Browsing by Author "Milicic, Tanja (24073432600)"

Background: Previous studies suggested an important role of impairments in T cell subsets in different stages during type 1 diabetes (T1D) development, while data regarding CD25high T cells and transforming growth factor β1 (TGFβ1), both T regulatory associated, remains controversial. We analyzed the level of (a) CD25high T cells (b) TGFβ1 in 17 first-degree relatives of patients with T1D in stage 1 (FDRs1) (GADA+, IA-2+); 34 FDRs in stage 0 (FDRs0) (GADA-, IA-2-); 24 recent-onset T1D in insulin-requiring state (IRS); 10 patients in clinical remission (CR); 18 healthy, unrelated controls (CTR). Methods: T cell subsets were characterized by two-color immunofluorescence staining and flow cytometry; TGFβ1 was determined by ELISA, GADA, and IA-2 by RIA. Results: The percentage of CD25high T cells in FDRs1 was lower than controls, FDRs0, IRS, and CR (p<0.001). Additionally, the cut-off value for CD25high = 1.19%, with a probability of 0.667, for having a higher risk for T1D. TGFβ1 concentration in FDRs1, FDRs0, IRS, and CR, was lower than controls (p<0.001). IRS has a higher TGFβ1 concentration than CR (p<0.001). Conclusions: Stage 1, a higher risk for T1D, is characterized by decreases in CD25high T cells and TGFβ1, partially reflecting impaired T regulatory response, implying that changes of this T cells subset might be a risk marker for T1D. FDRs, irrespective of risk for T1D and T1D patients irrespective of state, had depletion of TGFβ1, suggesting the association of TGFβ1 could have potential with familiar risk and manifestation of T1D. Furthermore, the result suggested that the clinical course of overt T1D might be modulated on the TGFβ1 level. © 2024 Society of Medical Biochemists of Serbia. All rights reserved.

Background: Previous studies suggested an important role of impairments in T cell subsets in different stages during type 1 diabetes (T1D) development, while data regarding CD25high T cells and transforming growth factor β1 (TGFβ1), both T regulatory associated, remains controversial. We analyzed the level of (a) CD25high T cells (b) TGFβ1 in 17 first-degree relatives of patients with T1D in stage 1 (FDRs1) (GADA+, IA-2+); 34 FDRs in stage 0 (FDRs0) (GADA-, IA-2-); 24 recent-onset T1D in insulin-requiring state (IRS); 10 patients in clinical remission (CR); 18 healthy, unrelated controls (CTR). Methods: T cell subsets were characterized by two-color immunofluorescence staining and flow cytometry; TGFβ1 was determined by ELISA, GADA, and IA-2 by RIA. Results: The percentage of CD25high T cells in FDRs1 was lower than controls, FDRs0, IRS, and CR (p<0.001). Additionally, the cut-off value for CD25high = 1.19%, with a probability of 0.667, for having a higher risk for T1D. TGFβ1 concentration in FDRs1, FDRs0, IRS, and CR, was lower than controls (p<0.001). IRS has a higher TGFβ1 concentration than CR (p<0.001). Conclusions: Stage 1, a higher risk for T1D, is characterized by decreases in CD25high T cells and TGFβ1, partially reflecting impaired T regulatory response, implying that changes of this T cells subset might be a risk marker for T1D. FDRs, irrespective of risk for T1D and T1D patients irrespective of state, had depletion of TGFβ1, suggesting the association of TGFβ1 could have potential with familiar risk and manifestation of T1D. Furthermore, the result suggested that the clinical course of overt T1D might be modulated on the TGFβ1 level. © 2024 Society of Medical Biochemists of Serbia. All rights reserved.

