Independent component analysis of Alzheimer's DNA microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA) and independent component analysis (ICA) have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics.</p> <p>Results</p> <p>ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD) hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In comparison to the PCA and support vector machine recursive feature elimination (SVM-RFE) methods, which are widely used in microarray data analysis, ICA can identify more AD-related genes. Furthermore, we have validated and identified many genes that are associated with AD pathogenesis.</p> <p>Conclusion</p> <p>We demonstrated that ICA exploits higher-order statistics to identify gene expression profiles as linear combinations of elementary expression patterns that lead to the construction of potential AD-related pathogenic pathways. Our computing results also validated that the ICA model outperformed PCA and the SVM-RFE method. This report shows that ICA as a microarray data analysis tool can help us to elucidate the molecular taxonomy of AD and other multifactorial and polygenic complex diseases.</p

A Cross Comparison of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites and Ground in a Northern U.S. Mixed Forest

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring

Fluorescent Phosphatidylinositol 4,5-Bisphosphate Derivatives with Modified 6-Hydroxy Group as Novel Substrates for Phospholipase C

The capacity to monitor spatiotemporal activity of phospholipase C (PLC) isozymes with a PLC-selective sensor would dramatically enhance understanding of the physiological function and disease relevance of these signaling proteins. Previous structural and biochemical studies defined critical roles for several of the functional groups of the endogenous substrate of PLC isozymes, phosphatidylinositol 4,5-bisphosphate (PIP2), indicating that these sites cannot be readily modified without compromising interactions with the lipase active site. However, the role of the 6-hydroxy group of PIP2 for interaction and hydrolysis by PLC has not been explored, possibly due to challenges in synthesizing 6-hydroxy derivatives. Here, we describe an efficient route for the synthesis of novel, fluorescent PIP2 derivatives modified at the 6-hydroxy group. Two of these derivatives were used in assays of PLC activity in which the fluorescent PIP2 substrates were separated from their diacylglycerol products and reaction rates quantified by fluorescence. Both PIP2 analogues effectively function as substrates of PLC-δ1, and the KM and Vmax values obtained with one of these are similar to those observed with native PIP2 substrate. These results indicate that the 6-hydroxy group can be modified to develop functional substrates for PLC isozymes, thereby serving as the foundation for further development of PLC-selective sensors

Stem cell membrane engineering for cell rolling using peptide conjugation and tuning of cell–selectin interaction kinetics

Dynamic cell–microenvironment interactions regulate many biological events and play a critical role in tissue regeneration. Cell homing to targeted tissues requires well balanced interactions between cells and adhesion molecules on blood vessel walls. However, many stem cells lack affinity with adhesion molecules. It is challenging and clinically important to engineer these stem cells to modulate their dynamic interactions with blood vessels. In this study, a new chemical strategy was developed to engineer cell–microenvironment interactions. This method allowed the conjugation of peptides onto stem cell membranes without affecting cell viability, proliferation or multipotency. Mesenchymal stem cells (MSCs) engineered in this manner showed controlled firm adhesion and rolling on E-selectin under physiological shear stresses. For the first time, these biomechanical responses were achieved by tuning the binding kinetics of the peptide-selectin interaction. Rolling of engineered MSCs on E-selectin is mediated by a Ca[superscript 2+] independent interaction, a mechanism that differs from the Ca[superscript 2+] dependent physiological process. This further illustrates the ability of this approach to manipulate cell–microenvironment interactions, in particular for the application of delivering cells to targeted tissues. It also provides a new platform to engineer cells with multiple functionalities.National Heart, Lung, and Blood Institute (Programs of Excellence in Nanotechnology Award Contract HHSN268201000045C)National Institutes of Health (U.S.) (Grant 2-P30-CA14051)Armed Forces Institute of Regenerative Medicine (Award W81XWH-08-2-0034

The role of Endobronchial ultrasound guided transbronchial needle aspiration (EBUS-TBNA) for qualitative diagnosis of mediastinal and hilar lymphadenopathy: a prospective analysis

<p>Abstract</p> <p>Background</p> <p>Recently EBUS-TBNA, which has a sensitivity of 94.6%, specificity of 100% and diagnostic accuracy rate of 96.3% as previously reported, has been widely used for patients with mediastinal and hilar lymphadenopathy or suspected lung cancer to get accurate diagnosis. The purpose of the current study was to evaluate the usefulness of EBUS-TBNA in obtaining cytological and histological diagnosis of mediastinal and hilar lymph nodes compared to the results obtained with conventional mediastinoscopy as previously reported, and to assess the relationship of diagnostic accuracy and number of passes and size of lymph nodes.</p> <p>Methods</p> <p>101 patients with mediastinal and hilar lymphadenopathy or suspected lung cancer in our institution were included in this prospective study. EBUS-TBNA was performed in all cases. The final diagnosis was confirmed by cytology, surgical results, and/or clinical follow-up for at least 6 months. Sensitivity, specificity, accuracy, and positive and negative predictive values were calculated using standard formulas.</p> <p>Results</p> <p>In 101 patients, EBUS-TBNA was successfully performed to obtain samples from 225 lymph nodes, 7 lung masses, 1 mediastinal mass and 2 esophageal masses. 63 malignant tumors and 38 benign diseases were confirmed. Epidermal growth factor receptor mutation was detected in 10 biopsy samples, and epidermal growth factor receptor mutation was detected in 4 cases. With respect to the correct diagnosis of mediastinal and hilar lymphadenopathy, EBUS-TBNA had a sensitivity of 95.08%, specificity of 100%, positive predictive value of 100%, negative predictive value of 93.02%, and overall accuracy of 97.02%. The relationship of diagnostic accuracy and number of lymph node passes or size of lymph nodes was both insignificant (p = 0.27; p = 0.23). The procedure was uneventful without complications.</p> <p>Conclusions</p> <p>EBUS-TBNA is an accurate and safe tool in diagnosis of mediastinal and hilar lymphadenopathy. It cannot completely replace mediastinoscopy, it may indeed reduce the number of mediastinoscopy procedures. In some cases, it can necessarily be the first-line procedure before mediastinoscopy.</p

Identification of manganese superoxide dismutase from Sphingobacterium sp. T2 as a novel bacterial enzyme for lignin oxidation

The valorisation of aromatic heteropolymer lignin is an important unsolved problem in the development of a biomass-based biorefinery, for which novel high-activity biocatalysts are needed. Sequencing of the genomic DNA of lignin-degrading bacterial strain Sphingobacterium sp. T2 revealed no matches to known lignin-degrading genes. Proteomic matches for two manganese superoxide dismutase proteins were found in partially purified extracellular fractions. Recombinant MnSOD1 and MnSOD2 were both found to show high activity for oxidation of Organosolv and Kraft lignin, and lignin model compounds, generating multiple oxidation products. Structure determination revealed that the products result from aryl-Cα and Cα-Cβ bond oxidative cleavage and O-demethylation. The crystal structure of MnSOD1 was determined to 1.35 Å resolution, revealing a typical MnSOD homodimer harbouring a 5-coordinate trigonal bipyramidal Mn(II) centre ligated by three His, one Asp and a water/hydroxide in each active site. We propose that the lignin oxidation reactivity of these enzymes is due to the production of hydroxyl radical, a highly reactive oxidant. This is the first demonstration that MnSOD is a microbial lignin-oxidising enzyme

High-sensitive and temperature-self-calibrated tilted fiber grating biological sensing probe

High sensitivity biological sample measurement has been achieved by using a 10° tilted fiber Bragg grating sensing probe. Human acute leukemia cells with different intracellular densities were clearly discriminated by identifying their slight refraction index (RI) perturbations in the range from 1.3342 to 1.3344, combining with a temperature self-calibration property. We studied the relationship between the intrace

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN