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Human pluripotent stem cells (hPSCs) offer an unprecedented opportunity to model diverse cell types and tissues. To enable systematic exploration of the programming landscape mediated by transcription factors (TFs), we present the Human TFome, a comprehensive library containing 1,564 TF genes and 1,732 TF splice isoforms. By screening the library in three hPSC lines, we discovered 290 TFs, including 241 that were previously unreported, that induce differentiation in 4 days without alteration of external soluble or biomechanical cues. We used four of the hits to program hPSCs into neurons, fibroblasts, oligodendrocytes and vascular endothelial-like cells that have molecular and functional similarity to primary cells. Our cell-autonomous approach enabled parallel programming of hPSCs into multiple cell types simultaneously. We also demonstrated orthogonal programming by including oligodendrocyte-inducible hPSCs with unmodified hPSCs to generate cerebral organoids, which expedited in situ myelination. Large-scale combinatorial screening of the Human TFome will complement other strategies for cell engineering based on developmental biology and computational systems biology. A library of human transcription factor genes is screened for differentiation of human pluripotent stem cells.

Advances in biomanufacturing techniques have opened the doors to recapitulate human sensory organs such as the nose and ear in vitro with adequate levels of functionality. Such advancements have enabled simultaneous targeting of two challenges in engineered sensory organs, especially the nose: i) mechanically robust reconstruction of the nasal cartilage with high precision and ii) replication of the nose functionality: odor perception. Hybrid nasal organs can be equipped with remarkable capabilities such as augmented olfactory perception. Herein, a proof‐of‐concept for an odor‐perceptive nose‐like hybrid, which is composed of a mechanically robust cartilage‐like construct and a biocompatible biosensing platform, is proposed. Specifically, 3D cartilage‐like tissue constructs are created by multi‐material 3D bioprinting using mechanically tunable chondrocyte‐laden bioinks. In addition, by optimizing the composition of stiff and soft bioinks in macro‐scale printed constructs, the competence of this system in providing improved viability and recapitulation of chondrocyte cell behavior in mechanically robust 3D constructs is demonstrated. Furthermore, the engineered cartilage‐like tissue construct is integrated with an electrochemical biosensing system to bring functional olfactory sensations toward multiple specific airway disease biomarkers, explosives, and toxins under biocompatible conditions. Proposed hybrid constructs can lay the groundwork for functional bionic interfaces and humanoid cyborgs. An odor‐perceptive nose‐like hybrid is developed using multi‐material 3D bioprinting. The mechanically robust cartilage‐mimetic tissue is integrated with a biosensing platform tunable to “sniff out” a wide range of chemical structures, such as explosives. This integrative approach lays the groundwork for functional bionic interfaces and humanoid cyborgs.

Experimental models of the central nervous system (CNS) are imperative for developmental and pathophysiological studies of neurological diseases. Among these models, three-dimensional (3D) induced pluripotent stem cell (iPSC)-derived brain organoid models have been successful in mitigating some of the drawbacks of 2D models; however, they are plagued by high organoid-to-organoid variability, making it difficult to compare specific gene regulatory pathways across 3D organoids with those of the native brain. Single-cell RNA sequencing (scRNA-seq) transcriptome datasets have recently emerged as powerful tools to perform integrative analyses and compare variability across organoids. However, transcriptome studies focusing on late-stage neural functionality development have been underexplored. Here, we combine and analyze 8 brain organoid transcriptome databases to study the correlation between differentiation protocols and their resulting cellular functionality across various 3D organoid and exogenous brain models. We utilize dimensionality reduction methods including principal component analysis (PCA) and uniform manifold approximation projection (UMAP) to identify and visualize cellular diversity among 3D models and subsequently use gene set enrichment analysis (GSEA) and developmental trajectory inference to quantify neuronal behaviors such as axon guidance, synapse transmission and action potential. We showed high similarity in cellular composition, cellular differentiation pathways and expression of functional genes in human brain organoids during induction and differentiation phases, i.e., up to 3 months in culture. However, during the maturation phase, i.e., 6-month timepoint, we observed significant developmental deficits and depletion of neuronal and astrocytes functional genes as indicated by our GSEA results. Our results caution against use of organoids to model pathophysiology and drug response at this advanced time point and provide insights to tune in vitro iPSC differentiation protocols to achieve desired neuronal functionality and improve current protocols.

Multifactorial complex diseases such as Alzheimer’s have combinatory root causes that are difficult to sufficiently model by traditional two-dimensional (2D) cultures. Specifically, cell-cell interactions as well as organ-organ communications in traditional 2D mono-culture systems are limited, causing significant divergence from in vivo models and in human testing results. Therefore, there is currently a need for a multi-faceted system with multicellular architecture that can also replicate these diseases at the organ level. Advances in biomanufacturing techniques, specifically organ-on-a-chip (OOC) technologies, provide opportunities to recapitulate human tissues in vitro with adequate levels of functionality. These engineering tools can be combined with the human-induced pluripotent stem cell (hiPSC) technology to provide unbounded resources for complex disease modeling and the development of personalized engineered tissue or organ models. In this dissertation, we target multifactorial disease modeling at three levels by proposing a multipurpose platform consisting of biomolecule biosensing, targeted stem cell differentiation and ubiquitous external disease biomarker detection. These modules and functionalities can be combined in various formats to replicate external and intercellular factors causing a multifactorial disease.

Large-scale vessel-integrated muscle-like lattices (VMLs) containing dense and aligned human induced pluripotent stem cell (hiPSC)-derived myofibers alongside vessel-like microchannels were fabricated using an advanced bioprinting technology and stem cell-laden extracellular matrix-based bioinks.Incorporating vessel-like lattice was of vital importance for enhancing myofiber maturation in vitro and host vessel invasion in vivo, improving implant integration.Successful de novo muscle formation and muscle function restoration was achieved through a combinatorial effect between improved hiPSC-derived VML graft–host integration and increased release of paracrine factors at volumetric muscle loss injury.Observing the human markers in the implantation area confirmed that the hiPSC-muscle precursor cells (MPCs) at the transplantation site play a significant role for improving regenerative capacity of volumetric muscle loss. Engineering biomimetic tissue implants with human induced pluripotent stem cells (hiPSCs) holds promise for repairing volumetric tissue loss. However, these implants face challenges in regenerative capability, survival, and geometric scalability at large-scale injury sites. Here, we present scalable vessel-integrated muscle-like lattices (VMLs), containing dense and aligned hiPSC-derived myofibers alongside passively perfusable vessel-like microchannels inside an endomysium-like supporting matrix using an embedded multimaterial bioprinting technology. The contractile and millimeter-long myofibers are created in mechanically tailored and nanofibrous extracellular matrix-based hydrogels. Incorporating vessel-like lattice enhances myofiber maturation in vitro and guides host vessel invasion in vivo, improving implant integration. Consequently, we demonstrate successful de novo muscle formation and muscle function restoration through a combinatorial effect between improved graft–host integration and its increased release of paracrine factors within volumetric muscle loss injury models. The proposed modular bioprinting technology enables scaling up to centimeter-sized prevascularized hiPSC-derived muscle tissues with custom geometries for next-generation muscle regenerative therapies. [Display omitted] We developed scalable vessel-integrated muscle-like lattices (VMLs) with dense, aligned human induced pluripotent stem cell (hiPSC)-derived myofibers and vessel-like structures using a novel bioprinting technology. These VMLs significantly improved muscle tissue regeneration and function in mice post-volumetric muscle loss. These modular lattices can be adapted to large-scale muscle defects where native regeneration is impaired. To treat volumetric muscle loss in practice, implants should contain enough cell density to compensate for cell death during the implantation procedure and in the early hours of host integration. To this end, we have optimized construct design to achieve highly dense muscle-laden channels with millimeter-long and densely aligned human induced pluripotent stem cell (hiPSC)-derived myofibers. This cell density has proven effective in achieving functional regeneration in the mice tested. However, more studies are needed in larger animals to quantify the number of cells needed for large defects and this study may result in construct pattern redesign. The hiPSC-derived vessel-integrated muscle-like lattices (VMLs) demonstrate successful de novo muscle formation and muscle function restoration through a combinatorial effect between improved graft–host integration and increased release of paracrine factors. As such, we believe that we have achieved a technology readiness level (TRL) 3 in proving that the concept works in vitro and in a relevant environment (e.g., in vivo). Next, the modular building blocks should be assembled and tested in larger defects to validate continuous elastic behavior, large-scale muscle regeneration capacity of the construct, and implant-wide cellular viability. Moreover, the assembly should be implanted in larger animals, for longer durations of culture, to validate long-term muscle functionality to achieve TRL 4. Ultimately, upon successful completion of the mentioned tests, the constructs should be implanted in human defects during clinical trials to inform regeneration efficiency and muscle function restoration.

Background The link between obesity and metabolic dysfunction is well‐established. However, the choice of an anthropometric index best reflective of risk remains debatable. This study aimed to evaluate the predictive performance of several indices for diabetes and hypertension in a population at risk for cardiovascular disease. Materials and methods Data from 1,537 participants was analyzed. The predictive value of 19 indices for diabetes and hypertension was evaluated via area under the receiver operating characteristic curve (AUC) analysis. Analyses were adjusted for major risk factors to evaluate the independent utility of each index. Modified versions of the American Diabetes Association (ADA) diabetes risk assessment tool were examined, where body mass index (BMI) was substituted for indices demonstrating strong or independent predictive values. Results The Deurenberg formula was the best predictor of diabetes in both male (AUC = 0.67; 95% CI 0.62–0.73) and female (AUC = 0.77; 95% CI 0.73–0.82) participants, and significantly better than BMI. Body roundness index (BRI; aAUC = 0.63; 95% CI 0.56–0.70), waist‐to‐height ratio (WHtR; aAUC = 0.63; 95% CI 0.57–0.70), and waist‐to‐height1/2 ratio (WHT.5R; aAUC = 0.63; 95% CI 0.57–0.70) showed independent predictive values for diabetes in female participants. The risk assessment tool's performance was improved when BMI was substituted for these indices. BMI (aAUC = 0.66; 95% CI 0.61–0.70), Deurenberg (aAUC = 0.66; 95% CI 0.61–0.70), and Gallagher (aAUC = 0.66; 95% CI 0.62–0.70) formulas were independent predictors of hypertension in male participants. Conclusions Several indices showed promising performances for use in diabetes screening. Future research should focus on incorporating these indices in screening tools. The current study evaluated the predictive performance of 19 readily calculable anthropometric indices to be used in quick risk assessment tools for diabetes in time and resource‐constrained settings. No singular index was found to be a per se predictor of metabolic disorder. Estimations of body fat percentage obtained using the Deurenberg formula (male: AUC = 0.67; 95% CI 0.62–0.73 and female: AUC = 0.77; 95% CI 0.73–0.82) were the best predictor for diabetes and significantly outperformed BMI. Body roundness index (BRI), waist‐to‐height ratio (WHtR), and waist‐to‐height1/2 (WHT.5R) predicted diabetes in a manner independent from commonly considered risk factors. Substitution of BMI for these indices improved a multifactorial diabetes risk assessment tool's performance.