Framework for mapping key areas for marine megafauna to inform Marine Spatial Planning: the Falkland Islands case study

Marine Spatial Planning (MSP) is becoming a key management approach throughout the world. The process includes the mapping of how humans and wildlife use the marine environment to inform the development of management measures. An integrated multi-species approach to identifying key areas is important for MSP because it allows managers a global representation of an area, enabling them to see where management can have the most impact for biodiversity protection. However, multi-species analysis remains challenging. This paper presents a methodological framework for mapping key areas for marine megafauna (seabirds, pinnipeds, cetaceans) by incorporating different data types across multiple species. The framework includes analyses of tracking data and observation survey data, applying analytical steps according to the type of data available during each year quarter for each species. It produces core-use area layers at the species level, then combines these layers to create megafauna core-use area layers. The framework was applied in the Falkland Islands. The study gathered over 750,000 tracking and at-sea observation locations covering an equivalent of 5495 data days between 1998 and 2015 for 36 species. The framework provides a step-by-step implementation protocol, replicable across geographic scales and transferable to multiple taxa. R scripts are provided. Common repositories, such as the Birdlife International Tracking Database, are invaluable tools, providing a secure platform for storing and accessing spatial data to apply the methodological framework. This provides managers with data necessary to enhance MSP efforts and marine conservation worldwide

Inflammatory biomarkers in Alzheimer's disease plasma

Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers. A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation