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This study investigates how base-stacking interactions affect the stability of DNA tetrahedra by testing 16 designs, finding that altering a single base stack can change melting temperatures by up to 10°C.

This study evaluates sparse inertial sensor setups for accurate sagittal-plane motion analysis during walking and running, finding that setups with foot and thigh sensors provide reliable results.

This study develops a 3D-printed flexible microfluidic device for organ-on-a-chip applications, showing improved cell viability and differentiation compared to conventional methods.

This paper uses robotic visible-light OCT to visualize segmental Schlemms canal anatomy and its response to pilocarpine in mice, showing segmental changes in volume.

This paper investigates VEGF supplementation as a treatment for congenital diaphragmatic hernia (CDH)-associated lung abnormalities using an ex vivo model and nanoparticle-based delivery in vivo.

This study uses WISH-BONE to analyze 3D Sost mRNA and sclerostin distribution in mouse tibia midshafts after mechanical loading, showing region-specific changes and highlighting the method's importance for mechanoadaptation research.

The paper develops a U-Net model to segment mitochondrial networks in endothelial cells using holotomographic microscopy images.

This paper introduces an unsupervised neural network method for bladder endoscopy image stitching, achieving high success rates and robustness in challenging conditions.

This study evaluates biodegradable PDLLA optical fibers as neural interfaces in mice, showing degradation and efficient SW-NIR light transmission with potential for optogenetics and therapy.

This paper introduces a rapid, PCR- and sequencing-free DNA mutation detection method using CRISPR-Cas12a and extracellular vesicles for cancer diagnosis and treatment monitoring.

This study introduces hydroporation as a scalable and efficient method for delivering CAR-T cells, achieving higher yields and viability compared to traditional methods.

This study identifies a pro-myogenic domain in CYTOR and shows that chemically modified RNA delivery improves dystrophic myotube function.

This paper develops 3D human lung models using biomaterials to replicate early pulmonary fibrosis features and tests drug responses.

This paper introduces a biodegradable neural interface that monitors nerve injury recovery using machine learning, enabling early detection of neuroma formation and improved therapeutic outcomes.

This study uses physiologically-based muscle models to predict in vivo skeletal muscle energetics and finds they capture general features but underpredict energetic cost magnitude.

This study develops a highly extensible hydrogel bioink for high-speed 3D bioprinting, showing significant improvements in print speed and resolution.

This paper improves the sustainability of photofibroin by using an eco-friendly solvent, enabling versatile fabrication techniques for biomedical applications.

This paper validates Cellpose as a reliable method for segmenting single cells in autofluorescence microscopy images, showing high accuracy compared to manual segmentation.

This study uses electrophysiology and computational models to predict octopus arm movements based on spike timing and neural activity patterns.

This paper accelerates multi-electrode array simulations using sparse and low-rank matrix techniques, achieving up to 133x speedup with minimal error.