Minimal effect of long-term clonazepam on cognitive function in patients with isolated RBD

STUDY OBJECTIVES

Despite its widespread use in patients with isolated rapid eye movement sleep behavior disorder (iRBD), the cognitive effect of clonazepam is uncertain. This study aimed to investigate effect of cumulative clonazepam on cognitive function in patients with iRBD.

METHODS

Demographic characteristics, baseline cognitive test, and most recent cognitive test information were collected retrospectively. Based on cumulative clonazepam doses, patients were classified into four subgroups: group 1 < 365 mg (1 mg * 1 year); 365 mg ≤ group 2 < 1,095 mg (1 mg * 3 years); 1,095 mg ≤ group 3 < 2,190 mg (1 mg * 6 years); and group 4 ≥ 2,190 mg. Cognitive test scores were calculated as z-scores adjusted for age, education, and sex.

RESULTS

This study included 101 patients with iRBD (63 males). Groups 1, 2, 3, and 4 had 14, 20, 32, and 35 patients, respectively. In within-group comparisons, follow-up Digit Span Backward test and the Trail Making Test A (TMT-A) scores decreased in group 3, and follow-up TMT-A and the Trail Making Test B scores decreased significantly in group 4. In the multiple regression analysis to determine influential factors on cognitive decline, cumulative clonazepam dose did not show a significant correlation with any cognitive domain. Follow-up cognitive function showed significant correlation only with baseline cognitive function.

CONCLUSIONS

Memory and executive functions tended to decline in patients with iRBD. However, there was no significant effect of cumulative clonazepam. There was no evidence that long-term use of clonazepam was related to cognitive decline in patients with iRBD.

Modest Effects of Neurofeedback-Assisted Meditation Using a Wearable Device on Stress Reduction: A Randomized, Double-Blind, and Controlled Study

BACKGROUND

To evaluate the therapeutic effectiveness and safety of a neurofeedback wearable device for stress reduction.

METHODS

A randomized, double-blind, controlled study was designed. Participants had psychological stress with depression or sleep disturbances. They practiced either neurofeedback-assisted meditation (n = 20; female, 15 [75.0%]; age, 49.40 ± 11.76 years) or neurofeedback non-assisted meditation (n = 18; female, 11 [61.1%]; age, 48.67 ± 12.90 years) for 12 minutes twice a day for two weeks. Outcome variables were self-reported questionnaires, including the Korean version of the Perceived Stress Scale, Beck Depression Inventory-II, Insomnia Severity Index, Pittsburgh Sleep Quality Index, and State Trait Anxiety Index, quantitative electroencephalography (qEEG), and blood tests. Satisfaction with device use was measured at the final visit.

RESULTS

The experimental group had a significant change in PSS score after two weeks of intervention compared with the control group (6.45 ± 0.95 vs. 3.00 ± 5.54, P = 0.037). State anxiety tended to have a greater effect in the experimental group than in the control group (P = 0.078). Depressive mood and sleep also improved in each group, with no significant difference between the two groups. There were no significant differences in stress-related physiological parameters, such as stress hormones or qEEG, between the two groups. Subjective device satisfaction was significantly higher in the experimental group than in the control group (P = 0.008).

CONCLUSION

Neurofeedback-assisted meditation using a wearable device can help improve subjective stress reduction compared with non-assisted meditation. These results support neurofeedback as an effective adjunct to meditation for relieving stress.

TRIAL REGISTRATION

Clinical Research Information Service Identifier: KCT0007413.

Efficacy of cranial electrotherapy stimulation on mood and sense of well-being in people with subclinical insomnia

Cranial electrotherapy stimulation is a non-invasive brain stimulation method characterised by using a microcurrent. The objective of the study was to investigate whether a novel device with a stable supplement of electronic stimulation would improve sleep and the accompanying mood symptoms in people with subclinical insomnia. People who had insomnia symptoms without meeting the criteria for chronic insomnia disorder were recruited and randomly assigned to an active or a sham device group. They were required to use the provided device for 30 min each time, twice a day for 2 weeks. Outcome measures included questionnaires for sleep, depression, anxiety, and quality of life, 4 day actigraphy, and 64-channel electroencephalography. Fifty-nine participants (male 35.6%) with a mean age of 41.1 ± 12.0 years were randomised. Improvement of depression (p = 0.032) and physical well-being (p = 0.041) were significant in the active device group compared with the sham device group. Anxiety was also improved in the active device group, although the improvement was not statistically significant (p = 0.090). Regarding sleep, both groups showed a significant improvement in subjective rating, showing no significant group difference. The change in electroencephalography after the 2 week intervention was significantly different between the two groups, especially for occipital delta (p = 0.008) and beta power (p = 0.012), and temporo-parieto-occipital theta (p = 0.022). In conclusion, cranial electrotherapy stimulation can serve as an adjunctive therapy to ameliorate psychological symptoms and to alter brain activity. The effects of the device in a clinical population and an optimal set of parameters of stimulation should be further investigated.

Effects of cranial electrotherapy stimulation on improving depressive symptoms in people with stress: A randomized, double-blind controlled study

BACKGROUND

Cranial electrotherapy stimulation (CES) is a form of neurostimulation that delivers alternating microcurrent via electrodes on the head. We investigated the effectiveness of CES in reducing stress.

METHODS

Participants who experienced subjective stress combined with subclinical depression or insomnia were recruited based on interviews and questionnaires. The subjects were randomly assigned to the active CES or sham groups and asked to use the device for 30 min twice a day for three weeks. Psychological rating scales, quantitative electroencephalography (QEEG), and serial salivary cortisol levels were measured before and after the intervention.

RESULTS

Sixty-two participants (58 females, mean age = 47.3 ± 8.2 years) completed the trial. After intervention, the depression scores improved significantly to a nearly normal level (Beck depression inventory-II, 31.3 ± 11.6 to 10.8 ± 7.2, p < 0.001) in the CES group, which were greater improvement compared to the sham group (p = 0.020). There were significant group-by-visit interactions in absolute delta power in the temporal area (p = 0.033), and theta (p = 0.038), beta (p = 0.048), and high beta power (p = 0.048) in the parietal area. CES led to a flattening of the cortisol slope (p = 0.011) and an increase in bedtime cortisol (p = 0.036) compared to the sham group.

LIMITATIONS

Bias may have been introduced during the process because device use and sample collection were self-conducted by participants at home.

CONCLUSIONS

CES can alleviate depressive symptoms and stress response, showing a potential as an adjunctive therapy for stress.

[Microanatomy and functional MRI study of arcuate fasciculus and superior longitudinal fasciculus]

Objectives: To explore the microanatomy and functional MRI(fMRI) of arcuate fasciculus(AF) and superior longitudinal fasciculus(SLF),and to analyze their functions. Methods: Ten normal adult cadaveric head specimens (20 cerebral hemispheres) were fixed with 10% methanal at the Translational Research Institute for Neurological Disorders of the Wannan Medical Collegefrom February to December 2022.The Klingler fiber dissection technique was utilized to perform white matter fiber dissection,with a magnification ranging from 6 to 40.The study focused on the microanatomical structures of the AF and SLF,aiming to explore their relationships with deep brain fibers.Furthermore, six healthy adult volunteers who underwent fMRI of the brain were included.The collected diffusion tensor imaging (DTI) data were processed and integrated with the microanatomical findings for a comprehensive analysis. Results: After removing the gray matter of the cerebral cortex,the superficial U fibers were exposed.The long association fibers that beneath the U fibers were the AF and SLF,which were the main long association fibers in the superficial layers of the brain.The AF could be divided into dorsal and ventral parts,while the SLF could be divided into Ⅰ,Ⅱ,and Ⅲ.SLF Ⅰ lied within the upper bank of the cingulate sulcus,travels medial to the callosal sulcus.The SLF Ⅱ,Ⅲ,and the AF were located on the lateral surface of the brain.By removing the gray matter of the insular cortex and the extreme capsule,exposing the external capsule and claustrum.Subsequently,the AF and SLF Ⅱ,Ⅲ were dissected,revealing the corona radiata and sagittal stratum,along with other deep brain fibers.During the dissection,it was observed that there was a close connection between the AF,SLF Ⅱ,and the deep brain fibers.Furthermore,in the regions above the lateral fissure of the cerebral hemisphere,there was no direct connection of long association fibers between the gray matter cortex and the deep U fibers in the coronal plane.These findings were further supported by DTI studies. Conclusions: The AF and SLF are the major long association fibers that located in the superficial layers of the brain,and closely connect to the gray matter cortex and U fibers,even closely relate with deep brain fibers.In the regions above the lateral fissure of the hemisphere,only the AF and SLF Ⅱ and Ⅲ serve as superficial long association fibers in the anterior-posterior direction.These fibers are likely involved in the transmission of brain functional information between the top and bottom gray matter cortex in the coronal plane above the lateral fissure.

Prediction of Sleep Stages Via Deep Learning Using Smartphone Audio Recordings in Home Environments: Model Development and Validation

BACKGROUND

The growing public interest and awareness regarding the significance of sleep is driving the demand for sleep monitoring at home. In addition to various commercially available wearable and nearable devices, sound-based sleep staging via deep learning is emerging as a decent alternative for their convenience and potential accuracy. However, sound-based sleep staging has only been studied using in-laboratory sound data. In real-world sleep environments (homes), there is abundant background noise, in contrast to quiet, controlled environments such as laboratories. The use of sound-based sleep staging at homes has not been investigated while it is essential for practical use on a daily basis. Challenges are the lack of and the expected huge expense of acquiring a sufficient size of home data annotated with sleep stages to train a large-scale neural network.

OBJECTIVE

This study aims to develop and validate a deep learning method to perform sound-based sleep staging using audio recordings achieved from various uncontrolled home environments.

METHODS

To overcome the limitation of lacking home data with known sleep stages, we adopted advanced training techniques and combined home data with hospital data. The training of the model consisted of 3 components: (1) the original supervised learning using 812 pairs of hospital polysomnography (PSG) and audio recordings, and the 2 newly adopted components; (2) transfer learning from hospital to home sounds by adding 829 smartphone audio recordings at home; and (3) consistency training using augmented hospital sound data. Augmented data were created by adding 8255 home noise data to hospital audio recordings. Besides, an independent test set was built by collecting 45 pairs of overnight PSG and smartphone audio recording at homes to examine the performance of the trained model.

RESULTS

The accuracy of the model was 76.2% (63.4% for wake, 64.9% for rapid-eye movement [REM], and 83.6% for non-REM) for our test set. The macro F1-score and mean per-class sensitivity were 0.714 and 0.706, respectively. The performance was robust across demographic groups such as age, gender, BMI, or sleep apnea severity (accuracy 73.4%-79.4%). In the ablation study, we evaluated the contribution of each component. While the supervised learning alone achieved accuracy of 69.2% on home sound data, adding consistency training to the supervised learning helped increase the accuracy to a larger degree (+4.3%) than adding transfer learning (+0.1%). The best performance was shown when both transfer learning and consistency training were adopted (+7.0%).

CONCLUSIONS

This study shows that sound-based sleep staging is feasible for home use. By adopting 2 advanced techniques (transfer learning and consistency training) the deep learning model robustly predicts sleep stages using sounds recorded at various uncontrolled home environments, without using any special equipment but smartphones only.

The effect of proto-type wearable light-emitting devices on serum 25-hydroxyvitamin D levels in healthy adults: a 4-week randomized controlled trial

BACKGROUND

Many people in modern society have insufficient exposure to ultraviolet B (UVB) sunlight, which may lead to vitamin D deficiency. We aimed to investigate the effect of a proto-type wearable light-emitting diode (LED) device emitting UVB light on serum 25-hydroxyvitamin D levels.

METHODS

A total of 136 healthy adults were randomly assigned to receive either an active device emitting UVB light with a peak wavelength of 285 nm (n = 64) or a sham device emitting visible light (n = 72). All participants wore the device for a total of two minutes, one minute on each forearm, every day for 4 weeks. Serum 25-hydroxyvitamin D levels were assessed at baseline, 2, and 4 weeks of intervention, and 2 weeks after the end of the intervention.

