Maria Cheriyan

Stem cell-derived kidney organoids contain nephron segments that recapitulate morphological and functional aspects of the human kidney. However, directed differentiation protocols for kidney organoids are largely conducted using biochemical signals to control differentiation. Here, the hypothesis that mechanical signals regulate nephrogenesis is investigated in 3D culture by encapsulating kidney organoids within viscoelastic alginate hydrogels with varying rates of stress relaxation. Tubular nephron segments are significantly more convoluted in kidney organoids differentiated in encapsulating hydrogels when compared with those in suspension culture. Hydrogel viscoelasticity regulates the spatial distribution of nephron segments within the differentiating kidney organoids. Consistent with these observations, a particle-based computational model predicts that the extent of deformation of the hydrogel-organoid interface regulates the morphology of nephron segments. Elevated extracellular calcium levels in the culture medium, which can be impacted by the hydrogels, decrease the glomerulus-to-tubule ratio of nephron segments. These findings reveal that hydrogel encapsulation regulates nephron patterning and morphology and suggest that the mechanical microenvironment is an important design variable for kidney regenerative medicine.

Extracellular matrix (ECM) viscoelasticity broadly regulates cell behavior. While hydrogels can approximate the viscoelasticity of native ECM, it remains challenging to recapitulate the rapid stress relaxation observed in many tissues without limiting the mechanical stability of the hydrogel. Here, we develop macroporous alginate hydrogels that have an order of magnitude increase in the rate of stress relaxation as compared to bulk hydrogels. The increased rate of stress relaxation occurs across a wide range of polymer molecular weights (MWs), which enables the use of high MW polymer for improved mechanical stability of the hydrogel. The rate of stress relaxation in macroporous hydrogels depends on the volume fraction of pores and the concentration of bovine serum albumin, which is added to the hydrogels to stabilize the macroporous structure during gelation. Relative to cell spheroids encapsulated in bulk hydrogels, spheroids in macroporous hydrogels have a significantly larger area and smaller circularity because of increased cell migration. A computational model provides a framework for the relationship between the macroporous architecture and morphogenesis of encapsulated spheroids that is consistent with experimental observations. Taken together, these findings elucidate the relationship between macroporous hydrogel architecture and stress relaxation and help to inform the design of macroporous hydrogels for materials-based cell therapies.

Serious illness conversations (SICs) align care with patients' values, goals, and preferences, yet they rarely occur in emergency departments (EDs), where time constraints and emotional burden often leave clinicians making high-stakes decisions without documented insight into what matters most to patients. We present a case study of ED GOAL-AI, a voice-based conversational agent for brief, structured values discussions with older adults in the ED, evaluated with 55 patients for feasibility and acceptability. Most participants completed the conversation and reported the interaction as acceptable and feasible, with ratings of feeling heard and understood comparable to clinicians. However, we also observed critical failure modes, including boundary violations such as hallucinated diagnostic statements, highlighting ethical and emotional risks. This work points to early promise for AI-mediated SICs while underscoring the need for careful boundary setting and participatory design before broader deployment.

Serious illness conversations (SICs) align care with patients' values, goals, and preferences, yet they rarely occur in emergency departments (EDs), where time constraints and emotional burden often leave clinicians making high-stakes decisions without documented insight into what matters most to patients. We present a case study of ED GOAL-AI, a voice-based conversational agent for brief, structured values discussions with older adults in the ED, evaluated with 55 patients for feasibility and acceptability. Most participants completed the conversation and reported the interaction as acceptable and feasible, with ratings of feeling heard and understood comparable to clinicians. However, we also observed critical failure modes, including boundary violations such as hallucinated diagnostic statements, highlighting ethical and emotional risks. This work points to early promise for AI-mediated SICs while underscoring the need for careful boundary setting and participatory design before broader deployment.