Biology subjects

Choi, H.

Publications and source records attributed to Choi, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Mapping the Microstructure of Human Cerebral Cortex In Vivo with Diffusion MRI

Despite advances in diffusion MRI, which have led to remarkable progress in mapping white matter of the living human brain, the understanding of cerebral cortical microstructure in vivo and its relationship to macrostructure, myeloarchitecture, cytoarchitecture, chemoarchitecture, metabolism, and function lag far behind. We present neuromaps of 21 microstructural metrics derived from diffusion tensor, diffusion kurtosis, mean apparent propagator, and neurite orientation dispersion and density imaging of the young adult cerebral cortex. These 21 metrics are explained by four composite factors that correspond to diffusion kurtosis (intracellular volume fraction/neurite density), isotropic diffusion (free water fraction), heterogenous diffusion (extracellular volume fraction) and diffusion anisotropy (neurite orientation dispersion), respectively. We demonstrate how cortical microstructure follows cytoarchitectural and laminar differentiation, aligns with the macroscale sensory-fugal and sensorimotor-association axes, and contributes to functional brain networks, neural oscillatory dynamics, neurotransmitter receptor/transporter distributions, and cognition and behavior. We show that cortical dMRI metrics are heritable and can better predict participant age and cognition than can cortical thickness or myelination. We find cortical microstructural covariation across individuals to encode functional and structural connectivity as well as gene expression and neurotransmitter similarity. Finally, our exploratory analysis suggests cortical microstructure from diffusion MRI could prove useful in investigating a broad array of neuropsychiatric disorders.

neuroscience↗

bioRxiv2024

Single-nucleus and spatial transcriptomic analysis identified molecular features of neuronal heterogeneity and distinct glial responses in Parkinson's disease.

The heterogeneity of Parkinsons disease (PD) is increasingly recognized as an important aspect of understanding the disorder. Among the factors contributing to this heterogeneity, ethnic differences are primary sources, significantly influencing the likelihood of PD developing and its initial symptoms nature. While there have been numerous reports related to PD in East Asia, there has been a lack of contribution from single-cell (or nucleus) transcriptome studies, which have been making significant contributions to understanding PD. In this study, a total of 33,293 nuclei obtained from the substantia nigra (SN) of confirmed pathological PD and control patients in South Korea were profiled, revealing 8 different cell types through cluster analysis. Monocle-based pseudotime analysis identified two disease-associated trajectories for each astrocyte and microglia and identified genes that differentiate them. Interestingly, we uncovered the inflammatory intervention in the early PD-associated transition in microglia and identified the molecular features of this intermediate state of microglia. In addition, gene regulatory networks (GRNs) based on TENET analysis revealed the detrimental effect of an HSPA5-led module in microglia and MSRB3- and HDAC8- led modules specifying the two different astrocyte trajectories. In SN neurons, we observed population changes, a decrease in dopaminergic and glutamatergic neurons and a proportional increase in GABAergic neurons. By deconvolution in spatial transcriptome obtained the PD sample, we confirmed spatiotemporal heterogeneity of neuronal subpopulations and PD-associated progressive gliosis specific to dopaminergic nuclei, SN and ventral tegmental areas (VTAs). In conclusion, our approach has enabled us to identify the genetic and spatial characterization of neurons and to demonstrate different glial fates in PD. These findings advance our molecular understanding of cell type-specific changes in the progression of Korean PD, providing an important foundation for predicting and validating interventions or drug effects for future treatments.

neuroscience↗

bioRxiv2024

Diffusing protein binders to intrinsically disordered proteins

Proteins which bind intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) with high affinity and specificity could have considerable utility for therapeutic and diagnostic applications. However, a general methodology for targeting IDPs/IDRs has yet to be developed. Here, we show that starting only from the target sequence of the input, and freely sampling both target and binding protein conformation, RFdiffusion can generate binders to IDPs and IDRs in a wide range of conformations. We use this approach to generate binders to the IDPs Amylin, C-peptide and VP48 in a range of conformations with Kds in the 3 -100nM range. The Amylin binder inhibits amyloid fibril formation and dissociates existing fibers, and enables enrichment of amylin for mass spectrometry-based detection. For the IDRs G3bp1, common gamma chain (IL2RG) and prion, we diffused binders to beta strand conformations of the targets, obtaining 10 to 100 nM affinity. The IL2RG binder colocalizes with the receptor in cells, enabling new approaches to modulating IL2 signaling. Our approach should be widely useful for creating binders to flexible IDPs/IDRs spanning a wide range of intrinsic conformational preferences.

biochemistry↗

bioRxiv2024

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence

Convergent and divergent structures in the networks that make up biological brains are found across many species and brain regions at various spatial scales. Neurons in these networks fire action potentials, or "spikes", whose precise timing is becoming increasingly appreciated as large sources of information about both sensory input and motor output. While previous theories on coding in convergent and divergent networks have largely neglected the role of precise spike timing, our model and analyses place this aspect at the forefront. For a suite of stimuli with different timescales, we demonstrate that structural bottlenecks- small groups of neurons post-synaptic to network convergence - have a stronger preference for spike timing codes than expansion layers created by structural divergence. Additionally, we found that a simple network model based on convergence and divergence ratios of a hawkmoth (Manduca sexta) nervous system can reproduce the relative contribution of spike timing information in its motor output, providing testable predictions on optimal temporal resolutions of spike coding across the moth sensory-motor pathway at both the single-neuron and population levels. Our simulations and analyses suggest a relationship between the level of convergent/divergent structure present in a feedforward network and the loss of stimulus information encoded by its population spike trains as their temporal resolution decreases, which could be tested experimentally across diverse neural systems in future studies. We further show that this relationship can be generalized across different spike-generating models and measures of coding capacity, implying a potentially fundamental link between network structure and coding strategy using spikes. Author summaryWithin the complex anatomy of the brain, there are certain structures that appear more often than expected. One example of this is when large populations of neurons connect to much smaller populations, and vice versa. We refer to these structural patterns as network convergence and divergence; they are observed in systems like the cerebellum, insect olfactory networks, visuomotor pathways, and the early visual system of mammals. Despite the ubiquity of this connectivity pattern, we are only beginning to understand its functional implications from a computational point of view. Here, we construct and analyze mathematical models of spiking neural networks to understand how convergent and divergent structure shapes the way that information is represented in each part of the network, as a function of the temporal resolution of population spiking activity. We then developed a simple feedforward network model of the visuomotor pathway of a moth, with similar convergent/divergent network structure, and reproduce a similar proportion of spike timing to spike count information as observed experimentally. Our results form predictions about spike coding in populations previously unobserved in experiment.

neuroscience↗

bioRxiv2024

Spatial transcriptomics unveils landscape of resistance to concurrent chemo-radiotherapy in hypopharyngeal squamous cell carcinoma: the role of SPP1+ macrophages

Hypopharyngeal squamous cell carcinoma (SCC) is a highly aggressive cancer with a poor prognosis, particularly in advanced stages where concurrent chemoradiotherapy (CCRT) is used for treatment. However, resistance to CCRT poses a significant challenge, often leading to treatment failure and disease progression. This study explores the tumor microenvironment (TME) of hypopharyngeal SCC to understand the molecular mechanisms underlying CCRT resistance. Using spatial transcriptomics (ST), we analyzed tissue samples from patients with locally advanced hypopharyngeal SCC, distinguishing between those who were CCRT-resistant and those who were CCRT-naive. The analysis revealed six distinct cellular clusters within the TME, including a prominent epithelio-immune cellular area in CCRT-resistant tissues. SPP1 was identified as a key gene with significantly higher expression in CCRT-resistant samples, specifically within macrophages. Further investigation showed that SPP1+ macrophages interacted with malignant epithelial cells through SPP1-CD44 and SPP1-ITGB1 ligand-receptor pairs. These interactions were primarily localized in the peri-tumoral and intra-tumoral regions, highlighting their potential role in driving CCRT resistance. Our findings suggest that SPP1+ macrophages contribute to the resistant phenotype in hypopharyngeal SCC by modulating the TME and interacting with cancer cells. Understanding these interactions offers valuable insights into the mechanisms of CCRT resistance and may inform the development of targeted therapies to improve patient outcomes.

