mRNA decay analysis in Drosophila melanogaster: Drug-induced changes in glutathione S-transferase D21 mRNA stability

We have established an in vivo system to investigate mechanisms by which pentobarbital (PB), a psychoactive drug with a sedative effect, changes the rate of decay of gstD21 mRNA (encoding a Drosophila glutathione S-transferase). Here we describe methods for the use of hsp70 promoter-based transgenes and transgenic lines to determine mRNA half-lives by RNase protection assays in Drosophila. We are able to identify and map putative decay intermediates by cRT-PCR and DNA sequencing of the resulting clones. Our results indicate that the 3′-UTR of gstD21 mRNA is responsive to PB by regulating mRNA decay and that the cis-acting element(s) responsible for the PB-mediated stabilization resides in a 59 nucleotide sequence in the 3′-UTR of the gstD21 mRNA (Akgül and Tu, 2007).National Institute of Environmental Health Sciences (NIEHS) (ES02678

Superfluid and magnetic states of an ultracold Bose gas with synthetic three-dimensional spin-orbit coupling in an optical lattice

We study ultracold bosonic atoms with the synthetic three-dimensional spin-orbit (SO) coupling in a cubic optical lattice. In the superfluidity phase, the lowest energy band exhibits one, two or four pairs of degenerate single-particle ground states depending on the SO-coupling strengths, which can give rise to the condensate states with spin-stripes for the weak atomic interactions. In the deep Mott-insulator regime, the effective spin Hamiltonian of the system combines three-dimensional Heisenberg exchange interactions, anisotropy interactions and Dzyaloshinskii-Moriya interactions. Based on Monte Carlo simulations, we numerically demonstrate that the resulting Hamiltonian with an additional Zeeman field has a rich phase diagram with spiral, stripe, vortex crystal, and especially Skyrmion crystal spin-textures in each xy-plane layer. The obtained Skyrmion crystals can be tunable with square and hexagonal symmetries in a columnar manner along the z axis, and moreover are stable against the inter-layer spin-spin interactions in a large parameter region.Comment: 9 pages, 4 figures; title modified, references and discussions added; accepted by PR

Proton Heating in Solar Wind Compressible Turbulence with Collisions between Counter-propagating Waves

Magnetohydronamic turbulence is believed to play a crucial role in heating the laboratorial, space, and astrophysical plasmas. However, the precise connection between the turbulent fluctuations and the particle kinetics has not yet been established. Here we present clear evidence of plasma turbulence heating based on diagnosed wave features and proton velocity distributions from solar wind measurements by the Wind spacecraft. For the first time, we can report the simultaneous observation of counter-propagating magnetohydrodynamic waves in the solar wind turbulence. Different from the traditional paradigm with counter-propagating Alfv\'en waves, anti-sunward Alfv\'en waves (AWs) are encountered by sunward slow magnetosonic waves (SMWs) in this new type of solar wind compressible turbulence. The counter-propagating AWs and SWs correspond respectively to the dominant and sub-dominant populations of the imbalanced Els\"asser variables. Nonlinear interactions between the AWs and SMWs are inferred from the non-orthogonality between the possible oscillation direction of one wave and the possible propagation direction of the other. The associated protons are revealed to exhibit bi-directional asymmetric beams in their velocity distributions: sunward beams appearing in short and narrow patterns and anti-sunward broad extended tails. It is suggested that multiple types of wave-particle interactions, i.e., cyclotron and Landau resonances with AWs and SMWs at kinetic scales, are taking place to jointly heat the protons perpendicularly and parallel

Sound propagation over uneven ground and irregular topography

The acoustic impedance of the surface coverings used in the laboratory experiments on sound diffraction by topographical ridges was determined. The model, which was developed, takes into account full wave effects and the possibility of surface waves and predicts the sound pressure level at the receiver location relative to what would be expected if the flat surface were not present. The sound pressure level can be regarded as a function of frequency, sound speed in air, heights of source and receiver, and horizontal distance from source to receiver, as well as the real and imaginary parts of the surface impedance

Nanococktail Based on Supramolecular Glyco-Assembly for Eradicating Tumors In Vivo

The development of robust phototherapeutic strategies for eradicating tumors remains a significant challenge in the transfer of cancer phototherapy to clinical practice. Here, a phototherapeutic nanococktail atovaquone/17-dimethylaminoethylamino-17-demethoxygeldanamycin/glyco-BODIPY (ADB) was developed to enhance photodynamic therapy (PDT) and photothermal therapy (PTT) via alleviation of hypoxia and thermal resistance that was constructed using supramolecular self-assembly of glyco-BODIPY (BODIPY-SS-LAC, BSL-1), hypoxia reliever atovaquone (ATO), and heat shock protein inhibitor 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG). Benefiting from a glyco-targeting and glutathione (GSH) responsive units BSL-1, ADB can be rapidly taken up by hepatoma cells, furthermore the loaded ATO and 17-DMAG can be released in original form into the cytoplasm. Using in vitro and in vivo results, it was confirmed that ADB enhanced the synergetic PDT and PTT upon irradiation using 685 nm near-infrared light (NIR) under a hypoxic tumor microenvironment where ATO can reduce O2 consumption and 17-DMAG can down-regulate HSP90. Moreover, ADB exhibited good biosafety, and tumor eradication in vivo. Hence, this as-developed phototherapeutic nanococktail overcomes the substantial obstacles encountered by phototherapy in tumor treatment and offers a promising approach for the eradication of tumors. </p

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields

Lithography is fundamental to integrated circuit fabrication, necessitating large computation overhead. The advancement of machine learning (ML)-based lithography models alleviates the trade-offs between manufacturing process expense and capability. However, all previous methods regard the lithography system as an image-to-image black box mapping, utilizing network parameters to learn by rote mappings from massive mask-to-aerial or mask-to-resist image pairs, resulting in poor generalization capability. In this paper, we propose a new ML-based paradigm disassembling the rigorous lithographic model into non-parametric mask operations and learned optical kernels containing determinant source, pupil, and lithography information. By optimizing complex-valued neural fields to perform optical kernel regression from coordinates, our method can accurately restore lithography system using a small-scale training dataset with fewer parameters, demonstrating superior generalization capability as well. Experiments show that our framework can use 31% of parameters while achieving 69$\times$ smaller mean squared error with 1.3$\times$ higher throughput than the state-of-the-art.Comment: Accepted by DAC2