bluuebunny/crossref_metadata_2025_split huggingface dataset:
Luseogliflozin Inhibits HIF-1α Expression in Renal Proximal Tubular Epithelial Cells
Authors: BESSHO RYOICHI , TAKIYAMA YUMI , OTA TSUGUHITO 
Published: June 2018

Recent clinical trials have demonstrated the renoprotective effects of SGLT2 inhibitors in diabetic nephropathy (DN). However, the mechanisms of SGLT2 inhibitors on prevention of DN have not been fully elucidated. Hypoxia-induced tubulointerstitial fibrosis is considered to be a common pathway for various progressive kidney diseases including DN. Hypoxia inducible factor (HIF)-1α plays an important role in these pathological processes. In this study, we assessed the effects of luseogliflozin, an SGLT2 inhibitor, on HIF-1α expression in both cultured human renal proximal tubular epithelial cells (HRPTECs) and kidney of diabetic mice. Hypoxia (1%O2 for 24h) markedly increased HIF-1α protein in HRPTEC, whereas luseogliflozin inhibited expression of hypoxia-induced HIF-1α protein. In addition, luseogliflozin inhibited mRNA expression for HIF-1α-targeted genes, PAI-1, VEGF and GLUT-1 under hypoxia. The inhibitors of mitochondrial respiratory complex I, rotenone or complex III, antimycin A equally suppressed hypoxia-induced HIF-1α expression. We next treated db/db mice with 15 mg/kg/day luseogliflozin for 8 weeks. Luseogliflozin administration lowered plasma glucose levels and decreased glomerular mesangial matrix expansion as well as glomerular and interstitial fibronectin accumulation in db/db mice. Electron microscopic study revealed that luseogliflozin attenuated the thickening of glomerular basement membrane in db/db mice. Intriguingly, luseogliflozin decreased the length of mitochondria in the renal proximal tubules of the S1 segment. Furthermore, luseogliflozin attenuated diabetes-induced HIF-1α accumulation in the kidney of db/db mice. These results suggest that luseogliflozin inhibits hypoxia-induced HIF-1α accumulation at least partly by suppressing mitochondrial respiration. SGLT2 inhibitors may protect diabetic kidney from hypoxia-induced renal fibrosis by attenuating the expression of HIF-1α and profibrotic molecules.

Disclosure
R. Bessho: None. Y. Takiyama: None. T. Ota: None.
Insulin Degludec/Insulin Aspart (IDegAsp) Twice Daily (BID) vs. Biphasic Insulin Aspart 30 (BIAsp 30) BID—A Randomized Trial in Chinese Patients with Type 2 Diabetes
Authors: YANG WENYING , MA JIANHUA , HONG TIANPEI , LIU MING , MIAO HENG , PENG YONGDE , WANG CHANGJIANG , XU XIANGJIN , YANG TAO , NIELSEN ANNE MOELLER , PAN LILI , LIU WEIHONG , WEIGANG ZHAO 
Published: June 2018

IDegAsp is the first coformulation of long-acting basal (degludec) and bolus (IAsp) insulin with no need for re-suspension. This 26-week, phase 3, open-label, treat-to-target, 2:1, randomized trial assessed the efficacy and safety of IDegAsp BID vs. BIAsp 30 BID ±metformin in Chinese adults (N=541) with T2D inadequately controlled on pre-/self-mix or basal insulin ±metformin (NCT02762578). Hierarchical testing was used with non-inferiority of A1C change from baseline to week 26 as the primary endpoint and superiority for secondary endpoints. Non-inferiority of A1C change from baseline to week 26 and statistical superiority of IDegAsp BID vs. BIAsp 30 BID for change in fasting plasma glucose, nocturnal (00:01-05:59 hours inclusive) confirmed hypoglycemic and confirmed hypoglycemic episodes (severe or plasma glucose &lt;56mg/dL with or without symptoms) was confirmed (Table). Significantly more patients reached A1C &lt;7% without confirmed hypoglycemia with IDegAsp BID vs. BIAsp 30 BID by week 26. Daily insulin dose (U/kg [SD]) was lower in patients receiving IDegAsp BID vs. BIAsp 30 BID at week 26 (0.78 [0.35] vs. 0.95 [0.35]). No new safety signals were identified. These results demonstrate the efficacy and safety of IDegAsp in Chinese patients with T2D, confirming results from other international trials comparing the two treatment modalities (NCT02762578).

Disclosure
W. Yang: None. J. Ma: None. T. Hong: Advisory Panel; Self; Novo Nordisk A/S, AstraZeneca. M. Liu: None. H. Miao: None. Y. Peng: None. C. Wang: None. X. Xu: None. T. Yang: None. A. Moeller Nielsen: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. L. Pan: Employee; Self; Novo Nordisk (China). W. Liu: Employee; Self; Novo Nordisk (China). Z. Weigang: None.
MiniMed™ Veo™ Insulin Pump Analysis for Real-World Nonadjunctive CGM Insights
Authors: JIANG BOYI , SOLEYMANI SADAF , VIGERSKY ROBERT , SULLIVAN ASHLEY , ZHONG YUXIANG , AGRAWAL PRATIK , KAUFMAN FRANCINE R. 
Published: June 2018

To assess glycemic outcomes during non-adjunctive use of a Medtronic continuous glucose monitoring system, CareLink™ personal software data were analyzed after insulin bolus delivery to correct hyperglycemia.
Voluntarily uploaded data captured between January 1, 2015-August 12, 2016, from European users of the MiniMed™ Veo™ insulin pump with SmartGuard™ technology, were de-identified and analyzed. Non-adjunctive sensor glucose (SG) values were defined as manually-entered self-monitored blood glucose (SMBG) values that were within ±5mg/dL of the preceding SG value. Non-adjunct vs. adjunct performance of the system in frequent non-adjunct users (at least, 10% non-adjunct use) was evaluated based on the frequency of post-corrective bolus hypoglycemia (nadir) and hyperglycemia (peak) over the 4 hours following insulin bolus delivery. All statistics were conducted per patient and analyzed using Wilcoxon signed rank test.
Among 23,784 total users, 5,851 were identified as frequent non-adjunct users. Of the over 1.7 million corrective boluses evaluated, 32% met the non-adjunctive criteria. Outcomes results are presented in the Table below.
The frequency and severity of hypoglycemia and hyperglycemia, although lower statistically with non-adjunctive vs. adjunctive corrective bolus delivery, showed likely clinical equivalency.

Disclosure
B. Jiang: None. S. Soleymani: Employee; Self; Medtronic MiniMed, Inc. R. Vigersky: Employee; Self; Medtronic MiniMed, Inc.. A. Sullivan: None. Y. Zhong: None. P. Agrawal: None. F.R. Kaufman: Employee; Self; Medtronic.
Adults with Type 1 Diabetes (T1D) Using Continuous Glucose Monitoring (CGM) Report Disease Has Little Impact on Daily Functioning—T1D Exchange
Authors: FAN LUDI , GAREY COLLEEN , LIU JINGWEN , MITCHELL BETH , BISPHAM JEOFFREY , MCAULIFFE-FOGARTY ALICIA H. 
Published: June 2018

Glycemic Variability (GV) and Treatment Satisfaction (TS) are not accurately reflected in HbA1c. This study explored GV measures and their effect on insulin TS, productivity and activity in a real-world population with T1D. This prospective survey was of 98 adults from the T1D Exchange online patient community. Surveys were completed and CGM data were downloaded at baseline and weekly thereafter for 4 weeks (week). The Insulin Treatment Satisfaction Questionnaire was done at week 4, and Work Productivity Impairment (WPI) and Activity Impairment (AI)-General Health Questionnaire were done weekly for 4 weeks. Linear regression and mixed models explored the relationship between GV and TS, and impairment, respectively. Overall mean age was 43 years (SD 15.3), mean years with T1D was 22 (SD 14.2), 68% were female, and mean self-reported most recent HbA1c was 6.8% (SD 0.8). Participants on insulin pump (n=86) and multiple daily injections (n=12) took an average of 47.7 Units (±35.8) and 39.3 Units (±23.1) of insulin, respectively. Markers of GV and patient reported measures are in Table. Of the 14 GV measures examined, CV and LBGI showed a positive association with insulin TS (p&lt;.05). No GV measures significantly impacted WPI or AI. The adult population with T1D in this survey had high TS, and had low WPI and AI, despite overall moderate risk for hypoglycemia.

