AIMC Topic: Mice

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The geometry of representational drift in natural and artificial neural networks.

PLoS computational biology
Neurons in sensory areas encode/represent stimuli. Surprisingly, recent studies have suggested that, even during persistent performance, these representations are not stable and change over the course of days and weeks. We examine stimulus representa...

3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.

International journal of molecular sciences
Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and demyelination in the brain, spinal cord, and optic nerve. Optic neuritis, characterized by inflammation and demyelination of the optic nerve, is a sympt...

A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution.

Nature neuroscience
In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p) calcium imaging is a powerful tool to probe such network-scale phenomena. However, estimating the ...

Assessment of Thermal Damage from Robot-Drilled Craniotomy for Cranial Window Surgery in Mice.

Journal of visualized experiments : JoVE
Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphoton or other intravital imaging techniques. However, when performing any craniotomy by hand, there is often thermal damage to brain tissue, which is in...

A fully automated deep learning pipeline for micro-CT-imaging-based densitometry of lung fibrosis murine models.

Respiratory research
Idiopathic pulmonary fibrosis, the archetype of pulmonary fibrosis (PF), is a chronic lung disease of a poor prognosis, characterized by progressively worsening of lung function. Although histology is still the gold standard for PF assessment in prec...

An explainable deep learning-based algorithm with an attention mechanism for predicting the live birth potential of mouse embryos.

Artificial intelligence in medicine
In assisted reproductive technology (ART), embryos produced by in vitro fertilization (IVF) are graded according to their live birth potential, and high-grade embryos are preferentially transplanted. However, rates of live birth following clinical AR...

G2Φnet: Relating genotype and biomechanical phenotype of tissues with deep learning.

PLoS computational biology
Many genetic mutations adversely affect the structure and function of load-bearing soft tissues, with clinical sequelae often responsible for disability or death. Parallel advances in genetics and histomechanical characterization provide significant ...

Magnetic torque-driven living microrobots for increased tumor infiltration.

Science robotics
Biohybrid bacteria-based microrobots are increasingly recognized as promising externally controllable vehicles for targeted cancer therapy. Magnetic fields in particular have been used as a safe means to transfer energy and direct their motion. Thus ...

LangMoDHS: A deep learning language model for predicting DNase I hypersensitive sites in mouse genome.

Mathematical biosciences and engineering : MBE
DNase I hypersensitive sites (DHSs) are a specific genomic region, which is critical to detect or understand cis-regulatory elements. Although there are many methods developed to detect DHSs, there is a big gap in practice. We presented a deep learni...

Combining mass spectrometry and machine learning to discover bioactive peptides.

Nature communications
Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the lit...