Bayesian Forecasting and Dynamic Linear Models

Dynamic models offer a powerful framework for the modelling and analysis of time series, especially noisy time series, which are subject to abrupt changes in pattern. They are used in many time series applications from finance and econometrics, to biological series used in clinical monitoring. In this thesis we describe in detail how dynamic models can be used to model time series, following work from West and Harrison. In particular, we will focus our attention to a specific problem of monitoring kidney failure in patients that have just had cardiac surgery. This work is in joint collaboration with the cardiac surgery unit at the University Hospital of South Manchester. The particular problem studied is that of developing an on-line statistical procedure to monitor the progress of kidney function in individual patients who have recently had heart surgery

Activating receptors promote NK cell expansion for maintenance, IL-10 production, and CD8 T cell regulation during viral infection

Natural killer (NK) cells have the potential to deliver both direct antimicrobial effects and regulate adaptive immune responses, but NK cell yields have been reported to vary greatly during different viral infections. Activating receptors, including the Ly49H molecule recognizing mouse cytomegalovirus (MCMV), can stimulate NK cell expansion. To define Ly49H's role in supporting NK cell proliferation and maintenance under conditions of uncontrolled viral infection, experiments were performed in Ly49h−/−, perforin 1 (Prf1)−/−, and wild-type (wt) B6 mice. NK cell numbers were similar in uninfected mice, but relative to responses in MCMV-infected wt mice, NK cell yields declined in the absence of Ly49h and increased in the absence of Prf1, with high rates of proliferation and Ly49H expression on nearly all cells. The expansion was abolished in mice deficient for both Ly49h and Prf1 (Ly49h−/−Prf1−/−), and negative consequences for survival were revealed. The Ly49H-dependent protection mechanism delivered in the absence of Prf1 was a result of interleukin 10 production, by the sustained NK cells, to regulate the magnitude of CD8 T cell responses. Thus, the studies demonstrate a previously unappreciated critical role for activating receptors in keeping NK cells present during viral infection to regulate adaptive immune responses

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The descriptive epidemiology of DSM-IV Adult ADHD in the World Health Organization World Mental Health Surveys

We previously reported on the cross-national epidemiology of ADHD from the first 10 countries in the WHO World Mental Health (WMH) Surveys. The current report expands those previous findings to the 20 nationally or regionally representative WMH surveys that have now collected data on adult ADHD. The Composite International Diagnostic Interview (CIDI) was administered to 26,744 respondents in these surveys in high-, upper-middle-, and low-/lower-middle-income countries (68.5% mean response rate). Current DSM-IV/CIDI adult ADHD prevalence averaged 2.8% across surveys and was higher in high (3.6%)- and upper-middle (3.0%)- than low-/lower-middle (1.4%)-income countries. Conditional prevalence of current ADHD averaged 57.0% among childhood cases and 41.1% among childhood subthreshold cases. Adult ADHD was significantly related to being male, previously married, and low education. Adult ADHD was highly comorbid with DSM-IV/CIDI anxiety, mood, behavior, and substance disorders and significantly associated with role impairments (days out of role, impaired cognition, and social interactions) when controlling for comorbidities. Treatment seeking was low in all countries and targeted largely to comorbid conditions rather than to ADHD. These results show that adult ADHD is prevalent, seriously impairing, and highly comorbid but vastly under-recognized and undertreated across countries and cultures

Molecular changes in the postmortem parkinsonian brain

Parkinson disease (PD) is the second most common neurodegenerative disease after Alzheimer disease. Although PD has a relatively narrow clinical phenotype, it has become clear that its etiological basis is broad. Post-mortem brain analysis, despite its limitations, has provided invaluable insights into relevant pathogenic pathways including mitochondrial dysfunction, oxidative stress and protein homeostasis dysregulation. Identification of the genetic causes of PD followed the discovery of these abnormalities, and reinforced the importance of the biochemical defects identified post-mortem. Recent genetic studies have highlighted the mitochondrial and lysosomal areas of cell function as particularly significant in mediating the neurodegeneration of PD. Thus the careful analysis of post-mortem PD brain biochemistry remains a crucial component of research, and one that offers considerable opportunity to pursue etiological factors either by ‘reverse biochemistry’ i.e. from defective pathway to mutant gene, or by the complex interplay between pathways e.g. mitochondrial turnover by lysosomes. In this review we have documented the spectrum of biochemical defects identified in PD post-mortem brain and explored their relevance to metabolic pathways involved in neurodegeneration. We have highlighted the complex interactions between these pathways and the gene mutations causing or increasing risk for PD. These pathways are becoming a focus for the development of disease modifying therapies for PD. Parkinson's is accompanied by multiple changes in the brain that are responsible for the progression of the disease. We describe here the molecular alterations occurring in postmortem brains and classify them as: Neurotransmitters and neurotrophic factors; Lewy bodies and Parkinson's-linked genes; Transition metals, calcium and calcium-binding proteins; Inflammation; Mitochondrial abnormalities and oxidative stress; Abnormal protein removal and degradation; Apoptosis and transduction pathways

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives