Background Prediction of neonatal respiratory morbidity may be useful to plan delivery in complicated pregnancies. The limited predictive performance of the current diagnostic tests together with the risks of an invasive procedure restricts the use of fetal lung maturity assessment. Objective The objective of this study was to evaluate the performance of quantitative ultrasound texture analysis of the fetal lung (quantusFLM) to predict neonatal respiratory morbidity in preterm and early-term (<39.0 weeks) deliveries. Study Design This was a prospective multicenter study conducted in 20 centers worldwide. Fetal lung ultrasound images were obtained at 25.0-38.6 weeks of gestation within 48 hours of delivery, stored in Digital Imaging and Communication in Medicine format, and analyzed with quantusFLM. Physicians were blinded to the analysis. At delivery, perinatal outcomes and the occurrence of neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, were registered. The performance of the ultrasound texture analysis test to predict neonatal respiratory morbidity was evaluated. Results A total of 883 images were collected, but 17.3% were discarded because of poor image quality or exclusion criteria, leaving 730 observations for the final analysis. The prevalence of neonatal respiratory morbidity was 13.8% (101/730). The quantusFLM predicted neonatal respiratory morbidity with a sensitivity, specificity, and positive and negative predictive values of 74.3% (75/101), 88.6% (557/629), 51.0% (75/147), and 95.5% (557/583), respectively. Accuracy was 86.5% (632/730), and the positive and negative likelihood ratios were 6.5 and 0.3, respectively. Conclusion The quantusFLM predicted neonatal respiratory morbidity with an accuracy similar to that previously reported for other tests with the advantage of being a non-invasive technique.

BackgroundIntrauterine growth restriction (IUGR) induces fetal cardiac remodelling and dysfunction, which persists postnatally and may explain the link between low birth weight and increased cardiovascular mortality in adulthood. However, the cellular and molecular bases for these changes are still not well understood. We tested the hypothesis that IUGR is associated with structural and functional gene expression changes in the fetal sarcomere cytoarchitecture, which remain present in adulthood.Methods and ResultsIUGR was induced in New Zealand pregnant rabbits by selective ligation of the utero-placental vessels. Fetal echocardiography demonstrated more globular hearts and signs of cardiac dysfunction in IUGR. Second harmonic generation microscopy (SHGM) showed shorter sarcomere length and shorter A-band and thick-thin filament interaction lengths, that were already present in utero and persisted at 70 postnatal days (adulthood). Sarcomeric M-band (GO: 0031430) functional term was over-represented in IUGR fetal hearts.ConclusionThe results suggest that IUGR induces cardiac dysfunction and permanent changes on the sarcomere.

The relatively high rates of resistance to four of the 15 antibiotics tested confirm that for women allergic to penicillin and colonised with GBS, antibiotic sensitivities should be determined. We noticed increasing resistance to clindamycin over a 7-year period. Ongoing surveillance of local antibiotic resistance patterns at the institutional level is important in determining optimal prophylaxis as resistance patterns differ between institutions and are increasing.

Abstract. Automatic quantification of cardiac muscle properties in tissue sections might provide important information related to different types of diseases. Second harmonic generation (SHG) imaging provides a stain-free microscopy approach to image cardiac fibers that, combined with our methodology of the automated measurement of the ultrastructure of muscle fibers, computes a reliable set of quantitative image features (sarcomere length, A-band length, thick-thin interaction length, and fiber orientation). We evaluated the performance of our methodology in computer-generated muscle fibers modeling some artifacts that are present during the image acquisition. Then, we also evaluated it by comparing it to manual measurements in SHG images from cardiac tissue of fetal and adult rabbits. The results showed a good performance of our methodology at high signal-tonoise ratio of 20 dB. We conclude that our automated measurements enable reliable characterization of cardiac fiber tissues to systematically study cardiac tissue in a wide range of conditions.