Neuropathology of cigarette smoking

It is well established that cigarette smoking is hazardous to health and is a risk factor for many chronic diseases. However, its impact on the brain, whether it be from prenatal exposure to maternal cigarette smoking, cerebrovascular disease, Alzheimer’s disease (AD) or Parkinson’s disease, is still not very clear. Neuroimaging and neuropathological investigations suggest that there are heterogeneous effects of cigarette smoking on the brain. On the one hand, it is quite clear that cigarette smoking causes damage to endothelial cells, resulting in increased risk of cerebrovascular disease. On the other hand, it seems to be associated with different Alzheimer’s pathologies in post-mortem brains and experimental models, despite the fact that epidemiological studies clearly indicate a positive correlation between cigarette smoking and increased risk for AD. Interestingly, cigarette smoking appears to be associated with reduced Parkinson’s pathology in post-mortem brains. However, although nicotine in cigarettes may have some neuroprotective actions, the effects of all the other toxic compounds in cigarettes cannot be ignored. It is, therefore, our aim to summarize what is known about the neuropathology of cigarette smoking and, in particular, its implications for neurodegenerative diseases.     

新型快速中药材DNA提取方法的探索与应用

目的建立一种无设备快速30 s提取中药材DNA的方法。方法使用常规定性滤纸作为核酸吸附的载体,通过裂解液的裂解,释放核酸并吸附在滤纸上,利用洗脱液进行核酸纯化,即可完成不到30s的整个核酸提取过程,吸附核酸的滤纸可直接放入反应体系进行扩增。结果此方法可以成功提取不同药用部位的中药材核酸,提取得到的核酸经扩增验证,可获得与传统提取方法相一致的检测结果。结论此新型快速中药材DNA提取方法简单易行、速度快、成本低,可使核酸提取变得越来越大众化,不再局限于专业人员和实验室环境,为分子生药学的应用和发展提供了新思路。     

Mechanisms Underlying the Effect of Acupuncture on Cognitive Improvement: A Systematic Review of Animal Studies

Acupuncture has been reported to be beneficial in treating cognitive impairment in various pathological conditions. This review describes the effort to understand the signaling pathways that underlie the acupunctural therapeutic effect on cognitive function. We searched the literature in 12 electronic databases from their inception to November 2013, with full text available and language limited to English. Twenty-three studies were identified under the selection criteria. All recruited animal studies demonstrate a significant positive effect of acupuncture on cognitive impairment. Findings suggest acupuncture may improve cognitive function through modulation of signaling pathways involved in neuronal survival and function, specifically, through promoting cholinergic neural transmission, facilitating dopaminergic synaptic transmission, enhancing neurotrophin signaling, suppressing oxidative stress, attenuating apoptosis, regulating glycometabolic enzymes and reducing microglial activation. However, the quality of reviewed studies has room for improvement. Further high-quality animal studies with randomization, blinding and estimation of sample size are needed to strengthen the recognition of group differences.     

A combination of Sinomenine and Methotrexate reduces joint damage of collagen induced arthritis in rats by modulating osteoclast-related cytokines

ObjectiveTo analyze the combination therapy of Sinomenine (SIN) and Methotrexate (MTX) in rheumatoid arthritis (RA), we herein demonstrated the combination effect of SIN and MTX on collagen-induced arthritis (CIA) in rats through their modulation on osteoclast-related cytokines.MethodsCIA was induced by the immunization of type II collagen (CII) in SD rats. SIN and MTX were administrated alone or in combination after the onset of arthritis. Arthritis index and histological analysis were used to evaluate the effect of treatments. Effects of SIN and MTX on expression of receptor activator of NF-κB ligand (RANKL) and osteopontin (OPN) in synovial tissues were assayed by immunohistochemistry. RANKL, osteoprotegerin (OPG), IL-6, IL-17 and matrix metalloproteinases (MMPs) in rat serum were measured by ELISA. The expression of osteoclast-related cytokines in fibroblast-like synoviocytes (FLS) from RA patients was assayed by RT-PCR.ResultsSIN and MTX combination additively reduced the inflammatory symptoms and joint damage in CIA. Combination of SIN and MTX significantly repressed synovial RANKL and OPN production. SIN and MTX exhibited complementary and synergistic effect upon down-regulating RANKL, IL-6, IL-17 and MMPs in rat serum. SIN and MTX also modulated the expression of RANKL and OPG in RA-FLS.ConclusionSIN and MTX have additive effects, decreasing inflammation and joint damage in CIA rats by modulating osteoclast-related cytokines. These results are indicative of the combined effect of SIN and MTX for anti-arthritic treatment in RA.     

Macrolide sesquiterpene pyridine alkaloids from the stems of Tripterygium regelii

Nine new monomacrolide sesquiterpene pyridine alkaloids, macroregelines A–I (1–9), were isolated from the stems of Tripterygium regelii, along with a known alkaloid, tripfordine B. The structures of all the isolated compounds were characterized by extensive one-dimensional (1D) and two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopic analyses, as well as high-resolution electrospray-ionization mass spectrometry (HRESIMS) data. Compounds 4, 5, 6, and 8 showed antiproliferative effect on human rheumatoid arthritis synovial cell line MH7A at concentration of 20 μM, reducing their viability by 7.5, 18.0, 9.0, and 18.2 %, respectively.

     

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms.     

Learning using privileged information: SVM+ and weighted SVM

Prior knowledge can be used to improve predictive performance of learning algorithms or reduce the amount of data required for training. The same goal is pursued within the learning using privileged information paradigm which was recently introduced by Vapnik et al. and is aimed at utilizing additional information available only at training time—a framework implemented by SVM+. We relate the privileged information to importance weighting and show that the prior knowledge expressible with privileged features can also be encoded by weights associated with every training example. We show that a weighted SVM can always replicate an SVM+ solution, while the converse is not true and we construct a counterexample highlighting the limitations of SVM+. Finally, we touch on the problem of choosing weights for weighted SVMs when privileged features are not available.