23 research outputs found
Abstract LB-070: Nano self-assemblies of paclitaxel for breast cancer treatment
No full textAbstract
Objectives: Breast cancer (BC) is second leading cause of cancer-related deaths in the United States. Paclitaxel (Ptx) is an FDA-approved and frequently used chemotherapeutic agent against various cancers, including BC. However its adverse side effects and chemoresistance against it, limits its use in the clinic. Minimizing the toxicity issues of Ptx through nanoparticle technology (such as Ptx bound to human serum albumin nanoformulation, i.e., Abraxane®) is feasible and has displayed encouraging outcomes. With this background, we aim to generate Ptx self-assemblies (PSAs) using various biocompatible polymers and surfactants, and to evaluate its efficacy against BC cells.
Methods: PSAs composed of Ptx dispersion or a core formation with a polymer at a weight ratio of 1:50. The extent of Ptx assembly/binding efficiency was determined using a fluorescence quenching study. FT-IR spectral study was employed to confirm the presence of Ptx in PSAs. The optimal polymers for forming PSAs were identified through measurement of particle size, zeta potential and TEM. Another check point of generating a better PSAs was evaluated by its extent of cellular internalization in BC cells and through hemolytic assay. Finally, the finalized PSAs were examined for in vitro activity in BC cells using proliferation, colony formation, and immunoblotting assays.
Results: We screened 22 biocompatible polymers for PSA formation, out of which 8 were finalized due to excellent Ptx binding profiles, appropriate particle size ranges (40-300 nm), zeta potentials (-14.0 to -4.0 mV), and superior internalization in BC cells. The optimized PSAs exhibited enhanced anti-cancer capability in MCF-7 and MDA-MB-231 BC cells in proliferation and colony formation assays, compared to free Ptx. This was further affirmed through tubulin stabilization studies. Further, PSA treatment in BC cells demonstrates a distinct induction of the expression of apoptosis-associated proteins and distinct downregulation of anti-apoptotic proteins.
Conclusion: Overall this study suggests a simple and feasible Ptxl self-assembly approach for achieving superior anti-cancer activity with Ptx.
Citation Format: Prashanth Kumar Bhusetty Nagesh, Pallabita Chowdhury, Sumeeth S. Chauhan, Elham Hatami, Sheema Khan, Bilal Hafeez, Subhash C. Chauhan, Meena Jaggi, Murali M. Yallapu. Nano self-assemblies of paclitaxel for breast cancer treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-070. doi:10.1158/1538-7445.AM2017-LB-070</jats:p
Land Use and Land Cover Classification Using Deep Learning Techniques
No full textabstract: Large datasets of sub-meter aerial imagery represented as orthophoto mosaics are widely available today, and these data sets may hold a great deal of untapped information. This imagery has a potential to locate several types of features; for example, forests, parking lots, airports, residential areas, or freeways in the imagery. However, the appearances of these things vary based on many things including the time that the image is captured, the sensor settings, processing done to rectify the image, and the geographical and cultural context of the region captured by the image. This thesis explores the use of deep convolutional neural networks to classify land use from very high spatial resolution (VHR), orthorectified, visible band multispectral imagery. Recent technological and commercial applications have driven the collection a massive amount of VHR images in the visible red, green, blue (RGB) spectral bands, this work explores the potential for deep learning algorithms to exploit this imagery for automatic land use/ land cover (LULC) classification. The benefits of automatic visible band VHR LULC classifications may include applications such as automatic change detection or mapping. Recent work has shown the potential of Deep Learning approaches for land use classification; however, this thesis improves on the state-of-the-art by applying additional dataset augmenting approaches that are well suited for geospatial data. Furthermore, the generalizability of the classifiers is tested by extensively evaluating the classifiers on unseen datasets and we present the accuracy levels of the classifier in order to show that the results actually generalize beyond the small benchmarks used in training. Deep networks have many parameters, and therefore they are often built with very large sets of labeled data. Suitably large datasets for LULC are not easy to come by, but techniques such as refinement learning allow networks trained for one task to be retrained to perform another recognition task. Contributions of this thesis include demonstrating that deep networks trained for image recognition in one task (ImageNet) can be efficiently transferred to remote sensing applications and perform as well or better than manually crafted classifiers without requiring massive training data sets. This is demonstrated on the UC Merced dataset, where 96% mean accuracy is achieved using a CNN (Convolutional Neural Network) and 5-fold cross validation. These results are further tested on unrelated VHR images at the same resolution as the training set.Dissertation/ThesisMasters Thesis Computer Science 201
Asian Economic Integration - Perspectives from a Chinese Scholar
No full textSince the 1990s, regional economic integration has become an unstoppable trend throughout the world. As the most telling feature of that, regional trade agreements (RTAs) have expanded explosively in the past fifteen years (see figure 1). According to the latest WTO data, the number of RTAs of all kinds (including those in implementation or to be signed) had reached almost 300 by the end of 2005. 250 of them have been notified to WTO, among which 130 were notified after January 1995, with most signed recently. So far, 173 RTAs have been notified to WTO and taken effect. It is assessed that there are still over 70 RTAs which havent been notified to WTO but about to come into effect.Asian Economic Integration
Pollen Rate Based Control and Stabilization of Double Inverted Pendulum
No full textAbstractNaturally inspired Flower pollination unconstrained optimization method is applied for the stabilization of the double inverted pendulum control problem as part of this study which is a novelty. The optimization was applied under the influence of time delay and have proven that the influence of time delay is significantly felt and would cause loss of energy, however the presence of flower pollination for optimization minimizes the loss incurred due to time delay and makes the system significant in terms of sensitivity. The influence on settling time and peak overshoot are studied and are compared for performance with and without time delays. The developed strategy paves way to the analysis of complex dynamic systems wherein the controller design when designed using naturally inspired algorithm would make the system energy efficient
Optimal Power Flow with Static VAR Compensator Using Galaxy Based Search Algorithm to Minimize Real Power Losses
No full textAbstractIn this paper, Galaxy based search algorithm (GbSA) is used to solve multi-objective problem of optimization in power systems. The proposed GbSA resembles the spiral arms of some galaxies to search for the optimal solutions. The GbSA also uses a modified Hill Climbing algorithm as a local search. Simulation results show that the GbSA finds the optimal or very near optimal values in all runs of the algorithm. The weighted sum technique with equal weights has been chosen to solve the multi-objective function. The functions considered are to minimize the power losses in transmission line, cost of the real power generation and voltage deviation. Static VAR Compensator (SVC) is used for the purpose of optimal power flow. L-index is used to identify the optimal location to place SVC. The results have been compared with Genetic algorithm (GA) for IEEE-14 System
Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm
No full textBanal nationalism and soap opera
No full textAs Michael Billig (1995) argues, nationalism does not die with the establishment of relatively stable nation states- it changes from a ‘hot’ to a ‘banal’ form. In this multidisciplinary and multiperspectival study, I study nationalism (specifically Hindu nationalism or Hindutva) in its banal form within popular culture, specifically prime time television soap operas colloquially known as the K-serials. Through a conjunctural analysis, I show how banal Hindu nationalism played out on the K-serials in multiple ways. That is, these serials had an important role in the ongoing project of remaking of the Indian nation under the ideology of Hindutva, creating not just a Hindu nation but a Brahminical nation. This dissertation makes a number of contributions to different bodies of research. One, it examines how the changes in the political economy impact the way audiences are rounded up and how that influences the content of the soaps. I show how the structural limitations of the audience measurement system and the changing focus on the ‘bottom of the pyramid’ consumer influenced the arrival of Hindutva inflected content on television. (I show also, in passing, how the currency of television, TRPs, can themselves be gendered). Two, I show how the debate over secularism and religious nationalism in the political sphere get reflected in the cultural sphere, especially in texts that less obviously have anything to do with national politics. Three, I show how the agency and empowerment that other scholars have read into these soaps is derived largely from the discourses of the women’s wing of Hindu nationalism, and is therefore highly problematic, ahistorical, and limiting. Four, I show how the very structure of soaps, especially its ‘open’ ness, periodicity and everydayness can play a significant role in spreading banal nationalism. Five, I show how the operations of banal Hindutva disrupt the relationship between folk and Sanskritic practices, contributing to the homogenizing of Hinduism. And finally, I have shown how by going beyond the texts themselves, we find a bridge between the studies of soaps that look at the micropolitics of gender and those that look at macropolitics of national identity.Ph. D.Includes bibliographical referencesby Santanu Chakrabart
Novel Film-Forming Spray: Advancing Shelf Life Extension and Post-Harvest Loss Reduction in Eggs
No full textThis study explores the development of a topical film-forming spray infused with phytobiotic herbs to extend egg shelf life and maintain its quality. Unlike traditional surface treatments, film-forming sprays provide uniform drug distribution, better bioavailability, effective CO2 retention by sealing pores, and antibacterial effects. The spray includes a polymer to encapsulate phytoconstituents and form the film. The resulting film is highly water-resistant, glossy, transparent, and dries within two minutes. SEM analysis showed a fine, uniform morphology, while zeta analysis revealed a negative potential of −0.342 mV and conductivity of 0.390 mS/cm, indicating stable dispersion. The spray’s effectiveness was tested on 640 chicken eggs stored at varying temperatures. Eggs treated and kept at 2–8 °C showed the best results, with smaller air cells, higher specific gravity, and superior quality indicators such as pH, albumen weight, albumen height and index, Haugh unit, yolk weight, and yolk index. Additionally, the spray significantly reduced microbial load, including total plate count and E. coli. Eggs stored at 28 °C remained safe for 24–30 days, while those at 2–8 °C lasted over 42 days. This innovative film-forming spray offers a promising approach for preserving internal and external egg quality during storage
Studies on DC Magnetron Sputtered AZO Thin Films for HIT Solar Cell Application
No full textAluminum doped zinc oxide (AZO) is becoming an important and alternative transparent conducting oxide (TCO) material for solar photovoltaic applications due to its good electrical and optical characteristics, lower cost and more abundance, non-toxicity and stability in hydrogen plasma when compared to the popular indium tin oxide (ITO). In this work, AZO films are deposited on glass and silicon substrates with direct current (DC) magnetron sputtering using 5N pure Zinc Oxide target doped with 2 wt% Al2O3.The effect of deposition conditions on the structural, electrical and optical properties of the AZO films are investigated. The results demonstrated that the measured thickness of the deposited films are in the range 135- 490 nm. The X-ray diffraction studies reveal that the AZO films exhibit hexagaonal-wurtzite structure with the preferred orientation of grains along the (002) planes and an average crystal size of ~42 nm. At optimized sputter deposition parameters of an electrode distance of ~ 60 mm, substrate temperature of
~ 200 °C, target DC power of ~150 W and working pressure of ~2∙10¯³ mbar; the AZO films have shown an electrical resistivity of 1.27∙10¯³ Ω∙cm and an average optical transmittance value of 83.76% in the visible range for an optimal film thickness of ~265 nm. Finally HIT Solar Cells with AZO/p-a-Si:H/i-Si:H/n-c-Si/na-Si:H/Al structure have been fabricated by applying the optimized AZO films as front transparent electrodes. It is observed from the preliminary experiments that the fabricated cells have shown an initial photo conversion efficiency of 10.18% with an open circuit voltage (Voc) of 890 mV, short circuit current density (Jsc) of 15.68 mA/cm2 and a fill factor (FF) of ~ 73%
Adapting Prediction Models to Bare Soil Fractional Cover for Extending Topsoil Clay Content Mapping Based on AVIRIS-NG Hyperspectral Data
No full textInternational audienceThe deployment of remote sensing platforms has facilitated the mapping of soil properties to a great extent. However, the accuracy of these soil property estimates is compromised by the presence of non-soil cover, which introduces interference with the acquired reflectance spectra over pixels. Therefore, current soil property estimation by remote sensing is limited to bare soil pixels, which are identified based on spectral indices of vegetation. Our study proposes a composite mapping approach to extend the soil properties mapping beyond bare soil pixels, associated with an uncertainty map. The proposed approach first classified the pixels based on their bare soil fractional cover by spectral unmixing. Then, a specific regression model was built and applied to each bare soil fractional cover class to estimate clay content. Finally, the clay content maps created for each bare soil fractional cover class were mosaicked to create a composite map of clay content estimations. A bootstrap procedure was used to estimate the standard deviation of clay content predictions per bare soil fractional cover dataset, which represented the uncertainty of estimations. This study used a hyperspectral image acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor over cultivated fields in South India. The proposed approach provided modest performances in prediction (Rval2 ranging from 0.53 to 0.63) depending on the bare soil fractional cover class and showed a correct spatial pattern, regardless of the bare soil fraction classes. The model’s performance was observed to increase with the adoption of higher bare soil fractional cover thresholds. The mapped area ranged from 10.4% for pixels with bare soil fractional cover >0.7 to 52.7% for pixels with bare soil fractional cover >0.3. The approach thus extended the mapped surface by 42.4%, while maintaining acceptable prediction performances. Finally, the proposed approach could be adopted to extend the mapping capability of planned and current hyperspectral satellite missions
