Asteroid g-2 experiments: new fifth force and ultralight dark sector tests

We study for the first time the possibility of probing long-range fifth forces utilizing asteroid astrometric data, via the fifth force-induced orbital precession. We examine nine Near-Earth Object (NEO) asteroids whose orbital trajectories are accurately determined via optical and radar astrometry. Focusing on a Yukawa-type potential mediated by a new gauge field (dark photon) or a baryon-coupled scalar, we estimate the sensitivity reach for the fifth-force coupling strength and mediator mass in the mass range $m \simeq 10^{-21}-10^{-15}\,{\rm eV}$. Our estimated sensitivity is comparable to leading limits from torsion balance experiments, potentially exceeding these in a specific mass range. The fifth forced-induced precession increases with the orbital semi-major axis in the small $m$ limit, motivating the study of objects further away from the Sun. We discuss future exciting prospects for extending our study to more than a million asteroids (including NEOs, main-belt asteroids, Hildas, and Jupiter Trojans), as well as trans-Neptunian objects and exoplanets.Comment: 2 figures, 1 table, 5 pages + reference

NARRATE: A Normal Assisted Free-View Portrait Stylizer

In this work, we propose NARRATE, a novel pipeline that enables simultaneously editing portrait lighting and perspective in a photorealistic manner. As a hybrid neural-physical face model, NARRATE leverages complementary benefits of geometry-aware generative approaches and normal-assisted physical face models. In a nutshell, NARRATE first inverts the input portrait to a coarse geometry and employs neural rendering to generate images resembling the input, as well as producing convincing pose changes. However, inversion step introduces mismatch, bringing low-quality images with less facial details. As such, we further estimate portrait normal to enhance the coarse geometry, creating a high-fidelity physical face model. In particular, we fuse the neural and physical renderings to compensate for the imperfect inversion, resulting in both realistic and view-consistent novel perspective images. In relighting stage, previous works focus on single view portrait relighting but ignoring consistency between different perspectives as well, leading unstable and inconsistent lighting effects for view changes. We extend Total Relighting to fix this problem by unifying its multi-view input normal maps with the physical face model. NARRATE conducts relighting with consistent normal maps, imposing cross-view constraints and exhibiting stable and coherent illumination effects. We experimentally demonstrate that NARRATE achieves more photorealistic, reliable results over prior works. We further bridge NARRATE with animation and style transfer tools, supporting pose change, light change, facial animation, and style transfer, either separately or in combination, all at a photographic quality. We showcase vivid free-view facial animations as well as 3D-aware relightable stylization, which help facilitate various AR/VR applications like virtual cinematography, 3D video conferencing, and post-production.Comment: 14 pages,13 figures https://youtu.be/mP4FV3evmy

Different Methods to Constrain Dark Matter

The currently favored cosmological model suggests that over 85% of the matter in our universe is dark, yet the existence of dark matter is still to be confirmed by detecting it through interactions with normal matter. Direct detection experiments hope to observe signals from the scattering of dark matter particles off of cryogenic target nuclei. A null result from direct detection leads to an exclusion curve in the cross section-dark matter particle mass parameter space. Theoretical predictions for exclusion curves involve standard halo model, in which three astrophysical parameters are assumed to control the distribution of dark matter in the Milky Way. This thesis first discusses the uncertainties in these three parameters on the exclusion curve from the XENON1T experiment. Our estimate done with Monte Carlo simulations shows that at a low WIMP mass, the uncertainty in cross section can span six orders of magnitude. Dark matter self-annihilation might power the first-generation stars and form Dark Stars. The possibility of Dark Stars was originally proposed in the context of Weakly Interacting Massive Particle (WIMP) model. Although the WIMP model is successful in explaining large structures in the universe, it faces difficulties when applied to structures as small as dwarf galaxies. To overcome the small-structure problems, self-interactions between dark matter particles are introduced and the Self-Interacting Dark Matter (SIDM) model was proposed. In the second part of this thesis, we evaluate the probability that Dark Stars can be powered by SIDM. We first propose a simple particle physics model of SIDM that satisfies all the current constraints, and work out the phase space region in which Dark Stars can form. Then we investigate the gravothermal evolution of SIDM minihalos in the presence of a gas potential, and investigate whether it can lead to a sufficiently high dark matter density for Dark Stars to form. Finally, we present the first study of the properties of Dark Stars assuming they can reach hydrostatic equilibrium. Dark matter is a major player in the formation of Milky Way-like galaxies. Different dark matter models lead to a different accretion history of Milky Way-like galaxies. This thesis finally studies the recent accretion history of Milky Way-like galaxies using statistical cluster analysis. Stars from the same accreted satellite galaxy are clustered in action space. Since actions are conserved in slow enough gravitational evolution, the accreted satellites should remain clustered until today. We apply the cluster analysis algorithm Enlink to accreted star particles in action space from the halos of three simulated Milky Way-like galaxies in the FIRE-2 simulations. We compare the groups found by our cluster analysis with the actual accreted satellites from these galaxies, and find the well-recovered satellites. The results show that the member stars of satellites which fell into the galaxy less than 7.1 Gyr ago and were more massive than 4.0 times 10^8 solar mass can be well recovered by cluster analysis.PHDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/175664/1/youjiawu_1.pd

Dark Stars Powered by Self-Interacting Dark Matter

Dark matter annihilation might power the first luminous stars in the Universe. This type of stars, known as Dark Stars, could form in 10^6-10^8 solar mass protohalos at redshifts z around 20, and they could be much more luminous and larger in size than ordinary stars powered by nuclear fusion. We investigate the formation of Dark Stars in the self-interacting dark matter (SIDM) scenario. We present a concrete particle physics model of SIDM that can simultaneously give rise to the observed dark matter density, satisfy constraints from astrophysical and terrestrial searches, and address the various small-scale problems of collisionless dark matter via the self-interactions. In this model, the power from dark matter annihilation is deposited in the baryonic gas in environments where Dark Stars could form. We further study the evolution of SIDM density profiles in the protohalos at z around 20. As the baryon cloud collapses due to the various cooling processes, the deepening gravitational potential can speed up gravothermal evolution of the SIDM halo, yielding sufficiently high dark matter densities for Dark Stars to form. We find that SIDM-powered Dark Stars can have similar properties, such as their luminosity and size, as Dark Stars predicted in collisionless dark matter models.Comment: 11 pages, 4 figure

Congenital hypothyroidism impairs spine growth of dentate granule cells by downregulation of CaMKIV

Abstract Congenital hypothyroidism (CH), a common neonatal endocrine disorder, can result in cognitive deficits if delay in diagnose and treatment. Dentate gyrus (DG) is the severely affected subregion of the hippocampus by the CH, where the dentate granule cells (DGCs) reside in. However, how CH impairs the cognitive function via affecting DGCs and the underlying mechanisms are not fully elucidated. In the present study, the CH model of rat pups was successfully established, and the aberrant dendrite growth of the DGCs and the impaired cognitive behaviors were observed in the offspring. Transcriptome analysis of hippocampal tissues following rat CH successfully identified that calcium/calmodulin-dependent protein kinase IV (CaMKIV) was the prominent regulator involved in mediating deficient growth of DGC dendrites. CaMKIV was shown to be dynamically regulated in the DG subregion of the rats following drug-induced CH. Interference of CaMKIV expression in the primary DGCs significantly reduced the spine density of dendrites, while addition of T3 to the primary DGCs isolated from CH pups could facilitate the spine growth of dendrites. Insights into relevant mechanisms revealed that CH-mediated CaMKIV deficiency resulted in the significant decrease of phosphorylated CREB in DGCs, in association with the abnormality of dendrites. Our results have provided a distinct cell type in hippocampus that is affected by CH, which would be beneficial for the treatment of CH-induced cognitive deficiency

Study on Quality Control of Compound <i>Anoectochilus roxburghii</i> (Wall.) Lindl. by Liquid Chromatography–Tandem Mass Spectrometry

Compound Anoectochilus roxburghii (Wall.) Lindl. (A. roxburghii) oral liquid (CAROL) is a hospital preparation of A. roxburghii and Ganoderma lucidum (G. lucidum), which have hepatoprotective effects. Eight active components (five nucleosides/nucleobases and three triterpenoid acids) in CAROL, A. roxburghii, and G. lucidum were simultaneously detected by high-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS). The multiple reaction monitoring (MRM) mode was applied for the detection of analytes. These eight compounds were separated well within 12 min and quantified using the internal standard working curve method. The method showed good linearity (R2 > 0.9935) and high sensitivity (limit of detection = 0.29 ng/mL). The analyte recovery ranged from 85.07% to 97.50% (relative standard deviation G. lucidum and A. roxburghii from the five regions was determined using this method. The contents of guanosine and ganoderic acid A in four batches of oral liquid were high and stabilized and could be recommended as quality markers (Q-marker) for CAROL. Simultaneous qualitative and quantitative analysis of nucleosides and triterpenoid acids in CAROL, A. roxburghii, and G. lucidum by LC–MS/MS based on the MRM model was reported for the first time. The proposed method provides a sensitive, rapid, and reliable approach for the quality control of Chinese medicinal products

Knockdown of astrocyte elevated gene-1 inhibits tumor growth and modifies microRNAs expression profiles in human colorectal cancer cells

AbstractAstrocyte elevated gene-1 (AEG-1), upregulated in various types of malignancies including colorectal cancer (CRC), has been reported to be associated with the carcinogenesis. MicroRNAs (miRNAs) are widely involved in the initiation and progression of cancer. However, the functional significance of AEG-1 and the relationship between AEG-1 and microRNAs in human CRC remains unclear. The aim of this study was to investigate whether AEG-1 could serve as a potential therapeutic target of human CRC and its possible mechanism. We adopted a strategy of ectopic overexpression or RNA interference to upregulate or downregulate expression of AEG-1 in CRC models. Their phenotypic changes were analyzed by Western blot, MTT and transwell matrix penetration assays. MicroRNAs expression profiles were performed using microarray analysis followed by validation using qRT-PCR. Knockdown of AEG-1 could significantly inhibit colon cancer cell proliferation, colony formation, invasion and promotes apoptosis. Conversely, upregulation of AEG-1 could significantly enhance cell proliferation, invasion and reduced apoptisis. AEG-1 directly contributes to resistance to chemotherapeutic drug. Targeted downregulation of AEG-1 might improve the expression of miR-181a-2∗, -193b and -193a, and inversely inhibit miR-31 and -9∗. Targeted inhibition of AEG-1 can lead to modification of key elemental characteristics, such as miRNAs, which may become a potential effective therapeutic strategy for CRC