Probabilistic cardiac and respiratory based classification of sleep and apneic events in subjects with sleep apnea.

Current clinical standards to assess sleep and its disorders lack either accuracy or user-friendliness. They are therefore difficult to use in cost-effective population-wide screening or long-term objective follow-up after diagnosis. In order to fill this gap, the use of cardiac and respiratory information was evaluated for discrimination between different sleep stages, and for detection of apneic breathing. Alternative probabilistic visual representations were also presented, referred to as the hypnocorrogram and apneacorrogram. Analysis was performed on the UCD sleep apnea database, available on Physionet. The presence of apneic events proved to have a significant impact on the performance of a cardiac and respiratory based algorithm for sleep stage classification. WAKE versus SLEEP discrimination resulted in a kappa value of κ = 0.0439, while REM versus NREM resulted in κ = 0.298 and light sleep (N1N2) versus deep sleep (N3) in κ = 0.339. The high proportion of hypopneic events led to poor detection of apneic breathing, resulting in a kappa value of κ = 0.272. While the probabilistic representations allow to put classifier output in perspective, further improvements would be necessary to make the classifier reliable for use on patients with sleep apnea.

An evaluation of cardiorespiratory and movement features with respect to sleep-stage classification.

Polysomnography (PSG) is considered the gold standard to assess sleep accurately, but it can be expensive, time-consuming, and uncomfortable, specifically in long-term sleep studies. Actigraphy, on the other hand, is both cheap and userfriendly, but depending on the application lacks detail and accuracy. Our aim was to evaluate cardiorespiratory and movement signals in discriminating between wake, rapid-eye-movement (REM), light (N1N2), and deep (N3) sleep. The dataset comprised 85 nights of PSG from a healthy population. Starting from a total of 750 characteristic variables (features), problem-specific subsets of 40 features were forwardly selected using the combination of a wrapper method (Cohen's kappa statistic on radial basis function (RBF)-kernel support vector machine (SVM) classifier) and filter method (minimum redundancy maximum relevance criterion on mutual information). Final classification was performed using an RBF-kernel SVM. Non-subject-specific wake versus sleep classification resulted in a Cohen's kappa value of 0.695, while REM versus NREM resulted in 0.558 and N3 versus N1N2 in 0.553. The broad pool of initial features gave insight in which features discriminated best between the different classes. The classification results demonstrate the possibility of making long-term sleep monitoring more widely available.

Sleep misperception, EEG characteristics and autonomic nervous system activity in primary insomnia: a retrospective study on polysomnographic data.

Misperception of Sleep Onset Latency, often found in Primary Insomnia, has been cited to be influenced by hyperarousal, reflected in EEG- and ECG-related indices. The aim of this retrospective study was to examine the association between Central Nervous System (i.e. EEG) and Autonomic Nervous System activity in the Sleep Onset Period and the first NREM sleep cycle in Primary Insomnia (n=17) and healthy controls (n=11). Furthermore, the study examined the influence of elevated EEG and Autonomic Nervous System activity on Stage2 sleep-protective mechanisms (K-complexes and sleep spindles). Confirming previous findings, the Primary Insomnia-group overestimated Sleep Onset Latency and this overestimation was correlated with elevated EEG activity. A higher amount of beta EEG activity during the Sleep Onset Period was correlated with the appearance of K-complexes immediately followed by a sleep spindle in the Primary Insomnia-group. This can be interpreted as an extra attempt to protect sleep continuity or as a failure of the sleep-protective role of the K-complex by fast EEG frequencies following within one second. The strong association found between K-alpha (K-complex within one second followed by 8-12 Hz EEG activity) in Stage2 sleep and a lower parasympathetic Autonomic Nervous System dominance (less high frequency HR) in Slow-wave sleep, further assumes a state of hyperarousal continuing through sleep in Primary Insomnia.

Biomechanics-based active control of bedding support properties and its influence on sleep.

Proper body support plays an import role in the recuperation of our body during sleep. Therefore, this study uses an automatically adapting bedding system that optimises spinal alignment throughout the night by altering the stiffness of eight comfort zones. The aim is to investigate the influence of such a dynamic sleep environment on objective and subjective sleep parameters. The bedding system contains 165 sensors that measure mattress indentation. It also includes eight actuators that control the comfort zones. Based on the measured mattress indentation, body movements and posture changes are detected. Control of spinal alignment is established by fitting personalized human models in the measured indentation. A total of 11 normal sleepers participated in this study. Sleep experiments were performed in a sleep laboratory where subjects slept three nights: a first night for adaptation, a reference night and an active support night (in counterbalanced order). Polysomnographic measurements were recorded during the nights, combined with questionnaires aiming at assessing subjective information. Subjective information on sleep quality, daytime quality and perceived number of awakenings shows significant improvements during the active support (ACS) night. Objective results showed a trend towards increased slow wave sleep. On the other hand, it was noticed that % N1-sleep was significantly increased during ACS night, while % N2-sleep was significantly decreased. No prolonged N1 periods were found during or immediately after steering.

First Report of Tomato infectious chlorosis virus in Tomato in Indonesia.

In 2002, a breeding company submitted several samples of tomato (Lycopersicon esculentum) for diagnosis. Samples originated in Indonesia and were taken from protected and nonprotected crops. Plants exhibited severe chlorosis on fully expanded leaves, while young leaves were symptomless. Symptoms resembled those of the criniviruses Tomato chlorosis virus (ToCV) and Tomato infectious chlorosis virus (TICV). Moreover, large numbers of whiteflies, potential vectors of these viruses, had been observed at the plots with symptomatic plants. A reverse transcription-polymerase chain reaction (RT-PCR) with specific primers for TICV (1) yielded amplicons of the expected size of approximately 500 bp for all samples. One of the amplicons was sequenced (Genbank Accession No. AY221097) and revealed more than 98.9% identity to six isolates of TICV in NCBI Genbank. cDNA synthesis using the universal crinivirus primer HSP_M2-DW (5' -TCRAARGTWCCKCCNCCRAA-3') followed by PCR with a ToCV specific primerset (ToCV-UP 5'-TCATTAAAACTCAATGGGACCGAG-3' and ToCV-DW 5'-GCGACGT AAATTGAAACCC-3') was negative in all cases. Grafting of symptomatic shoots onto healthy tomato seedlings of cv. Money-maker showed transmission of the virus, as chlorosis appeared on fully expanded leaves of lateral shoots after 6 weeks. The presence of TICV in the graft-inoculated plants was confirmed by RT-PCR. Furthermore, mechanical inoculation to a range of herbaceous test plants did not evoke any virus symptoms, indicating the absence of mechanically transmissible viruses. Although other nonmechanically transmissible viruses cannot be fully excluded, the results together with the symptoms observed, indicate that TICV is the cause of the disease. TICV has been reported from Greece, Italy, Japan, Spain, and the United States, but to our knowledge, this is the first report of TICV in Indonesia. Reference: (1) A. M. Vaira et al. Phytoparasitica 30:290, 2002.

First Report of Pepper mottle virus in Tomato.

In 2000, a breeding company submitted a tomato (Lycopersicon esculentum) sample from Guatemala for diagnosis. The plants showed necrotic lesions on leaves surrounded by some chlorosis, necrotic streaks on stems, and large superficial necrotic lesions on fruits. By mechanical inoculation of plant sap to different plant species, symptoms appeared in Capsicum annuum 'Westlandse Grote Zoete', Lycopersicon esculentum 'Money-maker', Nicotiana benthamiana, N. bigelovii, N. glutinosa, N. hesperis-67A, N. occidentalis-P1, N. tabacum 'White Burley', and Physalis floridana. Systemically infected leaves from N. occidentalis-P1 were used for all further experiments. Leaf dip preparations were analyzed by transmission electron microscopy and revealed the presence of filamentous virus particles typical of a potyvirus. Double-antibody sandwich enzyme-linked immunosorbent assay tests for Potato virus A, V, and Y, Tobacco etch virus, and Wild potato mosaic virus were negative. An antiserum (PepMoV/DSMZ As 0186) to Pepper mottle virus (PepMoV), however, gave a positive reaction. To obtain further evidence for the presence of this virus, the nucleotide sequence of the complete 3' nontranslated region (3NTR) and the 3' terminal part of the coat protein gene (3CPG) was determined using the set of degenerate primers P9502/CPUP (1). The obtained nucleotide sequence (approximately 700 bp) was deposited in GenBank under Accession No. AF440801. It showed 93 to 94% 3NTR and 90 to 93% 3CPG homology with the three sequences of PepMoV from pepper already present in GenBank. The two viruses with the next closest nucleotide sequence homology were Potato virus V and Potato virus Y showing up to 80 and 75% homology with the 3CPG and up to 53 and 48% homology with the 3NTR, respectively. Based on these results, we concluded that the virus isolated from the symptomatic tomato plants was PepMoV. Because of the relatively low homologies with the pepper isolates of PepMoV, this tomato isolate might be a separate strain of the virus. To our knowledge, this is the first report of the occurrence of PepMoV in tomato. Reference: (1) R. A. A. van der Vlugt et al. Phytopathology 89:148, 1999.