Surgical anatomy of the nail apparatus

Nail surgery is an integral part of dermatologic surgery. An in-depth knowledge of the anatomy, biology, physiology, and gross pathology of the entire nail unit is essential. In particular, knowledge of nail histopathology is necessary to perform diagnostic nail biopsies and other nail procedures correctly.

Non-photorealistic rendering of virtual implant models for computer-assisted fluoroscopy-based surgical procedures

Surgical navigation systems visualize the positions and orientations of surgical instruments and implants as graphical overlays onto a medical image of the operated anatomy on a computer monitor. The orthopaedic surgical navigation systems could be categorized according to the image modalities that are used for the visualization of surgical action. In the so-called CT-based systems or 'surgeon-defined anatomy' based systems, where a 3D volume or surface representation of the operated anatomy could be constructed from the preoperatively acquired tomographic data or through intraoperatively digitized anatomy landmarks, a photorealistic rendering of the surgical action has been identified to greatly improve usability of these navigation systems. However, this may not hold true when the virtual representation of surgical instruments and implants is superimposed onto 2D projection images in a fluoroscopy-based navigation system due to the so-called image occlusion problem. Image occlusion occurs when the field of view of the fluoroscopic image is occupied by the virtual representation of surgical implants or instruments. In these situations, the surgeon may miss part of the image details, even if transparency and/or wire-frame rendering is used. In this paper, we propose to use non-photorealistic rendering to overcome this difficulty. Laboratory testing results on foamed plastic bones during various computer-assisted fluoroscopybased surgical procedures including total hip arthroplasty and long bone fracture reduction and osteosynthesis are shown.

Chemokine receptor 4 (CXCR4) is part of the lipopolysaccharide "sensing apparatus"

Recognition of bacterial lipopolysaccharide (LPS) by the innate immune system involves at least three receptor molecules: CD14, TLR4 and MD-2. Additional receptor components such as heat shock proteins, chemokine receptor 4 (CXCR4), or CD55 have been suggested to be part of this activation cluster; possibly acting as additional LPS transfer molecules. Our group has previously identified CXCR4 as a component of the "LPS-sensing apparatus". In this study we aimed to elucidate the role that CXCR4 plays in innate immune responses to LPS. Here we demonstrate that CXCR4 transfection results in responsiveness to LPS. Fluorescence correlation spectroscopy experiments further showed that LPS directly interacts with CXCR4. Our data suggest that CXCR4 is not only involved in LPS binding but is also responsible for triggering signalling, especially mitogen-activated protein kinases in response to LPS. Finally, co-clustering of CXCR4 with other LPS receptors seems to be crucial for LPS signalling, thus suggesting that CXCR4 is a functional part of the multimeric LPS "sensing apparatus".

BPAG1a and b Associate with EB1 and EB3 and Modulate Vesicular Transport, Golgi Apparatus Structure, and Cell Migration in C2.7 Myoblasts.

BPAG1a and BPAG1b (BPAG1a/b) constitute two major isoforms encoded by the dystonin (Dst) gene and show homology with MACF1a and MACF1b. These proteins are members of the plakin family, giant multi-modular proteins able to connect the intermediate filament, microtubule and microfilament cytoskeletal networks with each other and to distinct cell membrane sites. They also serve as scaffolds for signaling proteins that modulate cytoskeletal dynamics. To gain better insights into the functions of BPAG1a/b, we further characterized their C-terminal region important for their interaction with microtubules and assessed the role of these isoforms in the cytoskeletal organization of C2.7 myoblast cells. Our results show that alternative splicing does not only occur at the 5' end of Dst and Macf1 pre-mRNAs, as previously reported, but also at their 3' end, resulting in expression of additional four mRNA variants of BPAG1 and MACF1. These isoform-specific C-tails were able to bundle microtubules and bound to both EB1 and EB3, two microtubule plus end proteins. In the C2.7 cell line, knockdown of BPAG1a/b had no major effect on the organization of the microtubule and microfilament networks, but negatively affected endocytosis and maintenance of the Golgi apparatus structure, which became dispersed. Finally, knockdown of BPAG1a/b caused a specific decrease in the directness of cell migration, but did not impair initial cell adhesion. These data provide novel insights into the complexity of alternative splicing of Dst pre-mRNAs and into the role of BPAG1a/b in vesicular transport, Golgi apparatus structure as well as in migration in C2.7 myoblasts.

Scintillation crystal including a rare earth halide, and a radiation detection apparatus including the scintillation crystal.

A scintillation crystal can include Ln(1-y)REyX3, wherein Ln represents a rare earth element, RE represents a different rare earth element, y has a value at 0-1, and X represents a halogen. In an embodiment, the scintillation crystal is doped with a Group 1 element, a Group 2 element, or a mixt. thereof, and the scintillation crystal is formed from a melt having a concn. of such elements or mixt. thereof of at least ∼0.02%. In another embodiment, the scintillation crystal can have unexpectedly improved proportionality and unexpectedly improved energy resoln. properties. In a further embodiment, a radiation detection app. can include the scintillation crystal, a photosensor, and an electronics device. Such a radiation detection app. can be useful in a variety of applications.

Image Space Adaptive Rendering

In this thesis, we develop an adaptive framework for Monte Carlo rendering, and more specifically for Monte Carlo Path Tracing (MCPT) and its derivatives. MCPT is attractive because it can handle a wide variety of light transport effects, such as depth of field, motion blur, indirect illumination, participating media, and others, in an elegant and unified framework. However, MCPT is a sampling-based approach, and is only guaranteed to converge in the limit, as the sampling rate grows to infinity. At finite sampling rates, MCPT renderings are often plagued by noise artifacts that can be visually distracting. The adaptive framework developed in this thesis leverages two core strategies to address noise artifacts in renderings: adaptive sampling and adaptive reconstruction. Adaptive sampling consists in increasing the sampling rate on a per pixel basis, to ensure that each pixel value is below a predefined error threshold. Adaptive reconstruction leverages the available samples on a per pixel basis, in an attempt to have an optimal trade-off between minimizing the residual noise artifacts and preserving the edges in the image. In our framework, we greedily minimize the relative Mean Squared Error (rMSE) of the rendering by iterating over sampling and reconstruction steps. Given an initial set of samples, the reconstruction step aims at producing the rendering with the lowest rMSE on a per pixel basis, and the next sampling step then further reduces the rMSE by distributing additional samples according to the magnitude of the residual rMSE of the reconstruction. This iterative approach tightly couples the adaptive sampling and adaptive reconstruction strategies, by ensuring that we only sample densely regions of the image where adaptive reconstruction cannot properly resolve the noise. In a first implementation of our framework, we demonstrate the usefulness of our greedy error minimization using a simple reconstruction scheme leveraging a filterbank of isotropic Gaussian filters. In a second implementation, we integrate a powerful edge aware filter that can adapt to the anisotropy of the image. Finally, in a third implementation, we leverage auxiliary feature buffers that encode scene information (such as surface normals, position, or texture), to improve the robustness of the reconstruction in the presence of strong noise.

Growth at moderately elevated temperature alters the physiological response of the photosynthetic apparatus to heat stress in pea (Pisum sativum L.) leaves

The impact of heat stress on the functioning of the photosynthetic apparatus was examined in pea (Pisum sativum L.) plants grown at control (25 °C; 25 °C-plants) or moderately elevated temperature (35 °C; 35 °C-plants). In both types of plants net photosynthesis (Pn) decreased with increasing leaf temperature (LT) and was more than 80% reduced at 45 °C as compared to 25 °C. In the 25 °C-plants, LTs higher than 40 °C could result in a complete suppression of Pn. Short-term acclimation to heat stress did not alter the temperature response of Pn. Chlorophyll a fluorescence measurements revealed that photosynthetic electron transport (PET) started to decrease when LT increased above 35 °C and that growth at 35 °C improved the thermal stability of the thylakoid membranes. In the 25 °C-plants, but not in the 35 °C-plants, the maximum quantum yield of the photosystem II primary photochemistry, as judged by measuring the Fv/Fm ratio, decreased significantly at LTs higher than 38 °C. A post-illumination heat-induced reduction of the plastoquinone pool was observed in the 25 °C-plants, but not in the 35 °C-plants. Inhibition of Pn by heat stress correlated with a reduction of the activation state of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). Western-blot analysis of Rubisco activase showed that heat stress resulted in a redistribution of activase polypeptides from the soluble to the insoluble fraction of extracts. Heat-dependent inhibition of Pn and PET could be reduced by increasing the intercellular CO2 concentration, but much more effectively so in the 35 °C-plants than in the 25 °C-plants. The 35 °C-plants recovered more efficiently from heat-dependent inhibition of Pn than the 25 °C-plants. The results show that growth at moderately high temperature hardly diminished inhibition of Pn by heat stress that originated from a reversible heat-dependent reduction of the Rubisco activation state. However, by improving the thermal stability of the thylakoid membranes it allowed the photosynthetic apparatus to preserve its functional potential at high LTs, thus minimizing the after-effects of heat stress.

Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

Regularizing Image Reconstruction for Gradient-Domain Rendering with Feature Patches

We present a novel algorithm to reconstruct high-quality images from sampled pixels and gradients in gradient-domain rendering. Our approach extends screened Poisson reconstruction by adding additional regularization constraints. Our key idea is to exploit local patches in feature images, which contain per-pixels normals, textures, position, etc., to formulate these constraints. We describe a GPU implementation of our approach that runs on the order of seconds on megapixel images. We demonstrate a significant improvement in image quality over screened Poisson reconstruction under the L1 norm. Because we adapt the regularization constraints to the noise level in the input, our algorithm is consistent and converges to the ground truth.