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The Analysis of the Effects of Smoke and Water Vapor on Insect Pheromone Communication and Physical Condition: An Investigation of the Causes of Colony Collapse Disorder

Delatorre et al. | May 20, 2015

The Analysis of the Effects of Smoke and Water Vapor on Insect Pheromone Communication and Physical Condition: An Investigation of the Causes of Colony Collapse Disorder

The cause of insect colony collapse disorder (CCD) is still a mystery. In this study, the authors aimed to test the effects of two environmental factors, water vapor and smoke levels, on the social behavior and physical condition of insects. Their findings could help shed light on how changing environmental factors can contribute to CCD.

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Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Wang et al. | Feb 23, 2015

Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.

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Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation

Ganesh et al. | Feb 12, 2015

Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation

During transfer of organs from a donor to a patient, the organs deteriorate in part due to damage by free radicals. Application of antioxidant solutions could extend organ preservation times. The authors found that vitamin E and butylated hydroxytoluene seemed to be most effective in arresting cell damage of a bovine lung.

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Assessing machine learning model efficacy for brain tumor MRI classification: a multi-model approach

Dhingra et al. | Mar 14, 2026

Assessing machine learning model efficacy for brain tumor MRI classification: a multi-model approach
Image credit: Dhingra and Dhingra

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

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Examining the correlation between Massa Medicata Fermentata and Crohn’s disease: Implications for treatment and patient safety

Wang et al. | Sep 15, 2025

Examining the correlation between Massa Medicata Fermentata and Crohn’s disease: Implications for treatment and patient safety

Crohn’s disease is a chronic inflammatory bowel condition with symptoms like abdominal pain, fatigue, diarrhea, and malnutrition. Though there's no cure, various treatments help manage it. This study explored the potential impact of Massa Medicata Fermentata (MMF), a fermented Chinese herbal medicine containing Saccharomyces cerevisiae, on Crohn’s disease.

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