Epithelial-mesenchymal transition and mesenchymal-epithelial transition are essential for the acquisition of stem cell properties in hTERT-immortalised oral epithelial cells

BACKGROUND INFORMATION: Evidence has shown that mesenchymal-epithelial transition (MET) and epithelial-mesenchymal transition (EMT) are linked to stem cell properties. We currently lack a model showing how the occurrence of MET and EMT in immortalised cells influences the maintenance of stem cell properties. Thus, we established a project aiming to investigate the roles of EMT and MET in the acquisition of stem cell properties in immortalised oral epithelial cells. RESULTS: In this study, a retroviral transfection vector (pLXSN-hTERT) was used to immortalise oral epithelial cells by insertion of the hTERT gene (hTERT(+)-oral mucosal epithelial cell line [OME]). The protein and RNA expression of EMT transcriptional factors (Snail, Slug and Twist), their downstream markers (E-cadherin and N-cadherin) and embryonic stem cell markers (OCT4, Nanog and Sox2) were studied by reverse transcription PCR and Western blots in these cells. Some EMT markers were detected at both mRNA and protein levels. Adipocytes and bone cells were noted in the multi-differentiation assay, showing that the immortal cells underwent EMT. The differentiation assay for hTERT(+)-OME cells revealed the recovery of epithelial phenotypes, implicating the presence of MET. The stem cell properties were confirmed by the detection of appropriate markers. Altered expression of alpha-tubulin and gamma-tubulin in both two-dimensional-cultured (without serum) and three-dimensional-cultured hTERT(+)-OME spheroids indicated the re-programming of cytoskeleton proteins which is attributed to MET processes in hTERT(+)-OME cells. CONCLUSIONS: EMT and MET are essential for hTERT-immortalised cells to maintain their epithelial stem cell properties.

Computational fluid dynamics simulation and turbomachinery code validation of a high pressure ratio radial-inflow turbine

The present study explores reproducing the closest geometry of a high pressure ratio single stage radial-inflow turbine applied in the Sundstrans Power Systems T-100 Multipurpose Small Power Unit. The commercial software ANSYS-Vista RTD along with a built in module, BladeGen, is used to conduct a meanline design and create 3D geometry of one flow passage. Carefully examining the proposed design against the geometrical and experimental data, ANSYS-TurboGrid is applied to generate computational mesh. CFD simulations are performed with ANSYS-CFX in which three-dimensional Reynolds-Averaged Navier-Stokes equations are solved subject to appropriate boundary conditions. Results are compared with numerical and experimental data published in the literature in order to generate the exact geometry of the existing turbine and validate the numerical results against the experimental ones.

A comparison of techniques for the reconstruction of leaf surfaces from scanned data

The foliage of a plant performs vital functions. As such, leaf models are required to be developed for modelling the plant architecture from a set of scattered data captured using a scanning device. The leaf model can be used for purely visual purposes or as part of a further model, such as a fluid movement model or biological process. For these reasons, an accurate mathematical representation of the surface and boundary is required. This paper compares three approaches for fitting a continuously differentiable surface through a set of scanned data points from a leaf surface, with a technique already used for reconstructing leaf surfaces. The techniques which will be considered are discrete smoothing D2-splines [R. Arcangeli, M. C. Lopez de Silanes, and J. J. Torrens, Multidimensional Minimising Splines, Springer, 2004.], the thin plate spline finite element smoother [S. Roberts, M. Hegland, and I. Altas, Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions, SIAM, 1 (2003), pp. 208--234] and the radial basis function Clough-Tocher method [M. Oqielat, I. Turner, and J. Belward, A hybrid Clough-Tocher method for surface fitting with application to leaf data., Appl. Math. Modelling, 33 (2009), pp. 2582-2595]. Numerical results show that discrete smoothing D2-splines produce reconstructed leaf surfaces which better represent the original physical leaf.

Surface reconstruction of wheat leaf morphology from three-dimensional scanned data

Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.

Building a community of learners within the STEM higher education classroom

Building rich and authentic learning experiences in the STEM classroom, is a challenge for many educators within Higher Education. While many Higher Education Institutions have embraced the need to transform current teaching and learning practices and include a range of online tools, this has often been met with some resistance and approaches that do not always recognise the academic who are a critical component to the success of the transformational process. Over the last decade the Internet has evolved from being a tool used by a few dedicated educators to one that is being used by the majority of educators. However, what is important is how this great resource is used in teaching and learning to allow students to build knowledge. The ability for students to construct knowledge and engage in higher order thinking skills is at the heart of educational practices, and building a community of learners has the potential to support these practices, especially within STEM education. This paper explores the relationship between students and an academic teaching in a technology rich STEM learning environment and their adoption of social community and shared tools. In particular the paper reports on the critical components that make a successful community of learners and the educational tools and approaches that were successfully used to enhance the student learning experience in a STEM classroom.

