RESUMO
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
Assuntos
Doença de Alzheimer/complicações , Transtornos Cognitivos/diagnóstico , Transtornos Cognitivos/etiologia , Doença de Alzheimer/genética , Apolipoproteínas E/genética , Biomarcadores , Transtornos Cognitivos/genética , Biologia Computacional , Bases de Dados Bibliográficas/estatística & dados numéricos , Humanos , Valor Preditivo dos TestesRESUMO
Strontium (Sr) removal from water is required because excessive naturally occurring Sr exposure is hazardous to human health. Climate and seasonal changes cause water quality variations, in particular quality and quantity of organic matter (OM) and pH, and such variations affect Sr removal by nanofiltration (NF). The mechanisms for such variations are not clear and thus OM complexation and speciation require attention. Sr removal by NF was investigated with emphasis on the role of OM (type and concentration) and pH (2-12) on possible removal mechanisms, specifically size and/or charge exclusion as well as solute-solute interactions. The filtration results show that the addition of various OM (10 types) and an increase of OM concentration (2-100 mgC.L-1) increased Sr removal by 10-15%. The Sr-OM interaction was enhanced with increasing OM concentration, implying enhanced size exclusion via Sr-OM interaction as the main mechanism. Such interactions were quantified by asymmetric flow field-flow fractionation (FFFF) coupled with an inductively coupled plasma mass spectrometer (ICP-MS). Both extremely low and high pH increased Sr removal due to the enhanced charge exclusion and Sr-OM interactions. This work elucidated and verified the mechanism of OM and pH on Sr removal by NF membranes.