Quantitative polymerase chain reaction assays used in the evaluation.

<p>Quantitative polymerase chain reaction assays used in the evaluation.</p

Number of positive/negative samples and the corresponding positive rates for each assay using wastewater or stool samples.

<p>Number of positive/negative samples and the corresponding positive rates for each assay using wastewater or stool samples.</p

Recovery rates of spiked murine norovirus and Cq values from qPCR targeting the norovirus GI (a) and GII (b).

<p>Plots at Cq = 45 and 50 show positive but not quantifiable samples (original Cq > 40) and negative samples, respectively.</p

Distribution and box-and-whisker plots of Cq values from qPCR targeting the norovirus GI and GII.

<p>The assays were conducted with (a) wastewater samples and (b) stool samples. The box indicates the median and the quartiles. The whiskers are drawn to the furthest points within the 1.5-times interquartile range from the box. Plots at Cq = 45 and 50 show positive but not quantifiable samples (original Cq > 40) and negative samples, respectively.</p

PBMC cytokine gene expression after stimulation.

<p>Fold change of gene expression for IL-1β, GM-CSF, TNF-α, IFN-γ and IL-10 in PBMCs from control donors or acute or relapse brucellosis patients after stimulation with (A) LPS (B) Heat-killed <i>B. melitensis</i> or (C) R848 (asterisk indicates <i>p</i>≤0.05).</p

MOESM1 of Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines

Additional file 1. Examples of statistical code in R

Basal PBMC cytokine secretion measured by multiplex immunoassay.

<p>IL-2, IL-6, IL-8, IL-10, and TNF-α secretion in unstimulated PBMCs from control donors or acute or relapse brucellosis patients (asterisk indicates <i>p</i>≤0.05). Concentrations indicated by open circles were extrapolated beyond the assay standard curve and values in the red shaded zone fell outside the observable range (OOR).</p

Hierarchical clustering of patients by gene expression or cytokine secretion.

<p>Control (green), acute (blue), and relapse (red) patients were clustered hierarchically by Euclidean distance in their scaled gene expression (A) or cytokine secretion (B) profiles (see <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002424#s2" target="_blank">Methods</a>). Response variables are grouped by cytokine, indicated in the left margin, and values are indicated by luminosity. Misclassification rates for each patient after 20 model selection runs are indicated underneath the corresponding patient code (see Supporting <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002424#pntd.0002424.s006" target="_blank">Table S1</a>).</p

Model selection and classification results.

<p>Response variables were selected and a linear discriminant classifier was trained using the transformed gene expression (A) or cytokine secretion data (B). The left panels show the results of 20 model selection runs, with the best-performing classifier highlighted in color. The variable included after each step in the forward selection is listed for the optimal model. Zero features is equivalent to random guessing. The center column shows all 33 patients after being mapped by the first (LD1) and second (LD2) linear discriminant functions used by the best-performing classifier. Classification performance is summarized by the confusion matrix on the right. This matrix gives the proportion of (C)ontrol, (A)cute, and (R)elapse patients that were correctly (on-diagonal) and incorrectly classified (off-diagonal).</p

Incidence and Risk Factors of Childhood Pneumonia-Like Episodes in Biliran Island, Philippines—A Community-Based Study

<div><p>Pneumonia is a leading cause of deaths in infants and young children in developing countries, including the Philippines. However, data at the community level remains limited. Our study aimed to estimate incidence and mortality rates and to evaluate risk factors and health-seeking behavior for childhood pneumonia. A household level interview survey was conducted in Biliran Island, the Philippines. Caregivers were interviewed using a semi-structured questionnaire to check if children had symptoms suggesting pneumonia-like episodes from June 2011 to May 2012. Of 3,327 households visited in total, 3,302 (99.2%) agreed to participate, and 5,249 children less than 5 years of age were included in the study. Incidence rates of pneumonia-like episodes, severe pneumonia-like episodes, and pneumonia-associated mortality were 105, 61, and 0.9 per 1,000 person-years, respectively. History of asthma [hazard ratio (HR): 5.85, 95% confidence interval (CI): 4.83–7.08], low socioeconomic status (SES) (HR: 1.11, 95% CI: 1.02–1.20), and long travel time to the healthcare facility estimated by cost distance analysis (HR: 1.32, 95% CI: 1.09–1.61) were significantly associated with the occurrence of pneumonia-like episodes by the Cox proportional hazards model. For severe pneumonia-like episodes, a history of asthma (HR: 8.39, 95% CI: 6.54–10.77) and low SES (HR: 1.30, 95% CI: 1.17–1.45) were significant risk factors. Children who had a long travel time to the hospital were less likely to seek hospital care (Odds ratio: 0.32, 95% CI: 0.19–0.54) when they experienced severe pneumonia-like episodes. Incidence of pediatric pneumonia-like episodes was associated with a history of asthma, SES, and the travel time to healthcare facilities. Travel time was also identified as a strong indicator for health-seeking behavior. Improved access to healthcare facilities is important for early and effective management. Further studies are warranted to understand the causal relationship between asthma and pneumonia.</p></div