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Background: Clock genes govern circadian rhythms and shape the effect of alcohol use on the physiological system. Exposure to severe negative life events is related to both heavy drinking and disturbed circadian rhythmicity. The aim of this study was 1) to extend previous findings suggesting an association of a haplotype tagging single nucleotide polymorphism of PER2 gene with drinking patterns, and 2) to examine a possible role for an interaction of this gene with life stress in hazardous drinking.
Methods: Data were collected as part of an epidemiological cohort study on the outcome of early risk factors followed since birth. At age 19 years, 268 young adults (126 males, 142 females) were genotyped for PER2 rs56013859 and were administered a 45-day alcohol timeline follow-back interview and the Alcohol Use Disorders Identification Test (AUDIT). Life stress was assessed as the number of severe negative life events during the past four years reported in a questionnaire and validated by interview.
Results: Individuals with the minor G allele of rs56013859 were found to be less engaged in alcohol use, drinking at only 72% of the days compared to homozygotes for the major A allele. Moreover, among regular drinkers, a gene x environment interaction emerged (p = .020). While no effects of genotype appeared under conditions of low stress, carriers of the G allele exhibited less hazardous drinking than those homozygous for the A allele when exposed to high stress.
Conclusions: These findings may suggest a role of the circadian rhythm gene PER2 in both the drinking patterns of young adults and in moderating the impact of severe life stress on hazardous drinking in experienced alcohol users. However, in light of the likely burden of multiple tests, the nature of the measures used and the nominal evidence of interaction, replication is needed before drawing firm conclusions.
Understanding and accounting for the effect of exchange rate fluctuations on global learning rates
(2020)
Learning rates are a central concept in energy system models and integrated assessment models, as they allow researchers to project the future costs of new technologies and to optimize energy system costs. Here we argue that exchange rate fluctuations are an important, but thus far overlooked, determinant of the learning-rate variance observed in the literature. We explore how empirically observed global learning rates depend on where technologies are installed and which currency is used to calculate the learning rate. Using global data of large-scale photovoltaic (>= 5 MW) plants, we show that the currency choice can result in learning-rate differences of up to 16 percentage points. We then introduce an adjustment factor to correct for the effect of exchange rate and market focus fluctuations and discuss the implications of our findings for innovation scholars, energy modellers and decision makers. <br /> Learning rates are a measure of reduction in costs of energy from technologies such as solar photovoltaics. These are often estimated internationally with all monetary figures converted to a single currency, often US dollars. Lilliestam et al. show that such conversions can significantly affect the learning rate estimates.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
Background:
The medical care of patients with myositis is a great challenge in clinical practice. This is due to the rarity of these disease, the complexity of diagnosis and management as well as the lack of systematic analyses.
Objectives:
Therefore, the aim of this project was to obtain an overview of the current care of myositis patients in Germany and to evaluate epidemiological trends in recent years.
Methods:
In collaboration with BARMER Insurance, retrospective analysis of outpatient and inpatient data from an average of approximately 8.7 million insured patients between January 2005 and December 2019 was performed using ICD-10 codes for myositis for identification of relevant data.
In addition, a comparative analysis was performed between myositis patients and an age-matched comparison group from other populations insured by BARMER.
Results:
45,800 BARMER-insured individuals received a diagnosis of myositis during the observation period, with a relatively stable prevalence throughout. With regard to comorbidities, a significantly higher rate of cardiovascular disease as well as neoplasm was observed compared to the control group within the BARMER-insured population. In addition, myositis patients suffer more frequently from psychiatric disorders, such as depression and somatoform disorders.
However, the ICD-10 catalogue only includes the specific coding of "dermatomyositis" and "polymyositis" and thus does not allow for a sufficient analysis of all idiopathic inflammatory myopathies subtypes.
Conclusion:
The current data provide a comprehensive epidemiological analysis of myositis in Germany, highlighting the multimorbidity of myositis patients. This underlines the need for multidisciplinary management. However, the ICD-10 codes currently still in use do not allow for specific analysis of the subtypes of myositis.
The upcoming ICD-11 coding may improve future analyses in this regard.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2019. Selected projects have presented their results on April 9th and November 12th 2019 at the Future SOC Lab Day events.