Ecosystem complexity on the Kerguelen Axis: the need for integrated ecosystem studies and sustained coordinated monitoring

第6回極域科学シンポジウム[OB] 極域生物圏11月16日（月）　統計数理研究所 セミナー室1（D305

Brain volume estimation from post-mortem newborn and fetal MRI

AbstractObjectiveMinimally invasive autopsy using post-mortem magnetic resonance imaging (MRI) is a valid alternative to conventional autopsy in fetuses and infants. Estimation of brain weight is an integral part of autopsy, but manual segmentation of organ volumes on MRI is labor intensive and prone to errors, therefore unsuitable for routine clinical practice. In this paper we aim to show that volumetric measurements of the post-mortem fetal and neonatal brain can be accurately estimated using semi-automatic techniques and a high correlation can be found with the weights measured from conventional autopsy results.MethodsThe brains of 17 newborn subjects, part of Magnetic Resonance Imaging Autopsy Study (MaRIAS), were segmented from post-mortem MR images into cerebrum, cerebellum and brainstem using a publicly available neonate brain atlas and semi-automatic segmentation algorithm. The results of the segmentation were averaged to create a new atlas, which was then used for the automated atlas-based segmentation of 17 MaRIAS fetus subjects. As validation, we manually segmented the MR images from 8 subjects of each cohort and compared them with the automatic ones. The semi-automatic estimation of cerebrum weight was compared with the results of the conventional autopsy.ResultsThe Dice overlaps between the manual and automatic segmentations are 0.991 and 0.992 for cerebrum, 0.873 and 0.888 for cerebellum and 0.819 and 0.815 for brainstem, for newborns and fetuses, respectively. Excellent agreement was obtained between the estimated MR weights and autopsy gold standard ones: mean absolute difference of 5 g and 2% maximum error for the fetus cohort and mean absolute difference of 20 g and 11% maximum error for the newborn one.ConclusionsThe high correlation between the obtained segmentation and autopsy weights strengthens the idea of using post-mortem MRI as an alternative for conventional autopsy of the brain

Optimisation of arterial spin labelling using bayesian experimental design

Large-scale neuroimaging studies often use multiple individual imaging contrasts. Due to the finite time available for imaging,there is intense competition for the time allocated to the individual modalities; thus it is crucial to maximise the utility of each method given the resources available. Arterial Spin Labelled (ASL) MRI often forms part of such studies. Measuring perfusion of oxygenated blood in the brain is valuable for several diseases,but quantification using multiple inversion time ASL is time-consuming due to poor SNR and consequently slow acquisitions. Here,we apply Bayesian principles of experimental design to clinical-length ASL acquisitions,resulting in significant improvements to perfusion estimation. Using simulations and experimental data,we validate this approach for a five-minute ASL scan. Our design procedure can be constrained to any chosen scan duration,making it well-suited to improve a variety of ASL implementations. The potential for adaptation to other modalities makes this an attractive method for optimising acquisition in the time-pressured environment of neuroimaging studies

ASL-incorporated pharmacokinetic modelling of PET data with reduced acquisition time: Application to amyloid imaging

Pharmacokinetic analysis of Positron Emission Tomography (PET) data typically requires at least one hour of image acquisition, which poses a great disadvantage in clinical practice. In this work, we propose a novel approach for pharmacokinetic modelling with significantly reduced PET acquisition time, by incorporating the blood flow information from simultaneously acquired arterial spin labelling (ASL) magnetic resonance imaging (MRI). A relationship is established between blood flow, measured by ASL, and the transfer rate constant from plasma to tissue of the PET tracer, leading to modified PET kinetic models with ASL-derived flow information. Evaluation on clinical amyloid imaging data from an Alzheimer’s disease (AD) study shows that the proposed approach with the simplified reference tissue model can achieve amyloid burden estimation from 30 min [18F]florbetapir PET data and 5 min simultaneous ASL MR data, which is comparable with the estimation from 60 min PET data (mean error=−0.03). Conversely, standardised uptake value ratio (SUVR), the alternative measure from the data showed a positive bias in areas of higher amyloid burden (mean error=0.07)

Standardized NEON organismal data for biodiversity research

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high-quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30&thinsp;years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators' workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks. &nbsp;</p

The Carnegie Hubble Program: The Infrared Leavitt Law in IC 1613

We have observed the dwarf galaxy IC 1613, at multiple epochs in the mid-infrared using Spitzer and contemporaneously in the near-infrared using the new FourStar near-infrared camera on Magellan. We have constructed Cepheid period–luminosity relations in the J, H, K_s, [3.6] and [4.5] bands and have used the run of their apparent distance moduli as a function of wavelength to derive the line-of-sight reddening and distance to IC 1613. Using a nine-band fit, we find E(B − V) = 0.05 ± 0.01 mag and an extinction-corrected distance modulus of μ_0 = 24.29 ± 0.03_(statistical) ± 0.03_(systematic) mag. By comparing our multi-band and [3.6] distance moduli to results from the tip of the red giant branch and red clump distance indicators, we find that metallicity has no measurable effect on Cepheid distances at 3.6 μm in the metallicity range −1.0 ≤ [Fe/H] ≤ 0.2, hence derivations of the Hubble constant at this wavelength require no correction for metallicity

Climate change impacts on polar marine ecosystems: Toward robust approaches for managing risks and uncertainties

The Polar Regions chapter of the Intergovernmental Panel on Climate Change's Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) provides a comprehensive assessment of climate change impacts on polar marine ecosystems and associated consequences for humans. It also includes identification of confidence for major findings based on agreement across studies and weight of evidence. Sources of uncertainty, from the extent of available datasets, to resolution of projection models, to the complexity and understanding of underlying social-ecological linkages and dynamics, can influence confidence. Here we, marine ecosystem scientists all having experience as lead authors of IPCC reports, examine the evolution of confidence in observed and projected climate-linked changes in polar ecosystems since SROCC. Further synthesis of literature on polar marine ecosystems has been undertaken, especially within IPCC's Sixth Assessment Report (AR6) Working Group II; for the Southern Ocean also the Marine Ecosystem Assessment for the Southern Ocean (MEASO). These publications incorporate new scientific findings that address some of the knowledge gaps identified in SROCC. While knowledge gaps have been narrowed, we still find that polar region assessments reflect pronounced geographical skewness in knowledge regarding the responses of marine life to changing climate and associated literature. There is also an imbalance in scientific focus; especially research in Antarctica is dominated by physical oceanography and cryosphere science with highly fragmented approaches and only short-term funding to ecology. There are clear indications that the scientific community has made substantial progress in its ability to project ecosystem responses to future climate change through the development of coupled biophysical models of the region facilitated by increased computer power allowing for improved resolution in space and time. Lastly, we point forward—providing recommendations for future advances for IPCC assessments.publishedVersio