156 research outputs found

    Early-life Farm Exposure and Ovarian Reserve in a US Cohort of Women

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    Background: In a previous exploratory study, we reported lower concentrations of the ovarian reserve biomarker anti-MĂŒllerian hormone (AMH) in adulthood with prenatal farm exposure. We now examine this association as well as childhood farm exposure using enrollment data from the Sister Study, a large US cohort of women. Methods: We collected prenatal and childhood farm exposure data by questionnaire and telephone interview. However, serum AMH data were available only for a nested subset: premenopausal women ages 35-54 subsequently diagnosed with breast cancer (n = 418 cases) and their matched controls (n = 866). To avoid potential bias from restricting analyses to only premenopausal controls, we leveraged the available cohort data. We used data from both premenopausal cases and controls as well as postmenopausal women ages 35-54 (n = 3,526) (all presumed to have undetectable AMH concentrations) and applied weights to produce a sample representative of the cohort ages 35-54 (n = 17,799). The high proportion of undetectable AMH concentrations (41%) was addressed using reverse-scale Cox regression. An adjusted hazard ratio (HR) <1.0 indicates that exposed individuals had lower AMH concentrations than unexposed individuals. Results: Prenatal exposure to maternal residence or work on a farm was associated with lower AMH concentrations (HR 0.66; 95% confidence intervals [CI] = 0.48 to 0.90). Associations between childhood farm residence exposures and AMH were null or weak, except childhood contact with pesticide-treated livestock or buildings (HR 0.69; 95% CI = 0.40 to 1.2). Conclusions: Replication of the prenatal farm exposure and lower adult AMH association raises concern that aspects of prenatal farm exposure may result in reduced adult ovarian reserve

    Standardization of natural mycolic acid antigen composition and production for use in biomarker antibody detection to diagnose active tuberculosis

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    This research article published by Elsevier B.V., 2016Mycobacterium tuberculosis, the causative agent of tuberculosis, is characterized by the abundance of species specific, antigenic cell wall lipids called mycolic acids. These wax-like molecules all share an identical, amphiphilic mycolic motif, but have different functional groups in a long hydrophobic hydrocarbon mero-chain that divide them into three main classes: alpha-, keto- and methoxy-mycolic acids. Whereas alpha-mycolic acids constitutively maintain an abundance of around 50%, the ratio of methoxy- to keto-mycolic acid types may vary depending on, among other things, the growth stage of M. tuberculosis. In human patients, antibodies to mycolic acids have shown potential as diagnostic serum biomarkers for active TB. Variations in mycolic acid composition affect the antigenic properties and can potentially compromise the precision of detection of anti-mycolic acids antibodies in patient sera to natural mixtures. We demonstrate this here with combinations of synthetic mycolic acid antigens, tested against TB patient and control sera. Combinations of methoxy- and α-mycolic acids are more antigenic than combinations of keto- and α-mycolic acids, showing the former to give a more sensitive test for TB biomarker antibodies. Natural mixtures of mycolic acids isolated from mature cultures of M. tuberculosis H37Rv give the same sensitivity as that with synthetic methoxy- and α-mycolic acids in combination, in a surface plasmon resonance inhibition biosensor test. To ensure that the antigenic activity of isolates of natural mycolic acids is reproducible, we cultured M. tuberculosis H37Rv on Middlebrook 7H10 solid agar plates to stationary growth phase in a standardized, optimal way. The proportions of mycolic acid classes in various batches of the isolates prepared from these cultures were compared to a commercially available natural mycolic acid isolate. LC-MS/MS and NMR data for quantitation of mycolic acids class compositions show that the variation in batches is small, suggesting that the quality of the results for anti-mycolic acid antibody detection in the TB patients should not be affected by different batches of natural mycolic acid antigens if prepared in a standard way

    Knowledge discovery from post-project reviews

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    This article was published in the journal, Construction Management and Economics [© Taylor & Francis (Routledge)] and the definitive version is available at: http://dx.doi.org/10.1080/01446193.2011.588953Many construction companies conduct reviews on project completion to enhance learning and to fulfil quality management procedures. Often these reports are filed away never to be seen again. This means that potentially important knowledge that may assist other project teams is not exploited. In order to ascertain whether useful knowledge can be gleaned from such reports, Knowledge Discovery from Text (KDT) and text mining (TM) are applied. Text mining avoids the need for a manual search through a vast number of reports, potentially of different formats and foci, to seek trends that may be useful for current and future projects. Pilot tests were used to analyse 48 post-project review reports. The reports were first reviewed manually to identify key themes. They were then analysed using text mining software to investigate whether text mining could identify trends and uncover useful knowledge from the reports. Pilot tests succeeded in finding common occurrences across different projects that were previously unknown. Text mining could provide a potential solution and would aid project teams to learn from previous projects. However, a lot of work is currently required before the text mining tests are conducted and the results need to be examined carefully by those with domain knowledge to validate the results obtained

    Associations between Prenatal Urinary Biomarkers of Phthalate Exposure and Preterm Birth: A Pooled Study of 16 US Cohorts

