Retrospective analysis of the relationship between elevated plasma levels of TXNIP and carotid intima-media thickness in subjects with impaired glucose tolerance and early Type 2 diabetes mellitus.

AIMS: Accelerated atherosclerosis is the major cause of mortality in diabetic patients and increased oxidative stress probably plays an important role in its development. The aim of our study was to evaluate the relationship between thioredoxin-interacting protein (TXNIP) as an oxidative stress parameter and carotid artery intima-media thickness (CIMT) as an indicator of atherosclerosis in patients with early-state diabetes and impaired glucose tolerance. METHODS: The study was a retrospective analysis of 90 patients with impaired glucose regulation (IGR), 80 patients with early Type 2 diabetes mellitus (T2DM), and 80 subjects with normal glucose tolerance (NGT) as the control group. It was conducted at the endocrine out-patient clinic and hospital department of Cangzhou Central Hospital (Cangzhou, China) from June 2012 to Oct. 2013. Plasma TXNIP was measured to evaluate the level of oxidative stress. CIMT was assessed by carotid artery ultrasonography. Soluble vascular cell adhesion molecule-1 (sVCAM-1), a risk indicator for endothelial dysfunction, was also measured. RESULTS: Compared to the NGT control, patients with IGR showed significantly higher plasma levels of TXNIP (P<0.05). Compared to the IGR group, patients with T2DM also had significantly higher plasma levels of TXNIP (P<0.05). CIMT was significantly higher in the subjects with abnormal glucose metabolism than in the NGT group (P<0.05). CIMT showed positive correlations with both TXNIP and sVCAM-1 levels (r = 0.56 and r = 0.49, respectively, both P<0.01). CONCLUSIONS: The present study showed that plasma levels of TXNIP may be a useful predictor of subclinical atherosclerosis in Type 2 diabetic patients.

Remotely sensed assessment of water quality levels in the Pearl River Estuary, China.

In this paper, a method of assessing water quality from satellite data is introduced. The composite pollution index (CPI) was calculated from measured chemical oxygen demand (COD) and nutrient concentration. The relationships between CPI and 240 band combinations of SeaWiFS water-leaving radiance were analyzed and the optimal band combination for estimating CPI was chosen from the 240 band combinations. An algorithm for retrieval of CPI was developed using the optimal band combination, (L(443)xL(510))/(L(412)+L(490)). The CPI was estimated from atmospherically corrected SeaWiFS data by employing the algorithm. Furthermore, the CPI value range for each water quality level was determined based on data obtained from 850 samples taken in the Pearl River Estuary. The remotely sensed CPIs were then transferred to water quality levels and appropriate maps were derived. The remotely sensed water quality level maps displayed a similar distribution of levels based on in situ investigation issued by the State Ocean Administration, China. This study demonstrates that remote sensing can play an important role in water quality assessment.