The association of low endothelial shear stress (ESS) with high-risk plaque (HRP) has not been thoroughly investigated in humans. We investigated the local ESS and lumen remodelling patterns in HRPs using optical coherence tomography (OCT), developed the shear stress score, and explored its association with the prevalence of HRPs and clinical outcomes. A total of 35 coronary arteries from 30 patients with stable angina or acute coronary syndrome (ACS) were reconstructed with three dimensional (3D) OCT. ESS was calculated using computational fluid dynamics and classified into low, moderate, and high in 3-mm-long subsegments. In each subsegment, (i) fibroatheromas (FAs) were classified into HRPs and non-HRPs based on fibrous cap (FC) thickness and lipid pool size, and (ii) lumen remodelling was classified into constrictive, compensatory, and expansive. In each artery the shear stress score was calculated as metric of the extent and severity of low ESS. FAs in low ESS subsegments had thinner FC compared with high ESS (89 ± 84 vs.138 ± 83 µm, P < 0.05). Low ESS subsegments predominantly co-localized with HRPs vs. non-HRPs (29 vs. 9%, P < 0.05) and high ESS subsegments predominantly with non-HRPs (9 vs. 24%, P < 0.05). Compensatory and expansive lumen remodelling were the predominant responses within subsegments with low ESS and HRPs. In non-stenotic FAs, low ESS was associated with HRPs vs. non-HRPs (29 vs. 3%, P < 0.05). Arteries with increased shear stress score had increased frequency of HRPs and were associated with ACS vs. stable angina. Local low ESS and expansive lumen remodelling are associated with HRP. Arteries with increased shear stress score have increased frequency of HRPs and propensity to present with ACS.

Public awareness of and concerns about companies’ social and environmental impacts have seen a marked increase over recent decades. In parallel, the quantity of relevant information has increased, as states pass laws requiring certain forms of reporting, researchers investigate companies’ performance, and companies themselves seek to gain a competitive advantage by being seen to operate fairly and transparently. However, this information is typically dispersed and non-standardized, making it complicated to collect and analyze. To address this challenge, the WikiRate platform aims to collect this information and store it in a standardized format within a centralized public repository, making it much more amenable to analysis. In the context of WikiRate, this article introduces easIE, an easy-to-use information extraction (IE) framework that leverages general Web IE principles for building datasets with environmental, social, and governance information from the Web. To demonstrate the flexibility and value of easIE, we built a large-scale corporate social responsibility database comprising 654,491 metrics related to 49,009 companies spending less than 16 hours for data engineering, collection, and indexing. Finally, a data collection exercise involving 12 subjects was performed to showcase the ease of use of the developed framework.