Reproducibility of proton density fat fraction assessment of thigh muscle in a multi-site, multi-vendor cohort study at 10 years after anterior cruciate ligament reconstruction.

Background: Dixon-based magnetic resonance imaging (MRI) intramuscular proton density fat fraction (PDFF) is a potentially useful imaging biomarker of muscle quality. However, multi-vendor, multi-site reproducibility of intramuscular PDFF quantification, required for large clinical studies, can be strongly dependent on acquisition and processing. The purpose of this study was (I) to develop a 6-point Dixon MRI-based acquisition and processing technique for reproducible multi-vendor, multi-site quantification of thigh intramuscular PDFF; and (II) to evaluate the ability of the technique to detect differences in thigh muscle status between operated .

Quantitative CTA vascular calcification, atherosclerosis burden, and stroke mechanism in patients with ischemic stroke.

Background: Vascular calcification is recognized as the advanced stage of atherosclerosis burden. We hypothesized that vascular calcium quantification in CT angiography (CTA) would be helpful to differentiate large artery atherosclerosis (LAA) from other stroke etiology in patients with ischemic stroke.

Methods: We studied 375 acute ischemic stroke patients (200 males, mean age 69.

Towards Automatic Cartilage Quantification in Clinical Trials - Continuing from the 2019 IWOAI Knee Segmentation Challenge.

Objective: To evaluate whether the deep learning (DL) segmentation methods from the six teams that participated in the IWOAI 2019 Knee Cartilage Segmentation Challenge are appropriate for quantifying cartilage loss in longitudinal clinical trials.

Design: We included 556 subjects from the Osteoarthritis Initiative study with manually read cartilage volume scores for the baseline and 1-year visits. The teams used their methods originally trained for the IWOAI 2019 challenge to segment the 1130 knee MRIs.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Our framework includes radiotherapy treatment data (i.e.

Multi-vendor multi-site quantitative MRI analysis of cartilage degeneration 10 Years after anterior cruciate ligament reconstruction: MOON-MRI protocol and preliminary results.

Objective: To describe the protocol of a multi-vendor, multi-site quantitative MRI study for knee post-traumatic osteoarthritis (PTOA), and to present preliminary results of cartilage degeneration using MR T and T imaging 10 years after anterior cruciate ligament reconstruction (ACLR).

Design: This study involves three sites and two MR platforms. The patients are from a nested cohort (termed as Onsite cohort) within the Multicenter Orthopaedic Outcomes Network (MOON) cohort 10 years after ACLR.

Automated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning.

Background: This study aimed to build a deep learning model to automatically segment heterogeneous clinical MRI scans by optimizing a pre-trained model built from a homogeneous research dataset with transfer learning.

Methods: Conditional generative adversarial networks pretrained on the Osteoarthritis Initiative MR images was transferred to 30 sets of heterogenous MR images collected from clinical routines. Two trained radiologists manually segmented the 30 sets of clinical MR images for model training, validation and test.

Automatic segmentation of gadolinium-enhancing lesions in multiple sclerosis using deep learning from clinical MRI.

Gadolinium-enhancing lesions reflect active disease and are critical for in-patient monitoring in multiple sclerosis (MS). In this work, we have developed the first fully automated method to segment and count the gadolinium-enhancing lesions from routine clinical MRI of MS patients. The proposed method first segments the potential lesions using 2D-UNet from multi-channel scans (T1 post-contrast, T1 pre-contrast, FLAIR, T2, and proton-density) and classifies the lesions using a random forest classifier.

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.

Purpose: To organize a multi-institute knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression.

Materials And Methods: A dataset partition consisting of three-dimensional knee MRI from 88 retrospective patients at two time points (baseline and 1-year follow-up) with ground truth articular (femoral, tibial, and patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated against ground truth segmentations using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a holdout test set.

Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks.

Purpose: Fully automatic tissue segmentation is an essential step to translate quantitative MRI techniques to clinical setting. The goal of this study was to develop a novel approach based on the generative adversarial networks for fully automatic segmentation of knee cartilage and meniscus.

Theory And Methods: Defining proper loss function for semantic segmentation to enforce the learning of multiscale spatial constraints in an end-to-end training process is an open problem.

The exposome concept in a human nutrigenomics study: evaluating the impact of exposure to a complex mixture of phytochemicals using transcriptomics signatures.

The application of transcriptome analyses in molecular epidemiology studies has become a promising tool in order to evaluate the impact of environmental exposures. These analyses have a great value in establishing the exposome, the totality of human exposures, both by identifying the chemical nature of the exposures and the induced molecular responses. Transcriptomic signatures can be regarded as biomarker of exposure as well as markers of effect which reflect the interaction between individual genetic background and exposure levels.

High-throughput data integration of RNA-miRNA-circRNA reveals novel insights into mechanisms of benzo[a]pyrene-induced carcinogenicity.

The chain of events leading from a toxic compound exposure to carcinogenicity is still barely understood. With the emergence of high-throughput sequencing, it is now possible to discover many different biological components simultaneously. Using two different RNA libraries, we sequenced the complete transcriptome of human HepG2 liver cells exposed to benzo[a]pyrene, a potent human carcinogen, across six time points.

Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro.

In order to improve attrition rates of candidate-drugs there is a need for a better understanding of the mechanisms underlying drug-induced hepatotoxicity. We aim to further unravel the toxicological response of hepatocytes to a prototypical cholestatic compound by integrating transcriptomic and metabonomic profiling of HepG2 cells exposed to Cyclosporin A. Cyclosporin A exposure induced intracellular cholesterol accumulation and diminished intracellular bile acid levels.

Epigenetic mechanisms underlying arsenic-associated lung carcinogenesis.

Arsenic is an established human carcinogen, but the mechanisms through which it contributes to for instance lung cancer development are still unclear. As arsenic is methylated during its metabolism, it may interfere with the DNA methylation process, and is therefore considered to be an epigenetic carcinogen. In the present study, we hypothesize that arsenic is able to induce DNA methylation changes, which lead to changes in specific gene expression, in pathways associated with lung cancer promotion and progression.

Evaluation of database-derived pathway development for enabling biomarker discovery for hepatotoxicity.

Current testing models for predicting drug-induced liver injury are inadequate, as they basically under-report human health risks. We present here an approach towards developing pathways based on hepatotoxicity-associated gene groups derived from two types of publicly accessible hepatotoxicity databases, in order to develop drug-induced liver injury biomarker profiles. One human liver 'omics-based and four text-mining-based databases were explored for hepatotoxicity-associated gene lists.

Can transcriptomics provide insight into the chemopreventive mechanisms of complex mixtures of phytochemicals in humans?

Blueberries contain relatively large amounts of different phytochemicals, which are suggested to have chemopreventive properties, but little information is available on the underlying molecular modes of action. This study investigates whole genome gene expression changes in lymphocytes of 143 humans after a 4-week blueberry-apple juice dietary intervention. Differentially expressed genes and genes correlating with the extent of antioxidant protection were identified in four subgroups.

User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform.

RNA-Seq provides new insights in the transcriptome responses induced by the carcinogen benzo[a]pyrene.

Whole-genome transcriptome measurements are pivotal for characterizing molecular mechanisms of chemicals and predicting toxic classes, such as genotoxicity and carcinogenicity, from in vitro and in vivo assays. In recent years, deep sequencing technologies have been developed that hold the promise of measuring the transcriptome in a more complete and unbiased manner than DNA microarrays. Here, we applied this RNA-seq technology for the characterization of the transcriptomic responses in HepG2 cells upon exposure to benzo[a]pyrene (BaP), a well-known DNA damaging human carcinogen.

GO-Elite: a flexible solution for pathway and ontology over-representation.

Unlabelled: We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g.

Benzo[a]pyrene-induced changes in microRNA-mRNA networks.

Toxicological studies assessing the safety of compounds for humans frequently use in vitro systems to characterize toxic responses in combination with transcriptomic analyses. Thus far, changes have mostly been investigated at the mRNA level. Recently, microRNAs have attracted attention because they are powerful negative regulators of mRNA levels and, thus, may be responsible for the modulation of important mRNA networks implicated in toxicity.

'Omics analysis of low dose acetaminophen intake demonstrates novel response pathways in humans.

Acetaminophen is the primary cause of acute liver toxicity in Europe/USA, which led the FDA to reconsider recommendations concerning safe acetaminophen dosage/use. Unfortunately, the current tests for liver toxicity are no ideal predictive markers for liver injury, i.e.

Efficacy of catheter ablation in patients with an electrical storm.

Background: Electrical storm (ES) is a life-threatening condition requiring prompt and effective therapy. This may be achieved by the use of catheter ablation.

Aim: To assess safety and efficacy of catheter ablation in patients with ES.

Effect of Trichostatin A on miRNA expression in cultures of primary rat hepatocytes.

In the present study, the effect of Trichostatin A (TSA), a histone deacetylase inhibitor, was investigated on the microRNA (miR, miRNA) expression profile in cultured primary rat hepatocytes by means of microarray analysis. Simultaneously, albumin secretory capacity and morphological features of the hepatocytes were evaluated throughout the culture time. In total, 25 out of 348 miRNAs were found to be differentially expressed between freshly isolated hepatocytes and 7-day cultured cells.

Biotransformation pathway maps in WikiPathways enable direct visualization of drug metabolism related expression changes.

In recent decades, our knowledge of the genetics and functional genomics of drug-metabolizing enzymes has increased and a wealth of data on drug-related 'omics' has become available. Despite the availability of large amounts of biological information on xenobiotic biotransformation, the number of available biotransformation pathway maps that can easily be used for visualization of multiple omics data is limited. Here, we created integrated biotransformation pathway maps suitable for multiple omics analysis using PathVisio.