Endoplasmic reticulum targeting tumour selective photocytotoxic oxovanadium(IV) complexes having vitamin-B6 and acridinyl moieties

Oxovanadium(IV) complexes of vitamin-B6 Schiff base, viz., VO(HL1/L-2/L-3)(B)] Cl (1-4), where B is 2,2'-bipyridine (bpy in 1 and 2), 11-(9-acridinyl)dipyrido3,2-a:2',3'-c]phenazine (acdppz in 3 and 4), H2L1 center dot HCl is 3-hydroxy-5-(hydroxymethyl)-4-(((2-hydroxyphenyl)imino)methyl)-2-methylp yridin-1-ium chloride (in 1 and 4), HL2 is 2-(((2-(1H-imidazol-4-yl)ethyl) imino)methyl) phenol (in 2) and HL3 is 4-(((2-(1H-imidazol-4- yl)ethyl)imino)methyl)-5-(hydroxymethyl)-2-methylpyridin-3-ol (in 3) were synthesized, characterized and their cellular uptake, photo-activated cytotoxicity and intracellular localization were studied. Complexes 1a, as the perchlorate salt of 1, and 2a, as the hexafluorophosphate salt of 2, were structurally characterized. Vitamin-B6 transporting membrane carrier (VTC) mediated entry into tumour cells in preference to the normal ones seems to be responsible for the higher cellular uptake of the complexes into HeLa and MCF-7 cells over MCF-10A cells. Complexes 3 and 4 having acdppz as the photosensitizer exhibit remarkable photocytotoxicity in these cancer cells giving IC50 of < 0.9 mu M. The complexes remain non-toxic in the dark. The complexes show photo-induced apoptotic cell death via singlet oxygen (O-1(2)) generation. Fluorescence microscopy reveals specific localization of complex 4 to endoplasmic reticulum (ER) and generation of O-1(2) possibly leads to apoptotic cell death by triggering ER stress response (ERSR).

Endoplasmic reticulum targeting tumour selective photocytotoxic oxovanadium(IV) complexes having vitamin-B6 and acridinyl moieties

Oxovanadium(IV) complexes of vitamin-B6 Schiff base, viz., VO(HL1/L-2/L-3)(B)] Cl (1-4), where B is 2,2'-bipyridine (bpy in 1 and 2), 11-(9-acridinyl)dipyrido3,2-a:2',3'-c]phenazine (acdppz in 3 and 4), H2L1 center dot HCl is 3-hydroxy-5-(hydroxymethyl)-4-(((2-hydroxyphenyl)imino)methyl)-2-methylp yridin-1-ium chloride (in 1 and 4), HL2 is 2-(((2-(1H-imidazol-4-yl)ethyl) imino)methyl) phenol (in 2) and HL3 is 4-(((2-(1H-imidazol-4- yl)ethyl)imino)methyl)-5-(hydroxymethyl)-2-methylpyridin-3-ol (in 3) were synthesized, characterized and their cellular uptake, photo-activated cytotoxicity and intracellular localization were studied. Complexes 1a, as the perchlorate salt of 1, and 2a, as the hexafluorophosphate salt of 2, were structurally characterized. Vitamin-B6 transporting membrane carrier (VTC) mediated entry into tumour cells in preference to the normal ones seems to be responsible for the higher cellular uptake of the complexes into HeLa and MCF-7 cells over MCF-10A cells. Complexes 3 and 4 having acdppz as the photosensitizer exhibit remarkable photocytotoxicity in these cancer cells giving IC50 of < 0.9 mu M. The complexes remain non-toxic in the dark. The complexes show photo-induced apoptotic cell death via singlet oxygen (O-1(2)) generation. Fluorescence microscopy reveals specific localization of complex 4 to endoplasmic reticulum (ER) and generation of O-1(2) possibly leads to apoptotic cell death by triggering ER stress response (ERSR).

Prior image based temporally constrained reconstruction algorithm for magnetic resonance guided high intensity focused ultrasound

Purpose: A prior image based temporally constrained reconstruction ( PITCR) algorithm was developed for obtaining accurate temperature maps having better volume coverage, and spatial, and temporal resolution than other algorithms for highly undersampled data in magnetic resonance (MR) thermometry. Methods: The proposed PITCR approach is an algorithm that gives weight to the prior image and performs accurate reconstruction in a dynamic imaging environment. The PITCR method is compared with the temporally constrained reconstruction (TCR) algorithm using pork muscle data. Results: The PITCR method provides superior performance compared to the TCR approach with highly undersampled data. The proposed approach is computationally expensive compared to the TCR approach, but this could be overcome by the advantage of reconstructing with fewer measurements. In the case of reconstruction of temperature maps from 16% of fully sampled data, the PITCR approach was 1.57x slower compared to the TCR approach, while the root mean square error using PITCR is 0.784 compared to 2.815 with the TCR scheme. Conclusions: The PITCR approach is able to perform more accurate reconstructions of temperature maps compared to the TCR approach with highly undersampled data in MR guided high intensity focused ultrasound. (C) 2015 American Association of Physicists in Medicine.

Targeting human telomeric G-quadruplex DNA with curcumin and its synthesized analogues under molecular crowding conditions

The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.

Targeting human telomeric G-quadruplex DNA with curcumin and its synthesized analogues under molecular crowding conditions

The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.

PolyMage: Automatic Optimization for Image Processing Pipelines

This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious. The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.

Mitochondria-Targeting Iron(III) Catecholates for Photoactivated Anticancer Activity under Red Light

Iron(III) catecholates Fe(R-bpa)(R-dopa)Cl] (1, 2) with a triphenylphosphonium (TPP) moiety, where R-bpa is 2-(TPP-N,N-bis((pyridin-2-yl)methyl)ethanamine) chloride (TPPbpa) and R-dopa is 4-{2-(anthracen-9-yl)methylamino]ethyl}benzene-1,2-diol (andopa, 1) or 4-{2-(pyren-1-yl)-methylamino]ethyl}benzene-1,2-diol (pydopa, 2), were synthesized and their photocytotoxicity studied. Complexes 3 and 4 with phenyl-N,N-bis(pyridin-2-yl)methyl]methanamine (phbpa) were used as controls. The catecholate complexes showed an absorption band near 720 nm. The 5e(-) paramagnetic complexes showed a Fe-III/Fe-II irreversible response near -0.45 V and a quasi-reversible catechol/semiquinone couple near 0.5 V versus saturated calomel electrode (SCE) in DMF/0.1 M tetrabutylammonium perchlorate. They showed photocytotoxicity in red/visible light in HeLa, HaCaT, MCF-7, and A549 cells. Complexes 1 and 2 displayed mitochondrial localization, reactive oxygen species (ROS) generation under red light, and apoptotic cell death. Control complexes 3 and 4 exhibited uniform distribution throughout the cell. The complexes showed DNA photocleavage under red light (785 nm), forming hydroxyl radicals as the ROS.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Green Nanosilver as Reinforcing Eco-Friendly Additive to Epoxy Coating for Augmented Anticorrosive and Antimicrobial Behavior

Epoxy resin GY250 representing diglycidyl ethers of bisphenol-A (DGEBA) was reinforced with 1, 3 and 5 wt % of surface functionalized silver nanoparticles (F-AgNPs) which were synthesized using Couroupita guianensis leaves extract with a view of augmenting the corrosion control property of the epoxy resin and also imparting antimicrobial activity to epoxy coatings on mild steel. Corrosion resistance of the coatings was evaluated by EIS, potentiodynamic polarization studies and cross scratch tests. AFM, SEM, HRTEM and EDX were utilized to investigate the surface topography, morphology and elemental composition of the coatings on MS specimens. Results showed that the corrosion resistance, hardness and T-g of the DGEBA/F-AgNPs coatings increased at 1 wt % of F-AgNPs. The DGEBA/F-AgNPs coatings also offered manifold antimicrobial protection to the MS surfaces by inhibiting the growth of biofilm forming bacteria like P. aeruginosa, B. subtilis, the most common human pathogen E. coli and the most virulent human pathogenic yeast C. albicans.

FIVDL: Fingerprint Image Verification using Dictionary Learning

Fingerprints are used for identification in forensics and are classified into Manual and Automatic. Automatic fingerprint identification system is classified into Latent and Exemplar. A novel Exemplar technique of Fingerprint Image Verification using Dictionary Learning (FIVDL) is proposed to improve the performance of low quality fingerprints, where Dictionary learning method reduces the time complexity by using block processing instead of pixel processing. The dynamic range of an image is adjusted by using Successive Mean Quantization Transform (SMQT) technique and the frequency domain noise is reduced using spectral frequency Histogram Equalization. Then, an adaptive nonlinear dynamic range adjustment technique is utilized to determine the local spectral features on corresponding fingerprint ridge frequency and orientation. The dictionary is constructed using spatial fundamental frequency that is determined from the spectral features. These dictionaries help in removing the spurious noise present in fingerprints and reduce the time complexity by using block processing instead of pixel processing. Further, dictionaries are used to reconstruct the image for matching. The proposed FIVDL is verified on FVC database sets and Experimental result shows an improvement over the state-of-the-art techniques. (C) 2015 The Authors. Published by Elsevier B.V.

IMAGE DENOISING USING OPTIMALLY WEIGHTED BILATERAL FILTERS: A SURE AND FAST APPROACH

The bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.