Random forest prediction of Alzheimer's disease using pairwise selection from time series data

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a machine learning method to learn the relationship between pairs of data points at different time separations. The input vector comprises a summary of the time series history and includes both demographic and non-time varying variables such as genetic data. The dataset used is from the 2017 TADPOLE grand challenge which aims to predict the onset of Alzheimer's disease using including demographic, physical and cognitive data. The challenge is a three-fold diagnosis classification into AD, MCI and control groups, the prediction of ADAS-13 score and the normalised ventricle volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73. The results show that the method is effective and comparable with other methods.Comment: 6 pages, 1 figure, 6 table

Immune phenotype of chronic liver disease

Immune disorders in chronic liver disease may reflect common host propensities or disease-specific factors. Our aim was to determine the principal bases for these expressions. Four hundred fifty-one patients with various chronic liver diseases were assessed prospectively for concurrent immune disorders. Individuals with immune diseases were more frequently women (73% vs 60%, P = 0.02) and they had HLA DR4 more often than counterparts with other HLA (46% vs 23%, P = 0.000008). The association between HLA DR4 and immune disease was apparent within individual liver diseases and within different categories of liver disease. Women with HLA DR4 had a higher frequency of immune disease than women without HLA DR4 (52% vs 22%, P < or = 0.000001), and they also had immune diseases more commonly than DR4-positive men (52% vs 31%, P = 0.03). DR4-positive men, however, had higher frequencies of immune disease than DR4-negative men, especially in the nonimmune types of liver disease (26% vs 4%, P = 0.002). We conclude that HLA DR4 and female gender constitute an immune phenotype that is an important basis for autoimmune expression in chronic liver disease

Appreciating interconnectivity between habitats is key to Blue Carbon management

We welcome the recent synthesis by Howard et al. (2017), which drew attention to the role of marine systems and natural carbon sequestration in the oceans as a fundamental aspect of climate-change mitigation. The importance of long-term carbon storage in marine habitats (ie “blue carbon”) is rapidly gaining recognition and is increasingly a focus of national and international attempts to mitigate rising atmospheric emissions of carbon dioxide. However, effectively managing blue carbon requires an appreciation of the inherent connectivity between marine populations and habitats. More so than their terrestrial counterparts, marine ecosystems are “open”, with high rates of transfer of energy, matter, genetic material, and species across regional seascapes (Kinlan and Gaines 2003). We suggest that policy frameworks, and the science underpinning them, should focus not only on carbon sink habitats but also on carbon source habitats, which play critical roles in marine carbon cycling and natural carbon sequestration in the oceans

Potent induction of antibody-secreting B-cells by human dermal-derived CD14+ dendritic cells triggered by dual toll-like receptor ligation

Targeting CD14(+) dermal-derived dendritic cells (DDCs) is a rational approach for vaccination strategies aimed at improving humoral immune responses, because of their natural ability to stimulate naïve B-cells. Here, we show that CD14(+) DDCs express mRNA for TLRs 1–9, but respond differentially to single or paired TLR ligands. Compared to single ligands, some combinations were particularly effective at activating CD14(+) DDCs, as shown by enhanced expression of B-cell stimulatory cytokines (IL-6, IL-10 and TNF-α) and more pronounced phenotypic maturation. These combinations were Resiquimod (R-848) plus Polyinosinic:polycytidylic acid (Poly(I:C)); R-848 plus LPS; Pam3CSK4 plus Poly(I:C); LPS plus Poly(I:C). We also found that selected TLR ligand pairs (R-848 plus either LPS or Poly(I:C)) were superior to individual agents at boosting the inherent capacity of CD14(+) DDCs to induce naïve B-cells to proliferate and differentiate into CD27(+) CD38(+) B-cells that secrete high levels of IgG and IgA. When treated with the same TLR ligand combinations, CD14(+) DDCs also promoted the differentiation of Th1 (IFN-γ-secreting) CD4(+) T-cells, but not of Th2 or Th17 CD4(+) T-cells. These observations may help to identify adjuvant strategies aimed at inducing protective immune responses to various pathogens, including but not limited to HIV-1

