Differential expression of VEGF ligands and receptors in prostate cancer

BACKGROUND Prostate cancer disseminates to regional lymph nodes, however the molecular mechanisms responsible for lymph node metastasis are poorly understood. The vascular endothelial growth factor (VEGF) ligand and receptor family have been implicated in the growth and spread of prostate cancer via activation of the blood vasculature and lymphatic systems. The purpose of this study was to comprehensively examine the expression pattern of VEGF ligands and receptors in the glandular epithelium, stroma, lymphatic vasculature and blood vessels in prostate cancer. METHODS The localization of VEGF-A, VEGF-C, VEGF-D, VEGF receptor (VEGFR)-1, VEGFR-2, and VEGFR-3 was examined in cancerous and adjacent benign prostate tissue from 52 subjects representing various grades of prostate cancer. RESULTS Except for VEGFR-2, extensive staining was observed for all ligands and receptors in the prostate specimens. In epithelial cells, VEGF-A and VEGFR-1 expression was higher in tumor tissue compared to benign tissue. VEGF-D and VEGFR-3 expression was significantly higher in benign tissue compared to tumor in the stroma and the endothelium of lymphatic and blood vessels. In addition, the frequency of lymphatic vessels, but not blood vessels, was lower in tumor tissue compared with benign tissue. CONCLUSIONS These results suggest that activation of VEGFR-1 by VEGF-A within the carcinoma, and activation of lymphatic endothelial cell VEGFR-3 by VEGF-D within the adjacent benign stroma may be important signaling mechanisms involved in the progression and subsequent metastatic spread of prostate cancer. Thus inhibition of these pathways may contribute to therapeutic strategies for the management of prostate cancer.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Bonding and bridging : transition to school and social capital formation among a community of Indigenous Australian children

This study reports on an intervention program designed to facilitate transition to school of a whole community of Indigenous Australian children who had previously not been attending. The children were from families displaced from their traditional lands and experienced on-going social marginalisation and transience. A social capital framework was employed to track change in the children’s social inclusion and family-school engagement for two years, from school entry. Sociometric measurement and interview techniques were applied to assess the children’s social connectedness and peer relationship quality. Using these data, analyses examined whether bonding within the group supported or inhibited formation of new social relationships. Although transience disrupted attendance, there was a group trend towards increased social inclusion with some evidence that group bonds supported bridging to new social relationships. Change in family-school engagement was tracked using multi-informant interviews. Limited engagement between school and families presented an on-going challenge to sustained educational engagement.

Autonomous multisensor calibration and closed-loop fusion for SLAM

The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.

Crucial roles for olfactory ensheathing cells and olfactory mucosal cells in the repair of damaged neural tracts

Olfactory ensheathing cells, the glial cells of the olfactory nervous system, exhibit unique growth-promoting and migratory properties that make them interesting candidates for cell therapies targeting neuronal injuries such as spinal cord injury. Transplantation of olfactory cells is feasible and safe in humans; however, functional outcomes are highly variable with some studies showing dramatic improvements and some no improvements at all. We propose that the reason for this is that the identity and purity of the cells is different in each individual study. We have shown that olfactory ensheathing cells are not a uniform cell population and that individual subpopulations of OECs are present in different regions of the olfactory nervous system, with strikingly different behaviors. Furthermore, the presence of fibroblasts and other cell types in the transplant can dramatically alter the behavior of the transplanted glial cells. Thus, a thorough characterization of the differences between olfactory ensheathing cell subpopulations and how the behavior of these cells is affected by the presence of other cell types is highly warranted.

Simultaneous estimation of hunting pressure, harvest and hunter success rates using WinBUGS

The use of hierarchical Bayesian spatial models in the analysis of ecological data is increasingly prevalent. The implementation of these models has been heretofore limited to specifically written software that required extensive programming knowledge to create. The advent of WinBUGS provides access to Bayesian hierarchical models for those without the programming expertise to create their own models and allows for the more rapid implementation of new models and data analysis. This facility is demonstrated here using data collected by the Missouri Department of Conservation for the Missouri Turkey Hunting Survey of 1996. Three models are considered, the first uses the collected data to estimate the success rate for individual hunters at the county level and incorporates a conditional autoregressive (CAR) spatial effect. The second model builds upon the first by simultaneously estimating the success rate and harvest at the county level, while the third estimates the success rate and hunting pressure at the county level. These models are discussed in detail as well as their implementation in WinBUGS and the issues arising therein. Future areas of application for WinBUGS and the latest developments in WinBUGS are discussed as well.

Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

Heparan sulfate proteoglycans and human breast cancer epithelial cell tumorigenicity

Heparan sulfate proteoglycans (HSPGs) are key components of the extracellular matrix that mediate cell proliferation, invasion, and cellular signaling. The biological functions of HSPGs are linked to their co-stimulatory effects on extracellular ligands (e.g., WNTs) and the resulting activation of transcription factors that control mammalian development but also associated with tumorigenesis. We examined the expression profile of HSPG core protein syndecans (SDC1–4) and glypicans (GPC1–6) along with the enzymes that initiate or modify their glycosaminoglycan chains in human breast cancer (HBC) epithelial cells. Gene expression in relation to cell proliferation was examined in the HBC cell lines MCF-7 and MDA-MB-231 following treatment with the HS agonist heparin. Heparin increased gene expression of chain initiation and modification enzymes including EXT1 and NDST1, as well as core proteins SDC2 and GPC6. With HS/Wnt interactions established, we next investigated WNT pathway components and observed that increased proliferation of the more invasive MDA-MB-231 cells is associated with activation of the Wnt signaling pathway. Specifically, there was substantial upregulation (>5-fold) of AXIN1, WNT4A, and MYC in MDA-MB-231 but not in MCF-7 cells. The changes in gene expression observed for HSPG core proteins and related enzymes along with the associated Wnt signaling components suggest coordinated interactions. The influence of HSPGs on cellular proliferation and invasive potential of breast cancer epithelial cells are cell and niche specific. Further studies on the interactions between HSPGs and WNT ligands may yield clinically relevant molecular targets, as well as new biomarkers for characterization of breast cancer progression.

Investigation of brain derived neurotrophic factor (BDNF) gene variants in migraine

A number of observations have suggested that brain derived neurotrophic factor (BDNF) plays a role in migraine pathophysiology. This study investigates whether variants in the BDNF gene are associated with migraine in an Australian case-control population. Background. Brain derived neurotrophic factor (BDNF) has an important role in neural growth, development and survival in the central nervous system and is an important modulator of central and peripheral pain responses. Variants in BDNF, in particular the functional Val66Met polymorphism (rs6265), have been found to be associated with a number of psychiatric disorders, cognitive function and obesity. As BDNF has been found to be differentially expressed in a number of aspects related to migraine, we tested for association between single nucleotide polymorphisms (SNPs) in BDNF and migraine. Methods. Five SNPs in the BDNF locus (rs1519480, rs6265, rs712507, rs2049046 and rs12273363) were genotyped initially in a cohort of 277 migraine cases, including 172 diagnosed with migraine with aura (MA) and 105 with migraine without aura (MO), and 277 age- and sex-matched controls. Three of these SNPs (rs6265, rs2049046 and rs12273363) were subsequently genotyped in a second cohort of 580 migraineurs, including 473 diagnosed with MA and 105 with O, and 580 matched controls. Results. – BDNF SNPs rs1519480, rs6265, rs712507 and rs12273363 were not significantly associated with migraine. However, rs2049046 showed a significant association with migraine, and in particular, MA in the first cohort. In the second cohort, although an increase in the rs2049046 T-allele frequency was observed in migraine cases, and in both MA and MO subgroups, it was not significantly different from controls. Analysis of data combined from both cohorts for rs2049046 showed significant differences in the genotypic and allelic distributions for this marker in both migraine and the MA sub-group. Conclusion. This study confirmed previous studies that the functional BDNF SNP rs6265 (Val66Met) is not associated with migraine. However, we found that rs2049046, which resides at the 5’ end of 3 one the BDNF transcripts, may be associated with migraine, suggesting that further investigations of this SNP may be warranted.

Cryptanalysis of RC4(n, m) stream cipher

RC4(n, m) is a stream cipher based on RC4 and is designed by G. Gong et al. It can be seen as a generalization of the famous RC4 stream cipher designed by Ron Rivest. The authors of RC4(n, m) claim that the cipher resists all the attacks that are successful against the original RC4. The paper reveals cryptographic weaknesses of the RC4(n, m) stream cipher. We develop two attacks. The first one is based on non-randomness of internal state and allows to distinguish it from a truly random cipher by an algorithm that has access to 24·n bits of the keystream. The second attack exploits low diffusion of bits in the KSA and PRGA algorithms and recovers all bytes of the secret key. This attack works only if the initial value of the cipher can be manipulated. Apart from the secret key, the cipher uses two other inputs, namely, initial value and initial vector. Although these inputs are fixed in the cipher specification, some applications may allow the inputs to be under the attacker control. Assuming that the attacker can control the initial value, we show a distinguisher for the cipher and a secret key recovery attack that for the L-bit secret key, is able to recover it with about (L/n) · 2n steps. The attack has been implemented on a standard PC and can reconstruct the secret key of RC(8, 32) in less than a second.

A multi-genome analysis approach enables tracking of the invasion of a single Russian wheat aphid (Diuraphis noxia) clone throughout the New World

This study investigated the population genetics, demographic history and pathway of invasion of the Russian wheat aphid (RWA) from its native range in Central Asia, the Middle East and Europe to South Africa and the Americas. We screened microsatellite markers, mitochondrial DNA and endosymbiont genes in 504 RWA clones from nineteen populations worldwide. Following pathway analyses of microsatellite and endosymbiont data, we postulate that Turkey and Syria were the most likely sources of invasion to Kenya and South Africa, respectively. Furthermore, we found that one clone transferred between South Africa and the Americas was most likely responsible for the New World invasion. Finally, endosymbiont DNA was found to be a high resolution population genetic marker, extremely useful for studies of invasion over a relatively short evolutionary history time frame. This study has provided valuable insights into the factors that may have facilitated the recent global invasion by this damaging pest.

Mechanism‐based selection of a potent kallikrein‐related peptidase 7 inhibitor from a versatile library based on the sunflower trypsin inhibitor SFTI‐1

Potent and specific enzyme inhibition is a key goal in the development of therapeutic inhibitors targeting proteolytic activity. The backbone-cyclized peptide, Sunflower Trypsin Inhibitor (SFTI-1) affords a scaffold that can be engineered to achieve both these aims. SFTI-1's mechanism of inhibition is unusual in that it shows fast-on/slow-off kinetics driven by cleavage and religation of a scissile bond. This phenomenon was used to select a nanomolar inhibitor of kallikrein-related peptidase 7 (KLK7) from a versatile library of SFTI variants with diversity tailored to exploit distinctive surfaces present in the active site of serine proteases. Inhibitor selection was achieved through the use of size exclusion chromatography to separate protease/inhibitor complexes from unbound inhibitors followed by inhibitor identification according to molecular mass ascertained by mass spectrometry. This approach identified a single dominant inhibitor species with molecular weight of 1562.4 Da, which is consistent with the SFTI variant SFTI-WCTF. Once synthesized individually this inhibitor showed an IC50 of 173.9 ± 7.6 nM against chromogenic substrates and could block protein proteolysis. Molecular modeling analysis suggested that selection of SFTI-WCTF was driven by specific aromatic interactions and stabilized by an enhanced internal hydrogen bonding network. This approach provides a robust and rapid route to inhibitor selection and design.

Evaluation of BMP-2 gene-activated muscle grafts for cranial defect repair

Large, osseous, segmental defects heal poorly. Muscle has a propensity to form bone when exposed to an osteogenic stimulus such as that provided by transfer and expression of cDNA encoding bone morphogenetic protein-2 (BMP-2). The present study evaluated the ability of genetically modified, autologous muscle to heal large cranial defects in rats. Autologous grafts (8 mm � 2 mm) were punched from the biceps femoris muscle and transduced intraoperatively with recombinant adenovirus vector containing human BMP-2 or green fluorescent protein cDNA. While the muscle biopsies were incubating with the vector, a central parietal 8 mm defect was surgically created in the calvarium of the same animal. The gene-activated muscle graft was then implanted into the cranial defect. After 8 weeks, crania were examined radiographically, histologically, and by micro-computed tomography and dual energy X-ray absorptiometry. Although none of the defects were completely healed in this time, muscle grafts expressing BMP-2 deposited more than twice as much new bone as controls. Histology confirmed the anatomical integrity of the newly formed bone, which was comparable in thickness and mineral density to the original cranial bone. This study confirms the in vivo osteogenic properties of genetically modified muscle and suggests novel strategies for healing bone. � 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:1095–1102, 2012