In Vivo Evaluation of α7 Nicotinic Acetylcholine Receptor Agonists [11C]A-582941 and [11C]A-844606 in Mice and Conscious Monkeys

BACKGROUND: The alpha7 nicotinic acetylcholine receptors (nAChRs) play an important role in the pathophysiology of neuropsychiatric diseases such as schizophrenia and Alzheimer's disease. The goal of this study was to evaluate the two carbon-11-labeled alpha7 nAChR agonists [(11)C]A-582941 and [(11)C]A-844606 for their potential as novel positron emission tomography (PET) tracers. METHODOLOGY/PRINCIPAL FINDINGS: The two tracers were synthesized by methylation of the corresponding desmethyl precursors using [(11)C]methyl triflate. Effects of receptor blockade in mice were determined by coinjection of either tracer along with a carrier or an excess amount of a selective alpha7 nAChR agonist (SSR180711). Metabolic stability was investigated using radio-HPLC. Dynamic PET scans were performed in conscious monkeys with/without SSR180711-treatment. [(11)C]A-582941 and [(11)C]A-844606 showed high uptake in the mouse brain. Most radioactive compounds in the brain were detected as an unchanged form. However, regional selectivity and selective receptor blockade were not clearly observed for either compound in the mouse brain. On the other hand, the total distribution volume of [(11)C]A-582941 and [(11)C]A-844606 was high in the hippocampus and thalamus but low in the cerebellum in the conscious monkey brain, and reduced by pretreatment with SSR180711. CONCLUSIONS/SIGNIFICANCE: A nonhuman primate study suggests that [(11)C]A-582941 and [(11)C]A-844606 would be potential PET ligands for imaging alpha7 nAChRs in the human brain

Prevalence of childhood obstructive sleep apnea syndrome and its role in daytime sleepiness

ObjectivesTo investigate childhood obstructive sleep apnea syndrome (OSAS) and its role in daytime sleepiness among school-age children.MethodsA questionnaire survey was conducted with 25,211 children aged 6–15 (mean, 10.39) years attending 148 elementary and 71 middle schools in 10 prefectures across Japan and their parents. Questions concerned 4 sleep habit items (bedtime, sleep onset latency, wake time after sleep onset, wake-up time) and 4 sleep disorder items (loud snoring, snorts/gasps, breathing pauses, seems very sleepy in the daytime). Total sleep time (TST) was calculated with sleep habits. Severe possible OSAS (p-OSAS) was defined as having loud snoring, snorts and gasps, or breathing pauses “frequently” (≥ 5 times per week), and mild p-OSAS was rated as having any of these “sometimes” (2–4 times per week). Severe daytime sleepiness was defined as seeming very sleepy “frequently” and mild daytime sleepiness as seeming very sleepy “sometimes”.ResultsMean prevalence of mild to severe p-OSAS and severe p-OSAS in children across all grade levels was 9.5% and 1.6%, respectively. p-OSAS was particularly prevalent in children at lower elementary levels, decreasing with advancing grade levels. Prevalence of mild and severe daytime sleepiness was 6.1% and 0.9%, respectively, among all children (7.0%). Prevalence of daytime sleepiness increased with advancing grade levels, particularly in middle-school level. Average TST was 8.4 ± 2.2 h in both elementary and middle-school levels, and decreased as grades advanced, particularly in middle-school levels. Multivariate logistic regression analysis showed that middle-school level, TST < 8 h, and p-OSAS were independent factors for daytime sleepiness. Strong correlations were found between severe daytime sleepiness and severe p-OSAS or TST < 6 h, and between daytime sleepiness and loud snoring or breathing pauses.Conclusionp-OSAS may be an independent factor influencing daytime sleepiness in school-age children. Loud snoring and breathing pauses could be clinical markers for children with severe daytime sleepiness

Prevalence of childhood obstructive sleep apnea syndrome and its role in daytime sleepiness

Objectives To investigate childhood obstructive sleep apnea syndrome (OSAS) and its role in daytime sleepiness among school-age children. Methods A questionnaire survey was conducted with 25,211 children aged 6-15 (mean, 10.39) years attending 148 elementary and 71 middle schools in 10 prefectures across Japan and their parents. Questions concerned 4 sleep habit items (bedtime, sleep onset latency, wake time after sleep onset, wake-up time) and 4 sleep disorder items (loud snoring, snorts/gasps, breathing pauses, seems very sleepy in the daytime). Total sleep time (TST) was calculated with sleep habits. Severe possible OSAS (p-OSAS) was defined as having loud snoring, snorts and gasps, or breathing pauses frequently (>= 5 times per week), and mild p-OSAS was rated as having any of these sometimes (2-4 times per week). Severe daytime sleepiness was defined as seeming very sleepy frequently and mild daytime sleepiness as seeming very sleepy sometimes. Results Mean prevalence of mild to severe p-OSAS and severe p-OSAS in children across all grade levels was 9.5% and 1.6%, respectively. p-OSAS was particularly prevalent in children at lower elementary levels, decreasing with advancing grade levels. Prevalence of mild and severe daytime sleepiness was 6.1% and 0.9%, respectively, among all children (7.0%). Prevalence of daytime sleepiness increased with advancing grade levels, particularly in middle-school level. Average TST was 8.4 +/- 2.2 h in both elementary and middle-school levels, and decreased as grades advanced, particularly in middle-school levels. Multivariate logistic regression analysis showed that middle-school level, TST < 8 h, and p-OSAS were independent factors for daytime sleepiness. Strong correlations were found between severe daytime sleepiness and severe p-OSAS or TST < 6 h, and between daytime sleepiness and loud snoring or breathing pauses. Conclusion p-OSAS may be an independent factor influencing daytime sleepiness in school-age children. Loud snoring and breathing pauses could be clinical markers for children with severe daytime sleepiness

Prediction of stroke patients’ bedroom-stay duration: machine-learning approach using wearable sensor data

Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for activity outside their bedrooms. To address this issue, it is necessary to record the duration of stroke patients staying in their bedrooms, but it is impractical for medical providers to do this manually during their daily work of providing care. Although an automated approach using wearable devices and access points is more practical, implementing these access points into medical facilities is costly. However, when combined with machine learning, predicting the duration of stroke patients staying in their bedrooms is possible with reduced cost. We assessed using machine learning to estimate bedroom-stay duration using activity data recorded with wearable devices.Method: We recruited 99 stroke hemiparesis inpatients and conducted 343 measurements. Data on electrocardiograms and chest acceleration were measured using a wearable device, and the location name of the access point that detected the signal of the device was recorded. We first investigated the correlation between bedroom-stay duration measured from the access point as the objective variable and activity data measured with a wearable device and demographic information as explanatory variables. To evaluate the duration predictability, we then compared machine-learning models commonly used in medical studies.Results: We conducted 228 measurements that surpassed a 90% data-acquisition rate using Bluetooth Low Energy. Among the explanatory variables, the period spent reclining and sitting/standing were correlated with bedroom-stay duration (Spearman’s rank correlation coefficient (R) of 0.56 and −0.52, p &lt; 0.001). Interestingly, the sum of the motor and cognitive categories of the functional independence measure, clinical indicators of the abilities of stroke patients, lacked correlation. The correlation between the actual bedroom-stay duration and predicted one using machine-learning models resulted in an R of 0.72 and p &lt; 0.001, suggesting the possibility of predicting bedroom-stay duration from activity data and demographics.Conclusion: Wearable devices, coupled with machine learning, can predict the duration of patients staying in their bedrooms. Once trained, the machine-learning model can predict without continuously tracking the actual location, enabling more cost-effective and privacy-centric future measurements

Conductive Polymer Combined Silk Fiber Bundle for Bioelectrical Signal Recording

Electrode materials for recording biomedical signals, such as electrocardiography (ECG), electroencephalography (EEG) and evoked potentials data, are expected to be soft, hydrophilic and electroconductive to minimize the stress imposed on living tissue, especially during long-term monitoring. We have developed and characterized string-shaped electrodes made from conductive polymer with silk fiber bundles (thread), which offer a new biocompatible stress free interface with living tissue in both wet and dry conditions

[11C]CHIBA-1001 as a Novel PET Ligand for α7 Nicotinic Receptors in the Brain: A PET Study in Conscious Monkeys

BACKGROUND: The alpha7 nicotinic acetylcholine receptors (nAChRs) play an important role in the pathophysiology of neuropsychiatric diseases such as schizophrenia and Alzheimer's disease. However, there are currently no suitable positron emission tomography (PET) radioligands for imaging alpha7 nAChRs in the intact human brain. Here we report the novel PET radioligand [11C]CHIBA-1001 for in vivo imaging of alpha7 nAChRs in the non-human primate brain. METHODOLOGY/PRINCIPAL FINDINGS: A receptor binding assay showed that CHIBA-1001 was a highly selective ligand at alpha7 nAChRs. Using conscious monkeys, we found that the distribution of radioactivity in the monkey brain after intravenous administration of [11C]CHIBA-1001 was consistent with the regional distribution of alpha7 nAChRs in the monkey brain. The distribution of radioactivity in the brain regions after intravenous administration of [11C]CHIBA-1001 was blocked by pretreatment with the selective alpha7 nAChR agonist SSR180711 (5.0 mg/kg). However, the distribution of [11C]CHIBA-1001 was not altered by pretreatment with the selective alpha4beta2 nAChR agonist A85380 (1.0 mg/kg). Interestingly, the binding of [11C]CHIBA-1001 in the frontal cortex of the monkey brain was significantly decreased by subchronic administration of the N-methyl-D-aspartate (NMDA) receptor antagonist phencyclidine (0.3 mg/kg, twice a day for 13 days); which is a non-human primate model of schizophrenia. CONCLUSIONS/SIGNIFICANCE: The present findings suggest that [11C]CHIBA-1001 could be a novel useful PET ligand for in vivo study of the receptor occupancy and pathophysiology of alpha7 nAChRs in the intact brain of patients with neuropsychiatric diseases such as schizophrenia and Alzheimer's disease