Dataset Information

Dosimetry of N?-formyllysine adducts following [¹³C²H?]-formaldehyde exposures in rats.

ABSTRACT: With formaldehyde as the major source of endogenous N?-formyllysine protein adducts, we quantified endogenous and exogenous N?-formyllysine in the nasal epithelium of rats exposed by inhalation to 0.7, 2, 5.8, and 9.1 ppm [¹³C²H?]-formaldehyde using liquid chromatography-coupled tandem mass spectrometry. Exogenous N?-formyllysine was detected in the nasal epithelium, with concentration-dependent formation in total as well as fractionated (cytoplasmic, membrane, nuclear) proteins, but was not detected in the lung, liver, or bone marrow. Endogenous adducts dominated at all exposure conditions, with a 6 h 9.1 ppm formaldehyde exposure resulting in one-third of the total load of N?-formyllysine being derived from exogenous sources. The results parallel previous studies of formaldehyde-induced DNA adducts.

SUBMITTER: Edrissi B

PROVIDER: S-EPMC3805309 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dosimetry of N⁶-formyllysine adducts following [¹³C²H₂]-formaldehyde exposures in rats.

Edrissi Bahar B Taghizadeh Koli K Moeller Benjamin C BC Kracko Dean D Doyle-Eisele Melanie M Swenberg James A JA Dedon Peter C PC

Chemical research in toxicology 20131010 10

With formaldehyde as the major source of endogenous N⁶-formyllysine protein adducts, we quantified endogenous and exogenous N⁶-formyllysine in the nasal epithelium of rats exposed by inhalation to 0.7, 2, 5.8, and 9.1 ppm [¹³C²H₂]-formaldehyde using liquid chromatography-coupled tandem mass spectrometry. Exogenous N⁶-formyllysine was detected in the nasal epithelium, with concentration-dependent formation in total as well as fractionated (cytoplasmic, membrane, nuclear) proteins, but was not det ...[more]

PMID: 24087891

Similar Datasets

Project description:BACKGROUND:Accurate radiation dose estimates are critical for determining eligibility for therapies by timely triaging of exposed individuals after large-scale radiation events. However, the universal assessment of a large population subjected to a nuclear spill incident or detonation is not feasible. Even with high-throughput dosimetry analysis, test volumes far exceed the capacities of first responders to measure radiation exposures directly, or to acquire and process samples for follow-on biodosimetry testing. AIM:To significantly reduce data acquisition and processing requirements for triaging of treatment-eligible exposures in population-scale radiation incidents. METHODS:Physical radiation plumes modelled nuclear detonation scenarios of simulated exposures at 22 US locations. Models assumed only location of the epicenter and historical, prevailing wind directions/speeds. The spatial boundaries of graduated radiation exposures were determined by targeted, multistep geostatistical analysis of small population samples. Initially, locations proximate to these sites were randomly sampled (generally 0.1% of population). Empirical Bayesian kriging established radiation dose contour levels circumscribing these sites. Densification of each plume identified critical locations for additional sampling. After repeated kriging and densification, overlapping grids between each pair of contours of successive plumes were compared based on their diagonal Bray-Curtis distances and root-mean-square deviations, which provided criteria (<10% difference) to discontinue sampling. RESULTS/CONCLUSIONS:We modeled 30 scenarios, including 22 urban/high-density and 2 rural/low-density scenarios under various weather conditions. Multiple (3-10) rounds of sampling and kriging were required for the dosimetry maps to converge, requiring between 58 and 347 samples for different scenarios. On average, 70±10% of locations where populations are expected to receive an exposure ?2Gy were identified. Under sub-optimal sampling conditions, the number of iterations and samples were increased, and accuracy was reduced. Geostatistical mapping limits the number of required dose assessments, the time required, and radiation exposure to first responders. Geostatistical analysis will expedite triaging of acute radiation exposure in population-scale nuclear events.

Project description:Transarterial radioembolization (TARE) effectively treats unresectable primary and metastatic liver tumors through intra-arterial injection of Yttrium-90 (90 Y) beta particle emitting microspheres which implant around the tumor. Current dosimetry models are highly simplistic and there is a large need for an image-based dosimetry post-TARE, which would improve treatment safety and efficacy. Current post-TARE imaging is 90 Y bremsstrahlung SPECT/CT and we study the use of these images for dosimetry. Retrospective image review of ten patients having a Philips HealthcareTM SPECT/CT following TARE SIR-Spheres® implantation. Emission series with attenuation correction were resampled to 3 mm resolution and used to create image-based dose distributions. Dose distributions and analysis were performed in MIM Software SurePlanTM utilizing SurePlanTM Local Deposition Method (LDM) and a dose convolution method (WFBH). We sought to implement a patient-specific background subtraction prior to dose calculation to make these noisy bremsstrahlung SPECT images suitable for post-TARE dosimetry. On average the percentage of mean background counts to maximum count in the image across all patients was 9.4 ± 4.9% (maximum = 7.6%, minimum = 2.3%). Absolute dose increased and profile line width decreased as background subtraction value increased. The average value of the LDM and WFBH dose methods was statistically the same. As background subtraction value increased, the DVH curves become unrealistic and distorted. Background subtraction on bremsstrahlung SPECT image has a large effect on post-TARE dosimetry. The background contour defined provides a systematic estimate to the activity background that accounts for the scanner and patient conditions at the time of the image study and is easily implemented using commercially available software. Using the mean count in the background contour as a subtraction across the entire image gave the most realistic dose distributions. This methodology is independent of microsphere and software manufacturer allowing for use with any available products or tools.

Dataset Information

Dosimetry of N?-formyllysine adducts following [¹³C²H?]-formaldehyde exposures in rats.

Publications

Dosimetry of N⁶-formyllysine adducts following [¹³C²H₂]-formaldehyde exposures in rats.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets