Metal Complexes of Curcumin for Cellular Imaging, Targeting, and Photoinduced Anticancer Activity

CONSPECTUS: Curcumin is a polyphenolic species. As an active ingredient of turmeric, it is well-known for its traditional medicinal properties. The therapeutic values include antioxidant, anti-inflammatory, antiseptic, and anticancer activity with the last being primarily due to inhibition of the transcription factor NF-kappa B besides affecting several biological pathways to arrest tumor growth and its progression. Curcumin with all these positive qualities has only remained a potential candidate for cancer treatment over the years without seeing any proper usage because of its hydrolytic instability involving the diketo moiety in a cellular medium and its poor bioavailability. The situation has changed considerably in recent years with the observation that curcumin in monoanionic form could be stabilized on binding to a metal ion. The reports from our group and other groups have shown that curcumin in the metal-bound form retains its therapeutic potential. This has opened up new avenues to develop curcumin-based metal complexes as anticancer agents. Zinc(II) complexes of curcumin are shown to be stable in a cellular medium. They display moderate cytotoxicity against prostate cancer and neuroblastoma cell lines. A similar stabilization and cytotoxic effect is reported for (arene)ruthenium(II) complexes of curcumin against a variety of cell lines. The half-sandwich 1,3,5-triaza-7-phosphatricyclo-3.3.1.1]decane (RAPTA)-type ruthenium(II) complexes of curcumin are shown to be promising cytotoxic agents with low micromolar concentrations for a series of cancer cell lines. In a different approach, cobalt(III) complexes of curcumin are used for its cellular delivery in hypoxic tumor cells using intracellular agents that reduce the metal and release curcumin as a cytotoxin. Utilizing the photophysical and photochemical properties of the curcumin dye, we have designed and synthesized photoactive curcumin metal complexes that are used for cellular imaging by fluorescence microscopy and damaging the cancer cells on photoactivation in visible light while being minimally toxic in darkness. In this Account, we have made an attempt to review the current status of the chemistry of metal curcumin complexes and present results from our recent studies on curcumin complexes showing remarkable in vitro photocytotoxicity. The undesirable dark toxicity of the complexes can be reduced with suitable choice of the metal and the ancillary ligands in a ternary structure. The complexes can be directed to specific subcellular organelles. Selectivity by targeting cancer cells over normal cells can be achieved with suitable ligand design. We expect that this methodology is likely to provide an impetus toward developing curcumin-based photochemotherapeutics for anticancer treatment and cure.

Field-Portable Microfluidics-Based Imaging Flow Cytometer

Clinical microscopy is a versatile and robust tool used for the diagnosis of a plethora of diseases. However, due to various reasons, it remains inaccessible in resource limited settings. In this paper, we present an automated and cost-effective alternative to microscopy for use in clinical diagnostics. With the use of custom optics and microfluidics, we demonstrate a field-portable imaging flow cytometry system. Using the presented system, we have been able to image 586 cells per second. We demonstrate the clinical relevance of the proposed system by differentiating between suspensions of healthy and sphered RBCs based on high-throughput morphometric analysis. The instrument presented here is a major advancement in the domain of field portable diagnostics as it enables fast and robust quantitative diagnostic testing at the point-of-care.

Deformability Measurement of Single-Cells at High-Throughput With Imaging Flow Cytometry

Disease conditions like malaria, sickle cell anemia, diabetes mellitus, cancer, etc., are known to significantly alter the deformability of certain types of cells (red blood cells, white blood cells, circulating tumor cells, etc.). To determine the cellular deformability, techniques like micropipette aspiration, atomic force microscopy, optical tweezers, quantitative phase imaging have been developed. Many of these techniques have an advantage of determining the single cell deformability with ultrahigh precision. However, the suitability of these techniques for the realization of a deformability based diagnostic tool is questionable as they are expensive and extremely slow to operate on a huge population of cells. In this paper, we propose a technique for high-throughput (800 cells/s) determination of cellular deformability on a single cell basis. This technique involves capturing the image(s) of cells in flow that have undergone deformation under the influence of shear gradient generated by the fluid flowing through the microfluidic channels. Deformability indices of these cells can be computed by performing morphological operations on these images. We demonstrate the applicability of this technique for examining the deformability index on healthy, diabetic, and sphered red blood cells. We believe that this technique has a strong role to play in the realization of a potential tool that uses deformability as one of the important criteria in disease diagnosis.

SeamSeg: Video Object Segmentation using Patch Seams

In this paper, we propose a technique for video object segmentation using patch seams across frames. Typically, seams, which are connected paths of low energy, are utilised for retargeting, where the primary aim is to reduce the image size while preserving the salient image contents. Here, we adapt the formulation of seams for temporal label propagation. The energy function associated with the proposed video seams provides temporal linking of patches across frames, to accurately segment the object. The proposed energy function takes into account the similarity of patches along the seam, temporal consistency of motion and spatial coherency of seams. Label propagation is achieved with high fidelity in the critical boundary regions, utilising the proposed patch seams. To achieve this without additional overheads, we curtail the error propagation by formulating boundary regions as rough-sets. The proposed approach out-perform state-of-the-art supervised and unsupervised algorithms, on benchmark datasets.

MnFe2O4-Fe3O4 core-shell nanoparticles as a potential contrast agent for magnetic resonance imaging

In recent years, magnetic core-shell nanoparticles have received widespread attention due to their unique properties that can be used for various applications. We introduce here a magnetic core-shell nanoparticle system for potential application as a contrast agent in magnetic resonance imaging (MRI). MnFe2O4-Fe3O4 core-shell nanoparticles were synthesized by the wet-chemical synthesis method. Detailed structural and compositional charaterization confirmed the formation of a core-shell microstructure for the nanoparticles. Magnetic charaterization revealed the superparamagnetic nature of the as-synthesized core-shell nanoparticles. Average size and saturation magnetization values obtained for the as-synthesized core-shell nanoparticle were 12.5 nm and 69.34 emu g(-1) respectively. The transverse relaxivity value of the water protons obtained in the presence of the core-shell nanoparticles was 184.1 mM(-1) s(-1). To investigate the effect of the core-shell geometry towards enhancing the relaxivity value, transverse relaxivity values were also obtained in the presence of separately synthesized single phase Fe3O4 and MnFe2O4 nanoparticles. Average size and saturation magnetization values for the as-synthesized Fe3O4 nanoparticles were 12 nm and 65.8 emu g(-1) respectively. Average size and saturation magnetization values for the MnFe2O4 nanoparticles were 9 nm and 61.5 emu g(-1) respectively. The transverse relaxivity value obtained in the presence of single phase Fe3O4 and MnFe2O4 nanoparticles was 96.6 and 83.2 mM(-1) s(-1) respectively. All the nanoparticles (core-shell and single phase) were coated with chitosan by a surfactant exchange reaction before determining the relaxivity values. For similar nanoparticle sizes and saturation magnetization values, the highest value of the transverse relaxivity in the case of core-shell nanoparticles clearly illustrated that the difference in the magnetic nature of the core and shell phases in the core-shell nanoparticles creates greater magnetic inhomogeneity in the surrounding medium yielding a high value for proton relaxivity. The MnFe2O4-Fe3O4 core-shell nanoparticles exhibited extremely low toxicity towards the MCF-7 cell line. Taken together, this opens up new avenues for the use of core-shell nanoparticles in MRI.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

Ray tracing based path-length calculations for polarized light tomographic imaging

A ray tracing based path length calculation is investigated for polarized light transport in a pixel space. Tomographic imaging using polarized light transport is promising for applications in optical projection tomography of small animal imaging and turbid media with low scattering. Polarized light transport through a medium can have complex effects due to interactions such as optical rotation of linearly polarized light, birefringence, diattenuation and interior refraction. Here we investigate the effects of refraction of polarized light in a non-scattering medium. This step is used to obtain the initial absorption estimate. This estimate can be used as prior in Monte Carlo (MC) program that simulates the transport of polarized light through a scattering medium to assist in faster convergence of the final estimate. The reflectance for p-polarized (parallel) and s-polarized (perpendicular) are different and hence there is a difference in the intensities that reach the detector end. The algorithm computes the length of the ray in each pixel along the refracted path and this is used to build the weight matrix. This weight matrix with corrected ray path length and the resultant intensity reaching the detector for each ray is used in the algebraic reconstruction (ART) method. The proposed method is tested with numerical phantoms for various noise levels. The refraction errors due to regions of different refractive index are discussed, the difference in intensities with polarization is considered. The improvements in reconstruction using the correction so applied is presented. This is achieved by tracking the path of the ray as well as the intensity of the ray as it traverses through the medium.

Limited-view light sheet fluorescence microscopy for three dimensional volume imaging

We propose and demonstrate a limited-view light sheet microscopy (LV-LSM) for three dimensional (3D) volume imaging. Realizing that longer and frequent image acquisition results in significant photo-bleaching, we have taken limited angular views (18 views) of the macroscopic specimen and integrated with maximum likelihood (ML) technique for reconstructing high quality 3D volume images. Existing variants of light-sheet microscopy require both rotation and translation with a total of approximately 10-fold more views to render a 3D volume image. Comparatively, LV-LSM technique reduces data acquisition time and consequently minimizes light-exposure by many-folds. Since ML is a post-processing technique and highly parallelizable, this does not cost precious imaging time. Results show noise-free and high contrast volume images when compared to the state-of-the-art selective plane illumination microscopy. (C) 2015 AIP Publishing LLC.

Clean localization super-resolution microscopy for 3D biological imaging

We propose clean localization microscopy (a variant of fPALM) using a molecule filtering technique. Localization imaging involves acquiring a large number of images containing single molecule signatures followed by one-to-one mapping to render a super-resolution image. In principle, this process can be repeated for other z-planes to construct a 3D image. But, single molecules observed from off-focal planes result in false representation of their presence in the focal plane, resulting in incorrect quantification and analysis. We overcome this with a single molecule filtering technique that imposes constraints on the diffraction limited spot size of single molecules in the image plane. Calibration with sub-diffraction size beads puts a natural cutoff on the actual diffraction-limited size of single molecules in the focal plane. This helps in distinguishing beads present in the focal plane from those in the off-focal planes thereby providing an estimate of the single molecules in the focal plane. We study the distribution of actin (labeled with a photoactivatable CAGE 552 dye) in NIH 3T3 mouse fibroblast cells. (C) 2016 Author(s).

Ultrafine graphene oxide-CoFe2O4 nanoparticle composite as T-1 and T-2 contrast agent for magnetic resonance imaging

Graphene oxide-CoFe2O4 nanoparticle composites were synthesized using a two step synthesis method in which graphene oxide was initially synthesized followed by precipitation of CoFe2O4 nanoparticles in a reaction mixture containing graphene oxide. Samples were extracted from the reaction mixture at different times at 80 degrees C. All the extracted samples contained CoFe2O4 nanoparticles formed over the graphene oxide. It was observed that the increase in the reflux time significantly increased the saturation magnetization value for the superparamagnetic nanoparticles in the composite. It was also noticed that the size of the nanoparticles increased with increase in the reflux time. Transverse relaxivity of the water protons increased monotonically with increase in the reflux time. Whereas, the longitudinal relaxivity value initially increased and then decreased with the reflux time. Graphene oxide-CoFe2O4 nanoparticle composites also exhibit biocompatibility towards the MCF-7 cell line.

CROWD FLOW SEGMENTATION IN COMPRESSED DOMAIN USING CRF

Crowd flow segmentation is an important step in many video surveillance tasks. In this work, we propose an algorithm for segmenting flows in H.264 compressed videos in a completely unsupervised manner. Our algorithm works on motion vectors which can be obtained by partially decoding the compressed video without extracting any additional features. Our approach is based on modelling the motion vector field as a Conditional Random Field (CRF) and obtaining oriented motion segments by finding the optimal labelling which minimises the global energy of CRF. These oriented motion segments are recursively merged based on gradient across their boundaries to obtain the final flow segments. This work in compressed domain can be easily extended to pixel domain by substituting motion vectors with motion based features like optical flow. The proposed algorithm is experimentally evaluated on a standard crowd flow dataset and its superior performance in both accuracy and computational time are demonstrated through quantitative results.