AIMC Topic: Animals

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Deep learning-driven drug response prediction and mechanistic insights in cancer genomics.

Scientific reports
In the field of cancer therapy, the diversity and heterogeneity of cancer genomes in clinical patients complicate and challenge the effective use of non-targeted drugs, as these drugs often fail to address specific genetic events. Recent advancements...

Artificial intelligence derived grading of mustard gas induced corneal injury and opacity.

Scientific reports
Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessing corneal damage due to chemical injury in live rabbits remains lacking. This study aimed to develo...

Deep-learning-based automated prediction of mouse seminiferous tubule stage by using bright-field microscopy.

Scientific reports
Infertility is a global issue, and approximately 50% of cases are due to male factors, with defective spermatogenesis being the main one. For studies of spermatogenesis, evaluating the seminiferous tubule stage is essential. However, current evaluati...

Enhancing occluded and standard bird object recognition using fuzzy-based ensembled computer vision approach with convolutional neural network.

Scientific reports
Classifying bird species is essential for ecological study and biodiversity protection, currently, conventional approaches are frequently laborious and susceptible to mistakes. Convolutional Neural Networks (CNNs) provide a more reliable option for f...

Benthic communities on restored coral reefs confer equivalent aesthetic value to healthy reefs.

Scientific reports
Coral reefs are valuable ecosystems that provide diverse ecosystem services to people. For example, many reefs have exceptionally high tourism value, attracting visitors to experience their ecologically and visually rich reef habitat. However, human-...

ToxACoL: an endpoint-aware and task-focused compound representation learning paradigm for acute toxicity assessment.

Nature communications
Multi-species acute toxicity assessment forms the basis for chemical classification, labelling and risk management. Existing deep learning methods struggle with diverse experimental conditions, imbalanced data, and scarce target data, hindering their...

Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy.

Nature communications
Metabolic homeostasis requires engagement of catabolic and anabolic pathways consuming nutrients that generate and consume energy and biomass. Our current understanding of cell homeostasis and metabolism, including how cells utilize nutrients, comes ...

Brainstem noradrenergic modulation of the kisspeptin neuron GnRH pulse generator in mice.

Nature communications
Brainstem noradrenaline (NA) neurons modulate the activity of many neural networks including those responsible for the control of fertility. Using brain slice electrophysiology, we demonstrate that the arcuate nucleus kisspeptin (ARN) neurons, recent...

A simplified minimodel of visual cortical neurons.

Nature communications
Artificial neural networks (ANNs) have been shown to predict neural responses in primary visual cortex (V1) better than classical models. However, this performance often comes at the expense of simplicity and interpretability. Here we introduce a new...

Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy.

Nature communications
DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Micro...