195 research outputs found

    Noise-Net: Determining physical properties of HII regions reflecting observational uncertainties

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    Stellar feedback, the energetic interaction between young stars and their birthplace, plays an important role in the star formation history of the universe and the evolution of the interstellar medium (ISM). Correctly interpreting the observations of star-forming regions is essential to understand stellar feedback, but it is a non-trivial task due to the complexity of the feedback processes and degeneracy in observations. In our recent paper, we introduced a conditional invertible neural network (cINN) that predicts seven physical properties of star-forming regions from the luminosity of 12 optical emission lines as a novel method to analyze degenerate observations. We demonstrated that our network, trained on synthetic star-forming region models produced by the WARPFIELD-Emission predictor (WARPFIELD-EMP), could predict physical properties accurately and precisely. In this paper, we present a new updated version of the cINN that takes into account the observational uncertainties during network training. Our new network named Noise-Net reflects the influence of the uncertainty on the parameter prediction by using both emission-line luminosity and corresponding uncertainties as the necessary input information of the network. We examine the performance of the Noise-Net as a function of the uncertainty and compare it with the previous version of the cINN, which does not learn uncertainties during the training. We confirm that the Noise-Net outperforms the previous network for the typical observational uncertainty range and maintains high accuracy even when subject to large uncertainties.Comment: 22 pages, 14 figures, Accepted for publication by MNRAS on 04. Januar

    Electronic structure of REREAuMg and REREAgMg (RERE = Eu, Gd, Yb)

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    We have investigated the electronic structure of the equiatomic EuAuMg, GdAuMg, YbAuMg and GdAgMg intermetallics using x-ray photoelectron spectroscopy. The spectra revealed that the Yb and Eu are divalent while the Gd is trivalent. The spectral weight in the vicinity of the Fermi level is dominated by the mix of Mg ss, Au/Ag spsp and RERE spdspd bands, and not by the RERE 4f4f. We also found that the Au and Ag dd bands are extraordinarily narrow, as if the noble metal atoms were impurities submerged in a low density spsp metal host. The experimental results were compared with band structure calculations, and we found good agreement provided that the spin-orbit interaction in the Au an Ag dd bands is included and correlation effects in an open 4f4f shell are accounted for using the local density approximation + Hubbard UU scheme. Nevertheless, limitations of such a mean-field scheme to explain excitation spectra are also evident.Comment: 4 pages, 3 figures, Brief Repor

    Greater Weight Gain in Treatment-naive Persons Starting Dolutegravir-based Antiretroviral Therapy

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    Background Recent studies have reported weight gain in virologically suppressed persons living with human immunodeficiency virus (PLWH) switched from older antiretroviral therapy (ART) to newer integrase strand transfer inhibitor (INSTI)ā€“based regimens. In this study, we investigated whether weight gain differs among treatment-naive PLWH starting INSTI-based regimens compared to other ART regimens. Methods Adult, treatment-naive PLWH in the Vanderbilt Comprehensive Care Clinic cohort initiating INSTI-, protease inhibitor (PI)ā€“, and nonnucleoside reverse transcriptase inhibitor (NNRTI)ā€“based ART between January 2007 and June 2016 were included. We used multivariable linear mixed-effects models to generate marginal predictions of weights over time, adjusting for baseline clinical and demographic characteristics. We used restricted cubic splines to relax linearity assumptions and bootstrapping to generate 95% confidence intervals. Results Among 1152 ART-naive PLWH, 351 initiated INSTI-based regimens (135 dolutegravir, 153 elvitegravir, and 63 raltegravir), 86% were male, and 49% were white. At ART initiation, median age was 35 years, body mass index was 25.1 kg/m2, and CD4+ T-cell count was 318 cells/Ī¼L. Virologic suppression at 18 months was similar between different ART classes. At all examined study time points, weight gain was highest among PLWH starting dolutegravir. At 18 months, PLWH on dolutegravir gained 6.0 kg, compared to 2.6 kg for NNRTIs (P < .05), and 0.5 kg for elvitegravir (P < .05). PLWH starting dolutegravir also gained more weight at 18 months compared to raltegravir (3.4 kg) and PIs (4.1 kg), though these differences were not statistically significant. Conclusions Treatment-naive PLWH starting dolutegravir-based regimens gained significantly more weight at 18 months than those starting NNRTI-based and elvitegravir-based regimens

    Failure to decrease HbA1c levels following TB treatment is associated with elevated Th1/Th17 CD4+ responses

