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The Emergence of Tetracycline Resistance in Rumen Bacteria

Memili et al. | Sep 16, 2016

The Emergence of Tetracycline Resistance in Rumen Bacteria

The emergence of antibiotic-resistant pathogenic bacteria is a major concern for human health, rendering some antibiotics ineffective in treating diseases. The authors of this study tested the hypothesis that exposing rumen bacteria to tetracycline will gradually lead to the development of tetracycline-resistant bacteria, some of which will develop multidrug resistance.

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Ramifications of natural and artificial sweeteners on the gastrointestinal system

Cowen et al. | Jun 19, 2023

Ramifications of natural and artificial sweeteners on the gastrointestinal system

This study aimed to determine whether artificial sweeteners are harmful to the human microbiome by investigating two different bacteria found to be advantageous to the human gut, Escherichia coli and Bacillus coagulans. Results showed dramatic reduction in bacterial growth for agar plates containing two artificial sweeteners in comparison to two natural sweeteners. This led to the conclusion that both artificial sweeteners inhibit the growth of the two bacteria and warrants further study to determine if zero-sugar sweeteners may be worse for the human gut than natural sugar itself.

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Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Takemaru et al. | Feb 24, 2020

Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Acquired immunodeficiency syndrome (AIDS) is a life-threatening condition caused by the human immunodeficiency virus (HIV). In this work, Takemaru et al explored the role of Coiled-Coil Domain-Containing 11 (CCDC11) in HIV-1 budding. Their results suggest that CCDC11 is critical for efficient HIV-1 budding, potentially indicating CCDC11 a viable target for antiviral therapeutics without major side effects.

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Correlating inlet gas composition to conversion efficiency in plasma-assisted landfill gas reforming

Kim et al. | Jun 28, 2025

Correlating inlet gas composition to conversion efficiency in plasma-assisted landfill gas reforming

The escalating crisis of climate change, driven by the accumulation of greenhouse gases from human activities, demands urgent and innovative solutions to curb rising global temperatures. Plasma-based methane (CH4) and carbon dioxide (CO2) reforming offers a promising pathway for carbon capture and the sustainable production of hydrogen fuel and syngas components. To advance this technology, particularly in terms of energy efficiency and selectivity, it is essential to enhance the conversion efficiencies of CO2 and CH4.

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Artificial Intelligence Networks Towards Learning Without Forgetting

Kreiman et al. | Oct 26, 2018

Artificial Intelligence Networks Towards Learning Without Forgetting

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

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More Efficient Helicopter Blades Based on Whale Tubercles

Weitzman et al. | Dec 22, 2013

More Efficient Helicopter Blades Based on Whale Tubercles

Biomimicry is the practice of applying models and systems found in nature to improve the efficiency and usefulness of human technologies. In this study, the authors designed helicopter blades with tubercle structures similar to those found on the tails of humpback whales. The authors found that certain arrangements of these tubercle structures improved the windspeed and efficiency of a model helicopter.

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Tree-Based Learning Algorithms to Classify ECG with Arrhythmias

Sun et al. | Apr 23, 2025

Tree-Based Learning Algorithms to Classify ECG with Arrhythmias

Arrhythmias vary in type and treatment, and ECGs are used to detect them, though human interpretation can be inconsistent. The researchers tested four tree-based algorithms (gradient boosting, random forest, decision tree, and extra trees) on ECG data from over 10,000 patients.

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Part of speech distributions for Grimm versus artificially generated fairy tales

Arvind et al. | Nov 16, 2024

Part of speech distributions for Grimm versus artificially generated fairy tales
Image credit: Nayalia Y.

Here, the authors wanted to explore mathematical paradoxes in which there are multiple contradictory interpretations or analyses for a problem. They used ChatGPT to generate a novel dataset of fairy tales. They found statistical differences between the artificially generated text and human produced text based on the distribution of parts of speech elements.

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Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

Bennet et al. | Jul 02, 2024

Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.

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