Optical trapping with "on-demand" two-photon luminescence using Cr:LiSAF laser with optically addressed saturable Bragg reflector

We demonstrate a diode-pumped Cr:LiSAF laser with controllable and reliable fast switching between its continuous-wave and mode-locked states of operation using an optically-addressed semiconductor Bragg reflector, permitting dyed microspheres to be continuously trapped and monitored using a standard microscope imaging and on-demand two-photon-excited luminescence techniques

Development of Multigene Expression Signature Maps at the Protein Level from Digitized Immunohistochemistry Slides

Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC) is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps) of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions

Longitudinal optical binding

Longitudinal optical binding refers to the light induced self organisation of micro particles in one dimension. In this thesis I will present experimental and theoretical studies of the separation between two dielectric spheres in a counter-propagating (CP) geometry. I will explore the bistable nature of the bound sphere separation and its dependency on the refractive index mismatch between the spheres and the host medium, with an emphasis on the fibre separation. The physical under pining principle of longitudinal optical binding in the Mie regime is the refocusing effect of the light field from one sphere to its nearest neighbour. In a second set of experiments I developed means to visualise the field intensity distribution responsible for optical binding using two-photon fluorescence imaging from fluorescein added to the host medium. The experimental intensity distributions are compared to theoretical predictions and provide an in situ method to observe the binding process in real time. This coupling via the refocused light fields between the spheres is in detailed investigated experimentally and theoretically, in particular I present data and analysis on the correlated behaviour of the micro spheres in the presence of noise. The measurement of the decay times of the correlation functions of the modes of the optically bound array provides a methodology for determining the optical restoring forces acting in optical binding. Interestingly micro devices can be initiated by means of the light-matter interaction. Light induced forces and torques are exerted on such micro-objects that are then driven by the optical gradient or scattering force. I have experimentally investigate how the driving light interacts with and diffracts from the motor, utilising two-photon imaging. The micromotor rotation rate dependence on the light field parameters is explored and theoretically modelled. The results presented will show that the model can be used to optimise the system geometry and the micromotor

Construction and calibration of an optical trap on a fluorescence optical microscope

The application of optical traps has come to the fore in the last three decades. They provide a powerful, sterile and noninvasive tool for the manipulation of cells, single biological macromolecules, colloidal microparticles and nanoparticles. An optically trapped microsphere may act as a force transducer that is used to measure forces in the piconewton regime. By setting up a well-calibrated single-beam optical trap within a fluorescence microscope system, one can measure forces and collect fluorescence signals upon biological systems simultaneously. In this protocol, we aim to provide a clear exposition of the methodology of assembling and operating a single-beam gradient force trap (optical tweezers) on an inverted fluorescence microscope. A step-by-step guide is given for alignment and operation, with discussion of common pitfalls.</p

Glossary of Terms.

<p>Glossary of Terms.</p

Media 1: Optical trapping with “on-demand” two-photon luminescence using Cr:LiSAF laser with optically addressed saturable Bragg reflector

Originally published in Optics Express on 26 March 2012 (oe-20-7-7066

Generation of an IHC Signature Map.

<p>Displayed values of the IHC maps and IHC signature maps are in relative units (r. u.). (<b>A</b>) IHC Map for ENO2, shown in red since the weighting factor was positively signed (higher expression is associated with aggressive disease) and thus higher expression was shown as more intense red. (<b>B</b>) IHC Map for CD34 (also shown in red due to positively signed weighting factor). (<b>C</b>) IHC Map for MKI67 (also shown in red due to positively signed weighing factor). (<b>D</b>) IHC Map for ACPP, shown in blue since the weighting factor was negatively signed (higher expression is associated with non-aggressive disease) and thus higher expression was shown as more intense blue. (<b>E</b>) The weighted sum of IHC Scores (termed an IHC Signature Map) were projected in grid squares across annotated tumor areas of Gleason scores 3+3, 3+4, and 4+3 outlined in green, yellow and red, respectively.</p

Four-gene IHC signature map.

<p>The IHC signature map is displayed in relative units (r. u.), projected against a black background to illustrate the four-gene signature map in each pathologist-annotated area (tumor areas of Gleason sum scores 3+3, 3+4, and 4+3 outlined in green, yellow and red, respectively).</p

IHC signature scores from 11 annotated regions of cancer from 10 subjects.

<p>The benchmark (blue) and native (red) data for the same region are shown immediately adjacent to each other for comparison. For each region, the minimum, 1^st quartile, median, 3^rd quartile and the maximum values are shown. The data are sorted first by grade and then by the median of the benchmark data within each grade.</p

Registration errors between the IHC and H&E images.

<p>Registration errors between each of the 3 IHC datasets registered to the reference H&E data for all 10 subjects. The error estimate is based on the vector distance between landmarks placed on the same anatomic features present in the registered IHC and reference H&E slides. The histogram contains 5 measurements for each of 3 IHC datasets for 10 cases resulting in a total of 150 error estimates. The histogram shows the stain dependent errors for ACPP (blue), MKI67 (red) and CD34 (green).</p