Causal effect of sleep disturbance on cognitive decline in older adults

Prior studies have shown that sleep disturbance is closely associated with cognitive decline in older adults. However, one cannot use standard regression models to verify the causal relationship between sleep disorder and cognitive dysfunction. In this study, by combining propensity score weighting and honest causal tree technique, we balanced baseline characteristics between individuals with and without a certain type of sleep disorder, effectively partitioned older adults into groups based on the baseline conditions, and estimated heterogeneity in sleep disturbance impacts on cognitive function. We analyzed the data collected from the first nine waves of an ongoing community-based cohort study and the propensity score weighting causal tree model showed the causal effect of sleep disturbance on cognitive decline in various types of sleep disorder and cognitive domains. Sleep disorders caused faster decline in the memory and visuospatial domains. In addition, these causal relationship showed different effects among people with different sociodemigraphic or baseline health conditions, including age, gender, self-reported general health, systolic blood pressure (BP), diastolic BP, exercise, subjective memory complaint, and other baseline cognitive domain scores. Our findings advance the knowledge in cognitive dysfunction among the elderly and allow us to validate sleep disturbance as a therapeutic target for treating cognitive decline in older adults. PUBLIC HEALTH SIGNIFICANCE: Sleep deprivation and cognitive impairment are common among older adults yet the causal relationship between sleep disturbance and cognitive decline remains controversial. Causal tree method employed in this study directly clarified the causal effect of sleep deprivation on cognitive degeneration, thus improves our understanding of the underlying mechanisms for cognitive impairment among the elderly also helps clinicians with diagnosis and prognosis. In addition, the modifiable moderators examined in this study can help clinicians and public health practitioners find appropriate prevention and treatments for sleep disturbances

Effective Discriminative Feature Selection with Non-trivial Solutions

Feature selection and feature transformation, the two main ways to reduce dimensionality, are often presented separately. In this paper, a feature selection method is proposed by combining the popular transformation based dimensionality reduction method Linear Discriminant Analysis (LDA) and sparsity regularization. We impose row sparsity on the transformation matrix of LDA through ${\ell}_{2,1}$-norm regularization to achieve feature selection, and the resultant formulation optimizes for selecting the most discriminative features and removing the redundant ones simultaneously. The formulation is extended to the ${\ell}_{2,p}$-norm regularized case: which is more likely to offer better sparsity when $0<p<1$. Thus the formulation is a better approximation to the feature selection problem. An efficient algorithm is developed to solve the ${\ell}_{2,p}$-norm based optimization problem and it is proved that the algorithm converges when $0<p\le 2$. Systematical experiments are conducted to understand the work of the proposed method. Promising experimental results on various types of real-world data sets demonstrate the effectiveness of our algorithm

The impact of announcements of discovery of new product on stock prices : case for the fast food industry of Canada and the U.S.A.

1 online resource (vi, 35 p.) : col. ill.Includes abstract and appendix.Includes bibliographical references (p. 28-32).This study examines the impact of new product announcements from 8 fast food companies on share prices. All these announcements were from 2009-2013. Using historical stock price data, an analysis of the existence of abnormal returns was conducted to determine whether or not product announcements impact the stock prices. The results showed that although some companies suffer a negative cumulative abnormal return due to these announcements, there was a positive average cumulative abnormal return in this industry in 2003. Moreover, the means of abnormal returns in the event window (Day-2 to Day+2) imply that sample companies have negative average excess returns during this period, but there seems an significantly increasing trend of excess returns in the following period. The T-test result equally confirms the significance of abnormal returns in this study, meaning that announcements of new food discovery play an indispensable role in the Canada and U.S. fast food market

Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate.

Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air-blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2- AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration

On Newton Screening

Screening and working set techniques are important approaches to reducing the size of an optimization problem. They have been widely used in accelerating first-order methods for solving large-scale sparse learning problems. In this paper, we develop a new screening method called Newton screening (NS) which is a generalized Newton method with a built-in screening mechanism. We derive an equivalent KKT system for the Lasso and utilize a generalized Newton method to solve the KKT equations. Based on this KKT system, a built-in working set with a relatively small size is first determined using the sum of primal and dual variables generated from the previous iteration, then the primal variable is updated by solving a least-squares problem on the working set and the dual variable updated based on a closed-form expression. Moreover, we consider a sequential version of Newton screening (SNS) with a warm-start strategy. We show that NS possesses an optimal convergence property in the sense that it achieves one-step local convergence. Under certain regularity conditions on the feature matrix, we show that SNS hits a solution with the same signs as the underlying true target and achieves a sharp estimation error bound with high probability. Simulation studies and real data analysis support our theoretical results and demonstrate that SNS is faster and more accurate than several state-of-the-art methods in our comparative studies

A novel SETD2 variant causing global development delay without overgrowth in a Chinese 3-year-old boy

Background: Luscan-Lumish syndrome is characterized by macrocephaly, postnatal overgrowth, intellectual disability (ID), developmental delay (DD), which is caused by heterozygous SETD2 (SET domain containing 2) mutations. The incidence of Luscan-Lumish syndrome is unclear. The study was conducted to provide a novel pathogenic SETD2 variant causing atypical Luscan-Lumish syndrome and review all the published SETD2 mutations and corresponding symptoms, comprehensively understanding the phenotypes and genotypes of SETD2 mutations.Methods: Peripheral blood samples of the proband and his parents were collected for next-generation sequencing including whole-exome sequencing (WES), copy number variation (CNV) detection and mitochondrial DNA sequencing. Identified variant was verified by Sanger sequencing. Conservative analysis and structural analysis were performed to investigate the effect of mutation. Public databases such as PubMed, Clinvar and Human Gene Mutation Database (HGMD) were used to collect all cases with SETD2 mutations.Results: A novel pathogenic SETD2 variant (c.5835_c.5836insAGAA, p. A1946Rfs*2) was identified in a Chinese 3-year-old boy, who had speech and motor delay without overgrowth. Conservative analysis and structural analysis showed that the novel pathogenic variant would loss the conserved domains in the C-terminal region and result in loss of function of SETD2 protein. Frameshift mutations and non-sense mutations account for 68.5% of the total 51 SETD2 point mutations, suggesting that Luscan-Lumish syndrome is likely due to loss of function of SETD2. But we failed to find an association between genotype and phenotype of SETD2 mutations.Conclusion: Our findings expand the genotype-phenotype knowledge of SETD2-associated neurological disorder and provide new evidence for further genetic counselling

Content analysis of systematic reviews on the effectiveness of Traditional Chinese Medicine

AbstractObjectiveTo evaluate evidence for the efficacy of Traditional Chinese Medicine (TCM) in systematic reviews.MethodsChinese (TCMPeriodical Literature Database, Chinese Biological Medicine database, Chinese Medical Current Contents, China Hospital Knowledge Database journal fulltext database, Virtual Machining and Inspection System, and Wanfang) and English (Cochrane Database of Systematic Reviews, PubMed and Embase) databases were searched.ResultsThree thousand, nine hundred and fifty-five articles were initially identified, 606 of which met the inclusion criteria, including 251 in English (83 from the Cochrane Database) and 355 in Chinese. The number of articles published each year increased between 1989 and 2009. Cardiocerebrovascular disease was the most studied target disease. Intervention measures includedTCM preparations (177 articles), acupuncture (133 articles) and combinations of TCM and western medicine (38 articles). Control measures included positive medical (177 articles), basic treatment (100 articles), placebo (219 articles), and blank and mutual (107 articles). All articles included at least one reference; the greatest number was 268. Six of 10 articles with high quality references demonstrated curative effectsagainst target diseasesincludingupper respiratory tract infection, dementia and depression. Interventions that were not recommendedwere tripterygium for rheumatoid arthritis andTCM syndrome differentiation for pediatric nocturia. In 10.4% of the studies, the authors concluded that the intervention had a curative effect. The assessors agreed with the authors' conclusions in 88.32% of cases, but rejected 8.94% (54 articles).Conclusion1) Training in systematic review methods, including topic selection, study design, methods and technology, should be improved. 2) Upper respiratory tract infection, dementia and depression may become the predominant diseases treatedby TCM, and the corresponding interventions could be developed into practical applications. 3) Use of non-recommended interventions should be controlled, and there should be more research on side effects

Influence Analysis of Star Sensors' Sampling Frequency on Attitude Determination Accuracy

The star sensor has been widely used as an important and accurate attitude measurement sensor in classical satellite attitude determination systems. This paper analyses the influence of star sensor's sampling frequency on attitude determination accuracy within an Extended Kalman filter (EKF). Simulations are used to validate the theoretical analysis and determine the parameters of the influence function. The results show that in most scenarios, the influence of the star sensor's sampling frequency on the attitude determination accuracy can be expressed by the characteristic parameter in the influence function, which is not affected by other accuracy influence factors

Managing Diabetes Mellitus in Underserved Subjects of Western China Using a Telemedicine System— a Clinical Trial

Objective: To evaluate the effectiveness of Internet and telephone-based telemedicine system managing on patients’ glycemic index, blood pressure, and lipid level control in underserved subjects with type 2 diabetes in Western China. Research designs and methods: In a 3 years, randomized, controlled, single-blind, parallel-group treat-to-target study, 412 subjects with type 2 diabetes were randomized to telemedicine (Tel; n =208) group and usual care (control; n =204) group. We evaluated the effects of the intervention on blood sugar, blood pressure, and lipid levels at 1, 2, 3 years point, and investigated the cause of the loss during follow-up by phone call. Results: Intra-group comparison: in the Tel group, the FBS, 2HPG, HbA1c, and SBP at 1, 2, 3 years and DBP, TC, TG, BMI at 2, 3 years were significantly decreased compared with baseline level  (P<0.05). Moreover, the Tel group had an obvious better control of their HbA1c  at 2 and 3 years and 2HPG  at 3 years of follow-up respectively compared with the outcomes at 1 year (P<0.05).Inter-group comparison: the FBS, 2HPG, and HbA1c of Tel group decreased significantly from the baseline to the 1 year more than those of control group (P<0.05 or P<0.01 ). In this analysis, all clinical measures of Tel group had a significant downward compared with the outcomes of Control group  at 2 years, the FBS, HbA1c and BMI (P<0.001), the 2HPG and SBP (P<0.01) and DBP, TC, and TG (P<0.05) were statistically significant respectively. Logistic regression analysis showed that the subject loss during follow-up was associated with worse diabetes management (OR=3.842), low income (OR=3.201), low education level (OR=0.923), and greater distance to the hospital (OR=0.921).Conclusions: The study results indicated that the telemedicine may be a useful tool for managing diabetes mellitus