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.

Atherosclerosis, a leading cause of cardiovascular disease, necessitates advanced and innovative modeling techniques to better understand and predict plaque dynamics. The present work presents two distinct hypothetical models inspired by different research fields: the logistic map from chaos theory and Markov models from stochastic processes. The logistic map effectively models the nonlinear progression and sudden changes in plaque stability, reflecting the chaotic nature of atherosclerotic events. In contrast, Markov models, including traditional Markov chains, spatial Markov models, and Markov random fields, provide a probabilistic framework to assess plaque stability and transitions. Spatial Markov models, visualized through heatmaps, highlight the spatial distribution of transition probabilities, emphasizing local interactions and dependencies. Markov random fields incorporate complex spatial interactions, inspired by advances in physics and computational biology, but present challenges in parameter estimation and computational complexity. While these hypothetical models offer promising insights, they require rigorous validation with real-world data to confirm their accuracy and applicability. This study underscores the importance of interdisciplinary approaches in developing theoretical models for atherosclerotic plaques.

Cockayne Syndrome B (CSB) is a hereditary multiorgan syndrome which-through largely unknown mechanisms-can affect the brain where it clinically presents with microcephaly, intellectual disability and demyelination. Using human induced pluripotent stem cell (hiPSC)-derived neural 3D models generated from CSB patient-derived and isogenic control lines, we here provide explanations for these three major neuropathological phenotypes. In our models, CSB deficiency is associated with (i) impaired cellular migration due to defective autophagy as an explanation for clinical microcephaly; (ii) altered neuronal network functionality and neurotransmitter GABA levels, which is suggestive of a disturbed GABA switch that likely impairs brain circuit formation and ultimately causes intellectual disability; and (iii) impaired oligodendrocyte maturation as a possible cause of the demyelination observed in children with CSB. Of note, the impaired migration and oligodendrocyte maturation could both be partially rescued by pharmacological HDAC inhibition.

UNASSIGNED: This study sought to document and understand facilitators and barriers to producing, translating, and using modeled evidence in decision-making in Burkina Faso, Nigeria, India, and Kenya. We explored researcher-decision-maker engagement mechanisms as key facilitators of evidence use, with a focus on knowledge brokers and boundary organizations.
UNASSIGNED: The study used mixed methods drawing on analysis from key informant interviews and surveys, complemented by a rapid desk review to map modeling activities and actors. The survey was conducted online while the qualitative research entailed in-depth interviews with modelers, knowledge brokers, and decision-makers working in a representative variety of health fields, organizations, and levels of government. This study was approved by Health Media Lab IRB (Institutional Review Board) in the United States and a local IRB in each study country and conducted between September 2021 and June 2022.
UNASSIGNED: Informants interviewed for this study described a range of factors that facilitate and inhibit the use of modeled evidence in public health decision-making at the individual, organizational, and environmental levels. Key themes included the capacity to produce, translate, and use modeled evidence; the timing and relevance of modeling outputs; the existence of communications channels between modelers and decision-makers; the strength of underlying data systems; the role of sustained funding; and the impact of global crises.
UNASSIGNED: This study highlights the importance of taking an ecosystem approach to supporting modeling activities, considering individual, organizational, and environmental factors and how different actors and interact to inform the production, translation, and use of modeled evidence. Structured interaction that promotes dialogue, debate, and joint sense making between the producers and users of evidence is critical to informing and influencing the use of evidence in decision-making.

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.

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.

Since early 2020 the COVID-19 pandemic has paralyzed the world, resulting in more than half a billion infections and over 6 million deaths within a 28-month period. Knowledge about the disease remains largely disjointed, especially when considering the molecular mechanisms driving the diversity of clinical manifestations and symptoms. Despite the recent availability of vaccines, there remains an urgent need to develop effective treatments for cases of severe disease, especially in the face of novel virus variants. The complexity of the situation is exacerbated by the emergence of COVID-19 as a complex and multifaceted systemic disease affecting independent tissues and organs throughout the body. The development of effective treatment strategies is therefore predicated on an integrated understanding of the underlying disease mechanisms and their potentially causative link to the diversity of observed clinical phenotypes. To address this need, we utilized a computational technology (the Dataome platform) to build an integrated clinico-molecular view on the most important COVID-19 clinical phenotypes. Our results provide the first integrated, whole-patient model of COVID-19 symptomatology that connects the molecular lifecycle of SARS-CoV-2 with microvesicle-mediated intercellular communication and the contact activation and kallikrein-kinin systems. The model not only explains the clinical pleiotropy of COVID-19, but also provides an evidence-driven framework for drug development/repurposing and the identification of critical risk factors. The associated knowledge is provided in the form of the open source COVID-19 Explorer (https://covid19.molecularhealth.com), enabling the global community to explore and analyze the key molecular features of systemic COVID-19 and associated implications for research priorities and therapeutic strategies. Our work suggests that knowledge modeling solutions may offer important utility in expediting the global response to future health emergencies.

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.

Genome editing is a technology to make specific changes in the DNA of a cell or an organism. It has significantly altered the landscape of life sciences, facilitating the establishment of exceedingly customized genetic modifications. Among various genome editing technologies, the CRISPR/Cas9 system, a specific endonuclease induces a double stranded DNA break and enabling modifications to the genome, has surfaced as a formidable and adaptable instrument. Its significance cannot be overstated, as it not only allows for the manipulation of genomes in model organisms but also holds great potential for revolutionary advances in medicine, particularly in treating genetic diseases. This review paper explores the remarkable journey of CRISPR/Cas9, its natural function, mechanisms, and transformative impact on genome editing and finally the use of artificial intelligence and other intelligent manufacturing tools used. The introduction provides the background on genome editing, emphasizing the emergence and significance of CRISPR/Cas9. Subsequent sections comprehensively elucidate its natural function, disease modeling, agriculture, and biotechnology, address therapeutic applications, and ongoing clinical trials while also discussing prospects and ethical implications. We summarized the key findings, indicating that CRISPR/Cas9 has empowered the creation of disease-specific animal models. This provides invaluable insights into pathogenic mechanisms and opens new avenues for drug discovery, reaffirming the transformative impact of CRISPR/Cas9 on genome editing. Finally we discussed the importance of continued research and collaboration for comprehensive utilization of the inherent capabilities of this molecular precision tool in shaping forthcoming advancements.

Autosomal dominant optic atrophy (ADOA) is a rare progressive disease mainly caused by mutations in OPA1, a nuclear gene encoding for a mitochondrial protein that plays an essential role in mitochondrial dynamics, cell survival, oxidative phosphorylation, and mtDNA maintenance. ADOA is characterized by the degeneration of retinal ganglion cells (RGCs). This causes visual loss, which can lead to legal blindness in many cases. Nowadays, there is no effective treatment for ADOA. In this article, we have established an isogenic human RGC model for ADOA using iPSC technology and the genome editing tool CRISPR/Cas9 from a previously generated iPSC line of an ADOA plus patient harboring the pathogenic variant NM_015560.3: c.1861C>T (p.Gln621Ter) in heterozygosis in OPA1. To this end, a protocol based on supplementing the iPSC culture media with several small molecules and defined factors trying to mimic embryonic development has been employed. Subsequently, the created model was validated, confirming the presence of a defect of intergenomic communication, impaired mitochondrial respiration, and an increase in apoptosis and ROS generation. Finally, we propose the analysis of OPA1 expression by qPCR as an easy read-out method to carry out future drug screening studies using the created RGC model. In summary, this model provides a useful platform for further investigation of the underlying pathophysiological mechanisms of ADOA plus and for testing compounds with potential pharmacological action.