Publications by authors named "E E Romero"

Ice-free areas are habitats for most of Antarctica's terrestrial biodiversity. Although fungal communities are an important element of these habitats, knowledge of their assemblages and ecological functions is still limited. Herein, we investigated the diversity, composition, and ecological functionality of fungal communities inhabiting sediments from ice-free areas across pristine and anthropogenically impacted sites in the Fildes Peninsula on King George Island, Antarctica.

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Endoscopy is vital for detecting and diagnosing gastrointestinal diseases. Systematic examination protocols are key to enhancing detection, particularly for the early identification of premalignant conditions. Publicly available endoscopy image databases are crucial for machine learning research, yet challenges persist, particularly in identifying upper gastrointestinal anatomical landmarks to ensure effective and precise endoscopic procedures.

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Background: Climate change and human activities have caused the drying of marine environments around the world. An example is the Great Salt Lake in Utah, USA which is at a near record low water level. Adverse health effects have been associated with exposure to windblown dust originating from dried lakebed sediments, but mechanistic studies evaluating the health effects of these dusts are limited.

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The properties of two hybrid nanoarchaeosomes (hybrid nanoARCs) made of archaeolipids extracted from the halophilic archaea and combining the properties of archaeolipid bilayers with metallic nanoparticles are explored here. BS-nanoARC, consisting of a nanoARC loaded with yerba mate ( extract (YME)-biogenic silver nanoparticles (BSs), and [BS + BS-nanoARC], consistent of a BS-nanoARC core covered by an outer shell of BSs, were structurally characterized and their therapeutic activities screened. By employing 109 ± 5 µg gallic acid equivalents (GAEs) and 73.

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Cytomorphology evaluation of bone marrow cell is the initial step to diagnose different hematological diseases. This assessment is still manually performed by trained specialists, who may be a bottleneck within the clinical process. Deep learning algorithms are a promising approach to automate this bone marrow cell evaluation.

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