Multilayer Structured NMF for Spectral Unmixing of Hyperspectral Images

One of the challenges in hyperspectral data analysis is the presence of mixed pixels. Mixed pixels are the result of low spatial resolution of hyperspectral sensors. Spectral unmixing methods decompose a mixed pixel into a set of endmembers and abundance fractions. Due to nonnegativity constraint on abundance fraction values, NMF based methods are well suited to this problem. In this paper multilayer NMF has been used to improve the results of NMF methods for spectral unmixing of hyperspectral data under the linear mixing framework. Sparseness constraint on both spectral signatures and abundance fractions matrices are used in this paper. Evaluation of the proposed algorithm is done using synthetic and real datasets in terms of spectral angle and abundance angle distances. Results show that the proposed algorithm outperforms other previously proposed methods.Comment: 4 pages, conferenc

Unmixing of Hyperspectral Data Using Robust Statistics-based NMF

Mixed pixels are presented in hyperspectral images due to low spatial resolution of hyperspectral sensors. Spectral unmixing decomposes mixed pixels spectra into endmembers spectra and abundance fractions. In this paper using of robust statistics-based nonnegative matrix factorization (RNMF) for spectral unmixing of hyperspectral data is investigated. RNMF uses a robust cost function and iterative updating procedure, so is not sensitive to outliers. This method has been applied to simulated data using USGS spectral library, AVIRIS and ROSIS datasets. Unmixing results are compared to traditional NMF method based on SAD and AAD measures. Results demonstrate that this method can be used efficiently for hyperspectral unmixing purposes.Comment: 4 pages, conferenc

Tyrosine-Based Signals Regulate the Assembly of Daple⋅PARD3 Complex at Cell-Cell Junctions.

Polarized distribution of organelles and molecules inside a cell is vital for a range of cellular processes and its loss is frequently encountered in disease. Polarization during planar cell migration is a special condition in which cellular orientation is triggered by cell-cell contact. We demonstrate that the protein Daple (CCDC88C) is a component of cell junctions in epithelial cells which serves like a cellular "compass" for establishing and maintaining contact-triggered planar polarity. Furthermore, these processes may be mediated through interaction with the polarity regulator PARD3. This interaction, mediated by Daple's PDZ-binding motif (PBM) and the third PDZ domain of PARD3, is fine-tuned by tyrosine phosphorylation on Daple's PBM by receptor and non-receptor tyrosine kinases, such as Src. Hypophosphorylation strengthens the interaction, whereas hyperphosphorylation disrupts it, thereby revealing an unexpected role of Daple as a platform for signal integration and gradient sensing for tyrosine-based signals within the planar cell polarity pathway

Murine obscurin and Obsl1 have functionally redundant roles in sarcolemmal integrity, sarcoplasmic reticulum organization, and muscle metabolism.

Biological roles of obscurin and its close homolog Obsl1 (obscurin-like 1) have been enigmatic. While obscurin is highly expressed in striated muscles, Obsl1 is found ubiquitously. Accordingly, obscurin mutations have been linked to myopathies, whereas mutations in Obsl1 result in 3M-growth syndrome. To further study unique and redundant functions of these closely related proteins, we generated and characterized Obsl1 knockouts. Global Obsl1 knockouts are embryonically lethal. In contrast, skeletal muscle-specific Obsl1 knockouts show a benign phenotype similar to obscurin knockouts. Only deletion of both proteins and removal of their functional redundancy revealed their roles for sarcolemmal stability and sarcoplasmic reticulum organization. To gain unbiased insights into changes to the muscle proteome, we analyzed tibialis anterior and soleus muscles by mass spectrometry, uncovering additional changes to the muscle metabolism. Our analyses suggest that all obscurin protein family members play functions for muscle membrane systems

Proteomic analyses of Urine Exosomes reveal New Biomarkers of Diabetes in Pregnancy.

ObjectiveTo evaluate 24 hour urine exosome protein content changes among pregnant US subjects with diabetes and obesity during early pregnancy.MethodsThe exosome proteome content from 24 hour urine samples of pregnant subjects with gestational diabetes mellitus (GDM, N=8) and pre-gestational Type 2 diabetes (PGD, N = 10) were compared with control samples (CTRL, N = 10) obtained at week 20 of pregnancy. Differences in exosome protein load between groups was identified by liquid chromatography/mass spectrometry, analyzed by linear regression in negative binomial distribution, visualized in MetaboAnalyst (version 3.0), and validated by western immunoblotting.ResultsAt the 20th week of pregnancy, we identified 646, 734 and 856 proteins in exosomes from 24 hour urine samples of patients from the CTRL, GDM and PGD groups, respectively. S100 calcium binding protein A9, damage associated molecular pattern (DAMP) signal, was found to be significantly increased in both GDM and PGD subjects. In GDM subjects the peptide counts for S100A9 protein independently correlated with maternal obesity and macrosomia of the newborn infants. Early to late pregnancy developmental changes in the GDM group were shown to utilize pathways and protein expression levels differently from those in PGD or CTRL groups.ConclusionsUrinary exosome proteomic analysis non-invasively provides insights into maternal changes during diabetic pregnancy. Exosome biomarkers early in pregnancy can be potentially used to better understand pathophysiologic mechanisms of diabetes at a cellular level, and to distinguish between gestational and pre-gestational diabetes at the pathway level. This information can aid intervention efforts to improve pregnancy outcomes in women with diabetes

Chemical synthesis, 3D structure and ASIC binding site of mambalgin-2

Mambalgins are a novel class of snake venom components that exert potent analgesic effects mediated through the inhibition of acid-sensing ion channels (ASICs). The 57-residue polypeptide mambalgin-2 (Ma-2) was synthesized by using a combination of solid-phase peptide synthesis and native chemical ligation. The structure of the synthetic toxin, determined using homonuclear NMR, revealed an unusual three-finger toxin fold reminiscent of functionally unrelated snake toxins. Electrophysiological analysis of Ma-2 on wild-type and mutant ASIC1a receptors allowed us to identify -helix 5, which borders on the functionally critical acidic pocket of the channel, as a major part of the Ma-2 binding site. This region is also crucial for the interaction of ASIC1a with the spider toxin PcTx1, thus suggesting that the binding sites for these toxins substantially overlap. This work lays the foundation for structure-activity relationship (SAR) studies and further development of this promising analgesic peptide

Sparsity Constrained Graph Regularized NMF for Spectral Unmixing of Hyperspectral Data

Hyperspectral images contain mixed pixels due to low spatial resolution of hyperspectral sensors. Mixed pixels are pixels containing more than one distinct material called endmembers. The presence percentages of endmembers in mixed pixels are called abundance fractions. Spectral unmixing problem refers to decomposing these pixels into a set of endmembers and abundance fractions. Due to nonnegativity constraint on abundance fractions, nonnegative matrix factorization methods (NMF) have been widely used for solving spectral unmixing problem. In this paper we have used graph regularized NMF (GNMF) method combined with sparseness constraint to decompose mixed pixels in hyperspectral imagery. This method preserves the geometrical structure of data while representing it in low dimensional space. Adaptive regularization parameter based on temperature schedule in simulated annealing method also has been used in this paper for the sparseness term. Proposed algorithm is applied on synthetic and real datasets. Synthetic data is generated based on endmembers from USGS spectral library. AVIRIS Cuprite dataset is used as real dataset for evaluation of proposed method. Results are quantified based on spectral angle distance (SAD) and abundance angle distance (AAD) measures. Results in comparison with other methods show that the proposed method can unmix data more effectively. Specifically for the Cuprite dataset, performance of the proposed method is approximately 10% better than the VCA and Sparse NMF in terms of root mean square of SAD.Comment: 10 pages, Journa