Sputum TWEAK expression correlates with severity and degree of control in non‐eosinophilic childhood asthma

Background

Tumor necrosis factor‐like weak inducer of apoptosis (TWEAK) is known to play a role in the pathogenesis of various inflammatory diseases. However, no study has been performed on childhood asthma.

Methods

Ninety‐five children with asthma and 78 controls aged 5‐18 years were included. Sputum induction, pulmonary function test (PFT), and methacholine challenge test were performed. The subjects were divided into the eosinophilic airway (EA) and non‐EA (NEA) groups based on sputum analysis and into the high and low TWEAK groups according to the TWEAK cutoff level (263.0 pg/mL). TWEAK in induced sputum supernatant was measured through enzyme‐linked immunosorbent assay.

Results

Children with asthma had higher TWEAK levels than healthy controls (493.0 [157.1‐904.3] vs 118.2 (67.5‐345.5) pg/mL, P < .001). Sputum TWEAK levels were significantly correlated with PFT parameters reflecting airway obstruction. This association was particularly prominent in subjects with NEA inflammation. Significant differences in FEF_25‐75 (maximum mid‐expiratory flow, % predicted; P = .017), AX (reactance area; P < .001), R5‐R20 (difference between resistance at 5 and 20 Hz; P = .025), and X5 (reactance at 5 Hz, % predicted; P < .001) were noted between the high and low TWEAK groups within the NEA group. Sputum TWEAK level also showed significant positive correlations with asthma severity (r = .358, P = .001) and control status (r = .470, P < .001), distinctively in subjects with NEA inflammation.

Conclusions

Airway TWEAK may play a role in small airway inflammation especially in children with non‐eosinophilic asthma.     

Glioma grading using apparent diffusion coefficient map: application of histogram analysis based on automatic segmentation

The accurate diagnosis of glioma subtypes is critical for appropriate treatment, but conventional histopathologic diagnosis often exhibits significant intra‐observer variability and sampling error. The aim of this study was to investigate whether histogram analysis using an automatically segmented region of interest (ROI), excluding cystic or necrotic portions, could improve the differentiation between low‐grade and high‐grade gliomas. Thirty‐two patients (nine low‐grade and 23 high‐grade gliomas) were included in this retrospective investigation. The outer boundaries of the entire tumors were manually drawn in each section of the contrast‐enhanced T₁‐weighted MR images. We excluded cystic or necrotic portions from the entire tumor volume. The histogram analyses were performed within the ROI on normalized apparent diffusion coefficient (ADC) maps. To evaluate the contribution of the proposed method to glioma grading, we compared the area under the receiver operating characteristic (ROC) curves. We found that an ROI excluding cystic or necrotic portions was more useful for glioma grading than was an entire tumor ROI. In the case of the fifth percentile values of the normalized ADC histogram, the area under the ROC curve for the tumor ROIs excluding cystic or necrotic portions was significantly higher than that for the entire tumor ROIs (p < 0.005). The automatic segmentation of a cystic or necrotic area probably improves the ability to differentiate between high‐ and low‐grade gliomas on an ADC map. Copyright © 2014 John Wiley & Sons, Ltd.