AIMC Topic: Animals

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Artificial intelligence and companion animals: Perspectives on digital healthcare for dogs, cats, and pet ownership.

Research in veterinary science
The exponential increase in global pet ownership has been creating an urgent demand for novel solutions to upgrade care for companion animals, particularly dogs and cats. Similar to its impact on other domains, artificial intelligence (AI) delivers a...

Multi-omics reveals the polyethylene terephthalate carcinogenicity: Cancer progression and immune microenvironment.

Ecotoxicology and environmental safety
Polyethylene terephthalate (PET), a polymer widely used in consumer products, has recently been implicated in cancer progression, though its mechanistic underpinnings remain elusive. This multidisciplinary study systematically investigates PET's carc...

Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.

Nature communications
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed...

Microglial pruning of glycinergic synapses disinhibits spinal PKCγ interneurons to drive pain hypersensitivity in mice.

Science translational medicine
Microglial activation is linked to neuroinflammation in neuropathic pain. Recently, microglia-mediated synaptic pruning has received mounting attention. However, the exact role of spinal microglia in modulating neuropathic pain-associated neural circ...

Bio-inspired robotics in times of ecological crisis: an attempt at self-criticism.

Bioinspiration & biomimetics
This article attempts to show that current trends in bio-inspired robotics research are incompatible with the transformations needed to address the current ecological crisis. A large part of the scientific community takes refuge behind short-term cha...

Chemical imaging for biological systems: techniques, AI-driven processing, and applications.

Journal of materials chemistry. B
Visualizing the chemical compositions of biological samples is pivotal to advancing biological sciences, with the past two decades witnessing the emergence of innovative chemical imaging platforms such as single-molecule imaging, coherent Raman scatt...

Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.

PloS one
Ecologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series. Modern technological devices such as video recorders and drones now allow researchers to dir...

Morphological traits and machine learning for genetic lineage prediction of two reef-building corals.

PloS one
Integrating multiple lines of evidence that support molecular taxonomy analysis has proven to be a robust method for species delimitation in scleractinian corals. However, morphology often conflicts with genetic approaches due to high phenotypic plas...

Hidden Markov model for acoustic pesticide exposure detection and hive identification in stingless bees.

PloS one
Pollinator populations are declining globally at an unprecedented rate, driven by factors such as pathogens, habitat loss, climate change, and the widespread application of pesticides. Although colony losses remain difficult to prevent, precision bee...

Unsupervised learning reveals rapid gait adaptation after leg loss and regrowth in spiders.

The Journal of experimental biology
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...