Gene Ontology: Pitfalls, Biases, and Remedies.

The Gene Ontology (GO) is a formidable resource, but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices

IVUS-based imaging modalities for tissue characterization: similarities and differences

Gray-scale intravascular ultrasound (IVUS) is the modality that has been established as the golden standard for in vivo imaging of the vessel wall of the coronary arteries. The use of IVUS in clinical practice is an important diagnostic tool used for quantitative assessment of coronary artery disease. This has made IVUS the de-facto invasive imaging method to evaluate new interventional therapies such as new stent designs and for atherosclerosis progression-regression studies. However, the gray-scale representation of the coronary vessel wall and plaque morphology in combination with the limited resolution of the current IVUS catheters makes it difficult, if not impossible, to identify qualitatively (e.g. visually) the plaque morphology similar as that of histopathology, the golden standard to characterize and quantify coronary plaque tissue components. Meanwhile, this limitation has been partially overcome by new innovative IVUS-based post-processing methods such as: virtual histology IVUS (VH-IVUS, Volcano Therapeutics, Rancho Cordova, CA, USA), iMAP-IVUS (Bostoc Scientific, Santa Clara, CA, USA), Integrated Backscatter IVUS (IB-IVUS) and Automated Differential Echogenicity (ADE)

Modelling the impact of atherosclerosis on drug release and distribution from coronary stents

Although drug-eluting stents (DES) are now widely used for the treatment of coronary heart disease, there remains considerable scope for the development of enhanced designs which address some of the limitations of existing devices. The drug release profile is a key element governing the overall performance of DES. The use of in vitro, in vivo, ex vivo, in silico and mathematical models has enhanced understanding of the factors which govern drug uptake and distribution from DES. Such work has identified the physical phenomena determining the transport of drug from the stent and through tissue, and has highlighted the importance of stent coatings and drug physical properties to this process. However, there is limited information regarding the precise role that the atherosclerotic lesion has in determining the uptake and distribution of drug. In this review, we start by discussing the various models that have been used in this research area, highlighting the different types of information they can provide. We then go on to describe more recent methods that incorporate the impact of atherosclerotic lesions

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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