Spatial variability in the diversity and structure of faunal assemblages associated with kelp holdfasts (<i>Laminaria hyperborea</i>) in the northeast Atlantic

<p>Map indicating the locations of the four study regions in the UK, northeast Atlantic: (A) northern Scotland, (B) western Scotland, (C) southwest Wales and (D) southwest England. Smaller panels show the positions of the 3 study sites within each region.</p

Impacts of climate change on shallow and shelf subtidal habitats, relevant to the coastal and marine environment around the UK

A comprehensive review of the literature identified thirteen new relevant studies published since the MCCIP 2013 report on ‘what is already happening’, of which all but one were conducted in UK waters. A further four studies have been published since 2013 on ‘what is likely to happen in the future’. • North Sea infaunal (burrowing) species have shifted their distributions in response to changing sea temperature, however, most species have not been able to keep pace with shifting temperature, meaning that species are subjected to warmer conditions. Leading (expanding) edges are responding more quickly than trailing (retreating) edges, which has been observed elsewhere in the world. • Analysis of a 40-year data–series found that small, generally shorter lived, infauna experienced some changes in community structure related to changes in Sea-Surface Temperature (SST), but this affect was dampened because increased food availability meant that temperature induced rises in energy use were counteracted. This was not the case for large-bodied species that experienced increased competition leading to altered community structures. This highlights that changes in non-climate drivers may interact with climate change to mediate species – community level responses and that responses may depend on species life-history traits. • A number of UK kelp species have experienced changes in abundance linked to altered SST. In particular the warm-water species, Laminaria ochroleuca, has increased in abundance and expanded its distribution into more wave-exposed conditions. While superficially similar, there are differences between warm-water and cold-water species in terms of life history characteristics (e.g. cold-water species such as L. hyperborea and L. digitata are perennial, whereas the warm-water species Saccorhiza polyschides is a pseudo-annual), and habitat provision (e.g. L. hyperborea supports diverse epiphyte assemblages whereas L. ochroleuca does not)

Mechanistic simulations of kelp populations in a dynamic landscape of light, temperature, and winter storms

\ua9 2023 The Author(s). Kelp forests are widely distributed across the coastal ocean, support high levels of biodiversity and primary productivity, and underpin a range of ecosystem services. Laminaria hyperborea is a forest-forming kelp species in the Northeast Atlantic that alters the local environment, providing biogenic structure for a diversity of associated organisms. Populations are strongly affected by light availability, temperature, and storm-related disturbance. We constructed a stage-based, two-season model of L. hyperborea populations along the coast of Great Britain and Ireland to predict biomass across a range of depths, drawing on extensive surveys and data from the literature. Population dynamics were driven by wave exposure, historic winter storm intensity, and simulated interannual variation in temperature and depth-attenuated light intensity, with density-dependent competition for light and space. High biomass was predicted in shallow depths across the domain on suitable substrate, with populations extending deeper in the north and west where light penetration was greater. Detritus production was heavily skewed across years, particularly at greater depths, with 10 % of years comprising more than 50 % of detritus on average below 10 m depth. Annual fluctuations in light and storm intensity produced opposing population oscillations with a ∼6-year period persisting for up to a decade but diminishing sharply with depth. Interannual variation in temperature had minimal impact. Biomass was most sensitive to survival and settlement rates, with negligible sensitivity to individual growth rates. This model highlights the need for an improved understanding of canopy and subcanopy mortality, particularly regarding increasingly frequent heatwaves. Estimations of kelp forest contributions to carbon sequestration should consider the high variability among years or risk underestimating the potential value of kelp forests. Process-based simulations of populations with realistic spatiotemporal environmental variability are a valuable approach to forecasting biotic responses to an increasingly extreme climate