Mortality Risk Prediction Models for People With Kidney Failure: A Systematic Review.

Importance: People with kidney failure have a high risk of death and poor quality of life. Mortality risk prediction models may help them decide which form of treatment they prefer.

Objective: To systematically review the quality of existing mortality prediction models for people with kidney failure and assess whether they can be applied in clinical practice.

Ethical considerations on the use of big Data and Artificial Intelligence in kidney research from the ERA ethics committee.

In the current paper, we will focus on requirements to ensure big data can advance the outcomes of our patients suffering from kidney disease. The associated ethical question is whether and how we as a nephrology community can and should encourage the collection of big data of our patients. We identify some ethical reflections on the use of big data, and their importance and relevance.

Detection and Response Evaluation of Extramedullary and Medullary Blast Crisis in Chronic Myeloid Leukemia on 18 F-FDG PET/CT.

FDG PET/CT imaging is usually not routinely undertaken in patients of chronic myeloid leukemia (CML). We present a case of CML on tyrosine kinase inhibitor treatment with disease control indicated by BCR-ABL1 quantitative reverse transcription-polymerase chain reaction, who underwent PET/CT for evaluation of recent onset vision deterioration with subretinal exudates on ophthalmological examination. PET CT detected FDG-avid sinonasal thickening and bilateral marrow lesions.

Genetic variation drives cancer cell adaptation to ECM stiffness.

The progression of many solid tumors is accompanied by temporal and spatial changes in the stiffness of the extracellular matrix (ECM). Cancer cells adapt to soft and stiff ECM through mechanisms that are not fully understood. It is well known that there is significant genetic heterogeneity from cell to cell in tumors, but how ECM stiffness as a parameter might interact with that genetic variation is not known.