Visualization 2: Looking inside the heart: a see-through view of the vascular tree

Visualization 2. 3D imaging of the vasculature obtained with SPIM following perfusion with FITC-labelled lectin Originally published in Biomedical Optics Express on 01 June 2017 (boe-8-6-3110

Visualization 1: Looking inside the heart: a see-through view of the vascular tree

Visualization 1. 3D imaging of the vasculature obtained with SPIM following anti-CD31 labelling Originally published in Biomedical Optics Express on 01 June 2017 (boe-8-6-3110

Media 1: Helical optical projection tomography

Originally published in Optics Express on 04 November 2013 (oe-21-22-25912

A versatile imaging platform for light sheet microscopy and FRAP.

<p>(A) 3D scheme of the LSM and components (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s005" target="_blank">S1 Video</a> for full 3D overview of the setup and compare photographs in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s001" target="_blank">S1 Fig</a>). The red line indicates the path of the laser beam. The laser beam is guided by a flexible mirror set to pass through the cylindrical lens, where a laser light sheet is created and focused on the sample, which is immersed in an index matching fluid bath. A 3D stage is used to move the sample along x-, y- and z-axis into position for imaging via the CCD camera with tube lens attachment, which is placed orthogonal to the light sheet. Components for FRAP performance are encircled and consist of a flip mirror and a focal lens to concentrate the beam for fluorescent photobleaching of the sample. A detailed description is provided in Materials and Methods. (B) Basic 2D scheme of the setup showing its essential components. LAS = laser, SH = shutter, FM = flip mirror, CL = cylindrical lens, FL1 = focal lens 1, FL2 = focal lens 2, OS = 3D stage, RBS = Refractive index matching fluid bath and sample, LED = white light LED, CCD = CCD camera, TL = tube lens, I = iris, F = fluorescent filter set, OL = objective lens.</p

Changes of protein localization upon starvation-induced stress.

<p>(A) Representative images of 3 starved animals grown at 25°C at day 1 and 3 in a group. Decrease of fluorescence for both reporters p_<i>ife-2</i>IFE-2::GFP and p_{<i>dcap-1</i>}DCAP-1::dsRED from day 1 to day 3 are visible, while the signal persists in some tissues, including pharynx, canal cells, muscles and the developing embryos (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s009" target="_blank">S5 Video</a>). Size bars correspond to 100μm. (B) IFE-2::GFP and (C) DCAP-1::dsRED fluorescent intensity quantification of the 3 animals in (A) individually and in the group.</p

Protein dynamics in a longitudinal ageing study in <i>C</i>. <i>elegans</i>.

<p>(A) Representative images of 3 single animals grown at 25°C at day 1, 3 and 5. Animals co-express p_<i>ife-2</i>IFE-2::GFP and p_{<i>dcap-1</i>}DCAP-1::dsRED (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s008" target="_blank">S4 Video</a>). Individuals show differences in protein localization during ageing. Size bars correspond to 100μm. (B) IFE-2::GFP and (C) DCAP-1::dsRED fluorescent intensity quantification of the 3 animals in (A).</p

A Parallel Radiosity System for Large Data Sets

this paper we will explore this definition and define a practical working system. Most radiosity methods use a discretisation approach, in which the environment is divided into a finite set of patches. This approach was initially used in thermal engineering and applied to diffuse reflection by Goral et al [6]. The radiance function of each surface is approximated by the set of patches attributed to that surface. More recent methods have used polynomials [15] and wavelet models [7] to represent the radiance functions over surfaces. The CARM system is patch-based, with each patch holding a mesh of sample points. Although discretised systems have a number of shortcomings (such as aliasing) they can accurately represent very abrupt changes in the radiance function. The input geometry to the system is triangulated; this allows all object primitives and also all complex objects to be represented by meshes. The input triangles are then automatically tested for D0 discontinuities (i.e. tests for intersecting or abutting triangles) and also for excessive size, and automatically subdivided if required. The triangles left after such subdivision correspond to a traditional hand-crafted radiosity patches. Radiance values (or flux values) are stored at sample points, which are located at patch vertices, and also within the patch. These sample points are stored in a mesh, which can be triangulated and then interpolated to reconstruct the radiance function. By adaptive subdivision of the mesh the system allows sample points to be added as the solution progresses, When new sample points are added the mesh is re-triangulated; these triangles are analogous to traditional elements. Subdivision is controlled by examining the gradient and difference between neighbouring sample points; if e..

FRAP imaging by low-photobleaching light sheet microscopy.

<p>(A) Workflow for FRAP imaging by light sheet microscopy. After monitoring, the animals can be recovered to assess possible damage induced through the procedure. (B) Representative images of recovery at several time points after photobleaching IFE-2::GFP fluorescence in the anterior part of the animal (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s010" target="_blank">S6 Video</a>). The red arrow indicates a developing embryo within the parental gonad. Size bars correspond to 100μm. (C) Imaging of the anterior region after photobleaching and recovery time points of DCAP-1::dsRED fluorescence. The signal also recovers to the subcellular structures of P bodies (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#pone.0127869.s011" target="_blank">S7 Video</a>). Size bars correspond to 100μm. (D) IFE-2::GFP and (E) DCAP-1::dsRED quantification of recovering fluorescent intensity of the animals in (B) and (C), respectively. The respective equations describing best-fit lines as well as r² values for each graph are shown. The line slopes correspond to the first derivative of fluorescent change within a time unit (df/dt) and determine the recovery rate.</p

Workflow for light sheet 3D microscopy to measure protein dynamics in <i>C</i>. <i>elegans</i>.

<p>Animals are maintained following standard procedures, collected and immobilized on agar pads, which are immersed in an oil bath. The laser beam for sample illumination passes through a cylindrical lens and forms a light sheet that is directed on the specimen. The recording lens is focused on the illuminated sheet and records stacks of the specimen, which is moved along the x-axis. Recorded data sets consist of image stacks and are combined into a 3D visualization via freeware, such as ImageJ. Anatomic landmarks (b_i1, b_i2, b_i3) are used to map and transform images via registration algorithms so that they can be aligned to a reference image A (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0127869#sec002" target="_blank">Materials and Methods</a>).</p

Visualization 2: 3D imaging in CUBIC-cleared mouse heart tissue: going deeper

Video 2. 10X cleared tissue transgenic mouse heart Originally published in Biomedical Optics Express on 01 September 2016 (boe-7-9-3716