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This study analyzes genetic alterations and expression patterns of protein kinases involved in phagocytosis across multiple cancers using TCGA data.

Detecting cervical spondylosis using deep learning

The authors looked at how injuries sustained during water tubing, that require treatment at an emergency department, differ between males and females.

The authors looked at how nanosilver particles may negatively impact the pond water environment. They used D. magna as an indicator species to look at the impact of different concentrations of nanosilver particles.

To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.

The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.

The authors use blood smears from individuals with sickle cell disease to correlate sickle cell frequency with the occurrence of vaso-occlusive crises.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

The study explored converting Gracilaria seaweed waste—known for releasing toxic hydrogen sulfide when decomposed—into biochar as a sustainable solution for waste management and soil improvement.

The authors looked at the correlation between C reactive protein levels and neurological deficits in patients who had suffered an ischemic stroke.