AIMC Topic: Animals

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Manipulation of neuronal activity by an artificial spiking neural network implemented on a closed-loop brain-computer interface in non-human primates.

Journal of neural engineering
Closed-loop brain-computer interfaces can be used to bridge, modulate, or repair damaged connections within the brain to restore functional deficits. Towards this goal, we demonstrate that small artificial spiking neural networks can be bidirectional...

Hybrid deep learning optimization for smart agriculture: Dipper throated optimization and polar rose search applied to water quality prediction.

PloS one
Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dippe...

Quantitative modeling of mortality patterns in dogs exposed to alpha particle emitting radionuclides: Insights from competing risks and causal inference machine learning.

PloS one
This study employed state-of-the-art machine learning to evaluate the mortality effects of alpha-emitting radionuclides (241Am, 249Cf, 252Cf, 238Pu, 239Pu, 224Ra, 226Ra, 228Th) on 2,576 dogs, factoring in radioactivity levels, composition, administra...

Exploration of common pathogenic genes between cerebral amyloid angiopathy and insomnia based on bioinformatics and experimental validation.

Scientific reports
Cerebral amyloid angiopathy (CAA) and insomnia are age-related neurological disorders increasingly recognized as being closely associated. However, research on the shared genes and their biological mechanisms remains limited. This study aims to ident...

Computer vision to predict cell seeding coverage in re-endothelialized mouse lungs.

Scientific reports
Transplantation of donor grafts recellularized with recipient-derived or non-immunogenic universal cells is a potential means of reducing the graft rejection and post-transplant complications in lung transplantation. Achieving a fully recellularized ...

Artificial intelligence-driven computational methods for antibody design and optimization.

mAbs
Antibodies play a crucial role in our immune system. Their ability to bind to and neutralize pathogens opens opportunities to develop antibodies for therapeutic and diagnostic use. Computational methods capable of designing antibodies for a target an...

Deep Learning-Based Multimodal Fusion Approach for Predicting Acute Dermal Toxicity.

Journal of chemical information and modeling
Acute dermal toxicity testing is essential for assessing the safety of chemicals used in pharmaceuticals, pesticides, cosmetics, and industrial chemicals. Conventional toxicity testing methods rely significantly on animal tests, which are resource-in...

An in silico to in vivo approach identifies retinoid-X receptor activating tert-butylphenols used in food contact materials.

Scientific reports
The potential for food contact chemicals to disrupt genetic programs in development and metabolism raises concerns. Nuclear receptors (NRs) control many of these programs, and the retinoid-X receptor (RXR) is a DNA-binding partner for one-third of th...

Automated seafood freshness detection and preservation analysis using machine learning and paper-based pH sensors.

Scientific reports
Seafood, including fish, prawns and various marine products, is a critical component of global nutrition due to its high protein content, essential fatty acids, vitamins and minerals. Traditional methods for assessing seafood freshness such as sensor...

High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing.

Scientific reports
Caenorhabditis elegans is a widely used animal model for researching new disease treatments. In recent years, automated methods have been developed to extract mobility phenotypes and analyse, using statistical methods, whether there are differences b...