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  • Casey, Caitlin M., et al. (author)
  • Physical Characterization of an Unlensed, Dusty Star-forming Galaxy at z = 5.85
  • 2019
  • In: Astrophysical Journal. - : American Astronomical Society. - 1538-4357 .- 0004-637X. ; 887:1
  • Journal article (peer-reviewed)abstract
    • We present a physical characterization of MM J100026.36+021527.9 (a.k.a. "Mambo-9"), a dusty star-forming galaxy (DSFG) at z = 5.850 ± 0.001. This is the highest-redshift unlensed DSFG (and fourth most distant overall) found to date and is the first source identified in a new 2 mm blank-field map in the COSMOS field. Though identified in prior samples of DSFGs at 850 μm to 1.2 mm with unknown redshift, the detection at 2 mm prompted further follow-up as it indicated a much higher probability that the source was likely to sit at z > 4. Deep observations from the Atacama Large Millimeter and submillimeter Array (ALMA) presented here confirm the redshift through the secure detection of 12CO(J = 6→5) and p-H2O (21,1 → 20,2). Mambo-9 is composed of a pair of galaxies separated by 6 kpc with corresponding star formation rates of 590 M o˙ yr-1 and 220 M o˙ yr-1, total molecular hydrogen gas mass of (1.7 ± 0.4) × 1011 M o˙, dust mass of (1.3 ± 0.3) × 109 M o˙, and stellar mass of (3.2-1.5+1.0) × 109 M o˙. The total halo mass, (3.3 ± 0.8) × 1012 M o˙, is predicted to exceed 1015 M o˙ by z = 0. The system is undergoing a merger-driven starburst that will increase the stellar mass of the system tenfold in τ depl = 40-80 Myr, converting its large molecular gas reservoir (gas fraction of 96-2+1) into stars. Mambo-9 evaded firm spectroscopic identification for a decade, following a pattern that has emerged for some of the highest-redshift DSFGs found. And yet, the systematic identification of unlensed DSFGs like Mambo-9 is key to measuring the global contribution of obscured star formation to the star formation rate density at z ⪆ 4, the formation of the first massive galaxies, and the formation of interstellar dust at early times (≲1 Gyr).
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2.
  • Lee, Crystal Man Ying, et al. (author)
  • Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes.
  • 2019
  • In: BMJ open diabetes research & care. - : BMJ. - 2052-4897. ; 7:1
  • Journal article (peer-reviewed)abstract
    • There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful.We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points.Sixteen studies, with 76513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6mmol/L, 2-hour postload glucose 7.0mmol/L and HbA1c 5.6% (38 mmol/mol).In terms of identifying individuals at greatest risk of developing diabetes within 5years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.
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