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"Davis, Frank"
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Dysfunctional Wound Healing in Diabetic Foot Ulcers: New Crossroads
Purpose of ReviewDiabetic foot ulcerations (DFU) affect 25% of patients with diabetes mellitus during their lifetime and constitute a major health problem as they are often recalcitrant to healing due to a constellation of both intrinsic and extrinsic factors. The purpose of this review is to (1) detail the current mechanistic understanding of DFU formation and (2) highlight future therapeutic targets.Recent FindingsFrom a molecular perspective, DFUs exhibit a chronic inflammatory predisposition. In addition, increased local hypoxic conditions and impaired cellular responses to hypoxia are pathogenic factors that contribute to delayed wound healing. Finally, recent evidence suggests a role for epigenetic alterations, including microRNAs, in delayed DFU healing due to the complex interplay between genes and the environment.SummaryIn this regard, notable progress has been made in the molecular and genetic understanding of DFU formation. However, further studies are needed to translate preclinical investigations into clinical therapies.
Journal Article
Tree mortality predicted from drought-induced vascular damage
Forests may be vulnerable to future droughts. A tree mortality threshold based on plant hydraulics suggests that increased drought may trigger widespread dieback in the southwestern United States by mid-century.
The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality
1
,
2
,
3
. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality
4
,
5
. Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in
Populus tremuloides
in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.
Journal Article
X-men reload. Vol. 1, The end of history
\"The team is reborn with a proactive new mission, new alliances are formed and old friendships are rekindled - but the X-Men's world remains as deadly as ever!\"--Page 4 of cover.
BOOK
A Convolutional Neural Network Classifier Identifies Tree Species in Mixed-Conifer Forest from Hyperspectral Imagery
In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN). We tested our methods by identifying seven dominant trees species as well as dead standing trees in a mixed-conifer forest in the Southern Sierra Nevada Mountains, CA (USA) using training, validation, and testing datasets composed of spatially-explicit transects and plots sampled across a single strip of imaging spectroscopy. We also used a three-band ‘Red-Green-Blue’ pseudo true-color subset of the hyperspectral imagery strip to test the classification accuracy of a CNN model without the additional non-visible spectral data provided in the hyperspectral imagery. Our classifier is pixel-based rather than object based, although we use three-dimensional structural information from airborne Light Detection and Ranging (LiDAR) to identify trees (points > 5 m above the ground) and the classifier was applied to image pixels that were thus identified as tree crowns. By training a CNN classifier using field data and hyperspectral imagery, we were able to accurately identify tree species and predict their distribution, as well as the distribution of tree mortality, across the landscape. Using a window size of 15 pixels and eight hidden convolutional layers, a CNN model classified the correct species of 713 individual trees from hyperspectral imagery with an average F-score of 0.87 and F-scores ranging from 0.67–0.95 depending on species. The CNN classification model performance increased from a combined F-score of 0.64 for the Red-Green-Blue model to a combined F-score of 0.87 for the hyperspectral model. The hyperspectral CNN model captures the species composition changes across ~700 meters (1935 to 2630 m) of elevation from a lower-elevation mixed oak conifer forest to a higher-elevation fir-dominated coniferous forest. High resolution tree species maps can support forest ecosystem monitoring and management, and identifying dead trees aids landscape assessment of forest mortality resulting from drought, insects and pathogens. We publicly provide our code to apply deep learning classifiers to tree species identification from geospatial imagery and field training data.
Journal Article
Animation
With an introduction by John Lasseter-- and very little else in the way of words-- this second book in The Artist Series lavishly showcases the most brilliant animation created by such luminaries as Ub Iwerks, Norm Ferguson, Ben Sharpsteen, Hamilton Luske, Dick Huemer, Grim Natwick, Art Babbitt, Fred Moore, Bill Tytla, Frank Thomas, Ollie Johnston, Milt Kahl, Marc Davis, John Lounsbery, Ward Kimball, Eric Larson, Les Clark, Wolfgang Reitherman, John Sibley, Bill Justice, Clyde Geronimi, Ted Berman, Glen Keane, Andreas Deja, Eric Goldberg, Mark Henn and Tony Bancroft. The artwork-- much of which has never before been published-- offers the opportunity to marvel at the those magical lines of pencil that brought life to so many unforgettable Disney characters. Animation represents a rare opportunity to enjoy a glimpse into the truly spectacular trove of treasures from the Walt Disney Animation Research Library.
Book
Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems
The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: ( 1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or a t least two or more bands a t 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.
Journal Article
Coronavirus induces diabetic macrophage-mediated inflammation via SETDB2
COVID-19 induces a robust, extended inflammatory “cytokine storm” that contributes to an increased morbidity and mortality, particularly in patients with type 2 diabetes (T2D). Macrophages are a key innate immune cell population responsible for the cytokine storm that has been shown, in T2D, to promote excess inflammation in response to infection. Using peripheral monocytes and sera from human patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and a murine hepatitis coronavirus (MHV-A59) (an established murine model of SARS), we identified that coronavirus induces an increased Mφ-mediated inflammatory response due to a coronavirus-induced decrease in the histone methyltransferase, SETDB2. This decrease in SETDB2 upon coronavirus infection results in a decrease of the repressive trimethylation of histone 3 lysine 9 (H3K9me3) at NFkB binding sites on inflammatory gene promoters, effectively increasing inflammation. Mφs isolated from mice with a myeloid-specific deletion of SETDB2 displayed increased pathologic inflammation following coronavirus infection. Further, IFNβ directly regulates SETDB2 in Mφs via JaK1/STAT3 signaling, as blockade of this pathway altered SETDB2 and the inflammatory response to coronavirus infection. Importantly, we also found that loss of SETDB2 mediates an increased inflammatory response in diabetic Mϕs in response to coronavirus infection. Treatment of coronavirus-infected diabeticMφs with IFNβ reversed the inflammatory cytokine production via up-regulation of SETDB2/H3K9me3 on inflammatory gene promoters. Together, these results describe a potential mechanism for the increased Mφ-mediated cytokine storm in patients with T2D in response to COVID-19 and suggest that therapeutic targeting of the IFNβ/SETDB2 axis in T2D patients may decrease pathologic inflammation associated with COVID-19.
Journal Article
Macrophage-specific inhibition of the histone demethylase JMJD3 decreases STING and pathologic inflammation in diabetic wound repair
Macrophage plasticity is critical for normal tissue repair following injury. In pathologic states such as diabetes, macrophage plasticity is impaired, and macrophages remain in a persistent proinflammatory state; however, the reasons for this are unknown. Here, using single-cell RNA sequencing of human diabetic wounds, we identified increased JMJD3 in diabetic wound macrophages, resulting in increased inflammatory gene expression. Mechanistically, we report that in wound healing, JMJD3 directs early macrophage-mediated inflammation via JAK1,3/STAT3 signaling. However, in the diabetic state, we found that IL-6, a cytokine increased in diabetic wound tissue at later time points post-injury, regulates JMJD3 expression in diabetic wound macrophages via the JAK1,3/STAT3 pathway and that this late increase in JMJD3 induces NFκB-mediated inflammatory gene transcription in wound macrophages via an H3K27me3 mechanism. Interestingly, RNA sequencing of wound macrophages isolated from mice with JMJD3-deficient myeloid cells (Jmjd3f/fLyz2Cre+) identified that the STING gene (Tmem173) is regulated by JMJD3 in wound macrophages. STING limits inflammatory cytokine production by wound macrophages during healing. However, in diabetic mice, its role changes to limit wound repair and enhance inflammation. This finding is important since STING is associated with chronic inflammation, and we found STING to be elevated in human and murine diabetic wound macrophages at late time points. Finally, we demonstrate that macrophage-specific, nanoparticle inhibition of JMJD3 in diabetic wounds significantly improves diabetic wound repair by decreasing inflammatory cytokines and STING. Taken together, this work highlights the central role of JMJD3 in tissue repair and identifies cell-specific targeting as a viable therapeutic strategy for nonhealing diabetic wounds.
Journal Article