196 papers
Bioengineering sits at the vibrant intersection of biology and engineering, where scientists design new tools to understand life and solve real-world problems. From creating artificial organs to developing smart materials that mimic natural tissues, this field turns complex biological questions into tangible innovations that improve human health and our environment.
At Gist.Science, we track every new preprint in this category directly from bioRxiv. Our team processes each submission to provide both plain-language explanations for curious minds and detailed technical summaries for researchers, ensuring these cutting-edge discoveries are accessible to everyone. Below are the latest papers in bioengineering that have recently appeared on bioRxiv.
This study combines human experiments and modeling to demonstrate that while the Virtual Pivot Point strategy and trunk dynamics effectively manage stability and energy on gentle slopes, humans recruit a multi-joint knee and ankle strategy to navigate steeper terrain, offering critical insights for exoskeleton design.
This study presents a robust photoelectrochemical biosensing platform that integrates clamp-inhibited loop-mediated isothermal amplification with enzyme-free singlet oxygen transduction to achieve highly selective and sensitive detection of KRAS mutations in complex wild-type backgrounds, demonstrating clinical utility through validation in cell lines and patient tissues.
This study optimized the Zebrafish Embryo Genotyper (ZEG) automated system by refining chip design and operational parameters, achieving over 95% DNA collection sensitivity and embryo survival while increasing DNA yield by more than 50% without adverse effects on development.
This paper proposes the Plasmonic-AI-Organoid (PAO) framework, a systems-level architecture that integrates geometry-controlled plasmonic modeling, Bayesian kinetic inference via MCMC, and organoid validation to optimize next-generation biosensors through an active learning loop that significantly reduces computational costs while enhancing analytical performance.
This study demonstrates that the level of anatomical fidelity in computational models of the common iliac veins critically influences both the statistical characterization of shape variability and the accuracy of hemodynamic risk predictions for deep vein thrombosis, revealing that simplified geometries significantly overestimate low wall shear stress areas compared to patient-specific 3D reconstructions.
This paper introduces RDBCycleGAN-CBAM, a novel deep learning model that integrates residual dense blocks and convolutional block attention modules into a CycleGAN framework to significantly improve the quality of low-dose CT images while preserving structural details and reducing radiation exposure.
This study introduces a novel therapeutic strategy using bispecific antibody "Shedders" to recruit the protease ADAM10 to cell-surface proteins, inducing selective extracellular domain shedding that bypasses lysosomal trafficking and effectively reinvigorates immune responses, as demonstrated by the depletion of LAG-3 and other immune receptors.
This paper introduces MicrowellMicrofluidicsMiner (M3), a framework leveraging large language model agents to autonomously extract and curate microwell microfluidics design parameters from unstructured literature, achieving a 78% accuracy rate that significantly outperforms standalone models and facilitates data-driven device optimization.
This paper introduces a microfluidic agarose microdroplet platform that enables high-throughput DNA-encoded library screening of chromatin-associated targets within a near-native cellular context by combining mechanical stability, selective protein retention via mild permeabilization, and efficient ligand diffusion.
This study presents a zwitterionic polymer-coated multimodal microelectrode array that enables stable, chronic simultaneous detection of dopamine and electrophysiological signals in freely moving mice over four weeks by effectively mitigating biofouling and ensuring reference electrode stability.