Increased spatial resolution has been shown to be an important factor in enabling machine learning to map burn extent and severity with extremely high accuracy. Unfortunately, the acquisition of ...drone imagery is a labor-intensive endeavor, making the capture of drone imagery impractical for large catastrophic fires, which account for the majority of the area burned each year in the western US. To overcome this difficulty, satellites, such as PlanetScope, are now available which can produce imagery with remarkably high spatial resolution (approximately three meters). In addition to having higher spatial resolution, PlanetScope imagery contains up to eight bands in the visible and near-infrared spectra. This study examines the efficacy of each of the eight bands observed in PlanetScope imagery using a variety of feature selection methods, then uses these bands to map the burn extent and biomass consumption of three wildland fires. Several classifications are produced and compared based on the available bands, resulting in highly accurate maps with slight improvements as additional bands are utilized. The near-infrared band proved contribute most to increased mapping accuracy, while the green 1 and yellow bands contributed the least.
Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing ...of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.
Ischemic preconditioning is the phenomenon whereby brief periods of sublethal ischemia protect against a subsequent, more prolonged, ischemic insult. In remote ischemic preconditioning (RIPC), ...ischemia to one organ protects others organs at a distance. We created mouse models to ask if inhibition of the alpha-ketoglutarate (αKG)-dependent dioxygenase Egln1, which senses oxygen and regulates the hypoxia-inducible factor (HIF) transcription factor, could suffice to mediate local and remote ischemic preconditioning. Using somatic gene deletion and a pharmacological inhibitor, we found that inhibiting Egln1 systemically or in skeletal muscles protects mice against myocardial ischemia-reperfusion (I/R) injury. Parabiosis experiments confirmed that RIPC in this latter model was mediated by a secreted factor. Egln1 loss causes accumulation of circulating αKG, which drives hepatic production and secretion of kynurenic acid (KYNA) that is necessary and sufficient to mediate cardiac ischemic protection in this setting.
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•Inhibition of EGLN1 locally or at a distance protects the heart against I/R injury•Remote ischemic protection after EGLN1 loss is mediated by a humoral factor•Diversion of the EGLN1 co-substrate αKG stimulates hepatic kynurenic acid production
Cardiac protection from ischemia can be provided remotely by skeletal muscle inhibition of the oxygen sensor EGLN1, which leads to accumulation of its co-substrate α-ketoglutarate in the blood and increased liver production of the tryptophan metabolite kynurenic acid.
Traditional statistical models allow population based inferences and comparisons. Machine learning (ML) explores datasets to develop algorithms that do not assume linear relationships between ...variables and outcomes and that may account for higher order interactions to make individualized outcome predictions. To evaluate the performance of machine learning models compared to traditional risk stratification methods for the prediction of major adverse cardiovascular events (MACE) and bleeding in patients with acute coronary syndrome (ACS) that are treated with antithrombotic therapy. Data on 24,178 ACS patients were pooled from four randomized controlled trials. The super learner ensemble algorithm selected weights for 23 machine learning models and was compared to traditional models. The efficacy endpoint was a composite of cardiovascular death, myocardial infarction, or stroke. The safety endpoint was a composite of TIMI major and minor bleeding or bleeding requiring medical attention. For the MACE outcome, the super learner model produced a higher c-statistic (0.734) than logistic regression (0.714), the TIMI risk score (0.489), and a new cardiovascular risk score developed in the dataset (0.644). For the bleeding outcome, the super learner demonstrated a similar c-statistic as the logistic regression model (0.670 vs. 0.671). The machine learning risk estimates were highly calibrated with observed efficacy and bleeding outcomes (Hosmer–Lemeshow
p
value = 0.692 and 0.970, respectively). The super learner algorithm was highly calibrated on both efficacy and safety outcomes and produced the highest c-statistic for prediction of MACE compared to traditional risk stratification methods. This analysis demonstrates a contemporary application of machine learning to guide patient-level antithrombotic therapy treatment decisions.
Clinical Trial Registration
ATLAS ACS-2 TIMI 46:
https://clinicaltrials.gov/ct2/show/NCT00402597
. Unique Identifier: NCT00402597. ATLAS ACS-2 TIMI 51:
https://clinicaltrials.gov/ct2/show/NCT00809965
. Unique Identifier: NCT00809965. GEMINI ACS-1:
https://clinicaltrials.gov/ct2/show/NCT02293395
. Unique Identifier: NCT02293395. PIONEER-AF PCI:
https://clinicaltrials.gov/ct2/show/NCT01830543
. Unique Identifier: NCT01830543.
Here we review the current understanding of the genetic architecture of intracranial berry aneurysms (IBA) to aid in the genetic counseling of patients at risk for this condition. The familial ...subtype of IBA, familial intracranial aneurysms (FIA), is associated with increased frequency of IBA, increased risk of rupture, and increased morbidity and mortality after rupture. Family history is the strongest predictor for the development of IBA. However, a genetic test is not yet available to assess risk within a family. Studies using linkage analysis, genome-wide association, and next-generation sequencing have found several candidate loci and genes associated with disease onset, but have not conclusively implicated a single gene. In addition to family history, a separate or concurrent diagnosis of autosomal dominant polycystic kidney disease is a strong genetic risk factor for IBA formation. We also discuss the relative risk for developing IBA in several Mendelian syndromes including vascular Ehlers-Danlos syndrome, Marfan syndrome, Neurofibromatosis Type I, and Loeys–Dietz syndrome.
This article reports on the analysis of an online forum on the UK’s National Health Service website where participants debated the provision of homeopathy as publicly funded medical treatment. Using ...membership categorisation analysis, the article looks at how members negotiated a category distinction between homeopathy and ‘orthodox Western medicine’, focusing on the discursive resources that the participants drew on to position each other and the website itself in moral terms. This analysis contributes to our understanding of the institutionalisation of complementary and alternative medicine by demonstrating the strong polarisation of views that are present in the public domain, and the ways that public institutions become held accountable to ideologies of evidence and choice. In this way, the study adds to our growing knowledge about public engagement in pluralistic healthcare systems, showing further the limitations of the ‘rational choice’ assumptions that underlie pluralism.
Mutations in EZH2 Cause Weaver Syndrome Gibson, William T.; Hood, Rebecca L.; Zhan, Shing Hei ...
American journal of human genetics,
01/2012, Letnik:
90, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We used trio-based whole-exome sequencing to analyze two families affected by Weaver syndrome, including one of the original families reported in 1974. Filtering of rare variants in the affected ...probands against the parental variants identified two different de novo mutations in the enhancer of zeste homolog 2 (EZH2). Sanger sequencing of EZH2 in a third classically-affected proband identified a third de novo mutation in this gene. These data show that mutations in EZH2 cause Weaver syndrome.
Adipocytes undergo considerable volumetric expansion in the setting of obesity. It has been proposed that such marked increases in adipocyte size may be sensed via adipocyte-autonomous mechanisms to ...mediate size-dependent intracellular signalling. Here, we show that SWELL1 (LRRC8a), a member of the Leucine-Rich Repeat Containing protein family, is an essential component of a volume-sensitive ion channel (VRAC) in adipocytes. We find that SWELL1-mediated VRAC is augmented in hypertrophic murine and human adipocytes in the setting of obesity. SWELL1 regulates adipocyte insulin-PI3K-AKT2-GLUT4 signalling, glucose uptake and lipid content via SWELL1 C-terminal leucine-rich repeat domain interactions with GRB2/Cav1. Silencing GRB2 in SWELL1 KO adipocytes rescues insulin-pAKT2 signalling. In vivo, shRNA-mediated SWELL1 knockdown and adipose-targeted SWELL1 knockout reduce adiposity and adipocyte size in obese mice while impairing systemic glycaemia and insulin sensitivity. These studies identify SWELL1 as a cell-autonomous sensor of adipocyte size that regulates adipocyte growth, insulin sensitivity and glucose tolerance.
Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb ...repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research.
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