Open Problems on Central Simple Algebras

We provide a survey of past research and a list of open problems regarding central simple algebras and the Brauer group over a field, intended both for experts and for beginners.Comment: v2 has some small revisions to the text. Some items are re-numbered, compared to v

The Dopamine Augmenter L-DOPA Does Not Affect Positive Mood in Healthy Human Volunteers

Dopamine neurotransmission influences approach toward rewards and reward-related cues. The best cited interpretation of this effect proposes that dopamine mediates the pleasure that commonly accompanies reward. This hypothesis has received support in some animal models and a few studies in humans. However, direct assessments of the effect of transiently increasing dopamine neurotransmission have been largely limited to the use of psychostimulant drugs, which elevate brain levels of multiple neurotransmitters in addition to dopamine. In the present study we tested the effect of more selectively elevating dopamine neurotransmission, as produced by administration of the immediate dopamine precursor, L-DOPA (0, 100/25, 200/50 mg, Sinemet), in healthy human volunteers. Neither dose altered positive mood. The results suggest that dopamine neurotransmission does not directly influence positive mood in humans

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Robust Metabolic Responses to Varied Carbon Sources in Natural and Laboratory Strains of Saccharomyces cerevisiae

Understanding factors that regulate the metabolism and growth of an organism is of fundamental biologic interest. This study compared the influence of two different carbon substrates, dextrose and galactose, on the metabolic and growth rates of the yeast Saccharomyces cerevisiae. Yeast metabolic and growth rates varied widely depending on the metabolic substrate supplied. The metabolic and growth rates of a yeast strain maintained under long-term laboratory conditions was compared to strain isolated from natural condition when grown on different substrates. Previous studies had determined that there are numerous genetic differences between these two strains. However, the overall metabolic and growth rates of a wild isolate of yeast was very similar to that of a strain that had been maintained under laboratory conditions for many decades. This indicates that, at in least this case, metabolism and growth appear to be well buffered against genetic differences. Metabolic rate and cell number did not co-vary in a simple linear manner. When grown in either dextrose or galactose, both strains showed a growth pattern in which the number of cells continued to increase well after the metabolic rate began a sharp decline. Previous studied have reported that O2 consumption in S. cerevisiae grown in reduced dextrose levels were elevated compared to higher levels. Low dextrose levels have been proposed to induce caloric restriction and increase life span in yeast. However, there was no evidence that reduced levels of dextrose increased metabolic rates, measured by either O2 consumption or CO2 production, in the strains used in this study

Achieving Optimal Growth through Product Feedback Inhibition in Metabolism

Recent evidence suggests that the metabolism of some organisms, such as Escherichia coli, is remarkably efficient, producing close to the maximum amount of biomass per unit of nutrient consumed. This observation raises the question of what regulatory mechanisms enable such efficiency. Here, we propose that simple product-feedback inhibition by itself is capable of leading to such optimality. We analyze several representative metabolic modules—starting from a linear pathway and advancing to a bidirectional pathway and metabolic cycle, and finally to integration of two different nutrient inputs. In each case, our mathematical analysis shows that product-feedback inhibition is not only homeostatic but also, with appropriate feedback connections, can minimize futile cycling and optimize fluxes. However, the effectiveness of simple product-feedback inhibition comes at the cost of high levels of some metabolite pools, potentially associated with toxicity and osmotic imbalance. These large metabolite pool sizes can be restricted if feedback inhibition is ultrasensitive. Indeed, the multi-layer regulation of metabolism by control of enzyme expression, enzyme covalent modification, and allostery is expected to result in such ultrasensitive feedbacks. To experimentally test whether the qualitative predictions from our analysis of feedback inhibition apply to metabolic modules beyond linear pathways, we examine the case of nitrogen assimilation in E. coli, which involves both nutrient integration and a metabolic cycle. We find that the feedback regulation scheme suggested by our mathematical analysis closely aligns with the actual regulation of the network and is sufficient to explain much of the dynamical behavior of relevant metabolite pool sizes in nutrient-switching experiments

Executive Function and Falls in Older Adults: New Findings from a Five-Year Prospective Study Link Fall Risk to Cognition

Background: Recent findings suggest that executive function (EF) plays a critical role in the regulation of gait in older adults, especially under complex and challenging conditions, and that EF deficits may, therefore, contribute to fall risk. The objective of this study was to evaluate if reduced EF is a risk factor for future falls over the course of 5 years of follow-up. Secondary objectives were to assess whether single and dual task walking abilities, an alternative window into EF, were associated with fall risk. Methodology/Main Results We longitudinally followed 256 community-living older adults (age: 76.4±4.5 yrs; 61% women) who were dementia free and had good mobility upon entrance into the study. At baseline, a computerized cognitive battery generated an index of EF, attention, a closely related construct, and other cognitive domains. Gait was assessed during single and dual task conditions. Falls data were collected prospectively using monthly calendars. Negative binomial regression quantified risk ratios (RR). After adjusting for age, gender and the number of falls in the year prior to the study, only the EF index (RR: .85; CI: .74–.98, p = .021), the attention index (RR: .84; CI: .75–.94, p = .002) and dual tasking gait variability (RR: 1.11; CI: 1.01–1.23; p = .027) were associated with future fall risk. Other cognitive function measures were not related to falls. Survival analyses indicated that subjects with the lowest EF scores were more likely to fall sooner and more likely to experience multiple falls during the 66 months of follow-up (p<0.02). Conclusions/Significance: These findings demonstrate that among community-living older adults, the risk of future falls was predicted by performance on EF and attention tests conducted 5 years earlier. The present results link falls among older adults to cognition, indicating that screening EF will likely enhance fall risk assessment, and that treatment of EF may reduce fall risk

The role of impulsivity in the aetiology of drug dependence: reward sensitivity versus automaticity

Journal ArticleResearch Support, Non-U.S. Gov'tCopyright © The Author(s) 2011.RATIONALE: Impulsivity has long been known as a risk factor for drug dependence, but the mechanisms underpinning this association are unclear. Impulsivity may confer hypersensitivity to drug reinforcement which establishes higher rates of instrumental drug-seeking and drug-taking behaviour, or may confer a propensity for automatic (non-intentional) control over drug-seeking/taking and thus intransigence to clinical intervention. METHOD: The current study sought to distinguish these two accounts by measuring Barratt Impulsivity and craving to smoke in 100 smokers prior to their completion of an instrumental concurrent choice task for tobacco (to measure the rate of drug-seeking) and an ad libitum smoking test (to measure the rate of drug-taking-number of puffs consumed). RESULTS: The results showed that impulsivity was not associated with higher rates of drug-seeking/taking, but individual differences in smoking uptake and craving were. Rather, nonplanning impulsivity moderated (decreased) the relationship between craving and drug-taking, but not drug-seeking. CONCLUSIONS: These data suggest that whereas the uptake of drug use is mediated by hypervaluation of the drug as an instrumental goal, the orthogonal trait nonplanning impulsivity confers a propensity for automatic control over well-practiced drug-taking behaviour.MR

A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division

Upstream events that trigger initiation of cell division, at a point called START in yeast, determine the overall rates of cell proliferation. The identity and complete sequence of those events remain unknown. Previous studies relied mainly on cell size changes to identify systematically genes required for the timely completion of START. Here, we evaluated panels of non-essential single gene deletion strains for altered DNA content by flow cytometry. This analysis revealed that most gene deletions that altered cell cycle progression did not change cell size. Our results highlight a strong requirement for ribosomal biogenesis and protein synthesis for initiation of cell division. We also identified numerous factors that have not been previously implicated in cell cycle control mechanisms. We found that CBS, which catalyzes the synthesis of cystathionine from serine and homocysteine, advances START in two ways: by promoting cell growth, which requires CBS's catalytic activity, and by a separate function, which does not require CBS's catalytic activity. CBS defects cause disease in humans, and in animals CBS has vital, non-catalytic, unknown roles. Hence, our results may be relevant for human biology. Taken together, these findings significantly expand the range of factors required for the timely initiation of cell division. The systematic identification of non-essential regulators of cell division we describe will be a valuable resource for analysis of cell cycle progression in yeast and other organisms

Metabotropic glutamate receptor 5 as a potential target for smoking cessation

Rationale Most habitual smokers find it difficult to quit smoking because they are dependent upon the nicotine present in tobacco smoke. Tobacco dependence is commonly treated pharmacologically using nicotine replacement therapy or drugs, such as varenicline, that target the nicotinic receptor. Relapse rates, however, remain high and there remains a need to develop novel non-nicotinic pharmacotherapies for the dependence that are more effective than existing treatments. Objective The purpose of this paper is to review the evidence from preclinical and clinical studies that drugs that antagonise the metabotropic glutamate receptor 5 (mGluR5) in the brain are likely to be efficacious as treatments for tobacco dependence. Results Imaging studies reveal that chronic exposure to tobacco smoke reduces the density of mGluR5s in human brain. Preclinical results demonstrate that negative allosteric modulators (NAMs) at mGluR5 attenuate both nicotine self-administration and the reinstatement of responding evoked by exposure to conditioned cues paired with nicotine delivery. They also attenuate the effects of nicotine on brain dopamine pathways implicated in addiction. Conclusions Although mGluR5 NAMs attenuate most of the key facets of nicotine dependence they potentiate the symptoms of nicotine withdrawal. This may limit their value as smoking cessation aids. The NAMs that have been employed most widely in preclinical studies of nicotine dependence have too many \u201coff target\u201d effects to be used clinically. However newer mGluR5 NAMs have been developed for clinical use in other indications. Future studies will determine if these agents can also be used effectively and safely to treat tobacco dependence

Large-Scale Phylogenetic Analysis of Emerging Infectious Diseases

Microorganisms that cause infectious diseases present critical issues of national security, public health, and economic welfare.  For example, in recent years, highly pathogenic strains of avian influenza have emerged in Asia, spread through Eastern Europe and threaten to become pandemic. As demonstrated by the coordinated response to Severe Acute Respiratory Syndrome (SARS) and influenza, agents of infectious disease are being addressed via large-scale genomic sequencing.  The goal of genomic sequencing projects are to rapidly put large amounts of data in the public domain to accelerate research on disease surveillance, treatment, and prevention. However, our ability to derive information from large comparative genomic datasets lags far behind acquisition.  Here we review the computational challenges of comparative genomic analyses, specifically sequence alignment and reconstruction of phylogenetic trees.  We present novel analytical results on from two important infectious diseases, Severe Acute Respiratory Syndrome (SARS) and influenza.SARS and influenza have similarities and important differences both as biological and comparative genomic analysis problems.  Influenza viruses (Orthymxyoviridae) are RNA based.  Current evidence indicates that influenza viruses originate in aquatic birds from wild populations. Influenza has been studied for decades via well-coordinated international efforts.  These efforts center on surveillance via antibody characterization of the hemagglutinin (HA) and neuraminidase (N) proteins of the circulating strains to inform vaccine design. However we still do not have a clear understanding of: 1) various transmission pathways such as the role of intermediate hosts such as swine and domestic birds and 2) the key mutation and genomic recombination events that underlie periodic pandemics of influenza.  In the past 30 years, sequence data from HA and N loci has become an important data type. In the past year, full genomic data has become prominent.  These data present exciting opportunities to address unanswered questions in influenza pandemics.SARS is caused by a previously unrecognized lineage of coronavirus, SARS-CoV, which like influenza has an RNA based genome.  Although SARS-CoV is widely believed to have originated in animals there remains disagreement over the candidate animal source that lead to the original outbreak of SARS.  In contrast to the long history of the study of influenza, SARS was only recognized in late 2002 and the virus that causes SARS has been documented primarily by genomic sequencing.In the past, most studies of influenza were performed on a limited number of isolates and genes suited to a particular problem.  Major goals in science today are to understand emerging diseases in broad geographic, environmental, societal, biological, and genomic contexts. Synthesizing diverse information brought together by various researchers is important to find out what can be done to prevent future outbreaks {JON03}.  Thus comprehensive means to organize and analyze large amounts of diverse information are critical.  For example, the relationships of isolates and patterns of genomic change observed in large datasets might not be consistent with hypotheses formed on partial data.  Moreover when researchers rely on partial datasets, they restrict the range of possible discoveries.Phylogenetics is well suited to the complex task of understanding emerging infectious disease. Phylogenetic analyses can test many hypotheses by comparing diverse isolates collected from various hosts, environments, and points in time and organizing these data into various evolutionary scenarios.  The products of a phylogenetic analysis are a graphical tree of ancestor-descendent relationships and an inferred summary of mutations, recombination events, host shifts, geographic, and temporal spread of the viruses.  However, this synthesis comes at a price.  The cost of computation of phylogenetic analysis expands combinatorially as the number of isolates considered increases. Thus, large datasets like those currently produced are commonly considered intractable.  We address this problem with synergistic development of heuristics tree search strategies and parallel computing.Fil: Janies, D.. Ohio State University; Estados UnidosFil: Pol, Diego. Ohio State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin