Modelling the dynamics of cutting during turning

This thesis presents an approach to cutting dynamics during turning based upon the mechanism of deformation of work material around the tool nose known as "ploughing". Starting from the shearing process in the cutting zone and accounting for "ploughing", new mathematical models relating turning force components to cutting conditions, tool geometry and tool vibration are developed. These models are developed separately for steady state and for oscillatory turning with new and worn tools. Experimental results are used to determine mathematical functions expressing the parameters introduced by the steady state model in the case of a new tool. The form of these functions are of general validity though their coefficients are dependent on work and tool materials. Good agreement is achieved between experimental and predicted forces. The model is extended on one hand to include different work material by introducing a hardness factor. The model provides good predictions when predicted forces are compared to present and published experimental results. On the other hand, the extension of the ploughing model to taming with a worn edge showed the ability of the model in predicting machining forces during steady state turning with the worn flank of the tool. In the development of the dynamic models, the dynamic turning force equations define the cutting process as being a system for which vibration of the tool tip in the feed direction is the input and measured forces are the output The model takes into account the shear plane oscillation and the cutting configuration variation in response to tool motion. Theoretical expressions of the turning forces are obtained for new and worn cutting edges. The dynamic analysis revealed the interaction between the cutting mechanism and the machine tool structure. The effect of the machine tool and tool post is accounted for by using experimental data of the transfer function of the tool post system. Steady state coefficients are corrected to include the changes in the cutting configuration with tool vibration and are used in the dynamic model. A series of oscillatory cutting tests at various conditions and various tool flank wear levels are carried out and experimental results are compared with model—predicted forces. Good agreement between predictions and experiments were achieved over a wide range of cutting conditions. This research bridges the gap between the analysis of vibration and turning forces in turning. It offers an explicit expression of the dynamic turning force generated during machining and highlights the relationships between tool wear, tool vibration and turning force. Spectral analysis of tool acceleration and turning force components led to define an "Inertance Power Ratio" as a flank wear monitoring factor. A formulation of an on—line flank wear monitoring methodology is presented and shows how the results of the present model can be applied to practical in—process tool wear monitoring in • turning operations.

Monitoring of transcriptional dynamics of HIF and NFκB activities

Genetic experiments over the last few decades have identified many regulatory proteins critical for DNA transcription. The dynamics of their transcriptional activities shape the differential expression of the genes they control. Here we describe a simple method, based on the secreted luciferase, to measure the activities of two transcription factors NF?B and HIF. This technique can effectively monitor dynamics of transcriptional events in a population of cells and be up-scaled for high-throughput screening and promoter analysis, making it ideal for data-demanding applications such as mathematical modelling.

Novel neuronal and astrocytic mechanisms in thalamocortical loop dynamics

In this review, we summarize three sets of findings that have recently been observed in thalamic astrocytes and neurons, and discuss their significance for thalamocortical loop dynamics. (i) A physiologically relevant ‘window’ component of the low–voltage–activated, T–type Ca2+ current (ITwindow) plays an essential part in the slow (less than 1 Hz) sleep oscillation in adult thalamocortical (TC) neurons, indicating that the expression of this fundamental sleep rhythm in these neurons is not a simple reflection of cortical network activity. It is also likely that ITwindow underlies one of the cellular mechanisms enabling TC neurons to produce burst firing in response to novel sensory stimuli. (ii) Both electrophysiological and dye–injection experiments support the existence of gap junction–mediated coupling among young and adult TC neurons. This finding indicates that electrical coupling–mediated synchronization might be implicated in the high and low frequency oscillatory activities expressed by this type of thalamic neuron. (iii) Spontaneous intracellular Ca2+ ([Ca2+]i) waves propagating among thalamic astrocytes are able to elicit large and long–lasting N–methyl–D–aspartate–mediated currents in TC neurons. The peculiar developmental profile within the first two postnatal weeks of these astrocytic [Ca2+]i transients and the selective activation of these glutamate receptors point to a role for this astrocyte–to–neuron signalling mechanism in the topographic wiring of the thalamocortical loop. As some of these novel cellular and intracellular properties are not restricted to thalamic astrocytes and neurons, their significance may well apply to (patho)physiological functions of glial and neuronal elements in other brain areas.

