The quantization of the chiral Schwinger model based on the BFT-BFV formalism II

We apply an improved version of Batalin-Fradkin-Tyutin (BFT) Hamiltonian method to the a=1 chiral Schwinger Model, which is much more nontrivial than the a>1.$one. Furthermore, through the path integral quantization, we newly resolve the problem of the non-trivial$\delta$function as well as that of the unwanted Fourier parameter$\xi$ in the measure. As a result, we explicitly obtain the fully gauge invariant partition function, which includes a new type of Wess-Zumino (WZ) term irrelevant to the gauge symmetry as well as usual WZ action.Comment: 17 pages, To be published in J. Phys.

Chiral Supergravity

We study the linearized approximation of N=1 topologically massive supergravity around AdS3. Linearized gravitino fields are explicitly constructed. For appropriate boundary conditions, the conserved charges demonstrate chiral behavior, so that chiral gravity can be consistently extended to chiral supergravity.Comment: 30 page

Single-Cell Glia and Neuron Gene Expression in the Central Amygdala in Opioid Withdrawal Suggests Inflammation With Correlated Gut Dysbiosis.

Drug-seeking in opioid dependence is due in part to the severe negative emotion associated with the withdrawal syndrome. It is well-established that negative emotional states emerge from activity in the amygdala. More recently, gut microflora have been shown to contribute substantially to such emotions. We measured gene expression in single glia and neurons gathered from the amygdala using laser capture microdissection and simultaneously measured gut microflora in morphine-dependent and withdrawn rats to investigate drivers of negative emotion in opioid withdrawal. We found that neuroinflammatory genes, notabl

APAF1 is a key transcriptional target for p53 in the regulation of neuronal cell death

p53 is a transcriptional activator which has been implicated as a key regulator of neuronal cell death after acute injury. We have shown previously that p53-mediated neuronal cell death involves a Bax-dependent activation of caspase 3; however, the transcriptional targets involved in the regulation of this process have not been identified. In the present study, we demonstrate that p53 directly upregulates Apaf1 transcription as a critical step in the induction of neuronal cell death. Using DNA microarray analysis of total RNA isolated from neurons undergoing p53-induced apoptosis a 5–6-fold upregulation of Apaf1 mRNA was detected. Induction of neuronal cell death by camptothecin, a DNA-damaging agent that functions through a p53-dependent mechanism, resulted in increased Apaf1 mRNA in p53-positive, but not p53-deficient neurons. In both in vitro and in vivo neuronal cell death processes of p53-induced cell death, Apaf1 protein levels were increased. We addressed whether p53 directly regulates Apaf1 transcription via the two p53 consensus binding sites in the Apaf1 promoter. Electrophoretic mobility shift assays demonstrated p53–DNA binding activity at both p53 consensus binding sequences in extracts obtained from neurons undergoing p53-induced cell death, but not in healthy control cultures or when p53 or the p53 binding sites were inactivated by mutation. In transient transfections in a neuronal cell line with p53 and Apaf1 promoter–luciferase constructs, p53 directly activated the Apaf1 promoter via both p53 sites. The importance of Apaf1 as a p53 target gene in neuronal cell death was evaluated by examining p53-induced apoptotic pathways in primary cultures of Apaf1-deficient neurons. Neurons treated with camptothecin were significantly protected in the absence of Apaf1 relative to those derived from wild-type littermates. Together, these results demonstrate that Apaf1 is a key transcriptional target for p53 that plays a pivotal role in the regulation of apoptosis after neuronal injury

Predictive phage therapy for Escherichia coli urinary tract infections: cocktail selection for therapy based on machine learning models

This study supports the development of predictive bacteriophage (phage) therapy: the concept of phage cocktail selection to treat a bacterial infection based on machine learning models (MLM). For this purpose, MLM were trained on thousands of measured interactions between a panel of phage and sequenced bacterial isolates. The concept was applied to Escherichia coli (E. coli) associated with urinary tract infections. This is an important common infection in humans and companion animals from which multi-drug resistant (MDR) bloodstream infections can originate. The global threat of MDR infection has reinvigorated international efforts into alternatives to antibiotics including phage therapy. E. coli exhibit extensive genome-level variation due to horizontal gene transfer via phage and plasmids. Associated with this, phage selection for E. coli is difficult as individual isolates can exhibit considerable variation in phage susceptibility due to differences in factors important to phage infection including phage receptor profiles and resistance mechanisms. The activity of 31 phage were measured on 314 isolates with growth curves in artificial urine. Random Forest models were built for each phage from bacterial genome features and the more generalist phage, acting on over 20% of the bacterial population, exhibited F1 scores of >0.6 and could be used to predict phage cocktails effective against previously untested strains. The study demonstrates the potential of predictive models which integrate bacterial genomics with phage activity datasets allowing their use on data derived from direct sequencing of clinical samples to inform rapid and effective phage therapy.Significance Statement With the growing challenge of antimicrobial resistance there is an urgency for alternative treatments for common bacterial diseases including urinary tract infections (UTIs). Escherichia coli is the main causative agent of UTIs in both humans and companion animals with multidrug resistant strains such as the globally disseminated ST131 becoming more common. Bacteriophage (phage) are natural predators of bacteria and potentially an alternative therapy. However, a major barrier for phage therapy is the specificity of phage on target bacteria and therefore difficulty efficiently selecting the appropriate phage. Here, we demonstrate a genomics driven approach using machine learning prediction models combined with phage activity clustering to select phage cocktails based only on the genome sequence of the infecting bacterial strain

Apoptosis-inducing factor is involved in the regulation of caspase-independent neuronal cell death

Caspase-independent death mechanisms have been shown to execute apoptosis in many types of neuronal injury. P53 has been identified as a key regulator of neuronal cell death after acute injury such as DNA damage, ischemia, and excitotoxicity. Here, we demonstrate that p53 can induce neuronal cell death via a caspase-mediated process activated by apoptotic activating factor-1 (Apaf1) and via a delayed onset caspase-independent mechanism. In contrast to wild-type cells, Apaf1-deficient neurons exhibit delayed DNA fragmentation and only peripheral chromatin condensation. More importantly, we demonstrate that apoptosis-inducing factor (AIF) is an important factor involved in the regulation of this caspase-independent neuronal cell death. Immunofluorescence studies demonstrate that AIF is released from the mitochondria by a mechanism distinct from that of cytochrome-c in neurons undergoing p53-mediated cell death. The Bcl-2 family regulates this release of AIF and subsequent caspase-independent cell death. In addition, we show that enforced expression of AIF can induce neuronal cell death in a Bax- and caspase-independent manner. Microinjection of neutralizing antibodies against AIF significantly decreased injury-induced neuronal cell death in Apaf1-deficient neurons, indicating its importance in caspase-independent apoptosis. Taken together, our results suggest that AIF may be an important therapeutic target for the treatment of neuronal injury

Studying the [OIII]λ\lambda5007A emission-line width in a sample of ∼\sim80 local active galaxies: A surrogate for σ⋆\sigma_{\star}?

For a sample of $\sim$80 local ($0.02 \leq z \leq 0.1$) Seyfert-1 galaxies with high-quality long-slit Keck spectra and spatially-resolved stellar-velocity dispersion ($\sigma_{\star}$) measurements, we study the profile of the [OIII]$\lambda$5007A emission line to test the validity of using its width as a surrogate for $\sigma_{\star}$. Such an approach has often been used in the literature, since it is difficult to measure $\sigma_{\star}$ for type-1 active galactic nuclei (AGNs) due to the AGN continuum outshining the stellar-absorption lines. Fitting the [OIII] line with a single Gaussian or Gauss-Hermite polynomials overestimates $\sigma_{\star}$ by 50-100%. When line asymmetries from non-gravitational gas motion are excluded in a double Gaussian fit, the average ratio between the core [OIII] width ($\sigma_{\rm {[OIII],D}}$) and $\sigma_{\star}$ is $\sim$1, but with individual data points off by up to a factor of two. The resulting black-hole-mass-$\sigma_{\rm {[OIII],D}}$ relation scatters around that of quiescent galaxies and reverberation-mapped AGNs. However, a direct comparison between $\sigma_{\star}$ and $\sigma_{\rm {[OIII],D}}$ shows no close correlation, only that both quantities have the same range, average and standard deviation, probably because they feel the same gravitational potential. The large scatter is likely due to the fact that line profiles are a luminosity-weighted average, dependent on the light distribution and underlying kinematic field. Within the range probed by our sample (80-260 km s$^{-1}$), our results strongly caution against the use of [OIII] width as a surrogate for $\sigma_{\star}$ on an individual basis. Even though our sample consists of radio-quiet AGNs, FIRST radio-detected objects have, on average, a $\sim$10% larger [OIII] core width.Comment: 15 pages, 10 figures, 6 tables. Accepted for publication in the Monthly Notices of the Royal Astronomical Societ

Comprehensive analysis of promoter-proximal RNA polymerase II pausing across mammalian cell types

Background: For many genes, RNA polymerase II stably pauses before transitioning to productive elongation. Although polymerase II pausing has been shown to be a mechanism for regulating transcriptional activation, the extent to which it is involved in control of mammalian gene expression and its relationship to chromatin structure remain poorly understood. Results: Here, we analyze 85 RNA polymerase II chromatin immunoprecipitation (ChIP)-sequencing experiments from 35 different murine and human samples, as well as related genome-wide datasets, to gain new insights into the relationship between polymerase II pausing and gene regulation. Across cell and tissue types, paused genes (pausing index > 2) comprise approximately 60 % of expressed genes and are repeatedly associated with specific biological functions. Paused genes also have lower cell-to-cell expression variability. Increased pausing has a non-linear effect on gene expression levels, with moderately paused genes being expressed more highly than other paused genes. The highest gene expression levels are often achieved through a novel pause-release mechanism driven by high polymerase II initiation. In three datasets examining the impact of extracellular signals, genes responsive to stimulus have slightly lower pausing index on average than non-responsive genes, and rapid gene activation is linked to conditional pause-release. Both chromatin structure and local sequence composition near the transcription start site influence pausing, with divergent features between mammals and Drosophila. Most notably, in mammals pausing is positively correlated with histone H2A.Z occupancy at promoters. Conclusions: Our results provide new insights into the contribution of RNA polymerase II pausing in mammalian gene regulation and chromatin structure. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-0984-2) contains supplementary material, which is available to authorized users