Toll-Like Receptor 4 Decoy, TOY, Attenuates Gram-Negative Bacterial Sepsis

Lipopolysaccharide (LPS), the Gram-negative bacterial outer membrane glycolipid, induces sepsis through its interaction with myeloid differentiation protein-2 (MD-2) and Toll-like receptor 4 (TLR4). To block interaction between LPS/MD-2 complex and TLR4, we designed and generated soluble fusion proteins capable of binding MD-2, dubbed TLR4 decoy receptor (TOY) using ‘the Hybrid leucine-rich repeats (LRR) technique’. TOY contains the MD-2 binding ectodomain of TLR4, the LRR motif of hagfish variable lymphocyte receptor (VLR), and the Fc domain of IgG1 to make it soluble, productive, and functional. TOY exhibited strong binding to MD-2, but not to the extracellular matrix (ECM), resulting in a favorable pharmacokinetic profile in vivo. TOY significantly extended the lifespan, when administered in either preventive or therapeutic manners, in both the LPS- and cecal ligation/puncture-induced sepsis models in mice. TOY markedly attenuated LPS-triggered NF-κB activation, secretion of proinflammatory cytokines, and thrombus formation in multiple organs. Taken together, the targeting strategy for sequestration of LPS/MD-2 complex using the decoy receptor TOY is effective in treating LPS- and bacteria-induced sepsis; furthermore, the strategy used in TOY development can be applied to the generation of other novel decoy receptor proteins

Improving gastric cancer preclinical studies using diverse in vitro and in vivo model systems

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background Biomarker-driven targeted therapy, the practice of tailoring patients treatment to the expression/activity levels of disease-specific genes/proteins, remains challenging. For example, while the anti-ERBB2 monoclonal antibody, trastuzumab, was first developed using well-characterized, diverse in vitro breast cancer models (and is now a standard adjuvant therapy for ERBB2-positive breast cancer patients), trastuzumab approval for ERBB2-positive gastric cancer was largely based on preclinical studies of a single cell line, NCI-N87. Ensuing clinical trials revealed only modest patient efficacy, and many ERBB2-positive gastric cancer (GC) patients failed to respond at all (i.e., were inherently recalcitrant), or succumbed to acquired resistance. Method To assess mechanisms underlying GC insensitivity to ERBB2 therapies, we established a diverse panel of GC cells, differing in ERBB2 expression levels, for comprehensive in vitro and in vivo characterization. For higher throughput assays of ERBB2 DNA and protein levels, we compared the concordance of various laboratory quantification methods, including those of in vitro and in vivo genetic anomalies (FISH and SISH) and xenograft protein expression (Western blot vs. IHC), of both cell and xenograft (tissue-sectioned) microarrays. Results The biomarker assessment methods strongly agreed, as did correlation between RNA and protein expression. However, although ERBB2 genomic anomalies showed good in vitro vs. in vivo correlation, we observed striking differences in protein expression between cultured cells and mouse xenografts (even within the same GC cell type). Via our unique pathway analysis, we delineated a signaling network, in addition to specific pathways/biological processes, emanating from the ERBB2 signaling cascade, as a potential useful target of clinical treatment. Integrated analysis of public data from gastric tumors revealed frequent (10 – 20 %) amplification of the genes NFKBIE, PTK2, and PIK3CA, each of which resides in an ERBB2-derived subpathway network. Conclusion Our comprehensive bioinformatics analyses of highly heterogeneous cancer cells, combined with tumor omics profiles, can optimally characterize the expression patterns and activity of specific tumor biomarkers. Subsequent in vitro and in vivo validation, of specific disease biomarkers (using multiple methodologies), can improve prediction of patient stratification according to drug response or nonresponse