cancer biology↗

bioRxiv2024

Analysis of Unmapped RNA-seq Data from Cancer Spatial Transcriptome to Decipher Cancer Microbiome

Recent research increasingly emphasizes the importance of the microbiome in the development and progression of cancer. Thus, exploring the microbiome modulation in tumor microenvironment and understanding its composition and function are becoming important. The introduction of spatial transcriptomics has provided new insights into microbiome research, as it enables how microbiome affects tumor microenvironment. In this study, we analyzed the spatial distribution of microbial RNA observed through PathSeq and our extended method for unmapped RNA reads in oral squamous cell carcinoma, head and neck cancer, and colorectal cancer samples. Our novel method is designed to identify and classify microbial RNA, using a custom reference that includes species-specific microbial 16S rRNA sequences to enhance the accuracy of species-level microbiome analysis. The results of this study showed a potential for a deeper understanding of the microbial distribution and their functional roles within cancer tissues. These findings will reevaluate the role of the microbiome in cancer research, providing an insight for the development of microbiome-based therapies in the future.

bioinformatics↗

bioRxiv2024

Dual-mode action of scalable, high-quality engineered stem cell-derived SIRP alpha extracellular vesicles for treating acute liver failure

Acute liver failure (ALF) is a critical inflammatory condition characterized by rapid hepatocyte death, impaired liver regeneration due to the delayed removal of necroptotic cells, and high mortality rates. This study introduces a novel dual-mode action therapeutic approach using extracellular vesicles expressing Signal Regulatory Protein Alpha (SIRP-EVs) derived from genetically engineered mesenchymal stem cells (MSCs). These SIRP-EVs are designed to concurrently resolve necroptosis and promote liver regeneration. Our studies identified CD47 and SIRP as promising therapeutic targets for ALF. We developed a scalable 3D bioreactor-based process that produces high-purity SIRP-EVs, which preserve MSC properties and achieve significant production levels. SIRP-EVs target both macrophages and necroptotic hepatocytes in ALF models, enhancing macrophage phagocytic activity against necroptotic cells via CD47 blockade and promoting liver regeneration by reprogramming macrophages with MSC-derived cargo. Comprehensive in vitro and in vivo studies demonstrate that SIRP-EVs decrease CD47+ necroptotic cells and promote liver regeneration in ALF models, leading to reduced liver damage markers and enhanced survival rates. These findings highlight the potential of SIRP-EVs as a dual-mode action therapeutic for ALF, offering promising prospects for their application in other inflammatory diseases. Moreover, these results pave the way for advancing engineered EV-based therapies toward clinical implementation.

bioengineering↗

bioRxiv2024

PITPβ promotes COPI vesicle fission through lipid transfer and membrane contact formation

Intracellular transport among organellar compartments occurs in two general ways, by membrane-bound carriers or membrane contacts. Specific circumstances that involve the coordination of these two modes of transport remain to be defined. Studying Coat Protein I (COPI) transport, we find that phosphatidylcholine with short acyl chains (sPC) is delivered through membrane contact from the endoplasmic reticulum (ER) to sites of COPI vesicle formation at the Golgi to support the fission stage. Phosphatidylinositol transfer protein beta (PITP{beta}) plays a key role in this process, with the elucidation of this role advancing a new understanding of how PITP{beta} acts, providing a mechanistic understanding of a specific circumstance when vesicular transport requires membrane contact, and contributing to a basic understanding of how transport carriers in a model intracellular pathway are formed. SummarySpecific circumstances that membrane contact is needed for vesicular transport remain to be defined. We find that a critical lipid is delivered through membrane contact to support the fission stage of a model intracellular transport pathway.

cell biology↗

bioRxiv2024

Exploring the Architectural Biases of the Canonical Cortical Microcircuit

The cortex plays a crucial role in various perceptual and cognitive functions, driven by its basic unit, the canonical cortical microcircuit. Yet, we remain short of a framework that definitively explains the structure-function relationships of this fundamental neuroanatomical motif. To better understand how physical substrates of cortical circuitry facilitate their neuronal dynamics, we employ a computational approach using recurrent neural networks and representational analyses. We examine the differences manifested by the inclusion and exclusion of biologically-motivated inter-areal laminar connections on the computational roles of different neuronal populations in the microcircuit of two hierarchically-related areas, throughout learning. Our findings show that the presence of feedback connections correlates with the functional modularization of cortical populations in different layers, and provides the microcircuit with a natural inductive bias to differentiate expected and unexpected inputs at initialization. Furthermore, when testing the effects of training the microcircuit and its variants with a predictive-coding inspired strategy, we find that doing so helps better encode noisy stimuli in areas of the cortex that receive feedback, all of which combine to suggest evidence for a predictive-coding mechanism serving as an intrinsic operative logic in the cortex.

neuroscience↗

bioRxiv2024

Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression

While cancer-associated fibroblasts (CAFs) are crucial in influencing tumor growth and immune responses in lung cancer, we still lack a comprehensive understanding of their spatial organization associated with tumor progression and clinical outcomes. This gap highlights the need to elucidate how the intricate spatial arrangement of CAFs affects their interactions within the tumor microenvironment, ultimately shaping cancer progression and patient prognosis. Here, we unveil the spatial diversity of CAFs in lung squamous cell carcinoma (LUSC), a prevalent and aggressive lung cancer type, elucidating their impact on tumor progression and patient outcomes using spatial transcriptomics (ST). Image-based ST data from 33 LUSC patients demonstrated a significant association of spatial interactions of tumor epithelium and CAFs with tumor size and metabolic activity measured by [18F]fluorodeoxyglucose PET. Furthermore, the proximity of fibroblasts to tumor epithelial cells was linked to recurrence-free survival in LUSC patients. By characterizing CAFs based on their spatial relationship, we identified distinct molecular signatures related to spatially distinct fibroblast subpopulations. In addition, barcode-based ST data from 8 LUSC patients revealed spatially overlapping fibroblast regions characterized by upregulated glycolysis pathways. Our study underscores the importance of the complex spatial dynamics of the tumor microenvironment revealed by ST and its implications for patient outcomes in LUSC.

cancer biology↗

bioRxiv2024

CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities

Large-scale single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have transformed biomedical research into a data-driven field, enabling the creation of comprehensive data atlases. These methodologies facilitate detailed understanding of biology and pathophysiology, aiding in the discovery of new therapeutic targets. However, the complexity and sheer volume of data from these technologies present analytical challenges, particularly in robust cell typing, integration and understanding complex spatial relationships of cells. To address these challenges, we developed CELLama (Cell Embedding Leverage Language Model Abilities), a framework that leverage language model to transform cell data into sentences that encapsulate gene expressions and metadata, enabling universal cellular data embedding for various analysis. CELLama, serving as a foundation model, supports flexible applications ranging from cell typing to the analysis of spatial contexts, independently of manual reference data selection or intricate dataset-specific analytical workflows. Our results demonstrate that CELLama has significant potential to transform cellular analysis in various contexts, from determining cell types across multi-tissue atlases and their interactions to unraveling intricate tissue dynamics.

bioinformatics↗

bioRxiv2024

Context specific ubiquitin modification of ribosomes regulate translation under oxidative stress

Cellular exposure to stress is known to activate several translational control pathways through ribosome ubiquitination. However, how unique patterns of ribosome ubiquitination act at the site-specific level to drive distinct modes of translation regulation remains unclear. To further understand the complexity of these ubiquitin signals, we developed a new targeted proteomics approach to quantify site-specific ubiquitin modification across the ribosome. This method increased the sensitivity and throughput of current approaches and allowed us to systematically measure the ubiquitin status of 78 ribosome peptides and ubiquitin linkages in response to stress. Using this method, we were able to detect the ubiquitination of several ribosome sites even in steady-state conditions, and to show that their modification increases non-stoichiometrically in a dynamic range of >4 orders of magnitude in response to hydrogen peroxide. Besides demonstrating new patterns of global ribosome ubiquitination, our study also revealed an unexpected increase of ubiquitination of ribosomal protein uS10/Rps20 and uS3/Rps3 independent of the canonical E3 ubiquitin ligase Hel2. Furthermore, we show that unique and mixed patterns of ribosome ubiquitination occur in a stress specific manner, depending on the nature of stressor and the enzymes involved. Finally, we showed that while deletion of HEL2 further induces the integrated stress response in response to the nucleotide alkylating agent 4-NQO, deletion of the E2 conjugase RAD6 leads to sustained translation only in response to H2O2. Our findings contribute to deciphering the complexity of the stress response at the translational level, revealing the induction of dynamic and selective ubiquitin codes, which shed light on the integration of important quality control pathways during cellular response to stress.

