The elucidation of the cause of Alzheimer’s disease remains one of the greatest questions in neurodegenerative research. The lack of highly reliable low-cost sensors to study the structural changes ...in key proteins during the progression of the disease is a contributing factor to this lack of insight. In the current work, we describe the rational design and synthesis of two fluorescent BODIPY-based probes, named Tau 1 and Tau 2. The probes were evaluated on the molecular surface formed by a fibril of the PHF6 (306VQIVYK311) tau fragment using molecular docking studies to provide a potential molecular model to rationalize the selectivity of the new probes as compared to a homologous Aβ-selective probe. The probes were synthesized in a few steps from commercially available starting products and could thus prove to be highly cost-effective. We demonstrated the excellent photophysical properties of the dyes, such as a large Stokes shift and emission in the near-infrared window of the electromagnetic spectrum. The probes demonstrated a high selectivity for self-assembled microtubule-associated protein tau (Tau protein), in both solution and cell-based experiments. Moreover, the administration to an acute murine model of tauopathy clearly revealed the staining of self-assembled hyperphosphorylated tau protein in pathologically relevant hippocampal brain regions. Tau 1 demonstrated efficient blood–brain barrier penetrability and demonstrated a clear selectivity for tau tangles over Aβ plaques, as well as the capacity for in vivo imaging in a transgenic mouse model. The current work could open up avenues for the cost-effective monitoring of the tau protein aggregation state in animal models as well as tissue staining. Furthermore, these fluorophores could serve as the basis for the development of clinically relevant sensors, for example based on PET imaging.
Metformin, a well known antidiabetic agent that improves peripheral insulin sensitivity, also elicits anti-inflammatory actions, but its mechanism is unclear. Here, we investigated the mechanism ...responsible for the anti-inflammatory effect of metformin action in lipopolysaccharide (LPS)-stimulated murine macrophages. Metformin inhibited LPS-induced production of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in a concentration-dependent manner and in parallel induction of activating transcription factor-3 (ATF-3), a transcription factor and member of the cAMP-responsive element-binding protein family. ATF-3 knockdown abolished the inhibitory effects of metformin on LPS-induced proinflammatory cytokine production accompanied with reversal of metformin-induced suppression of mitogen-activated protein kinase (MAPK) phosphorylation. Conversely, AMP-activated protein kinase (AMPK) phosphorylation and NF-κB suppression by metformin were unaffected by ATF-3 knockdown. ChIP-PCR analysis revealed that LPS-induced NF-κB enrichments on the promoters of IL-6 and TNF-α were replaced by ATF-3 upon metformin treatment. AMPK knockdown blunted all the effects of metformin (ATF-3 induction, proinflammatory cytokine inhibition, and MAPK inactivation), suggesting that AMPK activation by metformin is required for and precedes ATF-3 induction. Oral administration of metformin to either mice with LPS-induced endotoxemia or ob/ob mice lowered the plasma and tissue levels of TNF-α and IL-6 and increased ATF-3 expression in spleen and lungs. These results suggest that metformin exhibits anti-inflammatory action in macrophages at least in part via pathways involving AMPK activation and ATF-3 induction.
Alzheimer's disease (AD) is a neurodegenerative disorder associated with cognitive decline. Despite worldwide efforts to find a cure, no proper treatment has been developed yet, and the only ...effective countermeasure is to prevent the disease progression by early diagnosis. The reason why new drug candidates fail to show therapeutic effects in clinical studies may be due to misunderstanding the cause of AD. Regarding the cause of AD, the most widely known is the amyloid cascade hypothesis, in which the deposition of amyloid beta and hyperphosphorylated tau is the cause. However, many new hypotheses were suggested. Among them, based on preclinical and clinical evidence supporting a connection between AD and diabetes, insulin resistance has been pointed out as an important factor in the development of AD. Therefore, by reviewing the pathophysiological background of brain metabolic insufficiency and insulin insufficiency leading to AD pathology, we will discuss how can insulin resistance cause AD.
We investigated the association between the incidence of severe hypoglycemia and the risk of end-stage renal disease (ESRD) in patients with type 2 diabetes. Baseline and follow-up data for 988,333 ...participants with type 2 diabetes were retrieved from the National Health Insurance System database. The number of severe hypoglycemia episodes experienced from 2007 to 2009 was determined. The primary outcome was the development of ESRD after the baseline evaluation. Participants were followed from the baseline until death or December 31, 2016, during this period 14,545 participants (1.5%) developed ESRD. In the crude model, compared with those who experienced no severe hypoglycemia, the hazard ratios (95% confidential intervals) for developing ESRD were 4.96 (4.57-5.39), 6.84 (5.62-8.32), and 9.51 (7.14-12.66) in participants who experienced one, two, and three or more episodes of severe hypoglycemia, respectively. Further adjustment for various confounding factors attenuated the association between severe hypoglycemia and ESRD; the significance of the association between severe hypoglycemia and ESRD was maintained. Having three or more severe hypoglycemia episodes was associated with a nearly two-fold increased risk of developing ESRD. Prior episodes of severe hypoglycemia were associated with an increased risk of ESRD among Korean adults with type 2 diabetes.
The carbohydrate response element binding protein (ChREBP), a basic helix-loop-helix/leucine zipper transcription factor, plays a critical role in the control of lipogenesis in the liver. To identify ...the direct targets of ChREBP on a genome-wide scale and provide more insight into the mechanism by which ChREBP regulates glucose-responsive gene expression, we performed chromatin immunoprecipitation-sequencing and gene expression analysis. We identified 1153 ChREBP binding sites and 783 target genes using the chromatin from HepG2, a human hepatocellular carcinoma cell line. A motif search revealed a refined consensus sequence (CABGTG-nnCnG-nGnSTG) to better represent critical elements of a functional ChREBP binding sequence. Gene ontology analysis shows that ChREBP target genes are particularly associated with lipid, fatty acid and steroid metabolism. In addition, other functional gene clusters related to transport, development and cell motility are significantly enriched. Gene set enrichment analysis reveals that ChREBP target genes are highly correlated with genes regulated by high glucose, providing a functional relevance to the genome-wide binding study. Furthermore, we have demonstrated that ChREBP may function as a transcriptional repressor as well as an activator.
We investigated the association regarding severe hypoglycemia episodes with cardiovascular disease risk and all-cause mortality in patients with type 2 diabetes.
Baseline and follow-up data (n = ...1,568,097) from patients with type 2 diabetes were retrieved from the National Health Insurance System database (covering the entire Korean population). Type 2 diabetes, severe hypoglycemia, and major comorbidities were identified using International Classification of Diseases 10 codes and medication information. Individuals who were classified as type 2 diabetes in the year of 2009 were screened, and we counted severe hypoglycemia episodes from 2007 to 2009. The primary outcome was newly developed myocardial infarction (MI), stroke, heart failure, or all-cause mortality. Participants were followed from the baseline index date to the date of death or until December 31, 2015.
In total, 19,660 (1.2%) patients developed at least one severe hypoglycemia event during the period from 2007 to 2009. Mean follow-up was 5.7 years. After adjustment for confounding factors, the hazard ratio (HR) of MI significantly and sequentially increased: 0 vs. 1 episode, HR 1.56, 95% CI 1.46-1.64; 0 vs. 2 episodes, HR 1.86, 95% CI 1.61-2.15; 0 vs. 3 or more episodes, HR 1.86, 95% CI 1.48-2.35, P for trend < 0.001. Similar findings were noted regarding the relationship of severe hypoglycemia episodes with stroke, heart failure, and all-cause mortality. Risks for all outcomes were highest within 1 year from the index date and showed decreasing trends with follow-up. Sensitivity analyses of the data from the subgroup population and 797,544 subjects who received a national health examination did not change the significance of the main findings.
Among adult Korean patients with type 2 diabetes, a severe hypoglycemia episode is associated with increased risk for cardiovascular outcomes and all-cause mortality. Significant results from dose-response, temporal, and sensitivity analyses may suggest the possibility of direct causality between severe hypoglycemia and cardiovascular outcomes and mortality.
Background
A system that combines technology and web-based coaching can help treat chronic conditions such as diabetes. However, the effectiveness of apps in mobile health (mHealth) interventions is ...inconclusive and unclear due to heterogeneous interventions and varying follow-up durations. In addition, randomized controlled trial data are limited, and long-term follow-up is lacking, especially for apps integrated into electronic medical records.
Objective
We aimed to assess the effect of an electronic medical record–integrated mobile app for personalized diabetes self-care, focusing on the self-monitoring of blood glucose and lifestyle modifications, on glycemic control in patients with type 2 diabetes mellitus.
Methods
In a 26-week, 3-arm, randomized, controlled, open-label, parallel group trial, patients with type 2 diabetes mellitus and a hemoglobin A1c (HbA1c) level of ≥7.5% were recruited. The mHealth intervention consisted of self-monitoring of blood glucose with the automatic transfer of glucose, diet, and physical activity counseling data (iCareD system). Participants were randomly assigned to the following three groups: usual care (UC), mobile diabetes self-care (MC), and MC with personalized, bidirectional feedback from physicians (MPC). The primary outcome was the change in HbA1c levels at 26 weeks. In addition, diabetes-related self-efficacy, self-care activities, and satisfaction with the iCareD system were assessed after the intervention.
Results
A total of 269 participants were enrolled, and 234 patients (86.9%) remained in the study at 26 weeks. At 12 weeks after the intervention, the mean decline in HbA1c levels was significantly different among the 3 groups (UC vs MC vs MPC: −0.49% vs −0.86% vs −1.04%; P=.02). The HbA1c level decreased in all groups; however, it did not differ among groups after 26 weeks. In a subgroup analysis, HbA1c levels showed a statistically significant decrease after the intervention in the MPC group compared with the change in the UC or MC group, especially in patients aged <65 years (P=.02), patients with a diabetes duration of ≥10 years (P=.02), patients with a BMI of ≥25.0 kg/m2 (P=.004), patients with a C-peptide level of ≥0.6 ng/mL (P=.008), and patients who did not undergo treatment with insulin (P=.004) at 12 weeks. A total of 87.2% (137/157) of the participants were satisfied with the iCareD system.
Conclusions
The mHealth intervention for diabetes self-care showed short-term efficacy in glycemic control, and the effect decreased over time. The participants were comfortable with using the iCareD system and exhibited high adherence.
Trial Registration
Clinical Research Information Service, Republic of Korea KCT0004128; https://tinyurl.com/bdd6pa9m
Background
The primary aim of this study was to assess the utility of fasting plasma glucose (FPG) and HbA1c to identify diabetes by the 2‐hour plasma glucose (PG) criterion in the Korean population ...at high risk for diabetes.
Methods
A total of 1646 participants with a body mass index of ≥23 kg/m2 without having a history of diabetes were recruited in this study. The cut‐off values of FPG and HbA1c for detecting diabetes were identified using the Youden index using receiver operating characteristic (ROC) analysis. The gold standard for diabetes prediction was defined by the 2‐hour PG level of ≥200 mg/dL.
Results
The participants comprised 54.0% women, and the mean age of all participants was 55.0 ± 8.1 years. At baseline, FPG was 104.1 ± 14.2 mg/dL, the 2‐hour PG value was 162.9 ± 55.3 mg/dL, and HbA1c was 5.9% ± 0.5%. Four hundred and forty‐six subjects (27.1%) were diagnosed with diabetes and 976 subjects (59.3%) were determined to be at prediabetes. The area under the ROC curve (AUC) of FPG and HbA1c for diabetes were 0.776 and 0.802, while the AUC of FPG and HbA1c for prediabetes were 0.515 and 0.477. The optimal cut‐off value for diagnosing diabetes of FPG and HbA1c were 104.5 mg/dL (sensitivity 75.8%, specificity 67.5%) and 5.9% (sensitivity 80.6%, specificity 63.8%), respectively.
