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Background  

Peripheral tissue inflammation initiates hyperalgesia accompanied by tissue acidosis, nociceptor activation, and inflammation mediators. Recent studies have suggested a significantly increased expression of acid-sensing ion channel 3 (ASIC3) in both carrageenan- and complete Freund's adjuvant (CFA)-induced inflammation. This study tested the hypothesis that acupuncture is curative for mechanical hyperalgesia induced by peripheral inflammation.  相似文献   
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Background  

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities.  相似文献   
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Background  

DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.  相似文献   
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Background

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data.

Results

Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG.

Conclusions

We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.
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Brown SA  Rohrich RJ  Kenkel J  Young VL  Hoopman J  Coimbra M 《Plastic and reconstructive surgery》2004,113(6):1796-804; discussion 1805-6
Low-level laser therapy is a new subspecialty for the medical application of lasers that provides therapeutic rather than surgical outcomes for many medical indications. Recently, low-level laser therapy was reported to "liquefy" or release stored fat in adipocytes by the opening of specialized yet not identified cell membrane-associated pores after a brief treatment. Currently, low-level laser therapy is a U.S. Food and Drug Administration-approved technology for improving pain alleviation. To explore these data further, a series of in vitro studies on human preadipocytes and institutional animal care and use committee-approved protocols in a porcine Yucatan model and an institutional review board-approved clinical study were performed. Using a 635-nm low-level laser of 1.0 J/cm supplied to the authors by the vendor, these studies were designed to determine whether alteration in adipocyte structure or function was modulated after low-level laser therapy. Cultured human preadipocytes after 60 minutes of laser therapy did not change appearance compared with nonirradiated control cells. In the porcine model, low-level laser therapy (30 minutes) was compared with traditional lipoplasty (suction-assisted lipoplasty) and ultrasound-assisted lipoplasty. From histologic and scanning electron microscopic evaluations of the lipoaspirates, no differences were observed between low-level laser therapy-derived and suction-assisted lipoplasty-derived specimens. Using exposure times of 0, 15, 30, and 60 minutes in the presence or absence of superwet wetting solution and in the absence of lipoplasty, total energy values of 0.9 mW were delivered to tissue samples at three increasing depths from each experimental site. No histologic tissue changes or specifically in adipocyte structure were observed at any depth with the longest low-level laser therapy (60 minutes with superwet fluid). Three subjects undergoing large-volume lipoplasty were exposed to superwet wetting fluid infiltration 14 minutes before and 12 minutes after, according to vendor instructions. Tissue samples from infiltrated areas were collected before suction-assisted lipoplasty and lipoaspirates from suction-assisted lipoplasty. No consistent observations of adipocyte disruptions were observed in the histologic or scanning electron microscopy photographs. These data do not support the belief that low-level laser therapy treatment before lipoplasty procedures disrupts tissue adipocyte structure.  相似文献   
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