J/Psi Propagation in Hadronic Matter

We study J/$\psi$ propagation in hot hadronic matter using a four-flavor chiral Lagrangian to model the dynamics and using QCD sum rules to model the finite size effects manifested in vertex interactions through form factors. Charmonium breakup due to scattering with light mesons is the primary impediment to continued propagation. Breakup rates introduce nontrivial temperature and momentum dependence into the J/$\psi$ spectral function.Comment: 6 Pages LaTeX, 3 postscript figures. Proceedings for Strangeness in Quark Matter 2003, Atlantic Beach, NC, March 12-17, 2003; minor corrections in version 2, to appear in J. Phys.

Neonatal Blood Methylation Marks Associated with Obstetric Pain Relief

The placenta, responsible for intrauterine development, can facilitate modifications within the placental epigenome in response to changes in the mother. In turn these changes have the potential to also influence the neonate1. Pain relief during delivery is widely used and frequently involves the use of nitrous oxide (N2O, commonly referred to as laughing gas), and pudendal blocks. These treatments, alone or in combination, are generally accepted as safe methods of providing pain relief to mothers. However, laughing gas and local anesthetics such as the ones used during pudendal blocks have been known to cross the placental barrier from mother to child2,3. Furthermore, although current literature about the effects of laughing gas and pudendal blocks on the epigenome, when used as maternal pain relief, is very limited, some evidence implicates effects of obstetric anesthesia on the neonatal methylome2,4,5. Thus, it is reasonable to hypothesize that obstetric pain relief administered to the mother during childbirth may affect the methylome of the child. In conclusion, we detected methylome-wide significantly associated loci for laughing gas and pudendal block treatment when studied in combination, but not for either of the treatments separately.https://scholarscompass.vcu.edu/uresposters/1421/thumbnail.jp

Post-Mortem Brain Nuclei Isolation for Single Nucleus RNA Sequencing

Abstract Post-Mortem Brain Nuclei Isolation for Single Nucleus RNA Sequencing Charles Tran, Dept. of Biology, with Dr. Karolina Aberg, VCU School of Pharmacy When tissue samples are studied in bulk without consideration for different cell proportions and types, results can be biased due to the attenuation of unique cellular expressions. In order to study cell type specific RNA expression profiles within tissue, single cell RNA sequencing (scRNA-seq) is used. For scRNA-seq studies it is critical to have intact cells. However, when investigating frozen post-mortem brain tissue, it is often challenging to isolate intact whole cells. An alternative solution is to instead isolate nuclei (which have similar, but not identical, transcriptomes to cells) and then perform single-nucleus RNA sequencing (snRNA-seq). In this study we have carefully optimized a protocol for nuclei extraction from post-mortem brain cells suitable for downstream snRNA-seq analysis. We found that adjusting our protocol to include less aggressive methods of tissue homogenization and sample-retaining lab techniques has resulted in the successful removal of cell debris and myelin alongside providing a workable sample size. In conclusion we have successfully evaluated and prepared enough high-quality nuclei for downstream scRNA-seq using our optimized protocol.https://scholarscompass.vcu.edu/uresposters/1398/thumbnail.jp

Predictions for B→KγγB \to K \gamma \gamma decays

We present a phenomenological study of the rare double radiative decay $B\to K \gamma\gamma$ in the Standard Model (SM) and beyond. Using the operator product expansion (OPE) technique, we estimate the short-distance (SD) contribution to the decay amplitude in a region of the phase space which is around the point where all decay products have energy $\sim m_b/3$ in the rest frame of the $B$-meson. At lowest order in 1/Q, where $Q$ is of order $m_b$, the $B\to K \gamma\gamma$ matrix element is then expressed in terms of the usual $B\to K$ form factors known from semileptonic rare decays. The integrated SD branching ratio in the SM in the OPE region turns out to be $\Delta {\cal{B}}(B \to K \gamma \gamma)_{SM}^{OPE} \simeq 1 \times 10^{-9}$. We work out the di-photon invariant mass distribution with and without the resonant background through $B\to K \{\eta_c,\chi_{c0}\}\to K\gamma \gamma$. In the SM, the resonance contribution is dominant in the region of phase space where the OPE is valid. The present experimental upper limit on $B_s \to \tau^+ \tau^-$ decays, which constrains the scalar/pseudoscalar Four-Fermi operators with $\tau^+ \tau^-$, leaves considerable room for new physics in the one-particle-irreducible contribution to $B\to K \gamma \gamma$ decays. In this case, we find that the SD $B\to K \gamma \gamma$ branching ratio can be enhanced by one order of magnitude with respect to its SM value and the SD contribution can lie outside of the resonance peaks.Comment: 17 pages, 4 figures; Note added on Schouten identity and 2 references added; v4: typos in Eqs (8), (44) and erroneous statement on mixing before Eq (44) fixed. All results and conclusions unchange

