998 resultados para TEMPORAL STEM


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Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

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Mesenchymal stem cells (MSC) are emerging as a leading cellular therapy for a number of diseases. However, for such treatments to become available as a routine therapeutic option, efficient and cost-effective means for industrial manufacture of MSC are required. At present, clinical grade MSC are manufactured through a process of manual cell culture in specialized cGMP facilities. This process is open, extremely labor intensive, costly, and impractical for anything more than a small number of patients. While it has been shown that MSC can be cultivated in stirred bioreactor systems using microcarriers, providing a route to process scale-up, the degree of numerical expansion achieved has generally been limited. Furthermore, little attention has been given to the issue of primary cell isolation from complex tissues such as placenta. In this article we describe the initial development of a closed process for bulk isolation of MSC from human placenta, and subsequent cultivation on microcarriers in scalable single-use bioreactor systems. Based on our initial data, we estimate that a single placenta may be sufficient to produce over 7,000 doses of therapeutic MSC using a large-scale process.

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Nerve tissue engineering requires suitable precursor cells as well as the necessary biochemical and physical cues to guide neurite extension and tissue development. An ideal scaffold for neural regeneration would be both fibrous and electrically conductive. We have contrasted the growth and neural differentiation of mouse embryonic stem cells on three different aligned nanofiber scaffolds composed of poly L: -lactic acid supplemented with either single- or multi-walled carbon-nanotubes. The addition of the nanotubes conferred conductivity to the nanofibers and promoted mESC neural differentiation as evidenced by an increased mature neuronal markers expression. We propose that the conductive scaffold could be a useful tool for the generation of neural tissue mimics in vitro and potentially as a scaffold for the repair of neural defects in vivo.

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Hematopoietic stem cell (HSC) transplant is a well established curative therapy for some hematological malignancies. However, achieving adequate supply of HSC from some donor tissues can limit both its application and ultimate efficacy. The theory that this limitation could be overcome by expanding the HSC population before transplantation has motivated numerous laboratories to develop ex vivo expansion processes. Pioneering work in this field utilized stromal cells as support cells in cocultures with HSC to mimic the HSC niche. We hypothesized that through translation of this classic coculture system to a three-dimensional (3D) structure we could better replicate the niche environment and in turn enhance HSC expansion. Herein we describe a novel high-throughput 3D coculture system where murine-derived HSC can be cocultured with mesenchymal stem/stromal cells (MSC) in 3D microaggregates—which we term “micromarrows.” Micromarrows were formed using surface modified microwells and their ability to support HSC expansion was compared to classic two-dimensional (2D) cocultures. While both 2D and 3D systems provide only a modest total cell expansion in the minimally supplemented medium, the micromarrow system supported the expansion of approximately twice as many HSC candidates as the 2D controls. Histology revealed that at day 7, the majority of bound hematopoietic cells reside in the outer layers of the aggregate. Quantitative polymerase chain reaction demonstrates that MSC maintained in 3D aggregates express significantly higher levels of key hematopoietic niche factors relative to their 2D equivalents. Thus, we propose that the micromarrow platform represents a promising first step toward a high-throughput HSC 3D coculture system that may enable in vitro HSC niche recapitulation and subsequent extensive in vitro HSC self-renewal.

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Despite efforts to motivate students to engage in Science, technology, engineering and mathematics (STEM) education, women are still underrepresented in these areas in the workforce and higher education. Targeting females at high school or earlier may be a key towards engaging them in STEM. In this paper we report on the research question: How do middle school females interact for learning about engineering education? This ethnographic study, part of a three-year longitudinal research project, investigated Year 8 female students’ learning about engineering concepts associated with designing, constructing, testing, and evaluating a catapult. Through a series of lead-up lessons and the four lesson catapult challenge (total of 18 x 45-minute lessons over 9 weeks), data from two girls within a focus group showed that the students needed to: (1) receive clarification on engineering terms to facilitate more fluent discourse, (2) question and debate conceptual understandings without peers being judgemental, and (3) have multiple opportunities for engaging with materials towards designing, constructing and explaining key concepts learnt. Implications for teachers undertaking STEM education are evident, including outlining expectations for clarifying STEM terms, outlining to students about interacting non-judgementally, and providing multiple opportunities for interacting within engineering education.

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Implementing educational reform requires partnerships, and university-school collaborations in the form of investigative and experimental projects can aim to determine the practicalities of reform. However, there are funded projects that do not achieve intended outcomes. In the context of a new reform initiative in education, namely, science, technology, engineering and mathematics (STEM) education, this article explores the management of a government-funded project. In a university school partnership for STEM education, how can leadership be distributed for achieving project outcomes? Participants included university personnel from different STEM areas, school teachers and school executives. Data collected included observations, interviews, resource materials, and video and photographic images. Findings indicated that leadership roles were distributed and selfactivated by project partners according to their areas of expertise and proximal activeness to the project phases, that is: (1) establishing partnerships; (2) planning and collaboration; (3) project implementation; and (4) project evaluation and further initiatives. Leadership can be intentional and unintentional within project phases, and understanding how leadership can be distributed and selfactivated more purposefully may aid in generating more expedient project outcomes.

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Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

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Introduction: Inherent and acquired cisplatin resistance reduces the effectiveness of this agent in the management of non-small cell lung cancer (NSCLC). Understanding the molecular mechanisms underlying this process may result in the development of novel agents to enhance the sensitivity of cisplatin. Methods: An isogenic model of cisplatin resistance was generated in a panel of NSCLC cell lines (A549, SKMES-1, MOR, H460). Over a period of twelve months, cisplatin resistant (CisR) cell lines were derived from original, age-matched parent cells (PT) and subsequently characterized. Proliferation (MTT) and clonogenic survival assays (crystal violet) were carried out between PT and CisR cells. Cellular response to cisplatin-induced apoptosis and cell cycle distribution were examined by FACS analysis. A panel of cancer stem cell and pluripotent markers was examined in addition to the EMT proteins, c-Met and β-catenin. Cisplatin-DNA adduct formation, DNA damage (γH2AX) and cellular platinum uptake (ICP-MS) was also assessed. Results: Characterisation studies demonstrated a decreased proliferative capacity of lung tumour cells in response to cisplatin, increased resistance to cisplatin-induced cell death, accumulation of resistant cells in the G0/G1 phase of the cell cycle and enhanced clonogenic survival ability. Moreover, resistant cells displayed a putative stem-like signature with increased expression of CD133+/CD44+cells and increased ALDH activity relative to their corresponding parental cells. The stem cell markers, Nanog, Oct-4 and SOX-2, were significantly upregulated as were the EMT markers, c-Met and β-catenin. While resistant sublines demonstrated decreased uptake of cisplatin in response to treatment, reduced cisplatin-GpG DNA adduct formation and significantly decreased γH2AX foci were observed compared to parental cell lines. Conclusion: Our results identified cisplatin resistant subpopulations of NSCLC cells with a putative stem-like signature, providing a further understanding of the cellular events associated with the cisplatin resistance phenotype in lung cancer. © 2013 Barr et al.

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The cancer stem-cell (CSC) hypothesis suggests that there is a small subset of cancer cells that are responsible for tumor initiation and growth, possessing properties such as indefinite self-renewal, slow replication, intrinsic resistance to chemotherapy and radiotherapy, and an ability to give rise to differentiated progeny. Through the use of xenotransplantation assays, putative CSCs have been identified in many cancers, often identified by markers usually expressed in normal stem cells. This is also the case in lung cancer, and the accumulated data on side population cells, CD133, CD166, CD44 and ALDH1 are beginning to clarify the true phenotype of the lung cancer stem cell. Furthermore, it is now clear that many of the pathways of normal stem cells, which guide cellular proliferation, differentiation, and apoptosis are also prominent in CSCs; the Hedgehog (Hh), Notch, and Wnt signaling pathways being notable examples. The CSC hypothesis suggests that there is a small reservoir of cells within the tumor, which are resistant to many standard therapies, and can give rise to new tumors in the form of metastases or relapses after apparent tumor regression. Therapeutic interventions that target CSC pathways are still in their infancy and clinical data of their efficacy remain limited. However Smoothened inhibitors, gamma-secretase inhibitors, anti-DLL4 antagonists, Wnt antagonists, and CBP/β-catenin inhibitors have all shown promising anticancer effects in early studies. The evidence to support the emerging picture of a lung cancer CSC phenotype and the development of novel therapeutic strategies to target CSCs are described in this review.

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Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

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Resistance to chemotherapy and metastases are the major causes of breast cancer-related mortality. Moreover, cancer stem cells (CSC) play critical roles in cancer progression and treatment resistance. Previously, it was found that CSC-like cells can be generated by aberrant activation of epithelial–mesenchymal transition (EMT), thereby making anti-EMT strategies a novel therapeutic option for treatment of aggressive breast cancers. Here, we report that the transcription factor FOXC2 induced in response to multiple EMT signaling pathways as well as elevated in stem cell-enriched factions is a critical determinant of mesenchymal and stem cell properties, in cells induced to undergo EMT- and CSC-enriched breast cancer cell lines. More specifically, attenuation of FOXC2 expression using lentiviral short hairpin RNA led to inhibition of the mesenchymal phenotype and associated invasive and stem cell properties, which included reduced mammosphere-forming ability and tumor initiation. Whereas, overexpression of FOXC2 was sufficient to induce CSC properties and spontaneous metastasis in transformed human mammary epithelial cells. Furthermore, a FOXC2-induced gene expression signature was enriched in the claudin-low/basal B breast tumor subtype that contains EMT and CSC features. Having identified PDGFR-β to be regulated by FOXC2, we show that the U.S. Food and Drug Administration-approved PDGFR inhibitor, sunitinib, targets FOXC2-expressing tumor cells leading to reduced CSC and metastatic properties. Thus, FOXC2 or its associated gene expression program may provide an effective target for anti-EMT-based therapies for the treatment of claudin-low/basal B breast tumors or other EMT-/CSC-enriched tumors.

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This paper begins by identifying three main reasons why many of the more STEM-Talented students at our universities do not consider enrolling in STEM teacher education programs. Then based on a review of the literature, a framework for addressing this dilemma is presented and discussed. This framework consists of a set of three principles together with eleven strategies for the operationalization of these principles. During the presentation of the framework, the roles of governments and of universities at the institutional, faculty/division and departmental levels in the operationalization of the frameworks are examined.