Evidence of the impacts of pharmaceuticals on aquatic animal behaviour: a systematic map protocol

Background: Globally, there is growing concern over the impacts of pharmaceuticals and drug manufacturing on aquatic animals, and pharmaceuticals are now recognized as contaminants of emerging environmental concern. In recent years, scientists, environmental managers, and policymakers have been interested in using behavioural endpoints for chemical regulation, given their importance for ftness and survival. The body of research on whether and how pharmaceutical exposure alters the behaviour of aquatic animals has grown exponentially, making it diffcult to get an overview of the results. With an international spotlight on the management of these environmental threats, synthesizing the currently available data is vital to inform managers and policymakers, as well as highlighting areas where more research is needed. This is a protocol for a systematic evidence map (SEM) and serves as an a priori record of our objectives and methodological decisions. Our objectives are to identify, catalogue, and present primary research articles on the efects of human and veterinary pharmaceuticals on aquatic animal behaviour. Methods: The literature search will be conducted using two electronic databases: Web of Science and Scopus, and we will supplement these searches with additional sources. The search string has been developed using a Population–Exposure–Comparison–Outcome (PECO) framework, to capture articles that used an aquatic organism (P, population) to test the efects of a pharmaceutical (E, exposure) on behaviour (O, outcome). Eligible articles must also have a control group (C, comparison). Articles will be screened in two stages, title and abstract, followed by full-text screening before data extraction. Decision trees have been designed a priori to appraise articles for eligibility at both stages of screening. At both stages, screening each article will be completed by two independent reviewers. Study validity will be appraised but not used as a basis for article inclusion. The information extracted from the eligible articles, along with bibliometric data, will be mapped and displayed. All data associated with this SEM will be publicly available through the Open Science Framework (OSF) and a future project webpage

A Distinct Class of Antibodies May Be an Indicator of Gray Matter Autoimmunity in Early and Established Relapsing Remitting Multiple Sclerosis Patients

We have previously identified a distinct class of antibodies expressed by B cells in the cerebrospinal fluid (CSF) of early and established relapsing remitting multiple sclerosis (RRMS) patients that is not observed in healthy donors. These antibodies contain a unique pattern of mutations in six codons along V(H)4 antibody genes that we termed the antibody gene signature (AGS). In fact, patients who have such B cells in their CSF are identified as either having RRMS or developing RRMS in the future. As mutations in antibody genes increase antibody affinity for particular antigens, the goal for this study was to investigate whether AGS(+) antibodies bind to brain tissue antigens. Single B cells were isolated from the CSF of 10 patients with early or established RRMS. We chose 32 of these B cells that expressed antibodies enriched for the AGS for further study. We generated monoclonal full-length recombinant human antibodies (rhAbs) and used both immunological assays and immunohistochemistry to investigate the capacity of these AGS(+) rhAbs to bind brain tissue antigens. AGS(+) rhAbs did not recognize myelin tracts in the corpus callosum. Instead, AGS(+) rhAbs recognized neuronal nuclei and/or astrocytes, which are prevalent in the cortical gray matter. This pattern was unique to the AGS(+) antibodies from early and established RRMS patients, as AGS(+) antibodies from an early neuromyelitis optica patient did not display the same reactivity. Prevalence of CSF-derived B cells expressing AGS(+) antibodies that bind to these cell types may be an indicator of gray matter-directed autoimmunity in early and established RRMS patients