Optimising the assessment of cerebral autoregulation from black box models

Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and non-linear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single – or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end 26 recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a ‘gold’ standard for the study of dynamic CA, lower inter- and intra-subject variability of the parameters in relation to the difference between normo- and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies

A novel video-tracking system to quantify the behaviour of nocturnal mosquitoes attacking human hosts in the field

Many vectors of malaria and other infections spend most of their adult life within human homes, the environment where they bloodfeed and rest, and where control has been most successful. Yet, knowledge of peri-domestic mosquito behaviour is limited, particularly how mosquitoes find and attack human hosts or how insecticides impact on behaviour. This is partly because technology for tracking mosquitoes in their natural habitats, traditional dwellings in disease-endemic countries, has never been available. We describe a sensing device that enables observation and recording of nocturnal mosquitoes attacking humans with or without a bed net, in the laboratory and in rural Africa. The device addresses requirements for sub-millimetre resolution over a 2.0 x 1.2 x 2.0 m volume while using minimum irradiance. Data processing strategies to extract individual mosquito trajectories and algorithms to describe behaviour during host/net interactions are introduced. Results from UK laboratory and Tanzanian field tests showed that Culex quinquefasciatus activity was higher and focused on the bed net roof when a human host was present, in colonized and wild populations. Both C. quinquefasciatus and Anopheles gambiae exhibited similar behavioural modes, with average flight velocities varying by less than 10%. The system offers considerable potential for investigations in vector biology and many other fields

DeadEasy Mito-Glia: Automatic Counting of Mitotic Cells and Glial Cells in Drosophila

Cell number changes during normal development, and in disease (e.g., neurodegeneration, cancer). Many genes affect cell number, thus functional genetic analysis frequently requires analysis of cell number alterations upon loss of function mutations or in gain of function experiments. Drosophila is a most powerful model organism to investigate the function of genes involved in development or disease in vivo. Image processing and pattern recognition techniques can be used to extract information from microscopy images to quantify automatically distinct cellular features, but these methods are still not very extended in this model organism. Thus cellular quantification is often carried out manually, which is laborious, tedious, error prone or humanly unfeasible. Here, we present DeadEasy Mito-Glia, an image processing method to count automatically the number of mitotic cells labelled with anti-phospho-histone H3 and of glial cells labelled with anti-Repo in Drosophila embryos. This programme belongs to the DeadEasy suite of which we have previously developed versions to count apoptotic cells and neuronal nuclei. Having separate programmes is paramount for accuracy. DeadEasy Mito-Glia is very easy to use, fast, objective and very accurate when counting dividing cells and glial cells labelled with a nuclear marker. Although this method has been validated for Drosophila embryos, we provide an interactive window for biologists to easily extend its application to other nuclear markers and other sample types. DeadEasy MitoGlia is freely available as an ImageJ plug-in, it increases the repertoire of tools for in vivo genetic analysis, and it will be of interest to a broad community of developmental, cancer and neuro-biologists

Optimising the assessment of cerebral autoregulation from black box models

Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and non-linear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single – or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end 26 recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a ‘gold’ standard for the study of dynamic CA, lower inter- and intra-subject variability of the parameters in relation to the difference between normo- and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies

Wavefront sensing for single view three-component three-dimensional flow velocimetry

We present the application of wavefront sensing to particle image velocimetry for three-component (3C), three-dimensional (3D) flow measurement from a single view. The technique is based upon measuring the wavefront scattered by a tracer particle and from that wavefront the 3D tracer location can be determined. Hence, from a temporally resolved sequence of 3D particle locations the velocity vector field is obtained. Two approaches to capture the data required to measure the wavefronts are described: multi-planar imaging using a distorted diffraction grating and an anamorphic technique. Both techniques are optically efficient, robust and compatible with coherent and incoherent scattering from flow tracers. The depth (range) resolution and repeatability have been quantified experimentally using a single mode fiber source representing a tracer particle. The anamorphic approach is shown to have the greatest measurement range and hence was selected for the first proof of principle experiments using this technique for 3D particle imaging velocimetry (PIV) on a sparsely seeded gas phase flow.</p

Wavefront sensing for three-component three-dimensional flow velocimetry in microfluidics

We present the application of wavefront sensing to three-component, three-dimensional micro particle tracking velocimetry (lPTV). The technique is based upon examining the defocus of the wavefront scattered by a tracer particle and from such information establishing the 3-D tracer location. The imaging system incorporates a cylindrical lens acting as an anamorphic element that creates different magnifications in the two orthogonal axes. A single anamorphic image is obtained from each tracer, which contains sufficient information to reconstruct the wavefront defocus and uniquely identify the tracer’s axial position. A mathematical model of the optical system is developed and shows that the lateral and depth performance of the sensor can be largely independently varied across a wide range. Hence, 3-D image resolution can be achieved from a single viewpoint, using simple and inexpensive optics and applied to a wide variety of microfluidic or biological systems. Our initial results show that an uncertainty in depth of 0.18 µm was achieved over a 20 µm range. The technique was employed to measure the 3-D velocity field of micron-sized fluorescent tracers in a flow within a micro channel, and an uncertainty of 2.8 µm was obtained in the axial direction over a range of 500 µm. The experimental results were in agreement with the expected fluid flow when compared to the corresponding CFD model. Thus, wavefront sensing proved to be an effective approach to obtain quantitative measurements of three component three-dimensional flows in microfluidic devices