Association between TNF Receptors and KIM-1 with Kidney Outcomes in Early-Stage Diabetic Kidney Disease

Background and objectives: Clinical trials in nephrology are enriched for patients with micro- or macroalbuminuria to enroll patients at risk of kidney failure. However, patients with normoalbuminuria can also progress to kidney failure. Tumor Necrosis Factor Receptor (TNFR)-1, TNFR-2 and Kidney Injury Marker (KIM)-1 are known to be associated with kidney disease progression in patients with micro- or macroalbuminuria. We assessed the value of TNFR-1, TNFR-2 and KIM-1 as prognostic biomarkers for CKD progression in patients with type 2 diabetes and normoalbuminuria. Design, setting, participants and measurements: TNFR-1, TNFR-2, and KIM-1 were measured using immunoassays in plasma samples from patients with type 2 diabetes at high cardiovascular risk participating in the CANVAS trial. We used multivariable adjusted Cox proportional hazards analyses to estimate hazard ratios per doubling of each biomarker for the kidney outcome and stratified the population by the 4th quartile of each biomarker distribution and assessed the number of events and event rates. Results: In patients with normoalbuminuria (N=2,553), 51 kidney outcomes were recorded during a median follow-up of 6.1 (IQR 5.8 to 6.4) years (event rate 3.5 [95%CI 2.6-4.6] per 1,000-patient-years). Each doubling of baseline TNFR-1 (HR 4.16; 95%CI 1.80-9.61) and TNFR-2 (HR 2.35; 95%CI 1.51-3.63) was associated with a higher risk for the kidney outcome. Baseline KIM-1, UACR and eGFR were not associated with kidney outcomes. The event rates in the highest quartile of the TNFR-1 (≥2,992 ng/ml) or TNFR-2 (≥11,394 ng/ml) were 5.6 and 7.0 events per 1000-patient-years compared to 2.4 and 2.8 in the lower three quartiles. Conclusion: TNFR-1 and TNFR-2 are associated with kidney outcomes in patients with type 2 diabetes and normoalbuminuria

Charting Past, Present, and Future Research in the Semantic Web and Interoperability

Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research on the semantic web and interoperability has recently received much attention, a dearth of studies investigates the relationship between these two concepts in depth. To address this knowledge gap, the objective of this study is to conduct a review and bibliometric analysis of 3511 Scopus-registered papers on the semantic web and interoperability published over the past two decades. In addition, the publications were analyzed using a variety of bibliometric indicators, such as publication year, journal, authors, countries, and institutions. Keyword co-occurrence and co-citation networks were utilized to identify the primary research hotspots and group the relevant literature. The findings of the review and bibliometric analysis indicate the dominance of conference papers as a means of disseminating knowledge and the substantial contribution of developed nations to the semantic web field. In addition, the keyword co-occurrence network analysis reveals a significant emphasis on semantic web languages, sensors and computing, graphs and models, and linking and integration techniques. Based on the co-citation clustering, the Internet of Things, semantic web services, ontology mapping, building information modeling, bioinformatics, education and e-learning, and semantic web languages were identified as the primary themes contributing to the flow of knowledge and the growth of the semantic web and interoperability field. Overall, this review substantially contributes to the literature and increases scholars’ and practitioners’ awareness of the current knowledge composition and future research directions of the semantic web field. View Full-Tex