Links between host genetics, metabolism, gut microbiome and amoebic gill disease (AGD) in Atlantic Salmon

Background: Rapidly spreading parasitic infections like amoebic gill disease (AGD) are increasingly problematic for Atlantic salmon reared in aquaculture facilities and potentially pose a risk to wild fish species in surrounding waters. Currently, it is not known whether susceptibility to AGD differs between wild and farmed salmon. Wild Atlantic salmon populations are declining and this emerging disease could represent an additional threat to their long-term viability. A better understanding of how AGD affects fish health is therefore relevant for the accurate assessment of the associated risk, both to farming and to the well-being of wild populations. In this study, we assessed the impact of natural exposure to AGD on wild, hybrid and farmed post-smolt Atlantic salmon reared in a sea farm together under common garden conditions. Results: Wild fish showed substantially higher mortality levels (64%) than farmed fish (25%), with intermediate levels for hybrid fish (39%) suggesting that AGD susceptibility has an additive genetic basis. Metabolic rate measures representing physiological performance were similar among the genetic groups but were significantly lower in AGD-symptomatic fish than healthy fish. Gut microbial diversity was significantly lower in infected fish. We observed major shifts in gut microbial community composition in response to AGD infections. In symptomatic fish the relative abundance of key taxa Aliivibrio, Marinomonas and Pseudoalteromonas declined, whereas the abundance of Polaribacter and Vibrio increased compared to healthy fish. Conclusions: Our results highlight the stress AGD imposes on fish physiology and suggest that low metabolic-rate fish phenotypes may be associated with better infection outcomes. We consider the role increased AGD outbreak events and a warmer future may have in driving secondary bacterial infections and in reducing performance in farmed and wild fish

Comparisons of time series of annual mean surface air temperature for China since the 1900s: Observations, model simulations and extended reanalysis

This paper assesses the similarities and differences of several annual average SAT time series for China based on historical meteorological observations since the 1900s. Time series of global or regional average surface air temperature (SAT) are fundamental to climate change studies. A number of studies have developed several national and regional SAT series for China, but due to the diversity of meteorological observational sites, different quality control routines for data and the inconsistency of statistical methods used, they differ in long-term trends. This paper assesses the similarities and differences of the existing time series of the annual average SAT for China that are based upon historical meteorological observations since the 1900s. The results indicate that the China average is similar to the series for the Northern Hemisphere (NH) landmass, except that the initial warming of the NH series derived from the CRUTEM3/4 datasets ends earlier (before the early 1940s) than in China’s series. A major difference among the existing China average time series is the 1940s warmth, a period when there were very few observations across the country due to World War II. The SAT anomalies for China during the 1930s-1940s have been reduced by improved homogeneity assessment compared to previous estimates. The new improved time series is in better agreement with both the historical 20th century reanalysis data and the historical climate simulation of CMIP5 models. The new time series also shows the slowdown of the warming trend during the past 18 years (1998-2015). The best estimate of a linear trend for increases in temperature with a 95% uncertainty range is 0.121±0.009 °C per decade for 1900-2015, indicating that the improved homogeneity assessment for China leads to a slightly greater trend than that based on raw data (0.107±0.009 °C per decade)

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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

Middle East - North Africa and the millennium development goals : implications for German development cooperation

          Closed-loop controlled combustion is a promising technique to improve the overall performance of internal combustion engines and Diesel engines in particular. In order for this technique to be implemented some form of feedback from the combustion process is required. The feedback signal is processed and from it combustionrelated parameters are computed. These parameters are then fed to a control process which drives a series of outputs (e.g. injection timing in Diesel engines) to control their values. This paper’s focus lies on the processing and computation that is needed on the feedback signal before this is ready to be fed to the control process as well as on the electronics necessary to support it. A number of feedback alternatives are briefly discussed and for one of them, the in-cylinder pressure sensor, the CA50 (crank angle in which the integrated heat release curve reaches its 50% value) and the IMEP (Indicated Mean Effective Pressure) are identified as two potential control variables. The hardware architecture of a system capable of calculating both of them on-line is proposed and necessary feasibility size and speed considerations are made by implementing critical blocks in VHDL targeting a flash-based Actel ProASIC3 automotive-grade FPGA

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazonia Sustentavel, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.Keywords: Social–ecological systems, Tropical forests, Land use, Interdisciplinary research, Sustainability, Trade-off

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

The role of Cyclin D1 and Ki‐67 in the development and prognostication of thin melanoma

Background Despite their low individual metastatic potential, thin melanomas (≤ 1 mm Breslow thickness) contribute significantly to melanoma mortality overall. Therefore, identification of prognostic biomarkers is particularly important in this subgroup of melanoma. Prompted by pre‐clinical results, we investigated cyclin D1 protein and Ki‐67 expression in in situ, metastatic and non‐metastatic thin melanomas. Material and Methods Immunohistochemistry was performed on 112 melanoma specimens, thereof 22 in situ, 48 non‐metastatic and 42 metastatic thin melanomas. Overall, epidermal and dermal cyclin D1 and Ki‐67 expression were semi‐quantitatively evaluated by three independent investigators and compared between groups. Results Epidermal Ki‐67 expression did not differ statistically in in situ and invasive melanoma (P = 0.7). Epidermal cyclin D1 expression was significantly higher in thin invasive than in in situ melanoma (P = 0.003). No difference was found in cyclin D1 expression between metastatic and non‐metastatic invasive tumours. Metastatic and non‐metastatic thin melanomas did not show significant differences in epidermal expression of Ki‐67 and cyclin D1 (P = 0.148 and P = 0.611, respectively). In contrast, strong dermal expression of Ki‐67 was more frequent in metastatic than non‐metastatic samples (28.6 vs. 8.3%, respectively, P = 0.001). The prognostic value of dermal Ki‐67 expression was confirmed by multivariate analysis (P = 0.047). Conclusion We found an increased expression of cyclin D1 invasive thin melanomas compared to in situ melanomas which supports a potential role of this protein in early invasion in melanoma, as suggested by pre‐clinical findings. Moreover, our results confirm that high dermal Ki‐67 expression is associated with an increased risk of metastasis development in thin melanoma and could possibly serve as a prognostic biomarker in clinical practice, especially if combined with additional methods

Physical face cloning

We propose a complete process for designing, simulating, and fabricating synthetic skin for an animatronics character that mimics the face of a given subject and its expressions. The process starts with measuring the elastic properties of a material used to manufacture synthetic soft tissue. Given these measurements we use physicsbased simulation to predict the behavior of a face when it is driven by the underlying robotic actuation. Next, we capture 3D facial expressions for a given target subject. As the key component of our process, we present a novel optimization scheme that determines the shape of the synthetic skin as well as the actuation parameters that provide the best match to the target expressions. We demonstrate this computational skin design by physically cloning a real human face onto an animatronics figure. © 2012 ACM 0730-0301/2012/08-ART118