Multivariate variance-components analysis of longitudinal blood pressure measurements from the Framingham Heart Study

Multivariate variance-components analysis provides several advantages over univariate analysis when studying correlated traits. It can test for pleiotropy or (in the longitudinal context) gene × age interaction. It can also have more power than univariate analyses to detect a quantitative trait locus influencing several traits. We apply multivariate variance components to longitudinal systolic blood pressure data from the Framingham Heart Study. We find evidence for a polygenic influence on blood pressure (heritabilities at different ages range from 27% to 38%). Tests based on a factor-analytic parameterization of the polygenic variance find significant (p < 2 × 10(-3)) evidence that different genes affect blood pressure at different ages. Still, estimates for the proportion of polygenic variance due to shared genes ran as high as 85% for some trait pairs. Univariate and multivariate linkage analyses replicate previous linkage results on chromosome 17 (maximum LOD scores of 2.2 and 2.4, respectively). In this study, multivariate analysis provides no increase in power; this is likely due to the strong positive correlation in systolic blood pressure measured at different ages

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm

Decentralized Stochastic Gradient Descent (SGD) is an emerging neural network training approach that enables multiple agents to train a model collaboratively and simultaneously. Rather than using a central parameter server to collect gradients from all the agents, each agent keeps a copy of the model parameters and communicates with a small number of other agents to exchange model updates. Their communication, governed by the communication topology and gossip weight matrices, facilitates the exchange of model updates. The state-of-the-art approach uses the dynamic one-peer exponential-2 topology, achieving faster training times and improved scalability than the ring, grid, torus, and hypercube topologies. However, this approach requires a power-of-2 number of agents, which is impractical at scale. In this paper, we remove this restriction and propose \underline{D}ecentralized \underline{SGD} with \underline{C}ommunication-optimal \underline{E}xact \underline{C}onsensus \underline{A}lgorithm (DSGD-CECA), which works for any number of agents while still achieving state-of-the-art properties. In particular, DSGD-CECA incurs a unit per-iteration communication overhead and an $\tilde{O}(n^3)$ transient iteration complexity. Our proof is based on newly discovered properties of gossip weight matrices and a novel approach to combine them with DSGD's convergence analysis. Numerical experiments show the efficiency of DSGD-CECA

Five Dimensions of School-Based Counseling Practice: Factor Analysis Identification Using the International Survey of School Counselors’ Activities

This article describes a factor analytic study designed to identify the underlying dimensions of school-based counseling practice that will be useful in describing cross-national differences in school-based counseling practice and in enabling comparative research on school-based counseling policy and effectiveness. Practicing school-based counselors (N = 2913) from 10 countries (China, Costa Rica, India, Kenya, South Korea, Malta, Nigeria, Turkey, the United States, and Venezuela) used the International Survey of School-Based Counseling Activities (ISSCA) to rate the centrality of 40 activities to the role of a school-based counselor. Factor analysis determined that five dimensions adequately described the school-based counselor role: Counseling Services; Advocacy and Systemic Improvement; Prevention Programs; Administrator Role; and Educational and Career Planning. Analysis of Bartlett Factor Score averages revealed that each country demonstrates a unique profile which reflects that country’s dominant mode of practice. This lead article describes these dimensions and the cross-national differences on these dimensions. Subsequent articles in this special issue describe country-specific results and explain factors that affect practice within each country

Serum alkaline phosphatase predicts survival outcomes in patients with skeletal metastatic nasopharyngeal carcinoma

OBJECTIVE: Bone metastasis is frequently associated with nasopharyngeal carcinoma. The diagnosis and follow-up of bone metastatic patients usually relies on skeletal X-ray and bone scintigraphy, which are time-consuming and costly. This study aimed to evaluate whether serum alkaline phosphatase offers clinical value in predicting the clinical response and survival outcome for skeletal metastatic nasopharyngeal carcinoma. METHODS: Serum alkaline phosphatase was measured at baseline and then before each cycle of treatment in 416 nasopharyngeal carcinoma patients with bone metastasis. The correlations between the pre-treatment and post-treatment alkaline phosphatase levels and the treatment efficacy were analyzed using the chi-square test. Survival was analyzed using the Kaplan–Meier method and then compared using the log-rank test. RESULTS: Patients with elevated pre-treatment alkaline phosphatase (>;110 IU/L) had significantly worse progression-free survival (

Intranasal immunization with a helper-dependent adenoviral vector expressing the codon-optimized fusion glycoprotein of human respiratory syncytial virus elicits protective immunity in BALB/c mice

BACKGROUND: Human respiratory syncytial virus (RSV) is a serious pediatric pathogen of the lower respiratory tract. Currently, there is no clinically approved vaccine against RSV infection. Recent studies have shown that helper-dependent adenoviral (HDAd) vectors may represent effective and safe vaccine vectors. However, viral challenge has not been investigated following mucosal vaccination with HDAd vector vaccines. METHODS: To explore the role played by HDAd as an intranasally administered RSV vaccine vector, we constructed a HDAd vector encoding the codon optimized fusion glycoprotein (Fsyn) of RSV, designated HDAd-Fsyn, and delivered intranasally HDAd-Fsyn to mice. RESULTS: RSV-specific humoral and cellular immune responses were generated in BALB/c mice, and serum IgG with neutralizing activity was significantly elevated after a homologous boost with intranasal (i.n.) application of HDAd-Fsyn. Humoral immune responses could be measured even 14 weeks after a single immunization. Immunization with i.n. HDAd-Fsyn led to effective protection against RSV infection on challenge. CONCLUSION: The results indicate that HDAd-Fsyn can induce powerful systemic immunity against subsequent i.n. RSV challenge in a mouse model and is a promising candidate vaccine against RSV infection

Development of the Taxonomy of Policy Levers to Promote High Quality School-Based Counseling: An Initial Test of its Utility and Comprehensiveness

This article is the second of a two-part series that describes the development of the Taxonomy of Policy Levers to Promote High Quality School-Based Counseling. A previous article (Morshed & Carey, in press) described the development of the Taxonomy using content analysis of existing published descriptions of policy levers used to promote quality school-based counseling. This present article tested the utility and comprehensiveness of the Taxonomy by having experts from South Korea, Nigeria, and West Virginia review policies in their regions.. They analyzed the utility and comprehensiveness of the Taxonomy by using it to describe the school-based counseling policy landscape in their own contexts. Overall, the Taxonomy provided a useful framework for identifying policy levers that were implemented as well as the levers which were not implemented but could be put in place to further improve school-based counseling. Four additional levers were added, and the revised Taxonomy is presented. Additional research to expand the taxonomy is suggested, and the utility of the taxonomy to guiding policy research and evaluation is explained