Neuronal network dynamics during epileptogenesis in the medial temporal lobe

Epilepsy is one of the most common neurological disorders, a large fraction of which is resistant to pharmacotherapy. In this light, understanding the mechanisms of epilepsy and its intractable forms in particular could create new targets for pharmacotherapeutic intervention. The current project explores the dynamic changes in neuronal network function in the chronic temporal lobe epilepsy (TLE) in rat and human brain in vitro. I focused on the process of establishment of epilepsy (epileptogenesis) in the temporal lobe. Rhythmic behaviour of the hippocampal neuronal networks in healthy animals was explored using spontaneous oscillations in the gamma frequency band (SγO). The use of an improved brain slice preparation technique resulted in the natural occurence (in the absence of pharmacological stimulation) of rhythmic activity, which was then pharmacologically characterised and compared to other models of gamma oscillations (KA- and CCh-induced oscillations) using local field potential recording technique. The results showed that SγO differed from pharmacologically driven models, suggesting higher physiological relevance of SγO. Network activity was also explored in the medial entorhinal cortex (mEC), where spontaneous slow wave oscillations (SWO) were detected. To investigate the course of chronic TLE establishment, a refined Li-pilocarpine-based model of epilepsy (RISE) was developed. The model significantly reduced animal mortality and demonstrated reduced intensity, yet high morbidy with almost 70% mean success rate of developing spontaneous recurrent seizures. We used SγO to characterize changes in the hippocampal neuronal networks throughout the epileptogenesis. The results showed that the network remained largely intact, demonstrating the subtle nature of the RISE model. Despite this, a reduction in network activity was detected during the so-called latent (no seizure) period, which was hypothesized to occur due to network fragmentation and an abnormal function of kainate receptors (KAr). We therefore explored the function of KAr by challenging SγO with kainic acid (KA). The results demonstrated a remarkable decrease in KAr response during the latent period, suggesting KAr dysfunction or altered expression, which will be further investigated using a variety of electrophysiological and immunocytochemical methods. The entorhinal cortex, together with the hippocampus, is known to play an important role in the TLE. Considering this, we investigated neuronal network function of the mEC during epileptogenesis using SWO. The results demonstrated a striking difference in AMPAr function, with possible receptor upregulation or abnormal composition in the early development of epilepsy. Alterations in receptor function inevitably lead to changes in the network function, which may play an important role in the development of epilepsy. Preliminary investigations were made using slices of human brain tissue taken following surgery for intratctable epilepsy. Initial results showed that oscillogenesis could be induced in human brain slices and that such network activity was pharmacologically similar to that observed in rodent brain. Overall, our findings suggest that excitatory glutamatergic transmission is heavily involved in the process of epileptogenesis. Together with other types of receptors, KAr and AMPAr contribute to epilepsy establishment and may be the key to uncovering its mechanism.

Thermalized polarization dynamics of a discrete optical-waveguide system with four-wave mixing

Statistical mechanics of two coupled vector fields is studied in the tight-binding model that describes propagation of polarized light in discrete waveguides in the presence of the four-wave mixing. The energy and power conservation laws enable the formulation of the equilibrium properties of the polarization state in terms of the Gibbs measure with positive temperature. The transition line T=∞ is established beyond which the discrete vector solitons are created. Also in the limit of the large nonlinearity an analytical expression for the distribution of Stokes parameters is obtained, which is found to be dependent only on the statistical properties of the initial polarization state and not on the strength of nonlinearity. The evolution of the system to the final equilibrium state is shown to pass through the intermediate stage when the energy exchange between the waveguides is still negligible. The distribution of the Stokes parameters in this regime has a complex multimodal structure strongly dependent on the nonlinear coupling coefficients and the initial conditions.

Insulin-like growth factor-I gene expression as a growth indicator in Nile tilapia Oreochromis niloticus L.

Somatic growth in fishes is regulated by a variety of hormones. A central step in this hormonal network is the growth hormone-insulin-like growth factor-I (IGF-I) axis. Studies conducted evaluated the relationship of hepatic IGF-I (hIGF-1) mRNA with growth as affected by feeding regimes (satiation or restricted level; daily or alternate-day feeding), temperatures (high, ambient, low) and by social stress. To develop a cellular means for the quantification of hIGF-I mRNA levels in O. niloticus, hIGF-I cDNA was isolated and cloned. The partial sequence of IGF-I cDNA encodes for signal peptide, mature protein and a portion of the E-domain. A sensitive TaqMan quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay was developed based on the mature IGF-I. Using the developed qRT-PCR assay a significant positive correlation was observed between hIGF-I mRNA levels and growth rate of fish reared under different feeding regimes (r = 0.64) and temperature conditions (r = 0.64). On the dynamics of hIGF-I gene expression in response to elevated temperature, hIGF-I mRNA levels were significantly elevated after at least 2 days of exposure to warm temperature. This validates the concept that hIGF-I gene expressions are sufficiently sensitive to be used as a rapid growth rate indicator for O. niloticus. The hIGF-I levels have a significant positive correlation with specific growth rate (length; r = 0.92), and with condition factor (r = 0.55). On the effect of social stress, differential alterations in growth rates between the dominant and subordinates were observed which was attributed more to behavioral changes as transduced by physiological regulators. The fish's relative position in the social hierarchy was consistently reflected in the levels of hIGF-I mRNA and the eye color pattern. Subordination depressed hIGF-I levels while dominance stimulated it. These findings have shown that hGF-I level remained positively correlated to growth rate as affected by feeding regime, temperature and social stress. This suggests that hIGF-I plays a key role in controlling growth in O. niloticus and indicates that IGF-I mRNA quantification could prove useful for the rapid assessment of growth rate in this species of fish.

Glutaredoxin-1 Is up-regulated in preeclampsia and increases soluble Flt-1 expression

INTRODUCTION: Preeclampsia is a vascular disorder in pregnancyand is biochemical characterization by high soluble Flt-1 and lowplacenta growth factor as well as an imbalance in redox homeostasis.During conditions of high oxidative stress, cysteine residues on keyproteins are reversibly altered by S-glutathionylation, modifying theirfunction. Glutaredoxin-1 (Glrx) enzymatically catalyzes the removal of S-glutathione adducts, conferring reversible signaling dynamics toproteins with redox-sensitive cysteines. The role of Glrx in preeclampsiais unknown.METHODS: Immunohistochemistry and Western blot analysis for Glrx orglutathione were conducted on human placenta samples collected pre-termfrom early onset preeclamptic patients (n=10) or non-preeclamptic induceddeliveries (n=9). Human endothelial cells were infected with adenovirusencoding Glrx or LacZ prior to the cells being exposed to hypoxia (0.1%O2, 24h) to measure changes in soluble Flt-1 (sFlt-1). Quantitative PCRand ELISA were used to measure sFlt-1 at mRNA and protein level.RESULTS: Immunohistochemical staining for GSH revealed lowerS-glutathionylation adducts in preeclampsia placenta in comparison tocontrols. Glrx expression, which catalyses de-glutathionylation wasenhanced in early onset preeclampsia compared to pre-term controlsamples. In contrast, no change was observed in preeclamptic and IUGRplacentas at full term. In endothelial cells overexpressing Glrx, sFlt-1expression was dramatically enhanced at mRNA (3-fold P<0.05) andprotein level (5 fold P>0.01, n=4) after hypoxia andoverexpressing Glrxin mice enhanced levels of circulating sFlt-1 during in vivo ischemia.CONCLUSIONS: Enhanced Glrx expression in preeclamptic placentain line with an apparent decrease in S-glutathionylation may leavekey proteins susceptible to irreversible oxidation in conditions of highoxidative stress.

