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Alcohol use disorder (AUD) is a major component in the etiology of cognitive decline and dementia. Underlying mechanisms by which long-term alcohol abuse causes cognitive dysfunction include excessive oxidative stress and inflammation in the brain, activated by increased reactive oxygen/nitrogen species (ROS/RNS), advanced glycation end-products (AGEs) and high-mobility group box 1 protein (HMGB1). In a pilot study, we examine the potential clinical value of circulating biomarkers of oxidative stress including ROS/RNS, HMGB1, the soluble receptor for AGE (sRAGE), the brain biomarker of aging apolipoprotein D (ApoD), and the antioxidant regulator nuclear factor erythroid 2-related factor 2 (NRF2) as predictive indices for cognitive impairment (CI) in abstinent patients with AUD (n = 25) compared to patients with established Alzheimer’s disease (AD, n = 26) and control subjects (n = 25). Plasma concentrations of sRAGE were evaluated with immunoblotting; ROS/RNS with a fluorometric kit; and HMGB1, ApoD, and NRF2 by ELISA. Abstinent AUD patients had higher sRAGE, ROS/RNS (p < 0.05), and ApoD (p < 0.01) concentrations, similar to those of AD patients, and lower NRF2 (p < 0.01) concentrations, compared to controls. These changes were remarkable in AUD patients with CI. HMGB1, and sRAGE correlated positively with duration of alcohol use (rho = 0.398, p = 0.022; rho = 0.404, p = 0.018), whereas sRAGE correlated negatively with periods of alcohol abstinence (rho = −0.340, p = 0.045). A predictive model including ROS/RNS, HMGB1, sRAGE, alcohol use duration, and alcohol abstinence periods was able to differentiate AUD patients with CI (92.3% of correct predictions, ROC-AUC= 0.90) from those without CI. In conclusion, we propose ROS/RNS, HMGB1, and sRAGE as stress biomarkers capable of predicting cognitive impairment in AUD patients. 

Abstract. Plant transpiration links physiological responses ofvegetation to water supply and demand with hydrological, energy, and carbonbudgets at the land–atmosphere interface. However, despite being the mainland evaporative flux at the global scale, transpiration and its response toenvironmental drivers are currently not well constrained by observations.Here we introduce the first global compilation of whole-plant transpirationdata from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021).We harmonized and quality-controlled individual datasets supplied bycontributors worldwide in a semi-automatic data workflow implemented in theR programming language. Datasets include sub-daily time series of sap flowand hydrometeorological drivers for one or more growing seasons, as well asmetadata on the stand characteristics, plant attributes, and technicaldetails of the measurements. SAPFLUXNET contains 202 globally distributeddatasets with sap flow time series for 2714 plants, mostly trees, of 174species. SAPFLUXNET has a broad bioclimatic coverage, withwoodland/shrubland and temperate forest biomes especially well represented(80 % of the datasets). The measurements cover a wide variety of standstructural characteristics and plant sizes. The datasets encompass theperiod between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data areavailable for most of the datasets, while on-site soil water content isavailable for 56 % of the datasets. Many datasets contain data for speciesthat make up 90 % or more of the total stand basal area, allowing theestimation of stand transpiration in diverse ecological settings. SAPFLUXNETadds to existing plant trait datasets, ecosystem flux networks, and remotesensing products to help increase our understanding of plant water use,plant responses to drought, and ecohydrological processes. SAPFLUXNET version0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The“sapfluxnetr” R package – designed to access, visualize, and processSAPFLUXNET data – is available from CRAN.