344 papers
This study introduces a novel class of ionizable lipids featuring a sulfur-bearing HHES motif that simultaneously scavenges reactive oxygen species and enables rapid metabolic clearance, thereby decoupling mRNA delivery potency from toxicity and demonstrating safe, effective therapeutic outcomes in both systemic and subretinal applications.
This study demonstrates that replacing the BCL11A repressor binding site with a TAL1:GATA1 activator motif in the HBG1/2 promoters, particularly via CRISPR/Cas9-mediated homology-directed repair combined with NHEJ/alt-EJ inhibition, effectively reactivates fetal hemoglobin and corrects the sickle cell phenotype in patient-derived hematopoietic stem cells.
This paper presents a custom device that enables robust light sheet fluorescence microscopy imaging of biological specimens requiring an air-liquid interface, demonstrated through successful applications on mouse salivary glands, human skin cultures, and fruit fly brains.
This paper demonstrates that GROQ-seq enables highly reproducible, quantitative, and scalable measurement of protein function across independent biological replicates and distinct laboratory facilities, validating its utility for generating large-scale datasets for protein engineering and machine learning.
This study introduces an open-source, realistic in-silico brain phantom that incorporates susceptibility anisotropy to demonstrate how neglecting this factor significantly increases errors in negative susceptibility estimates, thereby highlighting the necessity of including anisotropy in susceptibility separation algorithms for improved accuracy.
This paper presents an autonomous LLM agent framework that enables microscopy researchers without machine learning expertise to develop, train, and optimize deep learning models for quantitative image analysis by simply describing their experimental goals, achieving performance comparable to human experts across diverse microscopy modalities.
This paper proposes a multi-metric consensus framework using rank aggregation to overcome the limitations of single-metric spectral similarity assessments, thereby providing a more robust and physically meaningful basis for validating biomechanical models and designing machine learning loss functions.
This study introduces a microfluidic platform that enables the co-development of distinct dorsal and ventral forebrain identities within a single, continuous organoid by delivering localized Sonic hedgehog signaling, thereby offering a scalable alternative to organoid fusion for studying brain regionalization.
This paper presents an improved 1300-nm three-photon microscope that enables high-resolution structural and functional imaging of the intact mouse brain at depths up to 2.5 mm and 2 mm, respectively, thereby accessing deep brain regions previously unreachable by multiphoton imaging.
This study demonstrates that engineering cytokines to anchor to hyaluronic acid, rather than collagen, significantly enhances intratumoral retention and therapeutic efficacy of IL-12/IL-15 combination therapy while markedly improving safety by reducing systemic inflammation, liver toxicity, and local tissue damage.
This paper introduces PA-SfM, a novel tracker-free framework that achieves high-fidelity 3D freehand photoacoustic imaging by integrating differentiable acoustic radiation modeling with a coarse-to-fine optimization strategy to simultaneously recover sensor poses and reconstruct vascular structures without external positioning devices.
By combining angle-resolved experiments with ray-tracing simulations, this study reveals that light scattering in *C. elegans* comprises distinct surface and volume components that differentially enhance boundary and internal structure visibility, thereby establishing a framework to optimize imaging contrast through specific illumination and environmental conditions.
This study presents KRH, a fully computationally designed Staphylococcus aureus Cas9 variant that expands PAM recognition to NNNRRT and achieves editing efficiencies comparable to or exceeding evolution-derived variants, demonstrating the power of computational design to rationally engineer high-performance genome-editing tools without experimental optimization.
This study characterizes the mechanical, rheological, and sensory properties of minimally processed lion's mane mushroom steak, demonstrating its favorable meat-like texture and establishing a significant inverse correlation between its measured physical stiffness and perceived softness to support its development as a whole-cut alternative protein.
The authors developed a human synovial tendon-on-a-chip model that recapitulates key features of peritendinous adhesions through synovial fibroblast-driven inflammation and matrix deposition, demonstrating its utility as a new approach methodology for identifying the IL-6/JAK/STAT pathway as a therapeutic target for anti-fibrotic drugs.
The study introduces Z-TAC, a scalable and generalizable strategy that converts existing IgG antibodies into plug-and-play degraders capable of efficiently and sustainably eliminating diverse cell-surface proteins, including receptor combinations and targets lacking selective antagonists.
This study experimentally validates that using Dirichlet boundary conditions derived from device impedance, rather than conventional Neumann current density conditions, is critical for accurately modeling directional DBS electric fields and preventing significant overestimation of the Volume of Tissue Activated.
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 introduces Volumetric Scattering Microscopy (VSM), a scan-free, optical-computational framework that enables high-fidelity, large-field 3D fluorescence imaging in scattering biological tissues by capturing angularly resolved speckle patterns and reconstructing volumetric structures without mechanical scanning or wavefront measurement.