Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.

RationaleThe monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.ObjectiveWe utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.MethodsSerum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.ResultsA total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.ConclusionA comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care

Healthcare practitioner views and experiences of patients self-monitoring blood pressure: vignette study

Background Home self-monitoring of blood pressure is widely used in primary care to assist in the diagnosis of hypertension, as well as to improve clinical outcomes and support adherence to medication. The National Institute for Health and Care Excellence (NICE) care pathways for hypertension recommend specific guidelines, although they lack detail on supporting patients to self-monitor. Aim To elicit primary care practitioners’ experiences of managing patients’ home blood pressure self-monitoring, across surgeries located in different socioeconomic areas. Design & setting A qualitative focus group study was conducted with a total of 21 primary care professionals. Method Participants were GPs and practice nurses (PNs), purposively recruited from surgeries in areas of low and high deprivation, according to the English indices of multiple deprivation. Six vignettes were developed featuring data from interviews with people who self-monitor and these were used in five focus groups. Results were thematically analysed. Results Themes derived in the thematic analysis largely reflected topics covered by the vignettes. These included: advice on purchase of a device; supporting home monitoring; mitigating patient anxiety experienced as a result of home monitoring; valuing patients’ data; and effect of socioeconomic factors. Conclusion The work provides an account of methods used by primary care practitioners in the management of home blood pressure self-monitoring, where guidance may be lacking and primary care practitioners act on their own judgement. Findings complement recent policy documentation, which recognises the need to adopt new ways of working to empower patients (for example, additional support from healthcare assistants), but lacks detail on how this should be done

The Apache Point Observatory Galactic Evolution Experiment: First Detection of High Velocity Milky Way Bar Stars

Commissioning observations with the Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, have produced radial velocities (RVs) for ~4700 K/M-giant stars in the Milky Way bulge. These high-resolution (R \sim 22,500), high-S/N (>100 per resolution element), near-infrared (1.51-1.70 um; NIR) spectra provide accurate RVs (epsilon_v~0.2 km/s) for the sample of stars in 18 Galactic bulge fields spanning -1-32 deg. This represents the largest NIR high-resolution spectroscopic sample of giant stars ever assembled in this region of the Galaxy. A cold (sigma_v~30 km/s), high-velocity peak (V_GSR \sim +200 km/s) is found to comprise a significant fraction (~10%) of stars in many of these fields. These high RVs have not been detected in previous MW surveys and are not expected for a simple, circularly rotating disk. Preliminary distance estimates rule out an origin from the background Sagittarius tidal stream or a new stream in the MW disk. Comparison to various Galactic models suggests that these high RVs are best explained by stars in orbits of the Galactic bar potential, although some observational features remain unexplained.Comment: 7 pages, 4 figures, accepted for publication in ApJ Letter

The Massive Progenitor of the Possible Type II-Linear Supernova 2009hd in Messier 66

We present observations of SN2009hd in the nearby galaxy M66. This SN is one of the closest to us in recent years but heavily obscured by dust, rendering it unusually faint in the optical, given its proximity. We find that the observed properties of SN2009hd support its classification as a possible Type II-L SN, a relatively rare subclass of CC-SNe. High-precision relative astrometry has been employed to attempt to identify a SN progenitor candidate, based on a pixel-by-pixel comparison between HST F555W and F814W images of the SN site prior to explosion and at late times. A progenitor candidate is identified in the F814W images only; this object is undetected in F555W. Significant uncertainty exists in the astrometry, such that we cannot definitively identify this object as the SN progenitor. Via insertion of artificial stars into the pre-SN HST images, we are able to constrain the progenitor's properties to those of a possible supergiant, with M(F555W)0>-7.6 mag and (V-I) 0>0.99 mag. The magnitude and color limits are consistent with a luminous RSG; however, they also allow for the possibility that the star could have been more yellow than red. From a comparison with theoretical massive-star evolutionary tracks, which include rotation and pulsationally enhanced mass loss, we can place a conservative upper limit on the initial mass for the progenitor of <20 M_sun. If the actual mass of the progenitor is near the upper range allowed by our derived mass limit, then it would be consistent with that for the identified progenitors of the SNII-L 2009kr and the high-luminosity SNII-P 2008cn. The progenitors of these three SNe may possibly bridge the gap between lower-mass RSG that explode as SNeII-P and LBV, or more extreme RSG, from which the more exotic SNeII-n may arise. Very late-time imaging of the SN2009hd site may provide us with more clues regarding the true nature of its progenitor.Comment: 19 pages, 9 figures, 3 tables, accepted for publication in Ap

Arctic Paleoceanography Cruise KH21-234 with R/V Kronprins Haakon

We set sail from Longyearbyen on 30.6.2021 to collect surface sediments, long sediment archives, water and plankton samples. The study area is located north of Svalbard, within the seasonal and permanent sea ice covered Arctic Ocean. We took stations N of Svalbard, near Nordaustlandet, Sophia Basin, Yermak Plateau and on the shelf east of Svalbard. In total, we had 52 stations. We deployed the multicorer at least once at every station and sampled the core tops already onboard. These samples will be included in the Arctic Surface Sediment DNA Database, which we will use to establish new aDNA based sea ice proxies. We recovered gravity cores from 12 stations that can be used to reconstruct the Arctic sea ice history in the Holocene, last glacial and likely also Last Interglacial. We collected ice and water and filtered these for eDNA and biomarkers, and water for tracing the isotope signal of the different water masses in the region (Atlantic Water, Polar Water).publishedVersio

Regulation of neutrophil senescence by microRNAs

Neutrophils are rapidly recruited to sites of tissue injury or infection, where they protect against invading pathogens. Neutrophil functions are limited by a process of neutrophil senescence, which renders the cells unable to respond to chemoattractants, carry out respiratory burst, or degranulate. In parallel, aged neutrophils also undergo spontaneous apoptosis, which can be delayed by factors such as GMCSF. This is then followed by their subsequent removal by phagocytic cells such as macrophages, thereby preventing unwanted inflammation and tissue damage. Neutrophils translate mRNA to make new proteins that are important in maintaining functional longevity. We therefore hypothesised that neutrophil functions and lifespan might be regulated by microRNAs expressed within human neutrophils. Total RNA from highly purified neutrophils was prepared and subjected to microarray analysis using the Agilent human miRNA microarray V3. We found human neutrophils expressed a selected repertoire of 148 microRNAs and that 6 of these were significantly upregulated after a period of 4 hours in culture, at a time when the contribution of apoptosis is negligible. A list of predicted targets for these 6 microRNAs was generated from http://mirecords.biolead.org and compared to mRNA species downregulated over time, revealing 83 genes targeted by at least 2 out of the 6 regulated microRNAs. Pathway analysis of genes containing binding sites for these microRNAs identified the following pathways: chemokine and cytokine signalling, Ras pathway, and regulation of the actin cytoskeleton. Our data suggest that microRNAs may play a role in the regulation of neutrophil senescence and further suggest that manipulation of microRNAs might represent an area of future therapeutic interest for the treatment of inflammatory disease

The Alzheimer's Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans

INTRODUCTION: We describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. METHODS: Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data. RESULTS: CSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. DISCUSSION: Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

Predictive Modeling of Hypoglycemia for Clinical Decision Support in Evaluating Outpatients with Diabetes Mellitus

Objective: Hypoglycemia occurs in 20–60% of patients with diabetes mellitus. Identifying at-risk patients can facilitate interventions to lower risk. We sought to develop a hypoglycemia prediction model. Methods: In this retrospective cohort study, urban adults prescribed a diabetes drug between 2004 and 2013 were identified. Demographic and clinical data were extracted from an electronic medical record (EMR). Laboratory tests, diagnostic codes and natural language processing (NLP) identified hypoglycemia. We compared multiple logistic regression, classification and regression trees (CART), and random forest. Models were evaluated on an independent test set or through cross-validation. Results: The 38,780 patients had mean age 57 years; 56% were female, 40% African-American and 39% uninsured. Hypoglycemia occurred in 8128 (539 identified only by NLP). In logistic regression, factors positively associated with hypoglycemia included infection, non-long-acting insulin, dementia and recent hypoglycemia. Negatively associated factors included long-acting insulin plus sulfonylurea, and age 75 or older. The models’ area under curve was similar (logistic regression, 89%; CART, 88%; random forest, 90%, with ten-fold cross-validation). Conclusions: NLP improved identification of hypoglycemia. Non-long-acting insulin was an important risk factor. Decreased risk with age may reflect treatment or diminished awareness of hypoglycemia. More complex models did not improve prediction