The cutting-edge progress in bioprinting for biomedicine: principles, applications, and future perspectives.

Bioprinting is a highly promising application area of additive manufacturing technology that has been widely used in various fields, including tissue engineering, drug screening, organ regeneration, and biosensing. Its primary goal is to produce biomedical products such as artificial implant scaffolds, tissues and organs, and medical assistive devices through software-layered discrete and numerical control molding. Despite its immense potential, bioprinting technology still faces several challenges. It requires concerted efforts from researchers, engineers, regulatory bodies, and industry stakeholders are principal to overcome these challenges and unlock the full potential of bioprinting. This review systematically discusses bioprinting principles, applications, and future perspectives while also providing a topical overview of research progress in bioprinting over the past two decades. The most recent advancements in bioprinting are comprehensively reviewed here. First, printing techniques and methods are summarized along with advancements related to bioinks and supporting structures. Second, interesting and representative cases regarding the applications of bioprinting in tissue engineering, drug screening, organ regeneration, and biosensing are introduced in detail. Finally, the remaining challenges and suggestions for future directions of bioprinting technology are proposed and discussed. Bioprinting is one of the most promising application areas of additive manufacturing technology that has been widely used in various fields. It aims to produce biomedical products such as artificial implant scaffolds, tissues and organs, and medical assistive devices. This review systematically discusses bioprinting principles, applications, and future perspectives, which provides a topical description of the research progress of bioprinting.

LMNA-Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-Derived iPSC Differentiation Support Cell Type and Lineage-Specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency.

LMNA-related dilated cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C (LMNA) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. The molecular mechanisms of the disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA-related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA-mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (four from Patients and eight from Controls) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for cardiac progenitors to cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Data integration and comparative analyses of Patient and Control cells found cell type and lineage-specific differentially expressed genes (DEGs) with enrichment, supporting pathway dysregulation. Top DEGs and enriched pathways included 10 ZNF genes and RNA polymerase II transcription in pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CMs; LMNA and epigenetic regulation, as well as DDIT4 and mTORC1 signaling in EPDCs. Top DEGs also included XIST and other X-linked genes, six imprinted genes (SNRPN, PWAR6, NDN, PEG10, MEG3, MEG8), and enriched gene sets related to metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs, as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.

Cell and gene therapy for amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disorder with rapidly progressive skeletal muscle weakness, which can also cause a variable cognitive deficit. Genetic causes are only identified in approximately 10% of all cases, with complex genotype-phenotype associations, making it challenging to identify treatment targets. What further hampers therapeutic development is a broad heterogeneity in mechanisms, possible targets, and disturbances across various cell types, aside from the cortical and spinal motor neurons that lie at the heart of the pathology of ALS. Over the last decade, significant progress in biotechnologic techniques, cell and ribonucleic acid (RNA) engineering, animal models, and patient-specific human stem cell and organoid models have accelerated both mechanistic and therapeutic discoveries. The growing number of clinical trials mirrors this. This chapter reviews the current state of human preclinical models supporting trial strategies as well as recent clinical cell and gene therapy approaches.

Assessment and Evaluation of Contemporary Approaches for Astrocyte Differentiation from hiPSCs: A Modeling Paradigm for Alzheimer's Disease.

BACKGROUND: Astrocytes have recently gained attention as key players in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease. Numerous differentiation protocols have been developed to study human astrocytes in vitro. However, the properties of the resulting glia are inconsistent, making it difficult to select an appropriate method for a given research question. Therefore, we compared three approaches for the generation of iPSC-derived astrocytes. We performed a detailed analysis using a widely used long serum-free (LSFP) and short serum-free (SSFP) protocol, as well as a TUSP protocol using serum for a limited time of differentiation. RESULTS: We used RNA sequencing and immunochemistry to characterize the cultures. Astrocytes generated by the LSFP and SSFP methods differed significantly in their characteristics from those generated by the TUSP method using serum. The TUSP astrocytes had a less neuronal pattern, showed a higher degree of extracellular matrix formation, and were more mature. The short-term presence of FBS in the medium facilitated the induction of astroglia characteristics but did not result in reactive astrocytes. Data from cell-type deconvolution analysis applied to bulk transcriptomes from the cultures assessed their similarity to primary and fetal human astrocytes. CONCLUSIONS: Overall, our analyses highlight the need to consider the advantages and disadvantages of a given differentiation protocol for solving specific research tasks or drug discovery studies with iPSC-derived astrocytes.

Innovative 3D bioprinting approaches for advancing brain science and medicine: a literature review.

The rapid advancements in 3D printing technology have revolutionized the field of tissue engineering, particularly in the development of neural tissues for the treatment of nervous system diseases. Brain neural tissue, composed of neurons and glial cells, plays a crucial role in the functioning of the brain, spinal cord, and peripheral nervous system by transmitting nerve impulses and processing information. By leveraging 3D bioprinting and bioinks, researchers can create intricate neural scaffolds that facilitate the proliferation and differentiation of nerve cells, thereby promoting the repair and regeneration of damaged neural tissues. This technology allows for the precise spatial arrangement of various cell types and scaffold materials, enabling the construction of complex neural tissue models that closely mimic the natural architecture of the brain. Human-induced pluripotent stem cells (hiPSCs) have emerged as a groundbreaking tool in neuroscience research and the potential treatment of neurological diseases. These cells can differentiate into diverse cell types within the nervous system, including neurons, astrocytes, microglia, oligodendrocytes, and Schwann cells, providing a versatile platform for studying neural networks, neurodevelopment, and neurodegenerative disorders. The use of hiPSCs also opens new avenues for personalized medicine, allowing researchers to model diseases and develop targeted therapies based on individual patient profiles. Despite the promise of direct hiPSC injections for therapeutic purposes, challenges such as poor localization and limited integration have led to the exploration of biomaterial scaffolds as supportive platforms for cell delivery and tissue regeneration. This paper reviews the integration of 3D bioprinting technologies and bioink materials in neuroscience applications, offering a unique platform to create complex brain and tissue architectures that mimic the mechanical, architectural, and biochemical properties of native tissues. These advancements provide robust tools for modelling, repair, and drug screening applications. The review highlights current research, identifies research gaps, and offers recommendations for future studies on 3D bioprinting in neuroscience. The investigation demonstrates the significant potential of 3D bioprinting to fabricate brain-like tissue constructs, which holds great promise for regenerative medicine and drug testing models. This approach offers new avenues for studying brain diseases and potential treatments.

Modeling Cystic Fibrosis Chronic Infection Using Engineered Mucus-like Hydrogels.

The airway mucus of patients with cystic fibrosis has altered properties, which create a microenvironment primed for chronic infections that are difficult to treat. These complex polymicrobial airway infections and corresponding mammalian-microbe interactions are challenging to model in vitro. Here, we report the development of mucus-like hydrogels with varied compositions and viscoelastic properties reflecting differences between healthy and cystic fibrosis airway mucus. Models of cystic fibrosis and healthy airway microenvironments were created by combining the hydrogels with relevant pathogens, human bronchial epithelial cells, and an antibiotic. Notably, pathogen antibiotic resistance was not solely dependent on the altered properties of the mucus-like hydrogels but was also influenced by culture conditions including microbe species, monomicrobial or polymicrobial culture, and the presence of epithelial cells. Additionally, the cystic fibrosis airway model showed the ability to mimic features characteristic of chronic cystic fibrosis airway infections including sustained polymicrobial growth and increased antibiotic tolerance.

Prediction of measles cases in US counties: A machine learning approach.

BACKGROUND: Although measles was declared eliminated from the United States in 2000, the frequency of measles outbreaks has increased in recent years. The ability to predict the locations of future cases could aid efforts to prevent and contain measles in the United States. METHODS: We estimated county-level measles risk using a machine learning model with 17 predictor variables, which was trained on 2014 and 2018 United States county-level measles case data and tested on data from 2019. We compared the predicted and actual locations of 2019 measles cases. RESULTS: The model accurately predicted 95 % (specificity) of United States counties without measles cases and 72 % (sensitivity) of the United States counties that experienced ≥1 measles case in 2019, accounting for 94 % of all measles cases in 2019. Among the top 30 counties with the highest risk scores, the model accurately predicted 22 (73 %) counties with a measles case in 2019, corresponding to 72 % of all measles cases. CONCLUSIONS: This machine learning model accurately predicted a majority of the United States counties at high risk for measles and could be used as a framework by state and national health agencies in their measles prevention and containment efforts.

A comprehensive review of electrophysiological techniques in amyotrophic lateral sclerosis research.

Amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, is characterized by progressive motor neuron degeneration, leading to widespread weakness and respiratory failure. While a variety of mechanisms have been proposed as causes of this disease, a full understanding remains elusive. Electrophysiological alterations, including increased motor axon excitability, likely play an important role in disease progression. There remains a critical need for non-animal disease models that can integrate electrophysiological tools to better understand underlying mechanisms, track disease progression, and evaluate potential therapeutic interventions. This review explores the integration of electrophysiological technologies with ALS disease models. It covers cellular and clinical electrophysiological tools and their applications in ALS research. Additionally, we examine conventional animal models and highlight advancements in humanized models and 3D organoid technologies. By bridging the gap between these models, we aim to enhance our understanding of ALS pathogenesis and facilitate the development of new therapeutic strategies.

Gastrointestinal tract organoids as novel tools in drug discovery.

Organoids, characterized by their high physiological attributes, effectively preserve the genetic characteristics, physiological structure, and function of the simulated organs. Since the inception of small intestine organoids, other organoids for organs including the liver, lungs, stomach, and pancreas have subsequently been developed. However, a comprehensive summary and discussion of research findings on gastrointestinal tract (GIT) organoids as disease models and drug screening platforms is currently lacking. Herein, in this review, we address diseases related to GIT organoid simulation and highlight the notable advancements that have been made in drug screening and pharmacokinetics, as well as in disease research and treatment using GIT organoids. Organoids of GIT diseases, including inflammatory bowel disease, irritable bowel syndrome, necrotizing enterocolitis, and Helicobacter pylori infection, have been successfully constructed. These models have facilitated the study of the mechanisms and effects of various drugs, such as metformin, Schisandrin C, and prednisolone, in these diseases. Furthermore, GIT organoids have been used to investigate viruses that elicit GIT reactions, including Norovirus, SARS-CoV-2, and rotavirus. Previous studies by using GIT organoids have shown that dasabuvir, gemcitabine, and imatinib possess the capability to inhibit viral replication. Notably, GIT organoids can mimic GIT responses to therapeutic drugs at the onset of disease. The GIT toxicities of compounds like gefitinib, doxorubicin, and sunset yellow have also been evaluated. Additionally, these organoids are instrumental for the study of immune regulation, post-radiation intestinal epithelial repair, treatment for cystic fibrosis and diabetes, the development of novel drug delivery systems, and research into the GIT microbiome. The recent use of conditioned media as a culture method for replacing recombinant hepatocyte growth factor has significantly reduced the cost associated with human GIT organoid culture. This advancement paves the way for large-scale culture and compound screening of GIT organoids. Despite the ongoing challenges in GIT organoid development (e.g., their inability to exist in pairs, limited cell types, and singular drug exposure mode), these organoids hold considerable potential for drug screening. The use of GIT organoids in this context holds great promises to enhance the precision of medical treatments for patients living with GIT diseases.

In silico and in vitro models reveal the molecular mechanisms of hypocontractility caused by TPM1 M8R.

Dilated cardiomyopathy (DCM) is an inherited disorder often leading to severe heart failure. Linkage studies in affected families have revealed hundreds of different mutations that can cause DCM, with most occurring in genes associated with the cardiac sarcomere. We have developed an investigational pipeline for discovering mechanistic genotype-phenotype relationships in DCM and here apply it to the DCM-linked tropomyosin mutation TPM1 M8R. Atomistic simulations predict that M8R increases flexibility of the tropomyosin chain and enhances affinity for the blocked or inactive state of tropomyosin on actin. Applying these molecular effects to a Markov model of the cardiac thin filament reproduced the shifts in Ca2+sensitivity, maximum force, and a qualitative drop in cooperativity that were observed in an in vitro system containing TPM1 M8R. The model was then used to simulate the impact of M8R expression on twitch contractions of intact cardiac muscle, predicting that M8R would reduce peak force and duration of contraction in a dose-dependent manner. To evaluate this prediction, TPM1 M8R was expressed via adenovirus in human engineered heart tissues and isometric twitch force was observed. The mutant tissues manifested depressed contractility and twitch duration that agreed in detail with model predictions. Additional exploratory simulations suggest that M8R-mediated alterations in tropomyosin-actin interactions contribute more potently than tropomyosin chain stiffness to cardiac twitch dysfunction, and presumably to the ultimate manifestation of DCM. This study is an example of the growing potential for successful in silico prediction of mutation pathogenicity for inherited cardiac muscle disorders.

Immune response caused by M1 macrophages elicits atrial fibrillation-like phenotypes in coculture model with isogenic hiPSC-derived cardiomyocytes.

BACKGROUND: Atrial fibrillation has an estimated prevalence of 1.5-2%, making it the most common cardiac arrhythmia. The processes that cause and sustain the disease are still not completely understood. An association between atrial fibrillation and systemic, as well as local, inflammatory processes has been reported. However, the exact mechanisms underlying this association have not been established. While it is understood that inflammatory macrophages can influence cardiac electrophysiology, a direct, causative relationship to atrial fibrillation has not been described. This study investigated the pro-arrhythmic effects of activated M1 macrophages on human induced pluripotent stem cell (hiPSC)-derived atrial cardiomyocytes, to propose a mechanistic link between inflammation and atrial fibrillation. METHODS: Two hiPSC lines from healthy individuals were differentiated to atrial cardiomyocytes and M1 macrophages and integrated in an isogenic, pacing-free, atrial fibrillation-like coculture model. Electrophysiology characteristics of cocultures were analysed for beat rate irregularity, electrogram amplitude and conduction velocity using multi electrode arrays. Cocultures were additionally treated using glucocorticoids to suppress M1 inflammation. Bulk RNA sequencing was performed on coculture-isolated atrial cardiomyocytes and compared to meta-analyses of atrial fibrillation patient transcriptomes. RESULTS: Multi electrode array recordings revealed M1 to cause irregular beating and reduced electrogram amplitude. Conduction analysis further showed significantly lowered conduction homogeneity in M1 cocultures. Transcriptome sequencing revealed reduced expression of key cardiac genes such as SCN5A, KCNA5, ATP1A1, and GJA5 in the atrial cardiomyocytes. Meta-analysis of atrial fibrillation patient transcriptomes showed high correlation to the in vitro model. Treatment of the coculture with glucocorticoids showed reversal of phenotypes, including reduced beat irregularity, improved conduction, and reversed RNA expression profiles. CONCLUSIONS: This study establishes a causal relationship between M1 activation and the development of subsequent atrial arrhythmia, documented as irregularity in spontaneous electrical activation in atrial cardiomyocytes cocultured with activated macrophages. Further, beat rate irregularity could be alleviated using glucocorticoids. Overall, these results point at macrophage-mediated inflammation as a potential AF induction mechanism and offer new targets for therapeutic development. The findings strongly support the relevance of the proposed hiPSC-derived coculture model and present it as a first of its kind disease model.

The effects of simultaneous respiratory infections on the nasal shedding of Mycoplasmopsis bovirhinis in dairy calves.

Although there are several studies that described the possible participation of Mycoplasmopsis bovirhinis (formerly, Mycoplasma bovirhinis) in respiratory disease in calves worldwide, none of these evaluated the effects of concomitant infections on the shedding of this organism. Accordingly, this study evaluated the effects of simultaneous respiratory infections in dairy calves on the nasal shedding of M. bovirhinis. A statistical two-step model, using univariable and multivariable with logistic regression was developed to investigate and predict the possible effects of simultaneous infections by Histophilus somni, Mannheimia haemolytica, Pasteurella multocida, bovine coronavirus (BCoV), and ovine gammaherpesvirus 2 (OvGHV2) in dairy calves on the nasal shedding of M. bovirhinis. The multivariable analysis demonstrated that dairy calves infected with OvGHV2 have 2.59 times likelihood of nasal shedding of M. bovirhinis relative to calves not infected by OvGHV2, while the odds of nasal shedding of M. bovirhinis was 3.46 times higher in dairy calves infected by M. haemolytica. In contrast, simultaneous respiratory infections in dairy calves by H. somni, P. multocida, and BCoV had no direct effect on the nasal shedding of M. bovirhinis. Consequently, infections by OvGHV2 and M. haemolytica may be possible risk factors for the nasal shedding of M. bovirhinis in dairy calves. These results demonstrated the importance of disease modeling in veterinary medicine to predict and understand the complex outcomes of associations in animals concomitantly infected by several disease pathogens.

Fully defined NGN2 neuron protocol reveals diverse signatures of neuronal maturation.

NGN2-driven induced pluripotent stem cell (iPSC)-to-neuron conversion is a popular method for human neurological disease modeling. In this study, we present a standardized approach for generating neurons utilizing clonal, targeted-engineered iPSC lines with defined reagents. We demonstrate consistent production of excitatory neurons at scale and long-term maintenance for at least 150 days. Temporal omics, electrophysiological, and morphological profiling indicate continued maturation to postnatal-like neurons. Quantitative characterizations through transcriptomic, imaging, and functional assays reveal coordinated actions of multiple pathways that drive neuronal maturation. We also show the expression of disease-related genes in these neurons to demonstrate the relevance of our protocol for modeling neurological disorders. Finally, we demonstrate efficient generation of NGN2-integrated iPSC lines. These workflows, profiling data, and functional characterizations enable the development of reproducible human in vitro models of neurological disorders.

History of the development of isolated heart perfusion experimental model and its pioneering role in understanding heart physiology.

The isolated heart perfusion model, a fundamental tool in cardiovascular research, has evolved significantly since its inception in the late 19th century. This review traces the development of the isolated heart model, from its early adaptations by pioneers such as Langendorff and Starling to modern advancements by researchers like Morgan and Neely. We discuss the various applications of the model in pharmacological testing, disease modeling, and educational settings, emphasizing its crucial role in understanding cardiac function and disease mechanisms. Recent technological enhancements, including high-resolution imaging, integration with bioengineering, and advanced genomic and proteomic analyses, have significantly broadened the capabilities of these models. Looking forward, we explore potential future developments such as the integration of precision medicine, stem cell research, and artificial intelligence, which promise to revolutionize the use of isolated heart perfusion models. This review highlights the model's crucial role in bridging experimental research and clinical applications.

Patient-derived bladder cancer organoids show stable transcript expression along cultivation.

INTRODUCTION: Bladder cancer (BC) is a prevalent malignancy with high recurrence rates. Patient-derived bladder cancer organoids (BCO) pose as a promising approach in both, disease modeling and individualized treatment screening. The aim of this study was to investigate the transcriptomic plasticity in BCOs as a function of cultivation times to define ideal time periods for the applications envisioned. METHODS: Tumor samples of three patients with pathologically confirmed non-muscle invasive and muscle-invasive bladder cancer were included in this study and expanded as BCOs. RNA expression was investigated at different time periods of cells in culture using differential gene expression for overall transcript expression and quantitative real-time PCR (qRT-PCR) for pathological relevant markers. RESULTS: Differential gene expression of the BCO lines was investigated across passages 1-4, in passages 5-9 and above 9, respectively. Analysis of the entire transcriptome of the respective BCO lines revealed consistent profiles without significant alterations throughout the cultivation and expansion procedure. Notably, key transcripts like TP53, PIK3CA, BRCA1, among others, exhibited stable expression levels in the quantitative RNA analysis during the cultivation period. CONCLUSION: The robust transcriptome during BCO cultivation advocates for the use of earlier passages of BCOs in personalized medicine providing a time-efficient drug screening option to accelerate the counseling of patients' treatment options. Higher passages of BCOs still hold the potential in topics demanding for expanded cell masses such as medical device development and others.

Modeling riboflavin transporter deficiency type 2: from iPSC-derived motoneurons to iPSC-derived astrocytes.

Introduction: Riboflavin transporter deficiency type 2 (RTD2) is a rare neurodegenerative autosomal recessive disease caused by mutations in the SLC52A2 gene encoding the riboflavin transporters, RFVT2. Riboflavin (Rf) is the precursor of FAD (flavin adenine dinucleotide) and FMN (flavin mononucleotide), which are involved in different redox reactions, including the energetic metabolism processes occurring in mitochondria. To date, human induced pluripotent stem cells (iPSCs) have given the opportunity to characterize RTD2 motoneurons, which reflect the most affected cell type. Previous works have demonstrated mitochondrial and peroxisomal altered energy metabolism as well as cytoskeletal derangement in RTD2 iPSCs and iPSC-derived motoneurons. So far, no attention has been dedicated to astrocytes. Results and discussion: Here, we demonstrate that in vitro differentiation of astrocytes, which guarantee trophic and metabolic support to neurons, from RTD2 iPSCs is not compromised. These cells do not exhibit evident morphological differences nor significant changes in the survival rate when compared to astrocytes derived from iPSCs of healthy individuals. These findings indicate that differently from what had previously been documented for neurons, RTD2 does not compromise the morpho-functional features of astrocytes.

Recent advances and applications of human brain models.

Recent advances in human pluripotent stem cell (hPSC) technologies have prompted the emergence of new research fields and applications for human neurons and brain organoids. Brain organoids have gained attention as an in vitro model system that recapitulates the higher structure, cellular diversity and function of the brain to explore brain development, disease modeling, drug screening, and regenerative medicine. This progress has been accelerated by abundant interactions of brain organoid technology with various research fields. A cross-disciplinary approach with human brain organoid technology offers a higher-ordered advance for more accurately understanding the human brain. In this review, we summarize the status of neural induction in two- and three-dimensional culture systems from hPSCs and the modeling of neurodegenerative diseases using brain organoids. We also highlight the latest bioengineered technologies for the assembly of spatially higher-ordered neural tissues and prospects of brain organoid technology toward the understanding of the potential and abilities of the human brain.

Pediatric Tumors as Disorders of Development: The Case for In Vitro Modeling Based on Human Stem Cells.

Despite improvements in patient outcomes, pediatric cancer remains a leading cause of non-accidental death in children. Recent genetic analysis of patients with pediatric cancers indicates an important role for both germline genetic predisposition and cancer-specific somatic driver mutations. Increasingly, evidence demonstrates that the developmental timepoint at which the cancer cell-of-origin transforms is critical to tumor identity and therapeutic response. Therefore, future therapeutic development would be bolstered by the use of disease models that faithfully recapitulate the genetic context, cell-of-origin, and developmental window of vulnerability in pediatric cancers. Human stem cells have the potential to incorporate all of these characteristics into a pediatric cancer model, while serving as a platform for rapid genetic and pharmacological testing. In this review, we describe how human stem cells have been used to model pediatric cancers and how these models compare to other pediatric cancer model modalities.

Today, pediatric cancer is a leading cause of non-accidental death in children. In order to further improve outcomes, it is important for researchers and clinicians alike to recognize how pediatric cancers are distinct from adult cancers. Inherited risk of cancer may play a greater role in pediatric cancer risk, and subsequent tumor-specific acquired driver mutations initiate tumor formation. However, there is substantial interaction between inherited and acquired mutations, which supports consideration of both simultaneously. Recent advancements in biotechnology, have improved matching between early cells of development and pediatric cancer cells, although cell-of-origin for certain pediatric central nervous system tumors remain elusive. Increasingly, evidence, particularly in pediatric medulloblastoma, demonstrates that the developmental timepoint at which the cancer cell-of-origin transforms is critical to tumor identity and therapeutic response. Therefore, future therapeutic development would be bolstered by the use of disease models that faithfully recapitulate the genetic context, cell-of-origin, and developmental window of pediatric cancers. Human stem cells have the potential to incorporate all of these characteristics into a pediatric cancer model, while serving as a platform for rapid genetic and pharmacological testing. In this review, we describe how human stem cells have been used to model pediatric cancers, how human these models compare to other pediatric cancer model modalities, and how these models can be improved in the future.

iPSC-Based Disease Modeling and Functional Assessment of Neurons in Patients with Metabolic Disorder.

The advancement in technology has allowed us to identify and accurately detect new mutations causing genetic disorders. However, their underlying physiological mechanisms of manifestation are not well understood. This chapter is a non-invasive blueprint to how iPSC-based disease modeling can be used to understand the neural activity and provide mechanistic insights for inborn disorder patients with neurological dysfunction seen more prominently with metabolic disorder patients. It has increasingly become easier to create personalized iPSCs from both specific patients and corresponding age and sex-matched controls by using their blood samples. These iPSCs can be used to generate any cell type of the body. This chapter covers how iPSCs can be generated from blood cells and their characterization followed by instructions on differentiating these iPSCs into mature neurons in a petri dish. The chapter most importantly describes how these mature neurons can be evaluated for their activity by using multi-well microelectrode array system and its analysis. This method of generating personalized iPSC derived neurons and their endpoint assessment can be applied to many clinical and preclinical studies. This iPSC-based application can be extrapolated to study any condition which can affect neuronal activity.