Effect of 1,5-anhydroglucitol levels on culprit plaque rupture in diabetic patients with acute coronary syndrome.

BACKGROUND: Postprandial hyperglycemia was reported to play a key role in established risk factors of coronary artery diseases (CAD) and cardiovascular events. Serum 1,5-anhydroglucitol (1,5-AG) levels are known to be a clinical marker of short-term postprandial glucose (PPG) excursions. Low serum 1,5-AG levels have been associated with occurrence of CAD. However, the relationship between 1,5-AG levels and coronary plaque rupture has not been fully elucidated. The aim of this study was to evaluate 1,5-AG as a predictor of coronary plaque rupture in diabetic patients with acute coronary syndrome (ACS). METHODS: A total of 144 diabetic patients with ACS were included in this study. All patients underwent intravascular ultrasound examination, which revealed 49 patients with plaque rupture and 95 patients without plaque rupture in the culprit lesion. Fasting blood glucose (FBG), hemoglobin A1c (HbA1c) and 1,5-AG levels were measured before coronary angiography. Fasting urinary 8-iso-prostaglandin F2α (8-iso-PGF2α) level was measured and corrected by creatinine clearance. RESULTS: Patients with ruptured plaque had significantly lower serum 1,5-AG levels, longer duration of diabetes, higher HbA1c and FBG levels than patients without ruptured plaque in our study population. In multivariate analysis, low 1,5-AG levels were an independent predictor of plaque rupture (odds ratio 3.421; P = 0.005) in diabetic patients with ACS. The area under the receiver-operating characteristic curve for 1,5-AG (0.658, P = 0.002) to predict plaque rupture was superior to that for HbA1c (0.587, P = 0.087). Levels of 1,5-AG were significantly correlated with urinary 8-iso-prostaglandin F2α levels (r = - 0.234, P = 0.005). CONCLUSIONS: Serum 1,5-AG may identify high risk for coronary plaque rupture in diabetic patients with ACS, which suggests PPG excursions are related to the pathogenesis of plaque rupture in diabetes.

[Study on inversion of temperature distribution based on principal components analysis].

Multispectral radiation thermometry (MRT) is one of the methods for non-contact temperature measurement. The present MRT could invert only one approximate temperature value, and the actual temperature distribution could not be given. In the present article principal component analysis (PCA) was applied to solve the problem based on Planck' s laws. For example, in the laser damage target experiments, input laser pulse energy is 34.2 J, the inversion temperature value is 2 700 K from the thermal radiation spectrum. The fitting relative deviation is 0.5%, and when the temperature distribution is from 2 600 to 2 800 K, the fitting relative deviation is reduced to 0.13%. Temperature distribution inversion was shown based on PCA for the first time, and the measurement accuracy of non-contact temperature was improved.