AIMC Topic: Calcium Signaling

Clear Filters Showing 1 to 10 of 14 articles

Multiscale simulations that incorporate patient-specific neural network models of platelet calcium signaling predict diverse thrombotic outcomes under flow.

PLoS computational biology
During thrombosis, platelets rapidly deposit and activate on the vessel wall, driving conditions such as myocardial infarction and stroke. The complexity of thrombus formation in pathological flow geometries, along with patient-specific pharmacologic...

Computational Fuzzy Modelling Approach to Analyze Neuronal Calcium Dynamics With Intracellular Fluxes.

Cell biochemistry and biophysics
Mathematical neuroscience investigates how calcium distribution in nerve cells affects the neurological system. The interaction of numerous systems is necessary for the operation of several cellular processes in neuron cells, such as calcium, buffer,...

Deep learning reveals a damage signalling hierarchy that coordinates different cell behaviours driving wound re-epithelialisation.

Development (Cambridge, England)
One of the key tissue movements driving closure of a wound is re-epithelialisation. Earlier wound healing studies describe the dynamic cell behaviours that contribute to wound re-epithelialisation, including cell division, cell shape changes and cell...

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to .

International journal of molecular sciences
(Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor gene...

A deep learning-based approach for efficient detection and classification of local Ca²⁺ release events in Full-Frame confocal imaging.

Cell calcium
The release of Ca ions from intracellular stores plays a crucial role in many cellular processes, acting as a secondary messenger in various cell types, including cardiomyocytes, smooth muscle cells, hepatocytes, and many others. Detecting and classi...

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.

Cell research
The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the ...

Learnable latent embeddings for joint behavioural and neural analysis.

Nature
Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neu...

Deep learning models for image and data processes of intracellular calcium ions.

Cellular signalling
Intracellular calcium ion (Ca) in cytoplasm as an intracellular second messenger is involved in almost all important cellular activities of organisms. Generally its concentration ([Ca]) is tested by live imaging followed image and data processes, in ...

Analysis of Drug Effects on iPSC Cardiomyocytes with Machine Learning.

Annals of biomedical engineering
Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive experimental platform to investigate cardiac diseases and therapeutic outcome. In this study, iPSC-CMs were utilized to study their calcium transient...

Efficient Position Decoding Methods Based on Fluorescence Calcium Imaging in the Mouse Hippocampus.

Neural computation
Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigati...