Superior performance of aptamer in tumor penetration over antibody : implication of aptamer-based theranostics in solid tumors

Insufficient penetration of therapeutic agents into tumor tissues results in inadequate drug distribution and lower intracellular concentration of drugs, leading to the increase of drug resistance and resultant failure of cancer treatment. Targeted drug delivery to solid tumors followed by complete drug penetration and durable retention will significantly improve clinical outcomes of cancer therapy. Monoclonal antibodies have been commonly used in clinic for cancer treatment, but their limitation of penetrating into tumor tissues still remains because of their large size. Aptamers, as "chemical antibodies", are 15-20 times smaller than antibodies. To explore whether aptamers are superior to antibodies in terms of tumor penetration, we carried out the first comprehensive study to compare the performance of an EpCAM aptamer with an EpCAM antibody in theranostic applications. Penetration and retention were studied in in vitro three-dimensional tumorspheres, in vivo live animal imaging and mouse colorectal cancer xenograft model. We found that the EpCAM aptamer can not only effectively penetrate into the tumorsphere cores but can also be retained by tumor sphere cells for at least 24 h, while limited tumor penetration by EpCAM antibody was observed after 4 h incubation. As observed from in vivo live animal imaging, EpCAM aptamers displayed a maximum tumor uptake at around 10 min followed by a rapid clearance after 80 min, while the signal of peak uptake and disappearance of antibody appeared at 3 h and 6 h after intravenous injection, respectively. The signal of PEGylated EpCAM aptamers in xenograft tumors was sustained for 26 h, which was 4.3-fold longer than that of the EpCAM antibody. Consistently, there were 1.67-fold and 6.6-fold higher accumulation of PEGylated aptamer in xenograft tumors than that of antibody, at 3 h and 24 h after intravenous administration, respectively. In addition, the aptamer achieved at least a 4-time better tumor penetration in xenograft tumors than that of the antibody at a 200 μm distances from the blood vessels 3 h after intravenous injection. Taken together, these data indicate that aptmers are superior to antibodies in cancer theranostics due to their better tumor penetration, more homogeneous distribution and longer retention in tumor sites. Thus, aptamers are promising agents for targeted tumor therapeutics and molecular imaging.

Localization and degmentation of 3D intervertebral discs in MR Images by data driven estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

LNA aptamer based multi-modal, Fe3O4-saturated lactoferrin (Fe3O4-bLf) nanocarriers for triple positive (EpCAM, CD133, CD44) colon tumor targeting and NIR, MRI and CT imaging

This is the first ever attempt to combine anti-cancer therapeutic effects of emerging anticancer biodrug bovine lactoferrin (bLf), and multimodal imaging efficacy of Fe3O4 nanoparticles (NPs) together, as a saturated Fe3O4-bLf. For cancer stem cell specific uptake of nanocapsules/nanocarriers (NCs), Fe3O4-bLf was encapsulated in alginate enclosed chitosan coated calcium phosphate (AEC-CP) NCs targeted (Tar) with locked nucleic acid (LNA) modified aptamers against epithelial cell adhesion molecule (EpCAM) and nucleolin markers. The nanoformulation was fed orally to mice injected with triple positive (EpCAM, CD133, CD44) sorted colon cancer stem cells in the xenograft cancer stem cell mice model. The complete regression of tumor was observed in 70% of mice fed on non-targeted (NT) NCs, with 30% mice showing tumor recurrence after 30 days, while only 10% mice fed with Tar NCs showed tumor recurrence indicating a significantly higher survival rate. From tumor tissue analyses of 35 apoptotic markers, 55 angiogenesis markers, 40 cytokines, 15 stem cell markers and gene expression studies of important signaling molecules, it was revealed that the anti-cancer mechanism of Fe3O4-bLf was intervened through TRAIL, Fas, Fas-associated protein with death domain (FADD) mediated phosphorylation of p53, to induce activation of second mitochondria-derived activator of caspases (SMAC)/DIABLO (inhibiting survivin) and mitochondrial depolarization leading to release of cytochrome C. Induction of apoptosis was observed by inhibition of the Akt pathway and activation of cytokines released from monocytes/macrophages and dendritic cells (interleukin (IL) 27, keratinocyte chemoattractant (KC)). On the other hand, the recurrence of tumor in AEC-CP-Fe3O4-bLf NCs fed mice mainly occurred due to activation of alternative pathways such as mitogen-activated protein kinases (MAPK)/extracellular signal-regulated kinases (ERK) and Wnt signaling leading to an increase in expression of survivin, survivin splice variant (survivin 2B) and other anti-apoptotic proteins Bad, Bcl-2 and XIAP. Apart from the promising anti-cancer efficacy and the exceptional tumor targeting ability observed by multimodal imaging using near-infrared (NIR) imaging, magnetic resonance imaging (MRI) and computerized tomographic (CT) techniques, these NCs also maintained the immunomodulatory benefits of bLf as they were able to increase the RBC, hemoglobin, iron calcium and zinc levels in mice.

Quick chip assay using locked nucleic acid modified epithelial cell adhesion molecule and nucleolin aptamers for the capture of circulating tumor cells

The role of circulating tumor cells (CTCs) in disease diagnosis, prognosis, monitoring of the therapeutic efficacy, and clinical decision making is immense and has attracted tremendous focus in the last decade. We designed and fabricated simple, flat channel microfluidic devices polydimethylsiloxane (PDMS based) functionalized with locked nucleic acid (LNA) modified aptamers (targeting epithelial cell adhesion molecule (EpCAM) and nucleolin expression) for quick and efficient capture of CTCs and cancer cells. With optimized flow rates (10 μl/min), it was revealed that the aptamer modified devices offered reusability for up to six times while retaining optimal capture efficiency (>90%) and specificity. High capture sensitivity (92%) and specificity (100%) was observed in whole blood samples spiked with Caco-2 cells (10-100 cells/ml). Analysis of blood samples obtained from 25 head and neck cancer patients on the EpCAM LNA aptamer functionalized chip revealed that an average count of 5 ± 3 CTCs/ml of blood were captured from 22/25 samples (88%). EpCAM intracellular domain (EpICD) immunohistochemistry on 9 oral squamous cell carcinomas showed the EpICD positivity in the tumor cells, confirming the EpCAM expression in CTCs from head and neck cancers. These microfluidic devices also maintained viability for in vitro culture and characterization. Use of LNA modified aptamers provided added benefits in terms of cost effectiveness due to increased reusability and sustainability of the devices. Our results present a robust, quick, and efficient CTC capture platform with the use of simple PDMS based devices that are easy to fabricate at low cost and have an immense potential in cancer diagnosis, prognosis, and therapeutic planning.

Fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images via a learning-based method

In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively.

Heterogeneity of miR-10b expression in circulating tumor cells

Circulating tumor cells (CTCs) in the blood of cancer patients are recognized as important potential targets for future anticancer therapies. As mediators of metastatic spread, CTCs are also promising to be used as € liquid biopsyto aid clinical decision-making. Recent work has revealed potentially important genotypic and phenotypic heterogeneity within CTC populations, even within the same patient. MicroRNAs (miRNAs) are key regulators of gene expression and have emerged as potentially important diagnostic markers and targets for anti-cancer therapy. Here, we describe a robust in situ hybridization (ISH) protocol, incorporating the CellSearch ® CTC detection system, enabling clinical investigation of important miRNAs, such as miR-10b on a cell by cell basis. We also use this method to demonstrate heterogeneity of such as miR-10b on a cell-by-cell basis. We also use this method to demonstrate heterogeneity of miR-10b in individual CTCs from breast, prostate and colorectal cancer patients.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

Polimorfismos dos genes do citocromo P450, da glutationa S-transferase e do supressor de tumor TP53 em populações sul-americanas e em pacientes com doença pulmonar obstrutiva crônica e câncer de pulmão

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Localization strategies of multinationals in Brazil which characteristics of the Brazilian market force multinational companies to localize their marketing activities?

Uma vez que as perspectivas de crescimento económico nos países mais desenvolvidos, como a Europa, os EUA eo Japão estão diminuindo, os mercados emergentes têm se tornado cada vez mais importante para muitas empresas multinacionais. Brasil, Rússia, Índia e China (BRICs) são agora os principais mercados em crescimento em todo o mundo e as empresas estão buscando estratégias para explorar ao máximo o potencial de consumo promissor nessas regiões. Um dos modos mais elaborados de prosseguir essa estratégia é conhecida como "localização" - uma adaptação das práticas de negócios (ao longo de toda a cadeia de suprimentos) com as preferências e condições locais. Este artigo é projetado para analisar as atividades de localização de empresas multinacionais no Brasil. O foco da análise é o de investigar as características do mercado brasileiro, que induzem as multinacionais a localizar o seu marketing mix (composto de produto, preço, colocação e promoção). Em dois estudos de casos com a empresa Suiça Nestlé e a empresa Alemã Volkswagen vários padrões de localização foram no mercado consumidor brasileiro. Os quatro resultados mais significativos da análise são os diferentes padrões sociais o Brasil, que forçar as empresas a reformular certas funções do seu mix de marketing (por exemplo, a colocação no caso da Nestlé), a aceitação dos consumidores brasileiros a pagar preços relativamente elevados (por exemplo, taxas de Volkswagen até 100% mais por seus produtos em relação à Alemanha); o enorme tamanho do Brasil ea infra-estrutura deficiente, que exigem uma abordagem de distribuição localizada; eo caráter atualmente ainda menos exigente dos estratos de consumidores brasileiros emergentes, que permitem às empresas oferecer produtos menos sofisticados em comparação aos mercados europeus.

Localization of a mobile robot based on odometry and natural landmarks using extended kalman filter

SANTANA, André M.; SOUZA, Anderson A. S.; BRITTO, Ricardo S.; ALSINA, Pablo J.; MEDEIROS, Adelardo A. D. Localization of a mobile robot based on odometry and natural landmarks using extended Kalman Filter. In: INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, 5., 2008, Funchal, Portugal. Proceedings... Funchal, Portugal: ICINCO, 2008.