Three-dimensional motion analysis of facial movement during verbal and nonverbal expressions in healthy subjects

Functional impairments of facial expressions alter the quality of life and their quantitative analysis is key to describing and grading facial function and dysfunction. The aim of this investigation was to quantify 3D lip movements in a group of healthy young subjects. Lip movements during five repetitions of common and random sequences of vowels and nonverbal expressions were recorded using an optoelectronic 3D motion analyzer. The mean maximum displacement of facial landmarks was used to compute 3D unilateral mobility and the symmetry indices (SI) separately for each sex. Facial mobility was significantly greater during open-mouth than closed-mouth smiles. Facial movement among the subjects was largest during articulation of the vowel /a/and smallest for /i/. Lips were pursed with a SI very close to 95%, while smiles were slightly more asymmetric. The vowel /a/was articulated with significantly greater symmetry than /e/, /i/and /u/. The outcomes suggest that the proposed method characterized normal facial animations satisfactorily, so it could be a useful tool for assessing patients with facial lesions and dentofacial deformities. Patient assessment would profit from this quantitative approach, which would reduce discrepancies among several clinical examinations

Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In this model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15 figures. This is an updated version of the preprint available at http://precedings.nature.com/documents/6956/version/

Feasibility study of imaging spectroscopy to monitor the quality of online welding

An online welding quality system based on the use of imaging spectroscopy is proposed and discussed. Plasma optical spectroscopy has already been successfully applied in this context by establishing a direct correlation between some spectroscopic parameters, e.g., the plasma electronic temperature and the resulting seam quality. Given that the use of the so-called hyperspectral devices provides both spatial and spectral information, we propose their use for the particular case of arc welding quality monitoring in an attempt to determine whether this technique would be suitable for this industrial situation. Experimental welding tests are presented, and the ability of the proposed solution to identify simulated defects is proved. Detailed spatial analyses suggest that this additional dimension can be used to improve the performance of the entire system

Ancient Migratory Events in the Middle East: New Clues from the Y-Chromosome Variation of Modern Iranians

Knowledge of high resolution Y-chromosome haplogroup diversification within Iran provides important geographic context regarding the spread and compartmentalization of male lineages in the Middle East and southwestern Asia. At present, the Iranian population is characterized by an extraordinary mix of different ethnic groups speaking a variety of Indo-Iranian, Semitic and Turkic languages. Despite these features, only few studies have investigated the multiethnic components of the Iranian gene pool. In this survey 938 Iranian male DNAs belonging to 15 ethnic groups from 14 Iranian provinces were analyzed for 84 Y-chromosome biallelic markers and 10 STRs. The results show an autochthonous but non-homogeneous ancient background mainly composed by J2a sub-clades with different external contributions. The phylogeography of the main haplogroups allowed identifying post-glacial and Neolithic expansions toward western Eurasia but also recent movements towards the Iranian region from western Eurasia (R1b-L23), Central Asia (Q-M25), Asia Minor (J2a-M92) and southern Mesopotamia (J1-Page08). In spite of the presence of important geographic barriers (Zagros and Alborz mountain ranges, and the Dasht-e Kavir and Dash-e Lut deserts) which may have limited gene flow, AMOVA analysis revealed that language, in addition to geography, has played an important role in shaping the nowadays Iranian gene pool. Overall, this study provides a portrait of the Y-chromosomal variation in Iran, useful for depicting a more comprehensive history of the peoples of this area as well as for reconstructing ancient migration routes. In addition, our results evidence the important role of the Iranian plateau as source and recipient of gene flow between culturally and genetically distinct population

An up-date on the prevalence of sickle cell trait in Eastern and Western Uganda

<p>Abstract</p> <p>Background</p> <p>The first survey on sickle cell disease (SCD) done in Uganda in 1949, reported the district of Bundibugyo in Western Uganda to have the highest sickle cell trait (SCT) prevalence (45%). This is believed to be the highest in the whole world. According to the same survey, the prevalence of SCT in the districts of Mbale and Sironko in the East was 20-28%, whilst the districts of Mbarara and Ntungamo in the West had 1-5%. No follow-up surveys have been conducted over the past 60 years. SCA accounts for approximately 16.2% of all pediatric deaths in Uganda. The pattern of SCT inheritance, however, predicts likely changes in the prevalence and distribution of the SCT. The objective of the study therefore was to establish the current prevalence of the SCT in Uganda.</p> <p>Methods</p> <p>This study was a cross sectional survey which was carried out in the districts of Mbale and Sironko in the Eastern, Mbarara/Ntungamo and Bundibugyo in Western Uganda. The participants were children (6 months-5 yrs). Blood was collected from each subject and analyzed for hemoglobin S using cellulose acetate Hb electrophoresis.</p> <p>Results</p> <p>The established prevalence of the SCT (As) in Eastern Uganda was 17.5% compared to 13.4% and 3% in Bundibugyo and Mbarara/Ntungamo respectively. 1.7% of the children in Eastern Uganda tested positive for haemoglobin ss relative to 3% in Bundibugyo, giving gene frequencies of 0.105 and 0.097 for the recessive gene respectively. No ss was detected in Mbarara/Ntungamo.</p> <p>Conclusions</p> <p>A shift in the prevalence of the SCT and ss in Uganda is notable and may be explained by several biological and social factors. This study offers some evidence for the possible outcome of intermarriages in reducing the incidence of the SCT.</p

