DNA targeting polyaza macrobicyclic dizinc(II) complexes promoting high in vitro caspase dependent anti-proliferative activity against human carcinoma cancer cells

A series of macrobicyclic dizinc(II) complexes Zn2L1-2B](ClO4)(4) (1-6) have been synthesized and characterized (L1-2 are polyaza macrobicyclic binucleating ligands, and B is the N,N-donor heterocyclic base (viz. 2,2'-bipyridine (bipy) and 1,10-phenanthroline (phen)). The DNA and protein binding, DNA hydrolysis and anticancer activity of these complexes were investigated. The interactions of complexes 1-6 with calf thymus DNA were studied by spectroscopic techniques, including absorption, fluorescence and CD spectroscopy. The DNA binding constant values of the complexes were found to range from 2.80 x 10(5) to 5.25 x 10(5) M-1, and the binding affinities are in the following order: 3 > 6 > 2 > 5 > 1 > 4. All the dizinc(II) complexes 1-6 are found to effectively promote the hydrolytic cleavage of plasmid pBR322 DNA under anaerobic and aerobic conditions. Kinetic data for DNA hydrolysis promoted by 3 and 6 under physiological conditions give observed rate constants (k(obs)) of 5.56 +/- 0.1 and 5.12 +/- 0.2 h(-1), respectively, showing a 10(7)-fold rate acceleration over the uncatalyzed reaction of dsDNA. Remarkably, the macrobicyclic dizinc(II) complexes 1-6 bind and cleave bovine serum albumin (BSA), and effectively promote the caspase-3 and caspase-9 dependent deaths of HeLa and BeWo cancer cells. The cytotoxicity of the complexes was further confirmed by lactate dehydrogenase enzyme levels in cancer cell lysate and content media.

Nuclear targeting terpyridine iron(II) complexes for cellular imaging and remarkable photocytotoxicity

Iron(II) complexes Fe(L)(2)](2+) as perchlorate (1-3) and chloride (1a-3a) salts, where L is 4'-phenyl-2,2':6',2 `'-terpyridine (phtpy in 1, 1a), 4'-(9-anthracenyl)-2,2':6',2 `'-terpyridine (antpy in 2, 2a) and 4'-(1-pyrenyl)-2,2':6',2 `'-terpyridine (pytpy in 3, 3a), were prepared and their photocytotoxicity studied. The diamagnetic complexes 1-3 having an FeN6 core showed an Fe(III)-Fe(II) redox couple near 1.0 V vs. saturated calomel electrode in MeCN-0.1 M tetrabutylammonium perchlorate. Complexes 2 and 3, in addition, displayed a quasi-reversible ligand-based redox process near 0.0 V. The redox and spectral properties are rationalized from the theoretical studies. The complexes bind to DNA in a partial intercalative mode. The pytpy complex efficiently photo-cleaves DNA in green light via superoxide and hydroxyl radical formation. The antpy and pytpy complexes exhibited a remarkable photocytotoxic effect in HeLa cancer cells (IC50, similar to 9 mu M) in visible light (400-700 nm), while remaining essentially nontoxic in dark (IC50, similar to 90 mu M). Formation of reactive oxygen species (ROS) inside the HeLa cells was evidenced from the fluorescence enhancement of dichlorofluorescein upon treatment with the pytpy complex followed by photo-exposure. The antpy and pytpy complexes were used for cellular imaging. Confocal imaging and dual staining study using propidium iodide (PI) showed nuclear localization of the complexes. (c) 2012 Elsevier Inc. All rights reserved.

Data-resolution based optimal choice of minimum required measurements for image-guided diffuse optical tomography

Image-guided diffuse optical tomography has the advantage of reducing the total number of optical parameters being reconstructed to the number of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem from underdetermined in nature to overdetermined. In such cases, the minimum required measurements might be far less compared to those of the traditional diffuse optical imaging. An approach to choose these optimally based on a data-resolution matrix is proposed, and it is shown that such a choice does not compromise the reconstruction performance. (C) 2013 Optical Society of America

Fast Likelihood Computation in Speech Recognition using Matrices

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for Large Vocabulary Continuous Speech Recognition (LVCSR) systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication. In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on 1,138 work vocabulary RM1 task and 6,224 word vocabulary TIMIT task using Sphinx 3.7 system show that, for a typical case the matrix multiplication based approach leads to overall speedup of 46 % on RM1 task and 115 % for TIMIT task. Our low-rank approximation methods provide a way for trading off recognition accuracy for a further increase in computational performance extending overall speedups up to 61 % for RM1 and 119 % for TIMIT for an increase of word error rate (WER) from 3.2 to 3.5 % for RM1 and for no increase in WER for TIMIT. We also express pairwise Euclidean distance computation phase in Dynamic Time Warping (DTW) in terms of matrix multiplication leading to saving of approximately of computational operations. In our experiments using efficient implementation of matrix multiplication, this leads to a speedup of 5.6 in computing the pairwise Euclidean distances and overall speedup up to 3.25 for DTW.

MULTI-OBJECTIVE GENETIC ALGORITHM FOR EFFICIENT POINT MATCHING IN MULTI-SENSOR SATELLITE IMAGE

This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Active-contour-based automated image quantitation techniques for Western Blot analysis

Western Blot analysis is an analytical technique used in Molecular Biology, Biochemistry, Immunogenetics and other Molecular Biology studies to separate proteins by electrophoresis. The procedure results in images containing nearly rectangular-shaped blots. In this paper, we address the problem of quantitation of the blots using automated image processing techniques. We formulate a special active contour (or snake) called Oblong, which locks on to rectangular shaped objects. Oblongs depend on five free parameters, which is also the minimum number of parameters required for a unique characterization. Unlike many snake formulations, Oblongs do not require explicit gradient computations and therefore the optimization is carried out fast. The performance of Oblongs is assessed on synthesized data and Western Blot Analysis images.

Multi-objective optimization of satellite image registration using discrete Pparticle swarm optimisation

A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

Fracture processes of self compacting Concrete using image analysis

The mode I fracture toughness of concrete can be experimentally determined using three point bend beam in conjunction with digital image correlation (DIC). Three different geometrically similar sizes of beams are cast for this study. To study the influence of fly ash and silica fume on fracture toughness of SCC, three SCC mixes are prepared with and without mineral additions. The scanning electron microscope (SEM) images are taken on the fractured surface to add information on fracture process in SCC. From this study, it is concluded that the fracture toughness of SCC with mineral addition is higher when compared to those without mineral addition.

Evaluation of kissing bond in composite adhesive lap joints using digital image correlation: Preliminary studies

The assembly of aerospace and automotive structures in recent years is increasingly carried out using adhesives. Adhesive joints have advantages of uniform stress distribution and less stress concentration in the bonded region. Nevertheless, they may suffer due to the presence of defects in bond line and at the interface or due to improper curing process. While defects like voids, cracks and delaminations present in the adhesive bond line may be detected using different NDE methods, interfacial defects in the form of kissing bond may go undetected. Attempts using advanced ultrasonic methods like nonlinear ultrasound and guided wave inspection to detect kissing bond have met with limited success stressing the need for alternate methods. This paper concerns the preliminary studies carried out on detectability of dry contact kissing bonds in adhesive joints using the Digital Image Correlation (DIC) technique. In this attempt, adhesive joint samples containing varied area of kissing bond were prepared using the glass fiber reinforced composite (GFRP) as substrates and epoxy resin as the adhesive layer joining them. The samples were also subjected to conventional and high power ultrasonic inspection. Further, these samples were loaded till failure to determine the bond strength during which digital images were recorded and analyzed using the DIC method. This noncontact method could indicate the existence of kissing bonds at less than 50% failure load. Finite element studies carried out showed a similar trend. Results obtained from these preliminary studies are encouraging and further tests need to be done on a larger set of samples to study experimental uncertainties and scatter associated with the method. (C) 2013 Elsevier Ltd. All rights reserved.

Bilateral smoothing of gradient vector field and application to image segmentation

Medical image segmentation finds application in computer-aided diagnosis, computer-guided surgery, measuring tissue volumes, locating tumors, and pathologies. One approach to segmentation is to use active contours or snakes. Active contours start from an initialization (often manually specified) and are guided by image-dependent forces to the object boundary. Snakes may also be guided by gradient vector fields associated with an image. The first main result in this direction is that of Xu and Prince, who proposed the notion of gradient vector flow (GVF), which is computed iteratively. We propose a new formalism to compute the vector flow based on the notion of bilateral filtering of the gradient field associated with the edge map - we refer to it as the bilateral vector flow (BVF). The range kernel definition that we employ is different from the one employed in the standard Gaussian bilateral filter. The advantage of the BVF formalism is that smooth gradient vector flow fields with enhanced edge information can be computed noniteratively. The quality of image segmentation turned out to be on par with that obtained using the GVF and in some cases better than the GVF.

