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This case study describes a 14-year-old male suffering from significant academic and personal difficulties, who has been diagnosed with depression, schizotypal personality disorder, and learning disabilities. Because of excessive sleepiness, assessment for a potential sleep disorder was performed. An overnight polysomnographic study revealed no primary sleep disorders. Wrist actigraphy revealed a non-24-hour sleep-wake pattern. Delay in temperature rhythm and dissociation with melatonin rhythms were also noted. Treatment with oral melatonin restored normal sleep-wake schedule. In a follow-up psychiatric evaluation, none of the above diagnoses were present. Greater awareness of sleep disorders may prevent psychiatric misdiagnosis of treatable sleep-wake schedule disorders.

Data Mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing large quantity of data in order to extract meaningful knowledge. Data mining methods are used in many studies to identify phenomena quicker and better than human experts. One class of these methods was designed for dealing with time series data. However, when several channels of data are collected simultaneously, data mining algorithms encounter numerous difficulties since channels may be measured in different units, may be recorded at different sampling-rates, or may have completely different characteristics. Furthermore, as the size of these data increases, the amount of irrelevant data usually increases as well and the process becomes impractical. Hence, in such cases, the analyst must be capable of focusing on the informational parts while ignoring the noise data. These kinds of difficulties complicate the analysis of multichannel data as compared to the analysis of single-channel data. This paper presents a useful technique for preprocessing multi channel data. Our technique supplies tools for coping with all the above-mentioned difficulties, and prepares the data for further analysis (using common algorithms, especially from the data mining field). The paper is divided as follows. After the introduction (Section I) we describe the state of the art (Section II), follows by the main section--methodology (Section III) which is divided to four steps (3.2-3.5). The results are described in a separate section (Section IV). Then, a discussion and conclusions of the proposed methodology are given in (Sections V and VI). Acknowledgements and the references follow. Index Terms--Data mining, multichannel, multi-channel, multivariable, recordings, signal quantization, signal discretization.

Current hypertension guidelines fail to provide a recommendation on when-to-treat, thus disregarding relevant circadian rhythms that regulate blood pressure (BP) level and 24 h patterning and medication pharmacokinetics and pharmacodynamics. The ideal purpose of ingestion-time (chronopharmacology, i.e. biological rhythm-dependent effects on the kinetics and dynamics of medications, and chronotherapy, i.e. the timing of pharmaceutical and other treatments to optimize efficacy and safety) trials should be to explore the potential impact of endogenous circadian rhythms on the effects of medications. Such investigations and outcome trials mandate adherence to the basic standards of human chronobiology research. In-depth review of the more than 150 human hypertension pharmacology and therapeutic trials published since 1974 that address the differential impact of upon-waking/morning versus at-bedtime/evening schedule of treatment reveals diverse protocols of sometimes suboptimal or defective design and conduct. Many have been "time-of-day," i.e. morning versus evening, rather than circadian-time-based, and some relied on wake-time office BP rather than around-the-clock ambulatory BP measurements (ABPM). Additionally, most past studies have been of too small sample size and thus statistically underpowered. As of yet, there has been no consensual agreement on the proper design, methods and conduct of such trials. This Position Statement recommends ingestion-time hypertension trials to follow minimum guidelines: (i) Recruitment of participants should be restricted to hypertensive individuals diagnosed according to ABPM diagnostic thresholds and of a comparable activity/sleep routine. (ii) Tested treatment-times should be selected according to internal biological time, expressed by the awakening and bed times of the sleep/wake cycle. (iii) ABPM should be the primary or sole method of BP assessment. (iv) The minimum-required features for analysis of the ABPM-determined 24 h BP pattern ought to be the asleep (not "nighttime") BP mean and sleep-time relative BP decline, calculated in reference to the activity/rest cycle per individual. (v) ABPM-obtained BP means should be derived by the so-called adjusted calculation procedure, not by inaccurate arithmetic averages. (vi) ABPM should be performed with validated and calibrated devices at least hourly throughout two or more consecutive 24 h periods (48 h in total) to achieve the highest reproducibility of mean wake-time, sleep-time and 48 h BP values plus the reliable classification of dipping status. (vii) Calculation of minimum required sample size in adherence with proper statistical methods must be provided. (viii) Hypertension chronopharmacology and chronotherapy trials should preferably be randomized double-blind, randomized open-label with blinded-endpoint, or crossover in design, the latter with sufficient washout period between tested treatment-time regimens. [ABSTRACT FROM AUTHOR]

The well-known Two-Process Model of Sleep Regulation describes the integration of the circadian rhythm of arousal and sleep – Process C, and the homeostatic pressure to sleep – Process S. Presently, the known biological markers for Process C are melatonin and core body temperature; whereas, for Process S, there is no biological marker except that of aspects of the electroencephalogram (EEG). Endozepines are a class of endogenous compounds that act like benzodiazepines (BZ), i.e., serving as ligands for the BZ binding sites on GABAA receptors. Not much is known about the role of endozepines, in particular non-peptide endozepines, in the sleep field except very few reports about high concentrations observed in endozepine stupor, a rare phenomenon of idiopathic recurring stupor. We focused on hypoxanthine and thromboxane A2, which are considered to have endozepine function. This study aimed to examine the effect of 24 h of acute sleep deprivation on blood levels of hypoxanthine and thromboxane A2 of healthy subjects without sleep problems or disorders. The results showed a significant decrease of both compounds in the morning after sleep deprivation in comparison to the unrestricted normal sleep condition, thereby suggesting that these endozepines are secreted regularly while asleep, and, thus, are necessary for the sleep process. This study is the first to suggest a connection between specific biological markers – endozepines and Process S – in the Two-Process Model of Sleep Regulation and, furthermore, it sheds light on the possible role of endozepines in sleepiness and fatigue. [ABSTRACT FROM AUTHOR]