Objective: Artificial intelligence-based decision support systems (DSS) need to provide decisions that are not inferior to those given by experts in the field. Recommended insulin dose adjustments on the same individual data set were compared among multinational physicians, and with recommendations made by automated Endo-Digital DSS (ED-DSS). Research Design and Methods: This was a noninterventional study surveying 20 physicians from multinational academic centers. The survey included 17 data cases of individuals with type 1 diabetes who are treated with multiple daily insulin injections. Participating physicians were asked to recommend insulin dose adjustments based on glucose and insulin data. Insulin dose adjustments recommendations were compared among physicians and with the automated ED-DSS. The primary endpoints were the percentage of comparison points for which there was agreement on the trend of insulin dose adjustments. Results: The proportion of agreement and disagreement in the direction of insulin dose adjustment among physicians was statistically noninferior to the proportion of agreement and disagreement observed between ED-DSS and physicians for basal rate, carbohydrate-to insulin ratio, and correction factor (P < 0.001 and P ≤ 0.004 for all three parameters for agreement and disagreement, respectively). The ED-DSS magnitude of insulin dose change was consistently lower than that proposed by the physicians. Conclusions: Recommendations for insulin dose adjustments made by automatization did not differ significantly from recommendations given by expert physicians regarding the direction of change. These results highlight the potential utilization of ED-DSS as a useful clinical tool to manage insulin titration and dose adjustments. © Copyright 2022, Mary Ann Liebert, Inc.

Objective: Artificial intelligence-based decision support systems (DSS) need to provide decisions that are not inferior to those given by experts in the field. Recommended insulin dose adjustments on the same individual data set were compared among multinational physicians, and with recommendations made by automated Endo-Digital DSS (ED-DSS). Research Design and Methods: This was a noninterventional study surveying 20 physicians from multinational academic centers. The survey included 17 data cases of individuals with type 1 diabetes who are treated with multiple daily insulin injections. Participating physicians were asked to recommend insulin dose adjustments based on glucose and insulin data. Insulin dose adjustments recommendations were compared among physicians and with the automated ED-DSS. The primary endpoints were the percentage of comparison points for which there was agreement on the trend of insulin dose adjustments. Results: The proportion of agreement and disagreement in the direction of insulin dose adjustment among physicians was statistically noninferior to the proportion of agreement and disagreement observed between ED-DSS and physicians for basal rate, carbohydrate-to insulin ratio, and correction factor (P < 0.001 and P ≤ 0.004 for all three parameters for agreement and disagreement, respectively). The ED-DSS magnitude of insulin dose change was consistently lower than that proposed by the physicians. Conclusions: Recommendations for insulin dose adjustments made by automatization did not differ significantly from recommendations given by expert physicians regarding the direction of change. These results highlight the potential utilization of ED-DSS as a useful clinical tool to manage insulin titration and dose adjustments. © Copyright 2022, Mary Ann Liebert, Inc.