A Genealogical Interpretation of Principal Components Analysis

Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to inform about historical demographic processes, little is known about the relationship between fundamental demographic parameters and the projection of samples onto the primary axes. Here I show that for SNP data the projection of samples onto the principal components can be obtained directly from considering the average coalescent times between pairs of haploid genomes. The result provides a framework for interpreting PCA projections in terms of underlying processes, including migration, geographical isolation, and admixture. I also demonstrate a link between PCA and Wright's fst and show that SNP ascertainment has a largely simple and predictable effect on the projection of samples. Using examples from human genetics, I discuss the application of these results to empirical data and the implications for inference

Mitochondrial DNA signals of late glacial recolonization of Europe from near Eastern refugia

Human populations, along with those of many other species, are thought to have contracted into a number of refuge areas at the height of the last Ice Age. European populations are believed to be, to a large extent, the descendants of the inhabitants of these refugia, and some extant mtDNA lineages can be traced to refugia in Franco-Cantabria (haplogroups H1, H3, V, and U5b1), the Italian Peninsula (U5b3), and the East European Plain (U4 and U5a). Parts of the Near East, such as the Levant, were also continuously inhabited throughout the Last Glacial Maximum, but unlike western and eastern Europe, no archaeological or genetic evidence for Late Glacial expansions into Europe from the Near East has hitherto been discovered. Here we report, on the basis of an enlarged whole-genome mitochondrial database, that a substantial, perhaps predominant, signal from mitochondrial haplogroups J and T, previously thought to have spread primarily from the Near East into Europe with the Neolithic population, may in fact reflect dispersals during the Late Glacial period, ?19–12 thousand years (ka) ago.<br/

Analysis of East Asia Genetic Substructure Using Genome-Wide SNP Arrays

Accounting for population genetic substructure is important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to different continental populations the understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's <0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. PCA showed substructure both between different East Asian groups and within the Han Chinese population. These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies

Sensitive Detection of Chromosomal Segments of Distinct Ancestry in Admixed Populations

Identifying the ancestry of chromosomal segments of distinct ancestry has a wide range of applications from disease mapping to learning about history. Most methods require the use of unlinked markers; but, using all markers from genome-wide scanning arrays, it should in principle be possible to infer the ancestry of even very small segments with exquisite accuracy. We describe a method, HAPMIX, which employs an explicit population genetic model to perform such local ancestry inference based on fine-scale variation data. We show that HAPMIX outperforms other methods, and we explore its utility for inferring ancestry, learning about ancestral populations, and inferring dates of admixture. We validate the method empirically by applying it to populations that have experienced recent and ancient admixture: 935 African Americans from the United States and 29 Mozabites from North Africa. HAPMIX will be of particular utility for mapping disease genes in recently admixed populations, as its accurate estimates of local ancestry permit admixture and case-control association signals to be combined, enabling more powerful tests of association than with either signal alone

The Impact of Divergence Time on the Nature of Population Structure: An Example from Iceland

The Icelandic population has been sampled in many disease association studies, providing a strong motivation to understand the structure of this population and its ramifications for disease gene mapping. Previous work using 40 microsatellites showed that the Icelandic population is relatively homogeneous, but exhibits subtle population structure that can bias disease association statistics. Here, we show that regional geographic ancestries of individuals from Iceland can be distinguished using 292,289 autosomal single-nucleotide polymorphisms (SNPs). We further show that subpopulation differences are due to genetic drift since the settlement of Iceland 1100 years ago, and not to varying contributions from different ancestral populations. A consequence of the recent origin of Icelandic population structure is that allele frequency differences follow a null distribution devoid of outliers, so that the risk of false positive associations due to stratification is minimal. Our results highlight an important distinction between population differences attributable to recent drift and those arising from more ancient divergence, which has implications both for association studies and for efforts to detect natural selection using population differentiation