Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices—namely, the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson’s correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients’ OSA severity. The high supine percentage of sleep may cause OSA indices’ overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis.

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Insomnia disorder (ID) and obstructive sleep apnea (OSA) with respiratory arousal threshold (ArTH) phenotypes often coexist in patients, presenting similar symptoms. However, the typical diagnosis examinations (in-laboratory polysomnography (lab-PSG) and other alternatives methods may therefore have limited differentiation capacities. Hence, this study established novel models to assist in the classification of ID and low- and high-ArTH OSA. Participants reporting insomnia as their chief complaint were enrolled. Their sleep parameters and body profile were accessed from the lab-PSG database. Based on the definition of low-ArTH OSA and ID, patients were divided into three groups, namely, the ID, low- and high-ArTH OSA groups. Various machine learning approaches, including logistic regression, k-nearest neighbors, naive Bayes, random forest (RF), and support vector machine, were trained using two types of features (Oximetry model, trained with oximetry parameters only; Combined model, trained with oximetry and anthropometric parameters). In the training stage, RF presented the highest cross-validation accuracy in both models compared with the other approaches. In the testing stage, the RF accuracy was 77.53% and 80.06% for the oximetry and combined models, respectively. The established models can be used to differentiate ID, low- and high-ArTH OSA in the population of Taiwan and those with similar craniofacial features.

BackgroundTiming of reproductive events has become central in ecological studies linking success in pollination and seed dispersion to optimizing the probability and periods of encounters with pollinators or dispersers. Obligate plant–insect interactions, especially Ficus–fig wasp mutualisms, offer striking examples of fine-tuned encounter optimization as biological cycles between mutualistic partners are deeply dependent on each other and intertwined over generations. Despite fig flowering phenology being crucial in maintaining Ficus–fig wasp mutualisms, until now, the forces of selection shaping the phenological evolution of dioecious fig trees have received little attention. By conducting a 2-year survey of a population of Ficus benguetensis in Northern Taiwan, we assessed whether environmental factors or other selective pressures shape the phenology of male and female fig trees.ResultsConstraints by mutualistic pollinating wasps and seed dispersers, rather than climatic factors, appeared to mainly shape fig phenology and allometry in F. benguetensis. We identified a new sexual specialization in dioecious fig trees: the position of fig production. We propose that the continuous male fig production on tree trunks can enhance the survival of pollinating fig wasps through faster localization of receptive figs while reducing the mutualistic conflict between the fig and its obligate pollinators. By contrast, in female trees, fig production is massive in summer, located on the twigs of the foliar crown and seem more related to seed dispersal and germination.ConclusionsIdentifying variations in the allometry and phenology of dioecious figs provide valuable insights into how monoecious and dioecious species resolve mutualism conflicts and into the emergence of dioecy in fig trees.Electronic supplementary materialThe online version of this article (doi:10.1186/s40529-015-0113-7) contains supplementary material, which is available to authorized users.

Obstructive sleep apnea (OSA) is a risk factor for neurodegenerative diseases. This study determined whether continuous positive airway pressure (CPAP), which can alleviate OSA symptoms, can reduce neurochemical biomarker levels. Thirty patients with OSA and normal cognitive function were recruited and divided into the control (n = 10) and CPAP (n = 20) groups. Next, we examined their in-lab sleep data (polysomnography and CPAP titration), sleep-related questionnaire outcomes, and neurochemical biomarker levels at baseline and the 3-month follow-up. The paired t-test and Wilcoxon signed-rank test were used to examine changes. Analysis of covariance (ANCOVA) was performed to increase the robustness of outcomes. The Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index scores were significantly decreased in the CPAP group. The mean levels of total tau (T−Tau), amyloid-beta-42 (Aβ42), and the product of the two (Aβ42 × T−Tau) increased considerably in the control group (ΔT−Tau: 2.31 pg/mL; ΔAβ42: 0.58 pg/mL; ΔAβ42 × T−Tau: 48.73 pg2/mL2), whereas the mean levels of T−Tau and the product of T−Tau and Aβ42 decreased considerably in the CPAP group (ΔT−Tau: −2.22 pg/mL; ΔAβ42 × T−Tau: −44.35 pg2/mL2). The results of ANCOVA with adjustment for age, sex, body mass index, baseline measurements, and apnea–hypopnea index demonstrated significant differences in neurochemical biomarker levels between the CPAP and control groups. The findings indicate that CPAP may reduce neurochemical biomarker levels by alleviating OSA symptoms.

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