Introduction: We evaluated the effectiveness of long-term continuous subcutaneous insulin infusion (CSII) compared with multiple daily insulin (MDI) injections for glycaemic control and variability, hypoglycaemic episodes and maternal/neonatal outcomes in pregnant women with pre-existing type 1 diabetes (pT1D). Methods: Our observational cohort study included 128 consecutive pregnant women with pT1D, who were treated from 1 January 2010 to 31 December 2017. Of 128 participants, 48 were on CSII and 80 were on MDI. Glycaemic control was determined by glycated haemoglobin (HbA1c) (captured in preconception and each trimester of pregnancy). Glucose variability (GV) was expressed as the coefficient of variation (CV) [calculated from self-monitoring of blood glucose (SMBG) values], and hypoglycaemia was defined as glucose values < 3.9 mmol/l. The data on maternal and neonatal outcomes were collected from obstetrical records. Results: Duration of the treatment was 8.8 ± 5.3 years in the CSII and 12.6 ± 8.0 years in the MDI group. The CSII lowered HbA1c in preconception (7.1 ± 0.1 vs. 7.9 ± 0.2%, p = 0.03) and the first (6.9 ± 0.1 vs. 7.7 ± 0.2%, p = 0.02), second (6.6 ± 0.1 vs. 7.2 ± 0.1%, p = 0.003) and third (6.5 ± 0.1 vs. 6.8 ± 0.1%, p = 0.02) trimesters significantly better than MDI. Significantly lower CV was observed only for fasting glycaemia in the first trimester (17.1 vs 28.4%, p < 0.001) in favour of CSII. Moreover, the CSII group had significantly lower mean hypoglycaemic episodes/week/patient only during the first trimester (2.0 ± 1.7 vs 4.8 ± 1.5, p < 0.01). In early pregnancy, the majority of women on CSII had less hypoglycaemia than on MDI (0–3: 79.1 vs. 29.1%; 4–6: 18.8 vs. 65.8%; ≥ 7: 2.1 vs. 5.1%, p < 0.01, respectively). We found no difference in the incidence of adverse maternal/neonatal outcomes. Conclusions: Treatment with CSII resulted in a favourable reduction of HbA1c in the preconception period and each trimester in pregnancy. Moreover, long-term CSII treatment demonstrated more stable metabolic control with less GV of fasting glycaemia and fewer hypoglyacemic episodes only during early pregnancy. © 2020, The Author(s).

We analyzed the level of (a) CXCR3+ (Th1) and CCR4+ (Th2) T memory cells (b) interferon-γ inducible chemokine (IP-10)(Th1) and thymus and activation-regulated chemokine (TARC)(Th2), in 51 first degree relatives (FDRs) of type 1 diabetics (T1D) (17 high risk FDRs (GADA+, IA-2+) and 34 low risk FDRs (GADA-, IA-2-)), 24 recent-onset T1D (R-T1D), and 18 healthy subjects. T memory subsets were analyzed by using four-color immunofluorescence staining and flowcytometry. IP-10 and TARC were determined by ELISA. High risk FDRs showed higher levels of CXCR3+ and lower level of CCR4+ T memory cells compared to low risk FDRs (64.98 ± 5.19 versus 42.13 ± 11.11; 29.46 ± 2.83 versus 41.90 ± 8.58%, resp., P < 0.001). Simultaneously, both IP-10 and TARC levels were increased in high risk versus low risk FDRs (160.12 ± 73.40 versus 105.39 ± 71.30; 438.83 ± 120.62 versus 312.04 ± 151.14 pg/mL, P < 0.05). Binary logistic regression analysis identified the level of CXCR3+ T memory cells as predictors for high risk FDRs, together with high levels of IP-10. The results imply that, in FDRs, the risk for T1D might be strongly influenced by enhanced activity of Th1 and diminished activity of Th2 autoimmune response. © 2014 Tanja Milicic et al.

We analyzed the level of (a) CXCR3+ (Th1) and CCR4+ (Th2) T memory cells (b) interferon-γ inducible chemokine (IP-10)(Th1) and thymus and activation-regulated chemokine (TARC)(Th2), in 51 first degree relatives (FDRs) of type 1 diabetics (T1D) (17 high risk FDRs (GADA+, IA-2+) and 34 low risk FDRs (GADA-, IA-2-)), 24 recent-onset T1D (R-T1D), and 18 healthy subjects. T memory subsets were analyzed by using four-color immunofluorescence staining and flowcytometry. IP-10 and TARC were determined by ELISA. High risk FDRs showed higher levels of CXCR3+ and lower level of CCR4+ T memory cells compared to low risk FDRs (64.98 ± 5.19 versus 42.13 ± 11.11; 29.46 ± 2.83 versus 41.90 ± 8.58%, resp., P < 0.001). Simultaneously, both IP-10 and TARC levels were increased in high risk versus low risk FDRs (160.12 ± 73.40 versus 105.39 ± 71.30; 438.83 ± 120.62 versus 312.04 ± 151.14 pg/mL, P < 0.05). Binary logistic regression analysis identified the level of CXCR3+ T memory cells as predictors for high risk FDRs, together with high levels of IP-10. The results imply that, in FDRs, the risk for T1D might be strongly influenced by enhanced activity of Th1 and diminished activity of Th2 autoimmune response. © 2014 Tanja Milicic et al.

Background: The growing body of evidence suggests that atherosclerosis risk factors are important in cognitive decline. Objective: To analyse insulin sensitivity, insulin secretion capacity, plasma insulin, adiponectin and lipid levels in normoglycaemic, nonobese patients with Alzheimer’s disease (AD) (group A, n=62), mild cognitive impairment (MCI) (group B, n=41), and healthy controls (group C, n=25). Method: Insulin sensitivity was determined by euglycemic hyperinsulinaemic clamp (M value) and homeostasis model assessment (HOMA-IR), insulin secretion capacity by first-phase insulin response (FPIR), plasma insulin by RIA, adiponectin by ELISA, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides by enzymatic method. Results: Insulin sensitivity was the lowest in group A (M value: A: 6.2±2.5; B:7.7±2.7; C:8.2±1.5 mg/min/kg, p<0.001; HOMA-IR: A: 4.6±2.2; B: 3.3±1.7; C: 1.5±1.0, p<0.001) as well as FPIR (A:68.9±27.8; B:112.5±47.1; C:147.4±56.0 mU/l, p<0.001). Plasma insulin was higher in group A vs B vs C, while adiponectin was lower in group A vs B vs C. Simultaneously, total and LDL-C were higher and HDL-C levels were lower in groups A and B vs C, with no difference between groups A and B. Triglycerides did not differ between the groups. Binary logistic regression analysis identified only M value, FPIR and plasma insulin as independent predictors of AD and MCI. Conclusion: These results imply that in AD and MCI insulin resistance with increased plasma insulin and decreased FPIR may be associated with the development of AD and MCI, accompanied with milder influence of low adiponectin levels and atherogenic lipid profile. © 2017 Bentham Science Publishers.

Background: The growing body of evidence suggests that atherosclerosis risk factors are important in cognitive decline. Objective: To analyse insulin sensitivity, insulin secretion capacity, plasma insulin, adiponectin and lipid levels in normoglycaemic, nonobese patients with Alzheimer’s disease (AD) (group A, n=62), mild cognitive impairment (MCI) (group B, n=41), and healthy controls (group C, n=25). Method: Insulin sensitivity was determined by euglycemic hyperinsulinaemic clamp (M value) and homeostasis model assessment (HOMA-IR), insulin secretion capacity by first-phase insulin response (FPIR), plasma insulin by RIA, adiponectin by ELISA, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides by enzymatic method. Results: Insulin sensitivity was the lowest in group A (M value: A: 6.2±2.5; B:7.7±2.7; C:8.2±1.5 mg/min/kg, p<0.001; HOMA-IR: A: 4.6±2.2; B: 3.3±1.7; C: 1.5±1.0, p<0.001) as well as FPIR (A:68.9±27.8; B:112.5±47.1; C:147.4±56.0 mU/l, p<0.001). Plasma insulin was higher in group A vs B vs C, while adiponectin was lower in group A vs B vs C. Simultaneously, total and LDL-C were higher and HDL-C levels were lower in groups A and B vs C, with no difference between groups A and B. Triglycerides did not differ between the groups. Binary logistic regression analysis identified only M value, FPIR and plasma insulin as independent predictors of AD and MCI. Conclusion: These results imply that in AD and MCI insulin resistance with increased plasma insulin and decreased FPIR may be associated with the development of AD and MCI, accompanied with milder influence of low adiponectin levels and atherogenic lipid profile. © 2017 Bentham Science Publishers.

Background/Objectives: Previous studies reported impairments in insulin secretion during different stages of type 1 diabetes (T1D), while data regarding insulin sensitivity and immunological changes are still controversial. We analyzed the following: (a) insulin secretion, (b) insulin sensitivity, and (c) pro-inflammatory interleukin-17 (IL-17) levels in peripheral blood in 17 healthy first-degree relatives in stage 1 (FDRs1) (GAD+, IA2+), 34 FDRs in stage 0 (FDRs0) (GAD−, IA2A−), 24 recent-onset T1D (R-T1D) patients in the insulin-requiring state (IRS), 10 in clinical remission (CR), and 18 healthy unrelated controls (HC). Methods: Insulin secretion was evaluated by an IVGTT and a glucagon stimulation test, expressed as a first-phase insulin response (FPIR) and a basal/stimulated C-peptide. Insulin sensitivity was tested by the euglycemic hyperinsulinemic clamp, expressed as an M value. Results: FDRs1 had a lower FPIR than FDRs0 (p < 0.05) and HC (p < 0.001) but higher than RT1D-IRS (p < 0.001) and RT1D-CR (p < 0.01). Moreover, FDRs1 had lower basal/stimulated C-peptide than FDRs0 (p < 0.01/p < 0.05) and HC (p < 0.001/p = 0.001) but higher levels than RT1D-IRS (p < 0.001/p < 0.001). However, the M value was similar among FDRs1, FDRs0, and HC (p = 1.0) but higher than RT1D-IRS (p < 0.001) and RT1D-CR (p < 0.01), while RT1D-IRS and RT1D-CR had lower M than HC (p < 0.001; p < 0.001; respectively). FDRs1 had higher IL-17 than FDRs0 (p < 0.001) and HC (p < 0.05). RT1D-IRS had higher IL-17 than FDRs0 (p < 0.001) and HC (p < 0.001), which was similar to RT1D-CR vs. FDRs0 (p < 0.001) and HC (p < 0.05). Conclusions: Early changes in pre-T1D might involve an initial decline of insulin secretion associated with a pro-inflammatory attack, which does not influence insulin sensitivity, whereas later, insulin sensitivity deterioration seems to be associated with the prominent reduction in insulin secretion. © 2025 by the authors.

The aim of this study was to examine the differences in pregnancy complications, delivery characteristics, and neonatal outcomes between women with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM). This study included all pregnant women with diabetes in pregnancy in Belgrade, Serbia, between 2010 and 2020. The total sample consisted of 6737 patients. In total, 1318 (19.6%) patients had T1DM, 138 (2.0%) had T2DM, and 5281 patients (78.4%) had GDM. Multivariate logistic regression with the type of diabetes as an outcome variable showed that patients with T1DM had a lower likelihood of vaginal delivery (OR: 0.73, 95% CI: 0.64–0.83), gestational hypertension (OR: 0.47, 95% CI: 0.36–0.62), higher likelihood of chronic hypertension (OR: 1.88, 95% CI: 1.55–2.29),and a higher likelihood ofgestational age at delivery before 37 weeks (OR: 1.38, 95% CI: 1.18–1.63) compared to women with GDM. Multivariate logistic regression showed that patients with T2DM had a lower likelihood ofgestational hypertension compared to women with GDM (OR: 0.37, 95% CI: 0.15–0.92).Our results indicate that the highest percentage of diabetes in pregnancy is GDM, and the existence of differences in pregnancy complications, childbirth characteristics, and neonatal outcomes are predominantly between women with GDM and women with T1DM. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

