Id genes are essential for early heart formation.

Deciphering the fundamental mechanisms controlling cardiac specification is critical for our understanding of how heart formation is initiated during embryonic development and for applying stem cell biology to regenerative medicine and disease modeling. Using systematic and unbiased functional screening approaches, we discovered that the Id family of helix-loop-helix proteins is both necessary and sufficient to direct cardiac mesoderm formation in frog embryos and human embryonic stem cells. Mechanistically, Id proteins specify cardiac cell fate by repressing two inhibitors of cardiogenic mesoderm formation-Tcf3 and Foxa2-and activating inducers Evx1, Grrp1, and Mesp1. Most importantly, CRISPR/Cas9-mediated ablation of the entire Id (Id1-4) family in mouse embryos leads to failure of anterior cardiac progenitor specification and the development of heartless embryos. Thus, Id proteins play a central and evolutionarily conserved role during heart formation and provide a novel means to efficiently produce cardiovascular progenitors for regenerative medicine and drug discovery applications.

Model system identification of novel congenital heart disease gene candidates: focus on RPL13.

Genetics is a significant factor contributing to congenital heart disease (CHD), but our understanding of the genetic players and networks involved in CHD pathogenesis is limited. Here, we searched for de novo copy number variations (CNVs) in a cohort of 167 CHD patients to identify DNA segments containing potential pathogenic genes. Our search focused on new candidate disease genes within 19 deleted de novo CNVs, which did not cover known CHD genes. For this study, we developed an integrated high-throughput phenotypical platform to probe for defects in cardiogenesis and cardiac output in human induced pluripotent stem cell (iPSC)-derived multipotent cardiac progenitor (MCPs) cells and, in parallel, in the Drosophila in vivo heart model. Notably, knockdown (KD) in MCPs of RPL13, a ribosomal gene and SON, an RNA splicing cofactor, reduced proliferation and differentiation of cardiomyocytes, while increasing fibroblasts. In the fly, heart-specific RpL13 KD, predominantly at embryonic stages, resulted in a striking 'no heart' phenotype. KD of Son and Pdss2, among others, caused structural and functional defects, including reduced or abolished contractility, respectively. In summary, using a combination of human genetics and cardiac model systems, we identified new genes as candidates for causing human CHD, with particular emphasis on ribosomal genes, such as RPL13. This powerful, novel approach of combining cardiac phenotyping in human MCPs and in the in vivo Drosophila heart at high throughput will allow for testing large numbers of CHD candidates, based on patient genomic data, and for building upon existing genetic networks involved in heart development and disease.

Effects of Information Availability on Command-and-Control Decision Making: Performance, Trust, and Situation Awareness.

OBJECTIVE: We investigated how increases in task-relevant information affect human decision-making performance, situation awareness (SA), and trust in a simulated command-and-control (C2) environment. BACKGROUND: Increased information is often associated with an improvement of SA and decision-making performance in networked organizations. However, previous research suggests that increasing information without considering the task relevance and the presentation can impair performance. METHOD: We used a simulated C2 task across two experiments. Experiment 1 varied the information volume provided to individual participants and measured the speed and accuracy of decision making for task performance. Experiment 2 varied information volume and information reliability provided to two participants acting in different roles and assessed decision-making performance, SA, and trust between the paired participants. RESULTS: In both experiments, increased task-relevant information volume did not improve task performance. In Experiment 2, increased task-relevant information volume reduced self-reported SA and trust, and incorrect source reliability information led to poorer task performance and SA. CONCLUSION: These results indicate that increasing the volume of information, even when it is accurate and task relevant, is not necessarily beneficial to decision-making performance. Moreover, it may even be detrimental to SA and trust among team members. APPLICATION: Given the high volume of available and shared information and the safety-critical and time-sensitive nature of many decisions, these results have implications for training and system design in C2 domains. To avoid decrements to SA, interpersonal trust, and decision-making performance, information presentation within C2 systems must reflect human cognitive processing limits and capabilities.

Conserved transcription factors promote cell fate stability and restrict reprogramming potential in differentiated cells.

Defining the mechanisms safeguarding cell fate identity in differentiated cells is crucial to improve 1) - our understanding of how differentiation is maintained in healthy tissues or altered in a disease state, and 2) - our ability to use cell fate reprogramming for regenerative purposes. Here, using a genome-wide transcription factor screen followed by validation steps in a variety of reprogramming assays (cardiac, neural and iPSC in fibroblasts and endothelial cells), we identified a set of four transcription factors (ATF7IP, JUNB, SP7, and ZNF207 [AJSZ]) that robustly opposes cell fate reprogramming in both lineage and cell type independent manners. Mechanistically, our integrated multi-omics approach (ChIP, ATAC and RNA-seq) revealed that AJSZ oppose cell fate reprogramming by 1) - maintaining chromatin enriched for reprogramming TF motifs in a closed state and 2) - downregulating genes required for reprogramming. Finally, KD of AJSZ in combination with MGT overexpression, significantly reduced scar size and improved heart function by 50%, as compared to MGT alone post-myocardial infarction. Collectively, our study suggests that inhibition of barrier to reprogramming mechanisms represents a promising therapeutic avenue to improve adult organ function post-injury.

Cognitive Models in Cybersecurity: Learning From Expert Analysts and Predicting Attacker Behavior.

Cybersecurity stands to benefit greatly from models able to generate predictions of attacker and defender behavior. On the defender side, there is promising research suggesting that Symbolic Deep Learning (SDL) may be employed to automatically construct cognitive models of expert behavior based on small samples of expert decisions. Such models could then be employed to provide decision support for non-expert users in the form of explainable expert-based suggestions. On the attacker side, there is promising research suggesting that model-tracing with dynamic parameter fitting may be used to automatically construct models during live attack scenarios, and to predict individual attacker preferences. Predicted attacker preferences could then be exploited for mitigating risk of successful attacks. In this paper we examine how these two cognitive modeling approaches may be useful for cybersecurity professionals via two human experiments. In the first experiment participants play the role of cyber analysts performing a task based on Intrusion Detection System alert elevation. Experiment results and analysis reveal that SDL can help to reduce missed threats by 25%. In the second experiment participants play the role of attackers picking among four attack strategies. Experiment results and analysis reveal that model-tracing with dynamic parameter fitting can be used to predict (and exploit) most attackers' preferences 40-70% of the time. We conclude that studies and models of human cognition are highly valuable for advancing cybersecurity.

Generation of First Heart Field-like Cardiac Progenitors and Ventricular-like Cardiomyocytes from Human Pluripotent Stem Cells.

The generation of large amounts of functional human pluripotent stem cells-derived cardiac progenitors and cardiomyocytes of defined heart field origin is a pre-requisite for cell-based cardiac therapies and disease modeling. We have recently shown that Id genes are both necessary and sufficient to specify first heart field progenitors during vertebrate development. This differentiation protocol leverages these findings and uses Id1 overexpression in combination with Activin A as potent specifying cues to produce first heart field-like (FHF-L) progenitors. Importantly, resulting progenitors efficiently differentiate (~70-90%) into ventricular-like cardiomyocytes. Here we describe a detailed method to 1) generate Id1-overexpressing hPSCs and 2) differentiate scalable quantities of cryopreservable FHF-L progenitors and ventricular-like cardiomyocytes.

An Automated Platform for Assessment of Congenital and Drug-Induced Arrhythmia with hiPSC-Derived Cardiomyocytes.

The ability to produce unlimited numbers of human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) harboring disease and patient-specific gene variants creates a new paradigm for modeling congenital heart diseases (CHDs) and predicting proarrhythmic liabilities of drug candidates. However, a major roadblock to implementing hiPSC-CM technology in drug discovery is that conventional methods for monitoring action potential (AP) kinetics and arrhythmia phenotypes in vitro have been too costly or technically challenging to execute in high throughput. Herein, we describe the first large-scale, fully automated and statistically robust analysis of AP kinetics and drug-induced proarrhythmia in hiPSC-CMs. The platform combines the optical recording of a small molecule fluorescent voltage sensing probe (VoltageFluor2.1.Cl), an automated high throughput microscope and automated image analysis to rapidly generate physiological measurements of cardiomyocytes (CMs). The technique can be readily adapted on any high content imager to study hiPSC-CM physiology and predict the proarrhythmic effects of drug candidates.

Conducting polymer nanoparticles decorated with collagen mimetic peptides for collagen targeting.

We report on the formation of conducting polymer nanoparticles (CPNs), stabilized by a collagen mimetic peptide (CMP)-polymer amphiphile. CPNs ranging from ∼15 to 40 nm were readily accessible upon modifying the amphiphile concentration. Surface presentation of CMPs on CPN precluded intra-/inter-particle trimerization, while preserving their ability to target collagen without pre-activation.