Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 μm and 300 μm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants

4000 years of human dietary evolution in central Germany, from the first farmers to the first elites

Investigation of human diet during the Neolithic has often been limited to a few archaeological cultures or single sites. In order to provide insight into the development of human food consumption and husbandry strategies, our study explores bone collagen carbon and nitrogen isotope data from 466 human and 105 faunal individuals from 26 sites in central Germany. It is the most extensive data set to date from an enclosed geographic microregion, covering 4,000 years of agricultural history from the Early Neolithic to the Early Bronze Age. The animal data show that a variety of pastures and dietary resources were explored, but that these changed remarkably little over time. In the human δ15N however we found a significant increase with time across the different archaeological cultures. This trend could be observed in all time periods and archaeological cultures (Bell Beaker phenomenon excluded), even on continuously populated sites. Since there was no such trend in faunal isotope values, we were able largely to exclude manuring as the cause of this effect. Based on the rich interdisciplinary data from this region and archaeological period we can argue that meat consumption increased with the increasing duration of farming subsistence. In δ13C, we could not observe any clear increasing or decreasing trends during the archaeological time periods, either for humans or for animals, which would have suggested significant changes in the environment and landscape use. We discovered sex-related dietary differences, with males of all archaeological periods having higher δ15N values than females, and an age-related increasing consumption of animal protein. An initial decrease of δ15N-values at the age of 1-2 years reveals partial weaning, while complete weaning took place at the age of 3-4 years

Development of an electronic frailty index for hospitalized older adults in Sweden

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Two Years with COVID-19 : The Electronic Frailty Index Identifies High-Risk Patients in the Stockholm GeroCovid Study

INTRODUCTION: Frailty, a measure of biological aging, has been linked to worse COVID-19 outcomes. However, as the mortality differs across the COVID-19 waves, it is less clear whether a medical record-based electronic frailty index (eFI) that we have previously developed for older adults could be used for risk stratification in hospitalized COVID-19 patients. OBJECTIVES: The aim of the study was to examine the association of frailty with mortality, readmission, and length of stay in older COVID-19 patients and to compare the predictive accuracy of the eFI to other frailty and comorbidity measures. METHODS: This was a retrospective cohort study using electronic health records (EHRs) from nine geriatric clinics in Stockholm, Sweden, comprising 3,980 COVID-19 patients (mean age 81.6 years) admitted between March 2020 and March 2022. Frailty was assessed using a 48-item eFI developed for Swedish geriatric patients, the Clinical Frailty Scale, and the Hospital Frailty Risk Score. Comorbidity was measured using the Charlson Comorbidity Index. We analyzed in-hospital mortality and 30-day readmission using logistic regression, 30-day and 6-month mortality using Cox regression, and the length of stay using linear regression. Predictive accuracy of the logistic regression and Cox models was evaluated by area under the receiver operating characteristic curve (AUC) and Harrell's C-statistic, respectively. RESULTS: Across the study period, the in-hospital mortality rate decreased from 13.9% in the first wave to 3.6% in the latest (Omicron) wave. Controlling for age and sex, a 10% increment in the eFI was significantly associated with higher risks of in-hospital mortality (odds ratio = 2.95; 95% confidence interval = 2.42-3.62), 30-day mortality (hazard ratio [HR] = 2.39; 2.08-2.74), 6-month mortality (HR = 2.29; 2.04-2.56), and a longer length of stay (β-coefficient = 2.00; 1.65-2.34) but not with 30-day readmission. The association between the eFI and in-hospital mortality remained robust across the waves, even after the vaccination rollout. Among all measures, the eFI had the best discrimination for in-hospital (AUC = 0.780), 30-day (Harrell's C = 0.733), and 6-month mortality (Harrell's C = 0.719). CONCLUSION: An eFI based on routinely collected EHRs can be applied in identifying high-risk older COVID-19 patients during the continuing pandemic.publishedVersionPeer reviewe

Rheological and flow birefringence studies of rod-shaped pigment nanoparticle dispersions

We study rheological and rheo-optical properties of suspensions of anisometric pigment particles in a non-polar fluid. Different rheological regimes from the dilute regime to an orientationally arrested gel state were characterized and compared with existing theoretical models. We demonstrate the intricate flow behaviour in a wide range of volume fractions. A unique combination of the optical properties of the particles results in a giant rheo-optical effect: an unprecedentedly large shear stress-induced birefringence was found in the isotropic range, exhibiting a sharp pre-transitional behaviour

Monitoring roots, nodule and pod development in vivo: New perspectives on legume development

Seed filling, root and nodule development are some of the key processes involved in abiotic stress resistance. However, these are complex processes hidden either by pod tissue (seed filling) or by soil (roots and nodules), so studying them quantitatively in-vivo is challenging. Non-invasive (3D) imaging techniques such as magnetic resonance imaging (MRI) can be used to investigate hidden structural development both above- and belowground. Co-registered positron emission tomography (PET) allows the acquisition of functional information by mapping of recent carbon investment of the plant and its dynamics e.g. in response to stress. For tasks not requiring spatial (volumetric) resolution, such as monitoring changes in pod water and dry-matter content, low field nuclear magnetic resonance relaxometry with portable devices (pNMR) can be applied. Such devices allow sensor-like applications in the greenhouse and the field. In the current contribution we will demonstrate the application of MRI to follow the development of root system architecture in soil grown pea and bean genotypes and monitor the progress of nodulation by repeated 3D mapping of nodule distribution. By correlating these maps with PET, monitoring carbon import, we get first insights into the functionality of nodules in the soil. Additionally we will demonstrate monitoring changes of bean pod water and dry-matter contents over the course of several weeks with pNMR. We discuss the potential and challenges of all three techniques (MRI, PET and pNMR) for application in legume research