Selective chemical probe inhibitor of Stat3, identified through structure-based virtual screening, induces antitumor activity

S31-201 (NSC 74859) is a chemical probe inhibitor of Stat3 activity, which was identified from the National Cancer Institute chemical libraries by using structure-based virtual screening with a computer model of the Stat3 SH2 domain bound to its Stat3 phosphotyrosine peptide derived from the x-ray crystal structure of the Stat3 beta homodimer. S31-201 inhibits Stat3-Stat3 complex formation and Stat3 DNA-binding and transcriptional activities. Furthermore, S31-201 inhibits growth and induces apoptosis preferentially in tumor cells that contain persistently activated Stat3. Constitutively climerized and active Stat3C and Stat3 SH2 domain rescue tumor cells from S31-201-induced apoptosis. Finally, S31-201 inhibits the expression of the Stat3-regulated genes encoding cyclin D1, BcI-xL, and survivin and inhibits the growth of human breast tumors in vivo. These findings strongly suggest that the antitumor activity of S31-201 is mediated in part through inhibition of aberrant Stat3 activation and provide the proof-of-concept for the potential clinical use of Stat3 inhibitors such as S31-201 in tumors harboring aberrant Stat3

Imprints of Short Distance Physics On Inflationary Cosmology

We analyze the impact of certain modifications to short distance physics on the inflationary perturbation spectrum. For the specific case of power-law inflation, we find distinctive -- and possibly observable -- effects on the spectrum of density perturbations.Comment: Revtex 4, 3 eps figs, 4 page

CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

Background: The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. Results: CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. Conclusions: We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available (https://sourceforge.net/projects/codingquarry/), and suitable for incorporation into genome annotation pipelines

Bi-allelic variants in SPATA5L1 lead to intellectual disability, spastic-dystonic cerebral palsy, epilepsy, and hearing loss

Spermatogenesis-associated 5 like 1 (SPATA5L1) represents an orphan gene encoding a protein of unknown function. We report 28 bi-allelic variants in SPATA5L1 associated with sensorineural hearing loss in 47 individuals from 28 (26 unrelated) families. In addition, 25/47 affected individuals (53%) presented with microcephaly, developmental delay/intellectual disability, cerebral palsy, and/or epilepsy. Modeling indicated damaging effect of variants on the protein, largely via destabilizing effects on protein domains. Brain imaging revealed diminished cerebral volume, thin corpus callosum, and periventricular leukomalacia, and quantitative volumetry demonstrated significantly diminished white matter volumes in several individuals. Immunofluorescent imaging in rat hippocampal neurons revealed localization of Spata5l1 in neuronal and glial cell nuclei and more prominent expression in neurons. In the rodent inner ear, Spata5l1 is expressed in the neurosensory hair cells and inner ear supporting cells. Transcriptomic analysis performed with fibroblasts from affected individuals was able to distinguish affected from controls by principal components. Analysis of differentially expressed genes and networks suggested a role for SPATA5L1 in cell surface adhesion receptor function, intracellular focal adhesions, and DNA replication and mitosis. Collectively, our results indicate that bi-allelic SPATA5L1 variants lead to a human disease characterized by sensorineural hearing loss (SNHL) with or without a nonprogressive mixed neurodevelopmental phenotype

High Gas-Phase Methanesulfonic Acid Production in the OH-Initiated Oxidation of Dimethyl Sulfide at Low Temperatures

Dimethyl sulfide (DMS) influences climate via cloud condensation nuclei (CCN) formation resulting from its oxidation products (mainly methanesulfonic acid, MSA, and sulfuric acid, H2SO4). Despite their importance, accurate prediction of MSA and H2SO4from DMS oxidation remains challenging. With comprehensive experiments carried out in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at CERN, we show that decreasing the temperature from +25 to -10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H2SO4production is modestly affected. This leads to a gas-phase H2SO4-to-MSA ratio (H2SO4/MSA) smaller than one at low temperatures, consistent with field observations in polar regions. With an updated DMS oxidation mechanism, we find that methanesulfinic acid, CH3S(O)OH, MSIA, forms large amounts of MSA. Overall, our results reveal that MSA yields are a factor of 2-10 higher than those predicted by the widely used Master Chemical Mechanism (MCMv3.3.1), and the NOxeffect is less significant than that of temperature. Our updated mechanism explains the high MSA production rates observed in field observations, especially at low temperatures, thus, substantiating the greater importance of MSA in the natural sulfur cycle and natural CCN formation. Our mechanism will improve the interpretation of present-day and historical gas-phase H2SO4/MSA measurements

Reduced anthropogenic aerosol radiative forcing caused by biogenic new particle formation

The magnitude of aerosol radiative forcing caused by anthropogenic emissions depends on the baseline state of the atmosphere under pristine preindustrial conditions. Measurements show that particle formation in atmospheric conditions can occur solely from biogenic vapors. Here, we evaluate the potential effect of this source of particles on preindustrial cloud condensation nuclei (CCN) concentrations and aerosol-cloud radiative forcing over the industrial period. Model simulations show that the pure biogenic particle formation mechanism has a much larger relative effect on CCN concentrations in the preindustrial atmosphere than in the present atmosphere because of the lower aerosol concentrations. Consequently, preindustrial cloud albedo is increased more than under present day conditions, and therefore the cooling forcing of anthropogenic aerosols is reduced. The mechanism increases CCN concentrations by 20-100% over a large fraction of the preindustrial lower atmosphere, and the magnitude of annual global mean radiative forcing caused by changes of cloud albedo since 1750 is reduced by 0.22 W m-2 (27%) to -0.60 W m-2. Model uncertainties, relatively slow formation rates, and limited available ambient measurements make it difficult to establish the significance of a mechanism that has its dominant effect under preindustrial conditions. Our simulations predict more particle formation in the Amazon than is observed. However, the first observation of pure organic nucleation has now been reported for the free troposphere. Given the potentially significant effect on anthropogenic forcing, effort should be made to better understand such naturally driven aerosol processes

High Gas-Phase Methanesulfonic Acid Production in the OH-Initiated Oxidation of Dimethyl Sulfide at Low Temperatures

Dimethyl sulfide (DMS) influences climate via cloud condensation nuclei (CCN) formation resulting from its oxidation products (mainly methanesulfonic acid, MSA, and sulfuric acid, H$_{2}$SO$_{4}$). Despite their importance, accurate prediction of MSA and H$_{2}$SO$_{4}$ from DMS oxidation remains challenging. With comprehensive experiments carried out in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at CERN, we show that decreasing the temperature from +25 to −10 °C enhances the gas-phase MSA production by an order of magnitude from OH-initiated DMS oxidation, while H$_{2}$SO$_{4}$ production is modestly affected. This leads to a gas-phase H$_{2}$SO$_{4}$-to-MSA ratio (H$_{2}$SO$_{4}$/MSA) smaller than one at low temperatures, consistent with field observations in polar regions. With an updated DMS oxidation mechanism, we find that methanesulfinic acid, CH$_{3}$S(O)OH, MSIA, forms large amounts of MSA. Overall, our results reveal that MSA yields are a factor of 2–10 higher than those predicted by the widely used Master Chemical Mechanism (MCMv3.3.1), and the NO$_{x}$ effect is less significant than that of temperature. Our updated mechanism explains the high MSA production rates observed in field observations, especially at low temperatures, thus, substantiating the greater importance of MSA in the natural sulfur cycle and natural CCN formation. Our mechanism will improve the interpretation of present-day and historical gas-phase H$_{2}$SO$_{4}$/MSA measurements