Matthew Caldwell

Nanoscale live cell imaging using hopping probe ion conductance microscopy

We describe hopping mode scanning ion conductance microscopy that allows noncontact imaging of the complex three-dimensional surfaces of live cells with resolution better than 20 nm. We tested the effectiveness of this technique by imaging networks of cultured rat hippocampal neurons and mechanosensory stereocilia of mouse cochlear hair cells. The technique allowed examination of nanoscale phenomena on the surface of live cells under physiological conditions.

Contact-Free Scanning and Imaging with the Scanning Ion Conductance Microscope

Scanning ion conductance microscopy (SICM) offers the ability to obtain very high-resolution topographical images of living cells. One of the great advantages of SICM lies in its ability to perform contact-free scanning. However, it is not yet clear when the requirements for this scan mode are met. We have used finite element modeling (FEM) to examine the conditions for contact-free scanning. Our findings provide a framework for understanding the contact-free mode of SICM and also extend previous findings with regard to SICM resolution. Finally, we demonstrate the importance of our findings for accurate biological imaging.

Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy.

Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, ‘BrainSignals’. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors.

Method for Estimating the Tip Geometry of Scanning Ion Conductance Microscope Pipets

Scanning ion conductance microscopy (SICM) offers the ability to perform contact-free, high-resolution imaging of biological cells and tissues at physiological conditions. However, imaging resolution is highly dependent on the geometry of the SICM probe, which is generally not known. Small, high-resolution probes are too fine to image optically and, to date, geometry estimation has usually required electron microscopy (EM). This is time-consuming and prone to failure and cannot provide information about the crucial internal geometry of the probe. Here we demonstrate a new method for determining SICM tip geometry that overcomes the limitations of EM imaging. The method involves fitting an analytical model to current changes during quasi-controlled breakage of the pipet tip. The data can be routinely obtained using the SICM apparatus itself and our method thus opens the way for substantially better quantification in SICM imaging and measurement.

BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology.

Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time.

Corrigendum: Nanoscale live-cell imaging using hopping probe ion conductance microscopy

Nat. Methods 6, 279–281 (2009); published online 1 March 2009; corrected after print 3 September 2009. In the version of this paper originally published, references to previous work on pulse mode SICM should have been included (Mann, S.A. et al. J. Neurosci. Methods 116, 113–117, (2002) and Happel, P.

Modelling Blood Flow and Metabolism in the Preclinical Neonatal Brain during and Following Hypoxic-Ischaemia

Hypoxia-ischaemia (HI) is a major cause of neonatal brain injury, often leading to long-term damage or death. In order to improve understanding and test new treatments, piglets are used as preclinical models for human neonates. We have extended an earlier computational model of piglet cerebral physiology for application to multimodal experimental data recorded during episodes of induced HI. The data include monitoring with near-infrared spectroscopy (NIRS) and magnetic resonance spectroscopy (MRS), and the model simulates the circulatory and metabolic processes that give rise to the measured signals. Model extensions include simulation of the carotid arterial occlusion used to induce HI, inclusion of cytoplasmic pH, and loss of metabolic function due to cell death. Model behaviour is compared to data from two piglets, one of which recovered following HI while the other did not. Behaviourally-important model parameters are identified via sensitivity analysis, and these are optimised to simulate the experimental data. For the non-recovering piglet, we investigate several state changes that might explain why some MRS and NIRS signals do not return to their baseline values following the HI insult. We discover that the model can explain this failure better when we include, among other factors such as mitochondrial uncoupling and poor cerebral blood flow restoration, the death of around 40% of the brain tissue.

Simulation of Preterm Neonatal Brain Metabolism During Functional Neuronal Activation Using a Computational Model

We present a computational model of metabolism in the preterm neonatal brain. The model has the capacity to mimic haemodynamic and metabolic changes during functional activation and simulate functional near-infrared spectroscopy (fNIRS) data. As an initial test of the model’s efficacy, we simulate data obtained from published studies investigating functional activity in preterm neonates. In addition we simulated recently collected data from preterm neonates during visual activation. The model is well able to predict the haemodynamic and metabolic changes from these observations. In particular, we found that changes in cerebral blood flow and blood pressure may account for the observed variability of the magnitude and sign of stimulus-evoked haemodynamic changes reported in preterm infants.

WeBCMD: A cross-platform interface for the BCMD modelling framework

Multimodal monitoring of the brain generates a great quantity of data, providing the potential for great insight into both healthy and injured cerebral dynamics. In particular, near-infrared spectroscopy can be used to measure various physiological variables of interest, such as haemoglobin oxygenation and the redox state of cytochrome-c-oxidase, alongside systemic signals, such as blood pressure. Interpreting these measurements is a complex endeavour, and much work has been done to develop mathematical models that can help to provide understanding of the underlying processes that contribute to the overall dynamics. BCMD is a software framework that was developed to run such models. However, obtaining, installing and running this software is no simple task. Here we present WeBCMD, an online environment that attempts to make the process simpler and much more accessible. By leveraging modern web technologies, an extensible and cross-platform package has been created that can also be accessed remotely from the cloud. WeBCMD is available as a Docker image and an online service.

Estimating the Geometry of Scanning Ion Conductance Microscope Pipettes from Resistance Variation with Breakage

The spatial resolution and non-contact working conditions of a scanning ion conductance microscope (SICM) are largely determined by the size and shape of the scanning probe tip. Estimating the tip geometry has traditionally required the use of scanning electron microscopy (SEM), a difficult, time-consuming process that, even if successful, provides little information about the crucial inner geometry of the probe. As a result, such measurements are not routinely made. Instead, tip sizes are often crudely estimated from pipette resistances. We have developed a simple method of more precisely estimating the geometry (tip radius and inner cone angle) from multiple resistance measurements recorded during quasi-controlled breakage of the tip. Such measurements can be easily obtained using only the standard SICM apparatus. Results compare favourably with SEM estimates, are more informative and avoid some of the assumptions necessary for SEM estimation.