Publications

Astrocytes have been shown to play a central role in Alzheimer’s Disease (AD). However, the genes and biological pathways underlying disease manifestation are unknown, and it is unclear whether regional molecular differences among astrocytes contribute to regional specificity of disease. Here, we began to address these challenges with integrated experimental and computational approaches. We constructed a human astrocyte-specific functional gene network using Bayesian integration of a large compendium of human functional genomics data, as well as regional astrocyte gene expression profiles we generated in the mouse. This network identifies likely region-specific astrocyte pathways that operate in healthy brains. We leveraged our findings to compile genome-wide astrocyte-associated disease-gene predictions, employing a novel network-guided differential expression analysis (NetDIFF). We also used this data to predict a list of astrocyte-expressed genes mediating region-specific human disease, using a network-guided shortest path method (NetPATH). Both the network and our results are publicly available using an interactive web interface at http://astrocyte.princeton.edu. Our experimental and computational studies propose a strategy for disease gene and pathway prediction that may be applied to a host of human neurological disorders.

We present a data-driven method for reconstructing the galactic acceleration field from phase-space measurements of stellar streams. Our approach is based on a flexible and differentiable fit to the stream in phase-space, enabling a direct estimate of the acceleration vector along the stream. Reconstruction of the local acceleration field can be applied independently to each of several streams, allowing us to sample the acceleration field due to the underlying galactic potential across a range of scales. Our approach is methodologically different from previous works, since a model for the gravitational potential does not need to be adopted beforehand. Instead, our flexible neural-network-based model treats the stream as a collection of orbits with a locally similar mixture of energies, rather than assuming that the stream delineates a single stellar orbit. Accordingly, our approach allows for distinct regions of the stream to have different mean energies, as is the case for real stellar streams. Once the acceleration vector is sampled along the stream, standard analytic models for the galactic potential can then be rapidly constrained. We find our method recovers the correct parameters for a ground-truth triaxial logarithmic halo potential when applied to simulated stellar streams. Alternatively, we demonstrate that a flexible potential can be constrained with a neural network, though standard multipole expansions can also be constrained. Our approach is applicable to simple and complicated gravitational potentials alike, and enables potential reconstruction from a fully data-driven standpoint using measurements of slowly phase-mixing tidal debris.

We use tensor network techniques to obtain high-order perturbative diagrammatic expansions for the quantum many-body problem at very high precision. The approach is based on a tensor train parsimonious representation of the sum of all Feynman diagrams, obtained in a controlled and accurate way with the tensor cross interpolation algorithm. It yields the full time evolution of physical quantities in the presence of any arbitrary time-dependent interaction. Our benchmarks on the Anderson quantum impurity problem, within the real-time nonequilibrium Schwinger-Keldysh formalism, demonstrate that this technique supersedes diagrammatic quantum Monte Carlo by orders of magnitude in precision and speed, with convergence rates \(1/N2\) or faster, where N is the number of function evaluations. The method also works in parameter regimes characterized by strongly oscillatory integrals in high dimension, which suffer from a catastrophic sign problem in quantum Monte Carlo calculations. Finally, we also present two exploratory studies showing that the technique generalizes to more complex situations: a double quantum dot and a single impurity embedded in a two-dimensional lattice.

Novel design of proteins to target receptors for treatment or tissue augmentation has come to the fore owing to advancements in computing power, modeling frameworks, and translational successes. Shorter proteins, or peptides, can offer combinatorial synergies with dendrimer, polymer, or other peptide carriers for enhanced local signaling, which larger proteins may sterically hinder. Here, we present a generalized method for designing a novel peptide. We first show how to create a script protocol that can be used to iteratively optimize and screen novel peptide sequences for binding a target protein. We present a step-by-step introduction to utilizing file repositories, data bases, and the Rosetta software suite. RosettaScripts, an .xml interface that allows for sequential functions to be performed, is used to order the functions for repeatable performance. These strategies may lead to more groups venturing into computational design, which may result in synergies from artificial intelligence/machine learning (AI/ML) to phage display and screening. Importantly, the beginner is expected to be able to design their first peptide ligand and begin their journey in peptide drug discovery. Generally, these peptides potentially could be used to interact with any enzyme or receptor, for example, in the study of chemokines and their interactions with glycosoaminoglycans and their receptors.

