Relations of stellar mass between electron temperature-based metallicity of star-forming galaxies in a wide mass range

We select 947 star-forming galaxies from SDSS-DR7 with [O~{\sc iii}]$\lambda$4363 emission lines detected at a signal-to-noise {ratio }larger than 5$\sigma$. Their electron temperatures and direct oxygen abundances are {then }determined. {W}e compare the results from different methods. $t_2${, the} electron temperature in {the }low ionization region{,} estimated from $t_3${, that} in {the }high ionization region{,} {is} compared {using} three analysis relations between $t_2-t_3${. These} show obvious differences, which result in some different ionic oxygen abundances. The results of $t_3$, $t_2$, {$\rm O^{++}$/$\rm H^+$} and {$\rm O^{+}$/$\rm H^+$} derived by using methods from IRAF and literature are also compared. The ionic abundances $\rm O^{++}$/$\rm H^+$ {are} higher than $\rm O^{+}$/$\rm H^+$ for most cases. The{ different} oxygen abundances derived from $T_{\rm e}$ and the strong-line ratios show {a }clear discrepancy, which is more obvious following increasing stellar mass and strong-line ratio $R_{23}$. The sample{ of} galaxies from SDSS {with} detected [O~{\sc iii}]$\lambda$4363 have lower metallicites and higher {star formation rates}, {so} they may not be typical representatives of the whole{ population of} galaxies. Adopting data objects from {Andrews \& Martini}, {Liang et al.} and {Lee et al.} data, we derive new relations of stellar mass and metallicity for star-forming galaxies in a much wider stellar mass range: from $10^6\,M_\odot$ to $10^{11}\,M_\odot$.Comment: 16 pages, 11 figures, Accepted by Research in Astronomy and Astrophysic

Characteristic Analysis of Salmonella Phage Pu29 and Its Application in Magnetic Separation and Enrichment of Salmonella

Salmonella pullorum phage Pu29 was comprehensively analyzed for its biological and genomic characteristics. A magnetic separation and enrichment technique for Salmonella was established using the phage Pu29 as a recognition element. The phage belonged to the genus Roufvirus and had an icosahedron head and an irreducible long tail. Pu29 had a wide host spectrum with an adsorption rate of 88.67% on host cells in 15 min, a latent period of 30 min, a rise period of 180 min, and a burst size of 115.74 PFU/cell. Meanwhile, Pu29 had good heat resistance (30–60 ℃) and pH tolerance (pH 4–11). Its genome was composed of 45 715 bp (GC content 46.08%) and 81 open reading frames (ORFs), including 18 ORFs with known functions that did not carry genes encoding toxicity or resistance factors. PhagePu29-MBs were prepared as a probe by coupling the phage with carboxylated nano-magnetic beads (MBs) through amide reaction. When 25 μg of the probe was incubated with Salmonella at 37 ℃ for 20 min, the highest capture rate of Salmonella of 83.93% and the lowest captured bacterial concentration of 45 CFU/mL were obtained. Transmission electron microscopy (TEM) was used to observe that PhagePu29-MBs could specifically capture Salmonella. In spiked samples, the highest capture rate of Salmonella separated and enriched by the probe reached 92.92%. The separation and enrichment process took approximately 30 min. Therefore, this study established a fast and highly specific magnetic separation method for Salmonella based on phage Pu29, which may lay the foundation for the development of a phage-based method for the rapid separation and enrichment of foodborne pathogens in food samples

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Phylogenomic relationships between amylolytic enzymes from 85 strains of fungi.

Fungal amylolytic enzymes, including α-amylase, gluocoamylase and α-glucosidase, have been extensively exploited in diverse industrial applications such as high fructose syrup production, paper making, food processing and ethanol production. In this paper, amylolytic genes of 85 strains of fungi from the phyla Ascomycota, Basidiomycota, Chytridiomycota and Zygomycota were annotated on the genomic scale according to the classification of glycoside hydrolase (GH) from the Carbohydrate-Active enZymes (CAZy) Database. Comparisons of gene abundance in the fungi suggested that the repertoire of amylolytic genes adapted to their respective lifestyles. Amylolytic enzymes in family GH13 were divided into four distinct clades identified as heterologous α-amylases, eukaryotic α-amylases, bacterial and fungal α-amylases and GH13 α-glucosidases. Family GH15 had two branches, one for gluocoamylases, and the other with currently unknown function. GH31 α-glucosidases showed diverse branches consisting of neutral α-glucosidases, lysosomal acid α-glucosidases and a new clade phylogenetically related to the bacterial counterparts. Distribution of starch-binding domains in above fungal amylolytic enzymes was related to the enzyme source and phylogeny. Finally, likely scenarios for the evolution of amylolytic enzymes in fungi based on phylogenetic analyses were proposed. Our results provide new insights into evolutionary relationships among subgroups of fungal amylolytic enzymes and fungal evolutionary adaptation to ecological conditions

Genome Mining and Analysis of PKS Genes in <i>Eurotium cristatum</i> E1 Isolated from Fuzhuan Brick Tea

Eurotium cristatum as the dominant fungi species of Fuzhuan brick tea in China, can produce multitudinous secondary metabolites (SMs) with various bioactivities. Polyketides are a very important class of SMs found in E. cristatum and have gained extensive attention in recent years due to their remarkable diversity of structures and multiple functions. Therefore, it is necessary to explore the polyketides produced by E. cristatum at the genomic level to enhance its application value. In this paper, 12 polyketide synthase (PKS) genes were found in the whole genome of E. cristatum E1 isolated from Fuzhuan brick tea. In addition, the qRT-PCR results further demonstrated that these genes were expressed. Moreover, metabolic analysis demonstrated E. cristatum E1 can produce a variety of polyketides, including citreorosein, emodin, physcion, isoaspergin, dihydroauroglaucin, iso-dihydroauroglaucin, aspergin, flavoglaucin and auroglaucin. Furthermore, based on genomic analysis, the putative secondary metabolites clusters for emodin and flavoglaucin were proposed. The results reported here will lay a good basis for systematically mining SMs resources of E. cristatum and broadening its application fields

Supraoptimal Cytokinin Content Inhibits Rice Seminal Root Growth by Reducing Root Meristem Size and Cell Length via Increased Ethylene Content

Cytokinins (CKs), a class of phytohormone, regulate root growth in a dose-dependent manner. A certain threshold content of CK is required for rapid root growth, but supraoptimal CK content inhibits root growth, and the mechanism of this inhibition remains unclear in rice. In this study, treatments of lovastatin (an inhibitor of CK biosynthesis) and kinetin (KT; a synthetic CK) were found to inhibit rice seminal root growth in a dose-dependent manner, suggesting that endogenous CK content is optimal for rapid growth of the seminal root in rice. KT treatment strongly increased ethylene level by upregulating the transcription of ethylene biosynthesis genes. Ethylene produced in response to exogenous KT inhibited rice seminal root growth by reducing meristem size via upregulation of OsIAA3 transcription and reduced cell length by downregulating transcription of cell elongation-related genes. Moreover, the effects of KT treatment on rice seminal root growth, root meristem size and cell length were rescued by treatment with aminoethoxyvinylglycine (an inhibitor of ethylene biosynthesis), which restored ethylene level and transcription levels of OsIAA3 and cell elongation-related genes. Supraoptimal CK content increases ethylene level by promoting ethylene biosynthesis, which in turn inhibits rice seminal root growth by reducing root meristem size and cell length

Possible evolutionary scenarios for amylolytic enzyme evolution in fungi.

<p>A. Evolutionary scenarios for the GH13 enzymes. A few α-amylases identified as heterologous α-amylases might be transferred from animals and Actinomycetes. Eukaryotic, bacterial and fungal α-amylases correspond to subfamilies GH13_1 and GH13_5, respectively. GH13 α-glucosidases seem evolved from ancestral α-amylase. B. Evolutionary scenarios for the GH15 enzymes. The function of novel GH15 branch is currently unknown. C. Evolutionary scenarios for the GH31 enzymes. The enzymes in the group of temporarily named bacterial α-glucosidase are phylogenetically close to their bacterial counterparts. They may constitute a new clade of GH31 α-glucosidases in fungi.</p