176 research outputs found

    Research Notes : United States : Linkage group 12

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    Weiss (1970a, b, c, d, e) described linkage groups 1 to 7 in soybean. Buzzell (1974, 1979) and Palmer (1977, 1984) have characterized further link-age group 1. Linkage group 8 was reported by Buzzell et al. (1977) and described further by Palmer and Kaul (1983), Sadanaga (1983) and Sadanaga and Grindeland (1984)

    Pathological regional blood flow in opiate-dependent patients during withdrawal: A HMPAO-SPECT study

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    The aims of the present study were to investigate regional cerebral blood flow (rCBF) in heroin-dependent patients during withdrawal and to assess the relation between these changes and duration of heroin consumption and withdrawal data. The rCBF was measured using brain SPECT with Tc-99m-HMPAO in 16 heroin-dependent patients during heroin withdrawal. Thirteen patients received levomethadone at the time of the SPECT scans. The images were analyzed both visually and quantitatively, a total of 21 hypoperfused brain regions were observed in 11 of the 16 patients. The temporal lobes were the most affected area, hypoperfusions of the right and left temporal lobe were observed in 5 and 5 patients, respectively. Three of the patients had a hypoperfusion of the right frontal lobe, 2 patients showed perfusion defects in the left frontal lobe, right parietal lobe and left parietal lobe. The results of the quantitative assessments of the rCBF were consistent with the results of the qualitative findings. The stepwise regression analysis showed a significant positive correlation (r = 0.54) between the dose of levomethadone at the time of the SPECT scan and the rCBF of the right parietal lobe. Other significant correlations between clinical data and rCBF were not found. The present results suggest brain perfusion abnormalities during heroin withdrawal in heroin-dependent patients, which are not due to the conditions of withdrawal

    A precision medicine initiative for Alzheimer's disease: the road ahead to biomarker-guided integrative disease modeling

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    After intense scientific exploration and more than a decade of failed trials, Alzheimer’s disease (AD) remains a fatal global epidemic. A traditional research and drug development paradigm continues to target heterogeneous late-stage clinically phenotyped patients with single 'magic bullet' drugs. Here, we propose that it is time for a paradigm shift towards the implementation of precision medicine (PM) for enhanced risk screening, detection, treatment, and prevention of AD. The overarching structure of how PM for AD can be achieved will be provided through the convergence of breakthrough technological advances, including big data science, systems biology, genomic sequencing, blood-based biomarkers, integrated disease modeling and P4 medicine. It is hypothesized that deconstructing AD into multiple genetic and biological subsets existing within this heterogeneous target population will provide an effective PM strategy for treating individual patients with the specific agent(s) that are likely to work best based on the specific individual biological make-up. The Alzheimer’s Precision Medicine Initiative (APMI) is an international collaboration of leading interdisciplinary clinicians and scientists devoted towards the implementation of PM in Neurology, Psychiatry and Neuroscience. It is hypothesized that successful realization of PM in AD and other neurodegenerative diseases will result in breakthrough therapies, such as in oncology, with optimized safety profiles, better responder rates and treatment responses, particularly through biomarker-guided early preclinical disease-stage clinical trials

    Biphasic activation of complement and fibrinolysis during the human nasal allergic response

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    Complement, coagulation and fibrinolysis contribute to the pathology of many respiratory diseases. Here we detail the biphasic activation of these pathways following nasal allergen challenge. Understanding these mechanisms may lead to therapeutic insight in common respiratory diseases

    Can we detect more ephemeral floods with higher density harmonized Landsat Sentinel 2 data compared to Landsat 8 alone?

