Browse Articles

Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Levy et al. | Oct 13, 2014

Comparing Suturing And Stapling In Coronary Bypass Grafting Anastomosis

Coronary artery bypass grafts are a common technique to treat coronary heart disease. The authors compared the efficacy of suturing and stapling techniques using an artificial heart pump and silicone tubing and found that suturing, while more time and skill intensive, held pressure in the tubing better than stapling.

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Phytochemical Analysis of Amaranthus spinosus Linn.: An in vitro Analysis

Sharma et al. | Mar 20, 2021

Phytochemical Analysis of <em>Amaranthus spinosus</em> Linn.: An <em>in vitro</em> Analysis

Mainstream cancer treatments, which include radiotherapy and chemotherapeutic drugs, are known to induce oxidative damage to healthy somatic cells due to the liberation of harmful free radicals. In order to avert this, physiological antioxidants must be complemented with external antioxidants. Here the authors performed a preliminary phytochemical screen to identify alkaloids, saponins, flavonoids, polyphenols, and tannins in all parts of the Amaranthus spinosus Linn. plant. This paper describes the preparation of this crude extract and assesses its antioxidant properties for potential use in complementary cancer treatment.

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Near-infrared activation of environmentally-friendly gold and silver nanoparticles for unclogging arteries

Gill et al. | Sep 06, 2024

Near-infrared activation of environmentally-friendly gold and silver nanoparticles for unclogging arteries

Coronary artery disease, the leading cause of death worldwide, results from cholesterol build-up in coronary arteries, limiting blood and oxygen flow to the heart. This study investigated the use of gold and silver nanoparticles coated with aspirin and activated by near-infrared light to improve blood flow in a clogged artery model. The nanoparticles increased simulated blood flow rates, demonstrating potential as a less invasive and more targeted treatment for cardiovascular disease.

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Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Mandal et al. | Aug 21, 2024

Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.

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Autologous transplantation of fresh ovarian tissue in the ICR mice model

Wang et al. | Oct 24, 2022

Autologous transplantation of fresh ovarian tissue in the ICR mice model

In this study, we performed orthotopic auto-transplantation of fresh ovarian tissues by transplanting unilateral half ovarian tissue to the contralateral ovary in the ICR (Institute of Cancer Research) strain of outbred, heterogeneous mice to determine if the transplanted tissue could be functional. We found that the freshly transplanted mouse ovarian tissue survived and functional, as histochemical and immunofluorescence assays have shown that not only both follicles at different developing stages and corpus luteum are available, but the morphology of them are properly maintained within the transplanted tissue.

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A novel approach for early detection of Alzheimer’s disease using deep neural networks with magnetic resonance imaging

Ganesh et al. | Mar 20, 2022

A novel approach for early detection of Alzheimer’s disease using deep neural networks with magnetic resonance imaging

In the battle against Alzheimer's disease, early detection is critical to mitigating symptoms in patients. Here, the authors use a collection of MRI scans, layering with deep learning computer modeling, to investigate early stages of AD which can be hard to catch by human eye. Their model is successful, able to outperform previous models, and detected regions of interest in the brain for further consideration.

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String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction

Carroll et al. | Jul 12, 2020

String analysis of exon 10 of the CFTR gene and the use of Bioinformatics in determination of the most accurate DNA indicator for CF prediction

Cystic fibrosis is a genetic disease caused by mutations in the CFTR gene. In this paper, the authors attempt to identify variations in stretches of up to 8 nucleotides in the protein-coding portions of the CFTR gene that are associated with disease development. This would allow screening of newborns or even fetuses in utero to determine the likelihood they develop cystic fibrosis.

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