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Mitochondrial genome editing reveals the impact of complex I heteroplasmic variants on human neurogenesis

This study edits mtDNA variants in human iPSCs to show that heteroplasmic complex I variants impair neuronal commitment.

Engineering an Enzymatically Active Granular Matrix for On-Chip Modeling of Bone-Like Mineralization

This paper develops an enzymatically active granular matrix for on-chip bone-like mineralization, demonstrating rapid in situ mineral formation under controlled conditions.

Modular biofabrication of a vascularized skeletal muscle model through endothelialized microvascular seeds

This paper develops a modular biofabrication strategy to create a vascularized skeletal muscle model by separately maturing muscle and vascular compartments and then assembling them.

Extending digital biology: bacterial survival and morphological heterogeneity under antibiotic stress

This study develops a workflow to generate morphological signatures of bacterial progeny under antibiotic stress, revealing distinct morphologies linked to survival and antibiotic type.

Measurement-Dependent Parameter Recoverability in Neural Cardiovascular LPN Inference

The paper evaluates parameter recoverability in cardiovascular LPN inference using a probabilistic neural framework, showing that accurate hemodynamic prediction does not guarantee correct parameter recovery.

Magnetoactive hydrogels to probe curvature-directed endothelial cell mechanosensing

This study uses a magnetoactive hydrogel to investigate how curvature affects endothelial cell mechanosensing, finding that curvature influences YAP localization and junctional dynamics independently of shear stress.

Agricultural digestate ultrafiltrate outperforms synthetic media for microalgal biomass production while enabling biostimulant generation

This study shows that livestock digestate ultrafiltrate supports higher microalgal biomass production than synthetic media and generates biostimulant biomass.

Detecting Sleep Deprivation from Running Biomechanics Using Machine Learning Classification: A Comparison Between Wearable and Laboratory Motion Capture

This study compares wearable and lab motion capture systems in detecting sleep deprivation through running biomechanics using machine learning, finding both systems can identify individual biomechanical changes but fail between-subject classification without personalized data.

NeuroPack: Advanced Learnable Packaging Toolkit Towards Ultra-High Compression Ratio for Volumetric Neuroimaging

NeuroPack compresses 3D neuroimaging data with high fidelity and ultra-high compression ratios using a hyperprior-driven deep learning toolkit.

Computational alternative to cardiac biopsy in multiple myeloma: utilizing the shape of routine laboratory data for the classification of AL cardiac amyloidosis

The paper develops machine learning models to classify AL cardiac amyloidosis in multiple myeloma patients using electronic medical records instead of cardiac biopsy.

Soft Sensing of Intracellular States for CHO Cell Bioprocessing with Ensemble Kalman Filters

This paper uses Ensemble Kalman Filters to estimate intracellular nucleotide sugar donors in CHO cell cultures from extracellular measurements, improving metabolic state inference.

Deep Learning Based Cell Segmentation of 3D Confocal Images of Wood for Enzymatic Hydrolysis Applications

This paper develops a 3D U-net model for segmenting wood cells in confocal images to improve predictions of enzymatic hydrolysis efficiency.

IOP-independent treatment for neurodegeneration in glaucoma using optimized ROS-scavenging microparticles for sustained release of erythropoietin

This paper develops ROS-scavenging microparticles for sustained EPO release to treat glaucoma neurodegeneration, showing neuron preservation in animal models.

A single-plane electrical impedance tomography framework for integrated liver and kidney assessment

This paper evaluates a single-plane electrical impedance tomography framework for assessing liver and kidney health, finding it feasible and effective for multi-organ evaluation.

Machine Learning-Based Early Prediction of Neural Microelectrode Lifetime Under Accelerated Aging Conditions

This paper develops a machine learning model to predict neural microelectrode lifetimes from early-life data under accelerated aging conditions, achieving significant error reduction through feature engineering and calibration.

Biosynthetic additive manufacturing through mycelium-bacteria consortia

This paper develops a biosynthetic additive manufacturing method using mycelium-bacteria consortia to convert lignocellulosic biomass into durable structural materials.

A Chemigenetic Fluorescence Lifetime Biosensor for Dopamine Sensing

This paper introduces dHaloLife635, a chemigenetic fluorescence lifetime sensor for dopamine that shows selectivity and stability in live cells.

Staged heavy-chain filtering enables Fab discovery from combinatorially intractable library spaces

This paper introduces a staged approach to Fab discovery by sequentially enriching heavy-chain variants and remating them with light-chain repertoires to overcome combinatorial complexity in antibody library screening.

EverGreen: A Calcium Sensing Fluorescent Protein with Ultra-Slow Response Properties

The paper introduces a fluorescent calcium biosensor with ultra-slow response kinetics, useful for applications where delayed signal detection is advantageous.

Tissue-Derived Insoluble Type I and Type II Collagen Inks for 3D Printing of Fibrillar Collagen Scaffolds

This paper develops tissue-derived insoluble type I and type II collagen inks for 3D printing of scaffolds, showing viable cell responses and dimensional stability.