The aim of this study was to examine the differences in pregnancy complications, delivery characteristics, and neonatal outcomes between women with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM). This study included all pregnant women with diabetes in pregnancy in Belgrade, Serbia, between 2010 and 2020. The total sample consisted of 6737 patients. In total, 1318 (19.6%) patients had T1DM, 138 (2.0%) had T2DM, and 5281 patients (78.4%) had GDM. Multivariate logistic regression with the type of diabetes as an outcome variable showed that patients with T1DM had a lower likelihood of vaginal delivery (OR: 0.73, 95% CI: 0.64–0.83), gestational hypertension (OR: 0.47, 95% CI: 0.36–0.62), higher likelihood of chronic hypertension (OR: 1.88, 95% CI: 1.55–2.29),and a higher likelihood ofgestational age at delivery before 37 weeks (OR: 1.38, 95% CI: 1.18–1.63) compared to women with GDM. Multivariate logistic regression showed that patients with T2DM had a lower likelihood ofgestational hypertension compared to women with GDM (OR: 0.37, 95% CI: 0.15–0.92).Our results indicate that the highest percentage of diabetes in pregnancy is GDM, and the existence of differences in pregnancy complications, childbirth characteristics, and neonatal outcomes are predominantly between women with GDM and women with T1DM. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Introduction. Managing non-communicable diseases (NCDs) requires redesigning health care delivery to achieve better coordination of services at all levels of health care. The aim of this study was improving prevention and strengthening high quality of care for NCDs by using type 2 diabetes as a model disease. Methods. The mix method approach served to analyse the impact of the intervention processes. Source of information were routine health statistics, interviews and observation. Key Performance Indicators in defined Improvement Areas assisted in the quality of diabetes care assessment. Results and discussion. During the study the National Diabetes Centre (NDC) was established. The NDC experts organized numerous educational events, 316 physicians and nurses have participated. New electronic data base was implemented in 20 pilot Primary Health Care Centres (PHCCs) with 38,833 electronic diabetes records. Conclusions. The intervention led to establishment of the NDC, strengthening competences of health care professionals and to the renewal of the Diabetes Care Units in PHCCs included in the study. © 2021 Istituto Superiore di Sanita. All rights reserved.

Objectives: Aiming to show that periodontitis (PD) and type 2 diabetes (T2D) are bidirectionally related and potentially linked by inflammatory cytokines, we searched for association between −308 G/A Tumor necrosis factor-alpha (TNFα), +252A/G Lymphotoxin-alpha (LTα), +36A/G Tumor necrosis factor receptor 1 (TNFR1) and +676 T/G tumor necrosis factor receptor 2 (TNFR2) single nucleotide polymorphisms (SNPs) and: risk of PD or PD + T2D; periodontitis parameters in PD and PD + T2D; serum levels of cytokines/their receptors. Relationship between periodontal inflammation and serum cytokine/receptor levels was also assessed. Design: Subjects were stratified as: 57 healthy controls (HC); 58 PD; 65 PD + T2D. Sociodemographic, environmental, behavioral and periodontal clinical data were recorded. SNPs were genotyped using polymerase chain reaction-restriction fragment length polymorphism, while cytokines/receptors levels were quantified by enzyme-linked immunosorbent assay. Impact of periodontal inflammation was measured using periodontal inflamed surface area (PISA). Results: TNFα AA genotype showed protective effect in T2D + PD compared to PD, even adjusted for behavioral/environmental factors (OR 0.18; 95 %CI 0.037−0.886; p = 0.035). LTα AG heterozygotes had increased risk of PD (OR 3.27; 95 %CI 1.35−7.96; p = 0.016), while TNFR2 TG genotype had protective effect (OR = 0.44; 95 %CI 0.954−0.9794; p = 0.043). TNFR1 AA was predictor of periodontal pocket depth and clinical attachment loss in PD. Correlation between TNFR2 concentration and PISA was negative in PD, positive in PD + T2D. Conclusions: None of the SNPs showed cross-susceptibility between PD and T2D. + 252A/G LTα and +676 T/G TNFR2 SNPs are associated with PD risk. Periodontal destruction in healthy individuals is influenced by TNFR1 genotype. Impact of periodontal on systemic inflammation is masked by T2D. © 2020 Elsevier Ltd

Objectives: Aiming to show that periodontitis (PD) and type 2 diabetes (T2D) are bidirectionally related and potentially linked by inflammatory cytokines, we searched for association between −308 G/A Tumor necrosis factor-alpha (TNFα), +252A/G Lymphotoxin-alpha (LTα), +36A/G Tumor necrosis factor receptor 1 (TNFR1) and +676 T/G tumor necrosis factor receptor 2 (TNFR2) single nucleotide polymorphisms (SNPs) and: risk of PD or PD + T2D; periodontitis parameters in PD and PD + T2D; serum levels of cytokines/their receptors. Relationship between periodontal inflammation and serum cytokine/receptor levels was also assessed. Design: Subjects were stratified as: 57 healthy controls (HC); 58 PD; 65 PD + T2D. Sociodemographic, environmental, behavioral and periodontal clinical data were recorded. SNPs were genotyped using polymerase chain reaction-restriction fragment length polymorphism, while cytokines/receptors levels were quantified by enzyme-linked immunosorbent assay. Impact of periodontal inflammation was measured using periodontal inflamed surface area (PISA). Results: TNFα AA genotype showed protective effect in T2D + PD compared to PD, even adjusted for behavioral/environmental factors (OR 0.18; 95 %CI 0.037−0.886; p = 0.035). LTα AG heterozygotes had increased risk of PD (OR 3.27; 95 %CI 1.35−7.96; p = 0.016), while TNFR2 TG genotype had protective effect (OR = 0.44; 95 %CI 0.954−0.9794; p = 0.043). TNFR1 AA was predictor of periodontal pocket depth and clinical attachment loss in PD. Correlation between TNFR2 concentration and PISA was negative in PD, positive in PD + T2D. Conclusions: None of the SNPs showed cross-susceptibility between PD and T2D. + 252A/G LTα and +676 T/G TNFR2 SNPs are associated with PD risk. Periodontal destruction in healthy individuals is influenced by TNFR1 genotype. Impact of periodontal on systemic inflammation is masked by T2D. © 2020 Elsevier Ltd

The aim of this study was to analyze the trends in diabetes in pregnancy in Belgrade, Serbia for the period of the past decade and forecast the number of women with pre-gestational diabetes for the years 2030 and 2050. The study included the data on all pregnant women with diabetes from the registry of the deliveries in Belgrade, by the City Institute of Public Health of Belgrade, Serbia for the period between 2010 and 2020 and the published data on the deliveries on the territory of Belgrade. During the examined period the total number of live births in Belgrade was 196,987, and the prevalence of diabetes in pregnancy was 3.4%, with the total prevalence of pre-gestational diabetes of 0.7% and overall prevalence of GDM of 2.7%. The average age of women in our study was significantly lower in 2010 compared to 2020. The forecasted prevalence of pre-gestational diabetes among all pregnant women for 2030 is 2% and 4% for 2050 in our cohort. Our study showed that the prevalence of pre-gestational diabetes has increased both among all pregnant women and among women with diabetes in pregnancy in the past decade in Belgrade, Serbia and that it is expected to increase further in the next decades and to further double by 2050. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

The aim of this study was to analyze the trends in diabetes in pregnancy in Belgrade, Serbia for the period of the past decade and forecast the number of women with pre-gestational diabetes for the years 2030 and 2050. The study included the data on all pregnant women with diabetes from the registry of the deliveries in Belgrade, by the City Institute of Public Health of Belgrade, Serbia for the period between 2010 and 2020 and the published data on the deliveries on the territory of Belgrade. During the examined period the total number of live births in Belgrade was 196,987, and the prevalence of diabetes in pregnancy was 3.4%, with the total prevalence of pre-gestational diabetes of 0.7% and overall prevalence of GDM of 2.7%. The average age of women in our study was significantly lower in 2010 compared to 2020. The forecasted prevalence of pre-gestational diabetes among all pregnant women for 2030 is 2% and 4% for 2050 in our cohort. Our study showed that the prevalence of pre-gestational diabetes has increased both among all pregnant women and among women with diabetes in pregnancy in the past decade in Belgrade, Serbia and that it is expected to increase further in the next decades and to further double by 2050. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

