Yuyu Wang

Neuroptera (lacewings) and allied orders Megaloptera (dobsonflies, alderflies) and Raphidioptera (snakeflies) are predatory insects and together make up the clade Neuropterida. The higher-level relationships within Neuropterida have historically been widely disputed with multiple competing hypotheses. Moreover, the evolution of important biological innovations among various Neuropterida families, such as the origin, timing and direction of transitions between aquatic and terrestrial habitats of larvae, remains poorly understood. To investigate the origin and diversification of lacewings and their allies, we undertook phylogenetic analyses of mitochondrial genomes of all families of Neuropterida using Bayesian inference, maximum likelihood and maximum parsimony methods. We present a robust, fully resolved phylogeny and divergence time estimation for Neuropterida with strong statistical support for almost all nodes. Mitochondrial sequence data are typified by significant compositional heterogeneity across lineages, and parsimony and models assuming homogeneous rates did not recover Neuroptera as monophyletic. Only a model accounting for compositional heterogeneity (i.e. CAT-GTR) recovered all orders of Neuropterida as monophyletic. Significant findings of the mitogenomic phylogeny include recovering Raphidioptera as sister to Megaloptera plus Neuroptera. The sister family of all other lacewings are the dusty-wings (Coniopterygidae), rather than Nevrorthidae. Nevrorthidae are instead returned to their traditional position as the sister group of the spongilla-flies (Sisyridae) and closely related to Osmylidae. Our divergence time analysis indicates that the Mesozoic was indeed a 'golden age' for lacewings, with most families of Neuropterida diverging during the Triassic and Jurassic and all extant families present by the Early Cretaceous. Based on ancestral character state reconstructions of larval habitat we evaluate competing hypotheses regarding the life style of early neuropteridan larvae as either aquatic or terrestrial.

Few clinical studies have explored altered urinary metabolite levels in patients with obstructive sleep apnea (OSA). Thus, we applied a metabolomics approach to analyze urinary metabolites in three groups of participants: patients with polysomnography (PSG)-confirmed OSA, simple snorers (SS), and normal subjects. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and gas chromatography coupled with time-of-flight mass spectrometry were used. A total of 21 and 31 metabolites were differentially expressed in the SS and OSA groups, respectively. Patients with OSA had 18 metabolites different from those with SS. Of the 56 metabolites detected among the 3 groups, 24 were consistently higher or lower. A receiver operator curve analysis revealed that the combination of 4-hydroxypentenoic acid, arabinose, glycochenodeoxycholate-3-sulfate, isoleucine, serine, and xanthine produced a moderate diagnostic score with a sensitivity (specificity) of 75% (78%) for distinguishing OSA from those without OSA. The combination of 4-hydroxypentenoic acid, 5-dihydrotestosterone sulfate, serine, spermine, and xanthine distinguished OSA from SS with a sensitivity of 85% and specificity of 80%. Multiple metabolites and metabolic pathways associated with SS and OSA were identified using the metabolomics approach, and the altered metabolite signatures could potentially serve as an alternative diagnostic method to PSG.