Stem-like cells with luminal progenitor phenotype survive castration in human prostate cancer

Castration is the standard therapy for advanced prostate cancer (PC). Although this treatment is initially effective, tumors invariably relapse as incurable, castration-resistant PC (CRPC). Adaptation of androgen-dependent PC cells to an androgen-depleted environment or selection of pre-existing,CRPC cells have been proposed as mechanisms of CRPC development. Stem cell (SC)-like PC cells have been implicated not only as tumor initiating/maintaining in PC but also as tumor-reinitiating cells in CRPC. Recently, castration-resistant cells expressing the NK3 homeobox 1 (Nkx3-1) (CARNs), the other luminal markers cytokeratin 18 (CK18) and androgen receptor (AR), and possessing SC properties, have been found in castrated mouse prostate and proposed as the cell-of-origin of CRPC. However, the human counterpart of CARNs has not been identified yet. Here, we demonstrate that in the human PC xenograft BM18, preexisting SC-like and neuroendocrine (NE) PC cells are selected by castration and survive as totally quiescent. SClike BM18 cells, displaying the SC markers aldehyde dehydrogenase 1A1 or NANOG, coexpress the luminal markers NKX3-1, CK18, and a low level of AR (ARlow) but not basal or NE markers. These CR luminal SC-like cells, but not NE cells, reinitiate BM18 tumor growth after androgen replacement. The ARlow seems to mediate directly both castration survival and tumor reinitiation. This study identifies for the first time in human PC SC-/CARN-like cells that may represent the cell-of-origin of tumor reinitiation as CRPC. This finding will be fundamental for refining the hierarchy among human PC cancer cells and may have important clinical implications.

A novel manoeuvering model based on low-aspect-ratio lift theory and Lagrangian mechanics

This paper proposes a physically motivated reappraisal of manoeuvring models for ships and presents a new model developed from first principles by application of low aspect-ratio aerodynamic theory and Lagrangian mechanics. The coefficients of the model are shown to be related to physical processes, and validation is presented using the results from a planar motion mechanism dataset.

Coordination and plasticity in leaf anatomical traits of invasive and native vine species

Premise of the study: Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the dataset for this premise rarely include linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance. Methods: Three ecological pairs of invasive vs non-invasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g. water use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored. Key results: Mean leaf anatomical trait differed significantly between the two groups, except for stomatal size. Plasticity of traits, and to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration. Conclusions: The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum.

Evaluation of features for leaf classification in challenging conditions

Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

The current state of play in human neural stem cell models : what we have learnt from the rodent

Rodent (mouse and rat) models have been crucial in developing our understanding of human neurogenesis and neural stem cell (NSC) biology. The study of neurogenesis in rodents has allowed us to begin to understand adult human neurogenesis and in particular, protocols established for isolation and in vitro propagation of rodent NSCs have successfully been applied to the expansion of human NSCs. Furthermore, rodent models have played a central role in studying NSC function in vivo and in the development of NSC transplantation strategies for cell therapy applications. Rodents and humans share many similarities in the process of neurogenesis and NSC biology however distinct species differences are important considerations for the development of more efficient human NSC therapeutic applications. Here we review the important contributions rodent studies have had to our understanding of human neurogenesis and to the development of in vitro and in vivo NSC research. Species differences will be discussed to identify key areas in need of further development for human NSC therapy applications.

Linking pedagogical knowledge practices and student outcomes in STEM education for primary schools

STEM education is a new frontier in Australia, particularly for primary schools. However, the E in STEM needs to have a stronger focus with science and mathematics concepts aligned to the presiding curricula. In addition, pedagogical knowledge practices such as planning, preparation, teaching strategies, assessment and so forth need to be connected to key concepts for developing a STEM education. One of the aims of this study was to understand how a pedagogical knowledge practice framework could be linked to student outcomes in STEM education. Specifically, this qualitative research investigated Year 4 students’ involvement in an integrated STEM education program that focused on science concepts (e.g., states of matter, testing properties of materials) and mathematics concepts (such as 3D shapes and metric measurements: millilitres, temperature, grams, centimetres) for designing, making and testing a strong and safe medical kit to insulate medicines at desirable temperatures. Eleven pedagogical knowledge practices (e.g., planning, preparation, teaching strategies, classroom management, and assessment) were used as a framework for understanding how teaching may be linked to student outcomes in STEM education. For instance, “planning” involved devising a student booklet as a resource for students to understand the tasks required of them, which also provided space for them to record ideas, results and information. Planning involved linking national and state curriculum documents to the STEM education activities. More studies are required around pedagogical knowledge frameworks to understand what students learn when involved in STEM education, particularly with the inclusion of engineering education.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.