In the experimental group, total iron concentrations were higher by an order of magnitude compared with piglets from the control group. The highest serum iron concentrations (p < 0.01) were in the experimental group at 24 h following Fe³⁺-dextran administration (Table 1).

The average total white blood cell (WBC) counts did not differ significantly between the experimental and the control group at any time point (Table 2).

There was an increase in WBC counts in 4 hours in both groups of piglets. At 24 hours after iron dextran administration the WBC counts in the control group returned to baseline. In the experimental group the WBC counts had not yet returned to baseline values.

There was a relative shift in the composition of the leukocyte population. In both groups of piglets the percentage of lymphocytes dropped. The decrease was nevertheless greater in the experimental group. The percentage of neutrophils increased in both groups of piglets. The decrease in lymphocytes and the increase in neutrophils were greater in the experimental group. The neutrophils recovery to baseline levels was also slower in iron treated group.

Evident changes were observed in monocyte counts. After an hour, a decrease in monocyte counts inline was found in the experimental group. We found also a decrease in eosinophil counts up to 4 h in both groups of piglets. The relative shift in the leukocyte population is indicative of stress. Brohee et al. [13] also reported monocytopaenia, eosinopaenia, lymphopaenia and neutrophilia during acute stress. The greater increase of neutrophils in the experimental group could indicate an additional effect of iron. However this is contradictory to Brock [14], who noted a decrease in neutrophil counts at high iron concentrations.

The decrease in monocyte counts in the experimental group may have been caused by monocyte migration to the site of iron dextran administration. It follows from our results that neither leukocyte counts nor cortisol concentrations are specific sensors of the response to iron dextran application in piglets.

Serum cortisol concentrations were determined at the first sampling (0 h) and 24 hours after Fe³⁺-dextran administration. The cortisol concentrations increased significantly in both groups.The handling stress also influenced immune cells and cortisol levels in the control group of piglets which received no iron dextran.

Mean neopterin levels in all the animals prior to the Fe³⁺-dextran administration were 18.62 ± 2.22 nmol·L⁻¹. An hour after Fe³⁺-dextran administration, neopterin concentrations of experimental group piglets rose significantly (p < 0.01). Neopterin levels in the control group, on the other hand, showed no major variations during the entire experiment. In the experimental group, neopterin concentrations at the 4 hour interval were always significantly higher compared with the controls (p < 0.01). By the end of the 24 hour period, neopterin concentrations in the experimental group had dropped significantly, but they remained statistically higher compared to those of the controls (p < 0.05; Figure 1).

A similar trend was ascertained in biopterin, i.e., the other of the pterins investigated. An hour after Fe³⁺-dextran administration, significantly higher serum biopterin concentrations in piglets were found compared with pre-administration levels (p < 0.01). After 4 hours, concentrations were still higher compared with the controls. At 24 hours, biopterin concentrations in the serum of experimental piglets dropped but still remained to be higher than in the control group (p < 0.01) (Figure 2).

It follows from our results that the Fe³⁺-dextran administration was followed by a short-term activation of the immune system. There is an ambivalent relationship between iron and immune functions and infection, because, on the one hand, it is an element indispensable for the performance of a number of cellular and immune functions, but, on the other, its deficit has an inhibitory effect [15]. It has been reported that an iron overdose affects immune system. In the study of Walker and Walker [16] high iron concentrations produced by an iron overdose significantly affected the immune system, where iron reduced the phagocytic capacity, affected T-lymphocyte activity and modified lymphocyte distribution at various locations of the immune system. Similarly Cardier et al. [17] mentioned the effects of high iron concentrations on T-lymphocyte distribution in blood, spleen and the mesenterial lymph nodes.

Iron deficiency, on the other hand, is associated with a decrease in neutrophil activity, or, rather, decreased activity of Fe³⁺-dependent enzymes, such as myeloperoxidase [18]. It also suppresses T-lymphocyte blastogenesis and mitogenesis during the immune response to various pathogens [19].

An increase in neopterin and biopterin production was observed already an hour after Fe³⁺-dextran administration. Neopterin and biopterin are closely related to the activation of the Th-1 immune system. These pterin derivatives are produced in the organism by monocytes/macrophages following stimulation by the interferon-gamma (INF-γ) cytokine, which is released by T-lymphocytes and NK cells. Biopterin synthesis also takes place in T-cells, B-cells, in the endothelium, smooth muscle cells, fibroblasts, etc. [20]. Neopterin functions have been the subject of many in vitro studies which suggest that the oxidation status may be affected by the neopterin’s pro-oxidative action [21–23]. NO synthase participating in the production of NO· requires a reduced form of biopterin for its activity. Tetrahydrobiopterin is also the cofactor for aromatic amino acid hydroxylases (PAH-phenylalanine-4-hydroxylase, tyrosine-3-hydroxylase and tryptophan-5-hydroxylase).

It is evident from our experiment that the administration of Fe³⁺-dextran may trigger acute activation of the immune system and production of pterin derivatives which are indicators of the production of pro-inflammatory cytokines (IFN-γ), NO, etc. Further studies with the employment of pro-inflammatory cytokines measurements will be needed to fully characterise these effects.

The variation of neopterin and biopterin values was high in both experimental and control groups. Similar variation was found also in duplicate samples. There is no comparative literature data so far presenting neopterin and biopterin levels in weaned piglets. In our opinion the variation may be explained by the individual stress responses.

There are only a few authors in veterinary medicine who studied the use of pterins in disease diagnosis. For instance, Schrodl et al. [24] investigated the effects of a bacterial infection (Haemophilus parasuis) on porcine serum neopterin levels. In their study they found a decrease in neopterin concentrations compared with the control group. In their experimental model with pigs, Amann et al. [25] evaluated the possibility of using neopterin to monitor heart attacks. Their results, however, suggest that neopterin is not a suitable biomarker of cardiovascular diseases in pigs. Biopterin production in the acute phase of hypoxia-ischemia in newborn piglets was monitored by Fujioka et al. [26] who found that while cerebral production of biopterin in newborn piglets showed no response to hypoxia-ischemia, biopterin blood plasma concentrations responded by a fivefold increase. Ziegler et al. [4] monitored erythrocyte biopterin concentrations in beagles in connection with bone marrow transplantations after its destruction by irradiation. Biopterin was perceived as a biomarker of haemolytic cell proliferation activity.

It follows from the above findings in the area of veterinary medicine that we have very few literary data that can be used for comparative purposes. Our study presented here has its originality, and brings a new angle to the assessment of stress situations in an animal’s organism. Last but not least, it broadens modest list of studies investigating pterins in their untraditional role of sensors of immune system activation which occurs as a response of organism’s internal environment to iron stress.

A total of 22 large white breed (LWB) piglets x Landrace piglets weighing 12 ± 1.15 kg on average were included in the study. The piglets were divided into two groups. Group 1 was the control group (n = 10). Group 2 was the experimental group (n = 12) where piglets received a single i.m. dose of 2.000 mg Fe³⁺-dextran (20 mL Fe³⁺-dextran per piglet, 1 mL contained 100 mg Fe³⁺, i.e., 2.000 mg Fe³⁺). Blood samples were collected from piglets prior to Fe³⁺-dextran administration (0 h), and 1 hour (1 h), 4 hours (4 h) and, lastly, 24 hours (24 h) after Fe³⁺-dextran administration to the experimental group piglets. At the above intervals, blood samples were withdrawn from piglets in both the control and the experimental groups. After precipitation, the blood samples collected were centrifuged at 3.000 rpm for 15 min, and serum was frozen at −18 °C until the final analysis. Blood (serum) samples were handled out of direct sunlight and, whenever possible, in a shaded environment.

EDTA (ethylenediaminetetraacetic acid) was used as an anticoagulant for the haematological examination. The white blood cell count (WBC) was determined by Celtac Alpha haematology analyzer (Nihon Kohden). Differential leukocyte counts were determined after staining blood smears with May-Grünwald and Giemsa-Romanowsky solutions.

Heparin was used as an anticoagulant for the determination of iron concentrations in blood plasma. Blood plasma iron concentrations (Fe) were determined photometrically by measuring iron complexes with ferrozine (set Iron Bio-La-TEST^® PLIVA-Lachema Diagnostics, Czech Republic).

Prior to the actual analysis, the serum samples were properly thawed at room temperature and carefully mixed by gentle turning. For protein removal, 100 μL of 20% trichloroacetic acid were added to 500 μL of serum sample and vortexed for 10 s. After 10 min in dark at room temperature, the samples were centrifuged at 3.000 rpm for 15 min.

The supernatant was filtered through a 0.45 μm nylon membrane filter, and 50 μL of the sample were injected into the HPLC system [27]. The detection was accomplished by means of Alliance 2695 chromatographic system with a fluorescent detector (Waters 2475, USA). The detection was performed at the wavelengths selected as γ_ex = 353 nm and γ_em = 438 nm. The column used was Zorbax Eclipse XDB-C18 (150 × 4.6 mm, 5-Micron; Agilent, USA). The analysis was done in an isocratic mode, using water/acetonitrile (97:3, v/v) as the mobile phase. The mobile phase flow rate was 0.9 mL·min⁻¹, column temperature 35 °C. All materials were HPLC-grade purity.

SPEC C₁₈ AR cartridges of 3 mL with 15 mg solid-phase mass per column (Varian, USA) were used. 500 μL of the sample containing the internal standard (19-nortestosterone, final concentration 2 ng/μL) was allowed to pass through a preconditioned cartridge (500 μL methanol and 500 μL water). The cartridge was then washed with 500 μL acetone/water (10:90, v/v) and after drying the cartridge for 5 min the analyte was eluted with 1 mL acetonitrile.

The sample volume injected into the HPLC system was 20 μL. Cortisol was separated by an isocratic elution method (65:35 acetonitrile/water, v/v) on the Zorbax Eclipse XDB-C18 column (150 × 4.6 mm, 5-Micron; Agilent, USA). The mobile phase flow rate was 1 mL·min⁻¹, column temperature was 30 °C, and UV detection was done at 245 nm.

Peak identification was based on the comparison of the retention time with the standards for the studied biomolecules. The linearity for neopterin was measured in the concentration range of 0.6–250 ng/mL (y = 9369.5x + 2111.4; R² = 0.999), for biopterin in the range of 1.6–52.0 ng/mL (y = 18602x − 7446; R² = 0.999) and for cortisol in the range of 0.01–20.0 μg/mL (y = 23.71x + 538.87; R² = 0.999). Neopterin detection limit was 0.5 ng/mL (3 S/N), for biopterin was 1.3 ng/mL, and for cortisol was 20.1 ng/mL (3 S/N). Determination limit for neopterin was 1.49 ng/mL (10 S/N), for biopterin 4.33 ng/mL, and for cortisol 64.6 ng/mL (10 S/N). The method’s yield was 91%, 94% and 89% for neopterin, biopterin and cortisol, respectively.

Statistical evaluation of results was carried out using Statistica software 8.0 for Windows (StatSoft). Data were first tested for normality (Kolmogorov-Smirnov test) and homoskedasticity of variance (Bartlett’s test). If those conditions were satisfied, one-way analysis of variance (ANOVA) was employed to determine whether there were any significant differences in measured variables between groups. When a difference was detected (p < 0.05), Tukey’s multiple comparison test was applied to identify which treatments were significantly different.