Reduction of malaria prevalence by indoor residual spraying: a meta-regression analysis.

Indoor residual spraying (IRS) has become an increasingly popular method of insecticide use for malaria control, and many recent studies have reported on its effectiveness in reducing malaria burden in a single community or region. There is a need for systematic review and integration of the published literature on IRS and the contextual determining factors of its success in controlling malaria. This study reports the findings of a meta-regression analysis based on 13 published studies, which were chosen from more than 400 articles through a systematic search and selection process. The summary relative risk for reducing malaria prevalence was 0.38 (95% confidence interval = 0.31-0.46), which indicated a risk reduction of 62%. However, an excessive degree of heterogeneity was found between the studies. The meta-regression analysis indicates that IRS is more effective with high initial prevalence, multiple rounds of spraying, use of DDT, and in regions with a combination of Plasmodium falciparum and P. vivax malaria.

Modeling endogenous technological change for climate policy analysis

The approach used to model technological change in a climate policy model is a critical determinant of its results in terms of the time path of CO2 prices and costs required to achieve various emission reduction goals. We provide an overview of the different approaches used in the literature, with an emphasis on recent developments regarding endogenous technological change, research and development, and learning. Detailed examination sheds light on the salient features of each approach, including strengths, limitations, and policy implications. Key issues include proper accounting for the opportunity costs of climate-related knowledge generation, treatment of knowledge spillovers and appropriability, and the empirical basis for parameterizing technological relationships. No single approach appears to dominate on all these dimensions, and different approaches may be preferred depending on the purpose of the analysis, be it positive or normative. © 2008 Elsevier B.V. All rights reserved.

Structuring the Calibration of Qualitative Data as Sets for Qualitative Comparative Analysis (QCA)

Most studies that apply qualitative comparative analysis (QCA) rely on macro-level data, but an increasing number of studies focus on units of analysis at the micro or meso level (i.e., households, firms, protected areas, communities, or local governments). For such studies, qualitative interview data are often the primary source of information. Yet, so far no procedure is available describing how to calibrate qualitative data as fuzzy sets. The authors propose a technique to do so and illustrate it using examples from a study of Guatemalan local governments. By spelling out the details of this important analytic step, the authors aim at contributing to the growing literature on best practice in QCA. © The Author(s) 2012.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Barriers to and facilitators of interventions to counter publication bias: thematic analysis of scholarly articles and stakeholder interviews.

BACKGROUND: When the nature and direction of research results affect their chances of publication, a distortion of the evidence base - termed publication bias - results. Despite considerable recent efforts to implement measures to reduce the non-publication of trials, publication bias is still a major problem in medical research. The objective of our study was to identify barriers to and facilitators of interventions to prevent or reduce publication bias. METHODS: We systematically reviewed the scholarly literature and extracted data from articles. Further, we performed semi-structured interviews with stakeholders. We performed an inductive thematic analysis to identify barriers to and facilitators of interventions to counter publication bias. RESULTS: The systematic review identified 39 articles. Thirty-four of 89 invited interview partners agreed to be interviewed. We clustered interventions into four categories: prospective trial registration, incentives for reporting in peer-reviewed journals or research reports, public availability of individual patient-level data, and peer-review/editorial processes. Barriers we identified included economic and personal interests, lack of financial resources for a global comprehensive trial registry, and different legal systems. Facilitators identified included: raising awareness of the effects of publication bias, providing incentives to make data publically available, and implementing laws to enforce prospective registration and reporting of clinical trial results. CONCLUSIONS: Publication bias is a complex problem that reflects the complex system in which it occurs. The cooperation amongst stakeholders to increase public awareness of the problem, better tailoring of incentives to publish, and ultimately legislative regulations have the greatest potential for reducing publication bias.

Memorability as a measure of processing: a unit analysis of prose and list learning.

