Structure and dynamics of protein excited states with millisecond lifetimes

An in-depth understanding of biological processes often requires detailed atomic resolution structures of the molecules involved. However in solution where most of these processes occur the conformation of biomolecules like RNA, DNA and proteins is not static but fluctuates. Routinely used structural techniques like X-ray crystallography, NMR spectroscopy and cryo-electron microscopy have almost always been used to determine the structure of the dominant conformation or obtain an average structure of the biomolecule in solution with very little detailed information regarding the dynamics of these molecules in solution. Over the last few years, NMR based methods have been developed to study the dynamics of these biomolecules in solution in a site-specific manner with the aim of generating structures of the different conformations that these molecules can adopt in solution. One powerful technique is the Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion experiment, which can be used to detect and characterize protein excited states that are populated for as less as 0.5% of the time with ∼0.5–10 millisecond lifetimes. Due to recent advances in NMR pulse sequences and labeling methodology, it is now possible to determine the structures of these transiently populated excited states with millisecond lifetimes by obtaining accurate chemical shifts, residual dipolar couplings (RDCs) and residual chemical shift anisotropies (RCSAs) of these excited states. In these excited states the dynamics of some methyl containing residues can also be studied.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

The Lovasz θ function, SVMs and finding large dense subgraphs

The Lovasz θ function of a graph, is a fundamental tool in combinatorial optimization and approximation algorithms. Computing θ involves solving a SDP and is extremely expensive even for moderately sized graphs. In this paper we establish that the Lovasz θ function is equivalent to a kernel learning problem related to one class SVM. This interesting connection opens up many opportunities bridging graph theoretic algorithms and machine learning. We show that there exist graphs, which we call SVM−θ graphs, on which the Lovasz θ function can be approximated well by a one-class SVM. This leads to a novel use of SVM techniques to solve algorithmic problems in large graphs e.g. identifying a planted clique of size Θ(n√) in a random graph G(n,12). A classic approach for this problem involves computing the θ function, however it is not scalable due to SDP computation. We show that the random graph with a planted clique is an example of SVM−θ graph, and as a consequence a SVM based approach easily identifies the clique in large graphs and is competitive with the state-of-the-art. Further, we introduce the notion of a ''common orthogonal labeling'' which extends the notion of a ''orthogonal labelling of a single graph (used in defining the θ function) to multiple graphs. The problem of finding the optimal common orthogonal labelling is cast as a Multiple Kernel Learning problem and is used to identify a large common dense region in multiple graphs. The proposed algorithm achieves an order of magnitude scalability compared to the state of the art.

Stereoselective geminal difunctionalization of vinyl arenes mediated by the bromonium ion

An anti-Markovnikov geminal oxyamination of styrenyl alkenes in an intermolecular fashion using the umpolung strategy mediated by the bromonium ion is reported. Isotope labeling studies confirm the migration of the phenyl group in the semipinacol rearrangement.

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

In vitro exposure of tobacco specific nitrosamines decreases the rat lung phospholipids by enhanced phospholipase A(2) activity

Tobacco-specific nitrosamines (TSNA) have implications in the pathogenesis of various lung diseases and conditions are prevalent even in non-smokers. N-nitrosonornicotine (NNN) and 4-(methyl nitrosamino)-1-(3-pyridyl)-1-butanone (NNK) are potent pulmonary carcinogens present in tobacco product and are mainly responsible for lung cancer. TSNA reacts with pulmonary surfactants, and alters the surfactant phospholipid. The present study was undertaken to investigate the in vitro exposure of rat lung tissue slices to NNK or NNN and to monitor the phospholipid alteration by P-32]orthophosphate labeling. Phospholipid content decreased significantly in the presence of either NNK or NNN with concentration and time dependent manner. Phosphatidylcholine (PC) is the main phospholipid of lung and significant reduction was observed in PC similar to 61%, followed by phosphatidylglycerol (PG) with 100 mu M of NNK, whereas NNN treated tissues showed a reduction in phosphatidylserine (PS) similar to 60% and PC at 250 mu M concentration. The phospholipase A(2) assays and expression studies reveal that both compounds enhanced phospholipid hydrolysis, thereby reducing the phospholipid content. Collectively, our data demonstrated that both NNK and NNN significantly influenced the surfactant phospholipid level by enhanced phospholipase A(2) activity. (C) 2014 Elsevier Ltd. All rights reserved.

STAT-1 expression is regulated by IGFBP-3 in malignant glioma cells and is a strong predictor of poor survival in patients with glioblastoma Laboratory investigation

Object. Insulin-like growth factor binding proteins (IGEBPs) have been implicated in the pathogenesis of glioma. In a previous study the authors demonstrated that IGFBP-3 is a novel glioblastoma biomarker associated with poor survival. Since signal transducer and activator of transcription 1 (STAT-1) has been shown to be regulated by IGFBP-3 during chondrogenesis and is a prosurvival and radioresistant molecule in different tumors, the aim in the present study was to explore the functional significance of IGFBP-3 in malignant glioma cells, to determine if STAT-1 is indeed regulated by IGFBP-3, and to study the potential of STAT-1 as a biomarker in glioblastoma. Methods. The functional significance of IGFBP-3 was investigated using the short hairpin (sh)RNA gene knockdown approach on U251MG cells. STAT-1 regulation by IGFBP-3 was tested on U251MG and U87MG cells by shRNA gene knockdown and exogenous treatment with recombinant IGFBP-3 protein. Subsequently, the expression of STAT-1 was analyzed with real-time reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC) in glioblastoma and control brain tissues. Survival analyses were done on a uniformly treated prospective cohort of adults with newly diagnosed glioblastoma (136 patients) using Kaplan-Meier and Cox regression models. Results. IGFBP-3 knockdown significantly impaired proliferation, motility, migration, and invasive capacity of U251MG cells in vitro (p < 0.005). Exogenous overexpression of IGFBP-3 in U251MG and U87MG cells demonstrated STAT-1 regulation. The mean transcript levels (by real-time RT-PCR) and the mean labeling index of STAT-1 (by IHC) were significantly higher in glioblastoma than in control brain tissues (p = 0.0239 and p < 0.001, respectively). Multivariate survival analysis revealed that STAT-1 protein expression (HR 1.015, p = 0.033, 95% CI 1.001-1.029) along with patient age (HR 1.025, p = 0.005, 95% CI 1.008-1.042) were significant predictors of shorter survival in patients with glioblastoma. Conclusions. IGFBP-3 influences tumor cell proliferation, migration, and invasion and regulates STAT-1 expression in malignant glioma cells. STAT-1 is overexpressed in human glioblastoma tissues and emerges as a novel prognostic biomarker.

Periodically Grafted Amphiphilic Copolymers: Effects of Steric Crowding and Reversal of Amphiphilicity

Two series of periodically clickable polyesters were prepared; one of them carries alkylene segments along its backbone, whereas the other carries poly(ethylene glycol) (PEG) segments. These polyesters were clicked with either MPEG-350 azide or docosyl (C22) azide to yield periodically grafted amphiphilic copolymers (PGACs) carrying either flexible hydrophilic or crystallizable hydrophobic backbone segments. The immiscibility between hydrocarbon and PEG segments causes both of these systems to fold in either a zigzag or hairpin-like conformation; the hairpin-like conformation appears to be preferred when flexible PEG segments are present in the backbone. The folded chains further reorganize in the solid state to develop a lamellar morphology that permits the collocation of the PEG and hydrocarbon (HC) segments within alternate domains; evidence for the self-segregation was gained from DSC, SAXS, and AFM studies. SAXS studies revealed the formation of an extended lamellar structure, whereas AFM images showed uniform layered morphology with layer heights that matched reasonably well with the interlamellar spacing obtained from the SAXS study. Labeling One representative PGAC, carrying crystallizable long alkylene segments in the backbone and pendant PEG-350 side chains, with a small mole fraction of pyrene fluorophore permitted the examination of the conformational transition that occurs upon going from a good to a poor solvent; this single-chain folded conformation, we postulate, is the intermediate that organizes into the lamellar morphology.

Biocompatibility property of 100% strontium-substituted SiO2-Al2O3-P2O5-CaO-CaF2 glass ceramics over 26 weeks implantation in rabbit model: Histology and micro-Computed Tomography analysis

One of the desired properties for any new biomaterial composition is its long-term stability in a suitable animal model and such property cannot be appropriately assessed by performing short-term implantation studies. While hydroxyapatite (HA) or bioglass coated metallic biomaterials are being investigated for in vivo biocompatibility properties, such study is not extensively being pursued for bulk glass ceramics. In view of their inherent brittle nature, the implant stability as well as impact of long-term release of metallic ions on bone regeneration have been a major concern. In this perspective, the present article reports the results of the in vivo implantation experiments carried out using 100% strontium (Sr)-substituted glass ceramics with the nominal composition of 4.5 SiO2-3Al(2)O(3)-1.5P(2)O(5)-3SrO-2SrF(2) for 26 weeks in cylindrical bone defects in rabbit model. The combination of histological and micro-computed tomography analysis provided a qualitative and quantitative understanding of the bone regeneration around the glass ceramic implants in comparison to the highly bioactive HA bioglass implants (control). The sequential polychrome labeling of bone during in vivo osseointegration using three fluorochromes followed by fluorescence microscopy observation confirmed homogeneous bone formation around the test implants. The results of the present study unequivocally confirm the long-term implant stability as well as osteoconductive property of 100% Sr-substituted glass ceramics, which is comparable to that of a known bioactive implant, that is, HA-based bioglass. (c) 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 103B: 1168-1179, 2015.

