AIMC Topic: Mice

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Tetanus-driven biohybrid multijoint robots powered by muscle rings with enhanced contractile force.

Science advances
Biohybrid actuators using muscle rings have been limited to twitching movements and are unsuitable for sustained contractile force applications. In this study, we developed muscle rings capable of generating high contractile forces under tetanus stim...

Exploration of Predictive Potential of AI-enabled Portable System in Anticancer Drug Delivery: A Comparative Study with Modified Gompertz like Biphasic Response Model.

AAPS PharmSciTech
Mathematical models are conventionally used to understand the of tumor behaviors, but they generally lack in precisely correlating drug efficacy with tumor response. Artificial intelligence (AI) has forged a new avenue in cancer management, but requi...

Molecular mechanisms of efferocytosis imbalance in the idiopathic pulmonary fibrosis microenvironment: from gene screening to dynamic regulation analysis.

Biology direct
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary disease characterized by alveolar structural destruction and fibrosis. In recent years, efferocytosis has been recognized as playing a crucial role in the occurrence a...

DeepEthoProfile-Rapid Behavior Recognition in Long-Term Recorded Home-Cage Mice.

eNeuro
Animal behavior is crucial for understanding both normal brain function and dysfunction. To facilitate behavior analysis of mice within their home environments, we developed DeepEthoProfile, an open-source software powered by a deep convolutional neu...

CalTrig: A GUI-Based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents.

eNeuro
Advances in in vivo Ca imaging using miniature microscopes have enabled researchers to study single-neuron activity in freely moving animals. Tools such as Minian and CalmAn have been developed to convert Ca visual signals to numerical data, collecti...

Identification of necroptotic biomarkers associated with immune microenvironment in sepsis based on the protein-protein interaction network and machine learning.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Necroptosis is inflammatorily sparked and closely associated with sepsis, but the crosstalk between necroptosis and inflammation in sepsis has rarely been studied in depth. This study is designed to reveal the role of necroptosis in the p...

Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity.

Nature communications
Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. Howe...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

Nature communications
The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urgent need for novel therapeutics. Drug-resistant infections now contribute to approximately 5 million deaths annually, yet traditional antibiotic discov...

Machine-Learning-Driven Discovery of -Phenylbenzenesulfonamides as a Novel Chemotype for Lactate Dehydrogenase A Inhibition with Anti-Pancreatic Cancer Activity.

Journal of medicinal chemistry
Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the structural diversity of LDHA inhibitors remains limited. Here, we utilized machine learning techniqu...