The puzzling dynamical status of the core of the globular cluster NGC 6752

We have used high resolution WFPC2-HST and ground based Wide Field images to determine the center of gravity and construct an extended radial density and brightness profile of the cluster NGC 6752 including, for the first time, detailed star counts in the very inner region. The barycenter of the 9 innermost X-ray sources detected by Chandra is located only 1.9" off the new center of gravity. Both the density and the brightness profile of the central region are best fitted by a double King model, suggesting that NGC 6752 is experiencing a post-core collapse "bounce". Taking advantage from our new optical data, we discuss the puzzling nature of the accelerations displayed by the innermost millisecond pulsars detected in this cluster. We discuss two possible origins to the accelerations: 1) the overall cluster gravitational potential which would require a central projected mass to light ratio of order 6-7 and the existence of a few thousand solar masses of low-luminosity matter within the inner 0.08 pc of NGC6752; 2) the existence of a local perturber(s) of the pulsar dynamics, such as a recently proposed binary black hole of intermediate (100-$200 Msun) mass.Comment: 24 pages, 5 figures (accepted on ApJ

IHCV: Discovery of Hidden Time-Dependent Control Variables in Non-Linear Dynamical Systems

Discovering non-linear dynamical models from data is at the core of science. Recent progress hinges upon sparse regression of observables using extensive libraries of candidate functions. However, it remains challenging to model hidden non-observable control variables governing switching between different dynamical regimes. Here we develop a data-efficient derivative-free method, IHCV, for the Identification of Hidden Control Variables. First, the performance and robustness of IHCV against noise are evaluated by benchmarking the IHCV method using well-known bifurcation models (saddle-node, transcritical, pitchfork, Hopf). Next, we demonstrate that IHCV discovers hidden driver variables in the Lorenz, van der Pol, Hodgkin-Huxley, and Fitzhugh-Nagumo models. Finally, IHCV generalizes to the case when only partial observational is given, as demonstrated using the toggle switch model, the genetic repressilator oscillator, and a Waddington landscape model. Our proof-of-principle illustrates that utilizing normal forms could facilitate the data-efficient and scalable discovery of hidden variables controlling transitions between different dynamical regimes and non-linear models.Comment: 12 pages, 2 figure

Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

Abstract Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology

Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation

The differentiation of self-renewingprogenitor cells requires not only the regulation of lineage-and developmental stage-specific genes, but also the coordinated adaptation of housekeeping functionsfrom a metabolically active, proliferative state towards quiescence. How metabolic and cell cycle states are coordinated with the regulation of cell type-specific genes is an important question, as dissociation between differentiation, cell cycle, and metabolic states is a hallmark of cancer. Here we use a model system to systematically identify key transcriptional regulators of Ikaros-dependent B cell progenitor differentiation. We find that the coordinated regulation of housekeeping functions and tissue-specific gene expressionrequires afeedforward circuit whereby Ikarosdownregulates the expression of Myc. Our findings show how coordination between differentiation and housekeeping statescan be achieved by interconnected regulators. Similar principles likely coordinate differentiation and housekeeping functions during progenitor cell differentiation in other cell lineages

An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates

Heterogeneity of lung tumor endothelial cell (TEC) phenotypes across patients, species (human/mouse), and models (in vivo/in vitro) remains poorly inventoried at the single-cell level. We single-cell RNA (scRNA)-sequenced 56,771 endothelial cells from human/mouse (peri)-tumoral lung and cultured human lung TECs, and detected 17 known and 16 previously unrecognized phenotypes, including TECs putatively regulating immune surveillance. We resolved the canonical tip TECs into a known migratory tip and a putative basement-membrane remodeling breach phenotype. Tip TEC signatures correlated with patient survival, and tip/breach TECs were most sensitive to vascular endothelial growth factor blockade. Only tip TECs were congruent across species/models and shared conserved markers. Integrated analysis of the scRNA-sequenced data with orthogonal multi-omics and meta-analysis data across different human tumors, validated by functional analysis, identified collagen modification as a candidate angiogenic pathway