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 study develops a biodegradable PLGA/PCL membrane-based lung alveoli-on-a-chip that mimics the dynamic structural evolution of the lung interface to effectively model diesel particulate matter-induced injury and evaluate therapeutic interventions.
This study presents a biodegradable, self-remodeling lung alveoli-on-a-chip that accurately mimics the human air-blood interface to effectively assess the oxidative and genotoxic pulmonary toxicity of various waste-combustion-derived particulates, revealing rubber combustion particles as the most hazardous.
This paper proposes a decoupled two-step framework that combines a YOLO-based detector with a specialized DenseNet121 ensemble classifier to achieve high-accuracy detection and fine-grained morphological classification of sickle red blood cells in full-scope microscopy, significantly outperforming single-step models especially for minority phenotypes.
This paper demonstrates that standard CTC-trained neural decoders in brain-to-text BCIs produce over-confident predictions, and proposes a two-stage cross-entropy training approach that generates calibrated, informative uncertainty to serve as an active control signal for safer and more effective probabilistic co-control.
This study demonstrates that engineering *Escherichia coli* with three coordinated pathways for sulfide generation, cadmium uptake, and nucleation enables the controlled biogenic synthesis of CdS quantum dots, where the specific combination of pathways dictates nanoparticle yield and size even under low cadmium concentrations.
This paper introduces D2IM-Strain, a data-driven approach that directly predicts bone strain fields from X-ray computed tomography images, significantly improving accuracy and reducing noise amplification compared to traditional displacement-derived methods.
This study demonstrates that deep-learning-guided tuning of heterodimeric coiled-coil linker stability enables the rational programming of artificial protein tube architectures, allowing for precise control over tube diameter and the formation of complex multilayered tube-in-tube structures through sequential assembly mechanisms.
This paper introduces a photothermal recycling (PTR) biosensing mechanism that utilizes plasmonic thermal effects to rapidly cycle biomolecular binders, thereby enabling continuous, subpicomolar-sensitive molecular quantification in complex biological fluids without the trade-off between measurement speed and sensitivity.
This study adapts the Merton jump-diffusion framework from quantitative finance to model tuberculosis patient survival as a state of biological solvency, demonstrating that a stochastic "distance-to-death" metric based on body mass index and HIV-driven volatility outperforms traditional Cox models in predicting mortality and enabling targeted clinical triage.
This paper validates a predictive simulation-based design optimization platform for personalizing assistive wearable devices, demonstrating that accurately predicting metabolic cost trends rather than achieving perfect biomechanical accuracy is sufficient for identifying optimal device parameters.