Characterization of Precursor PfHsp60 in Plasmodium falciparum Cytosol during Its Asexual Development in Human Erythrocytes

Mitochondrial heat shock protein 60 (Hsp60) is a nuclear encoded gene product that gets post-translationally translocated into the mitochondria. Using multiple approaches such as immunofluorescence experiments, isoelectric point analysis with two-dimensional gel electrophoresis, and mass spectrometric identification of the signal peptide, we show that Hsp60 from Plasmodium falciparum (PfHsp60) accumulates in the parasite cytoplasm during the ring, trophozoite, and schizont stages of parasite development before being imported into the parasite mitochondria. Using co-immunoprecipitation experiments with antibodies specific to cytoplasmic PfHsp90, PfHsp70-1, and PfHsp60, we show association of precursor PfHsp60 with cytoplasmic chaperone machinery. Metabolic labeling involving pulse and chase indicates translocation of the precursor pool into the parasite mitochondrion during chase. Analysis of results obtained with Geldanamycin treatment confirmed precursor PfHsp60 to be one of the clients for PfHsp90. Cytosolic chaperones bind precursor PfHsp60 prior to its import into the mitochondrion of the parasite. Our data suggests an inefficient co-ordination in the synthesis and translocation of mitochondrial PfHsp60 during asexual growth of malaria parasite in human erythrocytes.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

Glioblastoma-derived Macrophage Colony-stimulating Factor (MCSF) Induces Microglial Release of Insulin-like Growth Factor-binding Protein 1 (IGFBP1) to Promote Angiogenesis

Glioblastoma (grade IV glioma/GBM) is the most common primary adult malignant brain tumor with poor prognosis. To characterize molecular determinants of tumor-stroma interaction in GBM, we profiled 48 serum cytokines and identified macrophage colony-stimulating factor (MCSF) as one of the elevated cytokines in sera from GBM patients. Both MCSF transcript and protein were up-regulated in GBM tissue samples through a spleen tyrosine kinase (SYK)-dependent activation of the PI3K-NF kappa B pathway. Ectopic overexpression and silencing experiments revealed that glioma-secreted MCSF has no role in autocrine functions and M2 polarization of macrophages. In contrast, silencing expression of MCSF in glioma cells prevented tube formation of human umbilical vein endothelial cells elicited by the supernatant from monocytes/microglial cells treated with conditioned medium from glioma cells. Quantitative proteomics based on stable isotope labeling by amino acids in cell culture showed that glioma-derived MCSF induces changes in microglial secretome and identified insulin-like growth factor-binding protein 1 (IGFBP1) as one of the MCSF-regulated proteins secreted by microglia. Silencing IGFBP1 expression in microglial cells or its neutralization by an antibody reduced the ability of supernatants derived from microglial cells treated with glioma cell-conditioned medium to induce angiogenesis. In conclusion, this study shows up-regulation of MCSF in GBM via a SYK-PI3K-NF kappa B-dependent mechanism and identifies IGFBP1 released by microglial cells as a novel mediator of MCSF-induced angiogenesis, of potential interest for developing targeted therapy to prevent GBM progression.

Epithelial atrophy in oral submucous fibrosis is mediated by copper (II) and arecoline of areca nut

Exposure of oral cavity to areca nut is associated with several pathological conditions including oral submucous fibrosis (OSF). Histopathologically OSF is characterized by epithelial atrophy, chronic inflammation, juxtaepithelial hyalinization, leading to fibrosis of submucosal tissue and affects 0.5% of the population in the Indian subcontinent. As the molecular mechanisms leading to atrophied epithelium and fibrosis are poorly understood, we studied areca nut actions on human keratinocyte and gingival fibroblast cells. Areca nut water extract (ANW) was cytotoxic to epithelial cells and had a pro-proliferative effect on fibroblasts. This opposite effect of ANW on epithelial and fibroblast cells was intriguing but reflects the OSF histopathology such as epithelial atrophy and proliferation of fibroblasts. We demonstrate that the pro-proliferative effects of ANW on fibroblasts are dependent on insulin-like growth factor signalling while the cytotoxic effects on keratinocytes are dependent on the generation of reactive oxygen species. Treatment of keratinocytes with arecoline which is a component of ANW along with copper resulted in enhanced cytotoxicity which becomes comparable to IC50 of ANW. Furthermore, studies using cyclic voltammetry, mass spectrometry and plasmid cleavage assay suggested that the presence of arecoline increases oxidation reduction potential of copper leading to enhanced cleavage of DNA which could generate an apoptotic response. Terminal deoxynucleotidyl transferase dUTP Nick End Labeling assay and Ki-67 index of OSF tissue sections suggested epithelial apoptosis, which could be responsible for the atrophy of OSF epithelium.

A Label-Free Multisensing Immunosensor Based on Imaging Ellipsometry

An immunosensor based on imaging ellipsometry and its potential applications was demonstrated in this paper. It has been proven a fast, reliable, and convenient method to quantify the thickness distribution of protein layers or detect protein concentration in solution. Combined with a protein chip, the immunosensor was able to detect multiple analytes simultaneously without any labeling. Preliminary results demonstrated how this immunosensor could be used to monitor several independent biospecific binding processes in real-time and in situ conditions.