Benchmarking recognition results on camera captured word image data sets

We have benchmarked the maximum obtainable recognition accuracy on five publicly available standard word image data sets using semi-automated segmentation and a commercial OCR. These images have been cropped from camera captured scene images, born digital images (BDI) and street view images. Using the Matlab based tool developed by us, we have annotated at the pixel level more than 3600 word images from the five data sets. The word images binarized by the tool, as well as by our own midline analysis and propagation of segmentation (MAPS) algorithm are recognized using the trial version of Nuance Omnipage OCR and these two results are compared with the best reported in the literature. The benchmark word recognition rates obtained on ICDAR 2003, Sign evaluation, Street view, Born-digital and ICDAR 2011 data sets are 83.9%, 89.3%, 79.6%, 88.5% and 86.7%, respectively. The results obtained from MAPS binarized word images without the use of any lexicon are 64.5% and 71.7% for ICDAR 2003 and 2011 respectively, and these values are higher than the best reported values in the literature of 61.1% and 41.2%, respectively. MAPS results of 82.8% for BDI 2011 dataset matches the performance of the state of the art method based on power law transform.

miR-219-5p inhibits receptor tyrosine kinase pathway by targeting EGFR in glioblastoma

Glioblastoma is one of the common types of primary brain tumors with a median survival of 12-15 months. The receptor tyrosine kinase (RTK) pathway is known to be deregulated in 88% of the patients with glioblastoma. 45% of GBM patients show amplifications and activating mutations in EGFR gene leading to the upregulation of the pathway. In the present study, we demonstrate that a brain specific miRNA, miR-219-5p, repressed EGFR by directly binding to its 3'-UTR. The expression of miR-219-5p was downregulated in glioblastoma and the overexpression of miR-219-5p in glioma cell lines inhibited the proliferation, anchorage independent growth and migration. In addition, miR-219-5p inhibited MAPK and PI3K pathways in glioma cell lines in concordance with its ability to target EGFR. The inhibitory effect of miR-219-5p on MAPK and PI3K pathways and glioma cell migration could be rescued by the overexpression of wild type EGFR and vIII mutant of EGFR (both lacking 3'-UTR and thus being insensitive to miR-219-5p) suggesting that the inhibitory effects of miR-219-5p were indeed because of its ability to target EGFR. We also found significant negative correlation between miR-219-5p levels and total as well as phosphorylated forms of EGFR in glioblastoma patient samples. This indicated that the downregulation of miR-219-5p in glioblastoma patients contribute to the increased activity of the RTK pathway by the upregulation of EGFR. Thus, we have identified and characterized miR-219-5p as the RTK regulating novel tumor suppressor miRNA in glioblastoma.

Biotin-conjugated tumour-targeting photocytotoxic iron(III) complexes

Iron(III) complexes FeL(B)] (1-4) of a tetradentate phenolate-based ligand (H3L) and biotin-conjugated dipyridophenazine bases (B), viz. 7-aminodipyrido 3,2-a: 2',3'-c]-phenazine (dppza in 1), (N-dipyrido3,2-a: 2',3'-c]-phenazino) amidobiotin (dppzNB in 2), dipyrido 3,2-a: 2',3'-c]-phenazine-11-carboxylic acid (dppzc in 3) and 2-((2-biotinamido) ethyl) amidodipyrido 3,2-a: 2',3'-c]-phenazine (dppzCB in 4) are prepared, characterized and their interaction with streptavidin and DNA and their photocytotoxicity and cellular uptake in various cells studied. The high-spin iron(III) complexes display Fe(III)/Fe(II) redox couple near -0.7V versus saturated calomel electrode in dimethyl sulfoxide-0.1M tetrabutylammonium perchlorate. The complexes show non-specific interaction with DNA as determined from the binding studies. Complexes with appended biotin moiety show similar binding to streptavidin as that of free biotin, suggesting biotin conjugation to dppz does not cause any loss in its binding affinity to streptavidin. The photocytotoxicity of the complexes is tested in HepG2, HeLa and HEK293 cell lines. Complex 2 shows higher photocytotoxicity in HepG2 cells than in HeLa or HEK293, forming reactive oxygen species. This effect is attributed to the presence of overexpressed sodium-dependent multi-vitamin transporters in HepG2 cells. Microscopic studies in HepG2 cells show internalization of the biotin complexes 2 and 4 essentially occurring by receptor-mediated endocytosis, which is similar to that of native biotin and biotin fluorescein isothiocyanate conjugate.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.