To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This study aim to derive and validate a simple and well-performing risk calculator (RC) for predicting psychosis in individual patients at clinical high risk (CHR).
From the ongoing ShangHai-At-Risk-for-Psychosis (SHARP) program, 417 CHR cases were identified based on the Structured Interview for Prodromal Symptoms (SIPS), of whom 349 had at least 1-year follow-up assessment. Of these 349 cases, 83 converted to psychosis. Logistic regression was used to build a multivariate model to predict conversion. The area under the receiver operating characteristic (ROC) curve (AUC) was used to test the effectiveness of the SIPS-RC. Second, an independent sample of 100 CHR subjects was recruited based on an identical baseline and follow-up procedures to validate the performance of the SIPS-RC.
Four predictors (each based on a subset of SIPS-based items) were used to construct the SIPS-RC: (1) functional decline; (2) positive symptoms (unusual thoughts, suspiciousness); (3) negative symptoms (social anhedonia, expression of emotion, ideational richness); and (4) general symptoms (dysphoric mood). The SIPS-RC showed moderate discrimination of subsequent transition to psychosis with an AUC of 0.744 (p < 0.001). A risk estimate of 25% or higher had around 75% accuracy for predicting psychosis. The personalized risk generated by the SIPS-RC provided a solid estimate of conversion outcomes in the independent validation sample, with an AUC of 0.804 [95% confidence interval (CI) 0.662–0.951].
The SIPS-RC, which is simple and easy to use, can perform in the same manner as the NAPLS-2 RC in the Chinese clinical population. Such a tool may be used by clinicians to counsel appropriately their patients about clinical monitor v. potential treatment options.
Since the publication of the first edition of Rapid Eye Movement Sleep (Mallick and Inoue, 1999), the advances in the field of sleep research have been phenomenal; in particular, those concerning rapid eye movement (REM) sleep. The emphasis on REM sleep may be gauged by the fact that recently a conference exclusively devoted to this subject was organized in France to celebrate 50 years since the discovery of REM sleep as well as to honor Professor Michel Jouvet, a pioneer and one of the doyens in this field.
Spanning over half a century of investigation into Rapid Eye Movement (REM) sleep, this volume provides comprehensive coverage of a broad range of topics in REM sleep biology. World renowned researchers and experts are brought together to discuss past and current research and to set the foundation for future developments. Key topics are covered in six sections from fundamental topics (historical context and general biology) to cutting-edge research on neuronal regulation, neuroanatomy and neurochemistry, functional significance and disturbance in the REM sleep generating mechanism. A reference source for all aspects of REM sleep research, it also incorporates chapters on neural modelling, findings from non-human species and interactions between brain regions. This is an invaluable resource, essential reading for all involved in sleep research and clinical practice.
In this chapter, we will review the recent developments relevant to understanding the neural systems that regulate REM sleep. We will review the initial discovery of REM sleep, followed by a brief description of the polysomnographic characterization of REM sleep. Our discussion will continue with a review of the principal brain-stem executive neurons responsible for REM generation. Pontine reticular formation neurons are involved in the expression of the majority of REM-sleep phenomena, including low-amplitude/high-frequency cortical EEG, the hippocampal theta rhythm, PGO waves/P-waves, and muscle atonia. Cholinergic brain-stem neurons are REM-on, promoting REM sleep; and serotonergic and noradrenergic brain-stem neurons are REM-off, suppressing REM sleep. GABAergic and glutamatergic mechanisms are also integral to REM sleep control. We will also survey the prominent nuclei of the midbrain and forebrain that promote, but do not generate, REM-sleep expression. The conclusion of this chapter will provide a review of three prominent models of REM-sleep regulation: the reciprocal-interaction model; the REM sleep “flip-flop” circuit model; and the revised model of paradoxical (REM) sleep control proposed by Luppi and colleagues.