In the development of multicellular organisms, tissue development and homeostasis require coordinated cellular motion. For example, in conditions such as wound healing, immune and epithelial cells need to proliferate and migrate. Deregulation of key signalling pathways in pathological conditions causes alterations in cellular motion properties that are critical for disease development and progression, in cancer it leads to invasion and metastasis. Consequently there is strong interest in identifying factors, including drugs that affect the motion and interactions of cells in disease using experimental models suitable for high-content screening. There are two main modes of cell migration; individual and collective migration. Currently analysis tools for robust, sensitive and comprehensive motion characterisation in varying experimental conditions for large extended timelapse acquisitions that jointly considers both modes are limited. We have developed a systematic motion analysis framework, Motion Sensing Superpixels (MOSES) to quantitatively capture cellular motion in timelapse microscopy videos suitable for high-content screening. MOSES builds upon established computer vision approaches to deliver a minimal parameter, robust algorithm that can i) extract reliable phenomena-relevant motion metrics, ii) discover spatiotemporal salient motion patterns and iii) facilitate unbiased analysis with little prior knowledge through unique motion 'signatures'. The framework was validated by application to numerous datasets including YouTube videos, zebrafish immunosurveillance and Drosophila embryo development. We demonstrate two extended applications; the analysis of interactions between two epithelial populations in 2D culture using cell lines of the squamous and columnar epithelia from human normal esophagus, Barrett's esophagus and esophageal adenocarcinoma and the automatic monitoring of 3D organoid culture growth captured through label-free phase contrast microscopy. MOSES found unique boundary formation between squamous and columnar cells and could measure subtle changes in boundary formation due to external stimuli. MOSES automatically segments the motion and shape of multiple organoids even if present in the same field of view. Automated analysis of intestinal organoid branching following treatment agrees with independent RNA-seq results.

This study investigated the comparison between captured and revealed Pedagogical Content Knowledge (PCK) about graphs of motion. The aim of the study was to explore PCK when captured in a written format and discussions (captured PCK) and compare it to the PCK that the same teachers revealed in practice (revealed PCK) when teaching the topic. Four Grade 10 Physical sciences teachers were purposively and conveniently selected as participants of the study. Their PCK was captured through Content Representations (CoRes) and interviews. The revealed PCK on the other hand was gathered through lesson observations. The Topic Specific Pedagogical Content Knowledge (TSPCK) model was used as the framework that guided the analysis of the two manifestations of PCK. The focus was on teachers’ competences in the TSPCK components namely; learners’ prior knowledge including misconceptions, curricular saliency, what is difficult to teach, representations including analogies, and conceptual teaching strategies. The results of this study indicated that teachers’ competences in the TSPCK components varied. This was evident in both the captured and the revealed PCK. Thus it suggested that a teacher’s level of competence in one component is not necessarily an indication of his or her competence in the other components that define PCK, and subsequently in his/her overall captured or revealed PCK. Furthermore, the study suggested that the level of competence in a component in the captured PCK is not necessarily an indication of the level of competence within that component that the teacher would reveal during lesson presentation. The level may be the same, slightly different (higher or lower) or even be drastically different in the lesson than suggested by the captured PCK. A concluding remark was then made that teachers’ captured PCK is not necessarily a true reflection of the PCK they reveal during lesson presentation and that different instruments must be used to reflect on and assess teachers’ PCK in a topic. / Dissertation (MEd)--University of Pretoria, 2017. / Science, Mathematics and Technology Education / MEd / Unrestricted