137 research outputs found
Mutations in mákos, a Drosophila gene encoding the Cdc27 subunit of the anaphase promoting complex, enhance centrosomal defects in polo and are suppressed by mutations in twins/aar, which encodes a regulatory subunit of PP2A
The gene mákos (mks) encodes the Drosophila counterpart of the Cdc27 subunit of the anaphase promoting complex (APC/C). Neuroblasts from third-larval-instar mks mutants arrest mitosis in a metaphase-like state but show some separation of sister chromatids. In contrast to metaphase-checkpoint-arrested cells, such mutant neuroblasts contain elevated levels not only of cyclin B but also of cyclin A. Mutations in mks enhance the reduced ability of hypomorphic polo mutant alleles to recruit and/or maintain the centrosomal antigens γ-tubulin and CP190 at the spindle poles. Absence of the MPM2 epitope from the spindle poles in such double mutants suggests Polo kinase is not fully activated at this location. Thus, it appears that spindle pole functions of Polo kinase require the degradation of early mitotic targets of the APC/C, such as cyclin A, or other specific proteins. The metaphase-like arrest of mks mutants cannot be overcome by mutations in the spindle integrity checkpoint gene bub1, confirming this surveillance pathway has to operate through the APC/C. However, mutations in the twins/aar gene, which encodes the 55kDa regulatory subunit of PP2A, do suppress the mks metaphase arrest and so permit an alternative means of initiating anaphase. Thus the APC/C might normally be required to inactivate wild-type twins/aar gene product
Geographic and ecological eimensions of host plant-associated genetic differentiation and speciation in the Rhagoletis cingulata (Diptera: Tephritidae) sibling species group
Ascertaining the causes of adaptive radiation is central to understanding how new species arise and come to vary with their resources. The ecological theory posits adaptive radiation via divergent natural selection associated with novel resource use; an alternative suggests character displacement following speciation in allopatry and then secondary contact of reproductively isolated but ecologically similar species. Discriminating between hypotheses, therefore, requires the establishment of a key role for ecological diversification in initiating speciation versus a secondary role in facilitating co-existence. Here, we characterize patterns of genetic variation and postzygotic reproductive isolation for tephritid fruit flies in the Rhagoletis cingulata sibling species group to assess the significance of ecology, geography, and non-adaptive processes for their divergence. Our results support the ecological theory: no evidence for intrinsic postzygotic reproductive isolation was found between two populations of allopatric species, while nuclear-encoded microsatellites implied strong ecologically based reproductive isolation among sympatric species infesting different host plants. Analysis of mitochondrial DNA suggested, however, that cytoplasmic-related reproductive isolation may also exist between two geographically isolated populations within R cingulata. Thus, ecology associated with sympatric host shifts and cytoplasmic effects possiblyFil: Doellman, Meredith M.. University of Notre Dame-Indiana; Estados UnidosFil: Schuler, Hannes. University Of Bozen-bolzano; ItaliaFil: Saint Jean, Gilbert. University of Notre Dame-Indiana; Estados UnidosFil: Hood, Glenn R.. Wane State University; Estados UnidosFil: Egan, Scott P.. Rice University; Estados UnidosFil: Powell, Thomas H. Q.. University of Binghamton; Estados UnidosFil: Glover, Mary M.. University of Notre Dame-Indiana; Estados UnidosFil: Bruzzese, Daniel J.. University of Notre Dame-Indiana; Estados UnidosFil: Smith, James J.. Michigan State University; Estados UnidosFil: Yee, Wee L.. United States Department of Agriculture. Agricultural Research Service; ArgentinaFil: Goughnour, Robert B.. Washington State University; Estados UnidosFil: Rull Gabayet, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; ArgentinaFil: Aluja, Martín. Instituto de Ecología A.c.; MéxicoFil: Feder, Jeffrey L.. University of Notre Dame-Indiana; Estados Unido
3D Protein structure prediction with genetic tabu search algorithm
Abstract Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively
Stress Biomarkers as Outcomes for HIV+ Prevention: Participation, Feasibility and Findings Among HIV+ Latina and African American Mothers
Mothers living with HIV (MLH) are at high risk for acute and chronic stress, given challenges related to their HIV status, ethnicity, economic and urban living conditions. Biomarkers combined into a composite index show promise in quantifying psychosocial stress in healthy people, but have not yet been examined among MLH. According, we examined potential biomarker correlates of stress [cortisol and catecholamines from home-collected urine and basic health indicators (blood pressure, height and weight, waist-to-hip ratio) measured during an interview] among 100 poor African American and Latina mothers MLH and demographic-matched control mothers without HIV (n = 50). Participants had been enrolled in a randomized controlled trial about 18 months earlier and had either received (MLH-I) or were awaiting (MLH-W) the psychosocial intervention. Participation was high, biomarkers were correctly collected for 93% of cases, and a complete composite biomarker index (CBI) calculated for 133 mothers (mean age = 42). As predicted, MLH had a significantly higher CBI than controls, but there was no CBI difference across ethnicity or intervention group. CBI predicted CD4 counts independently after controlling for age, years since diagnosis, prior CD4 counts, medication adherence, and depression symptoms. The study demonstrates acceptability, feasibility and potential utility of community-based biomarker collections in evaluating individual differences in psychosocial stress
Recursive Cluster Elimination Based Support Vector Machine for Disease State Prediction Using Resting State Functional and Effective Brain Connectivity
Brain state classification has been accomplished using features such as voxel intensities, derived from functional magnetic resonance imaging (fMRI) data, as inputs to efficient classifiers such as support vector machines (SVM) and is based on the spatial localization model of brain function. With the advent of the connectionist model of brain function, features from brain networks may provide increased discriminatory power for brain state classification.In this study, we introduce a novel framework where in both functional connectivity (FC) based on instantaneous temporal correlation and effective connectivity (EC) based on causal influence in brain networks are used as features in an SVM classifier. In order to derive those features, we adopt a novel approach recently introduced by us called correlation-purged Granger causality (CPGC) in order to obtain both FC and EC from fMRI data simultaneously without the instantaneous correlation contaminating Granger causality. In addition, statistical learning is accelerated and performance accuracy is enhanced by combining recursive cluster elimination (RCE) algorithm with the SVM classifier. We demonstrate the efficacy of the CPGC-based RCE-SVM approach using a specific instance of brain state classification exemplified by disease state prediction. Accordingly, we show that this approach is capable of predicting with 90.3% accuracy whether any given human subject was prenatally exposed to cocaine or not, even when no significant behavioral differences were found between exposed and healthy subjects.The framework adopted in this work is quite general in nature with prenatal cocaine exposure being only an illustrative example of the power of this approach. In any brain state classification approach using neuroimaging data, including the directional connectivity information may prove to be a performance enhancer. When brain state classification is used for disease state prediction, our approach may aid the clinicians in performing more accurate diagnosis of diseases in situations where in non-neuroimaging biomarkers may be unable to perform differential diagnosis with certainty
Limb development genes underlie variation in human fingerprint patterns
Fingerprints are of long-standing practical and cultural interest, but little is known about the mechanisms that underlie their variation. Using genome-wide scans in Han Chinese cohorts, we identified 18 loci associated with fingerprint type across the digits, including a genetic basis for the long-recognized “pattern-block” correlations among the middle three digits. In particular, we identified a variant near EVI1 that alters regulatory activity and established a role for EVI1 in dermatoglyph patterning in mice. Dynamic EVI1 expression during human development supports its role in shaping the limbs and digits, rather than influencing skin patterning directly. Trans-ethnic meta-analysis identified 43 fingerprint-associated loci, with nearby genes being strongly enriched for general limb development pathways. We also found that fingerprint patterns were genetically correlated with hand proportions. Taken together, these findings support the key role of limb development genes in influencing the outcome of fingerprint patterning
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Optical Trapping with High Forces Reveals Unexpected Behaviors of Prion Fibrils
Amyloid fibrils are important in diverse cellular functions, feature in many human diseases and have potential applications in nanotechnology. Here we describe methods that combine optical trapping and fluorescent imaging to characterize the forces that govern the integrity of amyloid fibrils formed by a yeast prion protein. A crucial advance was to use the self-templating properties of amyloidogenic proteins to tether prion fibrils, enabling their manipulation in the optical trap. At normal pulling forces the fibrils were impervious to disruption. At much higher forces (up to 250 pN), discontinuities occurred in force-extension traces before fibril rupture. Experiments with selective amyloid-disrupting agents and mutations demonstrated that such discontinuities were caused by the unfolding of individual subdomains. Thus, our results reveal unusually strong noncovalent intermolecular contacts that maintain fibril integrity even when individual monomers partially unfold and extend fibril length.National Institutes of Health (U.S.) (Grant GM025874)National Science Foundation (U.S.). CAREER (Award 0643745
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