115 research outputs found

    Bone Marrow Transplantation Restores Follicular Maturation and Steroid Hormones Production in a Mouse Model for Primary Ovarian Failure

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    Recent studies suggest that bone marrow stem cells (BMSCs) are promising grafts to treat a variety of diseases, including reproductive dysfunction. Primary ovarian failure is characterized by amenorrhea and infertility in a normal karyotype female, with an elevated serum level of follicle-stimulating hormone (FSH) and a decrease level of estrogen caused by a mutation in FSH receptor (FSHR) gene. Currently, there is no effective treatment for this condition. The phenotype of FSHR (−/−) mouse, FORKO (follitropin receptor knockout), is a suitable model to study ovarian failure in humans. Female FORKO mice have elevated FSH, decreased estrogen levels, are sterile because of the absence of folliculogenesis, and display thin uteri and small nonfunctional ovaries. In this study, we determined the effects of BMSC transplantation on reproductive physiology in this animal model. Twenty four hours post BMSC transplantation, treated animals showed detectable estroidogeneic changes in daily vaginal smear. Significant increase in total body weight and reproductive organs was observed in treated animals. Hemotoxylin and eosin (H&E) evaluation of the ovaries demonstrated significant increase in both the maturation and the total number of the follicles in treated animals. The FSH dropped to 40–50% and estrogen increased 4–5.5 times in the serum of treated animals compared to controls. The FSHR mRNA was detected in the ovaries of treated animals. Our results show that intravenously injected BMSCs were able to reach the ovaries of FORKO mice, differentiate and express FHSR gene, make FSHR responsive to FSH, resume estrogen hormone production, and restore folliculogenesis

    Thermotropic phase behavior and headgroup interactions of the nonbilayer lipids phosphatidylethanolamine and monogalactosyldiacylglycerol in the dry state

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    <p>Abstract</p> <p>Background</p> <p>Although biological membranes are organized as lipid bilayers, they contain a substantial fraction of lipids that have a strong tendency to adopt a nonlamellar, most often inverted hexagonal (H<sub>II</sub>) phase. The polymorphic phase behavior of such nonbilayer lipids has been studied previously with a variety of methods in the fully hydrated state or at different degrees of dehydration. Here, we present a study of the thermotropic phase behavior of the nonbilayer lipids egg phosphatidylethanolamine (EPE) and monogalactosyldiacylglycerol (MGDG) with a focus on interactions between the lipid molecules in the interfacial and headgroup regions.</p> <p>Results</p> <p>Liposomes were investigated in the dry state by Fourier-transform Infrared (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC). Dry EPE showed a gel to liquid-crystalline phase transition below 0°C and a liquid-crystalline to H<sub>II </sub>transition at 100°C. MGDG, on the other hand, was in the liquid-crystalline phase down to -30°C and showed a nonbilayer transition at about 85°C. Mixtures (1:1 by mass) with two different phosphatidylcholines (PC) formed bilayers with no evidence for nonbilayer transitions up to 120°C. FTIR spectroscopy revealed complex interactions between the nonbilayer lipids and PC. Strong H-bonding interactions occurred between the sugar headgroup of MGDG and the phosphate, carbonyl and choline groups of PC. Similarly, the ethanolamine moiety of EPE was H-bonded to the carbonyl and choline groups of PC and probably interacted through charge pairing with the phosphate group.</p> <p>Conclusions</p> <p>This study provides a comprehensive characterization of dry membranes containing the two most important nonbilayer lipids (PE and MGDG) in living cells. These data will be of particular relevance for the analysis of interactions between membranes and low molecular weight solutes or soluble proteins that are presumably involved in cellular protection during anhydrobiosis.</p

    Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

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    Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

    Comprehensive molecular, genomic and phenotypic analysis of a major clone of Enterococcus faecalis MLST ST40

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    Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

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    Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

    Shifting school populations in the Long Beach Unified School District. - Page 69

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    Abstract. We propose a programming framework for the implementation of norm-aware multi-agent systems. The framework integrates the N-2APL norm-aware agent programming language with the 2OPL organisation programming language. Integration of N-2APL and 2OPL is achieved using a tuple space which represents both the (brute) state of the multi-agent environment and the detached norms and sanctions comprising its normative state. To the best of our knowledge, this is the first implementation of an integrated framework for norm-aware MAS in which autonomous agents deliberate about whether to conform to the norms imposed by a normative organisation. The use of a tuple space makes it straight-forward to integrate other system components. To illustrate the flexibility of our framework, we briefly describe its application in a novel normative application, a mixed reality game called GeoSense. We show how GeoSense game rules can be expressed as conditional norms with deadlines and sanctions, and how agents can deliberate about their individual goals and the norms imposed by the game.

    LFC:Combining Autonomous Agents and Automated Planning in the Multi-Agent Programming Contest

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    The 2019 Multi-Agent Programming Contest introduced a new scenario, Agents Assemble, where two teams of agents move around a 2D grid and compete to assemble complex block structures. In this paper, we describe the strategies used by our team that led us to achieve first place in the contest. Our strategies tackle some of the major challenges in the 2019 contest: how to explore and build a map when agents only have access to local vision and no global coordinates; how to move around the map efficiently even though there are dynamic events that can change the cells in the grid; and how to assemble and submit complex block structures given that the opposing team may try to sabotage us. To implement our strategies, we use the multi-agent systems development platform JaCaMo to program our agents and the Fast Downward planner to plan the movement of the agent in the grid. We also provide a brief discussion of our matches in the contest and give our analysis of how our team performed in each match
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