Conclusions
FPG of 104.5 mg/dL and HbA1c value of 5.9% (41 mmol/mol) can be used as an optimal screening value for diabetes by 2‐hour PG criterion in the Korean population at high risk for diabetes.
This study investigated the association between severe hypoglycemia (SH) and new onset atrial fibrillation (AF) and all-cause mortality in adult patients with type 2 diabetes mellitus (T2DM).
...Retrospective data on patients with T2DM aged between 30 and 75years who received healthcare checkups from January 1, 2005 to December 31, 2008 were analyzed using the National Health Insurance Database in Korea. The primary outcome was newly diagnosed non-valvular AF occurring after SH episode using ICD-10 codes.
Among 1,509,280 subjects, 10,864 (0.72%) patients had experienced SH events in the three years prior to health examination, and a total of 48,916 (3.24%) first-time AF episodes occurred during the follow-up period of 8.5years. The incidence of AF was significantly higher in the group with SH than the group without SH. After multivariable adjustment, previous SH was a significant risk factor for the development of AF (HR 1.10, 95% CI 1.01–1.19). All-cause mortality was also significantly increased in patients with previous SH events and prior SH with subsequent AF occurrence, compared to patients without SH events.
Prior SH events were associated with a higher risk of new onset AF and all-cause mortality in patients with T2DM.
Previous studies suggest that dipeptidyl peptidase-4 (DPP-4) inhibitors and sodium glucose cotransporter 2 (SGLT2) inhibitors have different effects on the lipid profile in patients with type 2 ...diabetes. We investigated the effects of DPP-4 inhibitors and SGLT2 inhibitors on the lipid profile in patients with type 2 diabetes.
From January 2013 to December 2015, a total of 228 patients with type 2 diabetes who were receiving a DPP-4 inhibitor or SGLT2 inhibitor as add-on therapy to metformin and/or a sulfonylurea were consecutively enrolled. We compared the effects of DPP-4 inhibitors and SGLT2 inhibitors on the lipid profile at baseline and after 24 weeks of treatment. To compare lipid parameters between the two groups, we used the analysis of covariance (ANCOVA).
A total of 184 patients completed follow-up (mean age: 53.1 ± 6.9 years, mean duration of diabetes: 7.1 ± 5.7 years). From baseline to 24 weeks, HDL-cholesterol (HDL-C) levels were increased by 0.5 (95% CI, -0.9 to 2.0) mg/dl with a DPP-4 inhibitor and by 5.1 (95% CI, 3.0 to 7.1) mg/dl with an SGLT2 inhibitor (p = 0.001). LDL-cholesterol (LDL-C) levels were reduced by 8.4 (95% CI, -14.0 to -2.8) mg/dl with a DPP-4 inhibitor, but increased by 1.3 (95% CI, -5.1 to 7.6) mg/dl with an SGLT2 inhibitor (p = 0.046). There was no significant difference in the mean hemoglobin A1c (8.3 ± 1.1 vs. 8.0 ± 0.9%, p = 0.110) and in the change of total cholesterol (TC) (p = 0.836), triglyceride (TG) (p = 0.867), apolipoprotein A (p = 0.726), apolipoprotein B (p = 0.660), and lipoprotein (a) (p = 0.991) between the DPP-4 inhibitor and the SGLT2 inhibitor.
The SGLT2 inhibitor was associated with a significant increase in HDL-C and LDL-C after 24 weeks of SGLT2 inhibitor treatment in patients with type 2 diabetes compared with those with DPP-4 inhibitor treatment in this study.
This study was conducted by retrospective medical record review.
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