Proteins of the major histocompatibility complex class I (MHCI) are known for their role in immunity and have recently been implicated in long-term plasticity of excitatory synaptic transmission. However, the mechanisms by which MHCI influences synaptic plasticity remain unknown. Here we show that endogenous MHCI regulates synaptic responses mediated by NMDA-type glutamate receptors (NMDARs) in the mammalian central nervous system (CNS). The AMPA/NMDA ratio is decreased at MHCI-deficient hippocampal synapses, reflecting an increase in NMDAR-mediated currents. This enhanced NMDAR response is not associated with changes in the levels, subunit composition, or gross subcellular distribution of NMDARs. Increased NMDAR-mediated currents in MHCI-deficient neurons are associated with characteristic changes in AMPA receptor trafficking in response to NMDAR activation. Thus, endogenous MHCI tonically inhibits NMDAR function and controls downstream NMDAR-induced AMPA receptor trafficking during the expression of plasticity.immune | GluR | hippocampus P roteins of the major histocompatibility complex class I (MHCI) are best known for their role in adaptive immunity, but several lines of evidence suggest they also have nonimmune functions in neurons (1, 2). MHCI is expressed by healthy neurons in the developing and adult CNS (3-7). Neuronal MHCI mRNA levels are dynamic during development and are regulated by electrical activity (3, 4) and by the cAMP-response element-binding protein (CREB) (8). MHCI protein is enriched in synaptic fractions (4) and is detected in hippocampal dendritic spines, where it colocalizes with PSD-95 (9).Studies in mice genetically deficient for cell-surface MHCI (β2m −/− TAP −/− mice) suggest a role for MHCI in activity-dependent plasticity. In MHCI-deficient mice, NMDA receptor (NMDAR)-dependent hippocampal long-term potentiation (LTP) is enhanced, whereas long-term depression (LTD) is abolished (4). Although the mechanisms by which MHCI mediates immune signaling have been relatively well characterized, nothing is known about how MHCI contributes to NMDAR-dependent plasticity in vitro or in vivo.In the adult hippocampus, plasticity induced by activation of NMDARs is expressed as changes in the trafficking and function of AMPA receptors (AMPARs) (10-13). In current models, the magnitude and kinetics of NMDAR activation determine whether potentiation or depression is induced, with large, transient NMDAR activation causing LTP and smaller, longer-lasting activation causing LTD (14, 15). Therefore, to better understand the role of endogenous MHCI in the induction or expression of synaptic plasticity, we examined the levels, distribution, trafficking, and function of AMPA-and NMDA-type receptors in MHCI-deficient hippocampal neurons.The current experiments reveal an unexpected role for postsynaptic MHCI in controlling NMDAR function. Loss of MHCI causes a drop in the AMPA/NMDA ratio and an enhancement of NMDAR-mediated responses at CA3-CA1 synapses. This enhancement cannot be attributed to changes in th...

The effect on performance overnight of a 1 h nap taken at 0200 h was studied in six young female subjects. The subjects completed three schedules, including one with a nap and two without a nap, during which either a placebo or 300 mg caffeine was ingested at 2315 h. Performance was measured from 1700 h in the evening until 1030 h the next morning. Caffeine improved performance overnight on almost all tasks compared with placebo. The nap had some limited beneficial effect compared with placebo, but most tasks remained impaired.

This paper starts by summarizing the development and refinement of the additive three-process model of alertness first published by Folkard and Akerstedt in 1987. It reviews some of the successes that have been achieved by the model in not only predicting variations in subjective alertness on abnormal sleep-wake schedules but also in accounting for objective measures of sleep latency and duration. Nevertheless, predictions derived from the model concerning alertness on different shifts, and over successive night shifts, are difficult to reconcile with published data on accident risk. In light of this, we have examined two large sets of alertness ratings with a view to further refining the model and identifying additional factors that may influence alertness at any given point in time. Our results indicate that, at least for the range of sleep durations and wake-up times commonly found on rotating shift systems, we may assume the phase of the endogenous circadian component of alertness (process C) to be "set" by the time of waking. Such an assumption considerably enhanced the predictive power of the model and yielded remarkably similar phase estimates to those obtained by maximizing the post-hoc fit of the model. We then examined the manner in which obtained ratings differed from predicted values over a complete 8-day cycle of two, 12-h shift systems. This revealed a pronounced "first night compensation effect" that resulted in shift workers rating themselves as progressively more alert than would be predicted over the course of the first night shift. However, this appeared to be achieved only at the cost of lowered ratings on the second night shift. Finally, we were able to identify a "time on shift" effect whereby, with the exception of the first night shift, alertness ratings decreased over the course of each shift before showing a modest "end effect." We conclude that the identification of these additional components offers the possibility that in the future we may be able to predict trends in accident risk on abnormal sleep-wake schedules.

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The authors recently published a prototypic Risk Index (RI) to estimate the risk of critical errors associated with shift systems. This RI was based on published trends in the relative risk of injuries and accidents, and a simple additive model was proposed to estimate the risk for a given shift system. However, extending the RI to irregular work schedules requires an estimation of the phase and amplitude of the circadian rhythm in risk. This paper integrates the published evidence on three independent sources of data that allow such estimations to be made: the trend in risk over a 24 h day, over the course of the night shift, and across the three different (8 h) shifts. Despite potential confounders, maximum risk (i.e., acrophase = peak time) estimates across these three trends showed a remarkable consistency, with all three estimates occurring at about midnight, although the amplitude estimates varied considerably. The best estimate of the amplitude of the circadian rhythm in risk would appear to be that based on trend over the three (8 h) shifts, as this trend is the least confounded. The estimated acrophase (peak time) in risk appeared earlier than would be predicted from consideration of the circadian rhythm in alertness, fatigue, or performance on simple interpolated tasks, such as reaction time or performance on the Psychomotor Vigilance Test.