AIMC Topic: Animals

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Identification and validation of key autophagy-related genes in lupus nephritis by bioinformatics and machine learning.

PloS one
INTRODUCTION: Lupus nephritis (LN) is one of the most frequent and serious organic manifestations of systemic lupus erythematosus (SLE). Autophagy, a new form of programmed cell death, has been implicated in a variety of renal diseases, but the relat...

Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics.

Molecules (Basel, Switzerland)
Overcoming the growing challenge of antimicrobial resistance (AMR), which affects millions of people worldwide, has driven attention for the exploration of marine-derived antimicrobial peptides (AMPs) for innovative solutions. Cnidarians, such as cor...

Psychophysiological foundations of human physical activity behavior and motivation: theories, systems, mechanisms, evolution, and genetics.

Physiological reviews
Physical activity is a meaningful part of life that starts before birth and lasts until death. There are many health benefits to be derived from physical activity; hence, regular engagement is recommended on a weekly basis. However, these recommendat...

Decoding cortical folding patterns in marmosets using machine learning and large language model.

NeuroImage
Macroscale neuroimaging results have revealed significant differences in the structural and functional connectivity patterns of gyri and sulci in the primate cerebral cortex. Despite these findings, understanding these differences at the molecular le...

SEPO-FI: Deep-learning based software to calculate fusion index of muscle cells.

Computers in biology and medicine
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive cou...

Ledged Beam Walking Test Automatic Tracker: Artificial intelligence-based functional evaluation in a stroke model.

Computers in biology and medicine
The quantitative evaluation of motor function in experimental stroke models is essential for the preclinical assessment of new therapeutic strategies that can be transferred to clinical research; however, conventional assessment tests are hampered by...

Alzheimer's Disease: Exploring Pathophysiological Hypotheses and the Role of Machine Learning in Drug Discovery.

International journal of molecular sciences
Alzheimer's disease (AD) is a major neurodegenerative dementia, with its complex pathophysiology challenging current treatments. Recent advancements have shifted the focus from the traditionally dominant amyloid hypothesis toward a multifactorial und...

Elephant-inspired tapered cable-driven hyper-redundant manipulator: design and performance analysis.

Bioinspiration & biomimetics
The cable-driven hyper-redundant manipulator (CDHM), distinguished by its high flexibility and adjustable stiffness, is extensively utilized in confined and obstacle-rich environments such as aerospace and nuclear facilities. This paper introduces a ...

Insect-inspired passive wing collision recovery in flapping wing microrobots.

Bioinspiration & biomimetics
Flying insects have developed two distinct adaptive strategies to minimize wing damage during collisions. One strategy includes an elastic joint at the leading edge, which is evident in wasps and beetles, while another strategy features an adaptive a...

Integrating Retinal Segmentation Metrics with Machine Learning for Predictions from Mouse SD-OCT Scans.

Current eye research
PURPOSE: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.