RESULTS

A significant difference was found between the experimental and control groups in changes in serum 25-hydroxyvitamin D levels from baseline after two (0.25 ± 3.10 ng/mL vs. -1.07 ± 2.68 ng/mL, p = 0.009) and 4 weeks of intervention (0.75 ± 3.98 ng/mL vs. -1.75 ± 3.04 ng/mL, p < 0.001). In the experimental group, the dropout rate due to mild, self-limiting adverse skin reactions was 11.8% (9/76). The mean total 25-hydroxyvitamin D production after UVB exposure was estimated at 0.031 ng/mL per 1 cm² of skin area.

CONCLUSIONS

A prototype wearable LED UVB device was effective for improving 25-hydroxyvitamin D status. The development of a safer wearable LED device for phototherapy may provide a novel daily, at-home option for vitamin D supplementation.

Clinical manifestation of patients with isolated rapid eye movement sleep behavior disorder after modest-to-long disease duration

Study Objectives

Patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD) are known to be at risk of neurodegenerative diseases but the time process of neurodegeneration remains unclear and its ethnic difference is rarely discussed. The objective of this study was to investigate the clinical manifestation of iRBD according to disease duration in a Korean cohort.

Methods

Patients who had been diagnosed with iRBD for at least 5 years were tracked and those currently remaining as iRBD were invited for motor, autonomic, olfactory, color discrimination, and cognitive tests. Cross-sectional comparison between patients with iRBD with modest disease duration (5–9.9 years) and long disease duration (≥10 years) was conducted.

Results

There were total of 198 patients with iRBD (135 males, 68.2%) tracked, whose average age at diagnosis was 65.9 years. Thirty-three had developed parkinsonism and 17 had developed dementia, resulting in a phenoconversion risk of 35.7% at 10 years. Hazard rate showed a gradually increasing trend over time, beginning from 2.1 conversions per year to 8.5 at 10 years. Patients with iRBD with a long disease duration (n = 19) had slightly higher motor scores than those with a modest duration (n = 82). However, they showed no difference in the frequency of motor abnormality or other clinical markers.

Conclusions

There is a possible racial or geographical difference of phenoconversion risk. The progression of neurodegeneration might be very subtle in that patients with iRBD with longer disease duration do not necessarily show higher frequency of neurodegeneration markers.

Age-Limited Effects of Low-Frequency Transcutaneous Electric Nerve Stimulation on Insomnia: A 4-Week Multi-Center, Randomized Controlled Study

OBJECTIVE

Insomnia disorder is a common condition with considerable harmful effects on health. We investigated the therapeutic efficacy and safety of low-frequency transcutaneous electric nerve stimulation (LF-TENS) as an alternative treatment option for insomnia disorder.

METHODS

A 4-week, multi-center, randomized controlled study was conducted. A total of 160 individuals aged 40 to 80 years with insomnia disorder were included and randomized to the experimental group receiving active device (n=81) or control group receiving sham device (n=79). Both groups used the device for four weeks, more than five days a week. The participants also completed pre- and post-intervention assessment with questionnaires, sleep diaries, wrist actigraphy, and blood tests.

RESULTS

There was no significant between-group difference in the changes of mood and sleep parameters and blood test results among the two study groups. Meanwhile, in the exploratory sub-group analysis of patients aged over 60 years, the experimental group showed better improvement after intervention in the change of Pittsburgh Sleep Quality Index (PSQI) score (-2.63±3.25 vs. -1.20±2.28, p=0.039; Cohen's d=0.99 vs. 0.45) and blood cortisol level (-1.65±3.37 μg/dL vs. -0.16±3.49 μg/dL, p=0.007; Cohen's d=0.56 vs. 0.05). In addition, no serious adverse reaction occurred during the study period in both groups.

CONCLUSION

The effect of LF-TENS was limited to older patients aged over 60 years, which might be related to the modulation of hypothalamic-pituitary-adrenal axis activity.