KUNLP system for NTCIR-3 English–Korean cross-language information retrieval

This paper describes KUNLP system for the English-Korean cross-language information retrieval track in NTCIR-3 workshop and some experiments after the workshop. Query translation method based on the bilingual dictionary and the document language corpus was used. To automatically transliterate some proper nouns such as Korean person names, Korean place names, and Korean company names, we have constructed the bilingual biographical dictionary, and collected the corresponding translations of Korean place names and Korean company names. We submitted a monolingual run and three cross-language runs, which used only a description field of each topic as a query. Cross-language runs were classified as to whether query expansion was used and whether manual transliteration was applied. Comparisons between cross-language runs show that query expansion is useful in the English-Korean cross-language information retrieval and transliteration also improves the system performance. And additional experiments after NTCIR-3 workshop show that the Korean query which consists of the best translation equivalents for English query terms is more effective than that consisting of two or more translation equivalents. In addition, including English acronyms and initial words in the Korean query is helpful to retrieve Korean documents. Keywords: English-Korean cross-language information retrieval, query translation, query expansion, query transliteration.

Microelectrical Impedance Spectroscopy for the Differentiation between Normal and Cancerous Human Urothelial Cell Lines: Real-Time Electrical Impedance Measurement at an Optimal Frequency

Purpose. To distinguish between normal (SV-HUC-1) and cancerous (TCCSUP) human urothelial cell lines using microelectrical impedance spectroscopy (μEIS). Materials and Methods. Two types of μEIS devices were designed and used in combination to measure the impedance of SV-HUC-1 and TCCSUP cells flowing through the channels of the devices. The first device (μEIS-OF) was designed to determine the optimal frequency at which the impedance of two cell lines is most distinguishable. The μEIS-OF trapped the flowing cells and measured their impedance at a frequency ranging from 5 kHz to 1 MHz. The second device (μEIS-RT) was designed for real-time impedance measurement of the cells at the optimal frequency. The impedance was measured instantaneously as the cells passed the sensing electrodes of μEIS-RT. Results. The optimal frequency, which maximized the average difference of the amplitude and phase angle between the two cell lines (p<0.001), was determined to be 119 kHz. The real-time impedance of the cell lines was measured at 119 kHz; the two cell lines differed significantly in terms of amplitude and phase angle (p<0.001). Conclusion. The μEIS-RT can discriminate SV-HUC-1 and TCCSUP cells by measuring the impedance at the optimal frequency determined by the μEIS-OF

Optical design of ZnO-based antireflective layers for enhanced GaAs solar cell performance

A series of hierarchical ZnO-based antireflection coatings with different nanostructures (nanowires and nanosheets) is prepared hydrothermally, followed by means of RF sputtering of MgF2 layers for coaxial nanostructures. Structural analysis showed that both ZnO had a highly preferred orientation along the ???0001??? direction with a highly crystalline MgF2 shell coated uniformly. However, a small amount of Al was present in nanosheets, originating from Al diffusion from the Al seed layer, resulting in an increase of the optical bandgap. Compared with the nanosheet-based antireflection coatings, the nanowire-based ones exhibited a significantly lower reflectance (???2%) in ultraviolet and visible light wavelength regions. In particular, they showed perfect light absorption at wavelength less than approximately 400 nm. However, a GaAs single junction solar cell with nanosheet-based antireflection coatings showed the largest enhancement (43.9%) in power conversion efficiency. These results show that the increase of the optical bandgap of the nanosheets by the incorporation of Al atoms allows more photons enter the active region of the solar cell, improving the performance. &amp;copy; the Owner Societies 2016close

Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study

<div><p>Aims</p><p>The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study.</p><p>Material and Methods</p><p>The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40–70 years, who participated from 2005–2008 (baseline) without metabolic syndrome and were followed up from 2008–2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods.</p><p>Results</p><p>During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422–0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124–0.337, P<0.001), and the integrated discrimination improvement was 0.0094 (95% CI: 0.0046–0.0143, P<0.001).</p><p>Conclusions</p><p>The AST-to-ALT ratio independently predicted the future development of metabolic syndrome and had incremental predictive value for incident metabolic syndrome.</p></div

Comparison of AUC of each component of metabolic syndrome and additional AST-to-ALT ratio model.

<p>Comparison of AUC of each component of metabolic syndrome and additional AST-to-ALT ratio model.</p