The ability to recognize that others have mental states, separate from us, and that these states are not always accurate portrayals of reality, is central for theory of mind (TOM). This capacity becomes particularly crucial when children explain causal relationships, as they must integrate their understanding of causality with their awareness of other's knowledge states. Skills like this are essential for effective communication and reflect a key developmental milestone in both cognitive and social reasoning. This study examines how children process causal scenarios while considering and tracking the knowledge states of multiple people. We will examine how children (ages 4-7) perform with conjunctive causal relationships, where two separate effects must combine to produce an outcome (e.g., watering a plant and giving it fertilizer causes it to bloom). Children are asked to explain how the outcome happened, and what knowledge each character has. The children will be given four causal events, varying in content, and follow the same causal structure, where each character is only aware of one cause (A or B). After the scenario, children will answer open-ended questions to assess their recall of what each character knows and test their understanding of how the outcome (C) occurred. We predict that younger children will recognize the causal outcome but struggle to differentiate knowledge states, while older children will demonstrate an improved ability to tailor their explanations based on other's perspectives. This study extends beyond previous studies that primarily focused on children's passive evaluation of explanation as our study will investigate children's active role in generating explanations tailored to different character's knowledge states. Our findings will contribute to the understanding of how the development of TOM shapes children's ability to understand and reason about causal relationships.

The proximal tubule (PT) and glomerulus are vital blood-filtering components of the nephron, the functional unit of the kidney. The components’ micro-scale sizes and intricate three-dimensional structures are critical to kidney function, although accurate in vitro modeling has proven difficult. Limitations in fabrication techniques have forced size scaling and imprecise morphology in models. In this study, we addressed fabrication limitations using multiphoton ablation to etch intricate, three-dimensional proximal tubule and glomerulus vessels in collagen hydrogels. We sought to demonstrate model viability by introducing human proximal tubular epithelial cells (hPTECs) and human umbilical vein endothelial cells (HUVECs), respectively, through cell perfusion. However, we encountered a significant challenge: due to the small diameter and high curvature of the micro-scale channels, the cells tended to aggregate, disrupting cell profusion and cellularization throughout the vessels. Cell aggregation was especially prominent in the glomerulus model due to the more tortuous and complex geometry. While our cellularization trials on native-scale models proved it is feasible to perfuse cells throughout the vessel, we still need to refine cellular profusion and cellularization. To improve cellular profusion and cellularization, we are first studying a 1.5-scale glomerulus model. The scaled model's increased vessel diameter and lower curvature demote cell aggregation and enhance the ease of cell profusion. We anticipate that cellularizing the 1.5-scale model will provide a deeper understanding of the variables facilitating cell profusion that we can use to improve native-scale vessel cellularization. Fabricating native-scale, accurate in vitro PT and glomerulus models is crucial for developing a deeper understanding of hemodynamic influence on kidney function. These findings contribute to the fabrication of more biomimetic in vitro PT and glomerulus models that will pioneer therapeutics and the understanding of kidney physiology and pathology.

Pulmonary Arterial Hypertension (PAH) is a deadly vascular disease, affecting the blood vessels of the lungs, with no existing cure. PAH is characterized by pulmonary arterial smooth muscle cell (PASMC) hypertrophy and hyperplasia, which increases resistance to blood flow within the pulmonary arteries, leading to rapid symptom progression and eventual death from right heart failure. My mentor and I hypothesize that defects in PASMC differentiation and alignment may contribute to PAH. To test whether alignment and phenotypic responses differ in patients with PAH, we designed a micropatterned collagen scaffold atop a glass coverslip. Explanted PASMCs from patients with PAH or failed donors (controls) were cultured on alternating 10-µm wide x 10-µm deep microchannels or unpatterned constructs and alignment, protein expression, and cellular morphology were compared across conditions. I evaluated 3 PAH and 3 control subjects and have collected preliminary data for each condition (control versus PAH), with three technical replicates each. Through these preliminary studies, I have demonstrated success of my model with consistent alignment observed on patterned substrates. Excitingly, PASMCs from patients with PAH expressed significantly decreased levels of the contractile protein, Calponin, when compared with control cells, including after responding to cues that promote alignment and contractility. This suggests that PAH PASMCs remain in an inappropriately synthetic or proliferative state. Moving forward, I plan to evaluate additional micropatterns by varying dimensions of rectangular and sine waves designs using an ablation protocol with a 2-photon microscope laser. Subsequent evaluation will include immunofluorescent staining of contractile and other SMC markers as well as transcriptomic evaluation of cellular responses to micropatterning. This work will enhance understanding of whether SMC abnormalities contribute to disease initiation and progression in PAH and will contribute to the broader effort of developing more complex models of pulmonary vascular disease.

Traumatic brain injury (TBI) is one of the leading causes of death in young adults. It is initiated by loss of endothelial junctions during deterioration of the blood-brain-barrier. Investigation into endothelial barriers has been enabled by high-resolution imaging via confocal microscopy. However, existing image analysis tools struggle to capture the complexity of EC morphology due to their reliance on rigid segmentation, limiting their ability to extract meaningful insights. My project focuses on developing a more effective method for analyzing ECs by implementing a pixel-based computational tool that provides a more nuanced analysis of EC junction integrity and morphology beyond traditional segmentation methods. Immunofluorescence (IF) images were obtained from an in vitro model of TBI mimicking 3D brain microvessels which were treated with kinase inhibitors (KIs) to determine which kinases promote or hinder recovery. If ECs remained damaged after treatment, it indicate the inhibited kinase was essential for recovery. If they improved, the kinase was likely disruptive. To identify these effects of KIs on EC based on IF images, I developed a pixel-based clustering tool that analyzes junction intensity without forcing explicit segmentation. By analyzing pixel intensities relative to cell nuclei, I generated profiles of each vessel that represent the tightness of EC junction. I used an existing AI-based tool, Cellpose, to define nucleus masks and wrote a customizable Python script to compute pixel distances and intensity variations, providing a detailed, unbiased view of EC behavior. Preliminary findings suggest that this method enhances the accuracy and efficiency of cellular analysis by eliminating segmentation bias and capturing subtle morphological changes. Future work involves integrating this tool with regression models to identify kinases that regulate EC junction integrity. This research has broad applications in vascular disease modeling and drug discovery, offering a new approach for studying cell behavior and developing targeted therapies. 

Children are not merely passive observers; they actively seek to understand the why behind events. A fundamental distinction in causal reasoning is between agentic causes, which attribute outcomes to the actions of an agent like a person, and non-agentic causes, which focus on environmental factors. Do children show preferences for agentic versus non-agentic explanations? Moreover, are they influenced by the outcome’s valence (positive or negative)? This study examines how outcome valence influences children's (4-9 years old) preferences for agentic versus non-agentic causes in situations where the cause is ambiguous. By analyzing their explanatory preferences, we investigate how the valence of outcomes shapes causal reasoning across development. Participants will be presented with scenarios describing everyday events. Each scenario will have a clear positive or negative outcome, and the cause of the event will be ambiguous, with both agentic and non-agentic explanations being plausible. For example, some participants might see an apple falling perfectly into someone's hand (positive), while others see it hitting their head (negative) - events that could be attributed to either a squirrel jumping up and down, or the wind blowing. Participants will then be asked to answer what caused the outcome via a forced-choice task. We predict that children will more often select agentic over non-agentic causes for negative outcomes compared to positive ones. We also expect that as age increases, their choice differences based on outcome valence will be more pronounced. This investigation helps us understand whether agency itself plays a role in early causal reasoning. If children demonstrate a stronger preference for agentic causes in negative outcomes, this may suggest that emotional valence influences how children construct causal explanations. Furthermore, examining children’s explanatory preferences - whether biased toward agentic causes or not - can tell us how they incorporate agency into their developing understanding of causality.

Engineered heart tissues (EHTs) have emerged as a promising tool for cardiac disease modeling and drug screening, allowing for better study of heart diseases (HDs). However, most current EHTs are composed of only a mixture of an extracellular matrix, heart muscle cells, called cardiomyocytes (CMs) and cardiac fibroblasts, without a vascular element. This prevents the study of the impacts of flow and the endothelium on cardiac function, despite their important role in both development and disease progression. Endothelial cell (EC) function is essential for maintaining cardiac homeostasis through protective signaling interactions between ECs and CMs. Disruption of endothelial function through vascular stressors such as hemodynamic changes and acute inflammation can trigger EC dysfunction, dysregulating cardioprotective signaling. It is important to incorporate the endothelial and perfusion components in EHT in vitro for better disease modeling and drug testing. The Zheng lab has developed a tube-like perfusable collagen-based EHT model, where CMs are embedded in the bulk collagen matrix, and the inner lumen of the tube can be endothelialized, serving as an effective, in vitro, model of cardiac vasculature. This project controls the size of the inner tube diameter of this model utilizing structural and contractile properties of muscle cells. Through the integration of these cells, we can maintain the inner diameter under a range of flow conditions, and subsequently use the model to identify healthy and unhealthy flow conditions within the EHTs. This project establishes a perfusable EHT model that allows us to examine EC function under several flow-related changes and, in the future, assess the effect of endothelial dysfunction on cardiac function.