Imaging Informatics Division
Optimum concentration-response curve metrics for supervised selection of discriminative cellular phenotypic endpoints for chemical hazard assessment
High-content imaging (HCI) provides quantitative and information-rich measurements of chemical effects on human in vitro cell models. Identification of discriminative phenotypic endpoints from cellular features obtained from HCI is required for accurate assessments of potential chemical hazards.
ReadSupervised Segmentation of Un-annotated Retinal Fundus Images by Synthesis
We focus on the practical challenge of segmenting new retinal fundus images that are dissimilar to existing well-annotated datasets. It is addressed in this paper by a supervised learning pipeline, with its core being the construction of a synthetic fundus image dataset using the proposed R-sGAN technique.
ReadPredicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling
Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmaceutical companies as well as other industries and regulators. The goal of the current study was to develop an in vitro/in silico method for the rapid and accurate prediction of drug- and chemical-induced hepatocyte injury in humans.
ReadMachine-Learning Studies on Spin Models
With the recent developments in machine learning, Carrasquilla and Melko have proposed a paradigm that is complementary to the conventional approach for the study of spin models. As an alternative to investigating the thermal average of macroscopic physical quantities, they have used the spin configurations for the classification of the disordered and ordered phases of a phase transition through machine learning.
ReadAutomated grading of acne vulgaris by deep learning with convolutional neural networks
BACKGROUND: The visual assessment and severity grading of acne vulgaris by physicians can be subjective, resulting in inter- and intra-observer variability. OBJECTIVE: To develop and validate an algorithm for the automated calculation of the Investigator's Global Assessment (IGA) scale, to standardize acne severity and outcome measurements.
ReadPhosphatase POPX2 interferes with cell cycle by interacting with Chk1
Protein–protein interaction network analysis plays critical roles in predicting the functions of target proteins. In this study, we used a combination of SILAC-MS proteomics and bioinformatic approaches to identify Checkpoint Kinase 1 (Chk1) as a possible POPX2 phosphatase interacting protein.
ReadUtility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization
Use of high-throughput, in vitro bioactivity data in setting a point-of-departure (POD) has the potential to accelerate the pace of human health safety evaluation by informing screening level assessments. The primary objective of this work was to compare PODs based on high-throughput predictions of bioactivity, exposure predictions, and traditional hazard information for 448 chemicals.
ReadPI3K Catalytic Subunits α and β Modulate Cell Death and IL-6 Secretion Induced by Talc Particles in Human Lung Carcinoma Cells
Hydrated magnesium silicate (or "talc" particles) is a sclerosis agent commonly used in the management of malignant pleural effusions (MPE), a common symptom of metastatic diseases including lung cancers. However, the direct effects of talc particles to lung carcinoma cells, which can be found in the MPE fluids from lung cancer patients, are not fully understood.
Read