Spatially Resolved 12CO(2–1)/12CO(1–0) in the Starburst Galaxy NGC 253 : Assessing Optical Depth to Constrain the Molecular Mass Outflow Rate

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of 12CO(1–0) and 12CO(2–1) in the central 40'' (680 pc) of the nuclear starburst galaxy NGC 253, including its molecular outflow. We measure the ratio of brightness temperature for CO(2–1)/CO(1–0), r 21, in the central starburst and outflow-related features. We discuss how r 21 can be used to constrain the optical depth of the CO emission, which impacts the inferred mass of the outflow and consequently the molecular mass outflow rate. We find r 21 lesssim 1 throughout, consistent with a majority of the CO emission being optically thick in the outflow, as it is in the starburst. This suggests that the molecular outflow mass is 3–6 times larger than the lower limit reported for optically thin CO emission from warm molecular gas. The implied molecular mass outflow rate is 25–50 M ⊙ yr−1, assuming that the conversion factor for the outflowing gas is similar to our best estimates for the bulk of the starburst. This is a factor of 9–19 times larger than the star formation rate in NGC 253. We see tentative evidence for an extended, diffuse CO(2–1) component.Peer reviewe

Chemokine-like receptor 1 mRNA weakly correlates with non-alcoholic steatohepatitis score in male but not female individuals

The chemokine-like receptor 1 (CMKLR1) ligands resolvin E1 and chemerin are known to modulate inflammatory response. The progression of non-alcoholic fatty liver disease (NAFLD) to non-alcoholic steatohepatitis (NASH) is associated with inflammation. Here it was analyzed whether hepatic CMKLR1 expression is related to histological features of NASH. Therefore, CMKLR1 mRNA was quantified in liver tissue of 33 patients without NAFLD, 47 patients with borderline NASH and 38 patients with NASH. Hepatic CMKLR1 mRNA was not associated with gender and body mass index (BMI) in the controls and the whole study group. CMKLR1 expression was similar in controls and in patients with borderline NASH and NASH. In male patients weak positive correlations with inflammation, fibrosis and NASH score were identified. In females CMKLR1 was not associated with features of NAFLD. Liver CMKLR1 mRNA tended to be higher in type 2 diabetes patients of both genders and in hypercholesterolemic women. In summary, this study shows that hepatic CMKLR1 mRNA is weakly associated with features of NASH in male patients only

Super Star Clusters in the Central Starburst of NGC 4945

The nearby (3.8Mpc) galaxy NGC 4945 hosts a nuclear starburst and Seyfert type 2 active galactic nucleus (AGN). We use the Atacama Large Millimeter/submillimeter Array (ALMA) to image the 93 GHz (3.2 mm) free-free continuum and hydrogen recombination line emission (H40 alpha and H42 alpha) at 2.2 pc (0 12) resolution. Our observations reveal 27 bright, compact sources with FWHM sizes of 1.4-4.0 pc, which we identify as candidate super star clusters. Recombination line emission, tracing the ionizing photon rate of the candidate clusters, is detected in 15 sources, six of which have a significant synchrotron component to the 93 GHz continuum. Adopting an age of similar to 5Myr, the stellar masses implied by the ionizing photon luminosities are log(10) (M*/M-circle dot) approximate to 4.7-6.1. We fit a slope to the cluster mass distribution and find beta = -1.8 +/-.0.4. The gas masses associated with these clusters, derived from the dust continuum at 350 GHz, are typically an order of magnitude lower than the stellar mass. These candidate clusters appear to have already converted a large fraction of their dense natal material into stars and, given their small freefall times of similar to 0.05 Myr, are surviving an early volatile phase. We identify a pointlike source in 93 GHz continuum emission that is presumed to be the AGN. We do not detect recombination line emission from the AGN and place an upper limit on the ionizing photons that leak into the starburst region of Q(0).<.10(52) s(-1)

Spatially Resolved 12CO(2-1)/12CO(1-0) in the Starburst Galaxy NGC 253: Assessing Optical Depth to Constrain the Molecular Mass Outflow Rate

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of 12CO(1-0) and 12CO(2-1) in the central 40″ (680 pc) of the nuclear starburst galaxy NGC 253, including its molecular outflow. We measure the ratio of brightness temperature for CO(2-1)/CO(1-0), r 21, in the central starburst and outflow-related features. We discuss how r 21 can be used to constrain the optical depth of the CO emission, which impacts the inferred mass of the outflow and consequently the molecular mass outflow rate. We find r 21 ≲ 1 throughout, consistent with a majority of the CO emission being optically thick in the outflow, as it is in the starburst. This suggests that the molecular outflow mass is 3-6 times larger than the lower limit reported for optically thin CO emission from warm molecular gas. The implied molecular mass outflow rate is 25-50 M ☉ yr-1, assuming that the conversion factor for the outflowing gas is similar to our best estimates for the bulk of the starburst. This is a factor of 9-19 times larger than the star formation rate in NGC 253. We see tentative evidence for an extended, diffuse CO(2-1) component.</p

The ENIGMA sports injury working group - an international collaboration to further our understanding of sport-related brain injury

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor

The Survey of Water and Ammonia in the Galactic Center (SWAG): Molecular Cloud Evolution in the Central Molecular Zone

The Survey of Water and Ammonia in the Galactic Center (SWAG) covers the Central Molecular Zone (CMZ) of the Milky Way at frequencies between 21.2 and 25.4 GHz obtained at the Australia Telescope Compact Array at $\sim 0.9$ pc spatial and $\sim 2.0$ km s$^{-1}$ spectral resolution. In this paper, we present data on the inner $\sim 250$ pc ($1.4^\circ$) between Sgr C and Sgr B2. We focus on the hyperfine structure of the metastable ammonia inversion lines (J,K) = (1,1) - (6,6) to derive column density, kinematics, opacity and kinetic gas temperature. In the CMZ molecular clouds, we find typical line widths of $8-16$ km s$^{-1}$ and extended regions of optically thick ($\tau > 1$) emission. Two components in kinetic temperature are detected at $25-50$ K and $60-100$ K, both being significantly hotter than dust temperatures throughout the CMZ. We discuss the physical state of the CMZ gas as traced by ammonia in the context of the orbital model by Kruijssen et al. (2015) that interprets the observed distribution as a stream of molecular clouds following an open eccentric orbit. This allows us to statistically investigate the time dependencies of gas temperature, column density and line width. We find heating rates between $\sim 50$ and $\sim 100$ K Myr$^{-1}$ along the stream orbit. No strong signs of time dependence are found for column density or line width. These quantities are likely dominated by cloud-to-cloud variations. Our results qualitatively match the predictions of the current model of tidal triggering of cloud collapse, orbital kinematics and the observation of an evolutionary sequence of increasing star formation activity with orbital phase

Genomic HIV RNA Induces Innate Immune Responses through RIG-I-Dependent Sensing of Secondary-Structured RNA

Contains fulltext : 108031.pdf (publisher's version ) (Open Access)BACKGROUND: Innate immune responses have recently been appreciated to play an important role in the pathogenesis of HIV infection. Whereas inadequate innate immune sensing of HIV during acute infection may contribute to failure to control and eradicate infection, persistent inflammatory responses later during infection contribute in driving chronic immune activation and development of immunodeficiency. However, knowledge on specific HIV PAMPs and cellular PRRs responsible for inducing innate immune responses remains sparse. METHODS/PRINCIPAL FINDINGS: Here we demonstrate a major role for RIG-I and the adaptor protein MAVS in induction of innate immune responses to HIV genomic RNA. We found that secondary structured HIV-derived RNAs induced a response similar to genomic RNA. In primary human peripheral blood mononuclear cells and primary human macrophages, HIV RNA induced expression of IFN-stimulated genes, whereas only low levels of type I IFN and tumor necrosis factor alpha were produced. Furthermore, secondary structured HIV-derived RNA activated pathways to NF-kappaB, MAP kinases, and IRF3 and co-localized with peroxisomes, suggesting a role for this organelle in RIG-I-mediated innate immune sensing of HIV RNA. CONCLUSIONS/SIGNIFICANCE: These results establish RIG-I as an innate immune sensor of cytosolic HIV genomic RNA with secondary structure, thereby expanding current knowledge on HIV molecules capable of stimulating the innate immune system

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. Practitioner Points: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.</p