Myoepithelial molecular markers in human breast carcinoma PMC42-LA cells are induced by extracellular matrix and stromal cells

The microenvironment plays a key role in the cellular differentiation of the two main cell lineages of the human breast, luminal epithelial, and myoepithelial. It is not clear, however, how the components of the microenvironment control the development of these cell lineages. To investigate how lineage development is regulated by 3-D culture and microenvironment components, we used the PMC42-LA human breast carcinoma cell line, which possesses stem cell characteristics. When cultured on a two-dimensional glass substrate, PMC42-LA cells formed a monolayer and expressed predominantly luminal epithelial markers, including cytokeratins 8, 18, and 19; E-cadherin; and sialomucin. The key myoepithelial-specific proteins α-smooth muscle actin and cytokeratin 14 were not expressed. When cultured within Engelbreth-Holm- Swarm sarcoma-derived basement membrane matrix (EHS matrix), PMC42-LA cells formed organoids in which the expression of luminal markers was reduced and the expression of other myoepithelial-specific markers (cytokeratin 17 and P-cadherin) was promoted. The presence of primary human mammary gland fibroblasts within the EHS matrix induced expression of the key myoepithelial-specific markers, α-smooth muscle actin and cytokeratin 14. Immortalized human skin fibroblasts were less effective in inducing expression of these key myoepithelial-specific markers. Confocal dual-labeling showed that individual cells expressed luminal or myoepithelial proteins, but not both. Conditioned medium from the mammary fibroblasts was equally effective in inducing myoepithelial marker expression. The results indicate that the myoepithelial lineage is promoted by the extracellular matrix, in conjunction with products secreted by breast-specific fibroblasts. Our results demonstrate a key role for the breast microenvironment in the regulation of breast lineage development.

Host rather than graft origin of Matrigel-induced adipose tissue in the murine tissue-engineering chamber

We have recently shown that Matrigel-filled chambers containing fibroblast growth factor-2 (FGF2) and placed around an epigastric pedicle in the mouse were highly adipogenic. Contact of this construct with pre-existing tissue or a free adipose graft was required. To further investigate the mechanisms underpinning formation of new adipose tissue, we seeded these chambers with human adipose biopsies and human adipose-derived cell populations in severe combined immunodeficient mice and assessed the origin of the resultant adipose tissue after 6 weeks using species-specific probes. The tissues were negative for human-specific vimentin labeling, suggesting that the fat originates from the murine host rather than the human graft. This was supported by the strong presence of mouse-specific Cot-1 deoxyribonucleic acid labeling, and the absence of human Cot-1 labeling in the new fat. Even chambers seeded with FGF2/Matrigel containing cultured human stromal-vascular fraction (SVF) labeled strongly only for human vimentin in cells that did not have a mature adipocyte phenotype; the newly formed fat tissue was negative for human vimentin. These findings indicate that grafts placed in the chamber have an inductive function for neo-adipogenesis, rather than supplying adipocyte-precursor cells to generate the new fat tissue, and preliminary observations implicate the SVF in producing inductive factors. This surprising finding opens the door for refinement of current adipose tissue-engineering approaches.

Time course analysis of hypoxia, granulation tissue and blood vessel growth, and remodeling in healing rat cutaneous incisional primary intention wounds

Hypoxia and the development and remodeling of blood vessels and connective tissue in granulation tissue that forms in a wound gap following full-thickness skin incision in the rat were examined as a function of time. A 1.5 cm-long incisional wound was created in rat groin skin and the opposed edges sutured together. Wounds were harvested between 3 days and 16 weeks and hypoxia, percent vascular volume, cell proliferation and apoptosis, α-smooth muscle actin, vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 expression in granulation tissue were then assessed. Hypoxia was evident between 3 and 7 days while maximal cell proliferation at 3 days (123.6 ± 22.2 cells/mm 2, p < 0.001 when compared with normal skin) preceded the peak percent vascular volume that occurred at 7 days (15.83 ± 1.10%, p < 0.001 when compared with normal skin). The peak in cell apoptosis occurred at 3 weeks (12.1 ± 1.3 cells/mm 2, p < 0.001 when compared with normal skin). Intense α-smooth muscle actin labeling in myofibroblasts was evident at 7 and 10 days. Vascular endothelial growth factor receptor-2 and vascular endothelial growth factor-A were detectable until 2 and 3 weeks, respectively, while transforming growth factor-β 1 protein was detectable in endothelial cells and myofibroblasts until 3-4 weeks and in the extracellular matrix for 16 weeks. Incisional wound granulation tissue largely developed within 3-7 days in the presence of hypoxia. Remodeling, marked by a decline in the percent vascular volume and increased cellular apoptosis, occurred largely in the absence of detectable hypoxia. The expression of vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 is evident prior, during, and after the peak of vascular volume reflecting multiple roles for these factors during wound healing.

Predicting movie ratings from audience behaviors

We propose a method of representing audience behavior through facial and body motions from a single video stream, and use these features to predict the rating for feature-length movies. This is a very challenging problem as: i) the movie viewing environment is dark and contains views of people at different scales and viewpoints; ii) the duration of feature-length movies is long (80-120 mins) so tracking people uninterrupted for this length of time is still an unsolved problem, and; iii) expressions and motions of audience members are subtle, short and sparse making labeling of activities unreliable. To circumvent these issues, we use an infrared illuminated test-bed to obtain a visually uniform input. We then utilize motion-history features which capture the subtle movements of a person within a pre-defined volume, and then form a group representation of the audience by a histogram of pair-wise correlations over a small-window of time. Using this group representation, we learn our movie rating classifier from crowd-sourced ratings collected by rottentomatoes.com and show our prediction capability on audiences from 30 movies across 250 subjects (> 50 hrs).

Changes to commercial service provision among sex workers from Queensland, Australia

Introduction: The role of commercial sex in facilitating infection transmission is a subject of ongoing empirical enquiry, with little attention to the variety and extent of ‘non-traditional’ commercial services that pose a lesser risk of infection. This study sought to examine the supply and demand of a wide range of traditional and non-traditional commercial sexual services among sex workers and their clients from Queensland, Australia. Methods: Cross-sectional convenience sampling was used to compare female sex workers in 1991 (n=200, aged 16-46 years) and 2003 (n=247, aged 18-57 years) and from male clients in 2003. The client sample comprised 160 male clients aged between 19 and 72 years. Results: Over the comparison period there was a significant increase in the provision of ‘exotic’ or non-traditional sexual services. In 2003, the availability of bondage and discipline, submission, fantasy, use of sex toys, golden showers, fisting and lesbian double acts had increased dramatically, while ‘traditional’ services had mostly remained at similar levels. Moreover, the proportion of sex workers in some industry sectors providing ‘exotic’ commercial services seem to have risen over time. Conclusion: Undoubtedly, the sex industry has professionalised and now includes more sophisticated and specialized suppliers. As with any commercial business, the diversification of services is largely driven with client demand, with the ‘menu’ being generally broader than the majority of client preferences. However, although clients demands for particular commercial sexual services seems to have been met, with regard to anal sex and anal play, supply has failed to meet client demand. Disclosure of Interest Statement: Funding for the 2003 study was provided by the Prostitution Licensing Authority. Acknowledgement and sincere thanks to the men and women who participated in this study.

Examining the neural correlates of choice behavior in a gambling task using steady state topography

The present study investigated the behavioral and neuropsychological characteristics of decision-making behavior during a gambling task as well as how these characteristics may relate to the Somatic Marker Hypothesis and the Frequency of Gain model. The applicability to intertemporal choice was also discussed. Patterns of card selection during a computerized interpretation of the Iowa Gambling Task were assessed for 10 men and 10 women. Steady State Topography was employed to assess cortical processing throughout this task. Results supported the hypothesis that patterns of card selection were in line with both theories. As hypothesized, these 2 patterns of card selection were also associated with distinct patterns of cortical activity, suggesting that intertemporal choice may involve the recruitment of right dorsolateral prefrontal cortex for somatic labeling, left fusiform gyrus for object representations, and the left dorsolateral prefrontal cortex for an analysis of the associated frequency of gain or loss. It is suggested that processes contributing to intertemporal choice may include inhibition of negatively valenced options, guiding decisions away from those options, as well as computations favoring frequently rewarded options.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Uncertain species distribution: From interpolation to extrapolation

Species distribution models (SDMs) are considered to exemplify Pattern rather than Process based models of a species' response to its environment. Hence when used to map species distribution, the purpose of SDMs can be viewed as interpolation, since species response is measured at a few sites in the study region, and the aim is to interpolate species response at intermediate sites. Increasingly, however, SDMs are also being used to also extrapolate species-environment relationships beyond the limits of the study region as represented by the training data. Regardless of whether SDMs are to be used for interpolation or extrapolation, the debate over how to implement SDMs focusses on evaluating the quality of the SDM, both ecologically and mathematically. This paper proposes a framework that includes useful tools previously employed to address uncertainty in habitat modelling. Together with existing frameworks for addressing uncertainty more generally when modelling, we then outline how these existing tools help inform development of a broader framework for addressing uncertainty, specifically when building habitat models. As discussed earlier we focus on extrapolation rather than interpolation, where the emphasis on predictive performance is diluted by the concerns for robustness and ecological relevance. We are cognisant of the dangers of excessively propagating uncertainty. Thus, although the framework provides a smorgasbord of approaches, it is intended that the exact menu selected for a particular application, is small in size and targets the most important sources of uncertainty. We conclude with some guidance on a strategic approach to identifying these important sources of uncertainty. Whilst various aspects of uncertainty in SDMs have previously been addressed, either as the main aim of a study or as a necessary element of constructing SDMs, this is the first paper to provide a more holistic view.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

Automated 3D mapping & shape analysis of the lateral ventricles via fluid registration of multiple surface-based atlases

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.