AIMC Topic: Larva

Clear Filters Showing 1 to 10 of 69 articles

Leveraging Retrieval-Augmented Generation to Accelerate Discoveries on Mealworm Larvae and Plastic Degradation.

Environmental science & technology
Large language models (LLMs) are transforming broad research areas, yet concerns about their trustworthiness remain. This study explored the use of Retrieval-Augmented Generation (RAG) to improve LLMs' knowledge extraction in the field of mealworm-me...

Maturation of GABAergic signalling times the opening of a critical period in Drosophila melanogaster.

Scientific reports
Critical periods (CPs) during the development of neural networks are widely documented. Activity manipulation during open CPs leads to debilitating effects to the mature neural network. Detailed understanding of the contribution of CPs to network dev...

High throughput machine learning pipeline to characterize larval zebrafish motor behavior.

PloS one
Using machine learning, we developed models that rigorously detect and classify larval zebrafish spontaneous and stimulus-evoked behaviors in various well plate formats. Zebrafish are an ideal model system for investigating the neural substrates unde...

Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors.

Science robotics
Brains evolve within specific sensory and physical environments, yet neuroscience has traditionally focused on studying neural circuits in isolation. Understanding of their function requires integrative brain-body testing in realistic contexts. To in...

VNC-Dist: A machine learning-based semi-automated pipeline for quantification of neuronal position in the C. elegans ventral nerve cord.

PloS one
The C. elegans ventral nerve cord (VNC) provides a genetically tractable model for investigating the developmental mechanisms involved in neuronal positioning and organization. The VNC of newly hatched larvae contains a set of 22 motoneurons organize...

Image-based honey bee larval viral and bacterial diagnosis using machine learning.

Scientific reports
Honey bees are essential pollinators of ecosystems and agriculture worldwide. With an estimated 50-80% of crops pollinated by honey bees, they generate approximately $20 billion annually in market value in the U.S. alone. However, commercial beekeepe...

Diverse prey capture strategies in teleost larvae.

eLife
Animal behavior is adapted to the sensory environment in which it evolved, while also being constrained by physical limits, evolutionary history, and developmental trajectories. The hunting behavior of larval zebrafish (), a cyprinid native to stream...

Unsupervised deep clustering as a tool for the identification of dark taxa in biomonitoring.

Environmental monitoring and assessment
The identification of aquatic macroinvertebrates, particularly dark taxa like Chironomidae, due to their complex morphological features and unresolved taxonomy hinder the efficiency of routine biomonitoring. This study proposes an unsupervised deep c...

Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis.

Frontiers in cellular and infection microbiology
BACKGROUND: Cutaneous myiasis, one of the most frequently diagnosed myiasis types, is defined as skin or soft tissue on a living host infested by dipterous larvae (maggots). However, bibliometric analysis of this disease remains sparse. Machine learn...

Microbiome determinants of productivity in aquaculture of whiteleg shrimp.

Applied and environmental microbiology
UNLABELLED: Aquaculture holds immense promise for addressing the food needs of our growing global population. Yet, a quantitative understanding of the factors that control its efficiency and productivity has remained elusive. In this study, we addres...