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    Spatiotemporal quantification of surface water and flooding is essential given that floods are among the largest natural hazards. Effective disaster response management requires near real-time information on flood extent. Satellite remote sensing is the only way of monitoring these dynamics across vast areas and over time. Previous water and flood mapping efforts have relied on optical time series, despite cloud contamination. This reliance on optical data is due to the availability of systematically acquired and easily accessible optical data globally for over 40 years. Prior research used either MODIS or Landsat data, trading either high temporal density but lower spatial resolution or lower cadence but higher spatial resolution. Both MODIS and Landsat pose limitations as Landsat can miss ephemeral floods, whereas MODIS misses small floods and inaccurately delineates flood edges. Leveraging high temporal frequency of 3–4 days of the existing Landsat-8 (L8) and two Sentinel-2 (S2) satellites combined, in this research, we assessed whether the increased temporal frequency of the three sensors improves our ability to detect surface water and flooding extent compared to a single sensor (L8 alone). Our study area was Australia's Murray-Darling Basin, one of the world's largest dryland basins that experiences ephemeral floods. We applied machine learning to NASA's Harmonized Landsat Sentinel-2 (HLS) Surface Reflectance Product, which combines L8 and S2 observations, to map surface water and flooding dynamics. Our overall accuracy, estimated from a stratified random sample, was 99%. Our user's and producer's accuracy for the water class was 80% (±3.6%, standard error) and 76% (±5.8%). We focused on 2019, one of the most recent years when all three HLS sensors operated at full capacity. Our results show that water area (permanent and flooding) identified with the HLS was greater than that identified by L8, and some short-lived flooding events were detected only by the HLS. Comparison with high resolution (3 m) PlanetScope data identified extensive mixed pixels at the 30 m HLS resolution, highlighting the need for improved spatial resolution in future work. The HLS has been able to detect floods in cases when one sensor (L8) alone was not, despite 2019 being one of the driest years in the area, with few flooding events. The dense optical time-series offered by the HLS data is thus critical for capturing temporally dynamic phenomena (i.e., ephemeral floods in drylands), highlighting the importance of harmonized data such as the HLS

    Fit for social innovation? Policy reflections for EU energy and climate policy making

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    Achieving climate-neutrality by mid-century and its intermediary reduction targets for 2030, notably the EU’s greenhouse gas emissions reduction of 55% by 2030, requires an accelerated transformation of our systems of production and consumption. In essence, such transformations are socio-technical change processes that require a combination of technological and social innovation. While it is widely acknowledged that ambitious climate and energy policies are needed to accelerate such transition processes, research and practise have largely focused on their importance for spurring technological innovation. In this research perspective, we argue that energy and climate policy making should pay more attention to social innovation as much needed additional puzzle piece for successful decarbonisation. Such social innovation is diverse, ranging from renewable energy cooperatives, to participatory incubation and experimentation, and crowdfunding as well as local electricity exchange. Based on a literature review that informed an EU policy dialogue bringing together policy makers, practitioners and researchers and followed up by a workshop with city administrations, twelve practical action points were co-created on how to better consider social innovation in energy and climate policy making in the EU (and beyond). We thereby hope to stimulate a broader discourse on the dual need for social and technological innovation for reaching climate-neutrality

    Natural Variation in an ABC Transporter Gene Associated with Seed Size Evolution in Tomato Species

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    Seed size is a key determinant of evolutionary fitness in plants and is a trait that often undergoes tremendous changes during crop domestication. Seed size is most often quantitatively inherited, and it has been shown that Sw4.1 is one of the most significant quantitative trait loci (QTLs) underlying the evolution of seed size in the genus Solanum—especially in species related to the cultivated tomato. Using a combination of genetic, developmental, molecular, and transgenic techniques, we have pinpointed the cause of the Sw4.1 QTL to a gene encoding an ABC transporter gene. This gene exerts its control on seed size, not through the maternal plant, but rather via gene expression in the developing zygote. Phenotypic effects of allelic variation at Sw4.1 are manifested early in seed development at stages corresponding to the rapid deposition of starch and lipids into the endospermic cells. Through synteny, we have identified the Arabidopsis Sw4.1 ortholog. Mutagenesis has revealed that this ortholog is associated with seed length variation and fatty acid deposition in seeds, raising the possibility that the ABC transporter may modulate seed size variation in other species. Transcription studies show that the ABC transporter gene is expressed not only in seeds, but also in other tissues (leaves and roots) and, thus, may perform functions in parts of the plants other than developing seeds. Cloning and characterization of the Sw4.1 QTL gives new insight into how plants change seed during evolution and may open future opportunities for modulating seed size in crop plants for human purposes

    Bilateral effects of unilateral cerebellar lesions as detected by voxel based morphometry and diffusion imaging

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    Over the last decades, the importance of cerebellar processing for cortical functions has been acknowledged and consensus was reached on the strict functional and structural cortico-cerebellar interrelations. From an anatomical point of view strictly contralateral interconnections link the cerebellum to the cerebral cortex mainly through the middle and superior cerebellar peduncle. Diffusion MRI (dMRI) based tractography has already been applied to address cortico-cerebellar-cortical loops in healthy subjects and to detect diffusivity alteration patterns in patients with neurodegenerative pathologies of the cerebellum. In the present study we used dMRI-based tractography to determine the degree and pattern of pathological changes of cerebellar white matter microstructure in patients with focal cerebellar lesions. Diffusion imaging and high-resolution volumes were obtained in patients with left cerebellar lesions and in normal controls. Middle cerebellar peduncles and superior cerebellar peduncles were reconstructed by multi fiber diffusion tractography. From each tract, measures of microscopic damage were assessed, and despite the presence of unilateral lesions, bilateral diffusivity differences in white matter tracts were found comparing patients with normal controls. Consistently, bilateral alterations were also evidenced in specific brain regions linked to the cerebellum and involved in higher-level functions. This could be in line with the evidence that in the presence of unilateral cerebellar lesions, different cognitive functions can be affected and they are not strictly linked to the side of the cerebellar lesion

    Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic.

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    Biomarker discovery and development for clinical research, diagnostics and therapy monitoring in clinical trials have advanced rapidly in key areas of medicine - most notably, oncology and cardiovascular diseases - allowing rapid early detection and supporting the evolution of biomarker-guided, precision-medicine-based targeted therapies. In Alzheimer disease (AD), breakthroughs in biomarker identification and validation include cerebrospinal fluid and PET markers of amyloid-β and tau proteins, which are highly accurate in detecting the presence of AD-associated pathophysiological and neuropathological changes. However, the high cost, insufficient accessibility and/or invasiveness of these assays limit their use as viable first-line tools for detecting patterns of pathophysiology. Therefore, a multistage, tiered approach is needed, prioritizing development of an initial screen to exclude from these tests the high numbers of people with cognitive deficits who do not demonstrate evidence of underlying AD pathophysiology. This Review summarizes the efforts of an international working group that aimed to survey the current landscape of blood-based AD biomarkers and outlines operational steps for an effective academic-industry co-development pathway from identification and assay development to validation for clinical use.I recieved an honorarium from Roche Diagnostics for my participation in the advisory panel meeting leading to this pape

    Advances in the therapy of Alzheimer's disease: Targeting amyloid beta and tau and perspectives for the future

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    Worldwide multidisciplinary translational research has led to a growing knowledge of the genetics and molecular pathogenesis of Alzheimer's disease (AD) indicating that pathophysiological brain alterations occur decades before clinical signs and symptoms of cognitive decline can be diagnosed. Consequently, therapeutic concepts and targets have been increasingly focused on early-stage illness before the onset of dementia; and distinct classes of compounds are now being tested in clinical trials. At present, there is a growing consensus that therapeutic progress in AD delaying disease progression would significantly decrease the expanding global burden. The evolving hypothesis- and evidence-based generation of new diagnostic research criteria for early-stage AD has positively impacted the development of clinical trial designs and the characterization of earlier and more specific target populations for trials in prodromal as well as in pre- and asymptomatic at-risk stages of AD
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