Evidence for the Priming Effect in a Planktonic Estuarine Microbial Community

The “priming effect,” in which addition of labile substances changes the remineralization rate of recalcitrant organic matter, has been intensively studied in soils, but is less well-documented in aquatic systems. We investigated the extent to which additions of nutrients or labile organic carbon could influence remineralization rates of 14C-labeled, microbially-degraded, phytoplankton-derived organic matter (OM) in microcosms inoculated with microbial communities drawn from Grove Creek Estuary in coastal Georgia, USA. We found that amendment with labile protein plus phosphorus increased remineralization rates of degraded, phytoplankton-derived OM by up to 100%, whereas acetate slightly decreased remineralization rates relative to an unamended control. Addition of ammonium and phosphate induced a smaller effect, whereas addition of ammonium alone had no effect. Counterintuitively, alkaline phosphatase activities increased in response to the addition of protein under P-replete conditions, indicating that production of enzymes unrelated to the labile priming compound may be a mechanism for the priming effect. The observed priming effect was transient: after 36 days of incubation roughly the same quantity of organic carbon had been mineralized in all treatments including no-addition controls. This timescale is on the order of the typical hydrologic residence times of well-flushed estuaries suggesting that priming in estuaries has the potential to influence whether OC is remineralized in situ or exported to the coastal ocean

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