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Diba, M.

Publications and source records attributed to Diba, M..

2 recordsLinked to original sources

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

Controlled biomineralization is central to engineering physiologically relevant hard-tissue models, yet achieving spatially organized, three-dimensional (3D) mineral deposition in microfluidic on-chip systems remains challenging. While cell-based bone-on-chip platforms offer biological complexity, they intrinsically couple mineral initiation to confounding factors such as matrix remodeling and paracrine signaling, obscuring the earliest biochemical drivers of nucleation. Drawing inspiration from bottom-up synthetic biology, we engineered an enzymatically active granular matrix that recapitulates a key osteogenic function within a perfusable 3D microenvironment. Alkaline phosphatase (ALP), the key driver of native bone formation, was covalently conjugated to poly(ethylene glycol)-based (PEG) microgels via thiol-ene photochemistry, retaining over 90% enzymatic activity after 48 h. These monodisperse microgels were assembled into a jammed, perfusable matrix within an on-chip chamber, enabling independent control over enzyme loading and substrate delivery. The system supported rapid in situ mineralization (24-48 h), yielding a carbonated, calcium-deficient, apatite-like phase characteristic of early-stage bone mineral. We demonstrate that the spatial 3D localization of enzymatic activity to discrete microscale compartments, coupled with interstitial perfusion, enables localized and near-physiological mineral formation. This mechanistically defined, acellular platform provides a programmable foundation for investigating ALP-driven 3D mineralization and establishes a modular route toward hybrid biosynthetic models of (patho)physiological tissue mineralization.

bioengineering↗

X-TRUDE: A Process-Informed Framework for High-Fidelity Analysis of Hydrogel Extrusion

Reliable extrusion of viscoelastic hydrogels is crucial for technologies ranging from 3D (bio)printing to injectable therapeutics, yet current methods to characterize extrusion performance fail to mimic key processing conditions. Consequently, extrusion performance cannot be precisely predicted or controlled, particularly for emerging thermosensitive, shear-thinning, or heterogeneous hydrogels. Fundamentally, reliable extrusion is an emergent outcome of intrinsic materials properties coupled to extrinsic processing conditions. Here, we introduce X-TRUDE, a process-informed characterization platform that recapitulates the spatiotemporal conditions of the extrusion process by integrating in situ pressure sensing, controlled thermal conditions, and process-relevant flow-path geometries. X-TRUDE reveals extrusion-specific phenomena inaccessible with conventional methods, including the transient evolution of apparent rheological response and time-local instabilities such as heterogeneity-induced variations in extrudate morphology. Across monolithic, thermosensitive, and granular hydrogel formulations, X-TRUDE establishes temporal pressure fluctuation patterns as quantitative metrics to unravel mechanisms underlying extrusion variability and correlate pressure profiles with extrudate morphology. By linking intrinsic rheology with the physical extrusion environment, X-TRUDE provides a quantitative, mechanistic framework to benchmark extrudability across soft matter systems. This framework enables more reliable formulation development, reduces failure during process translation, and offers a generalizable tool for extrusion-based technologies in biofabrication, therapeutic delivery, and soft material manufacturing.

bioengineering↗