum. For qualitative data numbers and percentages for each category were calculated. To assess the normality of quantitative variables the Shapiro-Wilk test was used, and to verify the homogeneity of variance Levene’s test was used. To compare the two groups (e.g. to determine the differences between men and women, a group of MS and C) the Student’s t-test was used, or in the event of failure of assumptions (normality, homogeneity of variance) equivalent non-parametric Mann-Whitney test was used. To assess the relationship between collected variables Spearman’s rank correlation coefficient was used (because the variables were not normally distributed). To find interesting factors affecting the dependent variable (e.g. the impact of glucose or FFA secretion of incretins) multiple regression analysis was used. The significance of the relationship between qualitative variables were analyzed by chi - square Pearson. In all analyzes a P value less than 0.05 was considered significant.

RESULTS

The characteristics of both analyzed groups are given in Table 2.

Table 2. Characteristics of the participants with metabolic syndrome (n = 50) and the control group (n = 18).

The data were presented by the use of arithmetic mean ± standard deviation (S.D.) or as a number of people (n) and percentage (%). Statistically significant differences: metabolic syndrome versus control P value < 0.05 (*); P < 0.01 (**); P < 0.001 (***). The Student’s t-test or in the event of failure of assumptions (normality, homogeneity of variance) equivalent non-parametric Mann-Whitney test was used.
AUC, area under curve; BMI, body mass index; BP, blood pressure; C, control; F, female; FA, free fatty acids; Glc, glucose; HOMA, homeostasis model assessment; Ins, insulin; M, male; MS, metabolic syndrome; OGTT, oral glucose tolerance test; OLTT, oral lipid tolerance test; TG, triglycerides; WHR, waist-hip ratio.

At fasting and during OGTT the glucose level was significantly higher in the MS patients (P < 0.001, P < 0.005). OLTT did not induce an increase of glucose, which documented the accurate lipid test selection. As expected, in the MS group a significantly higher amount of glucose and insulin (AUC) was observed than in the C group (P < 0.001) during OGTT, while during OLTT in the MS group essentially higher values of AUC-FFA (P < 0.05) and AUC-TG (P < 0.001) were noted (Table 2). The fasting insulin level was twice as high in patients with MS (P < 0.001). The output of insulin (AUC) during both tests (OGTT and OLTT) was over twice as high in MS patients. In OLTT the insulin level was lower than the amount of insulin released during OGTT, but still higher in MS than in control patients. In the MS group statistically significantly higher levels of TG and FFA during the whole test - OGTT and OLTT were observed (P < 0.005, P < 0.001). In the whole group of participants, the relation between the concentration of incretins with examined insulin resistance markers (HOMA-IR) and fasting FFA was confirmed (8, 19).

The fasting incretin concentrations did not differ between MS and C groups. At most measured time-points of both tests the release of GLP-1 tended to be lower in patients with MS (without statistical significance) (Fig. 1). In OLTT the release of GIP also was slightly lower in patients with MS, though this difference did not reach statistical significance (Fig. 2). No gender-dependent differences in incretins secretion in subgroups MS and C were found.

Fig. 1. GLP-1 concentration progress during tolerance tests with respect to group - metabolic syndrome (MS) versus control (C) group.

Fig. 2. GIP concentration progress during tolerance tests with respect to group - metabolic syndrome (MS) versus control (C) group.

Significant differences in incretin secretion dependent on the used test (the carbohydrate-rich (OGTT) versus lipid-rich (OLTT) load) were observed within the same group (Table 3). A significantly larger AUC-GIP after the lipid-rich meal over the carbohydrate meal was observed, while statistically bigger value of AUC-GLP1 was noticed in OGTT than in OLTT (P < 0.001) within each of the investigated groups (Table 3). These data also point that carbohydrates are a stronger activator of GLP-1 secretion, in turn lipids are a stronger activator of GIP release.

Table 3. Mean incretin secretion over 1 hour, by lasting tolerance tests (OGTT – 3 h, OLTT – 8 h) separately in MS and C groups.

