Magnetic Resonance Imaging of the Newborn Brain: Automatic Segmentation of Brain Images into 50 Anatomical Regions

We studied methods for the automatic segmentation of neonatal and developing brain images into 50 anatomical regions, utilizing a new set of manually segmented magnetic resonance (MR) images from 5 term-born and 15 preterm infants imaged at term corrected age called ALBERTs. Two methods were compared: individual registrations with label propagation and fusion; and template based registration with propagation of a maximum probability neonatal ALBERT (MPNA). In both cases we evaluated the performance of different neonatal atlases and MPNA, and the approaches were compared with the manual segmentations by means of the Dice overlap coefficient. Dice values, averaged across regions, were 0.81±0.02 using label propagation and fusion for the preterm population, and 0.81±0.02 using the single registration of a MPNA for the term population. Segmentations of 36 further unsegmented target images of developing brains yielded visibly high-quality results. This registration approach allows the rapid construction of automatically labeled age-specific brain atlases for neonates and the developing brain.     

Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span

Background  

The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of molecular sequence and profiling data. Here, the potential of such modeling is demonstrated by examining the 5,225 free-text items in the Caenorhabditis Genetic Center (CGC) Bibliography using techniques from statistical information retrieval. Items in the CGC biomedical text corpus were modeled using the Latent Dirichlet Allocation (LDA) model. LDA is a hierarchical Bayesian model which represents a document as a random mixture over latent topics; each topic is characterized by a distribution over words.     

Estimating the rate of evolution of the rate of molecular evolution

A simple model for the evolution of the rate of molecular evolution is presented. With a Bayesian approach, this model can serve as the basis for estimating dates of important evolutionary events even in the absence of the assumption of constant rates among evolutionary lineages. The method can be used in conjunction with any of the widely used models for nucleotide substitution or amino acid replacement. It is illustrated by analyzing a data set of rbcL protein sequences.      

Evaluation of a candidate International Standard for Meningococcal Group C polysaccharide

Meningococcal group C (MenC) plain polysaccharide (PS) and conjugate vaccines are primarily evaluated by physicochemical methods to ensure that batches are consistently manufactured. As different assays are employed to quantify the MenC PS content of final formulations and bulk intermediaries, there is a need for an International MenC PS Standard to calibrate internal references used in the different laboratories. Twelve laboratories from nine different countries participated in a collaborative study to determine the MenC PS content of a candidate International Standard MenC PS preparation (08/214) and to assess its suitability. On the basis of the results from this study the candidate standard 08/214 was established as an International Standard for the quantification of MenC PS content in vaccines and components. It has a content of 1.192 ± 0.192 mg MenC PS/ampoule (expanded uncertainty with coverage factor of k = 2.365 corresponding to a 95% level of confidence), as determined by the resorcinol assays carried out by eight of the participating laboratories. The standard is available from The National Institute of Biological Standards and Control who act as guardians and distributors of the material under the auspices of WHO.     

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

Background  

Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells.     

Seeing without being seen: a removal experiment with mixed flocks of Willow and Crested Tits Parus montanus and cristatus

This paper tests the hypothesis that foraging site selection reflects a trade-off between the various needs for concealment from predators, to find food, and for the individual to maintain some view of its surroundings. After removal of Crested Tits Parus cristatus (the dominant species in mixed flocks), Willow Tits P. montanus did not decrease their foraging heights as expected but remained in the most exposed parts of young pines. In contrast, after removal of Willow Tits, Crested Tits increased their foraging height from the sheltered lower canopy to sites previously occupied by Willow Tits. When flock size was reduced, the birds maintained the same high levels of vigilance without concealing themselves in dense vegetation. I suggest that flock members may benefit from foraging in sites that afford good anti-predator vigilance.     

Influence of Boar and Semen Parameters on Motility and Acrosome Integrity in Liquid Boar Semen Stored for Five Days

Ninety ejaculates from a total of 76 AI boars were extended in Beltsville Thawing Solution (BTS). Boar identity, breed, weight of the ejaculate and sperm concentration were registered. Motility and acrosome integrity were assessed after storage at 16–18°C for 6, 30, 54, 78, and 102 h. Storage time had a significant influence on both motility (p < 0.01) and acrosome integrity (p < 0.001). The Least Square Means for percentage of motility showed a small decline from 79.8% after 6 h of storage to 78.4% at 102 h. Motility at 78 and 102 h was significantly different from motility at 6 h (p < 0.05). The percentage of sperm cells with normal acrosomes declined throughout the experiment. The Least Square Means for 6, 30, 54, 78, and 102 h of storage were 93.9%, 90.6%, 88.0%, 84.8%, and 78.2%, respectively. The decrease in acrosome integrity from one storage time to the next was highly significant throughout the trial (p < 0.001). There was a significant influence of boar (p < 0.001) and sperm concentration (p < 0.01) on motility, while acrosome integrity was affected only by boar (p < 0.001). Breed of the boars and weight of the ejaculate did not influence the dependent variables.     

Classification and lateralization of temporal lobe epilepsies with and without hippocampal atrophy based on whole-brain automatic MRI segmentation

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study.