A Deep Learning Approach for Accurate Discrimination Between Optic Disc Drusen and Papilledema on Fundus Photographs.

BACKGROUND: Optic disc drusen (ODD) represent an important differential diagnosis of papilledema caused by intracranial hypertension, but their distinction may be difficult in clinical practice. The aim of this study was to train, validate, and test a dedicated deep learning system (DLS) for binary classification of ODD vs papilledema (including various subgroups within each category), on conventional mydriatic digital ocular fundus photographs collected in a large international multiethnic population. METHODS: This retrospective study included 4,508 color fundus images in 2,180 patients from 30 neuro-ophthalmology centers (19 countries) participating in the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI) Group. For training and internal validation, we used 857 ODD images and 3,230 papilledema images, in 1,959 patients. External testing was performed on an independent data set (221 patients), including 207 images with ODD (96 visible and 111 buried), provided by 3 centers of the Optic Disc Drusen Studies Consortium, and 214 images of papilledema (92 mild-to-moderate and 122 severe) from a previously validated study. RESULTS: The DLS could accurately distinguish between all ODD and papilledema (all severities included): area under the receiver operating characteristic curve (AUC) 0.97 (95% confidence interval [CI], 0.96-0.98), accuracy 90.5% (95% CI, 88.0%-92.9%), sensitivity 86.0% (95% CI, 82.1%-90.1%), and specificity 94.9% (95% CI, 92.3%-97.6%). The performance of the DLS remained high for discrimination of buried ODD from mild-to-moderate papilledema: AUC 0.93 (95% CI, 0.90-0.96), accuracy 84.2% (95% CI, 80.2%-88.6%), sensitivity 78.4% (95% CI, 72.2%-84.7%), and specificity 91.3% (95% CI, 87.0%-96.4%). CONCLUSIONS: A dedicated DLS can accurately distinguish between ODD and papilledema caused by intracranial hypertension, even when considering buried ODD vs mild-to-moderate papilledema.

Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification.

Robust prognostic gene signatures and therapeutic targets are difficult to derive from expression profiling because of the significant heterogeneity within breast cancer (BC) subtypes. Here, we performed forward genetic screening in mice using Sleeping Beauty transposon mutagenesis to identify candidate BC driver genes in an unbiased manner, using a stabilized N-terminal truncated ß-catenin gene as a sensitizer. We identified 134 mouse susceptibility genes from 129 common insertion sites within 34 mammary tumors. Of these, 126 genes were orthologous to protein-coding genes in the human genome (hereafter, human BC susceptibility genes, hBCSGs), 70% of which are previously reported cancer-associated genes, and ∼16% are known BC suppressor genes. Network analysis revealed a gene hub consisting of E1A binding protein P300 (EP300), CD44 molecule (CD44), neurofibromin (NF1) and phosphatase and tensin homolog (PTEN), which are linked to a significant number of mutated hBCSGs. From our survival prediction analysis of the expression of human BC genes in 2,333 BC cases, we isolated a six-gene-pair classifier that stratifies BC patients with high confidence into prognostically distinct low-, moderate-, and high-risk subgroups. Furthermore, we proposed prognostic classifiers identifying three basal and three claudin-low tumor subgroups. Intriguingly, our hBCSGs are mostly unrelated to cell cycle/mitosis genes and are distinct from the prognostic signatures currently used for stratifying BC patients. Our findings illustrate the strength and validity of integrating functional mutagenesis screens in mice with human cancer transcriptomic data to identify highly prognostic BC subtyping biomarkers.

Through the eyes into the brain, using artificial intelligence

INTRODUCTION@#Detection of neurological conditions is of high importance in the current context of increasingly ageing populations. Imaging of the retina and the optic nerve head represents a unique opportunity to detect brain diseases, but requires specific human expertise. We review the current outcomes of artificial intelligence (AI) methods applied to retinal imaging for the detection of neurological and neuro-ophthalmic conditions.@*METHOD@#Current and emerging concepts related to the detection of neurological conditions, using AI-based investigations of the retina in patients with brain disease were examined and summarised.@*RESULTS@#Papilloedema due to intracranial hypertension can be accurately identified with deep learning on standard retinal imaging at a human expert level. Emerging studies suggest that patients with Alzheimer's disease can be discriminated from cognitively normal individuals, using AI applied to retinal images.@*CONCLUSION@#Recent AI-based systems dedicated to scalable retinal imaging have opened new perspectives for the detection of brain conditions directly or indirectly affecting retinal structures. However, further validation and implementation studies are required to better understand their potential value in clinical practice.

Allelopathic effects of volatile organic compounds from Eucalyptus grandis rhizosphere soil on Eisenia fetida assessed using avoidance bioassays, enzyme activity, and comet assays.

Allelopathy has been identified as an underlying mechanism of detrimental environmental impacts within commercial plantations. Eucalyptus spp. are known to generate huge amounts of volatile organic compounds (VOCs) that can function as phytotoxins and thus inhibit other plants. In the present study, biochemical markers, including activities of acetylcholinesterase (AChE) and oxidative stress enzymes, such as superoxide dismutase (SOD) and glutathione S-transferase (GST), were assayed to assess changes in Eisenia fetida at the physiological level induced by different doses of VOCs as part of an acute toxicity test over 7 and 14-day exposures. In addition, the toxicities of VOCs were investigated using a soil avoidance test and comet assay. The results revealed that E. fetida exhibited significant avoidance behavior towards the highest concentrations of undecane, decane, 2,4-dimethyl heptane, and 2,2,4,6,6-pentametyl heptane. The tail DNA percentages were significantly increased for all experimental treatments relative to control. However, under the treatments of VOCs, Olive tail moment content and comet tail length also display an obvious increase compared to control, except for that of octane, undecane and decane treatments. As VOC concentrations and durations increased in the soil, activities of AChE, SOD, and GST were either stimulated or inhibited. Among the VOCs, decane, 2,4-dimethyl heptane, 2,2,4,6,6-pentamethyl heptane, and 2,4-di tert buyl phenol exerted stronger effects on enzymatic activities. In summary, VOCs in rhizosphere soils of E. grandis might exert a toxic impact on E. fetida, among which 2,4-dimethyl heptane, 2,2,4,6,6-pentamethyl heptane, and 2,4-di tert buyl phenol have the strongest effects.

Research progress of trimethylamine-N-oxide in the pathogenesis of atherosclerosis / 中南大学学报(医学版)

Trimethylamine-N-oxide (TMAO),metabolites of the intestinal microflora,is a newly discovered risk factor for cardiovascular disease.The intestinal flora converted choline and L-carnitine into trimethylamine in the food.Trimethylamine is oxidized to TMAO in liver enzymes.Lowering TMA can stimulate macrophages to reverse cholesterol transport and inhibit atherogenesis.TMAO poietin-monooxygenase 3 (FMO3) is a tool for cholesterol metabolism and reverse cholesterol transpor,lowering FMO3 can slow the gallbladder's secretion of bile,delay intestinal absorption of cholesterol,and limit the synthesis of oxidized cholesterol and cholesterol esters.TMAO in the blood can up regulate scavenger receptors in macrophages,and promote accumulation of cholesterol and formation of foam cells in macrophages,thereby promoting vascular plaque formation and promote the inflammatory response by MAPK and nuclear factor kappa B pathway.TMAO concentrates on affecting cholesterol metabolism,increasing insulin resistance,promoting platelet aggregation,increasing thrombosis,promoting vascular inflammatory response and directly leading to the formation of atherosclerotic plaques.Lowering TMAO levels can potentially prevent or treat atherosclerotic related diseases and reduce the incidence of cardiovascular and cerebrovascular diseases.The intestinal flora of the TMA/FMO3/TMAO pathway is the major pathway regulating lipid metabolism and inflammation.