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This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.

Plastic pollution in the ocean is a major global concern. Remotely Operated Vehicles (ROVs) have promise for removing debris from the ocean, but more research is needed to achieve full effectiveness of the ROV technology. Wahlig and Gonzales tackle this issue by developing a deep learning model to distinguish trash from the environment in ROV images.

In this study, the authors identify new potential targets to treat advanced diffuse large B-cell lymphoma after treatment relapse and loss of CD19 expression.

The authors develop a machine learning method to reduce misclassification of objects in safety-critical applications such as medical diagnosis.

Hydrogels are commonly used in medicine, pharmaceuticals, and agriculture. Hydrogels absorb water by swelling and re-release this water by diffusion. This study sought to synthesize a biodegradable, cellulose-based hydrogel that is more effective at absorbing and re-releasing water than those produced by current methods. We tested the compressive strength of both the dry and swollen gels and the tensile strength of the swollen gels to elucidate the gel structure.

Omega-3 fatty acid derived lipid mediators have been implicated in resolving inflammation, and wound healing. Authors measured the impact of supplementation with lipid mediator Resolvin D1 and its precursor 17-HDHA on planaria regeneration. Planaria not only synthesize RvD1 from 17-DHA, but both RvD1 and 17-DHA enhanced regeneration.