HNRNPK maintains epidermal progenitor function through transcription of proliferation genes and degrading differentiation promoting mRNAs.

Maintenance of high-turnover tissues such as the epidermis requires a balance between stem cell proliferation and differentiation. The molecular mechanisms governing this process are an area of investigation. Here we show that HNRNPK, a multifunctional protein, is necessary to prevent premature differentiation and sustains the proliferative capacity of epidermal stem and progenitor cells. To prevent premature differentiation of progenitor cells, HNRNPK is necessary for DDX6 to bind a subset of mRNAs that code for transcription factors that promote differentiation. Upon binding, these mRNAs such as GRHL3, KLF4, and ZNF750 are degraded through the mRNA degradation pathway, which prevents premature differentiation. To sustain the proliferative capacity of the epidermis, HNRNPK is necessary for RNA Polymerase II binding to proliferation/self-renewal genes such as MYC, CYR61, FGFBP1, EGFR, and cyclins to promote their expression. Our study establishes a prominent role for HNRNPK in maintaining adult tissue self-renewal through both transcriptional and post-transcriptional mechanisms

Non-Convex Bilevel Optimization with Time-Varying Objective Functions

Bilevel optimization has become a powerful tool in a wide variety of machine learning problems. However, the current nonconvex bilevel optimization considers an offline dataset and static functions, which may not work well in emerging online applications with streaming data and time-varying functions. In this work, we study online bilevel optimization (OBO) where the functions can be time-varying and the agent continuously updates the decisions with online streaming data. To deal with the function variations and the unavailability of the true hypergradients in OBO, we propose a single-loop online bilevel optimizer with window averaging (SOBOW), which updates the outer-level decision based on a window average of the most recent hypergradient estimations stored in the memory. Compared to existing algorithms, SOBOW is computationally efficient and does not need to know previous functions. To handle the unique technical difficulties rooted in single-loop update and function variations for OBO, we develop a novel analytical technique that disentangles the complex couplings between decision variables, and carefully controls the hypergradient estimation error. We show that SOBOW can achieve a sublinear bilevel local regret under mild conditions. Extensive experiments across multiple domains corroborate the effectiveness of SOBOW

Chiral spin liquids with projected Gaussian fermionic entangled pair states

We study the parton construction of chiral spin liquids (CSLs) using projected Gaussian fermionic entangled pair states (GfPEPSs). First, we show that GfPEPSs can represent generic spinless Chern insulators faithfully with finite bond dimensions. Then, by applying the Gutzwiller projection to a bi-layer GfPEPSs, spin-1/2 Abelian and non-Abelian CSLs are obtained for Chern number $C=1$ and $C=2$, respectively. As a consequence of the topological obstruction for GfPEPSs, very weak Gossamer tails are observed in the correlation functions of the fermionic projected entangled pair state (PEPS) ansatze, suggesting that the no-go theorem for chiral PEPS is universal but does not bring any practical limitation. Remarkably, without fine tuning, all topological sectors can be constructed showing the expected number of chiral branches in the respective entanglement spectra, providing a sharp improvement with respect to the known bosonic PEPS approach

Binding of the influenza A virus NS1 protein to PKR mediates the inhibition of its activation by either PACT or double-stranded RNA

AbstractA major component of the cellular antiviral system is the latent protein kinase PKR, which is activated by binding to either double-stranded RNA (dsRNA) or the cellular PACT protein. Activated PKR phosphorylates the translation initiation factor eIF2, thereby inhibiting viral and cellular protein synthesis and virus replication. To evade the antiviral effects of PKR, many viruses, including influenza A virus, have evolved multiple mechanisms. For influenza A virus, the non-structural (NS1A) protein plays a major role in blocking activation of PKR during virus infection. The mechanism by which the NS1A protein inhibits PKR activation in infected cells has not been established. In the present study, we first carried out a series of in vitro experiments to determine whether the NS1A protein could utilize a common mechanism to inhibit PKR activation by both PACT and dsRNA, despite their different modes of activation. We demonstrated that the direct binding of the NS1A protein to the N-terminal 230 amino acid region of PKR can serve as such a common mechanism and that this binding does not require the RNA-binding activity of the NS1A protein. The lack of requirement for NS1A RNA-binding activity for the inhibition of PKR activation in vivo was established by two approaches. First, we showed that an NS1A protein lacking RNA-binding activity, like the wild-type (wt) protein, blocked PKR activation by PACT in vivo, as well as the downstream effects of PKR activation in cells, namely, eIF2 phosphorylation and apoptosis. In addition, we demonstrated that PKR activation is inhibited in cells infected with a recombinant influenza A virus expressing NS1A mutant protein that cannot bind RNA, as is the case in cells infected with wild-type influenza A virus

US-LARP progress on LHC IR upgrades

We review the progress on LHC IR upgrades made by the US-LARP collaboration since the last CARE meeting in November 2004. We introduce a new optics design with doublet focusing, and discuss energy deposition calculations with an open mid-plane dipole. We present the results of a beam-beam experiment at RHIC. This experiment was the first phase of a planned test of the wire compensation principle at RHIC

Chemical Abundances of the Typhon Stellar Stream

We present the first high-resolution chemical abundances of seven stars in the recently discovered high-energy stream Typhon. Typhon stars have apocenters >100 kpc, making this the first detailed chemical picture of the Milky Way's very distant stellar halo. Though the sample size is limited, we find that Typhon's chemical abundances are more like a dwarf galaxy than a globular cluster, showing a metallicity dispersion and no presence of multiple stellar populations. Typhon stars display enhanced $\alpha$-element abundances and increasing r-process abundances with increasing metallicity. The high-$\alpha$ abundances suggest a short star formation duration for Typhon, but this is at odds with expectations for the distant Milky Way halo and the presence of delayed r-process enrichment. If the progenitor of Typhon is indeed a new dwarf galaxy, possible scenarios explaining this apparent contradiction include a dynamical interaction that increases Typhon's orbital energy, a burst of enhanced late-time star formation that raises [$\alpha$/Fe], and/or group preprocessing by another dwarf galaxy before infall into the Milky Way. Alternatively, Typhon could be the high-energy tail of a more massive disrupted dwarf galaxy that lost energy through dynamical friction. We cannot clearly identify a known low-energy progenitor of Typhon in the Milky Way, but 70% of high-apocenter stars in cosmological simulations are from high-energy tails of large dwarf galaxies. Typhon's surprising combination of kinematics and chemistry thus underscores the need to fully characterize the dynamical history and detailed abundances of known substructures before identifying the origin of new substructures.Comment: 12 pages, 4 figures, 2 tables, accepted to MNRA