molecular biology↗

bioRxiv2024

Generative Adversarial Implicit Successor Representation

We propose a novel method to implicitly encode Successor Representations (SRs) using a Generative Adversarial Network (GAN). SRs are a method to encode states of the environment in terms of their predictive relationships with other states, which can be used to predict long-term future rewards. In standard explicit methods, the value of SR is found from an explicit map between future states after an action or to find an approximate function. Instead, our method encodes SR implicitly using a GAN. The distribution of samples generated by the GAN system approximates the successor representation. We also suggest an action decision procedure for the implicit encoding of SR. The system makes the decision using an analysis-by-synthesis procedure that it attempts to synthesize a sample that can explain the action decision constraints of the current and target states. Our system is different from the classical SR in several points. It can sample actual samples reflecting SR distribution, which is not easy for explicit models. It can also get around the issue of explicitly representing probabilities or successor representation values and doing math over them. We tested our system in a toy environment, where the agent could learn the implicit successor representation successfully and use it for action decisions.

neuroscience↗

bioRxiv2024

A multi-looping chromatin signature predicts dysregulated gene expression in neurons with familial Alzheimer's disease mutations

Mammalian genomes fold into tens of thousands of long-range loops, but their functional role and physiologic relevance remain poorly understood. Here, using human post-mitotic neurons with rare familial Alzheimers disease (FAD) mutations, we identify hundreds of reproducibly dysregulated genes and thousands of miswired loops prior to amyloid accumulation and tau phosphorylation. Single loops do not predict expression changes; however, the severity and direction of change in mRNA levels and single-cell burst frequency strongly correlate with the number of FAD-gained or -lost promoter-enhancer loops. Classic architectural proteins CTCF and cohesin do not change occupancy in FAD-mutant neurons. Instead, we unexpectedly find TAATTA motifs amenable to binding by DLX homeodomain transcription factors and changing noncoding RNAPolII signal at FAD-dynamic promoter-enhancer loops. DLX1/5/6 mRNA levels are strongly upregulated in FAD-mutant neurons coincident with a shift in excitatory-to-inhibitory gene expression and miswiring of multi-loops connecting enhancers to neural subtype genes. DLX1 overexpression is sufficient for loop miswiring in wildtype neurons, including lost and gained loops at enhancers with tandem TAATTA arrays and singular TAATTA motifs, respectively. Our data uncover a genome structure-function relationship between multi-loop miswiring and dysregulated excitatory and inhibitory transcriptional programs during lineage commitment of human neurons homozygously-engineered with rare FAD mutations.

molecular biology↗

bioRxiv2023

Disruption of redox balance in glutaminolytic triple negative breast cancer by inhibition of glutamate export and glutaminase

In triple-negative breast cancer (TNBC) that relies on catabolism of amino acid glutamine, glutaminase (GLS) converts glutamine to glutamate, which facilitates glutathione synthesis by mediating the enrichment of intracellular cystine via xCT antiporter activity. To overcome chemo resistant TNBC, we have tested a strategy of disrupting cellular redox balance by inhibition of GLS and xCT by CB839 and Erastin, respectively. Key findings of our study include: 1. Dual metabolic inhibition (CB839+Erastin) led to significant increases of cellular superoxide level in both parent and chemo resistant TNBC cells, but superoxide level was distinctly lower in resistant cells. 2. Dual metabolic inhibition combined with doxorubicin or cisplatin induced significant apoptosis in TNBC cells and is associated with high degrees of GSH depletion. In vivo, dual metabolic inhibition plus cisplatin led to significant growth delay of chemo resistant human TNBC xenografts. 3. Ferroptosis is induced by doxorubicin (DOX) but not by cisplatin or paclitaxel. Addition of dual metabolic inhibition to DOX chemotherapy significantly enhanced ferroptotic cell death. 4. Significant changes in cellular metabolites concentration preceded transcriptome changes revealed by single cell RNA sequencing, underscoring the potential of capturing early changes in metabolites as pharmacodynamic markers of metabolic inhibitors. Here we demonstrated that 4-(3-[18F]fluoropropyl)-L-glutamic acid ([18F]FSPG) PET detected xCT blockade by Erastin or its analog in mice bearing human TNBC xenografts. In summary, our study provides compelling evidence for the therapeutic benefit and feasibility of non-invasive monitoring of dual metabolic blockade as a translational strategy to sensitize chemo resistant TNBC to cytotoxic chemotherapy.

cancer biology↗

bioRxiv2023

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with anatomy and direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

neuroscience↗

bioRxiv2023

Lysosomal release of amino acids at ER three-way junctions regulates transmembrane and secretory protein mRNA translation

One-third of the mammalian proteome is comprised of transmembrane and secretory proteins that are synthesized on endoplasmic reticulum (ER). Here, we investigate the spatial distribution and regulation of mRNAs encoding these membrane and secretory proteins (termed "secretome" mRNAs) through live cell, single molecule tracking to directly monitor the position and translation states of secretome mRNAs on ER and their relationship to other organelles. Notably, translation of secretome mRNAs occurred preferentially near lysosomes on ER marked by the ER junction-associated protein, Lunapark. Knockdown of Lunapark reduced the extent of secretome mRNA translation without affecting translation of other mRNAs. Less secretome mRNA translation also occurred when lysosome function was perturbed by raising lysosomal pH or inhibiting lysosomal proteases. Secretome mRNA translation near lysosomes was enhanced during amino acid deprivation. Addition of the integrated stress response inhibitor, ISRIB, reversed the translation inhibition seen in Lunapark knockdown cells, implying an eIF2 dependency. Altogether, these findings uncover a novel coordination between ER and lysosomes, in which local release of amino acids and other factors from ER-associated lysosomes patterns and regulates translation of mRNAs encoding secretory and membrane proteins.

cell biology↗

bioRxiv2023

Reproducing Left Ventricular Twist by Mimicking Myocardial Fiber Orientation Using 3D Bioprinting-assisted Tissue Assembly

BackgroundLeft ventricular twist, an opposite rotation of the apex and base, is caused by myocardial fiber orientation, a unique structural feature of the myocardium, and contributes to the effective ejection fraction of the native heart. Reproducing this structural-functional relationship in an in vitro heart model remains challenging due to the lack of synchrony between layers when mimicking the fiber orientations of each layer. MethodsWe employed a hierarchical approach for creating multilayered and multiaxial fibers in a chamber-like structure, as follows: 3D bioprinting-assisted tissue assembly, fabrication of uniaxially aligned engineered heart tissue as a building block, and assembly of them to create a myocardial fiber orientation in a chamber-like structure. ResultThe EHT module confirmed uniaxial alignment and cardiac functions such as contractility and electrophysiological properties. By fabricating the assembly platform by 3D bioprinting, it is possible to guide building blocks in various directions as intended, confirming the versatility of this method. The assembly platform allows structural and functional synchrony of assembled tissues while controlling and maintaining predefined cellular alignment. Furthermore, various shapes and sizes of EHT modules and assembly platform were fabricated for mimicking myocardial fiber orientation in a chamber-like structure. The resulting structure exhibited three layers and three orientations representing myocardial fiber orientation. Moreover, the left ventricular twist was confirmed by measuring basal and apical rotations. ConclusionsRecapitulation of the microscale structure of the left ventricle enabled the identification of information not discernible from the existing macroscale structure. This understanding of the structure-function relationship of the heart can provide insights into the mechanisms underlying cardiac structure, function, and related diseases. Furthermore, the versatility of the 3D bioprinting-assisted tissue assembly allows for the creation of organs and tissue collections with complex structural and functional features by fabricating and assembling modules that meet the specific requirements of target tissues and organs.

bioengineering↗