A non-coding genomic duplication at the HMX1 locus is associated with crop ears in highland cattle.

Highland cattle with congenital crop ears have notches of variable size on the tips of both ears. In some cases, cartilage deformation can be seen and occasionally the external ears are shortened. We collected 40 cases and 80 controls across Switzerland. Pedigree data analysis confirmed a monogenic autosomal dominant mode of inheritance with variable expressivity. All affected animals could be traced back to a single common ancestor. A genome-wide association study was performed and the causative mutation was mapped to a 4 Mb interval on bovine chromosome 6. The H6 family homeobox 1 (HMX1) gene was selected as a positional and functional candidate gene. By whole genome re-sequencing of an affected Highland cattle, we detected 6 non-synonymous coding sequence variants and two variants in an ultra-conserved element at the HMX1 locus with respect to the reference genome. Of these 8 variants, only a non-coding 76 bp genomic duplication (g.106720058_106720133dup) located in the conserved region was perfectly associated with crop ears. The identified copy number variation probably results in HMX1 misregulation and possible gain-of-function. Our findings confirm the role of HMX1 during the development of the external ear. As it is sometimes difficult to phenotypically diagnose Highland cattle with slight ear notches, genetic testing can now be used to improve selection against this undesired trait.

Genomic signatures of relaxed disruptive selection associated with speciation reversal in whitefish

Background: Speciation reversal: the erosion of species differentiation via an increase in introgressive hybridization due to the weakening of previously divergent selection regimes, is thought to be an important, yet poorly understood, driver of biodiversity loss. Our study system, the Alpine whitefish (Coregonus spp.) species complex is a classic example of a recent postglacial adaptive radiation: forming an array of endemic lake flocks, with the independent origination of similar ecotypes among flocks. However, many of the lakes of the Alpine radiation have been seriously impacted by anthropogenic nutrient enrichment, resulting in a collapse in neutral genetic and phenotypic differentiation within the most polluted lakes. Here we investigate the effects of eutrophication on the selective forces that have shaped this radiation, using population genomics. We studied eight sympatric species assemblages belonging to five independent parallel adaptive radiations, and one species pair in secondary contact. We used AFLP markers, and applied FST outlier (BAYESCAN, DFDIST) and logistic regression analyses (MATSAM), to identify candidate regions for disruptive selection in the genome and their associations with adaptive traits within each lake flock. The number of outlier and adaptive trait associated loci identified per lake were then regressed against two variables (historical phosphorus concentration and contemporary oxygen concentration) representing the strength of eutrophication. Results: Whilst we identify disruptive selection candidate regions in all lake flocks, we find similar trends, across analysis methods, towards fewer disruptive selection candidate regions and fewer adaptive trait/candidate loci associations in the more polluted lakes. Conclusions: Weakened disruptive selection and a concomitant breakdown in reproductive isolating mechanisms in more polluted lakes has lead to increased gene flow between coexisting Alpine whitefish species. We hypothesize that the resulting higher rates of interspecific recombination reduce either the number or extent of genomic islands of divergence surrounding loci evolving under disruptive natural selection. This produces the negative trend seen in the number of selection candidate loci recovered during genome scans of whitefish species flocks, with increasing levels of anthropogenic eutrophication: as the likelihood decreases that AFLP restriction sites will fall within regions of heightened genomic divergence and therefore be classified as FST outlier loci. This study explores for the first time the potential effects of human-mediated relaxation of disruptive selection on heterogeneous genomic divergence between coexisting species.

Selection criteria for selective dorsal rhizotomy in children with spastic cerebral palsy: a systematic review of the literature

AIM Information regarding the selection procedure for selective dorsal rhizotomy (SDR) in children with spastic cerebral palsy (CP) is scarce. Therefore, the aim of this study was to summarize the selection criteria for SDR in children with spastic CP. METHOD A systematic review was carried out using the following databases: MEDLINE, CINAHL, EMBASE, PEDro, and the Cochrane Library. Additional studies were identified in the reference lists. Search terms included 'selective dorsal rhizotomy', 'functional posterior rhizotomy', 'selective posterior rhizotomy', and 'cerebral palsy'. Studies were selected if they studied mainly children (<18y of age) with spastic CP, if they had an intervention of SDR, if they had a detailed description of the selection criteria, and if they were in English. The levels of evidence, conduct of studies, and selection criteria for SDR were scored. RESULTS Fifty-two studies were included. Selection criteria were reported in 16 International Classification of Functioning, Disability and Health model domains including 'body structure and function' (details concerning spasticity [94%], other movement abnormalities [62%], and strength [54%]), 'activity' (gross motor function [27%]), and 'personal and environmental factors' (age [44%], diagnosis [50%], motivation [31%], previous surgery [21%], and follow-up therapy [31%]). Most selection criteria were not based on standardized measurements. INTERPRETATION Selection criteria for SDR vary considerably. Future studies should describe clearly the selection procedure. International meetings of experts should develop more uniform consensus guidelines, which could form the basis for selecting candidates for SDR.

Dominance and the maintenance of polymorphism in multiallelic migration-selection models with two demes

The maintenance of genetic variation in a spatially heterogeneous environment has been one of the main research themes in theoretical population genetics. Despite considerable progress in understanding the consequences of spatially structured environments on genetic variation, many problems remain unsolved. One of them concerns the relationship between the number of demes, the degree of dominance, and the maximum number of alleles that can be maintained by selection in a subdivided population. In this work, we study the potential of maintaining genetic variation in a two-deme model with deme-independent degree of intermediate dominance, which includes absence of G x E interaction as a special case. We present a thorough numerical analysis of a two-deme three-allele model, which allows us to identify dominance and selection patterns that harbor the potential for stable triallelic equilibria. The information gained by this approach is then used to construct an example in which existence and asymptotic stability of a fully polymorphic equilibrium can be proved analytically. Noteworthy, in this example the parameter range in which three alleles can coexist is maximized for intermediate migration rates. Our results can be interpreted in a specialist-generalist context and (among others) show when two specialists can coexist with a generalist in two demes if the degree of dominance is deme independent and intermediate. The dominance relation between the generalist allele and the specialist alleles play a decisive role. We also discuss linear selection on a quantitative trait and show that G x E interaction is not necessary for the maintenance of more than two alleles in two demes.

WHEN DOES THE TROUBLE START? OBESITY, DIABETES RISKS AND METABOLIC DISTURBANCES IN YOUNG PEOPLE WITH PSYCHOSIS

People with psychotic disorders have higher mortality rates compared to the general population. Most deaths are due to cardiovascular (CV) disease, reflecting high rates of CV risk factors such as obesity and diabetes. Treatment with antipsychotic drugs is associated with weight gain in clinical trials. However, there is little information about how these drugs affect children and young people, and how early in the course of treatment the elevation in CV risk factors begins. This information is essential in understanding the costs and benefits of these treatments in young people, and establishing preventive and early intervention services to address physical health comorbidities. This symposium reports both prospective and naturalistic data from children and adolescents treated with antipsychotic drugs. These studies demonstrate that adverse effects on cardiometabolic measures, notably BMI and insulin resistance, become apparent very soon after treatment is initiated. Further, children and adolescents appear to be even more sensitive to these effects than adults. Population-wide studies are also informative. Danish data showing that young people exposed to antipsychotics have a higher risk of diabetes, compared with young people who had a psychiatric diagnosis but were not exposed to antipsychotic drugs, will be presented. In addition, an Australian comparison between a large, nationally representative sample of people with psychosis and a general population sample shows that higher rates of obesity and other cardiometabolic abnormalities are already evident in people with psychosis by the age of 25 years. Young people living with psychosis are already disadvantaged by the demands of living with mental illness, stigma, and social factors such as unemployment and low income. The addition of obesity, diabetes and other comorbidities adds a further burden. The data presented highlights the need for careful selection of antipsychotic drugs, regular monitoring of physical health and early intervention when weight gain, glucose dysregulation, or other cardiometabolic abnormalities are detected.

Total Tumor Volume and Alpha Fetoprotein for selection of transplant candidates with hepatocellular carcinoma: A prospective validation.

The selection of liver transplant candidates with hepatocellular carcinoma (HCC) is currently validated based on Milan criteria. The use of extended criteria has remained a matter of debate, mainly because of the absence of prospective validation. The present prospective study recruited patients according to the previously proposed Total Tumor Volume (TTV ≤115 cm(3) )/alpha fetoprotein (AFP ≤400 ng/ml) score. Patients with AFP >400 ng/ml were excluded, and as such the Milan group was modified to include only patients with AFP <400 ng/ml; these patients were compared to patients beyond Milan, but within TTV/AFP. From January 2007 to March 2013, 233 patients with HCC were listed for liver transplantation. Of them, 195 patients were within Milan, and 38 beyond Milan but within TTV/AFP. The average follow-up from listing was 33,9 ±24,9 months. The risk of drop-out was higher for patients beyond Milan but within TTV/AFP (16/38, 42,1%), than for patients within Milan (49/195, 25,1%, p=0,033). In parallel, intent-to-treat survival from listing was lower in the patients beyond Milan (53,8% vs. 71,6% at four years, p<0,001). After a median waiting time of 8 months, 166 patients were transplanted, 134 patients within Milan criteria, and 32 beyond Milan but within TTV/AFP. They demonstrated acceptable and similar recurrence rates (4,5% vs. 9,4%, p=0,138) and post-transplant survivals (78,7% vs. 74,6% at four years, p=0,932). CONCLUSION Based on the present prospective study, HCC liver transplant candidate selection could be expanded to the TTV (≤115 cm(3) )/AFP (≤400 ng/ml) criteria in centers with at least 8-month waiting time. An increased risk of drop-out on the waiting list can be expected but with equivalent and satisfactory post-transplant survival. This article is protected by copyright. All rights reserved.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.

Treatment intensification with insulin glargine in patients with inadequately controlled type 2 diabetes improves glycaemic control with a high treatment satisfaction and no weight gain

PRINCIPLES We aimed to evaluate the efficacy of, and treatment satisfaction with, insulin glargine administered with SoloSTAR® or ClikSTAR® pens in patients with type 2 diabetes mellitus managed by primary care physicians in Switzerland. METHODS A total of 327 patients with inadequately controlled type 2 diabetes were enrolled by 72 physicians in this prospective observational study, which aimed to evaluate the efficacy of a 6-month course of insulin glargine therapy measured as development of glycaemic control (glycosylated haemoglobin [HbA1c] and fasting plasma glucose [FPG]) and weight change. We also assessed preference for reusable or disposable pens, and treatment satisfaction. RESULTS After 6 months, the mean daily dose of insulin glargine was 27.7±14.3 U, and dose titration was completed in 228 (72.4%) patients. Mean HbA1c decreased from 8.9%±1.6% (n=327) to 7.3%±1.0% (n=315) (p<0.0001), and 138 (43.8%) patients achieved an HbA1c≤7.0%. Mean FPG decreased from 10.9±4.5 to 7.3±1.8 mmol/l (p<0.0001). Mean body weight did not change (85.4±17.2 kg vs 85.0±16.5 kg; p=0.11). Patients' preference was in favour of the disposable SoloStar® pen (80%), as compared with the reusable ClickStar® pen (20%). Overall, 92.6% of physicians and 96.3% of patients were satisfied or very satisfied with the insulin glargine therapy. CONCLUSIONS In patients with type 2 diabetes insulin glargine administered by SoloSTAR® or ClikSTAR® pens, education on insulin injection and on self-management of diabetes was associated with clinically meaningful improvements in HbA1c and FPG without a mean collective weight gain. The vast majority of both patients and primary care physicians were satisfied with the treatment intensification.

INCREASED EXPRESSION OF ONE OF TWO ADENOSINE DEAMINASE ALLELES IN A HUMAN CHORIOCARCINOMA CELL LINE FOLLOWING SELECTION WITH ADENINE NUCLEOSIDES

The human choriocarcinoma cell line JEG-3 is heterozygous at the adenosine deaminase (ADA) gene locus. Both allelic genes are under strong but incomplete repression causing a very low level expression of the gene locus. Because cytotoxic adenosine analogues such as 9-(beta)-D arabinofuranosyladenine (ara-A) and 9-(beta)-D xylofuranosyladenine (xyl-A) can be specifically detoxified by the action of ADA, these analogues were used to select for JEG-3 derived cells which had increased ADA expression. When JEG-3 cells were subjected to a multi-step, successively increasing dosage of either ara-A or xyl-A, resistant cells with increased ADA expression were generated. This increased ADA expression in the resistant cells was unstable, so that when the selective pressure was removed, cellular ADA expression would decrease. Subclone analysis of xyl-A resistant cells revealed that compared to parental JEG-3 cells, individual resistant cells had either elevated ADA levels or decreased adenosine kinase (ADK) levels or both. This altered ADA and ADK expression in the resistant cells were found to be independent events. Because of high endogenous tissue conversion factor (TCF) expression in the JEG-3 cells, the allelic nature of the increased ADA expression in most of the resistant cells could not be determined. However, several resistant subcloned cells were found to have lost TCF expression. These TCF('-) cells expressed only the ADA*2 allelic gene product. Cell fusion experiments demonstrated that the ADA*1 allelic gene was intact and functional in the A3-1A7 cell line. Chromosomal analysis of the A3-1A7 cells showed that they had no double-minutes or homogeneously staining chromosomal regions, although a pair of new chromosomes were found in these cells. Segregation analysis of the hybrid cells indicated that an ADA*2 allelic gene was probably located on this new chromosome. The analysis of the A3-1A7 cell line suggested that the expression of only ADA 2 in these cells was the result of possibly a cis-deregulation of the ADA gene locus or more probably an amplification of the ADA*2 allelic gene. Two effective positive selection systems for ADA('+) cells were also developed and tested. These selection systems should eventually lead to the isolation of the ADA gene.^

Detecting the signature of natural selection with microsatellites

Natural selection is one of the major factors in the evolution of all organisms. Detecting the signature of natural selection has been a central theme in evolutionary genetics. With the availability of microsatellite data, it is of interest to study how natural selection can be detected with microsatellites. ^ The overall aim of this research is to detect signatures of natural selection with data on genetic variation at microsatellite loci. The null hypothesis to be tested is the neutral mutation theory of molecular evolution, which states that different alleles at a locus have equivalent effects on fitness. Currently used tests of this hypothesis based on data on genetic polymorphism in natural populations presume that mutations at the loci follow the infinite allele/site models (IAM, ISM), in the sense that at each site at most only one mutation event is recorded, and each mutation leads to an allele not seen before in the population. Microsatellite loci, which are abundant in the genome, do not obey these mutation models, since the new alleles at such loci can be created either by contraction or expansion of tandem repeat sizes of core motifs. Since the current genome map is mainly composed of microsatellite loci and this class of loci is still most commonly studied in the context of human genome diversity, this research explores how the current test procedures for testing the neutral mutation hypothesis should be modified to take into account a generalized model of forward-backward stepwise mutations. In addition, recent literature also suggested that past demographic history of populations, presence of population substructure, and varying rates of mutations across loci all have confounding effects for detecting signatures of natural selection. ^ The effects of the stepwise mutation model and other confounding factors on detecting signature of natural selection are the main results of the research. ^

Selection of body fat distribution indices in adults and associations with plasma lipid metabolism variables

Body fat distribution is a cardiovascular health risk factor in adults. Body fat distribution can be measured through various methods including anthropometry. It is not clear which anthropometric index is suitable for epidemiologic studies of fat distribution and cardiovascular disease. The purpose of the present study was to select a measure of body fat distribution from among a series of indices (those traditionally used in the literature and others constructed from the analysis) that is most highly correlated with lipid-related variables and is independent of overall fatness. Subjects were Mexican-American men and women (N = 1004) from a study of gallbladder disease in Starr County, Texas. Multivariate associations were sought between lipid profile measures (lipids, lipoproteins, and apolipoproteins) and two sets of anthropometric variables (4 circumferences and 6 skinfolds). This was done to assess the association between lipid-related measures and the two sets of anthropometric variables and guide the construction of indices.^ Two indices emerged from the analysis that seemed to be highly correlated with lipid profile measures independent of obesity. These indices are: 2*arm circumference-thigh skinfold in pre- and post-menopausal women and arm/thigh circumference ratio in men. Next, using the sum of all skinfolds to represent obesity and the selected body fat distribution indices, the following hypotheses were tested: (1) state of obesity and centrally/upper distributed body fat are equally predictive of lipids, lipoproteins and apolipoproteins, and (2) the correlation among the lipid-related measures is not altered by obesity and body fat distribution.^ With respect to the first hypothesis, the present study found that most lipids, lipoproteins and apolipoproteins were significantly associated with both overall fatness and anatomical location of body fat in both sex and menopausal groups. However, within men and post-menopausal women, certain lipid profile measures (triglyceride and HDLT among post-menopausal women and apos C-II, CIII, and E among men) had substantially higher correlation with body fat distribution as compared with overall fatness.^ With respect to the second hypothesis, both obesity and body fat distribution were found to alter the association among plasma lipid variables in men and women. There was a suggestion from the data that the pattern of correlations among men and post-menopausal women are more comparable. Among men correlations involving apo A-I, HDLT, and HDL$\sb2$ seemed greatly influenced by obesity, and A-II by fat distribution; among post-menopausal women correlations involving apos A-I and A-II were highly affected by the location of body fat.^ Thus, these data point out that not only can obesity and fat distribution affect levels of single measures, they also can markedly influence the pattern of relationship among measures. The fact that such changes are seen for both obesity and fat distribution is significant, since the indices employed were chosen because they were independent of one another. ^

Dispersive optical bistability in quantum wells with logarithmic gain

We present an analytical model for studying optical bistability in semiconductor lasers that exhibit a logarithmic dependence of the optical gain on carrier concentration. Model results are shown for a Fabry–Pérot quantum-well laser and compared with the predictions of a commercial computer-aided design (CAD) software tool.

Automatic blood glucose classification for gestational diabetes with feature selection: decision trees vs neural networks

Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that compares 6 different feature selection methods for two machine learning algorithms: neural networks and decision trees. Three searching algorithms, Greedy, Best First and Genetic, were combined with two different evaluators, CSF and Wrapper, for the feature selection. The study has been made with 6080 blood glucose measurements from 25 patients. Decision trees with a feature set selected with the Wrapper evaluator and the Best first search algorithm obtained the best accuracy: 95.92%.