The data were presented as (AUC - GIP) area under curve of marker GIP concentration in 1 hour during oral tests, (AUC - GLP1) area under curve of marker GLP1 concentration in 1 hour during both oral tolerance tests. Statistically significant differences: OGTT versus OLTT, P value < 0.05 (*); P < 0.01 (**); P < 0.001(***) non-parametric Mann-Whitney test.
AUC, area under curve; C, control; MS, metabolic syndrome; OGTT, oral glucose tolerance test; OLTT, oral lipid tolerance test.

The FFA concentration during both tests was higher in patients with MS. The fasting values and those at the 30th, 60th, 90th and 120th minute of OGTT and fasting, and at the 2nd and 4th hour OLTT differed significantly. As expected (26), in both groups during OGTT the blood FFA concentration transiently decreased, while during OLTT the FFA blood concentration was long lasting increased. The time of the release of both incretins after OLTT took 2.5 times longer than after OGTT (3 versus 8 hours) (Fig. 1 and 2). After fatty food the maximal point of GIP output was after 2 hours of OLTT and was twice as high as in OGTT (Fig. 2, Table 3).

A lower concentration of GLP-1 in the case of higher fasting concentrations of FFA in the whole group of patients, as well as in MS and C subgroups was observed. Additionally, negative correlation between postprandial concentrations of GLP-1 and FFA in group C (R = –0.532, P = 0.016) and a positive correlation between GLP-1 and TG in the MS group (R = 0.622, P = 0.009) was observed.

Following significant correlations at individual time points of both functional tests were noticed: positive correlation between GIP and glucose level in OGTT at minute 0, 30 and 180 (in all participants and the MS group), and at minute 0 and 180 in males and 30 in women with MS (P = 0.003 – 0.047). Accordingly, the significance of a negative correlation between GLP-1 and glucose in OGTT was observed in the whole group of participants at time-point 0 and the 180th minute, in males with MS at time-point 0 and the 30th minute, and in women of the C group at the 180th minute of the test (P = 0.022 – 0.037).

There was no significant correlation between GIP concentration and FFA at individual time points during OLTT. However, a negative correlation between GLP-1 and FFA in OLTT in the C group achieved significance at the 8th hour (P = 0.011), and in women of the C group at the 6th and 8th hour of the OLTT test.

To check which was a stronger modulator of incretins secretion - carbohydrates or lipids, regression analysis was used. A statistically significant dependence of AUC-GIP and AUC-FFA was obtained in MS and C group (P = 0.035). There was no statistical significance for GLP-1.

Irrespective of the classification (MS, C, or gender), in the whole group of participants a positive correlation between fasting GIP and BMI (R Spearman = 0.277, P = 0.031), and a negative correlation between fasting GLP-1 and BMI (R = –0.566, P = 0.009), as well as the quantitative amount of adipose tissue (R = –0.507, P = 0.022) were observed.

Considering gender, a positive correlation between fasting GIP level and WHR was noticed (R = 0.430, P = 0.046 in males of MS group, and R = 0.943, P = 0.005 in C group).

No significant correlation between fasting GIP and GLP-1 vs fasting concentrations of measured adipokines: leptin and adiponectin was found. However, a positive correlation between the concentration of visfatin and GIP output (AUC-GIP) during the functional tests in the whole group (R = 0.359, P = 0.016 in OGTT; R = 0.386, P = 0.009 in OLTT), as well as in MS (R = 0.445; P = 0.006) and men with MS (R = 0.604; P = 0.022) was noticed.

For further calculations all subjects participating in this study were divided into three groups according to fasting plasma GIP levels. The significant cut off points between tertiles were: 19.44 pg/ml and 33.76 pg/ml. In this case patients with the highest fasting plasma GIP concentrations (3rd tertile) had the significantly increased sE-selectin and MCP-1 blood levels and the tendency of higher visfatin and IL-6 levels (Fig. 3). There was also a positive correlation between fasting GIP and inflammatory/endothelial injury markers: sE-selectin, MCP-1, visfatin and leptin/adiponectin ratio (20). Also postprandial GIP response (OLTT AUC) correlated with visfatin, and GIP response to glucose challenge (OGTT AUC) correlated with sE-selectin. The negative correlation between GIP OLTT AUC and glutathione peroxidase the free radical generation marker was also found (Table 4).

 

Fig. 3.Plasma levels of inflammatory markers MCP-1 (a), sE-Selectin (b), IL-6 (c) and visfatin (d) in three groups of subjects according to fasting plasma GIP tertiles.
Data presented as mean +S.D.; * P < 0.05, one-way ANOVA with Tukey’s post hoc test.
MCP-1, monocyte chemoattractant protein-1.

Table 4. The Pearson correlation coefficients (r) of fasting GIP plasma level, GIP response to OLTT, GIP response to OGTT with indicated inflammatory markers in all subjects, *P < 0.05 Pearson test.

OLTT AUC - area under curve of marker concentration during oral lipid tolerance test; OGTT AUC, area under curve of marker concentration during oral glucose tolerance test; MCP-1, monocyte chemoattractant protein-1.

DISCUSSION

In our study we have not observed any significant differences in the level of incretins at fasting state as well as between the used functional tests in healthy volunteers (group C) comparing with patients with early stage of MS. A significant relationship between basal GIP release and glucose concentration was found in the whole group and in the subgroups of males with MS and C (8, 14). The amount of released incretins may be dependent on the stage of metabolic disturbance, since the other authors assessing the incretins concentration in patients with diabetes mellitus reported that GIP level can be equal, or elevated in comparison to healthy people (27), while the concentration of GLP-1 decreases (28). Similarly, however a not significant tendency was observed in this study. Such differences were more evident in the postprandial period. The influence of pregnane X receptor activation on postprandial incretin secretion is suggested (29), but it requires further study. Additionally, as the others (14, 30) we also have seen that depending on the used functional test, carbohydrates were the main activator of GLP-1 release, whereas lipids mainly activated postprandial GIP secretion. Of the note is fact that the net amount of released during OLTT incretins, expressed as the AUC, was significantly higher and output was longer lasting in comparison with that measured during OGTT. It can be seen that the difference (2.5 times) in incretin response may come from more than 3-times higher energy load of OLTT, but when we compared mean incretin secretion over 1 hour of both tests separately, we found significant differences. A significantly larger AUC-GIP after the lipid-rich meal over the carbohydrate meal was observed, while statistically bigger value of AUC-GLP1 was noticed in OGTT than in OLTT (P < 0.001) within each of the investigated groups (Table 3). It argues for the statement that fat reach meal is the power activator of the long lasting release of incretin, mainly GIP.

Moreover the time differences in the incretins release during the postprandial period (much longer after lipids) may be explained by the dependence of the direct contact of fat with intestine mucosa (time of food passage) (31, 32). Also several authors reported that the main stimulators of GIP secretion in humans are lipids (14, 30, 33). The much higher GIP output after fatty food might indicate that GIP plays an important role in the maintaining of insulin output after dense, high lipid food intake. It has been demonstrated that long-chain (but not short-chain) monounsaturated fatty acids have a stronger influence on GIP secretion than saturated fatty acids (34, 35). This points at a connection between GIP release and the amount and composition of FFA in diet.

The results of our studies suggest a weaker stimulatory effect of FFA on GLP-1 release between meals. The negative correlations between postprandial concentrations of GLP-1 and FFA in group C may also argue for a weaker lipid-dependent release of GLP-1 in this period. Knowledge concerning the GLP-1 and especially GIP activity is still growing (33, 36, 37). Among the various components of the meal, fat is the strongest stimulus of GIP release (38). GIP binds to the G-protein-coupled receptor (GIPR) on β-cells, increases intracellular cAMP levels resulting in stimulation of insulin secretion, suppression of apoptosis and increase of β-cell proliferation (39). Incretins output is negatively connected with the increase of examined insulin resistance markers: HOMA-IR, fasting insulin and fasting FFA concentration (8, 19, 24, and our results).

