281 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 paper presents an integrated framework that automates the generation of bio-informed, closed-circuit microvasculature models by combining a stochastic growth algorithm, an inverse design strategy, and a rapid electrical network dynamics solver to bridge the gap between in silico simulations and in vitro microfluidic applications for studying vascular function in health and disease.
This paper presents Generative Lung Architecture Modeling (GLAM), an integrated framework that combines high-resolution 3D imaging with a U-Net generative diffusion model to design and 3D-bioprint anatomically accurate, biologically compatible lung microtissues for disease modeling and regenerative medicine.
This study presents a scalable, micro-patterned hydrogel vascular graft that utilizes engineered shear stress redistribution and a bioactive matrix to accelerate the formation of stable, mature endothelial monolayers, offering a promising solution for creating growth-competent, thrombosis-resistant small-diameter grafts for pediatric patients.
This study demonstrates that while cow parity has a comparable impact on the accuracy of near-infrared spectroscopy for predicting milk fat and somatic cell count, it significantly affects lactose measurement reliability, indicating that parity-specific calibration is essential for sustainable, real-time milk quality monitoring.
The paper introduces EnhancAR, an autoregressive deep learning model that leverages evolutionary conservation in unaligned homologous enhancer sequences to generate functionally diverse and cell-type-specific enhancers without relying on scarce labeled cell type data.
This study demonstrates that photo-crosslinkable silk fibroin-hyaluronic acid hybrid hydrogels provide an injectable, porous 3D platform that supports human chondrocyte viability and drives significant mechanical maturation through endogenous extracellular matrix deposition, making them a promising biomimetic strategy for cartilage tissue engineering.
This predictive simulation study reveals that muscle fibre type distribution significantly influences the metabolic cost and biomechanics of gait, with slow twitch fibres reducing energy costs at lower speeds but becoming less efficient than fast twitch fibres at higher running speeds, thereby driving adaptive changes in stride frequency and length to maintain mechanical efficiency.
This paper presents an improved, open-source LED-based optical autofocus module for light microscopy and a 2D autocorrelation method to quantify its performance, demonstrating that the new system achieves axial stability with a standard deviation of less than 10 nm over 45 minutes despite initial power variations.
This paper demonstrates how a coding agent can formalize and transfer DNA origami design expertise by converting human domain knowledge into repeatable text-file instructions, enabling autonomous execution of complex design pipelines, parametric scaling, and molecular dynamics simulations.
LAS3R is a low-cost, open-source, and secure framework built on a Raspberry Pi hub and ESP32 microcontrollers that enables researchers with minimal technical expertise to rapidly prototype, deploy, and remotely manage multiple custom laboratory automation devices while ensuring robustness and data security.