Jinfeng Huang1, Qi Wang2, Zhenhua Qi2, Shixiang Zhou2, Meijuan Zhou1, Zhidong Wang2. 1. Department of Radiation Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, People's Republic of China. 2. Department of Radiobiology, Beijing Key Laboratory for Radiobiology, Beijing Institute of Radiation Medicine, Beijing, People's Republic of China.
Abstract
Radiation biodosimeters are required urgently for fast and accurate evaluation of absorbed dose for irradiated individuals. Lipidomics has appeared as a credible technique for identification and quantification of lipid for researching biomarker of diseases. We performed a lipidomic profile on mice serum at time points of 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy irradiation to select radiation-responsive lipids and conducted Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis to recognize the pathways and network changes. Then, Pearson correlation analysis was performed to evaluate the feasibility of radiation-responsive lipids to estimate radiation dose. Seven radiation-responsive lipids including PC (18:2/18:2), PC (18:0/18:2), Lyso PC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were identified in which glycerophospholipid metabolism presented as the most significant pathway, and they all presented good linear correlation with the irradiated dose. This study identified 7 radiation-responsive lipids in mice serum and certificate their feasibility of dose estimation as biodosimeters.
Radiation biodosimeters are required urgently for fast and accurate evaluation of absorbed dose for irradiated individuals. Lipidomics has appeared as a credible technique for identification and quantification of lipid for researching biomarker of diseases. We performed a lipidomic profile on mice serum at time points of 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy irradiation to select radiation-responsive lipids and conducted Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis to recognize the pathways and network changes. Then, Pearson correlation analysis was performed to evaluate the feasibility of radiation-responsive lipids to estimate radiation dose. Seven radiation-responsive lipids including PC (18:2/18:2), PC (18:0/18:2), Lyso PC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were identified in which glycerophospholipid metabolism presented as the most significant pathway, and they all presented good linear correlation with the irradiated dose. This study identified 7 radiation-responsive lipids in mice serum and certificate their feasibility of dose estimation as biodosimeters.
In potential widespread radiation accidents such as nuclear and radiological events,
biodosimeters of high throughput and high accuracy are needed to fast evaluate the
absorbed dose of the wounded.[1] There are some approaches of biodosimeter including measuring the direct
radiation-induced changes such as stable-free radicals and measuring biological
responses to the radiation damage such as dysfunctional genes, proteins, and metabolites.[1-5] Nowadays, more and more efforts have been put into metabolomics (analysis of
molecules <1 kDa) as an approach to find biomarkers of diseases and body
dysfunction including radiation damage by detecting biofluids such as urine, serum,
and saliva.[6] And lipidomics is considered as a branch of metabolomics, lipid-targeted
metabolomics, which has been used to recognize biological changes in lipid level.[7]Lipids are an essential component of biological membranes and play crucial roles in
biological systems including making the cell comparatively independent of the
exterior environment by lipid bilayer structures, providing hydrophobic medium for
the functional performance and interactions of membrane proteins, and producing
second messengers by enzyme reactions.[8] On the basis of the diversity of chemical structure and the hydrophobic and
hydrophilic elements, there are 8 categories of lipids including glycerolipids,
saccharolipids, sphingolipids, glycerophospholipids (GPs), sterols, polyketides,
fatty acyls, and prenols.[9,10] Furthermore, exploring lipid biochemistry by lipidomics not only inquire into
the unique functions of lipid molecular species but also investigate potential
biomarkers of diseases. The phospholipidome of human serum ferritin (SF) acted as a
potential biomarker for the diagnosis of Parkinson disease, and the dysregulated
ethanolamine plasmalogens, particularly those with polyunsaturated fatty acids in
the circulatory system, was considered to be connected with neurodegeneration.[11] Eicosanoid oxygenation by lipoxygenase, CYP-450, and cyclooxygenase pathways
resulted in inflammation and are considerable biomarkers of tissue damage.[12] The deficient plasmalogen was the marker of increase oxidative stress and
peroxisomal disorders.[13]Several studies have investigated the relationship between lipid level in
serum/plasma and radiation. A phospholipids profiling analysis of rat plasma after
γ-irradiation exposure indicated that ionizing radiation could disorder phospholipid
metabolism, as phosphatidylethanolamine (PE) and phosphatidylserine (PS) increased remarkably.[14] With the nonhuman primate model, a significant increase was observed in the
level of polyunsaturated fatty acids at 7 days after 10 Gy irradiation, including
20:4 (arachidonic acid) and 22:6 (docosahexaenoic acid) acyl moieties.[4] The subsequent study with the same pattern found increases of PC (38:6), ePC
(40:3), and (40:5).[15] After 6.5 Gy irradiation, the rise levels of LysoPCs and reduced levels of
SMs would be considerable markers between 2 and 3 days postirradiation.[16]In the current study, we performed a lipidomic profile on mice serum at time points
of 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy irradiation to select potential
lipid biomarkers for radiation biodosimeters. Perturbations of SMs, PEs, PCs, LPEs,
and LyPs were detected overall. Partial least squares-discriminant analysis (PLS-DA)
clearly separated subject in 8 Gy groups from 0 Gy groups, which was an essential
dose for selection of radiation-responsive lipids. Seven radiation-responsive lipids
including PC (18:2/18:2), PC (18:0/18:2), Lyso PC 18:1, PC(18:0/20:4), SM
(D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were identified, then we performed
Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis to recognize the
pathways and network changes. Ultimately, Pearson correlation analysis was conducted
to evaluate the ability of the 7 lipids to estimate radiation doses as radiation
biodosimeters.
Materials and Methods
Chemicals
Standards for lipidomics included 19:0 Lyso PC, 19:0 PC, 17:0 PE, and 12:0 SM
(Avanti Polar Lipids, Inc, Alabaster, Alabama). All reagents were Optima LC/MS
grade (Fisher Scientific, Pittsburg, Pennsylvania) and all standards were of the
highest purity available.
Mouse Model, Radiation, and Serum Collection
Male C57BL/6J mice (6-8 weeks old) were purchased from and raised in the Academy
of Military Medical Sciences (Beijing, China). Mice were irradiated in 0, 2,
5.5, 7, and 8 Gy by 60Co source γ-ray at a dose rate of 101.90
cGy/min. Blood was collected from the orbital plexus at different time points
(6, 24, and 72 hours) after irradiation. Then serum was separated by
centrifugation at 3000 rpm/min for 5 minutes at 4°C and stored at −80°C. Five
mice were consisted in each group. Animal care and handling were performed in
accordance with the “Guide for the Care and Use of Laboratory Animal of AMMS in
China” and all animal experiments were approved by the Animal Care and Use
Committee of the Beijing Institute of Radiation Medicine (Beijing, China).
Sample Preparation and Analysis
Serum samples (10 μL) were extracted with cold chloroform:methanol (100 μL, 2:1)
containing internal standards, incubated for 30 minutes at 4°C, vortexed for 20
seconds, and centrifuged for 3 minutes (7800g, 4°C). The lower
organic phase was removed with a glass pipette, evaporated under N2, stored at
−20°C and reconstituted in 20 µL isopropanol:acetonitrile (1:1). Samples were
injected (2 μL) into SCIEX Triple TOF 5600 System (SCIEX, Framingham,
Massachusetts) equipped with a Waters XBridge Peptide BEH C18 (Milford,
Massachusetts) (2.1 mm × 100 mm; 3.5 μm) column with the temperature set at 40°C
and a flow rate of 0.40 mL/min. And both positive and negative electrospray
ionized lipid species were performed.
Data Processing, Statistics, and Marker Validation
PeakView workstation (version 1.2; SCIEX) was used to check lipid mass
spectrometry (MS/MS) information, and MultiQuant software (version 2.1; SCIEX)
was used to obtain lipid peak area. In this study, subsequent data analysis was
achieved based on positive electrospray ionized lipid species. Principal
component analysis (PCA) was used to observe the relationships between different
radiation dose groups. A 2-sample Student t test (2 tailed) and
PLS-DA were used to select radiation-responsive lipids (P value
< .05, variable importance in projection [VIP] values >1, representing a
1.5-fold change). Kyoto Encyclopedia of Genes and Genome enrichment analysis was
performed through MetaboAnalyst software (http://www.metaboanalyst.ca/).
Pearson’s correlation analysis was applied to assess the correlation between
lipids expression and irradiated doses and values of P < .05
were considered statistically significant. Student t tests,
hierarchical clustering analysis, PCA, PLS-DA plots, and Pearson correlation
analysis were performed using OmicShare (http://www.omicshare.com/tools).
Results
Selection of Radiation-Responsive Lipids
To obtain a full overview of lipids trend between different irradiation dose and
postirradiation time, a hierarchical clustering analysis with the normalized
abundance for a total of 42 lipids detected was performed (Supplementary Table
1). As observed in Figure
1, all PEs and 4 of 6 SMs were clustered together and the remaining
lipids were assembled in another clustering. In order to observe the trend of
lipidomic changes, PCA was used to cluster serum samples in each dose group at
each time point (Supplementary Figure 1). For the determination of lipidomic
signature, PLS-DA, a supervised method, was performed for all irradiation doses
at 6, 24, and 72 hours postirradiation, respectively. Figure 2 shows 0 and 8 Gy were separated
well no matter at 6 hours (R2Y = 0.952, Q2Y = 0.828) or at 24 hours (R2Y =
0.928, Q2Y = 0.479) and 72 hours (R2Y = 0.99, Q2Y = 0.963) postirradiation,
while 2, 5.5, and 7 Gy were not scattered well from 0 Gy (Supplementary Figure
2). Therefore, we selected radiation-responsive lipids from the results of
PLS-DA between 0 and 8 Gy, and the selection criteria of radiation-responsive
lipids were based on a P value <.05, fold change greater
than 1.5, and VIP values more than 1 (Supplementary Table 2). Consequently, 2
lipids, PC (18:2/18:2) and PC (18:0/18:2), were selected at 6 hours, 3 lipids,
LysoPC 18:1, PC (18:0/20:4), and SM (D18:0/24:1), were chosen at 24 hours, and 5
lipids, LysoPC 18:1, PC (16:0/18:1), PC (18:0/18:2), PC (18:0/20:4), and LysoPC
18:2, were elected as radiation-responsive lipids. Coincidently, PC (18:0/18:2)
represented responsive at 6 and 72 hours postirradiation, LysoPC 18:1 and PC
(18:0/20:4) were all reactive at 24 and 72 hours postirradiation. And Figure 3 shows the
dose–response relationship of the 7 radiation response lipids at 6, 24, and 72
hours after radiation.
Figure 1.
Heatmap generated by hierarchical clustering analysis comparing 42 lipids
in mouse serum after exposure to 0, 2, 5.5, 7, and 8 Gy at 6, 24, and 72
hours postradiation.
Figure 2.
PLS-DA score plots of serum samples from 0 and 8 Gy groups represented by
the blue line and red line, respectively, at (A) 6, (B) 24, and (C) 72
hours postradiation. One data point stands for 1 mouse. n = 5 per group.
The corresponding R2X, R2Y, and Q2Y values are shown in (A, B, and C),
respectively. PLS-DA indicates partial least squares discriminant
analysis.
Figure 3.
Dose–response relationship of (A) PC (18:2/18:2) and PC (18:0/18:2) at 6
hours after radiation; (B) SM (D18:0/24:1), PC (18:0/20:4), and LysoPC
18:1 at 24 hours after radiation; (C) LysoPC 18:1, PC (16:0/18:1), PC
(18:0/18:2), LysoPC 18:2, and PC (18:0/20:4) at 72 hours after
radiation. Error bars indicate ± 1 SD for each radiation exposure group.
n = 5 per group. *P < .05 in the irradiated mice
compared with mice in the 0 Gy group.