Besides the potent insulinotropic effect, GIP also exerts glucagonotropic and adipogenic effects (40). Animal and in vitro studies indicate, that this hormone modifies lipid metabolism and promotes fat deposition, not only in adipose tissue, but also in the muscles and liver (14). Administration of this hormone to the animals induced development of fatty liver and other obesity-related metabolic disorders (41). Human studies revealed, that patients with nonalcoholic fatty liver disease (NAFLD) exhibited a prolonged GIP elevation after fat ingestion (33, 42). Genetic ablation of GIPR resulted in prevention of fat deposition and higher energy expenditure in mice on high fat diet (18). Thus, GIP appears to be important modulator of lipid tissue accumulation (lipotoxicity, lipid droplet formation) metabolism per se. In hyperglycemia and hyperinsulinemia state, GIP accelerated removing of the postprandial TG and FFA from circulation (18, 41, 42). Thus GIP activity helps in normalization of the blood metabolic substrates level in postprandial period promoting lipid accumulation in tissues (18, 41, 43).

The most of published data indicate, that the incretin effect is reduced in obesity and diabetes type 2 (T2DM) due to impaired incretin hormone secretion and/or to a defective insulinotropic action (43). In obesity and T2DM the circulating level of GIP appears to be frequently elevated (44, 45). Moreover, it is suggested, that adipocytes remain sensitive to GIP effects while the insulinotropic activity of GIP is blunted (33). Experiments on human adipocytes showed, that GIP induces prolipolytic as well as proinflammatory response activating the PKA - NF-κB - IL-1 pathway signaling what impairs insulin sensitivity (17). Moreover, inhibition of GIP signaling protected against diet-induced obesity and insulin resistance (18, 19). However, these results are in contradiction with the other findings (46) what may be explained by the species-related differences.

Obesity, in particular excess of visceral adiposity, is associated with low grade inflammatory state and increased oxidative stress (47). Since GIP is postulated to be stimulator of adipogenesis, it simultaneously may play a role as a factor modulating the inflammatory process (17, 45). We explored the relationship between GIP levels and selected plasma inflammatory parameters. In the present study obese patients with the highest plasma GIP levels (the highest tertile of GIP fasting concentration) showed an increased blood concentration of the chemotactic MCP-1, and endothelial injury marker (sE-selectin; leptin/adiponectin ratio), which is an independent predictor of intima media thickness (20), as well as interleukin-6 and visfatin, considered as a proinflammatory adipokine (48). We also observed positive correlation between fasting and postprandial GIP levels and visfatin, sE-selectin, MCP-1. Also a negative correlation between postprandial GIP and glutathione peroxidase activity (the marker of the free radical generation typical for inflammation) was observed. It has been documented that genetic predisposition of GIP triggers the inflammatory state. Carriers of GIPR rs 10423928 A-allele revealed lower adipose tissue osteopontin mRNA levels, better insulin sensitivity, thus suggested protective properties due to reduced GIP expression (49). In another experimental study chronic GIP treatment induced an inflammatory and prolipolytic response due to activation of the PKA - NF-κB - IL1β pathway. In the same study the expression of interleukin-6, interleukin-1β and interleukin-1 were up-regulated, whereas tumor necrosis factor-α, interleukin-8 and MCP-1 level remained unchanged (17).

However in this study, any significant correlation between fasting GIP and GLP-1 versus fasting concentrations of measured adipokines - leptin and adiponectin was found, the leptin to adipocyte ratio, the marker of vessel wall injury (20), correlated with fasting GIP level. This data is consistent with suggestion that leptin to adiponectin ratio is predictor for cardiac syndrome X appearance (50).

Our results argue for the dietary lipids to be the longer-lasting incretinotropic food component than glucose and oral lipids are more efficient the GIP, when glucose the GLP-1 release stimulators. We have not observed the differences between control group and patients with metabolic syndrome in fasting and the postprandial blood incretin content. Consistently with the observed ‘proinflammatory’ effect of GIP. The possibility of the use of postprandial (OLTT) GIP release measurements for the low grade inflammation progress in patients with metabolic syndrome is suggested.

Acknowledgements: This work was supported by the State Department of Education - MNiI Grant (K/ZDS/000619 grant), European Nutrigenomic Organization - NuGO Exchange Grant and EU FW7 BIOCLAIMS, Grant agreement no. 244995.

Conflict of interests: None declared.

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