Evaluating Algorithm Efficiency for Optimizing Experimental Designs with Correlated Data

The search for efficient methods and procedures to optimize experimental designs is a vital process in field trials that is often challenged by computational bottlenecks. Most existing methods ignore the presence of some form of correlations in the data to simplify the optimization process at the design stage. This study explores several algorithms for improving field experimental designs using a linear mixed models statistical framework adjusting for both spatial and genetic correlations based on A- and D-optimality criteria. Relative design efficiencies are estimated for an array of algorithms including pairwise swap, genetic neighborhood, and simulated annealing and evaluated with varying levels of heritabilities, spatial and genetic correlations. Initial randomized complete block designs were generated using a stochastic procedure and can also be imported directly from other design software. Results showed that at a spatial correlation of 0.6 and a heritability of 0.3, under the A-optimality criterion, both simulated annealing and simple pairwise algorithms achieved the highest design efficiencies of 7.4 % among genetically unrelated individuals, implying a reduction in average variance of the random treatment effects by 7.4 % when the algorithm was iterated 5000 times. In contrast, results under D-optimality criterion indicated that simulated annealing had the lowest design efficiency. The simple pairwise algorithm consistently maintained highest design efficiencies in all evaluated conditions. Design efficiencies for experiments with full-sib families decreased with increasing heritability. The number of successful swaps appeared to decrease with increasing heritability and were highest for both simulated annealing and simple pairwise algorithms, and lowest for genetic neighborhood algorithm

Generating Improved Experimental Designs with Spatially and Genetically Correlated Observations Using Mixed Models

The aim of this study was to generate and evaluate the efficiency of improved field experiments while simultaneously accounting for spatial correlations and different levels of genetic relatedness using a mixed models framework for orthogonal and non-orthogonal designs. Optimality criteria and a search algorithm were implemented to generate randomized complete block (RCB), incomplete block (IB), augmented block (AB) and unequally replicated (UR) designs. Several conditions were evaluated including size of the experiment, levels of heritability, and optimality criteria. For RCB designs with half-sib or full-sib families, the optimization procedure yielded important improvements under the presence of mild to strong spatial correlation levels and relatively low heritability values. Also, for these designs, improvements in terms of overall design efficiency (ODE%) reached values of up to 8.7%, but these gains varied depending on the evaluated conditions. In general, for all evaluated designs, higher ODE% values were achieved from genetically unrelated individuals compared to experiments with half-sib and full-sib families. As expected, accuracy of prediction of genetic values improved as levels of heritability and spatial correlations increased. This study has demonstrated that important improvements in design efficiency and prediction accuracies can be achieved by optimizing how the levels of a treatment are assigned to the experimental units

A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa

Background Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context. Methods Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria. Results Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively. Conclusion The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors

Bronchoalveolar lavage (BAL) cells in idiopathic pulmonary fibrosis express a complex pro-inflammatory, pro-repair, angiogenic activation pattern, likely associated with macrophage iron accumulation

<div><p>Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease of unknown cause characterized by alveolar epithelial damage, patchy interstitial fibrosis and diffuse microvascular abnormalities. In IPF, alveolar clustering of iron-laden alveolar macrophages—a common sign of microhemorrhage, has been associated with vascular abnormalities and worsening of pulmonary hypertension. As iron-dependent ROS generation has been shown to induce unrestrained macrophage activation in disease models of vascular damage, we explored alveolar macrophage activation phenotype in IPF patients (n = 16) and healthy controls (CTR, n = 7) by RNA sequencing of bronchoalveolar lavage (BAL) cells. The frequencies of macrophages in BAL cells were 86+4% and 83.4+8% in IPF and CTR groups, respectively (p-value = 0.41). In IPF patients, BAL cells showed increased iron-dependent ROS generation (p-value<0.05 vs CTR). Gene expression analysis showed overrepresentation of Gene Ontology processes/functions and KEGG pathways enriched in upregulated M1-type inflammatory (p-value<0.01), M2-type anti-inflammatory/tissue remodeling (p-value<0.0001), and MTPP-type chronic inflammatory/angiogenic (p-value<0.0001) chemokine and cytokine genes. The <i>ex vivo</i> finding was confirmed by the induction of iron-dependent ROS generation and chemokine/cytokine overexpression of Ccl4, Cxcl10 (M1), Il1rn (M2), Cxcl2, and Cxcl7 (MTPP) in MH-S murine immortalized alveolar macrophages exposed to ferric ammonium citrate in culture (p-value<0.05 vs CTR). The data show alveolar macrophage expression of a pro-inflammatory, tissue remodeling and angiogenic complex activation pattern, suggesting that iron accumulation may play a role in macrophage activation.</p></div

Study population characteristics of IPF patients and controls undergoing fiberoptic bronchoscopy with BAL.

<p>Study population characteristics of IPF patients and controls undergoing fiberoptic bronchoscopy with BAL.</p

Principal Component Analysis of healthy controls and IPF patients.

<p>The PCA plot was computed using the differentially expressed gene list (FDR<0.05, log2FC>0.6 filter).</p

Quantification of BAL fluid chemokine levels by protein immunochemistry.

<p>Chemokines were measured in un-concentrated BAL fluid by protein immunochemistry on IPF affected individuals (closed circles) and Healthy Controls (open circles). CXCL-5 was quantified using the Chemokine Human 5-Plex Panel II for the Luminex 100/200 platform. PPBP/CXCL-7, CXCL-10, CCL13 and CCL18 were measured using enzyme-linked immunosorbent assay (ELISA) kits. Mann-Whitney test (*) and (**) denote statistical significance (P < 0.05, P < 0.01, respectively) vs. control.</p

Gene Ontology (GO) term and KEGG pathway analysis.

<p>Gene Ontology (GO) term and KEGG pathway analysis.</p

RNA-seq differential gene expression validation by qRT-PCR.

<p>Relative expression of selected chemokines in IPF (N = 7, closed circles) vs. Healthy control (N = 4, open circles) BAL cells represented by normalized ΔCt value. ΔCt value was normalized to the GNB2L1 housekeeping gene expression by subtracting GNB2L1 raw Ct from the selected gene raw Ct and by further adding the absolute GNB2L1 minimum value (the same for all samples) to the gene ΔCt. Lower cycle values correspond to higher expression level. Mann-Whitney test (*) and (**) denote statistical significance (P < 0.05, P < 0.01, respectively) vs. control.</p