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2012
2014
Temporal changes in per and polyfluoroalkyl substances and their associations with type 2 diabetes
We assessed temporal changes of PFAS and associations with T2DM over a period of 30 years in a nested case–control study with repeated measurements. Logistic regression was used to assess associations between 11 PFAS and T2DM at five time-points in 116 cases and 139 controls (3 pre- and 2 post-diagnostic time-points in cases). Mixed linear models were applied to assess if changes in PFAS were related to T2DM status. In the pre-diagnostic time-point T3 (2001), future cases had higher concentrations of PFHpA, PFNA, PFHxS and PFHpS compared to controls. In the post-diagnostic time point T5 (2015/16), PFNA and PFOS were higher in prevalent cases. PFHxS and PFHpS were positively associated with future T2DM at the pre-diagnostic time-point T3, whereas PFTrDA were inversely associated with future T2DM at T1 (1986/87) and prevalent T2DM at T4 (2007/8). Temporal changes in PFAS across the study period showed that cases experienced a greater increase in pre-diagnostic concentrations of PFHpA, PFTrDA, PFHxS and PFOSA, as well as a larger post-diagnostic decrease in PFOSA, compared to controls. This study is the first to show that temporal changes in PFAS are associated with T2DM status for certain PFAS, and associations between PFAS and T2DM vary according to sample year.
2025
1999
2017
2003
2011
2011
2017
Introduction
Per- and polyfluoroalkyl substances (PFAS) have been linked to effects on human lipid profiles, with several epidemiological studies reporting associations between specific PFAS and blood lipid concentrations. However, these associations have been inconsistent, and most studies have focused on cross-sectional analyses with limited repeated measurements.
Objective
In this study, we investigated associations between serum PFAS concentrations and major blood lipid classes over a 30-year period (1986–2016) and up to five time points. Lipids analyzed included total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG).
Methods
This study included 145 participants from The Tromsø Study, Norway, who donated plasma samples three to five times over the study period. Linear mixed-effects (LME) models assessed longitudinal associations between PFAS and lipid classes, while multiple linear regression (MLR) models were used for cross-sectional associations.
Results
LME models demonstrated positive longitudinal associations between perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), and perfluorotridecanoic acid (PFTrDA) with TC. Additionally, PFOA, PFDA, PFUnDA, PFDoDA, and PFTrDA were associated with LDL-C, and PFUnDA and summed perfluorooctane sulfonate isomers (∑PFOS) with HDL-C. Cross-sectional analyses corroborated positive associations between the six PFAS compounds and TC at least three times, but the LDL-C and HDL-C associations were not confirmed. Summed perfluorooctane sulfonamide isomers (∑PFOSA) showed a negative association with LDL-C longitudinally, but this was not confirmed cross-sectionally. No associations were observed between PFAS and TG, longitudinally or cross-sectionally.
Conclusion
Concentrations of multiple PFAS were positively associated with blood lipids in longitudinal analyses, with the most consistent associations observed between six PFCA compounds and TC. These findings highlight the need for further investigation into these complex associations.
2025
2008
2024
In contrast to previous studies that have tended to focus on the influence of the total Arctic sea-ice cover on the East Asian summer tripole rainfall pattern, the present study identifies the Barents Sea as the key region where the June sea-ice variability exerts the most significant impacts on the East Asian August tripole rainfall pattern, and explores the teleconnection mechanisms involved. The results reveal that a reduction in June sea ice excites anomalous upward air motion due to strong near-surface thermal forcing, which further triggers a meridional overturning wave-like pattern extending to midlatitudes. Anomalous downward motion therefore forms over the Caspian Sea, which in turn induces zonally oriented overturning circulation along the subtropical jet stream, exhibiting the east–west Rossby wave train known as the Silk Road pattern. It is suggested that the Bonin high, a subtropical anticyclone predominant near South Korea, shows a significant anomaly due to the eastward extension of the Silk Road pattern to East Asia. As a possible descending branch of the Hadley cell, the Bonin high anomaly ultimately triggers a meridional overturning, establishing the Pacific–Japan pattern. This in turn induces an anomalous anticyclone and cyclone pair over East Asia, and a tripole vertical convection anomaly meridionally oriented over East Asia. Consequently, a tripole rainfall anomaly pattern is observed over East Asia. Results from numerical experiments using version 5 of the Community Atmosphere Model support the interpretation of this chain of events.
2018
Teknisk løsning for nasjonalt beregningsverktøy. Dataflyt, systemdesign og krav til infrastruktur. NILU OR
Rapporten beskriver dataflyt, systemdesign og krav til infrastruktur for et system som modellerer og beregner luftkvalitet. Rapporten inneholder også beskrivelse av brukergrensesnittet i en webløsning.
2015
2008
2005
Technical specification for establishing the Monitoring Network and Calibration Laboratory in Dakar. NILU OR
2007
The comet assay (single cell gel electrophoresis) is widely used as a biomonitoring tool to assess DNA damage – strand breaks, as well as oxidised bases; it can also be adapted to measure DNA repair. It is based on the ability of breaks in the DNA to relax supercoiling, allowing DNA loops to extend from the nuclear core (nucleoid) under an electric field to form a comet-like tail. Most commonly, it is applied to white blood cells. The range of detection is between a few hundred breaks per cell and a few thousand, encompassing levels of damage that can be repaired and tolerated by human cells. Its applications include monitoring various diseases, studying the influence of nutrition on DNA stability, and investigating effects of environmental and occupational mutagens. Here we address the issue of inter-laboratory variation in comet assay results. This variation is largely due to differences in methods. Imposing a standard protocol is not practical, but users should be aware of the crucial parameters that affect performance of the assay. These include the concentration of agarose in which the cells are embedded; the duration of cell lysis, and of enzyme incubation when oxidised bases are being measured; the duration of alkaline unwinding; the duration of electrophoresis and the voltage gradient applied; and the method used to score the comets. Including reference standards in each experiment allows experimental variability to be monitored – and if variation is not extreme, results can be normalised using reference standard values. Reference standards are also essential for inter-laboratory comparison. Finally, we offer recommendations which, we believe, will limit variability and increase the usefulness of this assay in molecular epidemiology.
2019
2005
2005
Technical note: Reanalysis of Aura MLS chemical observations
This paper presents a reanalysis of the atmospheric chemical composition from the upper troposphere to the lower mesosphere from August 2004 to December 2017. This reanalysis is produced by the Belgian Assimilation System for Chemical ObsErvations (BASCOE) constrained by the chemical observations from the Microwave Limb Sounder (MLS) on board the Aura satellite. BASCOE is based on the ensemble Kalman filter (EnKF) method and includes a chemical transport model driven by the winds and temperature from the ERA-Interim meteorological reanalysis. The model resolution is 3.75∘ in longitude, 2.5∘ in latitude and 37 vertical levels from the surface to 0.1 hPa with 25 levels above 100 hPa. The outputs are provided every 6 h. This reanalysis is called BRAM2 for BASCOE Reanalysis of Aura MLS, version 2.
Vertical profiles of eight species from MLS version 4 are assimilated and are evaluated in this paper: ozone (O3), water vapour (H2O), nitrous oxide (N2O), nitric acid (HNO3), hydrogen chloride (HCl), chlorine oxide (ClO), methyl chloride (CH3Cl) and carbon monoxide (CO). They are evaluated using independent observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and N2O observations from a different MLS radiometer than the one used to deliver the standard product and ozonesondes. The evaluation is carried out in four regions of interest where only selected species are evaluated. These regions are (1) the lower-stratospheric polar vortex where O3, H2O, N2O, HNO3, HCl and ClO are evaluated; (2) the upper-stratospheric–lower-mesospheric polar vortex where H2O, N2O, HNO3 and CO are evaluated; (3) the upper troposphere–lower stratosphere (UTLS) where O3, H2O, CO and CH3Cl are evaluated; and (4) the middle stratosphere where O3, H2O, N2O, HNO3, HCl, ClO and CH3Cl are evaluated.
In general BRAM2 reproduces MLS observations within their uncertainties and agrees well with independent observations, with several limitations discussed in this paper (see the summary in Sect. 5.5). In particular, ozone is not assimilated at altitudes above (i.e. pressures lower than) 4 hPa due to a model bias that cannot be corrected by the assimilation. MLS ozone profiles display unphysical oscillations in the tropical UTLS, which are corrected by the assimilation, allowing a good agreement with ozonesondes. Moreover, in the upper troposphere, comparison of BRAM2 with MLS and independent observations suggests a positive bias in MLS O3 and a negative bias in MLS H2O. The reanalysis also reveals a drift in MLS N2O against independent observations, which highlights the potential use of BRAM2 to estimate biases between instruments. BRAM2 is publicly available and will be extended to assimilate MLS observations after 2017.
2019
2011