3D bioprinting enables rapid fabrication of complex biological structures for tissue engineering applications. However, optimizing bioink formulation remains challenging due to complex relationships among material properties, printability, and cell v...
Deep learning-based animal activity recognition (AAR) achieves promising performance but remains constrained by its reliance on large labeled datasets. While pre-training offers a viable path toward reducing annotation dependency, existing approaches...
The nervous system flexibly processes information under different conditions. To do this, neural networks frequently rely on uniform expression of modulatory receptors by distinct classes of neurons to fine tune the computations supported by each neu...
BACKGROUND: Atg9-containing vesicles are enriched in synapses and undergo cycles of exo- and endocytosis similarly to synaptic vesicles, thereby linking presynaptic autophagy to neuronal activity. Dysfunction of presynaptic autophagy is a pathophysio...
In socially complex species, vocal signals often convey individual identity, enabling recognition and coordination of individualized groups. Jackdaws (Corvus monedula) are highly social corvids that form life-long monogamous pair bonds. They frequent...
The red flour beetle (Tribolium castaneum) is a key model organism in developmental biology, genetics, and agricultural research. To address the limited availability of high-quality microscopy data documenting its embryonic morphogenesis, we assemble...
BACKGROUND: Artificial intelligence is emerging as a transformative force in pharmaceutical sciences by enabling data-driven decision-making, automation, and predictive modeling. In ocular drug delivery, where therapeutic efficacy is hindered by comp...
Plateau zokor mounds, created by the burrowing activity of Plateau zokor, cause significant damage to crops, grasslands, and infrastructure, particularly in the alpine meadows of the Tibetan Plateau. Traditional field surveys are inefficient and labo...
Recurrent neural networks (RNNs) have emerged as a prominent tool for modeling cortical function. However, their conventional architecture is fundamentally lacking in physiological and anatomical fidelity, often raising questions regarding the validi...
Journal of chemical information and modeling
Dec 11, 2025
The prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties remains a central bottleneck in small-molecule discovery. We present the third-place solution from the PolarisHub Antiviral Competition, covering five ...
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