Contributions of vascular and Alzheimer's disease pathology to dementia

Non peer reviewe

Radio-Frequency Single-Electron Refrigerator

We propose a cyclic refrigeration principle based on mesoscopic electron transport. Synchronous sequential tunnelling of electrons in a Coulomb-blockaded device, a normal metal-superconductor single-electron box, results in a cooling power of $\sim k_{\rm B}T \times f$ at temperature $T$ over a wide range of cycle frequencies $f$. Electrostatic work, done by the gate voltage source, removes heat from the Coulomb island with an efficiency of $\sim k_{\rm B}T/\Delta$, where $\Delta$ is the superconducting gap. The performance is not affected significantly by non-idealities, for instance by offset charges. We propose ways of characterizing the system and of its practical implementation.Comment: 5 pages, 4 figures; corrected typos, language improve

Effectiveness of legislative changes obligating notification of prolonged sickness absence and assessment of remaining work ability on return to work and work participation : a natural experiment in Finland

Objectives Policies have been introduced to reduce sickness absence, but their effectiveness is largely unknown. In a natural experiment, we examined effects of legislative changes on return to work and work participation. Methods The source population consisted of up to 72164 Finnish public sector employees with a permanent job contract in 2008-2011 (before) and in 2013-2014 (after). We used employees with a continuous sickness absence of at least 30 calendar-days (n=5708-6393), 60 compensated days (n=1481-1655) and 90 compensated days (n=766-932). We examined sustainable return to work (a minimum of 28 consecutive working days) with survival analysis as well as monthly work participation after a sickness absence, and annual gain in work participation after the intervention, using trajectory analyses. Results Sustainable return to work after 60days of sickness absence occurred earlier after the legislative changes (p value 0.017), although the effect reduced towards the end of the follow-up. There were no differences in return to work after a 30 or 90days of sickness absence. The largest annual gain, postintervention versus preintervention, in monthly work participation was observed among employees with 60days of sickness absence and was 230.9 person-years/10000 employees. The corresponding annual gains among those with 30days and 90days of sickness absence were 51.8 and 39.6, respectively. Conclusions Our findings suggest that the legislative changes, obligating early notification of prolonged sickness absences as well as assessment of remaining work ability and possibilities to continue working, may enhance sustainable return to work in the short term. Other measures will be needed to enhance work participation, especially in the long term.Peer reviewe

Learning and generalization of compositional representations of visual scenes

Complex visual scenes that are composed of multiple objects, each with attributes, such as object name, location, pose, color, etc., are challenging to describe in order to train neural networks. Usually,deep learning networks are trained supervised by categorical scene descriptions. The common categorical description of a scene contains the names of individual objects but lacks information about other attributes. Here, we use distributed representations of object attributes and vector operations in a vector symbolic architecture to create a full compositional description of a scene in a high-dimensional vector. To control the scene composition, we use artificial images composed of multiple, translated and colored MNIST digits. In contrast to learning category labels, here we train deep neural networks to output the full compositional vector description of an input image. The output of the deep network can then be interpreted by a VSA resonator network, to extract object identity or other properties of indiviual objects. We evaluate the performance and generalization properties of the system on randomly generated scenes. Specifically, we show that the network is able to learn the task and generalize to unseen seen digit shapes and scene configurations. Further, the generalisation ability of the trained model is limited. For example, with a gap in the training data, like an object not shown in a particular image location during training, the learning does not automatically fill this gap.Comment: 10 pages, 6 figure

High-resolution analysis of observed thermal growing season variability over northern Europe

Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 degrees C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990-2019) and consistent temporal trends (1950-2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 degrees C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m x 100 m) and with high accuracy (correlation >= 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.Peer reviewe

High-resolution analysis of observed thermal growing season variability over northern Europe

Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 degrees C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990-2019) and consistent temporal trends (1950-2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 degrees C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m x 100 m) and with high accuracy (correlation >= 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.Peer reviewe

Large Impacts of Climatic Warming on Growth of Boreal Forests since 1960

Peer reviewe

Trends in work disability with mental diagnoses among social workers in Finland and Sweden in 2005-2012

AIMS: Social workers report high levels of stress and have an increased risk for hospitalisation with mental diagnoses. However, it is not known whether the risk of work disability with mental diagnoses is higher among social workers compared with other human service professionals. We analysed trends in work disability (sickness absence and disability pension) with mental diagnoses and return to work (RTW) in 2005-2012 among social workers in Finland and Sweden, comparing with such trends in preschool teachers, special education teachers and psychologists. METHODS: Records of work disability (>14 days) with mental diagnoses (ICD-10 codes F00-F99) from nationwide health registers were linked to two prospective cohort projects: the Finnish Public Sector study, years 2005-2011 and the Insurance Medicine All Sweden database, years 2005-2012. The Finnish sample comprised 4849 employees and the Swedish 119 219 employees covering four occupations: social workers (Finland 1155/Sweden 23 704), preschool teachers (2419/74 785), special education teachers (832/14 004) and psychologists (443/6726). The reference occupations were comparable regarding educational level. Risk of work disability was analysed with negative binomial regression and RTW with Cox proportional hazards. RESULTS: Social workers in Finland and Sweden had a higher risk of work disability with mental diagnoses compared with preschool teachers and special education teachers (rate ratios (RR) 1.43-1.91), after adjustment for age and sex. In Sweden, but not in Finland, social workers also had higher work disability risk than psychologists (RR 1.52; 95% confidence interval 1.28-1.81). In Sweden, in the final model special education teachers had a 9% higher probability RTW than social workers. In Sweden, in the final model the risks for work disability with depression diagnoses and stress-related disorder diagnoses were similar to the risk with all mental diagnoses (RR 1.40-1.77), and the probability of RTW was 6% higher in preschool teachers after work disability with depression diagnoses and 9% higher in special education teachers after work disability with stress-related disorder diagnoses compared with social workers. CONCLUSION: Social workers appear to be at a greater risk of work disability with mental diagnoses compared with other human service professionals in Finland and Sweden. It remains to be studied whether the higher risk is due to selection of vulnerable employees to social work or the effect of work-related stress in social work. Further studies should focus on these mechanisms and the risk of work disability with mental diagnoses among human service professionals

C9orf72 hexanucleotide repeat length in older population: normal variation and effects on cognition

The hexanucleotide repeat expansion in C9orf72 is a common cause of amyotrophic lateral sclerosis/frontotemporal dementia and also rarely found in other psychiatric and neurodegenerative conditions. Alleles with >30 repeats are often considered an expansion, but the pathogenic repeat length threshold is still unclear. It is also unclear whether intermediate repeat length alleles (often defined either as 7-30 or 20-30 repeats) have clinically significant effects. We determined the C9orf72 repeat length distribution in 3142 older Finns (aged 60-104 years). The longest nonexpanded allele was 45 repeats. We found 7-45 repeats in 1036/3142 (33%) individuals, 20-45 repeats in 56/3142 (1.8%), 30-45 repeats in 12/3142 (0.38%), and expansion (>45 repeats) in 6/3142 (0.19%). There was no apparent clustering of neurodegenerative or psychiatric diseases in individuals with 30-45 repeats indicating that 30-45 repeats are not pathogenic. None of the 6 expansion carriers had a diagnosis of amyotrophic lateral sclerosis/frontotemporal dementia but 4 had a diagnosis of a neurodegenerative or psychiatric disease. Intermediate length alleles (categorized as 7-45 and 20-45 repeats) did not associate with Alzheimer's disease or cognitive impairment. (C) 2019 The Author(s). Published by Elsevier Inc.Peer reviewe

Heterozygous TYROBP deletion (PLOSLFIN) is not a strong risk factor for cognitive impairment

Biallelic loss-of-function mutations in TYROBP and TREM2 cause a rare disease that resembles early-onset frontotemporal dementia with bone lesions called polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy (PLOSL). Some PLOSL-causing variants in TREM2 have also been associated with Alzheimer's disease when heterozygous. Here, we studied the PLOSLFIN TYROBP deletion that covers 4 of the gene's 5 exons. We genotyped 3220 older Finns (mean age 79, range 58-104) and found 11 deletion carriers (mean age 78, range 60-94). The carrier prevalence was 0.0034 (1 in 293) that matches previous findings in younger cohorts suggesting no significant early mortality. By comparing Mini-Mental State Examination (MMSE) scores and diagnoses of dementia, we did not find any significant differences between TYROBP deletion carriers and noncarriers (all p-values >0.5). Neuropathological analysis of 2 deletion carriers (aged 89 and 94 years) demonstrated only minimal beta amyloid pathology (Consortium to Establish a Registry for Alzheimer's Disease (CERAD) score 0). Collectively these results suggest that heterozygous carriership of the TYROBP deletion is not a major risk factor of cognitive impairment. (C) 2017 Elsevier Inc. All rights reserved.Peer reviewe