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Recent advances in deep learning enable using chemical structures and phenotypic profiles to accurately predict assay results for compounds virtually, reducing the time and cost of screens in the drug discovery process. The relative strength of high-throughput data sources - chemical structures, images (Cell Painting), and gene expression profiles (L1000) - has been unknown. Here we compare their ability to predict the activity of compounds structurally different from those used in training, using a sparse dataset of 16,979 chemicals tested in 376 assays for a total of 542,648 readouts. Deep learning-based feature extraction from chemical structures provided a remarkable ability to predict assay activity for structures dissimilar to those used for training. Image-based profiling performed even better, but requires wet lab experimentation. It outperformed gene expression profiling, and at lower cost. Furthermore, the three profiling modalities are complementary, and together can predict a wide range of diverse bioactivity, including cell-based and biochemical assays. Our study shows that, for many assays, predicting compound activity from phenotypic profiles and chemical structures is an accurate and efficient way to identify potential treatments in the early stages of the drug discovery process.

We prove here that the height function associated to non-simple exclusion processes with arbitrary jump-length converges to the solution of the Kardar–Parisi–Zhang SPDE under suitable scaling and renormalization. This extends the work of Dembo and Tsai (Commun Math Phys 341(1):219–261, 2016) for arbitrary jump-length and Goncalves and Jara (Stoch Process Appl 127(12):4029–4052, 2017) for the non-stationary regime. Thus we answer a "Big Picture Question" from the AIM workshop on KPZ and also expand on the almost empty set of non-integrable and non-stationary particle systems for which weak KPZ universality is proven. We use an approximate microscopic Cole-Hopf transform like in Dembo and Tsai (2016) but we develop tools to analyze local statistics of the particle system via local equilibrium and work of Goncalves and Jara (2017). Local equilibrium is done via the one-block step in Guo et al. (Commun Math Phys 118:31, 1988) for path-space/dynamic statistics.

The purpose of this study was to explore the value of extraction of tumor features in contrast-enhanced ultrasonography (CEUS) images based on the deep belief networks (DBN) for the diagnosis of cervical cancer patients and realize the intelligent evaluation on effects of diagnosis and chemotherapy of the cervical cancer. An automatic extraction algorithm with the time-intensity curve (TIC) was proposed based on Sparse nonnegative matrix factorization (SNMF) in this study, and was applied to the framework of automatic analysis of cervical cancer tumors based on the deep belief networks, to assist doctors in the analysis of cervical cancer tumors. The framework was applied to the real clinical diagnostic data, and the feasibility of the method was verified by comparing the accuracy, sensitivity, and specificity. Later, the parameters of patients’ time to peak (TP), peak intensity (PI), mean transit time (MTT), and area under the curve (AUC) were obtained by drawing TICs, and the changes of p53 protein and ki-67 protein obtained by pathological section staining were analyzed to evaluate the therapeutic effect in the patients. It was found that the proposed model of tumor feature extraction based on the DBN had the higher accuracy (86.36%), sensitivity (83.33%), and specificity (87.50%). The related parameters of TIC curve obtained based on SNMF showed that there was a significant difference in p53 content between tissues with different degrees of disease (p

We have previously shown myofibroblasts subjacent to the squamous epithelium in the normal human esophagus and an increase in esophagitis. Myofibroblast contribution to bone morphogenetic protein (BMP) signaling and to paracrine mediated epithelial-mesenchymal interactions in the human esophagus remains incompletely defined. We investigated BMP4 and BMP inhibitor GREM1 gene expression and protein levels in previously characterized human esophageal myofibroblast primary cultures and in a human esophageal myofibroblast cell line. We adapted human esophageal myofibroblast conditioned media into a 3D organotypic model to investigate the effect of myofibroblast secreted factors on squamous epithelial morphology, proliferation, differentiation and BMP signaling. Human esophageal myofibroblasts constitutively secrete GREM1 and increase BMP4 expression and BMP4 secretion in response to epithelial Hedgehog ligand SHH. Detection of secreted BMP4 is decreased in the presence of GREM1. Myofibroblast conditioned media increases epithelial proliferation and expression of basal markers p63 and CK14 leading to an overall increase in epithelial thickness. Epithelial BMP signaling increases with myofibroblast conditioned media. These findings were partially reversed with GREM1 inhibition. Our results demonstrate that myofibroblasts are potential sources of GREM1 and of BMP4 in the human esophagus and that human esophageal myofibroblast-epithelial paracrine interactions contribute in part to the regulation of epithelial growth.

Background Adult mesenchymal stem cells (MSCs) hold great promise for regenerative medicine because of their self-renewal, multipotency, and trophic and immunosuppressive effects. Due to the rareness and high heterogeneity of freshly isolated MSCs, extensive in-vitro passage is required to expand their populations prior to clinical use; however, senescence usually accompanies and can potentially affect MSC characteristics and functionality. Therefore, a thorough characterization of the variations in phenotype and differentiation potential of in-vitro aging MSCs must be sought. Methods Human bone marrow-derived MSCs were passaged in vitro and cultivated with either DMEM-based or αMEM-based expansion media. Cells were prepared for subculture every 10 days up to passage 8 and were analyzed for cell morphology, proliferative capacity, and surface marker expression at the end of each passage. The gene expression profile and adipogenic and osteogenic differentiation capability of MSCs at early (passage 4) and late (passage 8) passages were also evaluated. Results In-vitro aging MSCs gradually lost the typical fibroblast-like spindle shape, leading to elevated morphological abnormality and inhomogeneity. While the DMEM-based expansion medium better facilitated MSC proliferation in the early passages, the cell population doubling rate reduced over time in both DMEM and αMEM groups. CD146 expression decreased with increasing passage number only when MSCs were cultured under the DMEM-based condition. Senescence also resulted in MSCs with genetic instability, which was further regulated by the medium recipe. Regardless of the expansion condition, MSCs at both passages 4 and 8 could differentiate into adipocyte-like cells whereas osteogenesis of aged MSCs was significantly compromised. For osteogenic induction, use of the αMEM-based expansion medium yielded longer osteogenesis and better quality. Conclusions Human MSCs subjected to extensive in-vitro passage can undergo morphological, phenotypic, and genetic changes. These properties are also modulated by the medium composition employed to expand the cell populations. In addition, adipogenic potential may be better preserved over osteogenesis in aged MSCs, suggesting that MSCs at early passages must be used for osteogenic differentiation. The current study presents valuable information for future basic science research and clinical applications leading to the development of novel MSC-based therapeutic strategies for different diseases. Electronic supplementary material The online version of this article (10.1186/s13287-018-0876-3) contains supplementary material, which is available to authorized users.

Mitochondrial ATP synthase catalyzes the coupling of oxidative phosphorylation. Under pathological conditions, ATP synthase hydrolyzes ATP to replenish protons from the matrix into the intermembrane space, sustaining mitochondrial membrane potential. ATPase inhibitory factor 1 (IF1) is a nuclear-encoded, ATP synthase-interacting protein that selectively inhibits the hydrolysis activity of ATP synthase, which may render the protective role of IF1 in ischemic hearts. However, the in vivo cardiac function of IF1 and the potential therapeutic application targeting IF1 remain obscure. In the present study, we uncovered that IF1 is upregulated in mouse hearts with pressure overload-induced hypertrophy and in human hearts with dilated cardiomyopathy. IF1 knockout (KO) mice were protected against cardiac dysfunction and pathological development induced by transverse aortic constriction (TAC) or isoproterenol infusion. The reduced ATP hydrolysis activated AMPK activity in IF1 KO hearts, which together facilitated autophagy. These results suggest that IF1 upregulation in the failing heart may be a maladaptive response. Inhibiting IF1 in the hypertrophied heart not only prevents cell death from excessive mitochondrial depolarization but also activates AMPK signaling and increases autophagy. Therefore, IF1 inhibition may serve as a potential therapeutic target in treating pathological cardiac hypertrophy and heart failure.