By fabricating and covalently assembling gelatin methacryloyl (GelMA) porous microgels, a new class of granular hydrogel scaffolds with hierarchical porosity is developed. These scaffolds have a significantly higher void fraction than their counterparts made up of nonporous microgels, enhancing cell recruitment and tissue integration. This research may
Alexander Kedzierski+9 more
wiley +1 more source
Wearable Haptic Feedback Interfaces for Augmenting Human Touch
The wearable haptic feedback interfaces enhance user experience in gaming, social media, biomedical instrumentation, and robotics by generating tactile sensations. This review discusses and categorizes current haptic feedback interfaces into force, thermal, and electrotactile stimulation‐based haptic feedback interfaces, elucidating their current ...
Shubham Patel+3 more
wiley +1 more source
Interpretable multi-instance heterogeneous graph network learning modelling CircRNA-drug sensitivity association prediction. [PDF]
Niu M, Wang C, Chen Y, Zou Q, Luo X.
europepmc +1 more source
The Emerging 4D Printing of Shape‐Memory Thermomorphs for Self‐Adaptative Biomedical Implants
4D printing enables the creation of smart implants that adapt to changing conditions in the human body over time. At the core of this technology are shape‐memory thermomorphs (SMTMs). This review offers an in‐depth analysis of 4D printing with SMTMs, emphasizing the latest advancements in smart materials, stimuli, programming principles, and their ...
Aixiang Ding, Fang Tang, Eben Alsberg
wiley +1 more source
A Novel Framework for Enhancing Decision-Making in Autonomous Cyber Defense Through Graph Embedding. [PDF]
Wang Z, Wang Y, Xiong X, Ren Q, Huang J.
europepmc +1 more source
scExtract: leveraging large language models for fully automated single-cell RNA-seq data annotation and prior-informed multi-dataset integration. [PDF]
Wu Y, Tang F.
europepmc +1 more source
Dynamic Multi-Behaviour, Orientation-Invariant Re-Identification of Holstein-Friesian Cattle. [PDF]
Perneel M+3 more
europepmc +1 more source
A deep learning model for prediction of lysine crotonylation sites by fusing multi-features based on multi-head self-attention mechanism. [PDF]
Liang Y, Li M.
europepmc +1 more source