5 research outputs found
Preeclampsia history and postpartum risk of cerebrovascular disease and cognitive impairment: Potential mechanisms
Hypertensive disorders of pregnancy such as preeclampsia, eclampsia, superimposed preeclampsia, and gestational hypertension are major causes of fetal and maternal morbidity and mortality. Women with a history of hypertensive pregnancy disorders have increased risk of stroke and cognitive impairments later in life. Moreover, women with a history of preeclampsia have increased risk of mortality from diseases including stroke, Alzheimerâs disease, and cardiovascular disease. The underlying pathophysiological mechanisms are currently not fully known. Here, we present clinical, epidemiological, and preclinical studies focused on evaluating the long-term cerebrovascular and cognitive dysfunction that affect women with a history of hypertensive pregnancy disorders and discuss potential underlying pathophysiological mechanisms
Recommended from our members
Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy
Conventional methods for intraoperative histopathologic diagnosis are labor- and time-intensive and may delay decision-making during brain tumor surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain tumor infiltration in fresh, unprocessed human tissues. Previously, the execution of SRS microscopy in a clinical setting has not been possible. We report the first demonstration of SRS microscopy in an operating room using a portable fiber-laser-based microscope in unprocessed specimens from 101 neurosurgical patients. Additionally, we introduce an image-processing method, stimulated Raman histology (SRH), which leverages SRS images to create virtual hematoxylin and eosin- stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, the concordance of SRH and conventional histology for predicting diagnosis was nearly perfect (Îș>0.89) and accuracy exceeded 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain tumor subtype with 90% accuracy. This study provides insight into how SRH can now be used to improve the surgical care of brain tumor patients.Chemistry and Chemical Biolog
TRY plant trait database â enhanced coverage and open access
Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of traitâbased plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
TRY plant trait database - enhanced coverage and open access
10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18