Disclosure
L. Fan: Employee; Self; Eli Lilly and Company. C. Garey: None. J. Liu: None. B. Mitchell: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. J. Bispham: None. A.H. McAuliffe-Fogarty: Advisory Panel; Self; Novo Nordisk Inc..
Adaptive Modeling of Glucose Measurements with Unannounced Meals and Exercise
Authors: HAJIZADEH IMAN , RASHID MUDASSIR , CINAR ALI 
Published: June 2018

Reliable artificial pancreas (AP) systems require accurate models of the glucose-insulin dynamics in people with type 1 diabetes mellitus (T1DM). The realization of a fully automated AP system, however, is not possible with manual user entries for meals and exercise. To promote the development of automated AP systems without any user inputs, an adaptive and personalized data-driven model is developed that characterizes the evolving glycemic dynamics of individuals while explicitly considering the estimated effects of unknown disturbances such as meals and exercise. To achieve this adaptive and personalized modeling approach that best describes the glucose dynamics at any given instant without manual user input, we first quantify the effects of the unknown meals through adaptive estimates of time-varying parameters in dynamic physiological model. The evaluated meal effects are incorporated with plasma insulin concentration estimates and readily measured physiological data from noninvasive sensors, such as heart rate and energy expenditure, to determine the overall state of the individuals. The proposed modeling approach integrates first-principles physiological models and data-driven empirical techniques to determine an accurate and comprehensive perspective of the individual at any given time. Simulation case studies involving in silico subjects from the U.S. Food and Drug Administration approved University of Virginia/Padova metabolic simulator demonstrate the improvement in prediction ability of the proposed approach. The root-mean-square error and mean absolute error for 30-, 45-, and 60-min-ahead predictions are 15.61 and 8.98 mg/dL, 21.82 and 13.49 mg/dL, and 25.96 and 17.00 mg/dL, respectively. The accurate predictions of future glucose concentration measurements without requiring manual user inputs will enable fully-automated AP systems that perform efficiently by maintaining euglycemia and mitigating glucose excursions.

Disclosure
I. Hajizadeh: None. M. Rashid: None. A. Cinar: None.
Intermittently Scanned Continuous Glucose Monitoring (isCGM)—Examination in Pediatric Patients With and Without Ketoacidosis
Authors: BOU GABRIELA A. , WURM MICHAEL , HANSEN BARBARA C. , SCHWAB KARL OTFRIED 
Published: June 2018

The isCGM (FreeStyle Libre “flash”) is approved in a number of countries for use in adults, but has had minimal study in pediatric groups and no reports of its use during ketoacidosis. This study in pediatric patients sought to compare paired samples from this isCGM to the Accucheck Aviva glucose monitor under conditions of varying glucose levels and varying degrees of ketoacidosis.
Twelve hyperglycemic T1D patients, ages 6-16 years, were studied with a minimum of 6 paired comparisons in each condition: 3 with ketoacidosis (pH 7.2-7.3) and one with severe ketoacidosis (pH &lt;7.2), and all others nonketotic. Up to a 15% measurement difference between BG and tissue glucose measurements for BG &gt; 100 mg/dL, or an absolute difference of 15 mg/dL for BG &lt; 100 mg/dL, were considered within target range. Blood glucose levels ranged from 35 to 556 mg/dl (1.94-30.89 mmol/L) and pH levels 6.9 to 7.6. Mean absolute relative differences (MARD, isCGM vs. Accucheck paired measurements) were: 426 non-ketoacidotic with BG &gt;100 mg/dL: MARD of 11.77% with 69.2% of values within a 15% difference; 96 non-ketoacidotic with BG &lt; 100 mg/dL: MARD of 12.4% with 78.1% within 15%; 17 ketoacidotic with BG&gt;100 mg/dL: MARD of 12.42% with 70.6% within 15%; and 6 severely ketoacidotic: MARD of 22.68% with 16.7% within 15%, constituting a major difference with severe ketoacidosis. Clarke Error Grid Analysis for results with non-ketoacidotic values with BG &lt;=79 mg/dL: 93% in Zone A and 7% in Zone B; ketoacidotic values: 94.11% in Zone A and 5.88% in Zone B; and severely ketoacidotic values: 50% in Zone A and 50% in Zone B. Of the 545 paired comparisons obtained, only 17 were obtained during ketosis and 6 during severe ketoacidosis. These results show that this “flash” isCGM and BG measurements determined by Accucheck Aviva are highly concordant, however, the major differences observed during severe ketoacidosis urge caution in interpreting the blood glucose levels under this condition.

