AI Medical Compendium Journal:
Biomaterials

Showing 1 to 10 of 10 articles

Gradient-driven deep penetration of self-electrophoretic nanoparticles in acidic tumor microenvironments for enhanced antitumor therapy.

Biomaterials
Difficulty of nanomedicines to effectively penetrate the tumor core and achieve effective killing of tumor stem cells is an important factor leading to recurrence, metastasis and drug resistance of tumors. Strategies based on the tumor microenvironme...

Optimal structural characteristics of osteoinductivity in bioceramics derived from a novel high-throughput screening plus machine learning approach.

Biomaterials
Osteoinduction is an important feature of the next generation of bone repair materials. But the key structural factors and parameters of osteoinductive scaffolds are not yet clarified. This study leverages the efficiency of high-throughput screening ...

3D printed PEDOT:PSS-based conducting and patternable eutectogel electrodes for machine learning on textiles.

Biomaterials
The proliferation of medical wearables necessitates the development of novel electrodes for cutaneous electrophysiology. In this work, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is combined with a deep eutectic solvent (DES) a...

Advances in materials-based therapeutic strategies against osteoporosis.

Biomaterials
Osteoporosis is caused by the disruption in homeostasis between bone formation and bone resorption. Conventional management of osteoporosis involves systematic drug administration and hormonal therapy. These treatment strategies have limited curative...

Deep learning identification of stiffness markers in breast cancer.

Biomaterials
While essential to our understanding of solid tumor progression, the study of cell and tissue mechanics has yet to find traction in the clinic. Determining tissue stiffness, a mechanical property known to promote a malignant phenotype in vitro and in...

Decompartmentalisation as a simple color manipulation of plant-based marbling meat alternatives.

Biomaterials
Recent efforts for cell-based meat cuts focus on engineering edible scaffolds, with visual cues which are key to enhancing consumer acceptance, receiving less attention Here, we employed artificial intelligence (AI)-based screening of potential plant...

Automated evaluation of tumor spheroid behavior in 3D culture using deep learning-based recognition.

Biomaterials
Three-dimensional in vitro tumor models provide more physiologically relevant responses to drugs than 2D models, but the lack of proper evaluation indices and the laborious quantitation of tumor behavior in 3D have limited the use of 3D tumor models ...

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Biomaterials
Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gaps remain to be filled prior to clinical applications (e.g., immunotherapy). The lack of databases on...

Automated quantification of three-dimensional organization of fiber-like structures in biological tissues.

Biomaterials
Fiber-like structures are prevalent in biological tissues, yet quantitative approaches to assess their three-dimensional (3D) organization are lacking. We develop 3D directional variance, as a quantitative biomarker of truly 3D fibrillar organization...

Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.

Biomaterials
Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and m...