AIMC Topic: Calcium

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Constructing biologically constrained RNNs via Dale's backpropagation and topologically informed pruning.

Science advances
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...

Light-field deep learning enables high-throughput, scattering-mitigated calcium imaging.

Proceedings of the National Academy of Sciences of the United States of America
Light-field microscopy (LFM) enables high-throughput functional imaging by scanlessly encoding entire volumes in single snapshots. However, LFM's computational burden and vulnerability to scattering limit its application to biological imaging. We pre...

Stable intracranial imaging of dura mater-engrafted pancreatic islet cells in awake mice.

Nature communications
By transplanting pancreatic islets onto the dura mater of the mouse brain, we establish a microscopy platform that enables longitudinal intravital imaging of otherwise optically inaccessible tissue. The system combines a cranial window with an air-cu...

Predicting macroelement content in legumes with machine learning.

Scientific reports
This study aims to develop accurate and efficient machine learning models to predict the concentrations of phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) in 10 legume species naturally growing in the Çamlıhemşin district of Rize prov...

Biologically inspired neural network layer with homeostatic regulation and adaptive repair mechanisms.

Scientific reports
Neural networks face persistent challenges in maintaining stability and robustness during training, particularly in noisy or high-dimensional domains like molecular analysis. Inspired by biological neural systems that leverage homeostasis and self-re...

Hierarchical AF2RAVE for Multiconformation Virtual Screening Targeting S100 Ca-Binding Proteins.

Journal of chemical theory and computation
Protein function is driven by transitions between metastable conformations, many of which are not conserved across homologues, offering opportunities for selective drug design. Accurately modeling both backbone and side chain metastability, and gener...

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.

Scientific reports
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...

Calcium ion dynamic trajectory is associated with prognosis in patients with sepsis: A potential class mixture modeling study.

International immunopharmacology
Disturbed calcium homeostasis in patients with sepsis is associated with poor prognosis; however, its dynamic pattern and clinical significance remain unclear. This study aimed to establish an early warning system for calcium homeostasis in sepsis by...

CalTrig: A GUI-Based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents.

eNeuro
Advances in in vivo Ca imaging using miniature microscopes have enabled researchers to study single-neuron activity in freely moving animals. Tools such as Minian and CalmAn have been developed to convert Ca visual signals to numerical data, collecti...

Incidental Finding of Coronary and Non-Coronary Artery Calcium: What Do Clinicians Need To Know?

Current atherosclerosis reports
PURPOSE OF REVIEW: This review summarizes the role of incidentally and non-incidentally discovered coronary artery calcification (CAC) and the evolving role of non-coronary artery calcification in atherosclerotic cardiovascular disease (ASCVD) risk a...