We analyzed (a) insulin sensitivity (IS) and (b) glutathione peroxidase (GSH-Px), glutathione reductase (GR), and superoxide dismutase (SOD) antioxidant enzyme activity in type 2 diabetic (T2D) patients with atherothrombotic infarction (ATI) (group A), lacunar infarction (LI) (B), or without stroke (C) and in nondiabetics with ATI (D), LI (E), or without stroke (F). ATI and LI were confirmed by brain imaging IS levels were determined by minimal model (Si index), and the enzyme activity by spectrophotometry. In T2D patients, Si was lower in A and B versus C (1.14 ± 0.58, 1.00 ± 0.26 versus 3.14 ± 0.62 min-1/mU/l × 104, P < 0.001) and in nondiabetics in D and E versus F (3.38 ± 0.77, 3.03 ± 0.72 versus 6.03 ± 1.69 min-1/mU/l × 104, P < 0.001). Also, GSH-Px and GR activities were lower in A and B versus C (GSH-Px: 21.96 ± 3.56, 22.51 ± 1.23 versus 25.12 ± 1.67; GR: 44.37 ± 3.58, 43.50 ± 2.39 versus 48.58 ± 3.67 U/gHb; P < 0.001) and in D and E versus F (GSH-Px: 24.75 ± 3.02, 25.57 ± 1.92 versus 28.56 ± 3.91; GR: 48.27 ± 6.81, 49.17 ± 6.24 versus 53.67 ± 3.96 U/gHb; P < 0.001). Decreases in Si and GR were significantly related to both ATI and LI in T2D. Our results showed that decreased IS and impaired antioxidant enzymes activity influence ischemic stroke subtypes in T2D. The influence of insulin resistance might be exerted on the level of glutathione-dependent antioxidant enzymes. © 2013 Aleksandra Jotic et al.

We analyzed (a) insulin sensitivity (IS) and (b) glutathione peroxidase (GSH-Px), glutathione reductase (GR), and superoxide dismutase (SOD) antioxidant enzyme activity in type 2 diabetic (T2D) patients with atherothrombotic infarction (ATI) (group A), lacunar infarction (LI) (B), or without stroke (C) and in nondiabetics with ATI (D), LI (E), or without stroke (F). ATI and LI were confirmed by brain imaging IS levels were determined by minimal model (Si index), and the enzyme activity by spectrophotometry. In T2D patients, Si was lower in A and B versus C (1.14 ± 0.58, 1.00 ± 0.26 versus 3.14 ± 0.62 min-1/mU/l × 104, P < 0.001) and in nondiabetics in D and E versus F (3.38 ± 0.77, 3.03 ± 0.72 versus 6.03 ± 1.69 min-1/mU/l × 104, P < 0.001). Also, GSH-Px and GR activities were lower in A and B versus C (GSH-Px: 21.96 ± 3.56, 22.51 ± 1.23 versus 25.12 ± 1.67; GR: 44.37 ± 3.58, 43.50 ± 2.39 versus 48.58 ± 3.67 U/gHb; P < 0.001) and in D and E versus F (GSH-Px: 24.75 ± 3.02, 25.57 ± 1.92 versus 28.56 ± 3.91; GR: 48.27 ± 6.81, 49.17 ± 6.24 versus 53.67 ± 3.96 U/gHb; P < 0.001). Decreases in Si and GR were significantly related to both ATI and LI in T2D. Our results showed that decreased IS and impaired antioxidant enzymes activity influence ischemic stroke subtypes in T2D. The influence of insulin resistance might be exerted on the level of glutathione-dependent antioxidant enzymes. © 2013 Aleksandra Jotic et al.