Browse Articles

The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Cheng et al. | Nov 07, 2021

The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro

Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.

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Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426

Còdol et al. | Oct 05, 2023

Defying chemical tagging: inhomogeneities in the wide binary system HIP 34407/HIP 34426
Image credit: Pixabay

This assessed the hypothesis that stars in wide binary systems are chemically homogeneous because of their shared origin. Abundances of the HIP 34407/HIP 34426 binary were obtained by analyzing high-resolution spectra of the system. Discrepancies found in the system’s elemental abundances might be an indicator of the presence of rocky planets around this star. Thus, the differences found in chemical composition might demonstrate limitations in the assumptions of chemical tagging.

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Machine learning for retinopathy prediction: Unveiling the importance of age and HbA1c with XGBoost

Ramachandran et al. | Sep 05, 2024

Machine learning for retinopathy prediction: Unveiling the importance of age and HbA1c with XGBoost

The purpose of our study was to examine the correlation of glycosylated hemoglobin (HbA1c), blood pressure (BP) readings, and lipid levels with retinopathy. Our main hypothesis was that poor glycemic control, as evident by high HbA1c levels, high blood pressure, and abnormal lipid levels, causes an increased risk of retinopathy. We identified the top two features that were most important to the model as age and HbA1c. This indicates that older patients with poor glycemic control are more likely to show presence of retinopathy.

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Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

Gunawardena et al. | Apr 18, 2022

Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

In this study, the authors examined how Sri Lankan Americans (SLAs) view racial issues in the U.S. The main hypothesis is that SLAs, as a minority in the U.S., are supportive of the Black Lives Matter movement and its political goal, challenging the common notion that SLAs are anti-Black. The study found that a majority of SLAs believe the U.S. has systemic racism, favor BLM, and favor affirmative action. IT also found that Tamil SLAs have more favorable views of BLM and affirmative action than Sinhalese SLAs.

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Comparing Measurements of Sun-Earth Distance: Shadow Method and Two Pinhole Method Variations

Rajakumar et al. | Feb 21, 2022

Comparing Measurements of Sun-Earth Distance: Shadow Method and Two Pinhole Method Variations

This study compares three methods regarding their accuracy in calculating the distance between the Earth and the Sun. The hypothesis presented was that the shadow method would have the greatest mean accuracy, followed by the tube pinhole method, and finally the plate pinhole method. The results validate the hypothesis; however, further investigation would be helpful in determining effective mitigation of each method’s limitations and the effectiveness of each method in determining the distance of other light-emitting objects distant from the Earth.

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Legacy mercury, reservoir dynamics, and dredging effects on methylmercury in San Francisco Bay

Silver et al. | Aug 24, 2026

Legacy mercury, reservoir dynamics, and dredging effects on methylmercury in San Francisco Bay

This study analyzes over two decades of monitoring data (1999-2022) to investigate how legacy mining, reservoir water releases, and dredging activities influence toxic methylmercury (MeHg) levels in San Francisco Bay. The findings reveal a significant delayed correlation between river flow and San Francisco Bay MeHg, and counter to the authors' hypothesis, a strong association between increased MeHg concentrations in the bay and both total annual dredging volume and beneficial sediment reuse / upland sediment disposal.

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Innovative fake health news detection: Integrating emotional features into graph neural networks

Wang et al. | Jul 03, 2026

Innovative fake health news detection: Integrating emotional features into graph neural networks
Image credit: Wang and Wang

This manuscript tackles a major social issue in the health news sector, with social media being one of the primary sources of information and a prime spot to propagate fake news. The author proposes X-HND , which is a unique architecture that combines emotional and contextual analysis in a Graph Neural Network to accurately detect fake news. This was a multi-step process which involved the creation of a custom health news dataset (HNDataset), and an emotional variant that uses RoBERTa to extract emotion. These dataset were then used to prove the hypothesis that accuracy increases when the custom dataset is used to train the model and that with the integration of emotion capture, the detection accuracy increases further.

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