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Alloferon improves the growth performance and developmental time of mealworms (Tenebrio molitor)

Shon et al. | Oct 20, 2023

Alloferon improves the growth performance and developmental time of mealworms <em>(Tenebrio molitor)</em>

Mealworms (Tenebrio molitor) are important food sources for reptiles, birds, and other organisms, as well as for humans. However, the slow growth and low survival rate of mealworms cause problems for mass production. Since alloferon, a synthetic peptide, showed long-term immunological effects on mealworms, we hypothesized that alloferon would function as a growth promoter to maximize mealworm production. We discovered that the overall weight of the alloferon-containing gelatin diet group was 39.5-90% heavier, and the development time of the experimental group was shortened up to 20.6-39.6% than the control group.

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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization

Singh et al. | Feb 08, 2023

Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Image credit: Robina Weermeijer

Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.

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Analysis of ultraviolet light as a bactericide of gram-negative bacteria in Cladophora macroalgae extracts

Newell et al. | Nov 07, 2022

Analysis of ultraviolet light as a bactericide of gram-negative bacteria in <em>Cladophora</em> macroalgae extracts

Here, the authors sought to use Cladophora macroalgae as a possible antibiotic to address the growing threat of antibiotic resistance in pathogenic bacteria. However, when they observed algae extracts to be greatly contaminated with gram-negative bacteria, they adapted to explore the ability to use ultraviolet light as a bactericide. They found that treatment with ultraviolet light had a significant effect.

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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

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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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