SR Proteins Collaborate with 7SK and Promoter-Associated Nascent RNA to Release Paused Polymerase

RNAP II is frequently paused near gene promoters in mammals, and its transition to productive elongation requires active recruitment of P-TEFb, a cyclin-dependent kinase for RNAP II and other key transcription elongation factors. A fraction of P-TEFb is sequestered in an inhibitory complex containing the 7SK noncoding RNA, but it has been unclear how P-TEFb is switched from the 7SK complex to RNAP II during transcription activation. We report that SRSF2 (also known as SC35, an SR-splicing factor) is part of the 7SK complex assembled at gene promoters and plays a direct role in transcription pause release. We demonstrate RNA-dependent, coordinated release of SRSF2 and P-TEFb from the 7SK complex and transcription activation via SRSF2 binding to promoter-associated nascent RNA. These findings reveal an unanticipated SR protein function, a role for promoter-proximal nascent RNA in gene activation, and an analogous mechanism to HIV Tat/TAR for activating cellular genes

Models of human core transcriptional regulatory circuitries

A small set of core transcription factors (TFs) dominates control of the gene expression program in embryonic stem cells and other well-studied cellular models. These core TFs collectively regulate their own gene expression, thus forming an interconnected auto-regulatory loop that can be considered the core transcriptional regulatory circuitry (CRC) for that cell type. There is limited knowledge of core TFs, and thus models of core regulatory circuitry, for most cell types. We recently discovered that genes encoding known core TFs forming CRCs are driven by super-enhancers, which provides an opportunity to systematically predict CRCs in poorly studied cell types through super-enhancer mapping. Here, we use super-enhancer maps to generate CRC models for 75 human cell and tissue types. These core circuitry models should prove valuable for further investigating cell-type–specific transcriptional regulation in healthy and diseased cells.United States. National Institutes of Health (HG002668

DHODH modulates transcriptional elongation in the neural crest and melanoma

Melanoma is a tumour of transformed melanocytes, which are originally derived from the embryonic neural crest. It is unknown to what extent the programs that regulate neural crest development interact with mutations in the BRAF oncogene, which is the most commonly mutated gene in human melanoma1. We have used zebrafish embryos to identify the initiating transcriptional events that occur on activation of human BRAF(V600E) (which encodes an amino acid substitution mutant of BRAF) in the neural crest lineage. Zebrafish embryos that are transgenic for mitfa:BRAF(V600E) and lack p53 (also known as tp53) have a gene signature that is enriched for markers of multipotent neural crest cells, and neural crest progenitors from these embryos fail to terminally differentiate. To determine whether these early transcriptional events are important for melanoma pathogenesis, we performed a chemical genetic screen to identify small-molecule suppressors of the neural crest lineage, which were then tested for their effects on melanoma. One class of compound, inhibitors of dihydroorotate dehydrogenase (DHODH), for example leflunomide, led to an almost complete abrogation of neural crest development in zebrafish and to a reduction in the self-renewal of mammalian neural crest stem cells. Leflunomide exerts these effects by inhibiting the transcriptional elongation of genes that are required for neural crest development and melanoma growth. When used alone or in combination with a specific inhibitor of the BRAF(V600E) oncogene, DHODH inhibition led to a marked decrease in melanoma growth both in vitro and in mouse xenograft studies. Taken together, these studies highlight developmental pathways in neural crest cells that have a direct bearing on melanoma formation

Recognition in Terra Incognita

It is desirable for detection and classification algorithms to generalize to unfamiliar environments, but suitable benchmarks for quantitatively studying this phenomenon are not yet available. We present a dataset designed to measure recognition generalization to novel environments. The images in our dataset are harvested from twenty camera traps deployed to monitor animal populations. Camera traps are fixed at one location, hence the background changes little across images; capture is triggered automatically, hence there is no human bias. The challenge is learning recognition in a handful of locations, and generalizing animal detection and classification to new locations where no training data is available. In our experiments state-of-the-art algorithms show excellent performance when tested at the same location where they were trained. However, we find that generalization to new locations is poor, especially for classification systems. (The dataset is available at https://beerys.github.io/CaltechCameraTraps/

Recognition in Terra Incognita

It is desirable for detection and classification algorithms to generalize to unfamiliar environments, but suitable benchmarks for quantitatively studying this phenomenon are not yet available. We present a dataset designed to measure recognition generalization to novel environments. The images in our dataset are harvested from twenty camera traps deployed to monitor animal populations. Camera traps are fixed at one location, hence the background changes little across images; capture is triggered automatically, hence there is no human bias. The challenge is learning recognition in a handful of locations, and generalizing animal detection and classification to new locations where no training data is available. In our experiments state-of-the-art algorithms show excellent performance when tested at the same location where they were trained. However, we find that generalization to new locations is poor, especially for classification systems. (The dataset is available at https://beerys.github.io/CaltechCameraTraps/