Disclosure
G.A. Bou: None. M. Wurm: None. B.C. Hansen: None. K. Schwab: None.
Use of the Tidepool Platform to Collect, Integrate, and Visualize Diabetes Device Data in a Pediatric Clinic Setting
Authors: WONG JENISE C. , IZADI ZARA , SCHROEDER SHANNON M. , NADER MARIE , MIN HYOJIN J. , NEINSTEIN AARON B. , ADI SALEH 
Published: June 2018

Glucose meters, insulin pumps, and continuous glucose monitoring systems provide data needed for people with type 1 diabetes to modify insulin regimens, evaluate lifestyle changes, or troubleshoot unexpected glucose levels. Health care providers (HCPs) can use device-specific software to review data at patient visits, often using separate, proprietary applications for each device. Using mixed qualitative and quantitative methods, we examined the feasibility of using the Tidepool platform and web application to view diabetes data from multiple devices together, in a multidisciplinary pediatric diabetes center where it was standard practice to upload and view data using device-specific software for each patient visit. Participating HCPs (n=15) used the software with compatible devices in all patient visits for 6 months. To evaluate the effect of the application on workflow, registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups. The time required to upload device data and the length of the office visit did not change. However, the number of times the provider referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per observed visit (p=0.0002). A significantly larger proportion of the children looked at the device data with the new application (61% at baseline vs. 94% at study end, p=0.015). HCPs liked the use of color to indicate glucose levels, the graphical web-based user interface, integration of the data in one application, and the ability to remotely access data via the web for telehealth. They found the application most useful for initiating patient conversations and education. Remaining challenges include the need for automated data upload and integration with electronic medical records. Future studies of HCP use of the application will focus on clinical outcomes and effects on patient engagement and self-management.

Disclosure
J.C. Wong: Research Support; Self; Dexcom, Inc.. Other Relationship; Self; Tidepool Project. Z. Izadi: None. S.M. Schroeder: None. M. Nader: None. H.J. Min: None. A.B. Neinstein: None. S. Adi: Stock/Shareholder; Spouse/Partner; Dexcom, Inc.. Speaker's Bureau; Self; Dexcom, Inc.. Board Member; Self; Tidepool Project. Other Relationship; Self; Novo Nordisk Inc..
Study of the Correlation between Tear Glucose Concentrations and Blood Glucose Concentrations
Authors: AIHARA MASAKAZU , KUBOTA NAOTO , KADOWAKI TAKASHI 
Published: June 2018

To achieve intensive glucose control for avoiding diabetic complications, it is necessary for diabetic patients to measure their blood glucose levels frequently. However, all currently available methods for blood glucose monitoring, including the finger prick method, are invasive. One of the possible noninvasive glucose monitoring approaches is tear glucose monitoring. Previous studies have showed the correlations between blood and tear glucose concentrations. But these correlations were not accurate sufficiently because the methods for tear sample collection were not standardized. For clinical development of tear glucose monitoring as a tool for predicting the blood glucose concentrations, we recruited 10 nondiabetic subjects and 20 diabetic subjects, observed the daily blood and tear glucose dynamics using samples collected under the standardized method, and determined the correlation between the blood and tear glucose concentrations. Preprandial blood glucose levels of diabetic subjects were significantly higher than those of nondiabetic subjects (p &lt; 0.001), and preprandial tear glucose levels of diabetic subjects had a higher tendency than those of nondiabetic subjects (p = 0.051). Two hours postprandial blood and tear glucose levels of diabetic subjects were significantly higher than those of nondiabetic subjects (p &lt; 0.001, p &lt; 0.05, respectively). The blood and tear glucose dynamics showed that the behavior of the tear glucose concentrations paralleled that of the blood glucose concentrations. A linear mixed model for diabetic subjects revealed the existence of a significant association between the blood glucose concentrations and tear glucose concentrations (p &lt; 0.001), and the association consisted even after adjusting for HbA1c levels and conditions of meals.
In conclusion, tear glucose monitoring would be a tool for predicting the blood glucose levels noninvasively for various diabetic patients.

Disclosure
M. Aihara: None. N. Kubota: None. T. Kadowaki: Consultant; Self; Novo Nordisk A/S, AstraZeneca, Merck Sharp & Dohme Corp.. Research Support; Self; Kissei Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Sanofi, Kyowa Hakko Kirin Co., Ltd., Novo Nordisk A/S, Astellas Pharma, Daiichi Sankyo Company, Limited, Takeda, Mitsubishi Tanabe Pharma Corporation, Ono Pharmaceutical Co., Ltd., Merck Sharp & Dohme Corp., Nippon Boehringer Ingelheim Co. Ltd.. Speaker's Bureau; Self; Astellas Pharma, AstraZeneca, Merck Sharp & Dohme Corp., Ono Pharmaceutical Co., Ltd., Takeda, Eli Lilly and Company, Nippon Boehringer Ingelheim Co. Ltd., Novo Nordisk A/S.
A Novel, Nonenzymatic Strategy for Stable, Optical Glucose Detection in Small Volumes of Fluid
Authors: WANG BING , BAZAN GUILLERMO , PENNATHUR SUMITA , QUEENAN B.N. , SCIDA KAREN 
Published: June 2018

The performance of any continuous glucose monitor (CGM) cannot exceed the performance of the underlying glucose sensor. Commercially available CGMs are built around the enzyme glucose oxidase. However, the performance of the enzyme is known to drift over time; accordingly, existing CGMs must be calibrated over periods of hours to days and replaced over periods of weeks. To overcome these fundamental limitations, we have developed a non-enzymatic glucose detection strategy that offers the promise of significantly improved stability and sensitivity. Specifically, we have designed and synthesized a water-soluble, molecular recognition element, which binds glucose with appropriate specificity and selectivity (Kd = 1.9 mM for glucose vs. Kd = 3.3 mM for fructose). The molecular recognition of glucose by our synthetic probes activates interactions between fluorescence-based reporters. Moreover, by coupling the recognition element with a light-harvesting molecular system with high optical cross-section, we are able to amplify optical signals that betray the presence of glucose, making it possible to carry out measurements in volumes as small as picoliters using off-the-shelf LEDs and photodetectors. Our detection platform also offers broad tunability: by altering the molecular recognition element and/or optical reporter we seek to achieve stable, optical detection of other sugars and biomarkers.

Disclosure
B. Wang: Research Support; Self; American Diabetes Association. G. Bazan: None. S. Pennathur: Stock/Shareholder; Self; Laxmi Therapeutic Devices. Research Support; Self; American Diabetes Association, JDRF. B. Queenan: Research Support; Self; American Diabetes Association. K. Scida: Research Support; Self; American Diabetes Association.
Costimulatory Molecules CD226 and TIGIT Impact CD8+ T-Cell Activity and Function during Type 1 Diabetes
Authors: YEH WEN-I , SEAY HOWARD , MATHEWS CLAYTON E. , BRUSKO TODD M. 
Published: June 2018

Investigations into the pathogenesis of type 1 diabetes (T1D) implicate antigen interaction and co-stimulation as key pathways in disease development. A non-synonymous polymorphism in CD226 (rs763361), that encodes for a co-stimulatory molecule, has been linked to risk for T1D. The CD226 activating pathway is constrained by TIGIT, the high-affinity co-inhibitory receptor T cell immunoreceptor with Ig and ITIM domains, which competes with CD226 for ligands CD112/CD155. We have previously demonstrated that CD226 facilitates CD4+ T effector function, whereas TIGIT potentiates regulatory T (Treg) cell activity. Here, we report that both receptors impact CD8+ T cell pathogenesis. Both CD226 and TIGIT are upregulated upon human CD8+ T cell activation and are divergently expressed by memory CD8+ T cell subsets. These results support our finding in the positive correlation between age and CD226 or TIGIT expression (P=0.0002 and P&lt;0.0001, respectively). Interestingly, TIGIT is co-expressed with the transcription factors T-bet and EOMES, whereas ∼80% of cytokine producing cells express CD226, demonstrating the coordinated expression of these factors with differentiated T cell lineages. We next sorted CD8+ T cells based on CD226 and TIGIT expression and assessed effector activity as well as gene expression profile following in vitro activation. Using a multiplex assay, we showed that CD226+ cells produced cytokines, chemokines, and cytolytic proteins (e.g., IFNγ, MIP-1α, granzyme B, and perforin) in a manner independent of TIGIT. Importantly, CD8+ T cell cytotoxicity to human β-cell line βLox5 that express high levels of ligands CD112 and CD155 is attenuated by blocking CD226 and enhanced by hindering TIGIT through a granzyme B dependent mechanism. These data support this co-stimulatory axis as a potential therapeutic pathway in T1D that could either attenuate CD226 co-stimulation of effector T cells, or inversely support tolerance induction by TIGIT signaling on Tregs.

Disclosure
W. Yeh: None. H. Seay: None. C.E. Mathews: None. T.M. Brusko: Stock/Shareholder; Self; OneVax, LLC. Advisory Panel; Self; Caladrius Biosciences, Inc.. Consultant; Self; Merck & Co., Inc., Sanofi-Aventis.