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 introduces a label-free, single-cell monitoring approach combining surface-enhanced Raman spectroscopy and machine learning to dynamically track both the identity and activation states of CAR T cells across donor-derived models and clinical patient samples, offering a rapid, point-of-care alternative to current static phenotyping methods.
The paper introduces **golgi**, an open-source, graphical platform that democratizes peripheral nerve stimulation modeling by integrating the entire workflow from anatomical imaging to fiber recruitment prediction, thereby enabling researchers and clinicians to achieve anatomically realistic, verifiable, and reproducible in-silico studies without requiring specialized coding expertise.
golgi is an open-source, multi-platform software suite that streamlines the entire workflow of peripheral nerve stimulation modeling—from image-based segmentation and meshing to fiber recruitment simulation—while ensuring verifiable reproducibility and eliminating commercial dependencies.
This study demonstrates that chemically targeting the active site of protein disulfide isomerase A6 (PDIA6) with a small molecule (pMePySH) significantly amplifies the catalytic efficiency of PDIA6 condensates, thereby accelerating oxidative protein folding and promoting insulin secretion both in vitro and in cellular environments.
This study demonstrates that device-embedded accelerometry provides a more robust and accurate biomarker for tracking Parkinsonian motor states across varying stimulation conditions compared to neural signals, supporting its integration into next-generation adaptive deep brain stimulation systems.
This study characterizes the optical properties of key tissue chromophores and tissue-mimicking phantoms across visible to short-wave infrared (SWIR) wavelengths, providing a consistent dataset integrated into an open-source toolkit to facilitate the design and simulation of next-generation SWIR spectroscopy and imaging technologies.
This paper presents an open-source, data-driven geometric framework that utilizes regression models trained on large anthropometric datasets to accurately estimate body segment inertial properties across diverse adult morphologies, including those with obesity, thereby outperforming existing methods and enhancing biomechanical analyses.
This paper introduces dodecagon light-sheet fluorescence microscopy (dodecaLSFM), a novel imaging technique that utilizes twelve omnidirectional light sheets to eliminate striping artifacts and achieve high-resolution, uniform large-volume imaging of cleared tissues, such as whole mouse brains, at both vascular and cellular levels.
This study presents a multiscale computational framework that successfully reproduces murine uterine electrophysiological properties from cellular to tissue levels during late pregnancy, identifying the regulation of specific ion currents (IK1, ICaL, and INa) as critical drivers in the transition from quiescence to labor.
While PLLA-PGA-CC scaffolds demonstrated biocompatibility and a trend toward enhanced bone regeneration compared to empty controls in a sheep mandibular defect model, their clinical utility for critical-sized defects is limited by poor osteoconductivity, fibrous tissue infiltration, and cyst formation.