Insulin resistance predicts progression of de novo atherosclerotic plaques in patients with coronary heart disease: a one-year follow-up study

BACKGROUND: The aim of our study was to explore and evaluate the relationship between insulin resistance and progression of coronary atherosclerotic plaques. With the great burden coronary heart disease is imposing on individuals, healthcare professionals have already embarked on determining its potential modifiable risk factors in the light of preventive medicine. Insulin resistance has been generally recognized as a novel risk factor based on epidemiological studies; however, few researches have focused on its effect on coronary atherosclerotic plaque progression. METHODS: From June 7, 2007 to December 30, 2011, 366 patients received their index coronary angiogram and were subsequently found to have coronary atherosclerotic plaques or normal angiograms were consecutively enrolled in the study by the department of cardiology at the Ruijin Hospital, which is affiliated to the Shanghai Jiaotong University School of Medicine. All patients had follow-up angiograms after the 1-year period for evaluating the progression of the coronary lesions. The modified Gensini score was adopted for assessing coronary lesions while the HOMA-IR method was utilized for determining the state of their insulin resistance. Baseline characteristics and laboratory test results were described and the binomial regression analysis was conducted to investigate the relationship between insulin resistance and coronary atherosclerotic plaque progression. RESULTS: Index and follow-up Gensini scores were similar between the higher insulin lower insulin resistant groups (9.09 ± 14.33 vs 9.44 ± 12.88, p = 0.813 and 17.21 ± 18.46 vs 14.09 ± 14.18, p =0.358). However the Gensini score assessing coronary lesion progression between both visits was significantly elevated in the higher insulin resistant group (8.13 ± 11.83 versus 4.65 ± 7.58, p = 0.019). Multivariate logistic binomial regression analysis revealed that insulin resistance (HOMA-IR > 3.4583) was an independent predictor for coronary arterial plaque progression (OR = 4.969, p = 0.011). We also divided all the participants into a diabetic (n = 136) and a non-diabetic group (n = 230), and HOMA-IR remained an independent predictor for atherosclerosis plaque progression. CONCLUSIONS: Insulin resistance is an independent predictor of atherosclerosis plaque progression in patients with coronary heart disease in both the diabetic and non-diabetic population

Systemic Revealing Pharmacological Signalling Pathway Networks in the Hippocampus of Ischaemia-Reperfusion Mice Treated with Baicalin

Background. Baicalin (BA) exhibits ill understood neuroprotective, anti-inflammatory, and antioxidative effects in brain injury. Objective. To identify the differential network pathways associated with BA-related biological effects. Methods. MCAO-induced mice received BA 5 mg/Kg (BA group). Controls received vehicle only. Following ischaemia-reperfusion, ArrayTrack analysed the whole genome microarray of hippocampal genes, and MetaCore analysed differentially expressed genes. Results. Four reversing pathways were common to BA and controls, but only 6 were in the top 10 for BA. Three of the top 5 signalling pathways in controls were not observed in BA. BA treatment made absent 3 pathways of the top 5 signalling pathways from the top 5 in controls. There were 2 reversing pathways between controls and BA that showed altered gene expression. Controls had 6 networks associated with cerebral ischaemia. After BA treatment, 9 networks were associated with cerebral ischaemia. Enrichment analysis identified 10 significant biological processes in BA and controls. Of the 10 most significant molecular functions, 7 were common to BA and controls, and only 3 occurred in BA. BA and controls had 7 significant cellular components. Conclusions. This study showed that the clinical effectiveness of BA was based on the complementary effects of multiple pathways and networks

Calculation of inlet capacitance for long-duration induction voltage test of single-phase three-winding converter transformers

The converter transformer is one of the core equipment in the high-voltage DC (HVDC) transmission project. The capacity of the converter transformer is much larger than that of an ordinary AC transformer, and its main function is to convert the AC system voltage to the phase change voltage required by the converter. The long-duration induction voltage test is an important technical means to assess the insulation strength of electrical equipment, and the calculation of the inlet capacitance of the converter transformer in the test design is extremely critical. This paper conducts circuit and mathematical modeling based on the structure of a single-phase three-winding converter transformer, calculates the equivalent capacitance between each winding of the converter transformer and each winding to ground by the model, and uses each equivalent capacitance to calculate the voltage added inlet capacitance, then obtains the appropriate compensation inductance. Moreover, the calculated inlet capacitance is verified by using the field test data, and the verification results show the reasonableness of the model. Finally, the calculation results are analyzed for errors and possible sources of errors are pointed out. This inlet capacitance calculation method has some universality and is expected to be promoted and applied in this field

Adsorption Study of 47 Elements on Alumina and Bentonite Using a Multitracer Technique

Uranyl nitrate, UO 2 (NO 3 ) 2 , was irradiated with a 25 MeV/nucleon 40 Ar ion beam, and the target material removed by means of solvent extraction. A radioactive multitracer solution containing 47 elements and 83 nuclides free from carriers was thereby prepared. The multitracer solution was used in an adsorption study of 47 elements on alumina and bentonite. The distribution coefficients (K d ) of the 47 elements were simultaneously determined and correlated with the electron binding energy (I z ), and explained by the thermodynamic model for adsorption of James and Healy (1972)