ERF

Plant secondary metabolites are unique sources for pharmaceuticals, food additives, flavors, and other industrial materials. Accumulation of such metabolites often occurs in plants subjected to stresses including various elicitors or signal molecules. Understanding signal transduction paths underlying elicitor-induced production of secondary metabolites is important for optimizing their commercial production. This paper summarizes progress made on several aspects of elicitor signal transduction leading to production of plant secondary metabolites, including: elicitor signal perception by various receptors of plants; avirulence determinants and corresponding plant R proteins; heterotrimeric and small GTP binding proteins; ion fluxes, especially Ca2+ influx, and Ca2+ signaling; medium alkalinization and cytoplasmic acidification; oxidative burst and reactive oxygen species; inositol trisphosphates and cyclic nucleotides (cAMP and cGMP); salicylic acid and nitric oxide; jasmonate, ethylene, and abscisic acid signaling; oxylipin signals such as allene oxide synthase-dependent jasmonate and hydroperoxide lyase-dependent C12 and C6 volatiles; as well as other lipid messengers such as lysophosphatidylcholine, phosphatidic acid, and diacylglycerol. All these signal components are employed directly or indirectly by elicitors for induction of plant secondary metabolite accumulation. Cross-talk between different signaling pathways is very common in plant defense response, thus the cross-talk amongst these signaling pathways, such as elicitor and jasmonate, jasmonate and ethylene, and each of these with reactive oxygen species, is discussed separately. This review also highlights the integration of multiple signaling pathways into or by transcription factors, as well as the linkage of the above signal components in elicitor signaling network through protein phosphorylation and dephosphorylation. Some perspectives on elicitor signal transduction and plant secondary metabolism at the transcriptome and metabolome levels are also presented.

The event-related potential (ERP) and event-related field (ERF) techniques provide valuable insights into the time course of processes in the brain. Because neural signals are typically weak, researchers commonly filter the data to increase the signal-to-noise ratio. However, filtering may distort the data, leading to false results. Using our own EEG data, we show that acausal high-pass filtering can generate a systematic bias easily leading to misinterpretations of neural activity. In particular, we show that the early ERP component C1 is very sensitive to such effects. Moreover, we found that about half of the papers reporting modulations in the C1 range used a high-pass digital filter cut-off above the recommended maximum of 0.1Hz. More generally, among 185 relevant ERP/ERF publications, 80 used cutoffs above 0.1Hz. As a consequence, part of the ERP/ERF literature may need to be re-analyzed. We provide guidelines on how to minimize filtering artifacts.