Revealing the Population of Isolated, Massive Stars in the Central Molecular Zone

We report on the current census of isolated massive stars in the Galactic center region, including recently discovered objects. The latest discoveries were selected for their hard X-ray counterparts, detected with the Chandra X-ray Observatory; or for their Paschen-α emission-line excess, detected in narrowband images with HST/NICMOS. The confirmed stars span a wide range of massive star evolutionary stages: OIa, Of, Ofpe, LBV, WNh, WN, WNE, WC, and WCd. We suspect that the majority of the hard X-ray-emitting, massive stars we have identified are colliding-wind binaries, although some may be HMXBs. Most of the confirmed massive stars have no obvious association with the known, young stellar clusters, but some may have escaped from them. Extrapolation of their numbers suggests the existence of a massive star population, comparable in size to that contained within the clusters collectively, which could account for the integrated far-IR luminosity emerging from the central half-kiloparsec. This additional massive-star population may have been supplemented by the tidal disruption of stellar clusters, or suggests an alternate mode of isolated massive star formation operating in the Galactic center region. Future experiments will constrain their kinematics, binary characteristics, and mode of formation

Differentiating dark energy and modified gravity with galaxy redshift surveys

The observed cosmic acceleration today could be due to an unknown energy component (dark energy), or a modification to general relativity (modified gravity). If dark energy models and modified gravity models are required to predict the same cosmic expansion history H(z), they will predict different growth rate for cosmic large scale structure, f_g(z)=d\ln \delta/d\ln a (\delta=(\rho_m-\bar{\rho_m})/\bar{\rho_m}), a is the cosmic scale factor). If gravity is not modified, the measured H(z) leads to a unique prediction for f_g(z), f_g^H(z). Comparing f_g^H(z) with the measured f_g(z) provides a transparent and straightforward test of gravity. We show that a simple \chi^2 test provides a general figure-of-merit for our ability to distinguish between dark energy and modified gravity given the measured H(z) and f_g(z). We study a magnitude-limited NIR galaxy redshift survey covering >10,000 (deg)^2 and the redshift range of 0.5<z<2. The resultant data can be divided into 7 redshift bins, and yield the measurement of H(z) to the accuracy of 1-2% via baryon acoustic oscillation measurements, and f_g(z) to the accuracy of a few percent via the measurement of redshift space distortions and the bias factor which describes how light traces mass. We find that if the H(z) data are fit by both a DGP gravity model and an equivalent dark energy model that predict the same expansion history, a survey area of 11,931 (deg)^2 is required to rule out the DGP gravity model at the 99.99% confidence level. It is feasible for such a galaxy redshift survey to be carried out by the next generation space missions from NASA and ESA, and it will revolutionize our understanding of the universe by differentiating between dark energy and modified gravity.Comment: 6 pages, 2 color figures. Expanded version accepted by JCA

Economic Stress of International Students: What Counselors Should Know

College students encounter high levels of stress due to intensive demands from developmental and academic tasks. In addition to the stress induced by developmental and academic tasks, economic stress adds substantial distress to college students. Economic contraction is known to bring up mental health concerns in society. Financial stress and diminished optimism are affected by distressful economic conditions. This study examined the different perceptions of economic stress between American students and international students of one English for Speakers of Other Language (ESOL) program. International students in this study sustained equally high economic stress but were more sensitive to the economic downturn. The results provide an opportunity to inform counselors how to better work with international students regarding their economic stress

Circulating miR-15b and miR-130b in serum as potential markers for detecting hepatocellular carcinoma: a retrospective cohort study

Objective: Serum α-fetoprotein (AFP) is the most commonly used biomarker for screening hepatocellular carcinoma (HCC) but fails to detect about half of the patients. Thus, we investigated if circulating microRNAs (miRNAs) could outperform AFP for HCC detection. Design: A retrospective cohort study. Setting: Two clinical centres in China. Participants: The exploration phase included 96 patients with HCC who received primary curative hepatectomy, and the validation phase included 29 hepatitis B carriers, 57 patients with HCC and 30 healthy controls. Main outcome measures: Expression of miRNAs was measured by real-time quantitative reverse transcription-PCR. Areas under receiver operating characteristic curves were used to determine the feasibility of using serum miRNA concentration as a diagnostic marker for defining HCC. A multivariate logistic regression analysis was used to evaluate performances of combined serum miRNAs. Results: In the exploration phase, miRNA profiling on resected tumour/adjacent non-tumour tissues identified miR-15b, miR-21, miR-130b and miR-183 highly expressed in tumours. These miRNAs were also detectable in culture supernatants of HCC cell lines and in serum samples of patients. Remarkably, these serum miRNAs were markedly reduced after surgery, indicating the tumour-derived source of these circulating miRNAs. In a cross-centre validation study, combined miR-15b and miR-130b demonstrated as a classifier for HCC detection, yielding a receiver operating characteristic curve area of 0.98 (98.2% sensitivity and 91.5% specificity). The detection sensitivity of the classifier in a subgroup of HCCs with low AFP (<20 ng/ml) was 96.7%. The classifier also identified early-stage HCC cases that could not be detected by AFP. Conclusion: The combined miR-15b and miR-130b classifier is a serum biomarker with clinical value for HCC screening.published_or_final_versio

Enantioselective Synthesis of (−)-Acetylapoaranotin

The first enantioselective total synthesis of the epipolythiodiketopiperazine (ETP) natural product (−)-acetylapoaranotin (3) is reported. The concise synthesis was enabled by an eight-step synthesis of a key cyclohexadienol-containing amino ester building block. The absolute stereochemistry of both amino ester building blocks used in the synthesis is set through catalytic asymmetric (1,3)-dipolar cycloaddition reactions. The formal syntheses of (−)-emethallicin E and (−)-haemotocin are also achieved through the preparation of a symmetric cyclohexadienol-containing diketopiperazine

Comparison of Pathway Analysis Approaches Using Lung Cancer GWAS Data Sets

Pathway analysis has been proposed as a complement to single SNP analyses in GWAS. This study compared pathway analysis methods using two lung cancer GWAS data sets based on four studies: one a combined data set from Central Europe and Toronto (CETO); the other a combined data set from Germany and MD Anderson (GRMD). We searched the literature for pathway analysis methods that were widely used, representative of other methods, and had available software for performing analysis. We selected the programs EASE, which uses a modified Fishers Exact calculation to test for pathway associations, GenGen (a version of Gene Set Enrichment Analysis (GSEA)), which uses a Kolmogorov-Smirnov-like running sum statistic as the test statistic, and SLAT, which uses a p-value combination approach. We also included a modified version of the SUMSTAT method (mSUMSTAT), which tests for association by averaging χ2 statistics from genotype association tests. There were nearly 18000 genes available for analysis, following mapping of more than 300,000 SNPs from each data set. These were mapped to 421 GO level 4 gene sets for pathway analysis. Among the methods designed to be robust to biases related to gene size and pathway SNP correlation (GenGen, mSUMSTAT and SLAT), the mSUMSTAT approach identified the most significant pathways (8 in CETO and 1 in GRMD). This included a highly plausible association for the acetylcholine receptor activity pathway in both CETO (FDR≤0.001) and GRMD (FDR = 0.009), although two strong association signals at a single gene cluster (CHRNA3-CHRNA5-CHRNB4) drive this result, complicating its interpretation. Few other replicated associations were found using any of these methods. Difficulty in replicating associations hindered our comparison, but results suggest mSUMSTAT has advantages over the other approaches, and may be a useful pathway analysis tool to use alongside other methods such as the commonly used GSEA (GenGen) approach

Searching for non-Gaussianity in the VSA data

We have tested Very Small Array (VSA) observations of three regions of sky for the presence of non-Gaussianity, using high-order cumulants, Minkowski functionals, a wavelet-based test and a Bayesian joint power spectrum/non-Gaussianity analysis. We find the data from two regions to be consistent with Gaussianity. In the third region, we obtain a 96.7% detection of non-Gaussianity using the wavelet test. We perform simulations to characterise the tests, and conclude that this is consistent with expected residual point source contamination. There is therefore no evidence that this detection is of cosmological origin. Our simulations show that the tests would be sensitive to any residual point sources above the data's source subtraction level of 20 mJy. The tests are also sensitive to cosmic string networks at an rms fluctuation level of $105 \mu K$ (i.e. equivalent to the best-fit observed value). They are not sensitive to string-induced fluctuations if an equal rms of Gaussian CDM fluctuations is added, thereby reducing the fluctuations due to the strings network to $74 \mu K$ rms . We especially highlight the usefulness of non-Gaussianity testing in eliminating systematic effects from our data.Comment: Minor corrections; accepted for publication to MNRA

QCD ghost f(T)-gravity model

Within the framework of modified teleparallel gravity, we reconstruct a f(T) model corresponding to the QCD ghost dark energy scenario. For a spatially flat FRW universe containing only the pressureless matter, we obtain the time evolution of the torsion scalar T (or the Hubble parameter). Then, we calculate the effective torsion equation of state parameter of the QCD ghost f(T)-gravity model as well as the deceleration parameter of the universe. Furthermore, we fit the model parameters by using the latest observational data including SNeIa, CMB and BAO data. We also check the viability of our model using a cosmographic analysis approach. Moreover, we investigate the validity of the generalized second law (GSL) of gravitational thermodynamics for our model. Finally, we point out the growth rate of matter density perturbation. We conclude that in QCD ghost f(T)-gravity model, the universe begins a matter dominated phase and approaches a de Sitter regime at late times, as expected. Also this model is consistent with current data, passes the cosmographic test, satisfies the GSL and fits the data of the growth factor well as the LCDM model.Comment: 19 pages, 9 figures, 2 tables. arXiv admin note: substantial text overlap with arXiv:1111.726

Non‐canonical autophagy functions of ATG16L1 in epithelial cells limit lethal infection by influenza A virus

Influenza A virus (IAV) and SARS-CoV-2 (COVID-19) cause pandemic infections where cytokine storm syndrome and lung inflammation lead to high mortality. Given the high social and economic cost of respiratory viruses, there is an urgent need to understand how the airways defend against virus infection. Here we use mice lacking the WD and linker domains of ATG16L1 to demonstrate that ATG16L1-dependent targeting of LC3 to single-membrane, non-autophagosome compartments - referred to as non-canonical autophagy - protects mice from lethal IAV infection. Mice with systemic loss of non-canonical autophagy are exquisitely sensitive to low-pathogenicity IAV where extensive viral replication throughout the lungs, coupled with cytokine amplification mediated by plasmacytoid dendritic cells, leads to fulminant pneumonia, lung inflammation and high mortality. IAV was controlled within epithelial barriers where non-canonical autophagy reduced IAV fusion with endosomes and activation of interferon signalling. Conditional mouse models and ex vivo analysis showed that protection against IAV infection of lung was independent of phagocytes and other leucocytes. This establishes non-canonical autophagy in airway epithelial cells as a novel innate defence that restricts IAV infection and lethal inflammation at respiratory surfaces