Latent Patient Network Learning for Automatic Diagnosis

Recently, Graph Convolutional Networks (GCNs) has proven to be a powerful machine learning tool for Computer Aided Diagnosis (CADx) and disease prediction. A key component in these models is to build a population graph, where the graph adjacency matrix represents pair-wise patient similarities. Until now, the similarity metrics have been defined manually, usually based on meta-features like demographics or clinical scores. The definition of the metric, however, needs careful tuning, as GCNs are very sensitive to the graph structure. In this paper, we demonstrate for the first time in the CADx domain that it is possible to learn a single, optimal graph towards the GCN's downstream task of disease classification. To this end, we propose a novel, end-to-end trainable graph learning architecture for dynamic and localized graph pruning. Unlike commonly employed spectral GCN approaches, our GCN is spatial and inductive, and can thus infer previously unseen patients as well. We demonstrate significant classification improvements with our learned graph on two CADx problems in medicine. We further explain and visualize this result using an artificial dataset, underlining the importance of graph learning for more accurate and robust inference with GCNs in medical applications

Estrogenic Plant Extracts Reverse Weight Gain and Fat Accumulation without Causing Mammary Gland or Uterine Proliferation

Long-term estrogen deficiency increases the risk of obesity, diabetes and metabolic syndrome in postmenopausal women. Menopausal hormone therapy containing estrogens might prevent these conditions, but its prolonged use increases the risk of breast cancer, as wells as endometrial cancer if used without progestins. Animal studies indicate that beneficial effects of estrogens in adipose tissue and adverse effects on mammary gland and uterus are mediated by estrogen receptor alpha (ERα). One strategy to improve the safety of estrogens to prevent/treat obesity, diabetes and metabolic syndrome is to develop estrogens that act as agonists in adipose tissue, but not in mammary gland and uterus. We considered plant extracts, which have been the source of many pharmaceuticals, as a source of tissue selective estrogens. Extracts from two plants, Glycyrrhiza uralensis (RG) and Pueraria montana var. lobata (RP) bound to ERα, activated ERα responsive reporters, and reversed weight gain and fat accumulation comparable to estradiol in ovariectomized obese mice maintained on a high fat diet. Unlike estradiol, RG and RP did not induce proliferative effects on mammary gland and uterus. Gene expression profiling demonstrated that RG and RP induced estradiol-like regulation of genes in abdominal fat, but not in mammary gland and uterus. The compounds in extracts from RG and RP might constitute a new class of tissue selective estrogens to reverse weight gain, fat accumulation and metabolic syndrome in postmenopausal women

Doxorubicin-induced chronic dilated cardiomyopathy—the apoptosis hypothesis revisited

The chemotherapeutic agent doxorubicin (DOX) has significantly increased survival rates of pediatric and adult cancer patients. However, 10% of pediatric cancer survivors will 10–20 years later develop severe dilated cardiomyopathy (DCM), whereby the exact molecular mechanisms of disease progression after this long latency time remain puzzling. We here revisit the hypothesis that elevated apoptosis signaling or its increased likelihood after DOX exposure can lead to an impairment of cardiac function and cause a cardiac dilation. Based on recent literature evidence, we first argue why a dilated phenotype can occur when little apoptosis is detected. We then review findings suggesting that mature cardiomyocytes are protected against DOX-induced apoptosis downstream, but not upstream of mitochondrial outer membrane permeabilisation (MOMP). This lack of MOMP induction is proposed to alter the metabolic phenotype, induce hypertrophic remodeling, and lead to functional cardiac impairment even in the absence of cardiomyocyte apoptosis. We discuss findings that DOX exposure can lead to increased sensitivity to further cardiomyocyte apoptosis, which may cause a gradual loss in cardiomyocytes over time and a compensatory hypertrophic remodeling after treatment, potentially explaining the long lag time in disease onset. We finally note similarities between DOX-exposed cardiomyocytes and apoptosis-primed cancer cells and propose computational system biology as a tool to predict patient individual DOX doses. In conclusion, combining recent findings in rodent hearts and cardiomyocytes exposed to DOX with insights from apoptosis signal transduction allowed us to obtain a molecularly deeper insight in this delayed and still enigmatic pathology of DC

Impact of volatile phenols and their precursors on wine quality and control measures of Brettanomyces/Dekkera yeasts

Volatile phenols are aromatic compounds and one of the key molecules responsible for olfactory defects in wine. The yeast genus Brettanomyces is the only major microorganism that has the ability to covert hydroxycinnamic acids into important levels of these compounds, especially 4-ethylphenol and 4-ethylguaiacol, in red wine. When 4-ethylphenols reach concentrations greater than the sensory threshold, all wine’s organoleptic characteristics might be influenced or damaged. The aim of this literature review is to provide a better understanding of the physicochemical, biochemical, and metabolic factors that are related to the levels of p-coumaric acid and volatile phenols in wine. Then, this work summarizes the different methods used for controlling the presence of Brettanomyces in wine and the production of ethylphenols