280 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 validates an automated ultrasound tracking algorithm for quantifying regional strain in human Achilles tendons and reveals that maximum and average longitudinal strains follow distinct progressive trajectories between survived and ruptured tendons during fatigue loading, suggesting early biomechanical differences precede overt structural failure.
The paper presents Dual-Mode Bio-CM2, a scalable computational miniature mesoscope that utilizes a shared optical architecture to simultaneously capture co-registered fluorescence and label-free reflectance images, enabling comprehensive multimodal analysis of biological function across diverse freely moving and head-fixed specimens.
Using a pooled CRISPR-Cas9 screen in patient-derived diffuse midline glioma models, researchers identified CTNNB1 as a key negative regulator of nanoparticle uptake and revealed that its depletion alters cell stiffness and endocytic mechanisms, thereby establishing a biology-first approach to optimize nanoparticle delivery strategies for pediatric brain tumors.
This study demonstrates that predictive simulations incorporating gait adaptations are essential for accurately estimating hip and knee joint loading in the presence of femoral and tibial torsional deformities, as failing to account for these natural kinematic adjustments leads to significant overestimation of joint forces.
This study demonstrates that for electrospun poly(vinylpyrrolidone) nanofibers used in regenerative endodontics, the specific identity of the loaded medicament is a superior predictor of fiber morphology than total drug loading, as revealed by a machine learning analysis of a failure-inclusive dataset.
This study establishes a comprehensive workflow integrating rheological characterization, computational fluid dynamics, and experimental validation to predict and assess the impact of shear stress on the viability and function of endothelial-epithelial co-cultures during extrusion bioprinting with GelMA hydrogels.
This study demonstrates that a simplified single-IMU visual biofeedback system using a Lower Limb Trajectory Error metric can effectively modify gait mechanics in able-bodied adults, inducing whole-limb reorganization across multiple segments rather than isolated joint changes, although the efficacy of adaptation depends on the specific movement target and feedback formulation.
This study utilizes subject-specific musculoskeletal modeling to demonstrate that trunk posture, movement direction, and magnitude significantly alter intervertebral loading and paraspinal muscle force asymmetry in adolescents with idiopathic scoliosis, with flexion and convex-sided movements generally producing the greatest biomechanical imbalances.
This study demonstrates that intrinsic extracellular matrix composition dictates tissue-specific susceptibility to decellularization damage, establishing a composition-driven strategy that shifts quality assessment from simple DNA removal toward preserving biologically relevant ECM components to enable the rational design of regenerative biomaterials with tissue-specific mechanical and biological properties.
This study demonstrates that the fluorescent marker Carbotrace 480, combined with Snailase treatment, provides an effective method for detecting protoplasts in a pigment-deficient *Chlorella sorokiniana* mutant, thereby facilitating the genetic optimization of this microalgae for sustainable nutrient production.