Heatmap generated by hierarchical clustering analysis comparing 42 lipids
in mouse serum after exposure to 0, 2, 5.5, 7, and 8 Gy at 6, 24, and 72
hours postradiation.PLS-DA score plots of serum samples from 0 and 8 Gy groups represented by
the blue line and red line, respectively, at (A) 6, (B) 24, and (C) 72
hours postradiation. One data point stands for 1 mouse. n = 5 per group.
The corresponding R2X, R2Y, and Q2Y values are shown in (A, B, and C),
respectively. PLS-DA indicates partial least squares discriminant
analysis.Dose–response relationship of (A) PC (18:2/18:2) and PC (18:0/18:2) at 6
hours after radiation; (B) SM (D18:0/24:1), PC (18:0/20:4), and LysoPC
18:1 at 24 hours after radiation; (C) LysoPC 18:1, PC (16:0/18:1), PC
(18:0/18:2), LysoPC 18:2, and PC (18:0/20:4) at 72 hours after
radiation. Error bars indicate ± 1 SD for each radiation exposure group.
n = 5 per group. *P < .05 in the irradiated mice
compared with mice in the 0 Gy group.
Dose–Response Relationship of Radiation-Responsive Lipids
Two lipids significantly changed in the 8 Gy group at 6 hours postirradiation.
Their normalized abundance in the 2, 5.5, and 7 Gy group is shown in Figure 3A, and a 2-sample
Student t test (2 tailed) was performed with 0 Gy group. PC
(18:2/18:2) and PC (18:0/18:2) decreased as the dose of radiation increased. PC
(18:2/18:2) began to decrease in the 2 Gy group and significantly decreased in
the 5.5, 7, and 8 Gy group. PC (18:0/18:2) slightly decreased in the 2 and 7 Gy
group and resulted in a significant reduction at 5.5 and 8 Gy.Three lipids significantly changed in the 8 Gy group at 24 hours postirradiation.
As shown in Figure 3B,
SM (D18:0/24:1) and PC (18:0/20:4) increased while LysoPC 18:1 decreased as the
dose of radiation increased. SM (D18:0/24:1) showed an increasing trend from 5.5
Gy and significantly increased in the 8 Gy group. Similar trend was observed in
PC (18:0/20:4), which increased after 5.5 Gy irradiation and significantly
increased in the 7 and 8 Gy group. LysoPC 18:1 start to decrease in the 2 Gy
group and significantly decreased in the 7 and 8 Gy group.Five lipids significantly changed in the 8 Gy group at 72 hours postirradiation.
As shown in Figure 3C,
only PC (18:0/20:4) resulted in an increased trend, while LysoPC 18:1, PC
(16:0/18:1), PC (18:0/18:2), and LysoPC 18:2 decreased with the increase in the
dose. Firstly, LysoPC 18:1 and LysoPC 18:2 smoothly and significantly decreased
in all dose groups. Then, PC (16:0/18:1) and PC (18:0/18:2) showed a
statistically significant response from 5 to 8 Gy. Finally, PC (18:0/20:4)
significantly increased only in the 7 and 8 Gy group.
Kyoto Encyclopedia of Genes and Genome Enrichment Analysis of the
Radiation-Responsive Lipids
To recognize the pathway and network changes in which the 7 radiation-responsive
lipids are involved, KEGG enrichment analysis was performed by the MetaAnalyst
software. A total of 5 pathways were enriched, including “Glycerophospholipid
metabolism,” “Linoleic acid metabolism,” “alpha-Linolenic acid metabolism,”
“Sphingolipid metabolism,” and “Arachidonic acid metabolism,” and the top 4 were
significant (Figure 4,
Supplementary Table 3). In addition, “Glycerophospholipid metabolism” was the
most remarkable pathway, as a total of 30 compounds were in the pathway and 2
hits matched with. In the other 3 significant pathways, only 1 hit
corresponded.
Figure 4.
KEGG pathway enrichment analysis of the 7 radiation-responsive lipids.
Count: number of compounds related to the enriched KEGG pathway. The
color of the dot indicates the P value. KEGG indicates
Kyoto Encyclopedia of Genes and Genome.
KEGG pathway enrichment analysis of the 7 radiation-responsive lipids.
Count: number of compounds related to the enriched KEGG pathway. The
color of the dot indicates the P value. KEGG indicates
Kyoto Encyclopedia of Genes and Genome.
Selection of Potential Lipid Biomarkers as Radiation Biodosimeters
To select potential lipid biomarkers as radiation biodosimeters, the correlation
between lipid expression and irradiated dose at all time points was assessed by
Pearson correlation analysis. Table 1 shows all correlation
coefficients and P values of the 7 radiation-responsive lipids.
The expression of PC (18:2/18:2) showed a good linear correlation with the
irradiated dose at 6 hours after exposure. PC (18:0/18:2) was correlated with
the irradiated dose both at 6 and 72 hours postirradiation. Then, LysoPC 18:1
showed a good linear correlation with the irradiated dose both at 24 and 72
hours after exposure. PC (18:0/20:4) was responsive to the irradiation after 24
and 72 hours, but its increase was correlated with the dose only at 24 hours
postirradiation. Finally, SM (D18:0/24:1) was correlated with the irradiated
dose at 24 hours, while PC (16:0/18:1) and LysoPC 18:2 presented a good linear
correlation only at 72 hours postirradiation.
Table 1.
Correlation Between Lipid Expression and Irradiated Doses at Different
Time Points Postradiation.
Compound
6 Hours
24 Hours
72 Hours
Correlation Coefficient
P Value
Correlation Coefficient
P Value
Correlation Coefficient
P Value
PC (18:2/18:2)
−0.966
.008
PC (18:0/18:2)
−0.966
.007
−0.960
.009
Lyso PC 18:1
−0.881
.049
−0.942
.016
PC (18:0/20:4)
0.955
.011
0.853
.066
SM (D18:0/24:1)
0.927
.023
PC (16:0/18:1)
−0.984
.003
Lyso PC 18:2
−0.988
.002
Correlation Between Lipid Expression and Irradiated Doses at Different
Time Points Postradiation.
Discussion
“An event that has led to significant consequences to people, the environment or the
facility” is the definition of a nuclear and radiation accident by the International
Atomic Energy Agency. Since the first nuclear reactors were created in 1954, more
than 100 serious nuclear accidents have occurred since 2014.[17] Thus, the estimation of the radiation dose has always been placed as first in
the medical management of these accidents. Biomarkers of radiation biodosimetry
including lymphocyte depletion and analysis of chromosomal aberrations, especially
the latter one, are widely used in the assessment of the radiation-induced changes.
Nowadays, gene expression and protein level are promising biomarkers.[18] Furthermore, lipid perturbations after radiation exposure have been reported,
although specific lipids considered as biomarkers of radiation have not been
investigated much enough.[4,14-16] Therefore, a lipidomic profile to evaluate biomarkers for radiation
biodosimetry was performed in the current study. A change was detected in a total of
42 lipids in the mouse serum at 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy
radiation and were included in 5 lipid classes, such as SMs, PEs, PCs, LPEs, and
LyPs. Then, PLS-DA, a linear classification model usually used to select
discriminative features in the data and to classify the samples,[19] was performed between the 0 Gy group and each radiation dose group (2, 5.5,
7, and 8 Gy). Unsurprisingly, 8 Gy groups were the ones best separated from 0 Gy
groups at 3 time points because 8 Gy was considered as the appropriate dose for the
occurrence of radiation metabolism effect.[4] Moreover, 7 Gy groups were also separated well from 0 Gy groups at 24 and 72
hours postirradiation (Supplementary Figure 1), as 7 Gy was also high enough to be
lethal and a reaction time of more than 24 hours was sufficient to obtain metabolic
changes after exposure. Therefore, the selection criteria were defined with a
P value <.05, fold change greater than 1.5, and VIP value
more than 1 in 8 Gy groups. Consequently, 7 lipids, such as PC (18:2/18:2), PC
(18:0/18:2), Lyso PC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and LysoPC 18:2, were selected as radiation-responsive lipids for further exploration as
biomarker for radiation biodosimetry.PC is a component of biological membranes and its biosynthesis and degradation is
considered necessary for cell cycle progression and its missing synthesis is a
hallmark of cell apoptosis.[20] After 2, 4, 6, 7, or 10 Gy total body irradiation, PCs in serum of non-human
primates (NHPs) generally declined in a dose-dependent trend.[4] A significant or slight increase in PCs is observed in the serum of NHPs
exposed to 6.5 Gy γ-radiation.[16] In our study, PC (18:2/18:2), PC (18:0/18:2), and PC (16:0/18:1) decreased
and PC (18:0/20:4) increased in a dose-dependent trend. It is well known that
radiation can induce cell apoptosis. The destruction of phosphatidylcholines
metabolism has been identified during apoptosis.[21] On the other hand, p53 is an important biological regulator of DNA
damage-induced G1 arrest in cells after irradiation, and a p53 pathway would be
stimulated by aberrant biological situation of deficient PC synthesis and degradation.[22] Therefore, this suggests that PC perturbation may be due to apoptosis caused
by radiation and simultaneously playing a role in G1 arrest.LyPs are membrane-derived signaling molecules that play various roles in a wide range
of biological activities and diseases. In addition, serum LyPs level can be
considered as biomarker for numerous disorders including myeloma, ovarian, and
colorectal cancer.[23-25] Moreover, after exposure to 6.5 Gy γ-radiation, Lyso PC 18:2 and Lyso PC 18:3
slightly decrease at 6 and 24 hours postirradiation in serum of NHPs,[16] and serum Lyso PCs level is significantly higher in NHPs exposed to 10 Gy
than 0, 2, 4, 6, and 7 Gy.[4] G-protein-coupled receptors–interacting proteins are considered as playing
crucial roles in repair mechanisms of DNA damages caused by radiation.[26] Furthermore, LyPs activities are mediated by G-protein–coupled receptors.[27] This aspect could be the reason of the declined trend of Lyso PC 18:1 and
Lyso PC 18:2 by the irradiation dose in our study. SMs, converted from ceramide
response to sphingomyelin synthase in the Golgi apparatus, can be stimulated by
pro-inflammatory cytokines and oxidative stress,[28] and their change can be also the result of the radiation damage to the
organism. This could be the explanation of the increase of SM (D18: 0/24:1) after 8
Gy exposure in our work.Glycerophospholipid metabolism—a pathway is related to acute lymphoblastic leukemia,[28] and it is considered as the most significant pathway among the 7
radiation-responsive lipids. The biosynthesis of GPs depends on CDP-DAG pathway and
Kennedy pathway, and the degradation is regulated by different phospholipases
including phospholipase A1, phospholipase A2, and phospholipase B.[29] Because of its complexity and hidden aspects of the GP metabolism, the
mechanism after the occurrence of radiation should be explored more in detail by
further studies.Finally, in our purpose of finding the potential biomarkers of radiation
biodosimetry, Pearson correlation analysis was performed to evaluate the ability of
the 7 lipids to estimate radiation doses. This is the first report attempting to
apply lipids to estimate the radiation dose rather than only find out the
biomarkers. Except for PC (18:0/20:4) that was not precise enough at 72 hours, the
other lipids resulted in a satisfactory correlation coefficient, suggesting that
these 7 lipids not only were radiation-responsive but also suitable as biomarkers to
establish radiation doses within 3 days after exposure. In our subsequent study,
longer time points beyond 7 days, such as 30 days will be considered in order to
determine different biomarkers in different radiation stages. Secondly, cytokines
regulated by radiation including interleukin (IL)-1β, IL-6, tumor necrosis factor-α,
granulocyte-macrophage colony stimulating factor (GM-CSF), and granulocyte
colony-stimulating factor (G-CSF) will be detected to further to explore the
mechanism of lipid regulation after exposure.
Conclusions
In this study, a lipidomic profile was performed to select potential lipid biomarkers
for radiation biodosimetry in mice serum at 6, 24, and 72 hours postradiation with
0, 2, 5.5, 7, and 8 Gy. Seven lipids including PC (18:2/18:2), PC (18:0/18:2), LysoPC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were
detected as modified and they also resulted appropriately for the estimation of the
radiation dose. Further studies on nonhuman primates as a radiation model should be
performed to better understand the application value of the results; then the
combination with longer time points and more reactive cytokines could play a
significant role in biodosimetry.Click here for additional data file.Supplementary_Figure_1 for Lipidomic Profiling for Serum Biomarkers in Mice
Exposed to Ionizing Radiation by Jinfeng Huang, Qi Wang, Zhenhua Qi, Shixiang
Zhou, Meijuan Zhou and Zhidong Wang in Dose-ResponseClick here for additional data file.Supplementary_Figure_2 for Lipidomic Profiling for Serum Biomarkers in Mice
Exposed to Ionizing Radiation by Jinfeng Huang, Qi Wang, Zhenhua Qi, Shixiang
Zhou, Meijuan Zhou and Zhidong Wang in Dose-ResponseClick here for additional data file.supplementary_Table_1 for Lipidomic Profiling for Serum Biomarkers in Mice
Exposed to Ionizing Radiation by Jinfeng Huang, Qi Wang, Zhenhua Qi, Shixiang
Zhou, Meijuan Zhou and Zhidong Wang in Dose-ResponseClick here for additional data file.supplementary_Table_2 for Lipidomic Profiling for Serum Biomarkers in Mice
Exposed to Ionizing Radiation by Jinfeng Huang, Qi Wang, Zhenhua Qi, Shixiang
Zhou, Meijuan Zhou and Zhidong Wang in Dose-ResponseClick here for additional data file.supplementary_Table_3 for Lipidomic Profiling for Serum Biomarkers in Mice
Exposed to Ionizing Radiation by Jinfeng Huang, Qi Wang, Zhenhua Qi, Shixiang
Zhou, Meijuan Zhou and Zhidong Wang in Dose-Response
Authors: Evagelia C Laiakis; Katrin Strassburg; Ralf Bogumil; Steven Lai; Rob J Vreeken; Thomas Hankemeier; James Langridge; Robert S Plumb; Albert J Fornace; Giuseppe Astarita Journal: J Proteome Res Date: 2014-08-15 Impact factor: 4.466
Authors: Cosima D Calvano; Giovanni Ventura; Anna Maria M Sardanelli; Laura Savino; Ilario Losito; Giuseppe De Michele; Francesco Palmisano; Tommaso R I Cataldi Journal: Int J Mol Sci Date: 2019-07-07 Impact factor: 5.923
Authors: Hanne Leysen; Jaana van Gastel; Jhana O Hendrickx; Paula Santos-Otte; Bronwen Martin; Stuart Maudsley Journal: Int J Mol Sci Date: 2018-09-26 Impact factor: 5.923
Authors: Charles P Hinzman; Meth Jayatilake; Sunil Bansal; Brian L Fish; Yaoxiang Li; Yubo Zhang; Shivani Bansal; Michael Girgis; Anton Iliuk; Xiao Xu; Jose A Fernandez; John H Griffin; Elizabeth A Ballew; Keith Unger; Marjan Boerma; Meetha Medhora; Amrita K Cheema Journal: J Transl Med Date: 2022-05-10 Impact factor: 8.440