text:
Alaa G.M. Osman1*, Khaled Y. AbouelFadl2, Abd El Baset M. Abd El Reheem1, Usama M. Mahmoud3, Werner Kloas4,5 and Mohsen A. Moustafa1
1Department of Zoology, Faculty of Science, Al-Azhar University (Assiut Branch), Assiut, Egypt
2Department of Aquatic Ecology, Faculty of Fish and Fisheries Technology, Aswan University, Aswan, Egypt
3Department of Zoology, Faculty of Science, Assiut University, Assiut, Egypt
4Department of Ecophysiology and Aquaculture, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm, Berlin, Germany
5Department of Endocrinology, Institute of Biology, Faculty of Life Sciences, Humboldt University of Berlin, Berlin, Germany
Received Date: 19.01.2018; Accepted Date: 29.01.2018; Published Date: 30.01.2018
In this work, we explore new sights of biomarker research and establish the use of blood parameters and erythron profile in wild fish. Water quality assessment along the Nile course concluded higher mean values of the detected physicochemical parameters in water collected from downstream sites. The mean values of nearly all the detected haematological parameters were significantly lower in the blood of Nile tilapia and African catfish collected from downstream (contaminated) compared to upstream sites. Lower cellular and nuclear areas and cellular and nuclear shape factor were recorded in the erythrocytes of fish collected from downstream compared to those caught from upstream sites. This was confirmed by higher immature ratios of red cells in the blood of fish sampled from downstream sites. Karyorrhectic and enucleated erythrocytes were recorded to be higher in the blood of fish collected from downstream sites. The levels of all the selected biochemical variables in the blood of both fish species were recorded to be significantly higher in downstream sites. The detected blood variables and erythrocyte malformations were proven to be suitable for bio-monitoring of aquatic pollution. The results revealed speciesspecific differences in sensitivities, suggesting that Nile tilapia may serve as a more sensitive test species compared to African catfish.
Blood biomarkers; Water pollution; Erythron profile; River Nile; African catfish; Nile tilapia
Fresh water resources all over the world such as rivers are polluted with a variety of solid and liquid wastes. One of the most impressive large rivers worldwide is in Egypt the river Nile. The river Nile has become polluted due to discharge of untreated waste, dumping of industrial effluents, and run-offs from agricultural fields, making it a model for a polluted ecosystem to asses biomarker responses in fish (Osman 2012). These pollutants are taken directly from the river Nile by the gills or through the intestines during the transit of contaminated food. Then they are distributed throughout the body via the blood. Blood cells are some of the first cells to come into contact with and be affected by aquatic pollution (Sadauskas-Henrique et al., 2011). So, the blood reveal measurable physiological changes in fish more rapidly than any physiological assessment parameters (Ezeri et al., 2004) and also respond to changes in other tissues due to exposure of pollutants (Ruas et al., 2008).
Recently, hematological and biochemical variables have become promising biomarkers in measuring the effects of aquatic pollution in fish, because blood parameters respond to low doses of pollutants. Blood parameters are considered as good physiological biomarkers of the whole body, and therefore, they are important in diagnosing the structural and functional status of fish exposed to environmental pollutants (Seriani et al., 2011). Typically, hematological and biochemical variables are unspecific in their responses towards environmental stressors. Nevertheless, they may provide important information in effect assessment studies by providing an indication to the general physiology and health status of fishes (Beyer et al., 1996). These indices could provide information comparable to that given by human blood variables. Several workers have investigated the hematological changes of pollutants in fish (Osman et al., 2010b; Mekkawy et al., 2011; Sayed et al., 2011; Heier et al., 2013), and the use of blood biomarkers in fisheries research is growing rapidly as it is very important in toxicological research environmental monitoring and predicting of fish health conditions (Bitten-Court et al., 2003).
Fish erythrocytes, however, are more responsive to environmental stresses, and often vary in morphology and effectiveness of oxygen transport. (Lowe-Jinde and Niimi, 1983) suggested that differential erythrocyte ratios may be a suitable index for fish laboratory and field studies. Because of the heterogeneity of erythrocytes in circulation, (Houston, 1997) proposed the use of an erythron profile as an alternative measure of contaminant exposure. An erythron profile describes the relative abundances of various developmental stages of red blood cells (Aliko et al., 2012). Houston (1997) argued that such a profile provides a more sensitive means for assessing contaminant exposure than the classic blood indices. The objectives of this study were to explore new sights of biomarker research and to establish the use of blood parameters and erythron profile in wild fish populations.
