Speech Perception, Metalinguistic Awareness, Reading, and Vocabulary in Chinese-English Bilingual Children

10.1037/a0017850Journal of Educational Psychology1022367-38

The effect of acute morphine on sleep in male patients suffering from sleep apnea: Is there a genetic effect? An RCT study

Questionnaire-based studies have suggested genetic differences in sleep symptoms in chronic opioid users. The present study aims to investigate if there is a genetic effect on sleep architecture and quantitative electroencephalogram (EEG) in response to acute morphine. Under a randomized, double-blind, placebo-controlled, crossover design, 68 men with obstructive sleep apnea undertook two overnight polysomnographic studies conducted at least 1 week apart. Each night they received either 40 mg of controlled-release morphine or placebo. Sleep architecture and quantitative EEG were compared between conditions. Blood was sampled before sleep and on the next morning for genotyping and pharmacokinetic analyses. We analysed three candidate genes (OPRM1 [rs1799971, 118 A > G], ABCB1[rs1045642, 3435 C > T] and HTR3B [rs7103572 C > T]). We found that morphine decreased slow wave sleep and rapid eye movement sleep and increased stage 2 sleep. Those effects were less in subjects with HTR3B CT/TT than in those with CC genotype. Similarly, sleep onset latency was shortened in the ABCB1 CC subgroup compared with the CT/TT subgroup. Total sleep time was significantly increased in ABCB1 CC but not in CT/TT subjects. Sleep apnea and plasma morphine and metabolite concentration were not confounding factors for these genetic differences in sleep. With morphine, patients had significantly more active/unstable EEG (lower delta/alpha ratio) during sleep. No genetic effects on quantitative EEG were detected. In summary, we identified two genes (HTR3B and ABCB1) with significant variation in the sleep architecture response to morphine. Morphine caused a more active/unstable EEG during sleep. Our findings may have relevance for a personalized medicine approach to targeted morphine therapy.Luke Rowsell, Justin Guang-Ao Wu, Brendon J. Yee, Keith K.H. Wong, Sheila Sivam, Andrew A. Somogyi, Ronald R. Grunstein, David Wan

The emerging role of the lung microbiome and its importance in non-small cell lung cancer diagnosis and treatment

Over the last 10 years, with the development of culture-free bacterial identification techniques, understanding of how the microbiome influences diseases has increased exponentially and has highlighted potential opportunities for its use as a diagnostic biomarker and interventional target in many diseases including malignancy. Initial research focused on the faecal microbiome since it contains the densest bacterial populations and many other mucosal sites, such as the lungs, were until recently thought to be sterile. However, in recent years, it has become clear that the lower airways are home to a dynamic bacterial population sustained by the migration and elimination of microbes from the gastrointestinal and upper airway tracts. As in the gut, the lung microbiome plays an important role in regulating mucosal immunity and maintaining the balance between immune tolerance and inflammation. Studies to date have all shown that the lung microbiome undergoes significant changes in the setting of pulmonary disease. In lung cancer, animal models and small patient cohort studies have suggested that microbiome dysbiosis may not only impact tumour progression and response to therapy, particularly immunotherapy, but also plays a key role in cancer pathogenesis by influencing early carcinogenic pathways. These early results have led to concerted efforts to identify microbiome signatures that represent diagnostic biomarkers of early-stage disease and to consider modulation of the lung microbiome as a potential therapeutic strategy. Lung microbiome research is in its infancy and studies to date have been small, single centre with significant methodological variation. Large, multicentre longitudinal studies are needed to establish the clinical potential of this exciting field

Predictors of weight loss in obese patients with obstructive sleep apnea

Vol. 26 pp 753-762Purpose: Consistent predictors of weight loss outcomes with very low-energy diets (VLEDs) in obstructive sleep apnea (OSA) have not been identified. This study aimed to identify variables predictive of weight loss success in obese patients with OSA undertaking an intensive weight loss programme. Methods: We analysed biological, psychological, and behavioural variables as potential predictors of weight loss in obese patients with OSA after a 2-month VLED followed by one of two 10-month weight loss maintenance diets. Actigraphy, in-lab polysomnography, urinary catecholamines, and various psychological and behavioural variables were measured at baseline, 2, and 12 months. Spearman’s correlations analysed baseline variables with 2-month weight loss, and 2-month variables with 2–12 month-weight change. Results: Forty-two patients completed the VLED and thirty-eight completed the maintenance diets. Actigraphy data revealed that late bedtime (rs =  − 0.45, p =  < 0.01) was correlated with 2-month weight loss. The change in the time that participants got out of bed (rise-time) from baseline to two months was also correlated with 2-month weight loss (rs = 0.36, p = 0.03). The Impact of Weight on Quality of Life-Lite questionnaire (IWQOL) Public Distress domain (rs =  − 0.54, p =  < 0.01) and total (rs =  − 0.38, p = 0.02) scores were correlated with weight loss maintenance from 2 to 12 months. Conclusions: Results from this small patient sample reveal correlations between actigraphy characteristics and weight loss in obese patients with OSA. We suggest the IWQOL may also be a useful clinical tool to identify OSA patients at risk of weight regain after initial weight loss.Thomas J. Altree, Delwyn J. Bartlett, Nathaniel S. Marshall, Camilla M. Hoyos, Craig L. Phillips, Callum Birks, Aran Kanagaratnam, Anna Mullins, Yasmina Serinel, Keith K.H. Wong, Brendon J. Yee, Ronald R. Grunstein, Elizabeth A. Cayana

Cardiogenol C can induce Mouse Hair Bulge Progenitor Cells to Transdifferentiate into Cardiomyocyte-like Cells

10.1186/1477-5956-9-3Proteome Science9

Improved algebraic cryptanalysis of QUAD, Bivium and trivium via graph partitioning on equation systems

We present a novel approach for preprocessing systems of polynomial equations via graph partitioning. The variable-sharing graph of a system of polynomial equations is defined. If such graph is disconnected, then the corresponding system of equations can be split into smaller ones that can be solved individually. This can provide a tremendous speed-up in computing the solution to the system, but is unlikely to occur either randomly or in applications. However, by deleting certain vertices on the graph, the variable-sharing graph could be disconnected in a balanced fashion, and in turn the system of polynomial equations would be separated into smaller systems of near-equal sizes. In graph theory terms, this process is equivalent to finding balanced vertex partitions with minimum-weight vertex separators. The techniques of finding these vertex partitions are discussed, and experiments are performed to evaluate its practicality for general graphs and systems of polynomial equations. Applications of this approach in algebraic cryptanalysis on symmetric ciphers are presented: For the QUAD family of stream ciphers, we show how a malicious party can manufacture conforming systems that can be easily broken. For the stream ciphers Bivium and Trivium, we nachieve significant speedups in algebraic attacks against them, mainly in a partial key guess scenario. In each of these cases, the systems of polynomial equations involved are well-suited to our graph partitioning method. These results may open a new avenue for evaluating the security of symmetric ciphers against algebraic attacks