The contemporaneous detection of gravitational waves and gamma rays from the GW170817/GRB 170817A, followed by kilonova emission a day after, confirmed compact binary neutron-star mergers as progenitors of short-duration gamma-ray bursts (GRBs), and cosmic sources of heavy r-process nuclei. However, the nature (and lifespan) of the merger remnant and the energy reservoir powering these bright gamma-ray flashes remains debated, while the first minutes after the merger are unexplored at optical wavelengths. Here, we report the earliest discovery of bright thermal optical emission associated with the short GRB 180618A with extended gamma-ray emission, with ultraviolet and optical multicolour observations starting as soon as 1.4 minutes post-burst. The spectrum is consistent with a fast-fading afterglow and emerging thermal optical emission at 15 minutes post-burst, which fades abruptly and chromatically (flux density Fν∝t−α, α=4.6±0.3) just 35 minutes after the GRB. Our observations from gamma rays to optical wavelengths are consistent with a hot nebula expanding at relativistic speeds, powered by the plasma winds from a newborn, rapidly-spinning and highly magnetized neutron star (i.e. a millisecond magnetar), whose rotational energy is released at a rate Lth∝t−(2.22±0.14) to reheat the unbound merger-remnant material. These results suggest such neutron stars can survive the collapse to a black hole on timescales much larger than a few hundred milliseconds after the merger, and power the GRB itself through accretion. Bright thermal optical counterparts to binary merger gravitational wave sources may be common in future wide-field fast-cadence sky surveys.

We examine the quenching characteristics of 328 isolated dwarf galaxies (108<Mstar/M⊙<1010) within the \Rom{} cosmological hydrodynamic simulation. Using mock observation methods, we identify isolated dwarf galaxies with quenched star formation and make direct comparisons to the quenched fraction in the NASA Sloan Atlas (NSA). Similar to other cosmological simulations, we find a population of quenched, isolated dwarf galaxies below Mstar<109M⊙ not detected within the NSA. We find that the presence of massive black holes (MBHs) in \Rom{} is largely responsible for the quenched, isolated dwarfs, while isolated dwarfs without an MBH are consistent with quiescent fractions observed in the field. Quenching occurs between z=0.5−1, during which the available supply of star-forming gas is heated or evacuated by MBH feedback. Mergers or interactions seem to play little to no role in triggering the MBH feedback. At low stellar masses, Mstar≲109.3M⊙, quenching proceeds across several Gyr as the MBH slowly heats up gas in the central regions. At higher stellar masses, Mstar≳109.3M⊙, quenching occurs rapidly within 1 Gyr, with the MBH evacuating gas from the central few kpc of the galaxy and driving it to the outskirts of the halo. Our results indicate the possibility of substantial star formation suppression via MBH feedback within dwarf galaxies in the field. On the other hand, the apparent over-quenching of dwarf galaxies due to MBH suggests higher resolution and/or better modeling is required for MBHs in dwarfs, and quenched fractions offer the opportunity to constrain current models.

Inspired by the recent realization of a two-dimensional (2-D) chiral fluid as an active monolayer droplet moving atop a 3-D Stokesian fluid, we formulate mathematically its free-boundary dynamics. The surface droplet is described as a general 2-D linear, incompressible and isotropic fluid, having a viscous shear stress, an active chiral driving stress and a Hall stress allowed by the lack of time-reversal symmetry. The droplet interacts with itself through its driven internal mechanics and by driving flows in the underlying 3-D Stokes phase. We pose the dynamics as the solution to a singular integral–differential equation, over the droplet surface, using the mapping from surface stress to surface velocity for the 3-D Stokes equations. Specializing to the case of axisymmetric droplets, exact representations for the chiral surface flow are given in terms of solutions to a singular integral equation, solved using both analytical and numerical techniques. For a disc-shaped monolayer, we additionally employ a semi-analytical solution that hinges on an orthogonal basis of Bessel functions and allows for efficient computation of the monolayer velocity field, which ranges from a nearly solid-body rotation to a unidirectional edge current, depending on the subphase depth and the Saffman–Delbrück length. Except in the near-wall limit, these solutions have divergent surface shear stresses at droplet boundaries, a signature of systems with codimension-one domains embedded in a 3-D medium. We further investigate the effect of a Hall viscosity, which couples radial and transverse surface velocity components, on the dynamics of a closing cavity. Hall stresses are seen to drive inward radial motion, even in the absence of edge tension.

We report discovery of a bright, nearby (G=13.8;d=480pc) Sun-like star orbiting a dark object. We identified the system as a black hole candidate via its astrometric orbital solution from the Gaia mission. Radial velocities validated and refined the Gaia solution, and spectroscopy ruled out significant light contributions from another star. Joint modeling of radial velocities and astrometry constrains the companion mass to M2=9.62±0.18M⊙. The spectroscopic orbit alone sets a minimum companion mass of M2>5M⊙; if the companion were a 5M⊙ star, it would be 500 times more luminous than the entire system. These constraints are insensitive to the mass of the luminous star, which appears as a slowly-rotating G dwarf (Teff=5850K, logg=4.5, M=0.93M⊙), with near-solar metallicity ([Fe/H]=−0.2) and an unremarkable abundance pattern. We find no plausible astrophysical scenario that can explain the orbit and does not involve a black hole. The orbital period, Porb=185.6 days, is longer than that of any known stellar-mass black hole binary. The system's modest eccentricity (e=0.45), high metallicity, and thin-disk Galactic orbit suggest that it was born in the Milky Way disk with at most a weak natal kick. How the system formed is uncertain. Common envelope evolution can only produce the system's wide orbit under extreme and likely unphysical assumptions. Formation models involving triples or dynamical assembly in an open cluster may be more promising. This is the nearest known black hole by a factor of 3, and its discovery suggests the existence of a sizable population of dormant black holes in binaries. Future Gaia releases will likely facilitate the discovery of dozens more.

Both the core collapse of rotating massive stars, and the coalescence of neutron star (NS) binaries, result in the formation of a hot, differentially rotating NS remnant. The timescales over which differential rotation is removed by internal angular-momentum transport processes (`viscosity') has key implications for the remnant's long-term stability and the NS equation-of-state (EOS). Guided by a non-rotating model of a cooling proto-NS, we estimate the dominant sources of viscosity using an externally imposed angular velocity profile Ω(r). Although the magnetorotational instability provides the dominant source of effective viscosity at large radii, convection and/or the Spruit-Tayler dynamo dominate in the core of merger remnants where dΩ/dr≥0. Furthermore, the viscous timescale in the remnant core is sufficiently short that solid body rotation will be enforced faster than matter is accreted from rotationally-supported outer layers. Guided by these results, we develop a toy model for how the merger remnant core grows in mass and angular momentum due to accretion. We find that merger remnants with sufficiently massive and slowly rotating initial cores may collapse to black holes via envelope accretion, even when the total remnant mass is less than the usually considered threshold ≈1.2MTOV for forming a stable solid-body rotating NS remnant (where MTOV is the maximum non-rotating NS mass supported by the EOS). This qualitatively new picture of the post-merger remnant evolution and stability criterion has important implications for the expected electromagnetic counterparts from binary NS mergers and for multi-messenger constraints on the NS EOS.

To prepare gametes with the appropriate number of chromosomes, mammalian oocytes undergo two sequential cell divisions. During each division, a large, long-lived, microtubule-based organelle called the meiotic spindle assembles around condensed chromosomes. Although meiotic spindles have been intensively studied for several decades, as force-generating mechanical objects, they remain very poorly understood. In materials physics, coarse-grained theories have been essential in understanding the large-scale behavior of systems composed of many interacting particles. It is unclear, however, if this approach can succeed in capturing the properties of active, biochemically complex, living materials like the spindle. Here, we show that a class of models based on nematic liquid crystal theory can describe important aspects of the organelle-scale structure and dynamics of spindles in living mouse oocytes. Using our models to interpret quantitative polarization microscopy data, we measure for the first time material properties relating to stress propagation in living oocytes, including the nematic diffusivities corresponding to splay and bend deformations. Unlike the reconstituted amphibian spindles that were previously studied in vitro, nematic elastic stress is exponentially screened in the microtubule network of living mammalian oocytes, with a screening length of order one micron. This observation can be explained by the relatively high volume fraction of embedded chromosomes in mammalian meiotic spindles, which cause long voids in the microtubule network and so disrupt orientational stress propagation.