351 papers
This paper introduces HDX FineMapping, a fast, low-cost, and high-resolution mass spectrometry methodology that achieves 100% sequence coverage and complete epitope characterization for glycosylated targets like PD1, offering a superior alternative to traditional methods for validating AI-designed therapeutics without requiring crystallization or mutations.
This study utilizes a neonatal rat model to demonstrate that necrotizing enterocolitis-induced acute kidney injury is characterized by systemic inflammation and renal hypoxia, validating photoacoustic imaging as a promising non-invasive method for early detection of these physiological changes.
This study introduces a 3D organotypic artery-graft culture platform that enables non-destructive, longitudinal multiphoton imaging of tissue remodeling, successfully correlating short-term in vitro responses to specific TGF-beta isoforms and graft designs with long-term in vivo outcomes to facilitate the pre-clinical optimization of vascular grafts.
This paper presents a patient-specific, multiscale biatrial digital twin that integrates electrophysiology, mechanics, and circulation to simulate and analyze the physiological and pathological (atrial fibrillation) mechanisms driving atrial function and hemodynamic changes.
This paper introduces a high-resolution three-dimensional analytical framework for retinal microvasculature that overcomes the limitations of traditional two-dimensional methods to reveal the intermediate layer plexus as a critical site of early vulnerability during abnormal vascular development and neovascular remodeling.
This study demonstrates that engineering mesoscale microtrenches on cardiovascular biomaterials stabilizes endothelial monolayers under extreme shear by creating protective flow gradients that promote mechanoadaptation, enhance nitric oxide production, and suppress inflammatory activation, thereby offering a material-agnostic strategy to improve the hemocompatibility of high-shear implants.
This study develops and validates a computational fluid particle dynamics-informed machine learning framework that optimizes smart inhaler nozzle parameters based on patient-specific breathing patterns and drug properties to achieve uniform drug delivery to the small airways across all five lung lobes, significantly outperforming conventional inhalation strategies.
This study demonstrates that cell-cell interfacial tension serves as a tunable mechanical parameter for computationally designing and engineering diverse layered tissue architectures, including a recursive strategy capable of organizing multiple cell types into arbitrary numbers of distinct layers.
This paper presents a generalizable framework for high-plex spectral imaging that leverages DNA-barcoded labeling and programmable signal amplification to enable precise signal tuning, systematic panel optimization, and robust unmixing, thereby facilitating the simultaneous imaging of numerous subcellular structures without fluidic cycling.
This study demonstrates that non-continuous neuromodulation, triggered by either dorsal root ganglia signals or bladder volume thresholds, effectively increases bladder capacity in awake, unrestrained felines to a degree comparable to continuous stimulation while significantly reducing total stimulation time.
This paper presents a deterministic, bead-free DNA barcoding strategy for 512 microwell arrays using a vacuum-driven multi-layer microfluidic network and combinatorial dual indexing, which enables efficient, low-cost, and uniform sample pooling for next-generation sequencing applications.
This paper presents advancements in an automated breast density detection algorithm that utilizes signal-dependent noise modeling and ensemble averaging to achieve robust, technology-agnostic performance across diverse mammographic image representations for improved breast cancer risk prediction.
This paper introduces kinGEMs, a robust framework that integrates deep learning-predicted kinetic parameters with uncertainty-aware stochastic tuning to generate accurate, resource-constrained enzyme-constrained genome-scale models for a diverse range of organisms, thereby overcoming data scarcity barriers in metabolic engineering and synthetic biology.
This paper introduces SAKe, a thermally stable, kelch-like designer protein engineered to form large, well-defined, pH-dependent two-dimensional assemblies on solid surfaces while maintaining structural integrity, thereby providing a versatile platform for the nanofabrication of functional protein-based materials.
This study demonstrates that a continuous bioreactor, optimized for specific environmental conditions and inoculated with either nasal swab specimens or synthetic microbial communities, can maintain stable, reproducible nasal microbiomes for over a month, providing a robust model for investigating nasal ecology and developing targeted *Staphylococcus aureus* decolonization strategies.
This study demonstrates a bioprinting strategy using human iPSC-derived mesodermal progenitor cells to generate centimeter-scale, self-organizing macrovascular constructs that spontaneously differentiate into multi-layered vessel walls, integrate with microvasculature, and withstand perfusion, thereby addressing a critical bottleneck in creating perfusable, vascularized tissue constructs.
This study proposes a new pre-operative hemodynamic risk factor, derived from patient-specific Fluid-Structure Interaction simulations, to effectively predict the occurrence of type I and III endoleaks following Thoracic Endovascular Aortic Repair (TEVAR).
This study presents a gold nanoparticle-assisted optoporation technique that enables spatially selective gene delivery to tumor-associated macrophages within 3D pancreatic cancer spheroids, successfully reprogramming them to an anti-tumorigenic state and modulating the tumor microenvironment.
This study identifies the accumulation of unrepaired DNA damage and a consequent decline in DNA damage response signaling as the primary drivers of viability loss and transcriptional dysfunction in high-density Chinese hamster ovary (CHO) cell perfusion cultures, revealing an intrinsic limitation in CHO genomic plasticity compared to HEK293 cells.
This study demonstrates that stimulated Raman scattering microscopy combined with deuterium-labeled metabolites can non-invasively quantify and distinguish cell-line-specific glycogen and lipid droplet dynamics in ovarian and cervical cancer models, offering a promising tool for metabolic phenotyping to guide early diagnosis and targeted therapies.