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    Importance: Phthalate exposure is widespread among pregnant women and may be a risk factor for preterm birth. Objective: To investigate the prospective association between urinary biomarkers of phthalates in pregnancy and preterm birth among individuals living in the US. Design, Setting, and Participants: Individual-level data were pooled from 16 preconception and pregnancy studies conducted in the US. Pregnant individuals who delivered between 1983 and 2018 and provided 1 or more urine samples during pregnancy were included. Exposures: Urinary phthalate metabolites were quantified as biomarkers of phthalate exposure. Concentrations of 11 phthalate metabolites were standardized for urine dilution and mean repeated measurements across pregnancy were calculated. Main Outcomes and Measures: Logistic regression models were used to examine the association between each phthalate metabolite with the odds of preterm birth, defined as less than 37 weeks of gestation at delivery (n = 539). Models pooled data using fixed effects and adjusted for maternal age, race and ethnicity, education, and prepregnancy body mass index. The association between the overall mixture of phthalate metabolites and preterm birth was also examined with logistic regression. G-computation, which requires certain assumptions to be considered causal, was used to estimate the association with hypothetical interventions to reduce the mixture concentrations on preterm birth. Results: The final analytic sample included 6045 participants (mean [SD] age, 29.1 [6.1] years). Overall, 802 individuals (13.3%) were Black, 2323 (38.4%) were Hispanic/Latina, 2576 (42.6%) were White, and 328 (5.4%) had other race and ethnicity (including American Indian/Alaskan Native, Native Hawaiian, >1 racial identity, or reported as other). Most phthalate metabolites were detected in more than 96% of participants. Higher odds of preterm birth, ranging from 12% to 16%, were observed in association with an interquartile range increase in urinary concentrations of mono-n-butyl phthalate (odds ratio [OR], 1.12 [95% CI, 0.98-1.27]), mono-isobutyl phthalate (OR, 1.16 [95% CI, 1.00-1.34]), mono(2-ethyl-5-carboxypentyl) phthalate (OR, 1.16 [95% CI, 1.00-1.34]), and mono(3-carboxypropyl) phthalate (OR, 1.14 [95% CI, 1.01-1.29]). Among approximately 90 preterm births per 1000 live births in this study population, hypothetical interventions to reduce the mixture of phthalate metabolite levels by 10%, 30%, and 50% were estimated to prevent 1.8 (95% CI, 0.5-3.1), 5.9 (95% CI, 1.7-9.9), and 11.1 (95% CI, 3.6-18.3) preterm births, respectively. Conclusions and Relevance: Results from this large US study population suggest that phthalate exposure during pregnancy may be a preventable risk factor for preterm delivery

    Bottom trawl fishing footprints on the world’s continental shelves

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    Bottom trawlers land around 19 million tons of fish and invertebrates annually, almost one-quarter of wild marine landings. The extent of bottom trawling footprint (seabed area trawled at least once in a specified region and time period) is often contested but poorly described. We quantify footprints using high-resolution satellite vessel monitoring system (VMS) and logbook data on 24 continental shelves and slopes to 1,000-m depth over at least 2 years. Trawling footprint varied markedly among regions: from 50% in some European seas. Overall, 14% of the 7.8 million-km2 study area was trawled, and 86% was not trawled. Trawling activity was aggregated; the most intensively trawled areas accounting for 90% of activity comprised 77% of footprint on average. Regional swept area ratio (SAR; ratio of total swept area trawled annually to total area of region, a metric of trawling intensity) and footprint area were related, providing an approach to estimate regional trawling footprints when high-resolution spatial data are unavailable. If SAR was ≀0.1, as in 8 of 24 regions, there was >95% probability that >90% of seabed was not trawled. If SAR was 7.9, equal to the highest SAR recorded, there was >95% probability that >70% of seabed was trawled. Footprints were smaller and SAR was ≀0.25 in regions where fishing rates consistently met international sustainability benchmarks for fish stocks, implying collateral environmental benefits from sustainable fishing

    Search for gravitational-wave transients associated with magnetar bursts in advanced LIGO and advanced Virgo data from the third observing run

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    Gravitational waves are expected to be produced from neutron star oscillations associated with magnetar giant f lares and short bursts. We present the results of a search for short-duration (milliseconds to seconds) and longduration (∌100 s) transient gravitational waves from 13 magnetar short bursts observed during Advanced LIGO, Advanced Virgo, and KAGRA’s third observation run. These 13 bursts come from two magnetars, SGR1935 +2154 and SwiftJ1818.0−1607. We also include three other electromagnetic burst events detected by FermiGBM which were identified as likely coming from one or more magnetars, but they have no association with a known magnetar. No magnetar giant flares were detected during the analysis period. We find no evidence of gravitational waves associated with any of these 16 bursts. We place upper limits on the rms of the integrated incident gravitational-wave strain that reach 3.6 × 10−ÂČÂł Hz at 100 Hz for the short-duration search and 1.1 ×10−ÂČÂČ Hz at 450 Hz for the long-duration search. For a ringdown signal at 1590 Hz targeted by the short-duration search the limit is set to 2.3 × 10−ÂČÂČ Hz. Using the estimated distance to each magnetar, we derive upper limits upper limits on the emitted gravitational-wave energy of 1.5 × 1044 erg (1.0 × 1044 erg) for SGR 1935+2154 and 9.4 × 10^43 erg (1.3 × 1044 erg) for Swift J1818.0−1607, for the short-duration (long-duration) search. Assuming isotropic emission of electromagnetic radiation of the burst ïŹ‚uences, we constrain the ratio of gravitational-wave energy to electromagnetic energy for bursts from SGR 1935+2154 with the available ïŹ‚uence information. The lowest of these ratios is 4.5 × 103

    Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

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    The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages

    A joint Fermi-GBM and Swift-BAT analysis of gravitational-wave candidates from the third gravitational-wave observing run

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    We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma rays from binary black hole mergers
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