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 introduces TunLSCI, a deep learning-based framework that reconstructs high-fidelity cerebral blood flow images from ultra-low-illumination laser speckle contrast data, thereby reducing phototoxicity by approximately 157-fold and enabling stable, long-term longitudinal monitoring of cerebral perfusion in vivo.
This study presents a novel terahertz metamaterial absorber sensor featuring a central diamond-shaped threefold hexagon structure that achieves near-perfect triple-band absorption and high polarization conversion efficiency to effectively distinguish between healthy and Glioblastoma cells via microwave imaging.
This study demonstrates that coating individual *Chlamydomonas reinhardtii* cells with protective metal-phenolic networks not only enhances stress survival but also induces a reversible quiescent state that redirects carbon flux to significantly boost starch accumulation under light and lipid accumulation in darkness.
This paper demonstrates that the Gradient Impulse Response Function (GIRF) can effectively correct eddy current-induced sidebands in non-water-suppressed proton MR spectroscopy, enabling the recovery of metabolite signals and revealing that water suppression typically causes magnetization transfer effects that underestimate metabolite concentrations.
The paper introduces CRADLE-1, an automated framework that leverages fine-tuned protein language models and a multi-model workflow to accelerate multi-property lead optimization across diverse protein modalities by 4–7x compared to rational design, demonstrating that sequence-function data can largely supersede structural information in a black-box, lab-in-the-loop process.
This paper presents and validates a robust, label-free Digital Holographic Microscopy pipeline capable of accurately estimating cell viability across diverse industrial bioproduction conditions without requiring calibration, while also offering early detection of viability decline and correlation with protein titer.
This study characterizes peptide-induced extracellular vesicles in *E. coli* as a distinct, high-yield platform that enables the efficient production and purification of concentrated, correctly folded recombinant proteins with superior purity compared to endogenous outer membrane vesicles.
This paper introduces a teacher-student deep learning framework that generates white matter tractography from FLAIR images by leveraging knowledge distilled from diffusion MRI, demonstrating that tractography patterns may reflect a shared latent structural space rather than being unique to diffusion-specific imaging.
This study demonstrates that pubertal development in female pigs alters the anterior cruciate ligament's molecular profile and histology, specifically increasing estrogen receptor alpha expression in post-pubescent tissues, which suggests an age-dependent shift in hormonal sensitivity that may contribute to the higher risk of ACL injuries in adolescent female athletes.
This study introduces a synthetic immunological niche scaffold that captures stage-specific immune dysregulation in Type 1 Diabetes, enabling the identification of an early gene signature that distinguishes disease progressors and predicts therapeutic response to anti-TNF-α treatment.