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    Introduction: The rising global burden of metabolic disease impacts the control of endemic tuberculosis (TB) in many regions, as persons with diabetes mellitus (DM) are up to three times more likely to develop active TB than those without DM. Active TB can also promote glucose intolerance during both acute infection and over a longer term, potentially driven by aspects of the immune response. Identifying patients likely to have persistent hyperglycemia following TB treatment would enable closer monitoring and care, and an improved understanding of underlying immunometabolic dysregulation. // Methods: We measured the relationship of plasma cytokine levels, T cell phenotypes and functional responses with the change in hemoglobin A1c (HbA1c) before and after treatment of pulmonary TB in a prospective observational cohort in Durban, South Africa. Participants were stratified based on stable/increased HbA1c (n = 16) versus decreased HbA1c (n = 46) levels from treatment initiation to 12 month follow-up. // Results: CD62 P-selectin was up- (1.5-fold) and IL-10 downregulated (0.85-fold) in plasma among individuals whose HbA1c remained stable/increased during TB treatment. This was accompanied by increased pro-inflammatory TB-specific IL-17 production (Th17). In addition, Th1 responses were upregulated in this group, including TNF-Ī± production and CX3CR1 expression, with decreased IL-4 and IL-13 production. Finally, the TNF-Ī±+ IFNĪ³+ CD8+ T cells were associated with stable/increased HbA1c. These changes were all significantly different in the stable/increased HbA1c relative to the decreased HbA1c group. // Discussion: Overall, these data suggest that patients with stable/increased HbA1c had an increased pro-inflammatory state. Persistent inflammation and elevated T cell activity in individuals with unresolved dysglycemia following TB treatment may indicate failure to fully resolve infection or may promote persistent dysglycemia in these individuals, and further studies are needed to explore potential mechanisms

    Disease biomarkers in cerebrospinal fluid of patients with first-onset psychosis

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    BACKGROUND: Psychosis is a severe mental condition that is characterized by a loss of contact with reality and is typically associated with hallucinations and delusional beliefs. There are numerous psychiatric conditions that present with psychotic symptoms, most importantly schizophrenia, bipolar affective disorder, and some forms of severe depression referred to as psychotic depression. The pathological mechanisms resulting in psychotic symptoms are not understood, nor is it understood whether the various psychotic illnesses are the result of similar biochemical disturbances. The identification of biological markers (so-called biomarkers) of psychosis is a fundamental step towards a better understanding of the pathogenesis of psychosis and holds the potential for more objective testing methods. METHODS AND FINDINGS: Surface-enhanced laser desorption ionization mass spectrometry was employed to profile proteins and peptides in a total of 179 cerebrospinal fluid samples (58 schizophrenia patients, 16 patients with depression, five patients with obsessive-compulsive disorder, ten patients with Alzheimer disease, and 90 controls). Our results show a highly significant differential distribution of samples from healthy volunteers away from drug-naĆÆve patients with first-onset paranoid schizophrenia. The key alterations were the up-regulation of a 40-amino acid VGF-derived peptide, the down-regulation of transthyretin at approximately 4 kDa, and a peptide cluster at approximately 6,800-7,300 Da (which is likely to be influenced by the doubly charged ions of the transthyretin protein cluster). These schizophrenia-specific protein/peptide changes were replicated in an independent sample set. Both experiments achieved a specificity of 95% and a sensitivity of 80% or 88% in the initial study and in a subsequent validation study, respectively. CONCLUSIONS: Our results suggest that the application of modern proteomics techniques, particularly mass spectrometric approaches, holds the potential to advance the understanding of the biochemical basis of psychiatric disorders and may in turn allow for the development of diagnostics and improved therapeutics. Further studies are required to validate the clinical effectiveness and disease specificity of the identified biomarkers

    Measuring Young Stars in Space and Time -- I. The Photometric Catalog and Extinction Properties of N44

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    In order to better understand the role of high-mass stellar feedback in regulating star formation in giant molecular clouds, we carried out a Hubble Space Telescope (HST) Treasury Program "Measuring Young Stars in Space and Time" (MYSST) targeting the star-forming complex N44 in the Large Magellanic Cloud (LMC). Using the F555W and F814W broadband filters of both the ACS and WFC3/UVIS, we built a photometric catalog of 461,684 stars down to mF555Wā‰ƒ29m_\mathrm{F555W} \simeq 29 mag and mF814Wā‰ƒ28m_\mathrm{F814W} \simeq 28 mag, corresponding to the magnitude of an unreddened 1 Myr pre-main-sequence star of ā‰ˆ0.09\approx0.09 MāŠ™M_\odot at the LMC distance. In this first paper we describe the observing strategy of MYSST, the data reduction procedure, and present the photometric catalog. We identify multiple young stellar populations tracing the gaseous rim of N44's super bubble, together with various contaminants belonging to the LMC field population. We also determine the reddening properties from the slope of the elongated red clump feature by applying the machine learning algorithm RANSAC, and we select a set of Upper Main Sequence (UMS) stars as primary probes to build an extinction map, deriving a relatively modest median extinction AF555Wā‰ƒ0.77A_{\mathrm{F555W}}\simeq0.77 mag. The same procedure applied to the red clump provides AF555Wā‰ƒ0.68A_{\mathrm{F555W}}\simeq 0.68 mag.Comment: 29 pages, 15 figures, accepted for publication in A

    Measuring Young Stars in Space and Time -- II. The Pre-Main-Sequence Stellar Content of N44

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    The Hubble Space Telescope (HST) survey Measuring Young Stars in Space and Time (MYSST) entails some of the deepest photometric observations of extragalactic star formation, capturing even the lowest mass stars of the active star-forming complex N44 in the Large Magellanic Cloud. We employ the new MYSST stellar catalog to identify and characterize the content of young pre-main-sequence (PMS) stars across N44 and analyze the PMS clustering structure. To distinguish PMS stars from more evolved line of sight contaminants, a non-trivial task due to several effects that alter photometry, we utilize a machine learning classification approach. This consists of training a support vector machine (SVM) and a random forest (RF) on a carefully selected subset of the MYSST data and categorize all observed stars as PMS or non-PMS. Combining SVM and RF predictions to retrieve the most robust set of PMS sources, we find āˆ¼26,700\sim26,700 candidates with a PMS probability above 95% across N44. Employing a clustering approach based on a nearest neighbor surface density estimate, we identify 18 prominent PMS structures at 11 Ļƒ\sigma significance above the mean density with sub-clusters persisting up to and beyond 33 Ļƒ\sigma significance. The most active star-forming center, located at the western edge of N44's bubble, is a subcluster with an effective radius of āˆ¼5.6\sim 5.6 pc entailing more than 1,100 PMS candidates. Furthermore, we confirm that almost all identified clusters coincide with known H II regions and are close to or harbor massive young O stars or YSOs previously discovered by MUSE and Spitzer observations.Comment: 29 pages, 21 figures, accepted for publication in A

    CSF Metabolic and Proteomic Profiles in Patients Prodromal for Psychosis

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    BACKGROUND: The initial prodromal state of psychosis (IPS) is defined as an early disease stage prior to the onset of overt psychosis characterized by sub-threshold or more unspecific psychiatric symptoms. Little is known regarding the biochemical changes during this period. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the metabolic/proteomic profiles of cerebrospinal fluid (CSF) of first-onset drug naĆÆve paranoid schizophrenia patients (n = 54) and individuals presenting with initial prodromal symptoms (n = 24), alongside healthy volunteers (n = 70) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy and surface enhanced laser desorption ionization (SELDI) mass spectrometry, respectively. Partial least square discriminant analysis (PLS-DA) showed that 36%/29% of IPS patients displayed proteomic/metabolic profiles characteristic of first-onset, drug naĆÆve schizophrenia, i.e., changes in levels of glucose and lactate as well as changes in a VGF-derived peptide (VGF23-62) and transthyretin protein concentrations. However, only 29% (n = 7) of the investigated IPS patients (who to date have been followed up for up to three years) have so far received a diagnosis of schizophrenia. The presence of biochemical alterations in the IPS group did not correlate with the risk to develop schizophrenia. CONCLUSIONS/SIGNIFICANCE: Our results imply that schizophrenia-related biochemical disease processes can be traced in CSF of prodromal patients. However, the biochemical disturbances identified in IPS patients, at least when measured at a single time point, may not be sufficient to predict clinical outcome

    Resting-state gamma-band power alterations in schizophrenia reveal E/I-balance abnormalities across illness-stages

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    We examined alterations in E/I-balance in schizophrenia (ScZ) through measurements of resting-state gamma-band activity in participants meeting clinical high-risk (CHR) criteria (n = 88), 21 first episode (FEP) patients and 34 chronic ScZ-patients. Furthermore, MRS-data were obtained in CHR-participants and matched controls. Magnetoencephalographic (MEG) resting-state activity was examined at source level and MEG-data were correlated with neuropsychological scores and clinical symptoms. CHR-participants were characterized by increased 64ā€“90 Hz power. In contrast, FEP- and ScZ-patients showed aberrant spectral power at both low- and high gamma-band frequencies. MRS-data showed a shift in E/I-balance toward increased excitation in CHR-participants, which correlated with increased occipital gamma-band power. Finally, neuropsychological deficits and clinical symptoms in FEP and ScZ-patients were correlated with reduced gamma band-activity, while elevated psychotic symptoms in the CHR group showed the opposite relationship. The current study suggests that resting-state gamma-band power and altered Glx/GABA ratio indicate changes in E/I-balance parameters across illness stages in ScZ
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