Lung Ultrasound Segmentation and Adaptation Between COVID-19 and Community-Acquired Pneumonia

Lung ultrasound imaging has been shown effective in detecting typical patterns for interstitial pneumonia, as a point-of-care tool for both patients with COVID-19 and other community-acquired pneumonia (CAP). In this work, we focus on the hyperechoic B-line segmentation task. Using deep neural networks, we automatically outline the regions that are indicative of pathology-sensitive artifacts and their associated sonographic patterns. With a real-world data-scarce scenario, we investigate approaches to utilize both COVID-19 and CAP lung ultrasound data to train the networks; comparing fine-tuning and unsupervised domain adaptation. Segmenting either type of lung condition at inference may support a range of clinical applications during evolving epidemic stages, but also demonstrates value in resource-constrained clinical scenarios. Adapting real clinical data acquired from COVID-19 patients to those from CAP patients significantly improved Dice scores from 0.60 to 0.87 (p < 0.001) and from 0.43 to 0.71 (p < 0.001), on independent COVID-19 and CAP test cases, respectively. It is of practical value that the improvement was demonstrated with only a small amount of data in both training and adaptation data sets, a common constraint for deploying machine learning models in clinical practice. Interestingly, we also report that the inverse adaptation, from labelled CAP data to unlabeled COVID-19 data, did not demonstrate an improvement when tested on either condition. Furthermore, we offer a possible explanation that correlates the segmentation performance to label consistency and data domain diversity in this point-of-care lung ultrasound application

Effects of triclosan in the freshwater mussel Dreissena polymorpha: a proteomic investigation

Triclosan (TCS, 5-chloro-2-(2,4-dichlorophenoxy)phenol) is commonly used in several personal care products, textiles, and children's toys. Because the removal of TCS by wastewater treatment plants is incomplete, its environmental fate is to be discharged into freshwater ecosystems, where its ecotoxicological impact is still largely unexplored. Previously, we began a structured multi-tiered approach in order to evaluate TCS toxicity in the freshwater mussel Dreissena polymorpha. The results of our previous studies, based on in vitro and in vivo experiments, highlighted a pronounced cytogenotoxic effect exerted by TCS, and showed that an increase in oxidative stress was likely to be one of its main toxic mechanisms. In this work, in order to investigate TCS toxicity mechanisms in aquatic non-target species in greater depth, we decided to use a proteomic approach, analysing changes in protein expression profiles in gills of D. polymorpha exposed for seven days to TCS. Moreover, thiobarbituric acid reactive substances (TBARS) were measured to investigate further the role played by TCS in inducing oxidative stress. Finally, TCS bioaccumulation in mussel tissues was also assessed, to ensure an effective accumulation of the toxicant. Our results not only confirmed the role played by TCS in inducing oxidative stress, but furthered knowledge about the mechanism exerted by TCS in inducing toxicity in an aquatic non-target organisms. TCS induced significant alterations in protein expression profiles in gills of D. polymorpha. The wide range of proteins affected suggested that this chemical has marked effects on various biological processes, especially those involved in calcium binding or stress response. We also confirmed that the proteomic analysis, using 2-DE and de novo sequencing, is a reliable and powerful approach to investigate cellular responses to pollutants in a non-model organism with few genomic sequences available in databases

A redox proteomic investigation of oxidative stress caused by benzoylecgonine in the freshwater bivalve Dreissena polymorpha

Drugs of abuse and their human metabolites have been recently recognized as emerging environmental contaminants. Notwithstanding the fact that these kinds of compounds share some features with pharmaceuticals, their ecotoxicology has not yet been extensively investigated, although some of their characteristics may potentially threaten aquatic ecosystems. One of the most abundant drugs found in rivers and wastewaters is benzoylecgonine (BE), the main metabolite of cocaine. We applied a redox proteomics approach to evaluate changes in the proteome of Dreissena polymorpha exposed to two different concentrations of BE (0.5 and 1 mu g/l). Exposures were performed in vivo for a period of 14days and the effect of oxidative stress on protein thiol and carbonyl groups in mussel gills were evaluated. One-dimensional electrophoresis did not reveal a reduction in protein thiol content but showed a significant increase of protein carbonylation at both doses tested. Then, protein profiling using two-dimensional gel electrophoresis was performed with subsequent matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) and TOF/TOF with LIFT technique and linear ion trap combined with orbitrap mass spectrometer (LTQ-Orbitrap). This yielded de novo protein sequences suitable for database searching. These preliminary results and protein identifications obtained suggest that BE causes oxidative stress. Oxidative modifications were detected in differing classes of proteins such as those of the cytoskeleton, energetic metabolism and stress response