Role of Carotid Ultrasonography Combined with Monocyte/HDL Ratio in Internal Carotid Artery Stenosis.

BACKGROUND: Carotid duplex ultrasonography (DUS) is the primary screening tool for carotid artery stenosis, but has low reliability. MHR, which is the ratio of monocytes to high-density lipoprotein cholesterol (HDL-C), can be a marker for the degree and distribution of extracranial and intracranial atherosclerotic stenosis. OBJECTIVE: We determined the diagnostic value of DUS+MHR for internal carotid artery (ICA) stenosis. METHODS: We divided 273 hospitalized patients into non-stenosis (<50%) and ICA stenosis (≥50%) groups based on Digital Subtraction Angiography (DSA). We determined the peak systolic velocity (PSV) in the ICA on DUS, calculated the MHR, and investigated their relationship with ICA stenosis. RESULTS: On DSA, 34.1% (93/273) patients had moderate-to-severe ICA stenosis. DUS and DSA showed low concordance for detecting ICA stenosis (kappa = 0.390). With increasing age, the incidence of moderate-to-severe ICA stenosis increased. PSV, monocyte count, and MHR were significantly greater in the stenosis group than in the non-stenosis group (P < 0.001), while the HDL-C level was significantly lower (P = 0.001). PSV (OR: 1.020, 95% CI: 1.011-1.029, P < 0.001) and MHR (OR: 5.662, 95% CI: 1.945-16.482, P = 0.002) were independent risk factors for ICA stenosis. The area under the receiver operating characteristic curve of PSV+MHR (0.819) was significantly higher than that of PSV or MHR alone (77.42% sensitivity, P = 0.0207; 73.89% specificity, P = 0.0032). CONCLUSION: The combination of ICA PSV on DUS and MHR is better than PSV alone at identifying ICA stenosis and is well-suited to screen high-risk patients.

Asymmetric Henry Reaction of 2-Acylpyridine N-Oxides Catalyzed by a Ni-Aminophenol Sulfonamide Complex: An Unexpected Mononuclear Catalyst.

The asymmetric Henry reaction of 2-acylpyridine N-oxide remains a challenge as N-oxides generally act as competitive catalyst inhibitors or displace activating ligands. A novel variable yield (up to 99%) asymmetric Henry reaction of 2-acypyridine N-oxides catalyzed by a Ni-aminophenol sulfonamide complex with good to excellent enantioselectivity (up to 99%) has been developed. Mechanistic studies suggest that the unique properties of the electron-pairs of N-oxides for complexation with Ni makes the unexpected mononuclear complex, rather than the previously reported dinuclear complex, the active species.

Raman chemical feature extraction for quality control of dairy products.

As a fast information acquisition technique, Raman spectroscopy can be used to control the quality of dairy products. Feature extraction is a necessary processing step to improve the efficiency of Raman spectral data. Principal component analysis is a traditional method that can effectively extract the features and reduce the dimension of spectral data. However, it is difficult to analyze the chemical information of the extracted feature, thus limiting its practical application. In this work, Raman spectral chemical feature extraction was carried out. The quality control of Dingxin dairy products (a famous dairy brand in China; purchased from Heilongjiang Zhaodong Tianlong Dairy Co. Ltd., Heilongjiang, China) was used as an example. Raman peak intensity, peak area, and peak ratio were extracted as chemical features and further investigated using Euclidean distance and the quality fluctuation control chart. The potential quality discrimination ability of the Raman feature extraction methods was demonstrated. The results showed that the Puzhen dairy products (purchased from Inner Mongolia Yinuo Halal Food Co. Ltd., Inner Mongolia, China) and Xueyuan dairy products (used as a control; purchased from Inner Mongolia Wulanchabu City Jining Xueyuan Dairy Co. Ltd., Inner Mongolia, China) could be distinguished from Dingxin dairy products when the Raman chemical features special peak intensity, peak area, and peak ratio were used, and their discriminatory ability increased in sequence. Hence, it was shown that Raman chemical feature extraction can achieve quality control and discriminant analysis of dairy products and that the spectral information is clear.