Polymer Fluid Dynamics: Continuum and Molecular Appoaches

To solve problems in polymer fluid dynamics, one needs the equation of continuity, motion, and energy. The last two equations contain the stress tensor and the heat-flux vector for the material. There are two ways to formulate the stress tensor: (1) one can write a continuum expression for the stress tensor in terms of kinematic tensors, or (2) one can select a molecular model that represents the polymer molecule, and then develop an expression for the stress tensor from kinetic theory. The advantage of the kinetic theory approach is that one gets information about the relation between the molecular structure of the polymers and the rheological properties. In this review, we restrict the discussion primarily to the simplest stress tensor expressions or “constitutive equations” containing from two to four adjustable parameters, although we do indicate how these formulations may be extended to give more complicated expressions. We also explore how these simplest expressions are recovered as special cases of a more general framework, the Oldroyd 8-constant model. The virtue of studying the simplest models is that we can discover some general notions as to which types of empiricisms or which types of molecular models seem to be worth investigating further. We also explore equivalences between continuum and molecular approaches. We restrict the discussion to several types of simple flows, such as shearing flows and extensional flows. These are the flows that are of greatest importance in industrial operations. Furthermore, if these simple flows cannot be well described by continuum or molecular models, then it is not necessary to lavish time and energy to apply them to more complex flow problems.

Maternal and paternal growth regulatory factor expression in hybrid sunfish.

Unidirectional hybridization between bluegill (Lepomis macrochirus) and pumpkinseed (L. gibbosus) sunfish enables researchers to explore the relative expression of paternal and maternal alleles in hybrids. Past studies have found that the metabolic dysfunction in bluegill-pumpkinseed hybrids may be due to incompatibilities between nuclear and mitochondrial genomes. However, the consequences of hybridization on body size and muscle growth have not been examined. This topic is particularly interesting because hybrids grow larger than parentals despite the fact that they are often sired by smaller, precociously mature bluegills. In order to improve our understanding of growth dynamics in hybrid sunfish, I conducted real-time quantitative PCR using species-specific primers on the white muscle tissue of bluegills, pumpkinseeds, and hybrids collected from Lake Opinicon, ON. Five growth factors that have been linked to muscle growth and body size demonstrated similar expression for maternal and paternal alleles. While about half of the hybrids showed the same pattern with myogenin, about half showed very low levels of mRNA for the paternal (bluegill) gene. While this did not explain the heterosis seen in hybrids, it may explain the small body phenotype of the cuckholding bluegill males. I explored the upstream genetic structure of bluegill myogenin and established that four alleles exist within the population. Furthermore, I uncovered a relationship in hybrids between the proximal promoter/ 5’ UTR of myogenin and its transcript level. I found that the hybrids demonstrating low paternal myogenin expression unfailingly possessed A3 or A4 alleles, but future studies will be needed to reveal the molecular links between the genotype and the growth phenotype. A similar genotype-phenotype association was not obvious in parentals, even those that were homozygous for these alleles. Whether this relationship can provide insight into the genetic determinants of bluegill alternative mating strategies has yet to be determined.

The Democratic Dynamics of Government Consultations. Speaking Freely and Listening Properly

There is a growing use of consultation and e-consultation procedures by governments. This chapter seeks to examine the role of consultation as part of a new technology of government. Consultation on policy development can reinvigorate democratic engage- ment but often it can silence views through a sort of participatory disempowerment; it can loosen the democratic anchorage of the public service within the state. The chapter develops a governmentality perspective interrogating what participation, democratic engagement and free speech mean in this context, and how ideas of publicness are constructed, managed and controlled. The focus is on the nature of consultation, its relationship to ideas of free speech and speaking freely, and its potential to empower subaltern counterpublics which can formulate oppositional interpretations and urge alternative conclusions. The aim is to develop an idea of the democratic adequacy of the consultation process and draw out a sense of how democratic engagement here can be structured – for good or ill.

The interplay between neuronal activity and actin dynamics mimic the setting of an LTD synaptic tag

Persistent forms of plasticity, such as long-term depression (LTD), are dependent on the interplay between activity-dependent synaptic tags and the capture of plasticity-related proteins. We propose that the synaptic tag represents a structural alteration that turns synapses permissive to change. We found that modulation of actin dynamics has different roles in the induction and maintenance of LTD. Inhibition of either actin depolymerisation or polymerization blocks LTD induction whereas only the inhibition of actin depolymerisation blocks LTD maintenance. Interestingly, we found that actin depolymerisation and CaMKII activation are involved in LTD synaptic-tagging and capture. Moreover, inhibition of actin polymerisation mimics the setting of a synaptic tag, in an activity-dependent manner, allowing the expression of LTD in non-stimulated synapses. Suspending synaptic activation also restricts the time window of synaptic capture, which can be restored by inhibiting actin polymerization. Our results support our hypothesis that modulation of the actin cytoskeleton provides an input-specific signal for synaptic protein capture.

OPA1-related disorders: Diversity of clinical expression, modes of inheritance and pathophysiology

International audience

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.

Metastability and dynamics of stem cells: from direct observations to inference at the single cell level

Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.

Guided Migration and Collective Behavior: Cell Dynamics during Cancer Progression

This dissertation focuses on gaining understanding of cell migration and collective behavior through a combination of experiment, analysis, and modeling techniques. Cell migration is a ubiquitous process that plays an important role during embryonic development and wound healing as well as in diseases like cancer, which is a particular focus of this work. As cancer cells become increasingly malignant, they acquire the ability to migrate away from the primary tumor and spread throughout the body to form metastatic tumors. During this process, changes in gene expression and the surrounding tumor environment can lead to changes in cell migration characteristics. In this thesis, I analyze how cells are guided by the texture of their environment and how cells cooperate with their neighbors to move collectively. The emergent properties of collectively moving groups are a particular focus of this work as collective cell dynamics are known to change in diseases such as cancer. The internal machinery for cell migration involves polymerization of the actin cytoskeleton to create protrusions that---in coordination with retraction of the rear of the cell---lead to cell motion. This actin machinery has been previously shown to respond to the topography of the surrounding surface, leading to guided migration of amoeboid cells. Here we show that epithelial cells on nanoscale ridge structures also show changes in the morphology of their cytoskeletons; actin is found to align with the ridge structures. The migration of the cells is also guided preferentially along the ridge length. These ridge structures are on length scales similar to those found in tumor microenvironments and as such provide a system for studying the response of the cells' internal migration machinery to physiologically relevant topographical cues. In addition to sensing surface topography, individual cells can also be influenced by the pushing and pulling of neighboring cells. The emergent properties of collectively migrating cells show interesting dynamics and are relevant for cancer progression, but have been less studied than the motion of individual cells. We use Particle Image Velocimetry (PIV) to extract the motion of a collectively migrating cell sheet from time lapse images. The resulting flow fields allow us to analyze collective behavior over multiple length and time scales. To analyze the connection between individual cell properties and collective migration behavior, we compare experimental flow fields with the migration of simulated cell groups. Our collective migration metrics allow for a quantitative comparison between experimental and simulated results. This comparison shows that tissue-scale decreases in collective behavior can result from changes in individual cell activity without the need to postulate the existence of subpopulations of leader cells or global gradients. In addition to tissue-scale trends in collective behavior, the migration of cell groups includes localized dynamic features such as cell rearrangements. An individual cell may smoothly follow the motion of its neighbors (affine motion) or move in a more individualistic manner (non-affine motion). By decomposing individual motion into both affine and non-affine components, we measure cell rearrangements within a collective sheet. Finally, finite-time Lyapunov exponent (FTLE) values capture the stretching of the flow field and reflect its chaotic character. Applying collective migration analysis techniques to experimental data on both malignant and non-malignant human breast epithelial cells reveals differences in collective behavior that are not found from analyzing migration speeds alone. Non-malignant cells show increased cooperative motion on long time scales whereas malignant cells remain uncooperative as time progresses. Combining multiple analysis techniques also shows that these two cell types differ in their response to a perturbation of cell-cell adhesion through the molecule E-cadherin. Non-malignant MCF10A cells use E-cadherin for short time coordination of collective motion, yet even with decreased E-cadherin expression, the cells remain coordinated over long time scales. In contrast, the migration behavior of malignant and invasive MCF10CA1a cells, which already shows decreased collective dynamics on both time scales, is insensitive to the change in E-cadherin expression.