71 research outputs found
Targeting Potential Drivers of COVID-19: Neutrophil Extracellular Traps
Coronavirus disease 2019 (COVID-19) is a novel, viral-induced respiratory disease that in ∼10-15% of patients progresses to acute respiratory distress syndrome (ARDS) triggered by a cytokine storm. In this Perspective, autopsy results and literature are presented supporting the hypothesis that a little known yet powerful function of neutrophils-the ability to form neutrophil extracellular traps (NETs)-may contribute to organ damage and mortality in COVID-19. We show lung infiltration of neutrophils in an autopsy specimen from a patient who succumbed to COVID-19. We discuss prior reports linking aberrant NET formation to pulmonary diseases, thrombosis, mucous secretions in the airways, and cytokine production. If our hypothesis is correct, targeting NETs directly and/or indirectly with existing drugs may reduce the clinical severity of COVID-19
Recent Advances in Understanding Particle Acceleration Processes in Solar Flares
We review basic theoretical concepts in particle acceleration, with
particular emphasis on processes likely to occur in regions of magnetic
reconnection. Several new developments are discussed, including detailed
studies of reconnection in three-dimensional magnetic field configurations
(e.g., current sheets, collapsing traps, separatrix regions) and stochastic
acceleration in a turbulent environment. Fluid, test-particle, and
particle-in-cell approaches are used and results compared. While these studies
show considerable promise in accounting for the various observational
manifestations of solar flares, they are limited by a number of factors, mostly
relating to available computational power. Not the least of these issues is the
need to explicitly incorporate the electrodynamic feedback of the accelerated
particles themselves on the environment in which they are accelerated. A brief
prognosis for future advancement is offered.Comment: This is a chapter in a monograph on the physics of solar flares,
inspired by RHESSI observations. The individual articles are to appear in
Space Science Reviews (2011
Physics of Solar Prominences: I - Spectral Diagnostics and Non-LTE Modelling
This review paper outlines background information and covers recent advances
made via the analysis of spectra and images of prominence plasma and the
increased sophistication of non-LTE (ie when there is a departure from Local
Thermodynamic Equilibrium) radiative transfer models. We first describe the
spectral inversion techniques that have been used to infer the plasma
parameters important for the general properties of the prominence plasma in
both its cool core and the hotter prominence-corona transition region. We also
review studies devoted to the observation of bulk motions of the prominence
plasma and to the determination of prominence mass. However, a simple inversion
of spectroscopic data usually fails when the lines become optically thick at
certain wavelengths. Therefore, complex non-LTE models become necessary. We
thus present the basics of non-LTE radiative transfer theory and the associated
multi-level radiative transfer problems. The main results of one- and
two-dimensional models of the prominences and their fine-structures are
presented. We then discuss the energy balance in various prominence models.
Finally, we outline the outstanding observational and theoretical questions,
and the directions for future progress in our understanding of solar
prominences.Comment: 96 pages, 37 figures, Space Science Reviews. Some figures may have a
better resolution in the published version. New version reflects minor
changes brought after proof editin
Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes
Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference
The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18
7 10 124 ) or temporal stage (p = 3.96
7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine
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