Near infrared spectroscopy of the type IIn SN 2010jl: evidence for high velocity ejecta

The Type IIn supernova SN 2010jl was relatively nearby and luminous, allowing detailed studies of the near-infrared (NIR) emission. We present 1 - 2.4 micron spectroscopy over the age range of 36 - 565 days from the earliest detection of the supernova. On day 36, the H lines show an unresolved narrow emission component along with a symmetric broad component that can be modeled as the result of electron scattering by a thermal distribution of electrons. Over the next hundreds of days, the broad components of the H lines shift to the blue by 700 km/s, as is also observed in optical lines. The narrow lines do not show a shift, indicating they originate in a different region. He I 1.0830 and 2.0587 micron lines both show an asymmetric broad emission component, with a shoulder on the blue side that varies in prominence and velocity from -5500 km/s on day 108 to -4000 km/s on day 219. This component may be associated with the higher velocity flow indicated by X-ray observations of the supernova. The absence of the feature in the H lines suggests that this is from a He rich ejecta flow. The He I 1.0830 micron feature has a narrow P Cygni line, with absorption extending to ~100 km/s and strengthening over the first 200 days, and an emission component which weakens with time. At day 403, the continuum emission becomes dominated by a blackbody spectrum with a temperature of ~1900 K, suggestive of dust emission.Comment: 17 pages, 18 figure

Discovery of Two Rare Rigidly Rotating Magnetosphere Stars in the APOGEE Survey

The Apache Point Observatory Galactic Evolution Experiment (APOGEE)---one of the Sloan Digital Sky Survey III programs---is using near-infrared (NIR) spectra of ~100,000 red giant branch star candidates to study the structure of the Milky Way. In the course of the survey, APOGEE also acquires spectra of hot field stars to serve as telluric calibrators for the primary science targets. We report the serendipitous discovery of two rare, fast-rotating B-stars of the sigma Ori E type among those blue field stars observed during the first year of APOGEE operations. Both of the discovered stars display the spectroscopic signatures of rigidly rotating magnetospheres (RRM) common to this class of highly magnetized (B ~ 10 kGauss) stars, increasing the number of known RRM stars by ~10%. One (HD 345439) is a main-sequence B-star with unusually strong He absorption (similar to sigma Ori E), while the other (HD 23478) fits a "He-normal" B3IV classification. We combine the APOGEE discovery spectra with other optical and NIR spectra of these two stars, and of sigma Ori E itself, to show how NIR spectroscopy can be a uniquely powerful tool for discovering more of these rare objects, which may show little/no RRM signatures in their optical spectra. We discuss the potential for further discovery of sigma Ori E type stars, as well as the implications of our discoveries for the population of these objects and insights into their origin and evolution

Medical imaging of pulmonary disease in SARS-CoV-2-exposed non-human primates

Chest X-ray (CXR), computed tomography (CT), and positron emission tomography-computed tomography (PET-CT) are noninvasive imaging techniques widely used in human and veterinary pulmonary research and medicine. These techniques have recently been applied in studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-exposed non-human primates (NHPs) to complement virological assessments with meaningful translational readouts of lung disease. Our review of the literature indicates that medical imaging of SARS-CoV-2-exposed NHPs enables high-resolution qualitative and quantitative characterization of disease otherwise clinically invisible and potentially provides user-independent and unbiased evaluation of medical countermeasures (MCMs). However, we also found high variability in image acquisition and analysis protocols among studies. These findings uncover an urgent need to improve standardization and ensure direct comparability across studies

A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination.

Mycobacterium tuberculosis (Mtb), the causative infectious agent of tuberculosis (TB), kills more individuals per year than any other infectious agent. Granulomas, the hallmark of Mtb infection, are complex structures that form in lungs, composed of immune cells surrounding bacteria, infected cells, and a caseous necrotic core. While granulomas serve to physically contain and immunologically restrain bacteria growth, some granulomas are unable to control Mtb growth, leading to bacteria and infected cells leaving the granuloma and disseminating, either resulting in additional granuloma formation (local or non-local) or spread to airways or lymph nodes. Dissemination is associated with development of active TB. It is challenging to experimentally address specific mechanisms driving dissemination from TB lung granulomas. Herein, we develop a novel hybrid multi-scale computational model, MultiGran, that tracks Mtb infection within multiple granulomas in an entire lung. MultiGran follows cells, cytokines, and bacterial populations within each lung granuloma throughout the course of infection and is calibrated to multiple non-human primate (NHP) cellular, granuloma, and whole-lung datasets. We show that MultiGran can recapitulate patterns of in vivo local and non-local dissemination, predict likelihood of dissemination, and predict a crucial role for multifunctional CD8+ T cells and macrophage dynamics for preventing dissemination

SIV and Mycobacterium tuberculosis synergy within the granuloma accelerates the reactivation pattern of latent tuberculosis.

Human immunodeficiency virus infection is the most common risk factor for severe forms of tuberculosis (TB), regardless of CD4 T cell count. Using a well-characterized cynomolgus macaque model of human TB, we compared radiographic, immunologic and microbiologic characteristics of early (subclinical) reactivation of latent M. tuberculosis (Mtb) infection among animals subsequently infected with simian immunodeficiency virus (SIV) or who underwent anti-CD4 depletion by a depletion antibody. CD4 depleted animals had significantly fewer CD4 T cells within granulomas compared to Mtb/SIV co-infected and Mtb-only control animals. After 2 months of treatment, subclinical reactivation occurred at similar rates among CD4 depleted (5 of 7 animals) and SIV infected animals (4 of 8 animals). However, SIV-induced reactivation was associated with more dissemination of lung granulomas that were permissive to Mtb growth resulting in greater bacterial burden within granulomas compared to CD4 depleted reactivators. Granulomas from Mtb/SIV animals displayed a more robust T cell activation profile (IFN-α, IFN-γ, TNF, IL-17, IL-2, IL-10, IL-4 and granzyme B) compared to CD4 depleted animals and controls though these effectors did not protect against reactivation or dissemination, but instead may be related to increased viral and/or Mtb antigens. SIV replication within the granuloma was associated with reactivation, greater overall Mtb growth and reduced Mtb killing resulting in greater overall Mtb burden. These data support that SIV disrupts protective immune responses against latent Mtb infection beyond the loss of CD4 T cells, and that synergy between SIV and Mtb occurs within granulomas

Optimizing tuberculosis treatment efficacy: Comparing the standard regimen with Moxifloxacin-containing regimens.

Tuberculosis (TB) continues to be one of the deadliest infectious diseases in the world, causing ~1.5 million deaths every year. The World Health Organization initiated an End TB Strategy that aims to reduce TB-related deaths in 2035 by 95%. Recent research goals have focused on discovering more effective and more patient-friendly antibiotic drug regimens to increase patient compliance and decrease emergence of resistant TB. Moxifloxacin is one promising antibiotic that may improve the current standard regimen by shortening treatment time. Clinical trials and in vivo mouse studies suggest that regimens containing moxifloxacin have better bactericidal activity. However, testing every possible combination regimen with moxifloxacin either in vivo or clinically is not feasible due to experimental and clinical limitations. To identify better regimens more systematically, we simulated pharmacokinetics/pharmacodynamics of various regimens (with and without moxifloxacin) to evaluate efficacies, and then compared our predictions to both clinical trials and nonhuman primate studies performed herein. We used GranSim, our well-established hybrid agent-based model that simulates granuloma formation and antibiotic treatment, for this task. In addition, we established a multiple-objective optimization pipeline using GranSim to discover optimized regimens based on treatment objectives of interest, i.e., minimizing total drug dosage and lowering time needed to sterilize granulomas. Our approach can efficiently test many regimens and successfully identify optimal regimens to inform pre-clinical studies or clinical trials and ultimately accelerate the TB regimen discovery process