AIMC Topic: Organoids

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Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...

A semi-automated algorithm for image analysis of respiratory organoids.

PLoS computational biology
Respiratory organoids have emerged as a powerful in vitro model for studying respiratory diseases and drug discovery. However, the high-throughput analysis of organoid images remains a challenge due to the lack of automated and accurate segmentation ...

Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response.

Journal of experimental & clinical cancer research : CR
The high intra-patient heterogeneity in multifocal primary prostate cancer (PCa) has curtailed the efficacy of current treatment options. By employing twin biopsies from multiple lesions with matched patient-derived organoids (PDO) models, the PCa mo...

HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system.

Nature communications
Self-organised three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems ...

Organoids as predictive platforms: advancing disease modeling, therapeutic innovation, and drug delivery systems.

Journal of controlled release : official journal of the Controlled Release Society
As three-dimensional (3D), physiologically relevant models, organoids are rapidly becoming revolutionary platforms in biomedical research. With their ability to recapitulate tissue architecture, disease heterogeneity, and patient-specific therapeutic...

Robotic micromanipulation for patterned and complex organoid biofabrication.

Science advances
Organoids have emerged as powerful models for recapitulating tissue physiology and pathology in biomedical research. However, the need for consistent and complex manufacturing of organoids remains a challenge. The absence of standardization and quali...

Enhanced electrophysiological recordings in acute brain slices, spheroids, and organoids using 3D high-density multielectrode arrays.

PloS one
Recent advances in three-dimensional (3D) biological brain models in vitro and ex vivo are creating new opportunities to understand the complexity of neural networks but pose the technological challenge of obtaining high-throughput recordings of elec...

Mechanistic Insights into the Effects of Liquid Crystalline Monomers on Intestinal Stem Cell Differentiation Imbalance by Integrating Machine Learning and Adverse Outcome Pathway Framework Based on Organoids.

Environmental science & technology
The global annual output of liquid crystal monomers (LCMs) continues to increase, yet associated environmental and health risks remain poorly characterized. Assessing the toxic effects of the LCM mixture and individual components is critical for risk...

Non-genetic neuromodulation with graphene optoelectronic actuators for disease models, stem cell maturation, and biohybrid robotics.

Nature communications
Light can serve as a tunable trigger for neurobioengineering technologies, enabling probing, control, and enhancement of brain function with unmatched spatiotemporal precision. Yet, these technologies often require genetic or structural alterations o...

Prediction of the hypothalamus-pituitary organoid formation using machine learning.

Cell reports methods
Multi-cellular organoids are self-assembly aggregates that mimic biological functions and developmental processes of many tissue types in vitro. They are widely employed for disease modeling and functional studies. Hypothalamus-pituitary organoids ca...