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Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Mathew et al. | Aug 11, 2019

Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Coronary Artery Disease (CAD) is the leading cause of death in the United States, and 81% of Acute Kidney Injury (AKI) patients in the renal fibrosis stage later develop CAD. In this study, Mathew and Joykutty aimed to create a cost-effective strategy to treat AKI and thus prevent CAD using a model of the zebrafish, Danio rerio. They first tested whether AKI is induced in Danio rerio upon exposure to environmental toxins, then evaluated nitrotyrosine as an early biomarker for toxin-induced AKI. Finally, they evaluated 4 treatments of renal fibrosis, the last stage of AKI, and found that the compound SB431542 was the most effective treatment (reduced fibrosis by 99.97%). Their approach to treating AKI patients, and potentially prevent CAD, is economically feasible for translation into the clinic in both developing and developed countries.

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Stereolithography 3D-printed stents with silica and zirconia nanoparticle reinforcement for intracranial aneurysm treatment

Panda et al. | Oct 12, 2026

Stereolithography 3D-printed stents with silica and zirconia nanoparticle reinforcement for intracranial aneurysm treatment
Image credit: Panda, Jeong, and Srinivasan

This manuscript focuses on improving the mechanical strength and radiopacity of SLA 3D-printed stent materials by incorporating nanoparticles for their application in flow-diverting stents (FDSs) used to treat aneurysms. The authors used biocompatible, bioresorbable resin formulations with varying concentrations of silica and zirconium to enhance tensile strength and radiopacity, respectively. The authors employed SEM to confirm the incorporation of nanoparticles, and CT imaging was used to assess the effect of zirconium-infused FDSs.

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Feature extraction from peak detection algorithms for enhanced EMG-based hand gesture recognition models

Nathan et al. | Jan 10, 2026

Feature extraction from peak detection algorithms for enhanced EMG-based hand gesture recognition models
Image credit: Nathan and Raju

This manuscript evaluates peak detection algorithms for feature extraction in EMG-based hand gesture recognition using a random forest classifier. The study demonstrates that wavelet-based peak detection features achieve the highest classification accuracy (96.5%), outperforming other methods. The results highlight the potential of peak features to improve EMG-based prosthetic control systems.

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Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae

Jani et al. | Aug 11, 2023

Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae
Image credit: Jordan Whitfield

Modern day fossil fuels are prone to polluting our environment, which can provide major habitat loss to many animals in our ecosystems. Algae-based biofuels have become an increasingly popular alternative to fossil fuels because of their sustainability, effectiveness, and environmentally-friendly nature. To encourage algae growth and solidify its role as an emerging biofuel, we tested basic (in terms of pH) solutions on pond water to determine which solution is most efficient in inducing the growth of algae.

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