An image database of Drosophila melanogaster wings for phenomic and biometric analysis.

BACKGROUND: Extracting important descriptors and features from images of biological specimens is an ongoing challenge. Features are often defined using landmarks and semi-landmarks that are determined a priori based on criteria such as homology or some other measure of biological significance. An alternative, widely used strategy uses computational pattern recognition, in which features are acquired from the image de novo. Subsets of these features are then selected based on objective criteria. Computational pattern recognition has been extensively developed primarily for the classification of samples into groups, whereas landmark methods have been broadly applied to biological inference. RESULTS: To compare these approaches and to provide a general community resource, we have constructed an image database of Drosophila melanogaster wings - individually identifiable and organized by sex, genotype and replicate imaging system - for the development and testing of measurement and classification tools for biological images. We have used this database to evaluate the relative performance of current classification strategies. Several supervised parametric and nonparametric machine learning algorithms were used on principal components extracted from geometric morphometric shape data (landmarks and semi-landmarks). For comparison, we also classified phenotypes based on de novo features extracted from wing images using several computer vision and pattern recognition methods as implemented in the Bioimage Classification and Annotation Tool (BioCAT). CONCLUSIONS: Because we were able to thoroughly evaluate these strategies using the publicly available Drosophila wing database, we believe that this resource will facilitate the development and testing of new tools for the measurement and classification of complex biological phenotypes.

Gastroesophageal reflux, esophageal function, gastric emptying, and the relationship to dysphagia before and after antireflux surgery in children.

OBJECTIVES: To assess gastroesophageal reflux (GER), esophageal motility, and gastric emptying in children before and after laparoscopic fundoplication and to identify functional measures associated with postoperative dysphagia. STUDY DESIGN: Combined impedance-manometry, 24-hour pH-impedance, and gastric-emptying breath tests were performed before and after laparoscopic anterior partial fundoplication. Impedance-manometry studies were analyzed with the use of conventional analysis methods and a novel automated impedance manometry (AIM) analysis. RESULTS: Children with therapy resistent GER disease (n = 25) were assessed before fundoplication, of whom 10 (median age 6.4 years; range, 1.1-17.1 years; 7 male; 4 with neurologic impairment) underwent fundoplication. GER episodes reduced from 97 (69-172) to 66 (18-87)/24 hours (P = .012). Peristaltic contractions were unaltered. Complete lower esophageal sphincter relaxations decreased after fundoplication (92% [76%-100%] vs 65% [29%-91%], P = .038). Four (40%) patients developed postoperative dysphagia, which was transient in 2. In those patients, preoperative gastric emptying was delayed compared with patients without postoperative dysphagia, 96 minutes (71-104 minutes) versus 48 minutes (26-68 minutes), P = .032, and AIM analysis derived dysphagia risk index was greater (56 [15-105] vs 2 [2-6] P = .016). Two patients underwent a repeat fundoplication. DISCUSSION: Fundoplication in children reduced GER without altering esophageal motility. Four patients who developed dysphagia demonstrated slower gastric emptying and greater dysplasia risk index preoperatively. AIM analysis may allow detection of subtle esophageal abnormalities potentially leading to postoperative dysphagia.