Small dense LDL (sd-LDL) has recently emerged as an important coronary artery disease (CAD) risk factor. This study was performed to investigate how LDL particle size is related to CAD and acute coronary syndrome (ACS). Blood samples were collected from 504 patients that underwent coronary angiography to evaluate chest pain. The LDL particle size of these samples was measured. The mean LDL particle size was smaller in patients with angiographically proven CAD than in the controls (26.41 ± 0.95 vs 26.73 ± 0.64 nm, p < 0.001), and was negatively correlated with the Framingham risk score (r = -0.121, p = 0.007). Patients with more extensive CAD had smaller LDL particles. LDL particle size was also smaller in patients with acute coronary syndrome as compared to non-ACS patients (26.09 ± 1.42 vs 26.54 ± 0.63 nm, p = 0.011). These results suggest that sd-LDL is independently associated with the incidence and extent of CAD, and can be a risk factor for the development of ACS in the Korean population.

Plasma PTX3 is positively associated with DR development and progression, and may be a more accurate predictor of DR development than hsCRP.

The formation of advanced glycation end products (AGEs), in various tissues has been known to enhance immunoinflammatory reactions and local oxidant stresses in long standing diabetes. Recently, AGEs have been reported to play a role in neointimal formation in animal models of arterial injury. We attempted to determine whether the serum levels of AGEs are associated with coronary restenosis in diabetic patients. Blood samples were collected from diabetic patients with coronary artery disease undergoing stent implantation and the serum levels of AGEs were analyzed by the fluorescent intensity method. The development of in-stent restenosis (ISR) was evaluated by a 6-month follow-up coronary angiography. A total of 263 target lesions were evaluated, in 203 patients. The ISR rate in the high-AGE (>170 U/ml) group (40.1%) was significantly higher than in the low-AGE group (≤170 U/ml) (19.6%) (p<0.001). Furthermore, multivariate analysis revealed that a high level of serum AGEs is an independent risk factor for the development of ISR (odds ratio, 2.659; 95% CI, 1.431-4.940; p=0.002). The serum levels of AGEs constitute an excellent predictive factor for ISR, and should be one of the guidelines for medical therapy and interventional strategy to prevent ISR in diabetic patients.

Alisma canaliculatum is a herb commonly used in traditional Korean medicine, and has been shown in scientific studies to have antitumor, diuretic hepatoprotective, and antibacterial effects. Recently, the anti-osteoclastogenesis of alisol A 24-acetate from Alisma canaliculatum was investigated in vitro. However, the influence of alisol A 24-acetate on osteoporosis in animals has not been investigated. The present study was undertaken to investigate the anti-osteoporotic effect of alisol A 24-acetate on bone mass in ovariectomized (OVX) mice and to identify the mechanism responsible for its effects. OVX mice were treated daily with 0.5 or 2 µg/g of alisol A 24-acetate for a period of six weeks. It was found that these administrations significantly suppressed osteoporosis in OVX mice and improved bone morphometric parameters. The serum estradiol, bone alkaline phosphatase levels, regulatory T/Th17 cell numbers were significantly increased by alisol A 24-acetate as compared with untreated OVX mice. In addition, TRAP activity was inhibited by alisol A 24-acetate in OVX mice. These results suggest alisol A 24-acetate effectively prevents bone loss in OVX mice, and that it can be considered a potential therapeutic for the treatment of postmenopausal osteoporosis.

Summary Hypertext transfer protocol (HTTP) has become the main protocol to carry out malicious activities. Attackers typically use HTTP for communication with command‐and‐control servers, click fraud, phishing and other malicious activities, as they can easily hide among the large amount of benign HTTP traffic. The user‐agent (UA) field in the HTTP header carries information on the application, operating system (OS), device, and so on, and adversaries fake UA strings as a way to evade detection. Motivated by this, we propose a novel grammar‐guided UA string classification method in HTTP flows. We leverage the fact that a number of ‘standard’ applications, such as web browsers and iOS mobile apps, have well‐defined syntaxes that can be specified using context‐free grammars, and we extract OS, device and other relevant information from them. We develop association heuristics to classify UA strings that are generated by ‘non‐standard’ applications that do not contain OS or device information. We provide a proof‐of‐concept system that demonstrates how our approach can be used to identify malicious applications that generate fake UA strings to engage in fraudulent activities. Copyright © 2015 John Wiley & Sons, Ltd.