Characterization of the genetic control of fruit flesh color in peach

The analysis of a carotenoid cleavage dioxygenase gene in a pool of peach cultivars revealed the existence of a functional allele (W1), associated with the white flesh trait, and three independent mutations associated with the yellow phenotype: a 2 bp insertion within a repetitive sequence (y1), a large transposable element within the intron (y2) and a single base substitution generating a premature stop codon (y3). Based on these evidences, the yellow flesh phenotype seems to have arisen from at least three independent mutational events.

New design of polyphenylene dendrimers for full-color light-emitting diodes

Dendritic systems, and in particular polyphenylene dendrimers, have recently attracted considerable attention from the synthetic organic chemistry community, as well as from photophysicists, particularly in view of the search for synthetic model analogies to photoelectric materials to fabricate organic light-emitting diodes (OLEDs), and even more advanced areas of research such as light-harvesting system, energy transfer and non-host device. Geometrically, dendrimers are unique systems that consist of a core, one or more dendrons, and surface groups. The different parts of the macromolecule can be selected to give the desired optoelectronic and processing properties. Compared to small molecular or polymeric light-emitting materials, these dendritic materials can combine the benefits of both previous classes. The high molecular weights of these dendritic macromolecules, as well as the surface groups often attached to the distal ends of the dendrons, can improve the solution processability, and thus can be deposited from solution by simple processes such as spin-coating and ink-jet printing. Moreover, even better than the traditional polymeric light-emitting materials, the well-defined monodisperse distributed dendrimers possess a high purity comparable to that of small molecules, and as such can be fabricated into high performance OLEDs. Most importantly, the emissive chromophores can be located at the core of the dendrimer, within the dendrons, and/or at the surface of the dendrimers because of their unique dendritic architectures. The different parts of the macromolecule can be selected to give the desired optoelectronic and processing properties. Therefore, the main goals of this thesis are the design and synthesis, characterization of novel functional dendrimers, e.g. polytriphenylene dendrimers for blue fluorescent, as well as iridium(III) complex cored polyphenylene dendrimers for green and red phosphorescent light emitting diodes. In additional to the above mentioned advantages of dendrimer based OLEDs, the modular molecular architecture and various functionalized units at different locations in polyphenylene dendrimers open up a tremendous scope for tuning a wide range of properties in addition to color, such as intermolecular interactions, charge mobility, quantum yield, and exciton diffusion. In conclusion, research into dendrimer containing OLEDs combines fundamental aspects of organic semiconductor physics, novel and highly sophisticated organic synthetic chemistry and elaborate device technology.rn

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Frequency-dependent social dominance in a color polymorphic cichlid fish

A mechanism commonly suggested to explain the persistence of color polymorphisms in animals is negative frequency-dependent selection. It could result from a social dominance advantage to rare morphs. We tested for this in males of red and blue color morphs of the Lake Victoria cichlid, Pundamilia. Earlier work has shown that males preferentially attack the males of their own morph, while red males are more likely to win dyadic contests with blue males. In order to study the potential contribution of both factors to the morph co-existence, we manipulated the proportion of red and blue males in experimental assemblages and studied its effect on social dominance. We then tried to disentangle the effects of the own-morph attack bias and social dominance of red using simulations. In the experiment, we found that red males were indeed socially dominant to the blue ones, but only when rare. However, blue males were not socially dominant when rare. The simulation results suggest that an own-morph attack bias reduces the social dominance of red males when they are more abundant. Thus, there is no evidence of symmetric negative frequency-dependent selection acting on social dominance, suggesting that additional fitness costs to the red morph must explain their co-existence.

America's Shifting Color Line? Reexamining Determinants of Latino Racial Self-Identification

Objectives. Latinos are the nation's largest minority group and will double in size by 2050. Their size coupled with the fact that Latinos do not constitute a separate race raises questions about Latinos' incorporation into the U. S. racial hierarchy. This article explores patterns of Latino racial identity formation, examining the determinants of racial identity. Methods. Using the 2006 Latino National Survey, I estimate multinomial logit and ordered probit models of identification choices. Results. Latino racial identity is strongly associated with several factors, including socioeconomic status, measures of perceived discrimination and commonality, and measures of acculturation/assimilation. Most Latinos have a broader, more complex understanding of race. Furthermore, some Latinos do believe that they occupy a unique position in the racial hierarchy. Conclusions. The results suggest that the color line W. E. DuBois argued has long divided our nation may eventually shift.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.