AIMC Topic: Animals

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Identification and validation of endoplasmic reticulum stress-related diagnostic biomarkers for type 1 diabetic cardiomyopathy based on bioinformatics and machine learning.

Frontiers in endocrinology
BACKGROUND: Diabetic cardiomyopathy (DC) is a serious complication in patients with type 1 diabetes mellitus and has become a growing public health problem worldwide. There is evidence that endoplasmic reticulum stress (ERS) is involved in the pathog...

Robot-Assisted Stereotactic Microinjection Method for Precision Cell Transplantation in Rat and Canine Models.

Cell transplantation
Cell transplantation is a promising approach for addressing neurodegenerative conditions. In this study, we developed a robot-assisted stereotactic microinjection system for transplanting cells. We evaluated the factors that affect cellular graft via...

Design and application of ISSA-BP neural network model for predicting soft tissue relaxation force.

Acta of bioengineering and biomechanics
: Accurate biomechanical modeling is crucial for enhancing the realism of virtual surgical training. This study addressed the computational cost and complexity associated with traditional viscoelastic models by incorporating neural network algorithms...

Probing the dark chemical matter against PDE4 for the management of psoriasis using in silico, in vitro and in vivo approach.

Molecular diversity
The potential downsides for the present treatment for psoriasis are drug resistance, reduced efficacy, risk of mental episodes, and drug interactions. Hence, this study aims to discover a new drug for psoriasis by considering global research efforts ...

Histopathology image classification based on semantic correlation clustering domain adaptation.

Artificial intelligence in medicine
Deep learning has been successfully applied to histopathology image classification tasks. However, the performance of deep models is data-driven, and the acquisition and annotation of pathological image samples are difficult, which limit the model's ...

Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics.

Drug discovery today
Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyond lifestyle changes and current medications. Existing anti-obesity drugs face limitations regarding efficacy, side effects, weight regain and high co...

Miniature origami robot for various biological micromanipulations.

Nature communications
Robotic micromanipulation is widely applied in biological research and medical procedures, providing a level of operational precision and stability beyond human capability. Compared with traditional micromanipulators that require assembly from many p...

Generative AI extracts ecological meaning from the complex three dimensional shapes of bird bills.

PLoS computational biology
Data on the three dimensional shape of organismal morphology is becoming increasingly available, and forms part of a new revolution in high-throughput phenomics that promises to help understand ecological and evolutionary processes that influence phe...

Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning.

PLoS computational biology
Although the cerebellum is typically associated with supervised learning algorithms, it also exhibits extensive involvement in reward processing. In this study, we investigated the cerebellum's role in executing reinforcement learning algorithms, wit...

Machine learning-based prediction reveals kinase MAP4K4 regulates neutrophil differentiation through phosphorylating apoptosis-related proteins.

PLoS computational biology
Neutrophils, an essential innate immune cell type with a short lifespan, rely on continuous replenishment from bone marrow (BM) precursors. Although it is established that neutrophils are derived from the granulocyte-macrophage progenitor (GMP), the ...