Selective recovery of zinc from goethite residue in the zinc industry using deep-eutectic solvents

Several deep-eutectic solvents (DESs) were tested for the valorisation of goethite residue produced by the zinc industry. The objective of the work was to selectively recover zinc from the iron-rich matrix using deep-eutectic solvents as lixiviants. The effect of the type of hydrogen bond donor and hydrogen bond acceptor of the deep-eutectic solvent on the leaching efficiency was studied. Levulinic acid–choline chloride (x_ChCl = 0.33) (LevA–ChCl) could selectively leach zinc from the iron-rich matrix, and it was selected as the best-performing system to be used in further study. The leaching process was optimised in terms of temperature, contact time, liquid-to-solid ratio and water content of the deep-eutectic solvent. The role of the choline cation on the leaching process was investigated by considering the leaching properties of a LevA–CaCl₂ mixture. The goethite residue was also leached with pure levulinic acid. The results were compared to a purely hydrometallurgical approach using sulphuric acid leaching. Leaching with LevA–ChCl resulted in higher selectivity compared to the conventional “hot leaching” with 80 g L⁻¹ sulphuric acid. Furthermore, a slightly higher zinc recovery and comparable selectivity for zinc over iron were achieved with LevA–ChCl compared to conventional “neutral leaching” with 10 g L⁻¹ sulphuric acid.

A mixture of levulinic acid and choline chloride can be used to selectively leach zinc from industrial residues with iron-rich matrices.     

Characteristics of differentiated CD8+ and CD4+ T cells present in the human brain

Immune surveillance of the central nervous system (CNS) by T cells is important to keep CNS-trophic viruses in a latent state, yet our knowledge of the characteristics of CNS-populating T cells is incomplete. We performed a comprehensive, multi-color flow-cytometric analysis of isolated T cells from paired corpus callosum (CC) and peripheral blood (PB) samples of 20 brain donors. Compared to PB, CC T cells, which were mostly located in the perivascular space and sporadically in the parenchyma, were enriched for cells expressing CD8. Both CD4⁺ and CD8⁺ T cells in the CC had a late-differentiated phenotype, as indicated by lack of expression of CD27 and CD28. The CC contained high numbers of T cells expressing chemokine receptor CX3CR1 and CXCR3 that allow for homing to inflamed endothelium and tissue, but hardly cells expressing the lymph node-homing receptor CCR7. Despite the late-differentiated phenotype, CC T cells had high expression of the IL-7 receptor α-chain CD127 and did not contain the neurotoxic cytolytic enzymes perforin, granzyme A, and granzyme B. We postulate that CNS T cells make up a population of tissue-adapted differentiated cells, which use CX3CR1 and CXCR3 to home into the perivascular space, use IL-7 for maintenance, and lack immediate cytolytic activity, thereby preventing immunopathology in response to low or non-specific stimuli. The presence of these cells in this tightly regulated environment likely enables a fast response to local threats. Our results will enable future detailed exploration of T-cell subsets in the brain involved in neurological diseases.     

Predicting alcohol dependence from multi-site brain structural measures

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.