Deletion of complement factor H-related genes CFHR1 and CFHR3 is associated with atypical hemolytic uremic syndrome.

Atypical hemolytic uremic syndrome (aHUS) is associated with defective complement regulation. Disease-associated mutations have been described in the genes encoding the complement regulators complement factor H, membrane cofactor protein, factor B, and factor I. In this study, we show in two independent cohorts of aHUS patients that deletion of two closely related genes, complement factor H-related 1 (CFHR1) and complement factor H-related 3 (CFHR3), increases the risk of aHUS. Amplification analysis and sequencing of genomic DNA of three affected individuals revealed a chromosomal deletion of approximately 84 kb in the RCA gene cluster, resulting in loss of the genes coding for CFHR1 and CFHR3, but leaving the genomic structure of factor H intact. The CFHR1 and CFHR3 genes are flanked by long homologous repeats with long interspersed nuclear elements (retrotransposons) and we suggest that nonallelic homologous recombination between these repeats results in the loss of the two genes. Impaired protection of erythrocytes from complement activation is observed in the serum of aHUS patients deficient in CFHR1 and CFHR3, thus suggesting a regulatory role for CFHR1 and CFHR3 in complement activation. The identification of CFHR1/CFHR3 deficiency in aHUS patients may lead to the design of new diagnostic approaches, such as enhanced testing for these genes.

Acoustic features of song categories and their possible implications for communication in the common nightingale (Luscinia megarhynchos)

In many passerine species, males sing more than one distinct song type. Commonly, songs are assigned to different song types or song categories based on phonological and syntactical dissimilarities. However, temporal aspects, such as song length and song rate, also need to be considered to understand the possible functions of different songs. Common nightingales (Luscinia megarhynchos) have large vocal repertoires of different song types but their songs additionally can be grouped into two distinct categories (particular groups of song types): whistle songs and nonwhistle songs. Whistle songs are hypothesised to be important to attract migrating females. We studied temporal properties of whistle songs and nonwhistle songs and examined the relationship between those song parameters and song output parameters, such as song rate and song length. To investigate how song parameters vary among males, we calculated the coefficients of variation for different song traits. We found that the variation in the proportion of whistle songs was significantly higher among males than variation in other song parameters. Furthermore, the proportion of whistle songs was negatively correlated with other sona output patterns. These findings suggest that the production of whistle songs might be constrained and/or that whistle songs and their succeeding pauses may act as a functional unit in communication.

Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos

We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.

Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Demographics and landscape features determine intrariver population structure in Atlantic salmon (Salmo salar L.): the case of the River Moy in Ireland

Contemporary genetic structure of Atlantic salmon (Salmo salar L.) in the River Moy in Ireland is shown here to be strongly related to landscape features and population demographics, with populations being defined largely by their degree of physical isolation and their size. Samples of juvenile salmon were collected from the 17 major spawning areas on the river Moy and from one spawning area in each of five smaller nearby rivers. No temporal allele frequency differences were observed within locations for 12 microsatellite loci, whereas nearly all spatial samples differed significantly, suggesting that each was a separate population. Bayesian clustering and landscape genetic analyses suggest that these populations can be combined hierarchically into five genetically informative larger groupings. Lakes were found to be the single most important determinant of the observed population structure. Spawning area size was also an important factor. The salmon population of the closest nearby river resembled genetically the largest Moy population grouping. In addition, we showed that anthropogenic influences on spawning habitats, in this case arterial drainage, can affect relationships between populations. Our results show that Atlantic salmon biodiversity can be largely defined by geography, and thus, knowledge of landscape features (for example, as characterized within Geographical Information Systems) has the potential to predict population structure in other rivers without an intensive genetic survey, or at least to help direct sampling. This approach of combining genetics and geography, for sampling and in subsequent statistical analyses, has wider application to the investigation of population structure in other freshwater/anadromous fish species and possibly in marine fish and other organisms.