Journal: Journal of Diabetes

Article Title: Washed microbiota transplantation reduces glycemic variability in unstable diabetes

doi: 10.1111/1753-0407.13485

Figure Lengend Snippet: (A) Flow diagram of study design and participating patients. (B) Changes of daily insulin dose. Data of the same subject at different follow‐up time points are connected by gray lines. False discovery rate (represented as q ‐value) was calculated using repeated‐measures one‐way analysis of variance corrected by Benjamini and Hochberg method for multiple comparisons, n = 14. (C) Postprandial glucose excursions expressed as percentage of baseline during steamed bun meal test (SBMT). All data are represented as mean ± SEM, * q < 0.05 by mixed‐effects model for repeated measures corrected by Benjamini and Hochberg method, n = 9–12. (D–H) Changes of glycemic variability (GV) indices at 1 week (T1W) calculated using continuous glucose monitor (CGM) data: (D) MAGE, (E) SDBG, (F) BG > 11.1 mmol/L, (G) LAGE, and (H) MBG. † p < .05 by paired t test (two‐tailed), n = 14. (I–J) Changes of GV indices at T1W, 1 month (T1M), and 3 months (T3M) calculated using self‐monitoring of blood glucose data: (I) TIR and (J) hypoglycemic episodes. $ q < 0.05 as stated in (B); # q < 0.05 by repeated‐measures Friedman test corrected by Benjamini and Hochberg method, n = 14. (K) Representative CGM 24‐h glucose profiles demonstrating improved glycemic stability in two patients by WMT. Values of some GV indices were the same for different participants. Thus, both points and connecting lines overlapped with each other, exhibiting fewer than 14 points. LAGE, largest amplitude of glycemic excursions; MAGE, mean amplitude of glycemic excursion; MBG, mean blood glucose; SDBG, SD of blood glucose; TIR, time in range; WMT, washed microbiota transplantation.

Article Snippet: Three days before WMT, patients were implanted with a continuous glucose monitor (CGM) device (MeiQi Medical Instruments Co., Ltd., Huzhou, China).

Techniques: Two Tailed Test, Transplantation Assay

Journal: Journal of Diabetes

Article Title: Washed microbiota transplantation reduces glycemic variability in unstable diabetes

doi: 10.1111/1753-0407.13485

Figure Lengend Snippet: Washed microbiota transplantation (WMT) alters profiles of serum metabolites. (A) Heatmap showing changes of serum metabolites determined by non‐targeted metabolomics, n = 11–14. (B) Heatmap of Spearman's correlation coefficients between serum metabolites and glycemic variability (GV) indices. (C) The 8 positively correlated metabolites between fecal and serum compartments. Color range varies from light red (weaker correlation) to dark red (stronger correlation). Statistical methods were the same as stated in Figure . AUC, area under the curve; BG, blood glucose; CGM, continuous glucose monitor; CV, coefficient of variation; HbA1c, glycated hemoglobin; LAGE, largest amplitude of glycemic excursions; MBG, mean blood glucose; PPGE, postprandial glucose excursion; SBMT, steamed bun meal test; SMBG, self‐monitoring of blood glucose; TIR, time in range.

Article Snippet: Three days before WMT, patients were implanted with a continuous glucose monitor (CGM) device (MeiQi Medical Instruments Co., Ltd., Huzhou, China).

Techniques: Transplantation Assay

Journal: European Endocrinology

Article Title: Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

doi: 10.17925/EE.2014.10.01.36

Figure Lengend Snippet: Summary of Interstitial Glucose versus Blood Glucose Average Lag Time, Estimated Values and Related Study Information

Article Snippet: Feldman B, 2003 146 , 5 , People with type 1 diabetes (n=30) , Transcutaneous sensor , FreeStyle Navigator (Abbott).

Techniques: Sampling

Journal: Endocrinology and metabolism clinics of North America

Article Title: Evidence-based Mobile Medical Applications in Diabetes

doi: 10.1016/j.ecl.2016.06.001

Figure Lengend Snippet: Summary of commercially available mobile medical apps for DM management (N = 14)

Article Snippet: 9 Share (Dexcom) Dexcom continuous glucose monitoring (CGM) system with Share is an FDA-approved CGM system with Bluetooth technology built into the receiver that allows uploading of real-time CGM data via an iOS device onto a Health Insurance Portability and Accountability Act (HIPAA)–compliant server that can be shared with family and the care team.

Techniques: Activity Assay, Selection, Software, Medications