Mentha spp. Essential Oils: A Potential Toxic Fumigant with Inhibition of Acetylcholinesterase Activity on Reticulitermes dabieshanensis.

In this study, we analyzed the components of Mentha spp. essential oils (EOs) and evaluated their major constituents and binary combinations against Reticulitermes dabieshanensis. We also determined the activities of esterases (ESTs), glutathione S-transferases (GSTs), and acetylcholinesterase activity (AChE) in treated insects. According to our findings, the most effective oils were those obtained from M. citrata (with the major constituent linalool constituting 45.1%), M. piperita (menthol, 49.1%), and M. spicata (carvone, 69.0%), with LC50 values of 0.176, 0.366, and 0.146 µL/L, respectively. The LC50 values were recorded for linalool (0.303 µL/L), followed by menthol (0.272 µL/L), and carvone (0.147 µL/L). The insecticidal potency increased with binary mixtures of major active constituents, with carvone strongly synergizing the toxicity of linalool and menthol against R. dabieshanensis. Compared to the control, except for M. citrata treated with no difference in α-NA or GST activity, the activities of ESTs and GST in other treatment groups were significantly increased. Additionally, our results found that Mentha spp. EOs and their major constituents inhibited the activity of AChE in vivo and in vitro. Finally, we performed a structure-based virtual screening of linalool, menthol, and carvone to identify that linalool had the greatest potential to bind to the active site of AChE. The present study suggests that Mentha spp. EOs could provide an additional approach for the management of termites over synthetic insecticides.

Decreasing integration within face network and segregation beyond the face network in the aging brain.

Face processing is known to decline in older adults; however, a clear understanding of the brain networks behind this cognitive decline is still lacking. In this study, we investigated the neural correlates of the declined face processing with aging from a resting-state brain network perspective. Nineteen healthy old adults and 22 young adults were recruited and underwent two functional magnetic resonance imaging (fMRI) scanning sessions (i.e., resting-state and localizer task) and two behavioral tests (face matching and symbol-form matching). We examined age-related alterations in resting-state functional connectivity (FC) within face network as well as between face network and other networks, and tested their associations with behavioral performance of face and symbol-form processing. We found that (a) compared with young adults, old adults exhibited decreased FC between face-selective regions (fusiform face area and occipital face area), but increased FC between face-selective regions and non-face-selective regions; (b) these age-related FC alterations were correlated with individuals' behavioral performance of face and symbol-form processing. Collectively, these findings suggest the declines of face processing are associated with a mixture of decreased integration within the face network and segregation beyond the face network in the aging brain, and provide evidence for a neural basis of cognitive aging in face processing from an intrinsic brain network perspective.

Level of Orthographic Knowledge Helps to Reveal Automatic Predictions in Visual Word Processing.

The brain generates predictions about visual word forms to support efficient reading. The "interactive account" suggests that the predictions in visual word processing can be strategic or automatic (non-strategic). Strategic predictions are frequently demonstrated in studies that manipulated task demands, however, few studies have investigated automatic predictions. Orthographic knowledge varies greatly among individuals and it offers a unique opportunity in revealing automatic predictions. The present study grouped the participants by level of orthographic knowledge and recorded EEGs in a non-linguistic color matching task. The visual word-selective N170 response was much stronger to pseudo than to real characters in participants with low orthographic knowledge, but not in those with high orthographic knowledge. Previous work on predictive coding has demonstrated that N170 is a good index for prediction errors, i.e., the mismatches between predictions and visual inputs. The present findings provide unambiguous evidence that automatic predictions modulate the early stage of visual word processing.