0348 Sleep Staging Using End-to-End Deep Learning Model Based on Nocturnal Sound for Smartphones

Introduction

Convenient sleep tracking with mobile devices such as smartphones is desirable for people who want to easily objectify their sleep. The objective of this study was to introduce a deep learning model for sound-based sleep staging using audio data recorded with smartphones during sleep.

Methods

Two different audio datasets were used. One (N = 1,154) was extracted from polysomnography (PSG) data and the other (N = 327) was recorded using a smartphone during PSG from independent subjects. The performance of sound-based sleep staging would always depend on the quality of the audio. In practical conditions (non-contact and smartphone microphones), breathing and body movement sounds during night are so weak that the energy of such signals is sometimes smaller than that of ambient noise. The audio was converted into Mel spectrogram to detect latent temporal frequency patterns of breathing and body movement sound from ambient noise. The proposed neural network model consisted of two sub-models. The first sub-model extracted features from each 30-second epoch Mel spectrogram and the second one classified sleep stages through inter-epoch analysis of extracted features.

Results

Our model achieved 70 % epoch-by-epoch agreement for 4-class (wake, light, deep, rapid eye movement) stage classification and robust performance across various signal-to-noise conditions. More precisely, the model was correct in 77% of wake, 73% of light, 46% of deep, and 66% of REM. The model performance was not considerably affected by existence of sleep apnea but degradation observed with severe periodic limb movement. External validation with smartphone dataset also showed 68 % epoch-by-epoch agreement. Compared with some commercially available sleep trackers such as Fitbit Alta HR (0.6325 in mean per-class sensitivity) and SleepScore Max (0.565 in mean per-class sensitivity), our model showed superior performance in both PSG audio (0.655 in mean per-class sensitivity) and smartphone audio (0.6525 in mean per-class sensitivity).

Conclusion

To the best of our knowledge, this is the first end (Mel spectrogram-based feature extraction)-to-end (sleep staging) deep learning model that can work with audio data in practical conditions. Our proposed deep learning model of sound-based sleep staging has potential to be integrated in smartphone application for reliable at-home sleep tracking.

Support (If Any)

 

End-to-End Sleep Staging Using Nocturnal Sounds from Microphone Chips for Mobile Devices

PURPOSE

Nocturnal sounds contain numerous information and are easily obtainable by a non-contact manner. Sleep staging using nocturnal sounds recorded from common mobile devices may allow daily at-home sleep tracking. The objective of this study is to introduce an end-to-end (sound-to-sleep stages) deep learning model for sound-based sleep staging designed to work with audio from microphone chips, which are essential in mobile devices such as modern smartphones.

PATIENTS AND METHODS

Two different audio datasets were used: audio data routinely recorded by a solitary microphone chip during polysomnography (PSG dataset, N=1154) and audio data recorded by a smartphone (smartphone dataset, N=327). The audio was converted into Mel spectrogram to detect latent temporal frequency patterns of breathing and body movement from ambient noise. The proposed neural network model learns to first extract features from each 30-second epoch and then analyze inter-epoch relationships of extracted features to finally classify the epochs into sleep stages.

RESULTS

Our model achieved 70% epoch-by-epoch agreement for 4-class (wake, light, deep, REM) sleep stage classification and robust performance across various signal-to-noise conditions. The model performance was not considerably affected by sleep apnea or periodic limb movement. External validation with smartphone dataset also showed 68% epoch-by-epoch agreement.

CONCLUSION

The proposed end-to-end deep learning model shows potential of low-quality sounds recorded from microphone chips to be utilized for sleep staging. Future study using nocturnal sounds recorded from mobile devices at home environment may further confirm the use of mobile device recording as an at-home sleep tracker.

Modeling and optimization of process parameters of biofilm reactor for wastewater treatment

The efficiency of heavy metal in biofilm reactors depends on absorption process parameters, and those relationships are complicated. This study explores artificial neural networks (ANNs) feasibility to correlate the biofilm reactor process parameters with absorption efficiency. The heavy metal removal and turbidity were modeled as a function of five process parameters, namely pH, temperature(°C), feed flux(ml/min), substrate flow(ml/min), and hydraulic retention time(h). We developed a standalone ANN software for predicting and analyzing the absorption process in handling industrial wastewater. The model was tested extensively to confirm that the predictions are reasonable in the context of the absorption kinetics principles. The model predictions showed that the temperature and pH values are the most influential parameters affecting absorption efficiency and turbidity.

Differences in sleep measures and waking electroencephalography of patients with insomnia according to age and sex

STUDY OBJECTIVES

Sleep characteristics are known to be different according to age and sex. The objective of this study was to investigate differences in sleep parameters and quantitative electroencephalography of patients with insomnia according to age and sex.

METHODS

Patients with insomnia disorder ages 40-79 years were recruited. Each participant was assessed with the Pittsburgh Sleep Quality Index, 4-day wrist actigraphy, and quantitative electroencephalography derived from a 64-channel electroencephalogram system. These variables were compared between age groups (40-64 years vs 65-79 years) and sexes.

RESULTS

Among 173 participants, 61 (35%) were ages 65-79 years and 64 (35%) were males. The older group reported shorter (P = .009) total sleep time than the middle-aged group based on the Pittsburgh Sleep Quality Index, while women slept longer than men based on actigraphy (P = .040). Regarding electroencephalography, women had higher relative beta power than men (P = .006). Older patients showed slower dominant occipital frequency than younger patients (P = .008). The age effect was more noticeable on both clinical variables and quantitative electroencephalography for women. Compared with younger women, older women reported shorter total sleep time in the Pittsburgh Sleep Quality Index (P = .025), underestimated their sleep time (Pittsburgh Sleep Quality Index total sleep time/actigraphic total sleep time, P = .034), and showed reduced alpha power in the frontal area (P = .009).

CONCLUSIONS

Clinicians should be aware of the age and sex difference on manifestation of insomnia, which may further impact an individual's behaviors, such as staying in bed for a longer time or seeking sleep aids.

Confidence-Based Framework Using Deep Learning for Automated Sleep Stage Scoring

STUDY OBJECTIVES

Automated sleep stage scoring is not yet vigorously used in practice because of the black-box nature and the risk of wrong predictions. The objective of this study was to introduce a confidence-based framework to detect the possibly wrong predictions that would inform clinicians about which epochs would require a manual review and investigate the potential to improve accuracy for automated sleep stage scoring.

METHODS

We used 702 polysomnography studies from a local clinical dataset (SNUBH dataset) and 2804 from an open dataset (SHHS dataset) for experiments. We adapted the state-of-the-art TinySleepNet architecture to train the classifier and modified the ConfidNet architecture to train an auxiliary confidence model. For the confidence model, we developed a novel method, Dropout Correct Rate (DCR), and the performance of it was compared with other existing methods.

RESULTS

Confidence estimates (0.754) reflected accuracy (0.758) well in general. The best performance for differentiating correct and wrong predictions was shown when using the DCR method (AUROC: 0.812) compared to the existing approaches which largely failed to detect wrong predictions. By reviewing only 20% of epochs that received the lowest confidence values, the overall accuracy of sleep stage scoring was improved from 76% to 87%. For patients with reduced accuracy (ie, individuals with obesity or severe sleep apnea), the possible improvement range after applying confidence estimation was even greater.

CONCLUSION

To the best of our knowledge, this is the first study applying confidence estimation on automated sleep stage scoring. Reliable confidence estimates by the DCR method help screen out most of the wrong predictions, which would increase the reliability and interpretability of automated sleep stage scoring.

The Effects of Continuation-Maintenance Electroconvulsive Therapy on Reducing Hospital Re-Admissions in Patients with Treatment-Resistant Schizophrenia

OBJECTIVE

Continuation-maintenance electroconvulsive therapy (C/M-ECT) is used to prevent relapse or recurrence in patients with severe mental illnesses. We aimed to investigate the effect of C/M-ECT on reducing hospital re-admissions in patients with treatment-resistant schizophrenia.

METHODS

We applied a mirror-image design by retrospectively examining re-hospitalization rates of 18 patients with schizophrenia spectrum disorders. We compared the numbers of psychiatric admissions during the actual period over which C/M-ECT was administered with the same period prior to the beginning of C/M-ECT.

RESULTS

The number of psychiatric admissions was reduced significantly during C/M-ECT (0.33±0.77) compared with that of the same period prior to C/M-ECT (2.67±1.33) (Wilcoxon signed rank Z=-3.663; p＜0.001).

CONCLUSION

This finding shows that C/M-ECT augmentation could successfully reduce the re-hospitalization rates in patients with treatment-resistant schizophrenia.

Isolation and characterization of novel microsatellites for Abies koreana and A. nephrolepis (Pinaceae)

Abies koreana is an endemic and rare species from Korea and is classified as endangered by the International Union for Conservation of Nature. Although the genetic diversity assessment for current population of A. koreana needs to be performed urgently, no microsatellite markers have been developed for this species. In the present study, we developed 22 novel polymorphic microsatellite loci and the characteristics of these loci were determined in A. koreana as well as in Abies nephrolepis, the most closely related species, and these loci were compared with previously reported microsatellite markers developed for the Abies genus. Genomic sequence (161 Mbp; 325,776 reads) was obtained from one individual of A. koreana using Roche 454 GS-FLX Titanium sequencing and 19,258 repeat motifs were identified from it. A total of 288 primer pairs with high copy numbers of di-repeat motifs were evaluated for amplification in A. koreana and A. nephrolepis. A total of 71 primer pairs successfully amplified fragments, of which 22 showed polymorphisms in A. koreana and A. nephrolepis. The average expected diversity was 0.767 and 0.717 in A. koreana and A. nephrolepis, respectively; these heterozygosity levels were moderate compared to the previously reported microsatellite loci from Abies species. This is the first set of microsatellite markers developed for A. koreana as well as A. nephrolepis and further population genetic studies of both species and genetic delimitation can be carried out for the species conservation and management.

Effect of dietary supplementation of procyanidin on growth performance and immune response in pigs

This study was performed to determine the effect of dietary supplementation of procyanidin on growth performance, blood characteristics, and immune function in growing pigs. In experiment 1 (Exp. 1), thirty-two crossbred pigs with an initial BW of 19.2±0.3 kg were allocated into 4 treatments for an 8-wk experiment: i) CON (basal diet), ii) MOS 0.1 (basal diet+0.1% mannanoligosaccharide), iii) Pro-1 (basal diet+0.01% procyanidin), and iv) Pro-2 (basal diet+0.02% procyanidin). Pigs fed Pro-1 and Pro-2 diets had greater (p<0.05) gain:feed ratio compared with those fed CON or MOS 0.1 diets. Serum creatinine concentration was less (p<0.05) in Pro-2 treatment than those in CON, MOS 0.1 and Pro-1 treatments. In Exp. 2, twelve pigs (BW 13.4±1.3 kg) received basal diet with i) 0 (CON), ii) 0.02% (Pro-0.02%), and iii) 0.04% procyanidin (Pro-0.04%) for 4 wk. Concentration of platelets was lower (p<0.05) in the Pro-0.04% group compared to CON at 24 h after lipopolysaccharide (LPS) challenge. In addition, secretion of cytokines from cultured peripheral blood mononuclear cells (PBMC) in the presence or absence of procyanidin was examined. The levels of interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α were lower (p<0.05) in Pro (LPS-stimulated PBMCs+procyanidin) than those in CON (LPS-stimulated PBMCs+PBS) at 4 h after LPS challenge. These data suggest that dietary addition of procyanidin improves feed efficiency and anti-inflammatory cytokines of pigs.

Pepper gene encoding a basic class II chitinase is inducible by pathogen and ethephon

A chitinase cDNA clone (designated CAChi2) was isolated from the cDNA library of pepper leaves infected with Xanthomonas campestris pv. vesicatoria. The 1004-bp full-length CAChi2 cDNA encodes a basic chitinase with an N-terminal 24 amino acid signal peptide followed by a catalytic region. An analysis of its sequence indicates that CAChi2 is a class II chitinase, because it does not have chitin-binding domain and C-terminal extension sequences. The deduced amino acid sequence of CAChi2 has a high level of identity with class II chitinases from potato, tomato, tobacco and petunia. Southern analysis demonstrated that the CAChi2 chitinase is encoded by a single or two copy genes in the pepper genome. Following X. campestris pv. vesicatoria or Phytophthora capsici infection, the CAChi2 chitinase mRNA was more highly expressed in the incompatible interaction, compared to expression in the compatible interaction. Treatment with ethylene-releasing ethephon resulted in a strong accumulation of the transcripts in the leaves. In contrast, DL-beta-amino-n-butyric acid, salicylic acid and methyl jasmonate were not effective in inducing CAChi2 transcripts in pepper leaves.

Concomitant lichen scrofulosorum and erythema induratum

We describe a patient in whom two tuberculids, lichen scrofulosorum, and erythema induratum occurred simultaneously. The clinical and histopathologic features were characteristic and a Mantoux test showed a positive reaction. There was no extracutaneous focus of tuberculosis. Polymerase chain reaction for mycobacteria in the skin lesions was negative, but her lesions responded rapidly to antituberculous chemotherapy.

MR566A and MR566B, new melanin synthesis inhibitors produced by Trichoderma harzianum. II. Physico-chemical properties and structural elucidation

New melanin synthesis inhibitors (MR566A and B) and six related known isocyanocyclopentenes were isolated from the fermentation broth of Trichoderma harzianum, and their structures were elucidated by spectroscopic methods. The structures of novel isocyanides, MR566A (1) and B (2), were elucidated as 1-(3-chloro-1,2-dihydroxy-4-isocyano-4-cyclopenten-1-yl)etha nol, 1-(1,2,3-trihydroxy-3-isocyano-4-cyclopenten-1-yl)ethanol, respectively. The structure of novel oxazole, MR93B (9), was elucidated as 4-[(1Z)-3-hydroxy-2-hydroxymethyl-1-propen-1-yl]oxazole.

Determination of phenolalkylamines, narcotic analgesics, and beta-blockers by gas chromatography/mass spectrometry

An analytical procedure for determination of phenolalkylamines, narcotic analgesics, and beta-blockers in urine by gas chromatography/mass spectrometry (GC/MS) is described. The detection of phenolalkylamines, narcotic analgesics, and beta-blockers is based on acid hydrolysis, liquid-liquid extraction, and selective derivatization. For screening of phenolalkylamines the m/e 179 and 267 ions were monitored by GC/MS. With narcotic analgesics, the extracted ion corresponded to the molecular ion (M+) of the drug and two additional characteristic ions. Beta-blockers were analyzed as the selectively derivatized forms of the parent molecule and its metabolites by GC/MS with selected ion monitoring. The ions monitored for screening of beta-blockers containing an isopropylamine group were m/e 284 and 129 ions. The ion at m/e 86 was monitored to characterize the tert-butylamine group of beta-blockers.

Demonstration of opsonic and protective activity of human cord sera against type III group B streptococcus that are independent of type-specific antibody

In an effort to further understand the host defense against group B streptococcus (GBS), we examined 71 human cord sera for their content of type III GBS IgG antibody by enzyme-linked immunosorbent assay and correlated the results with opsonic and protective activity against type III GBS. Most cord sera (67%) containing greater than 0.1 microgram/ml of type III GBS IgG antibody promoted phagocytosis and killing in vitro and protection against type III GBS in neonatal rats. However, 26% of cord sera containing less than 0.1 microgram/ml of type III IgG antibody exhibited similar activity in vitro and in vivo against type III GBS. This opsonic and protective activity was retained in IgG fraction of whole serum, and was not directly associated with complement activity or with fibronectin. Further studies are needed to understand the mechanisms responsible for the opsonic and protective activity of some cord sera against type III GBS that may be independent of antibody to the type-specific polysaccharide antigen.