Comparative genetics of seven plants endemic to Florida’s Lake Wales Ridge

Here we submit that mathematical tools used in population viability analysis can be used in conjunction with floristic and faunistic surveys to predict changes in biogeographic range. We illustrate our point by summarizing the results of a demographic study of Lobelia boykinii. In this study we used deterministic and stochastic matrix models to estimate the growth rate and to predict the time to extinction for three populations growing in the Carolina bays. The stochastic model better discriminated among the fates of the three populations. It predicted extinction for two populations in the next 25 years but no extinction of the third population for at least 50 years. Probability of extinction is likely correlated with hydrologic regime and fire frequency of the bay in which a population is found. The stochastic model could be combined with information about the geographic distribution of L. boykinii habitats to predict short-term biogeographic change

Cohomology of the Lie Superalgebra of Contact Vector Fields on R1∣1\mathbb{R}^{1|1} and Deformations of the Superspace of Symbols

Following Feigin and Fuchs, we compute the first cohomology of the Lie superalgebra $\mathcal{K}(1)$ of contact vector fields on the (1,1)-dimensional real superspace with coefficients in the superspace of linear differential operators acting on the superspaces of weighted densities. We also compute the same, but $\mathfrak{osp}(1|2)$-relative, cohomology. We explicitly give 1-cocycles spanning these cohomology. We classify generic formal $\mathfrak{osp}(1|2)$-trivial deformations of the $\mathcal{K}(1)$-module structure on the superspaces of symbols of differential operators. We prove that any generic formal $\mathfrak{osp}(1|2)$-trivial deformation of this $\mathcal{K}(1)$-module is equivalent to a polynomial one of degree $\leq4$. This work is the simplest superization of a result by Bouarroudj [On $\mathfrak{sl}$(2)-relative cohomology of the Lie algebra of vector fields and differential operators, J. Nonlinear Math. Phys., no.1, (2007), 112--127]. Further superizations correspond to $\mathfrak{osp}(N|2)$-relative cohomology of the Lie superalgebras of contact vector fields on $1|N$-dimensional superspace

A single H/ACA small nucleolar RNA mediates tumor suppression downstream of oncogenic RAS.

Small nucleolar RNAs (snoRNAs) are a diverse group of non-coding RNAs that direct chemical modifications at specific residues on other RNA molecules, primarily on ribosomal RNA (rRNA). SnoRNAs are altered in several cancers; however, their role in cell homeostasis as well as in cellular transformation remains poorly explored. Here, we show that specific subsets of snoRNAs are differentially regulated during the earliest cellular response to oncogenic RASG12V expression. We describe a novel function for one H/ACA snoRNA, SNORA24, which guides two pseudouridine modifications within the small ribosomal subunit, in RAS-induced senescence in vivo. We find that in mouse models, loss of Snora24 cooperates with RASG12V to promote the development of liver cancer that closely resembles human steatohepatitic hepatocellular carcinoma (HCC). From a clinical perspective, we further show that human HCCs with low SNORA24 expression display increased lipid content and are associated with poor patient survival. We next asked whether ribosomes lacking SNORA24-guided pseudouridine modifications on 18S rRNA have alterations in their biophysical properties. Single-molecule Fluorescence Resonance Energy Transfer (FRET) analyses revealed that these ribosomes exhibit perturbations in aminoacyl-transfer RNA (aa-tRNA) selection and altered pre-translocation ribosome complex dynamics. Furthermore, we find that HCC cells lacking SNORA24-guided pseudouridine modifications have increased translational miscoding and stop codon readthrough frequencies. These findings highlight a role for specific snoRNAs in safeguarding against oncogenic insult and demonstrate a functional link between H/ACA snoRNAs regulated by RAS and the biophysical properties of ribosomes in cancer

Atomic Dark Matter

We propose that dark matter is dominantly comprised of atomic bound states. We build a simple model and map the parameter space that results in the early universe formation of hydrogen-like dark atoms. We find that atomic dark matter has interesting implications for cosmology as well as direct detection: Protohalo formation can be suppressed below $M_{proto} \sim 10^3 - 10^6 M_{\odot}$ for weak scale dark matter due to Ion-Radiation interactions in the dark sector. Moreover, weak-scale dark atoms can accommodate hyperfine splittings of order 100 \kev, consistent with the inelastic dark matter interpretation of the DAMA data while naturally evading direct detection bounds.Comment: 17 pages, 3 figure

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

Discovering Dark Matter with the MUonE Experiment

The MUonE experiment aims to extract the hadronic contribution to the muon anomalous magnetic moment from a precise measurement of the muon-electron differential scattering cross section. We show that MUonE can also discover thermal relic dark matter using only its nominal experimental setup. Our search strategy is sensitive to models of dark matter in which pairs of pseudo-Dirac fermions are produced in muon-nucleus scattering in the target, and the heavier state decays semivisibly to yield dilepton pairs displaced downstream from the interaction point. This approach can probe sub-GeV thermal-relic dark matter whose cosmological abundance is governed by the same model parameters that set the MUonE signal strength. Furthermore, our results show that the downstream electron calorimeter plays a key role in rejecting backgrounds for this search, thereby providing strong motivation for the MUonE to keep this component in the final experimental design

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference