Original Article

Age-dependent change trends of clinicopathological parameters in F344 rats

Mi Ju Lee1,*https://orcid.org/0000-0003-0308-7087, Jeong-Hee Han1https://orcid.org/0000-0002-2105-4994, Minha Kim1https://orcid.org/0009-0001-1746-9804
Author Information & Copyright
1Inhalation Toxicity Research Center, Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Daejeon 34122, Korea
*Corresponding author: Mi Ju Lee, Inhalation Toxicity Research Center, Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Daejeon 34122, Korea, Tel: +82-42-869-8535, E-mail: mjlee@kosha.or.kr

© Research Institute of Veterinary Medicine, Chungbuk National University.

Received: Jun 18, 2024; Revised: Aug 29, 2024; Accepted: Sep 07, 2024

Abstract

Clinical pathology, including hematology and serum chemistry, is an important indicator of biological changes. Animals for inhalation studies are kept in specific chambers and require historical data for accuracy. Age-related characteristics are essential for interpreting experimental results. This study aimed to provide historical clinical pathology data and analyze age-related trends in these parameters. We collected hematological and biochemical parameters from control groups of male and female F344 rats in the 4-, 13-, 26-, and 52-week repeated inhalation toxicity tests. The number of F344 rats from collected control groups were 24, 60, 50, and 25 males and 25, 60, 50, and 25 females in the 4-, 13-, 26-, and 52-week studies, respectively. Mean comparison, correlation analysis and simple linear regression analysis was conducted to reveal age-related trends. Neutrophil count, eosinophil count, neutrophil percentage, monocyte percentage, total protein, albumin, triglyceride, total cholesterol (TCHO) showed increasing trends, whereas lymphocyte count, lymphocyte percent, platelet count, alkaline phosphatase, albumin/globulin ratio, and inorganic phosphate showed decreasing trends in both the mean comparison and regression analyses. TCHO was considered the most affected parameter by aging in both sexes based on statistical results. In this study, we presented clinicopathological data from F344 rats for inhalation toxicity studies. We confirmed aging trends in clinicopathological parameters and identified TCHO as the parameter most affected by aging in F344 rats. These results would be helpful for inhalation research using F344 rats.

Keywords: Fischer 344 rats; inhalation; age-dependent trend; pathology, clinical; statistics

INTRODUCTION

The inhalation repeated toxicity study evaluates systemic toxicity induced by repeatedly inhaled test substances using experimental animals. During the experimental period, animals are kept in specific chambers equipped for spraying test materials and performing analyses. Control group animals are also kept in chambers supplied with fresh air to maintain the same environmental conditions as the test groups. This specific closed environment could induce stress [1] and the resulting biological changes [2, 3], making it is essential to establish historical data for inhalation toxicity tests.

Clinical pathology including hematology and serum chemistry, reflects pathological or functional changes in various organs [46] and is essential for distinguishing between normal and abnormal conditions and evaluating whether it is a toxic change [7, 8]. It is a crucial parameter in several test guidelines for evaluating the toxicity of chemical substances, including test guidelines of the Organization for Economic Cooperation and Development [911]. Clinical pathology is also valuable for extrapolating the potential impact on humans.

Historical data provide a basis for understanding the biological characteristics and range of variance in animal species and strains. They help determine whether observed alterations in the toxicity assessment of chemicals, including drugs, are actual or biological changes caused by individual differences [1215]. Understanding age-related biological characteristics is also essential for interpreting and understanding experimental results.

Recent studies on historical data have focused on neoplastic lesions of 104-week-old rats [1618]. However, more studies for clinicopathological background data are required to evaluate toxicity for animals in diverse environment. To date, clinicopathological background data for inhalation studies have not been reported, and statistical approaches have been limited in age-related trend analysis. Therefore, this study aimes to obtain background clinicopathological data for F344 rats of different week-ages used in inhalation toxicity studies. In addition, we statistically analyzed age-dependent trends in the data collected to determine aging changes in clinical pathology.

MATERIALS AND METHODS

Animals

Six-week old male and female F344/NSlc rats from a specific pathogen-free colony were purchased from Japan SLC (Hamamatsu, Japan) via Joongang Experimental Animal (Seoul, Korea) for use as the control group in 4-, 13-, 26-, and 52-week repeated inhalation toxicity studies. The rats were used after 1 week of quarantine and acclimatization. They rats were housed in a room maintained at 22°C ± 3°C with 50% ± 20% relative humidity, artificial lighting from 08:00 to 20:00 hr, and 12–15 air changes/hr. The rats were housed individually in wire-bottomed stainless-steel mesh cages placed in exposure chambers and provided sterilized tap water and commercial rodent chow (Teklad Certified Irradiated Global 18% Protein Rodent Diet; Envigo, Indianapolis, IN, USA) ad libitum. Rats were exposed to clean dry air for 6 hr/d, 5 d per week for 4, 13, 26, or 52 weeks in whole-body chambers. The study protocols were approved by the Institutional Animal Care and Use Committee (IACUC) of the Inhalation Toxicity Research Center (IACUC approval numbers: IACUC-1911, -1913, -1915, -1916, -1917, -1918, -1812, -1813, -1815, -1817, -1818, -1612, -1601).

Euthanasia and sample collection

All rats were fasted overnight before blood sample collection and anesthesia with isoflurane preceded euthanasia. Euthanasia was peformed by cutting the abdominal aorta and caudal vena cava after blood collection. Blood samples (7–8 mL) were collected from the abdominal aorta. Approximately 3 mL of each blood sample was placed in EDTA-containing vacutainers for hematological measurements. Subsequently, approximately 0.5–1 mL of blood mixed with 3.2% sodium citrate was centrifuged at 3,000 rpm for 10 min at 4°C to measure prothrombin time (PT) and activated partial thromboplastin time (APTT). Blood samples for blood chemistry analysis were also centrifuged at 3,000 rpm for 10 min at 4°C to obtain serum within 1 hr of sample collection.

Hematology

Measured hematology parameters included erythrocytes s(red blood cell, RBC), hemoglobin (HGB) concentration, hematocrit (HCT), mean cell volume (MCV), mean cell hemoglobin (MCH), mean cell hemoglobin concentration (MCHC), platelet (PLT), leucocytes (white blood cell, WBC), differential WBC count (neutrophils [NEUA], lymphocytes [LYMA], monocytes [MONA], eosinophils [EOSA], and basophils [BASA]), and each cell-to-WBC ratio expressed as neutrophil percentage (NEU%), lymphocyte percentage (LYM%), monocyte percentage (MON%), eosinophil percentage (EOS%), basophil percentage (BAS%), respectively. Reticulocyte count (RETA) and the reticulocyte-to-RBC ratio, expressed as the reticulocyte percentage (RET%), were also measured, along with PT and APTT. Hematological parameters, excluding PT and APTT, were analyzed using ADVIA 2120i (Siemens, Munich, Germany), whereas PT and APTT were analyzed using ACL ELITE systems (Instrumentation Laboratory, Bedford, MA, USA).

Biochemistry

The biochemical parameters measured included alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), blood urea nitrogen (BUN), creatinine (CREA), total bilirubin (TBIL), total protein (TP), albumin (ALB), albumin/globulin (A/G) ratio, total cholesterol (TCHO), triglyceride (TG), glucose (GLU), potassium (K), calcium (Ca), chloride (Cl), inorganic phosphorus (IP), and sodium (Na). These biochemical parameters were analyzed using a TBA-120FR automated clinical analyzer (Toshiba, Tokyo, Japan).

Data analysis

Data are presented as means ± S.D. Statistical analyse were performed using the SPSS Statistics version 28 software (IBM, Armonk, NY, USA). Differences between data were statistically evaluated. The homogeneity of variance was determined using Levene’s test. Homogeneous and heterogeneous data were compared using one-way analysis of variance (ANOVA) and non-parametric Kruskal–Wallis test, respectively. If statistical significance (p<0.05) was observed, Dunnett’s test (for ANOVA) or Dunn’s test (for Kruskal–Wallis) was used to compare 4-week data with those of 13-, 26-, and 52-week. In addition, correlation and simple linear regression analyses were performed to determine the relationship between age and each parameter. A simple linear regression analysis was performed on parameters that showed a significant relationship with the experimental week. Regression analysis was performed on the parameters that significant in the correlation analysis.

RESULTS

Change trends of hematological parameters at different ages in male rats

Statistically significant differences were observed in NEUA, EOSA, LYM%, NEU%, MON%, and PLT at 13, 26, and 52 weeks; HCT and MCHC at 26 weeks; LYMA and BAS% at 26 and 52 weeks; EOS% at 13 and 52 weeks; RBC, MCV, MCH, and WBC at 13 and 26 weeks; MONA and PT at 26 weeks; and RETA, RET%, and BASA at 13 weeks compared those at 4 weeks (Table 1). Their p-values are presented in Table 1. The correlation coefficients between experimental week and MCH (p<0.01), WBC (p<0.05), LYMA (p<0.01), NEUA (p<0.01), EOSA (p<0.05), BASA (p<0.01), LYM% (p<0.01), NEU% (p<0.01), EOS% (p<0.01), BAS% (p<0.01), MON% (p<0.01), and PLT (p<0.01) were significant (Table 2). All parameters analyzed using regression tests, except for WBC count, showed significant F values (MCH, LYMA, NEUA, BASA, LYM%, NEU%, EOS%, BAS%, MON%, and PLT: p<0.01, EOSA: p<0.05; Table 3). All parameters analyzed using regression test, except for MCH and WBC count, showed significant t value (MCH, LYMA, NEUA, BASA, LYM%, NEU%, EOS%, BAS%, MON%, and PLT: p<0.01, EOSA: p<0.05; Table 3). R2 value is presented in Table 3.

Table 1. Hematology data for F344 rats exposed to fresh air in whole-body chamber
Experimental week 4 13 26 52
No. of animals1) 24 60 50 25
Males
 RBC (× 106/µL) 8.78 ± 0.26 9.04 ± 0.20** 9.02 ± 0.36** 8.85 ± 0.38
 HGB (g/dL) 14.9 ± 0.5 14.8 ± 0.3 14.9 ± 1.9 15.0 ± 0.6
 HCT (%) 43.5 ± 1.1 43.3 ± 0.8 42.8 ± 1.6* 43.9 ± 1.7
 MCV (fL) 49.6 ± 0.5 47.9 ± 0.7** 47.4 ± 0.8** 49.7 ± 0.7
 MCH (pg) 17.0 ± 0.4 16.4 ± 0.4** 16.9 ± 0.3* 17.0 ± 0.3
 MCHC (g/dL) 34.3 ± 0.7 34.2 ± 0.7 35.6 ± 0.7** 34.3 ± 0.4
 RETA (× 103/µL) 204.2 ± 27.3 226.1 ± 24.9** 207.2 ± 24.6 214.7 ± 25.5
 RET% (%) 2.3 ± 0.3 2.5 ± 0.3* 2.3 ± 0.3 2.4 ± 0.3
 WBC (× 10³/µL) 3.97 ± 0.90 4.47 ± 0.86* 4.91 ± 0.88** 3.64 ± 0.65
 LYMA (× 103/µL) 2.93 ± 0.77 2.96 ± 0.64 2.67 ± 0.57* 1.88 ± 0.33**
 NEUA (× 103/µL) 0.89 ± 0.31 1.29 ± 0.33** 1.99 ± 0.63** 1.56 ± 0.41**
 EOSA (× 103/µL) 0.05 ± 0.02 0.08 ± 0.02** 0.07 ± 0.02** 0.08 ± 0.02**
 BASA (× 103/µL) 0.01 ± 0.01 0.01 ± 0.01** 0.01 ± 0.00 0.00 ± 0.00
 MONA (× 103/µL) 0.07 ± 0.02 0.10 ± 0.03 0.13 ± 0.04** 0.10 ± 0.03
 LYM% (%) 73.5 ± 6.7 66.2 ± 5.6* 54.6 ± 8.3** 51.9 ± 5.6**
 NEU% (%) 22.8 ± 6.8 28.9 ± 5.3* 40.2 ± 8.8** 42.5 ± 5.7**
 EOS% (%) 1.4 ± 0.7 1.8 ± 0.5* 1.5 ± 0.4 2.2 ± 0.5**
 BAS% (%) 0.2 ± 0.1 0.2 ± 0.1 0.1 ± 0.1** 0.1 ± 0.1**
 MON% (%) 1.7 ± 0.4 2.3 ± 0.6** 2.7 ± 0.7** 2.7 ± 0.5**
 PLT (× 103/µL) 748 ± 42 706 ± 42* 676 ± 99** 617 ± 119**
 APTT (sec) 18.0 ± 1.8 18.5 ± 2.1 16.7 ± 1.9 19.4 ± 3.3
 PT (sec) 10.5 ± 0.5 10.7 ± 0.4 12.6 ± 1.4** 10.6 ± 0.3

* Differences among ages are expressed as p<0.05,

** p<0.01 based on the result of Dunnett’s or Dunn’s test.

1) APTT and PT were examined in 23 males in the 52-week study.

RBC, red blood cell; HGB, hemoglobin; HCT, hematocrit; MCV, mean cell volume; MCH, mean cell hemoglobin; MCHC, mean cell hemoglobin concentration; RETA, reticulocyte count; RET%, reticulocyte percentage; WBC, white blood cell; LYMA, lymphocyte count; NEUA, neutrophil count; EOSA, eosinophil count; BASA, basophil count; MONA, monocyte count; LYM%, lymphocyte percentage; NEU%, neutrophil percentage; EOS%, eosinophil percentage; BAS%, basophil percentage; MON%, monocyte percentage; PLT, platelet; APTT, activated partial thromboplastin time; PT, prothrombin time.

Download Excel Table
Table 2. Correlation coefficients in hematology
Sex Male Female
Parameter Week Week
Week 1 1
RBC –0.066 –0.348**
HGB 0.061 –0.089
HCT 0.057 0.07
MCV 0.151 0.716**
MCH 0.279** 0.527**
MCHC 0.138 –0.018
RETA –0.046 –0.151
RET% –0.026 –0.101
WBC –0.182* –0.570**
LYMA –0.537** –0.270**
NEUA 0.362** 0.012
EOSA 0.167* –0.260**
BASA –0.376** –0.298**
MONA 0.065 –0.102
LYM% –0.651** –0.533**
NEU% 0.629** 0.548**
EOS% 0.309** 0.248**
BAS% –0.394** –0.274**
MON% 0.438** 0.177*
PLT –0.297** –0.464**
APTT 0.054 0.324**
PT 0.129 –0.323**

Week indicates the experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

RBC, red blood cell; HGB, hemoglobin; HCT, hematocrit; MCV, mean cell volume; MCH, mean cell hemoglobin; MCHC, mean cell hemoglobin concentration; RETA, reticulocyte count; RET%, reticulocyte percentage; WBC, white blood cell; LYMA, lymphocyte count; NEUA, neutrophil count; EOSA, eosinophil count; BASA, basophil count; MONA, monocyte count; LYM%, lymphocyte percentage; NEU%, neutrophil percentage; EOS%, eosinophil percentage; BAS%, basophil percentage; MON%, monocyte percentage; PLT, platelet; APTT, activated partial thromboplastin time; PT, prothrombin time.

Download Excel Table
Table 3. Results of simple linear regression analysis for males in hematology
Parameter F t Unstandardized Coefficients Standardized Coefficients R2
B S.E β
MCH
 Constant 11.343** 278.178 16.528 0.059 0.265 0.070
 Week 3.368** 0.008 0.002
WBC
 Constant 3.184 35.142 4.542 0.129 –0.144 0.021
 Week –1.784 –0.009 0.005
LYMA
 Constant 55.612** 36.646 3.178 0.087 –0.52 0.270
 Week –7.457** –0.025 0.003
NEUA
 Constant 26.361** 15.038 1.166 0.078 0.387 0.149
 Week 5.134** 0.015 0.003
EOSA
 Constant 5.38* 21.056 0.066 0.003 0.186 0.035
 Week 2.32* 0.000 0.000
BASA
 Constant 22.473** 12.237 0.009 0.001 –0.361 0.130
 Week –4.741** 0.000 0.000
LYM%
 Constant 113.622** 61.624 71.009 1.152 –0.657 0.431
 Week –10.659** –0.472 0.044
NEU%
 Constant 100.506** 21.555 24.698 1.146 0.633 0.401
 Week 10.025** 0.441 0.044
EOS%
 Constant 14.928** 19.599 1.464 0.075 0.301 0.091
 Week 3.864** 0.011 0.003
BAS%
 Constant 25.182** 17.158 0.217 0.013 –0.379 0.144
 Week –5.018** –0.002 0
MON%
 Constant 35.285** 23.233 1.998 0.086 0.436 0.190
 Week 5.94** 0.02 0.003
PLT
 Constant 17.176** 51.644 732.191 14.178 –0.321 0.103
 Week –4.144** –2.256 0.544

Week indicates experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

MCH, mean cell hemoglobin; WBC, white blood cell; LYMA, lymphocyte count; NEUA, neutrophil count; EOSA, eosinophil count; BASA, basophil count; LYM%, lymphocyte percentage; NEU%, neutrophil percentage; EOS%, eosinophil percentage; BAS%, basophil percentage; MON%, monocyte percentage; PLT, platelet.

Download Excel Table
Change trends of hematological parameters at different ages in female rats

Statistically significant differences were observed in MCV, MCH, LYMA, LYM%, NEU%, BAS%, and PLT at 13, 26, and 52 weeks; RBC, RETA, WBC, and BASA at 26 and 52 weeks; EOS% at 52 weeks; MCHC, RET%, PT, and APTT at 26 weeks; and HGB, HCT, and NEUA at 13 weeks compared with those at 4 weeks (Table 4). Their p-values are presented in Table 4. The correlation coefficients between experimental week and RBC count (p<0.01), MCV (p<0.01), MCH (p<0.01), WBC count (p<0.01), LYMA (p<0.01), EOSA (p<0.01), BASA (p<0.01), LYM% (p<0.01), NEU% (p<0.01), EOS% (p<0.01), BAS% (p<0.01), MON% (p<0.05), PLT (p<0.01), APTT (p<0.01), and PT (p<0.01) were significant (Table 2). All parameters analyzed using the regression test showed significant F- (RBC, MCV, MCH, WBC, LYMA, EOSA, BASA, LYM%, NEU%, BAS%, PLT, and APTT: p<0.01, EOS%, MON%, and PT: p<0.05) and t-values (RBC, MCV, MCH, WBC, LYMA, EOSA, BASA, LYM%, NEU%, BAS%, PLT, APTT, and PT: p<0.05, EOS% and MON%: p<0.05; Table 5). R2 value are presented in Table 5.

Table 4. Hematology data for F344 rats exposed to fresh air in whole-body chamber
Experimental week 4 13 26 52
No. of animals1) 25 60 50 25
Females
 RBC (× 106/µL) 8.54 ± 0.37 8.46 ± 0.22 8.29 ± 0.32** 8.16 ± 0.25**
 HGB (g/dL) 15.0 ± 0.6 14.6 ± 0.4** 15.3 ± 0.5 14.8 ± 0.4
 HCT (%) 43.2 ± 1.3 42.1 ± 0.9** 42.6 ± 1.9 43.1 ± 1.1
 MCV (fL) 50.6 ± 1.1 49.8 ± 0.6** 51.4 ± 0.5** 52.8 ± 1.0**
 MCH (pg) 17.6 ± 0.4 17.3 ± 0.4** 18.4 ± 0.3** 18.1 ± 0.4**
 MCHC (g/dL) 34.8 ± 0.9 34.7 ± 0.7 35.8 ± 0.6** 34.4 ± 0.5
 RETA (× 103/µL) 232.2 ± 158.3 184.7 ± 25.7 171.0 ± 18.9** 182.4 ± 51.3**
 RET% (%) 2.8 ± 2.3 2.2 ± 0.3 2.1 ± 0.3* 2.2 ± 0.7
 WBC (× 103/µL) 3.13 ± 0.87 2.84 ± 0.80 2.77 ± 0.73* 1.42 ± 0.36**
 LYMA (× 103/µL) 2.37 ± 0.73 1.97 ± 0.61** 1.76 ± 0.54* 0.80 ± 0.28**
 NEUA (× 103/µL) 0.62 ± 0.16 0.73 ± 0.24** 0.87 ± 0.34 0.51 ± 0.18
 EOSA (× 103/µL) 0.04 ± 0.01 0.05 ± 0.02 0.04 ± 0.02 0.03 ± 0.02
 BASA (× 103/µL) 0.01 ± 0.01 0.00 ± 0.00 0.00 ± 0.00** 0.00 ± 0.00**
 MONA (× 103/µL) 0.06 ± 0.03 0.07 ± 0.07 0.07 ± 0.02 0.05 ± 0.02
 LYM% (%) 75.5 ± 4.1 69.2 ± 8.7* 63.1 ± 8.0** 56.1 ± 14.2**
 NEU% (%) 20.4 ± 4.0 25.8 ± 6.0** 31.9 ± 8.2** 36.9 ± 12.6**
 EOS% (%) 1.5 ± 0.4 1.8 ± 0.6 1.5 ± 0.8 2.4 ± 1.9*
 BAS% (%) 0.2 ± 0.1 0.2 ± 0.1* 0.1 ± 0.1** 0.1 ± 0.1**
 MON% (%) 1.9 ± 0.6 2.5 ± 3.7 2.5 ± 0.5 3.5 ± 0.8
 PLT (× 103/µL) 808 ± 99 742 ± 51* 649 ± 85** 534 ± 169**
 APTT (sec) 17.5 ± 2.1 18.7 ± 2.0 19.3 ± 4.1 21.0 ± 1.8**
 PT (sec) 10.5 ± 0.7 10.4 ± 0.5 10.0 ± 0.7 9.9 ± 0.4**

* Differences among ages are expressed as p<0.05,

** p<0.01 based on the result of Dunnett’s or Dunn’s test.

1) APTT and PT were examined in 21 females in the 52-week study.

RBC, red blood cell; HGB, hemoglobin; HCT, hematocrit; MCV, mean cell volume; MCH, mean cell hemoglobin; MCHC, mean cell hemoglobin concentration; RETA, reticulocyte count; RET%, reticulocyte percentage; WBC, white blood cell; LYMA, lymphocyte count; NEUA, neutrophil count; EOSA, eosinophil count; BASA, basophil count; MONA, monocyte count; LYM%, lymphocyte percentage; NEU%, neutrophil percentage; EOS%, eosinophil percentage; BAS%, basophil percentage; MON%, monocyte percentage; PLT, platelet; APTT, activated partial thromboplastin time; PT, prothrombin time.

Download Excel Table
Table 5. Results of simple linear regression analysis for females in hematology
Parameter F t Unstandardized Coefficients Standardized Coefficients R2
B S.E. β
RBC
 Constant 20.967** 189.257 8.545 0.045 –0.358 0.128
 Week –4.579** –0.008 0.002
MCV
 Constant 144.754** 377.207 49.554 0.131 0.709 0.503
 Week 12.031** 0.062 0.005
MCH
 Constant 56.467** 244.87 17.35 0.071 0.532 0.283
 Week 7.514** 0.021 0.003
WBC
 Constant 59.757** 30.075 3.301 0.11 –0.543 0.295
 Week –7.73** –0.033 0.004
LYMA
 Constant 8.95** 14.304 1.533 0.107 –0.243 0.059
 Week –2.992** –0.013 0.004
EOSA
 Constant 12.167** 18.471 0.051 0.003 –0.28 0.078
 Week –3.488** 0.000 0.000
BASA
 Constant 12.121** 7.265 0.006 0.001 –0.28 0.078
 Week –3.481** 0.000 0.000
LYM%
 Constant 53.658** 60.243 74.226 1.232 –0.522 0.273
 Week –7.325** –0.355 0.048
NEU%
 Constant 60.074** 21.88 21.604 0.987 0.544 0.296
 Week 7.751** 0.301 0.039
EOS%
 Constant 5.724* 12.083 1.483 0.123 0.196 0.038
 Week 2.393* 0.012 0.005
BAS%
 Constant 12.153** 14.676 0.216 0.015 –0.28 0.078
 Week –3.486** –0.002 0.001
MON%
 Constant 4.712* 5.706 1.94 0.34 0.179 0.032
 Week 2.171* 0.029 0.013
PLT
 Constant 65.99** 47.366 803.03 16.954 –0.562 0.316
 Week –8.123** –5.418 0.667
APTT
 Constant 16.997** 40.523 17.723 0.437 0.326 0.106
 Week 4.123** 0.071 0.017
PT
 Constant 19.31* 127.187 10.582 0.083 –0.345 0.119
 Week –4.394** –0.014 0.003

Week indicates the experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

RBC, red blood cell; MCV, mean cell volume; MCH, mean cell hemoglobin; WBC, white blood cell; LYMA, lymphocyte count; EOSA, eosinophil count; BASA, basophil count; LYM%, lymphocyte percentage; NEU%, neutrophil percentage; EOS%, eosinophil percentage; BAS%, basophil percentage; MON%, monocyte percentage; PLT, platelet; APTT, activated partial thromboplastin time; PT, prothrombin time.

Download Excel Table
Change trends of biochemistry parameters at different ages in male rats

Statistically significant differences were observed in ALP, TP, ALB, A/G ratio, TG, TCHO, and IP at 13, 26, and 52 weeks; ALT, AST, and Cl at 26 and 52 weeks; GLU at 13 and 26 weeks; CREA at 52 weeks; and Na and Ca at 26 weeks compared with those at 4 weeks (Table 6). Their p-values are presented in Table 6. The correlation coefficients between experimental week and ALT (p<0.01), AST (p<0.01), ALP (p<0.01), TP (p<0.01), ALB (p<0.01), A/G ratio (p<0.01), TG (p<0.01), TCHO (p<0.01), GLU (p<0.01), BUN (p<0.05), CREA (p<0.05), Na (p<0.01), Cl (p<0.01), and IP (p<0.01) levels were significant (Table 7). All parameters analyzed using the regression test showed significant F- and t-values (ALT, AST, ALP, TP, ALB, A/G ratio, TG, TCHO, GLU, Na, Cl, and IP: p<0.01, BUN and CREA: p<0.01; Table 8 and Fig. 1). R2 value was presented in Table 8.

Table 6. Serum chemistry data for F344 rats exposed to fresh air in whole-body chamber
Experimental week 4 13 26 52
No. of animals 25 60 50 25
Males
 ALT (IU/L) 42.6 ± 13.8 46.8 ± 13.6 111.5 ± 45.2** 117.8 ± 38.8**
 AST (IU/L) 79.5 ± 11.6 93.2 ± 20.5 162.7 ± 42.2** 167.4 ± 39.4**
 ALP (IU/L) 697 ± 39 397 ± 49** 317 ± 32** 323 ± 30**
 TBIL (mg/dL) 0.18 ± 0.04 0.17 ± 0.03 0.20 ± 0.03 0.20 ± 0.00
 TP (g/dL) 5.6 ± 0.4 6.1 ± 0.5** 6.8 ± 0.3** 6.5 ± 0.2**
 ALB (g/dL) 3.9 ± 0.2 4.1 ± 0.3** 4.3 ± 0.2** 4.2 ± 0.1**
 A/G ratio 2.24 ± 0.11 2.04 ± 0.13** 1.79 ± 0.08** 1.77 ± 0.06**
 TG (mg/dL) 53.9 ± 15.5 96.3 ± 46.6** 100.4 ± 34.4** 135.1 ± 47.6**
 TCHO (mg/dL) 62.2 ± 5.7 77.3 ± 12.2** 76.2 ± 7.0** 127.3 ± 15.0**
 GLU (mg/dL) 161 ± 18 145 ± 29* 131 ± 10** 179 ± 26
 BUN (mg/dL) 18.6 ± 2.6 17.4 ± 2.9 19.9 ± 2.0 18.7 ± 1.6
 CREA (mg/dL) 0.41 ± 0.05 0.44 ± 0.05 0.42 ± 0.03 0.45 ± 0.03**
 Na (mmol/L) 137.2 ± 9.9 135.6 ± 11.0 143.8 ± 5.2** 143.1 ± 0.7
 Cl (mmol/L) 97.3 ± 7.0 95.9 ± 7.9 103.3 ± 3.8** 103.7 ± 0.9**
 K (mmol/L) 4.31 ± 0.60 4.19 ± 0.43 4.43 ± 0.28 4.33 ± 0.25
 Ca (mg/dL) 9.5 ± 0.8 9.8 ± 1.1 9.9 ± 0.4** 10.0 ± 0.2
 IP (mg/dL) 6.6 ± 1.0 5.4 ± 0.8** 6.2 ± 0.5* 4.5 ± 0.8**

* Differences among ages are expressed as p<0.05,

** p<0.01, based on Dunnett’s or Dunn’s test.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; TBIL, total bilirubin; TP, total protein; ALB, albumin; A/G, albumin/globulin; TG, triglyceride; TCHO, total cholesterol; GLU, glucose; BUN, blood urea nitrogen; CREA, creatinine; Na, sodium; Cl, chloride; K, potassium; Ca, calcium; IP, inorganic phosphorus.

Download Excel Table
Table 7. Correlation coefficients in serum chemistry
Sex Male Female
Parameter Week week
Week 1 1
ALT 0.476** 0.350**
AST 0.650** 0.494**
ALP –0.630** –0.685**
TBIL 0.064 –0.227**
TP 0.495** 0.753**
ALB 0.315** 0.705**
A/G –0.703** –0.667**
TG 0.442** 0.529**
TCHO 0.807** 0.853**
GLU 0.237** 0.604**
BUN 0.187* 0.298**
CREA 0.199* 0.426**
Na 0.301** 0.292**
K 0.1 0.053
Cl 0.408** 0.290**
Ca 0.153 0.290**
IP –0.407** –0.412**

Week indicates the experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; TBIL, total bilirubin; TP, total protein; ALB, albumin; A/G, albumin/globulin; TG, triglyceride; TCHO, total cholesterol; GLU, glucose; BUN, blood urea nitrogen; CREA, creatinine; Na, sodium; K, potassium; Cl, chloride; Ca, calcium; IP, inorganic phosphorus.

Download Excel Table
Table 8. Results of simple linear regression analysis for males in serum chemistry
Parameter F t Unstandardized Coefficients Standardized Coefficients R2
B S.E. β
ALT
 Constant 46.207** 5.4 48.521 8.986 0.476 0.226
 Week 6.798** 2.309 0.340
AST
 Constant 115.713** 15.28 69.860 4.572 0.650 0.423
 Week 10.757** 1.859 0.173
ALP
 Constant 104.05** 36.193 531.345 14.681 –0.630 0.397
 Week –10.201** –5.662 0.555
TP
 Constant 51.327** 83.692 5.872 0.070 0.495 0.245
 Week 7.164** 0.019 0.003
ALB
 Constant 17.463** 109.613 4.002 0.037 0.315 0.100
 Week 4.179** 0.006 0.001
A/G ratio
 Constant 154.073** 104.666 2.152 0.021 –0.703 0.494
 Week –12.413** –0.010 0.001
TG
 Constant 38.429** 11.837 66.352 5.606 0.442 0.196
 Week 6.199** 1.314 0.212
TCHO
 Constant 295.616** 29.711 55.768 1.877 0.807 0.652
 Week 17.193** 1.220 0.071
GLU
 Constant 9.426** 37.185 139.237 3.744 0.237 0.056
 Week 3.07** 0.435 0.142
BUN
 Constant 5.732* 8.851 15.979 1.805 0.187 0.035
 Week 2.394* 0.163 0.068
CREA
 Constant 6.521* 67.522 0.418 0.006 0.199 0.040
 Week 2.554* 0.001 0.000
Na
 Constant 15.727** 112.172 135.439 1.207 0.301 0.091
 Week 3.966** 0.181 0.046
Cl
 Constant 31.592** 108.464 95.423 0.880 0.408 0.167
 Week 5.621** 0.187 0.033
IP
 Constant 31.303** 46.397 6.266 0.135 –0.407 0.165
 Week –5.595** –0.029 0.005

Week indicates the experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; TP, total protein; ALB, albumin; A/G, albumin/globulin; TG, triglyceride; TCHO, total cholesterol; GLU, glucose; BUN, blood urea nitrogen; CREA, creatinine; Na, sodium; Cl, chloride; IP, inorganic phosphorus.

Download Excel Table
jbtr-25-3-145-g1
Fig. 1. Age-dependent TCHO change trend in F344 rats. Regression analysis for TCHO shows a direct linear relationship between TCHO and age in both sexes. The R2 values for TCHO were 0.652 in males (A) and 0.728 in females (B). TCHO, total cholesterol.
Download Original Figure
Change trends of biochemistry parameters at different ages in female rats

Statistically significant differences were observed in ALP, TP, ALB, A/G ratio, TCHO, and IP at 13, 26, and 52 weeks; ALT, TG, CREA, and Ca at 26 and 52 weeks; AST at 13 and 52 weeks; GLU at 52 weeks; and TBIL, Na, Cl, and K at 26 weeks compared with those at 4 weeks (Table 9). Their p-values are presented in Table 9. The correlation coefficients between experimental week and ALT (p<0.01), AST (p<0.01), ALP (p<0.01), TBIL (p<0.01), TP (p<0.01), ALB (p<0.01), A/G ratio (p<0.01), TG (p<0.01), TCHO (p<0.01), GLU (p<0.01), BUN (p<0.01), CREA (p<0.01), Na (p<0.01), Cl (p<0.01), Ca (p<0.01), and IP (p<0.01) were significant (Table 7). All parameters analyzed using the regression test showed significant F- and t-values (F- and t-values for ALT, AST, ALP, TBIL, TP, ALB, A/G ratio, TG, TCHO, GLU, BUN, CREA, Na, Cl, Ca, and IP: p<0.01; Table 10 and Fig. 1). R2 value are presented in Table 10.

Table 9. Serum chemistry data for F344 rats exposed to fresh air in whole body chamber
Experimental week 4 13 26 52
No. of animals 25 60 50 25
Females
 ALT (IU/L) 40.3 ± 11.7 41.8 ± 9.5 85.2 ± 40.5** 73.1 ± 22.7**
 AST (IU/L) 81.5 ± 10.5 96.2 ± 15.3* 136.8 ± 38.7 153.1 ± 60.2**
 ALP (IU/L) 537 ± 53 295 ± 44** 279 ± 37** 203 ± 33**
 TBIL (mg/dL) 0.16 ± 0.03 0.15 ± 0.02 0.14 ± 0.03* 0.14 ± 0.04
 TP (g/dL) 5.7 ± 0.5 6.3 ± 0.4** 7.0 ± 0.4** 7.5 ± 0.4**
 ALB (g/dL) 4.0 ± 0.3 4.2 ± 0.2** 4.5 ± 0.2** 4.8 ± 0.2**
 A/G ratio 2.25 ± 0.16 2.00 ± 0.12** 1.78 ± 0.11** 1.77 ± 0.08**
 TG (mg/dL) 24.5 ± 20.0 21.8 ± 8.6 33.7 ± 16.0* 49.4 ± 15.8**
 TCHO (mg/dL) 74.8 ± 11.1 89.6 ± 11.0** 99.2 ± 12.8** 140.2 ± 12.7**
 GLU (mg/dL) 127 ± 14 115 ± 18 120 ± 12 161 ± 10**
 BUN (mg/dL) 20.2 ± 3.7 19.1 ± 2.5 20.6 ± 2.2 21.9 ± 2.3
 CREA (mg/dL) 0.40 ± 0.03 0.42 ± 0.04 0.43 ± 0.04** 0.47 ± 0.04**
 Na (mmol/L) 137.8 ± 10.2 136.4 ± 10.9 148.9 ± 1.8** 142.5 ± 1.1
 Cl (mmol/L) 100.4 ± 8.4 99.3 ± 8.0 107.8 ± 2.1** 104.1 ± 1.4
 K (mmol/L) 4.14 ± 0.43 4.00 ± 0.41 4.64 ± 0.71** 4.00 ± 0.36
 Ca (mg/dL) 9.6 ± 0.8 9.7 ± 0.9 10.8 ± 1.1** 10.3 ± 0.3**
 IP (mg/dL) 6.7 ± 1.0 4.9 ± 0.8** 5.8 ± 1.2* 4.1 ± 1.0**

* Differences among ages are expressed as p<0.05,

** p<0.01 based on the result of Dunnett’s or Dunn’s test.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; TBIL, total bilirubin; TP, total protein; ALB, albumin; A/G, albumin/globulin; TG, triglyceride; TCHO, total cholesterol; GLU, glucose; BUN, blood urea nitrogen; CREA, creatinine; Na, sodium; Cl, chloride; K, potassium; Ca, calcium; IP, inorganic phosphorus.

Download Excel Table
Table 10. Results of simple linear regression analysis for females in serum chemistry
Parameter F t Unstandardized Coefficients Standardized Coefficients R2
B S.E. β
ALT
 Constant 21.756** 7.053 50.563 7.169 0.35 0.122
 Week 4.664** 1.264 0.271
AST
 Constant 50.314** 14.53 71.615 4.929 0.494 0.244
 Week 7.093** 1.321 0.186
ALP
 Constant 137.72** 37.961 422.898 11.14 –0.685 0.469
 Week –11.735** –4.942 0.421
TBIL
 Constant 8.499** 28.1 0.158 0.006 –0.227 0.052
 Week –2.915** –0.001 0
TP
 Constant 204.488** 88.11 5.868 0.067 0.753 0.567
 Week 14.3** 0.036 0.003
ALB
 Constant 154.496** 111.834 3.994 0.036 0.705 0.498
 Week 12.43** 0.017 0.001
A/G ratio
 Constant 125.315** 98.625 2.131 0.022 –0.667 0.445
 Week –11.194** –0.009 0.001
TG
 Constant 60.471** 8.447 16.868 1.997 0.529 0.279
 Week 7.776** 0.587 0.075
TCHO
 Constant 417.612** 41.8 70.335 1.683 0.853 0.728
 Week 20.436** 1.3 0.064
GLU
 Constant 89.591** 44.926 107.725 2.398 0.604 0.365
 Week 9.465** 0.858 0.091
BUN
 Constant 15.154** 50.778 19.088 0.376 0.298 0.089
 Week 3.893** 0.055 0.014
CREA
 Constant 34.58** 67.77 0.4 0.006 0.426 0.181
 Week 5.88** 0.001 0
Na
 Constant 14.504** 108.489 137.393 1.266 0.292 0.085
 Week 3.808** 0.182 0.048
Cl
 Constant 14.305** 105.67 99.889 0.945 0.29 0.084
 Week 3.782** 0.135 0.036
Ca
 Constant 14.28** 72.581 9.709 0.134 0.290 0.084
 Week 3.779** 0.019 0.005
IP
 Constant 31.945** 36.35 6.011 0.165 –0.412 0.170
 Week –5.652** –0.035 0.006

Week indicates the experimental week.

* Statistical significance is expressed as p<0.05,

** p<0.01.

ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; TBIL, total bilirubin; TP, total protein; ALB, albumin; A/G, albumin/globulin; TG, triglyceride; TCHO, total cholesterol; GLU, glucose; BUN, blood urea nitrogen; CREA, creatinine; Na, sodium; Cl, chloride; Ca, calcium; IP, inorganic phosphorus.

Download Excel Table

DISCUSSION

We collected background clinicopathology data for an inhalation study and described trends and alterations in hematological and biochemical parameters with aging in F344 rats.

Statistical significance in correlation analysis with age was noted in 27 parameters in males and 31 parameters in females for hematology and clinical chemistry. Regression analysis was performed on parameters showing the statistical significance in correlation analysis. Positive correlation coefficients indicate an increasing tendency and a direct linear relationship, whereas negative values indicate a decreasing tendency and an inverse linear relationship [19, 20]. Correlation and linear regression analyses revealed a direct linear relationship with age in both sexes for MCH, NEU%, EOS%, MON%, ALT, AST, TP, ALB, TG, TCHO, GLU, BUN, CREA, Na, Cl and an inverse linear relationship for PLT, LYMA, BASA, LYM%, BAS%, ALP, A/G ratio, and IP. Females additionally showed a direct linear relationship with MCV, APTT, and Ca and an inverse linear relationship with RBC, PT, WBC, EOSA, and TBIL with increasing weeks. Males showed a direct linear relationship with NEUA and EOSA, with an increase in weeks. However, most parameters, except for TCHO (R2 = 0.652 in males, R2 = 0.728 in females) and MCV (R2 = 0.503) and TP (R2 = 0.567) in females, had R2 values below 0.5. In addition, these results indicated that although aging is one of the factors affecting values, there are other more affectable factors to the values. Several factors, including aging pathobiology [21, 22], spontaneous changes [23, 24], and sample size, could affect data on clinical pathological parameters.

The intersection of results for mean comparison and regression analysis was examined to confirm change trends with increasing age. Mean comparison results identified parameters that showed significant differences from the 4-week mark across all weeks. LYM%, NEU%, PLT, ALP, TP, ALB, A/G ratio, TCHO, and IP in both sexes, LYMA in females, and NEUA, EOSA, MON%, and TG in males exhibited similar change patterns between mean comparison and regression analyses. NEUA, EOSA, NEU%, MON%, TP, ALB, TG, and TCHO increased, whereas LYMA, LYM%, PLT, ALP, A/G ratio, and IP decreased in both analyses. Parameters with R2 values greater than 0.5 in regression analysis among the common significant parameters in both mean comparison and regression analysis were TCHO in both sexes and TP in females. Therefore, we considered that TCHO is the parameter most affected by aging in both sexes. Age-related changes in TCHO have also been reported in humans, with suggested causes being decreased low-density lipoprotein receptor and the conversion of cholesterol to bile acid with aging [25, 26].

Until now, most studies on trends in historical data have not used statistical analysis or only performed mean comparisons [2729]. We conducted a mean comparison and regression analysis to clarify the relationships with aging. The results showed that mean difference comparison and trend analysis did not yield exactly the same results; however, they showed similar pattern and could be complementary. Therefore, we propose applying both mean comparison and regression analyses together for trend analysis.

In this study, the clinicopathological background data of F344 rats used in inhalation toxicity studies were presented. To our knowledge, we are the first to present the clinicopathological historical data for inhalation study and statistically analyze the age-related change trends. We confirmed aging trends in clinicopathological parameters and concluded that TCHO is most affected by aging under condition of this study. Further research is required to understand how age affects clinicopathological parameters. These results will be helpful for study design and data interpretation in the field of research using rats.

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Acknowledgements

This work was supported by a grant from the Occupational Safety and Health Research Institute of Korea Occupational Safety and Health Agency.

Ethics Approval

The study protocols were approved by the Institutional Animal Care and Use Committee (IACUC) of the Inhalation Toxicity Research Center (IACUC approval numbers: IACUC-1911, -1913, -1915, -1916, -1917, -1918, -1812, -1813, -1815, -1817, -1818, -1612, -1601).

REFERENCES

1.

Abidin İ, Keser H, Şahin E, Öztürk H, Başoğlu H, Alver A, Aydin-Abidin S. Effects of housing conditions on stress, depressive like behavior and sensory-motor performances of C57BL/6 mice. Lab Anim Res. 2024; 40:6

2.

Everds NE, Snyder PW, Bailey KL, Bolon B, Creasy DM, Foley GL, Rosol TJ, Sellers T. Interpreting stress responses during routine toxicity studies: a review of the biology, impact, and assessment. Toxicol Pathol. 2013; 41:560-614

3.

Matsuzawa T, Sakazume M. Effects of fasting on haematology and clinical chemistry values in the rat and dog. Comp Haematol Int. 1994; 4:152-156

4.

Giannini EG, Testa R, Savarino V. Liver enzyme alteration: a guide for clinicians. CMAJ. 2005; 172:367-379

5.

Makris K. The role of the clinical laboratory in the detection and monitoring of acute kidney injury. J Lab Precis Med. 2018; 3:69

6.

Aldapt MB, Haddad F, Abuasab T, Soliman DS, Abbas F, Mosalem O, Ahmed A, Saeed S, Abdulla MAJ, Mohamed SF. Extramedullary hematopoiesis (EMH) and myelodysplastic syndrome (MDS): review. Blood. 2022; 140:12331-12332

7.

Hall RL, Everds NE. Principles of clinical pathology for toxicology studies.In In: Hayes AW, Kruger CL, editors.(eds.) Hayes’ principles and methods of toxicology. 6th ed Baca Raton: CRC Press. 2014; p p. 1305-1344

8.

Palazzi X, Burkhardt JE, Caplain H, Dellarco V, Fant P, Foster JR, Francke S, Germann P, Gröters S, Harada T, Harleman J, Inui K, Kaufmann W, Lenz B, Nagai H, Pohlmeyer-Esch G, Schulte A, Skydsgaard M, Tomlinson L, Wood CE, Yoshida M. Characterizing “adversity” of pathology findings in nonclinical toxicity studies: results from the 4th ESTP International Expert Workshop. Toxicol Pathol. 2016; 44:810-824

9.

Organisation for Economic Co-operation and Development [OECD]. Test no. 412: subacute inhalation toxicity: 28-day study [Internet]. 2018.[cited 2024 Jun 5]Available from:
.

10.

Organisation for Economic Co-operation and Development [OECD]. Test no. 413: subchronic inhalation toxicity: 90-day study [Internet]. 2018.[cited 2024 Jun 5]Available from
.

11.

Organisation for Economic Co-operation and Development [OECD]. Test no. 452: chronic toxicity studies [Internet]. 2018.[cited 2024 Jun 5]Available from
.

12.

Hayashi M, Dearfield K, Kasper P, Lovell D, Martus HJ, Thybaud V. Compilation and use of genetic toxicity historical control data. Mutat Res Genet Toxicol Environ Mutagen. 2011; 723:87-90

13.

Ryan L. Using historical controls in the analysis of developmental toxicity data. Biometrics. 1993; 49:1126-1135

14.

Mitchell I, Rees RW, Gilbert PJ, Carlton JB. The use of historical data for identifying biologically unimportant but statistically significant results in genotoxicity assays. Mutagenesis. 1990; 5:159-164

15.

Haseman JK, Huff J, Boorman GA. Use of historical control data in carcinogenicity studies in rodents. Toxicol Pathol. 1984; 12:126-135

16.

Kumar A, Bockenstedt M, Laast V, Sharma A. Historical control background incidence of spontaneous neoplastic lesions of Sprague-Dawley rats in 104-week toxicity studies. Toxicol Pathol. 2023; 51:329-356

17.

Matsushita K, Ishii Y, Kijima A, Takasu S, Kuroda K, Takagi H, Nohmi T, Ogawa K, Umemura T. Background data of 2-year-old male and female F344 gpt delta rats. J Toxicol Pathol. 2021; 34:23-31

18.

Isobe K, Baily J, Mukaratirwa S, Petterino C, Bradley A. Historical control background incidence of spontaneous pituitary gland lesions of Han-Wistar and Sprague-Dawley rats and CD-1 mice used in 104-week carcinogenicity studies. J Toxicol Pathol. 2017; 30:339-344

19.

Shi R, Conrad SA. Correlation and regression analysis. Ann Allergy Asthma Immunol. 2009; 103:S35-S41

20.

Zou KH, Tuncali K, Silverman SG. Correlation and simple linear regression. Radiology. 2003; 227:617-628

21.

Short BG, Goldstein RS. Nonneoplastic lesions in the kidney.In In: Mohr U, Dungworth DL, Capen CC, editors.(eds.) Pathobiology of the aging rat. Washington: ILSI. 1992; p p. 211-225

22.

Mainwaring WIP. The effect of age on protein synthesis in mouse live. Biochem J. 1969; 113:869-878

23.

Suttie AW. Histopathology of the spleen. Toxicol Pathol. 2006; 34:466-503

24.

Thoolen B, Maronpot RR, Harada T, Nyska A, Rousseaux C, Nolte T, Malarkey DE, Kaufmann W, Küttler K, Deschl U, Nakae D, Gregson R, Vinlove MP, Brix AE, Singh B, Belpoggi F, Ward JM. Proliferative and nonproliferative lesions of the rat and mouse hepatobiliary system. Toxicol Pathol. 2010; 38:5S-81S

25.

Carroll MD, Lacher DA, Sorlie PD, Cleeman JI, Gordon DJ, Wolz M, Grundy SM, Johnson CL. Trends in serum lipids and lipoproteins of adults, 1960-2002. JAMA. 2005; 294:1773-1781

26.

Downer B, Estus S, Katsumata Y, Fardo DW. Longitudinal trajectories of cholesterol from midlife through late life according to apolipoprotein E allele status. Int J Environ Res Public Health. 2014; 11:10663-10693

27.

Wolford ST, Schroer RA, Gallo PP, Gohs FX, Brodeck M, Falk HB, Ruhren R. Age-related changes in serum chemistry and hematology values in normal Sprague-Dawley rats. Fundam Appl Toxicol. 1987; 8:80-88

28.

Kojima S, Haruta J, Enomoto A, Fujisawa H, Harada T, Maita K. Age-related hematological changes in normal F344 rats: during the neonatal period. Exp Anim. 1999; 48:153-159

29.

Piao Y, Liu Y, Xie X. Change trends of organ weight background data in Sprague Dawley rats at different ages. J Toxicol Pathol. 2013; 26:29-34