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Xi, C.

Publications and source records attributed to Xi, C..

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Cholecystokinin release triggered by presynaptic NMDA receptors produces LTP and sound-sound associative memory formation

Memory is stored in neural networks via changes in synaptic strength mediated in part by NMDA-dependent long-term potentiation (LTP). There is evidence that entorhinal cortex enables neocortical neuroplasticity through cholecystokinin (CCK)-containing neocortical projections. Here we show that a CCKB antagonist blocks high-frequency stimulation (HFS)-induced LTP in the auditory cortex, whereas local infusion of CCK induces LTP. CCK-/- mice lacked neocortical LTP and showed deficits in a cue-cue associative learning paradigm; administration of CCK rescued associative learning. HFS of CCK-containing entorhino-neocortical projection neurons in anesthetized mice enabled cue-cue associative learning. Furthermore, when one cue was pre-conditioned to footshock, the mouse showed a freezing response to the other cue, indicating that the mice had formed an association. HFS-induced neocortical LTP was completely blocked by either NMDA antagonist or CCK-BR antagonist, while application of either NMDA or CCK induced LTP after low-frequency stimulation (LFS). Moreover, in the presence of CCK LTP was still induced, even after blockade of NMDA receptors. Local application of NMDA induced CCK release in the neocortex. To identify how NMDA receptor switches LTP, a stimulation protocol of 25 pulse-pairs was adopted to replace HFS; NMDA-dependent LTP was induced with the inter-pulse intervals between 10 and 100 ms, but not with those of 5 and 200 ms. LTP-mediated plasticity was linked to localization of the NMDA receptor subunit NR2a on cortical CCK terminals originating in the entorhinal cortex. These novel findings suggest that presynaptic NMDA receptors on CCK terminals control the release of CCK, which enables neocortical LTP and formation of cue-cue associative memory.\n\nOne Sentence SummaryPresynaptic NMDA receptors switches the release of CCK from entorhinal neurons, which enables neocortical LTP and formation of sound-sound associative memory.

neuroscience

Modeling the emergence of antibiotic resistance in the environment: an analytical solution for the minimum selection concentration

Environmental antibiotic risk management requires an understanding of how subinhibitory antibiotic concentrations contribute to the spread of resistance. We develop a simple model of competition between sensitive and resistant bacterial strains to predict the minimum selection concentration (MSC), the lowest level of antibiotic at which resistant bacteria are selected. We present an analytical solution for the MSC based on the routinely measured minimum inhibitory concentration (MIC) and the selection coefficient (sc) that expresses fitness differences between strains. We calibrated the model by optimizing the shape of the bacterial growth dose-response curve to antibiotic or metal exposure (the Hill coefficient, {kappa}) to fit previously published experimental growth rate difference data. The model fit varied among nine compound-taxa combinations examined, but predicted the experimentally observed MSC/MIC ratio well (R2 [≥] 0.95). The shape of the antibiotic response curve varied among compounds (0.7 [≤] {kappa} [≤] 10.5), with the steepest curve for the aminoglycosides streptomycin and kanamycin. The model was sensitive to this antibiotic response curve shape and to the sc, indicating the importance of fitness differences between strains for determining the MSC. The MSC can be more than one order of magnitude lower than the MIC, typically by a factor sc{kappa}. This study provides an initial quantitative depiction and a framework for a research agenda to examine the growing evidence of selection for resistant bacteria communities at low environmental antibiotic concentrations.

microbiology