The percentage of subjects recalling each unit in a list or prose passage is considered as a dependent measure. When the same units are recalled in different tasks, processing is assumed to be the same; when different units are recalled, processing is assumed to be different. Two collections of memory tasks are presented, one for lists and one for prose. The relations found in these two collections are supported by an extensive reanalysis of the existing prose memory literature. The same set of words were learned by 13 different groups of subjects under 13 different conditions. Included were intentional free-recall tasks, incidental free recall following lexical decision, and incidental free recall following ratings of orthographic distinctiveness and emotionality. Although the nine free-recall tasks varied widely with regard to the amount of recall, the relative probability of recall for the words was very similar among the tasks. Imagery encoding and recognition produced relative probabilities of recall that were different from each other and from the free-recall tasks. Similar results were obtained with a prose passage. A story was learned by 13 different groups of subjects under 13 different conditions. Eight free-recall tasks, which varied with respect to incidental or intentional learning, retention interval, and the age of the subjects, produced similar relative probabilities of recall, whereas recognition and prompted recall produced relative probabilities of recall that were different from each other and from the free-recall tasks. A review of the prose literature was undertaken to test the generality of these results. Analysis of variance is the most common statistical procedure in this literature. If the relative probability of recall of units varied across conditions, a units by condition interaction would be expected. For the 12 studies that manipulated retention interval, an average of 21% of the variance was accounted for by the main effect of retention interval, 17% by the main effect of units, and only 2% by the retention interval by units interaction. Similarly, for the 12 studies that varied the age of the subjects, 6% of the variance was accounted for by the main effect of age, 32% by the main effect of units, and only 1% by the interaction of age by units.(ABSTRACT TRUNCATED AT 400 WORDS)

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.

MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

Return to sport after open and microdiscectomy surgery versus conservative treatment for lumbar disc herniation: a systematic review with meta-analysis.

BACKGROUND: Lumbar disc herniation has a prevalence of up to 58% in the athletic population. Lumbar discectomy is a common surgical procedure to alleviate pain and disability in athletes. We systematically reviewed the current clinical evidence regarding athlete return to sport (RTS) following lumbar discectomy compared to conservative treatment. METHODS: A computer-assisted literature search of MEDLINE, CINAHL, Web of Science, PEDro, OVID and PubMed databases (from inception to August 2015) was utilised using keywords related to lumbar disc herniation and surgery. The design of this systematic review was developed using the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Methodological quality of individual studies was assessed using the Downs and Black scale (0-16 points). RESULTS: The search strategy revealed 14 articles. Downs and Black quality scores were generally low with no articles in this review earning a high-quality rating, only 5 articles earning a moderate quality rating and 9 of the 14 articles earning a low-quality rating. The pooled RTS for surgical intervention of all included studies was 81% (95% CI 76% to 86%) with significant heterogeneity (I(2)=63.4%, p<0.001) although pooled estimates report only 59% RTS at same level. Pooled analysis showed no difference in RTS rate between surgical (84% (95% CI 77% to 90%)) and conservative intervention (76% (95% CI 56% to 92%); p=0.33). CONCLUSIONS: Studies comparing surgical versus conservative treatment found no significant difference between groups regarding RTS. Not all athletes that RTS return at the level of participation they performed at prior to surgery. Owing to the heterogeneity and low methodological quality of included studies, rates of RTS cannot be accurately determined.

The effectiveness of low-level laser therapy for nonspecific chronic low back pain: a systematic review and meta-analysis.

BACKGROUND: In recent decades, low-level laser therapy (LLLT) has been widely used to relieve pain caused by different musculoskeletal disorders. Though widely used, its reported therapeutic outcomes are varied and conflicting. Results similarly conflict regarding its usage in patients with nonspecific chronic low back pain (NSCLBP). This study investigated the efficacy of low-level laser therapy (LLLT) for the treatment of NSCLBP by a systematic literature search with meta-analyses on selected studies. METHOD: MEDLINE, EMBASE, ISI Web of Science and Cochrane Library were systematically searched from January 2000 to November 2014. Included studies were randomized controlled trials (RCTs) written in English that compared LLLT with placebo treatment in NSCLBP patients. The efficacy effect size was estimated by the weighted mean difference (WMD). Standard random-effects meta-analysis was used, and inconsistency was evaluated by the I-squared index (I(2)). RESULTS: Of 221 studies, seven RCTs (one triple-blind, four double-blind, one single-blind, one not mentioning blinding, totaling 394 patients) met the criteria for inclusion. Based on five studies, the WMD in visual analog scale (VAS) pain outcome score after treatment was significantly lower in the LLLT group compared with placebo (WMD = -13.57 [95 % CI = -17.42, -9.72], I(2) = 0 %). No significant treatment effect was identified for disability scores or spinal range of motion outcomes. CONCLUSIONS: Our findings indicate that LLLT is an effective method for relieving pain in NSCLBP patients. However, there is still a lack of evidence supporting its effect on function.