Sampling sites
Six sites were selected along the whole course of the River Nile from its start at Aswan to its estuaries at Rosetta and Damietta (Figure 1).
Water quality assessment
Water quality criteria [electrical conductivity, pH, water temperature, chemical oxygen demand (COD), total organic compound (TOC), total solids (TS), ammonia (NH3), nitrate (NO3), orthophosphate (o-PO4), chloride (Cl) florid (F) sulfate (SO4), phenolics (Phenol)] of the chosen sites were monitored bimonthly. Total Pb, Cu, Cr, Hg, and Cd were measured using graphite furnace AA (GFAA) spectroscopy. Sampling and assessment of water quality were done according to the traditional manual methods (APHA 2005).
Fish sampling
420 Nile tilapia and African catfish were caught bimonthly by gill net from the selected sites (210 specimens from each species; body weight ranging from 240-290 g for Nile tilapia and from 280-350 g for African catfish).
Blood sampling
Two blood samples of the peripheral blood were collected from cardiac puncture as described by Osman et al. (2011). No anesthetic was applied to fish as it may affect blood parameters. First sample was freshly collected in a small glass tubes containing heparin solution (0.2 ml/ml blood) as anticoagulant. This sample was used for hematological analysis. Second sample was collected and left to coagulate for 15–20 min at 4°C prior to centrifugation for 20 min at 3,000 rpm to separate serum. The fresh serum was subjected to biochemical analysis.
Hematological parameters
The whole blood was used for the estimation of hemoglobin concentration (Hb), hematocrit value (Hct), red blood cells count (RBCs), and thrombocytes count by using automated technical analyzer (Celltac α MEK- 6400J/K). Mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) were calculated according to Dacie and Lewis (2002). White blood cells count (WBCs) and white blood cell differential were calculated using the method according to Shaw (1930). Neutrophils, lymphocytes, eosinophils and monocytes were counted using an Olympus oilimmersion light microscope with 1000 X magnification.
Erythron profile
Two blood smears were immediately made with drops of fresh blood and allowed to air dry. Slides were stained with 5% Giemsa and Eosin & Hematoxylin stains. Slides were examined using an Olympus oil-immersion light microscope with 1000 X magnification and images were captured using a high performance camera (HDCE-50B) and analyzed using Image–Pro plus software (version 4 for windows). The major and minor axis length, area, and shape factor (=4π × area/perimeter 2) of erythrocyte cells and nuclei were measured (Rowan, 2007). To determine the numbers of karyorrhetic, dividing, and enucleate erythrocytes, seven fields were randomly selected on each slide. The numbers of each cell type were counted, and data were recorded as number of cells per seven fields (Rowan, 2007). To determine the developmental stages of erythrocytes, 100 erythrocytes were randomly selected and visually classified by shape into immature, intermediate, or mature.
Biochemical parameters
Colorimetric determinations of the selected biochemical parameters were performed using spectrophotometer (Jasco-V530). The absorbency of the detected sample was examined at an appropriate wavelength ranging from 340 to 546 nm according to the parameter tested. Total protein (g/dl), cholesterol (mg/dl), triglycerides (mg/dl), calcium (mg/dl), chlorides (mg/dl), alkaline phosphatase activity (ALP, IU/L), aspartate aminotransferase (AST, U/I), alanine aminotransferase (ALT, U/I), uric acid activity (mg/dl), creatinine (mg/dl), and serum glucose (mg/dl) were determined using commercial diagnostic kits (bioMérieux, France), following the manufacturer's instruction.
Statistical Analysis
Data are presented as the means ± standard deviation. Data were analyzed by one-way analysis of variance (ANOVA) test using data analysis software system (STATISTICA 2007) and figured by Microsoft Excel. Means were tested using Fisher Least Significant Difference (LSD) test. Two levels of significance were reported; *p<0.05; **p<0.01. The Pearson's product correlation coefficient was used to determine the relationship between the blood variables and physicochemical parameters in waters samples.
Physico–chemical water parameters
Table 1 shows mean ± SD of the detected physico-chemical parameters of water samples collected from the selected sites. Most of the detected physico-chemical parameters exhibited their highest values in the water of river Nile downstream. For nearly all detected parameters significant differences (p<0.05) were observed between the selected sites. Mean values of conductivity, chemical oxygen demand (COD), total organic carbon (TOC), ammonia (NH3), nitrate (NO3), total solid (TS), sulphate (SO4), chloride (Cl), and orthophosphate were recorded to be higher in the water of Damietta and Rosetta sites compared to other sampled sites. Also most of the detected heavy metals exhibited highest values at Damietta and Rosetta sites. The levels of such parameters were significantly (p<0.05) increased from the start of the river Nile at Aswan toward its estuaries at Damietta and Rosetta sites. All the detected parameters were below the permissible limits in the river Nile at upstream sites. In contrast, the levels of COD, phenol, Pb, Cd, Cr and Hg were above the permissible limits in the water of downstream river Nile (Rosetta and/or Damietta sites).
|Permissible limit
|Parameter (Unit)
|Mean ± SD
|Mean ± SD
|Mean ± SD
|Mean ± SD
|Mean ± SD
|Mean ± SD
|PH (Unit)
|7.86 ± 0.25
|8.01 ± 0.41
|8.15 ± 0.19
|8.27 ± 0.27
|8.40 ± 0.44
|8.23 ± 0.45
|0.26 ± 0.03
|0.27 ± 0.07
|0.29 ± 0.09
|0.34 ± 0.07
|0.38 ± 0.10
|0.58± 0.11
|Temperature ( °C )
|22.68 ± 2.22
|23.72 ± 3.15
|23.33 ± 4.67
|23.64 ± 4.24
|25.29 ± 5.66
|24.53± 4.44
|Over 5ºC
|Chemical oxygen demand (ppm)
|10.58 ± 3.62
|9.17 ± 3.04
|10.63 ± 2.18
|7.88 ± 2.15
|8.59 ± 2.51
|18.00 ± 10.38
|Total organic carbon (ppm)
|5.65 ± 2.88
|5.89 ± 1.93
|5.74 ± 0.92
|4.93 ± 2.58
|5.21 ± 2.64
|8.61 ± 6.06
|Total solid (ppm)
|198.88 ± 14.09
|212.67 ± 23.70
|227.75 ± 16.29
|259.50 ± 44.33
|305.25 ± 55.96
|411.25 ± 85.66
|Ammonia (ppm)
|0.11 ± 0.16
|0.01 ± 0.002
|0.02 ± 0.01
|0.01 ± 0.01
|0.05 ± 0.05
|0.15 ± 0.09
|Nitrate (ppm)
|0.89 ± 0.40
|0.77 ± 0.39
|0.51 ± 0.21
|0.72 ± 0.63
|1.13 ± 1.13
|2.05 ± 2.27
|Chlorides (ppm)
|7.05 ± 1.44
|8.56 ± 1.90
|10.03 ± 2.58
|15.28 ± 5.10
|22.42 ± 4.93
|40.55 ± 6.72
|Florid (ppm)
|0.29 ± 0.15
|0.32 ± 0.14
|0.39 ± 0.16
|0.31 ± 0.13
|0.30 ± 0.10
|0.37 ± 0.08
|Ortho phosphate (ppm)
|0.01 ± 0.02
|0.037 ± 0.04
|0.10 ± 0.090
|0.03 ± 0.034
|0.13 ± 0.07
|0.21 ± 0.19
|Sulphate (ppm)
|34.16 ± 13.30
|45.30 ± 15.37
|47.95 ± 14.11
|45.25 ± 15.81
|51.00 ± 12.76
|68.13 ± 11.42
|Phenol (ppm)
|0.01 ± 0.02
|0.01 ± 0.02
|0.01 ± 0.02
|0.01 ± 0.01
|0.03 ± 0.02
|0.04 ± 0.02
|Pb (ppm)
|0.01 ± 0.02
|0.02 ± 0.01
|0.02 ± 0.02
|0.02 ± 0.01
|0.03 ± 0.04
|0.06 ± 0.08
|Cd (ppm)
|0.004 ± 0.004
|0.002 ± 0.002
|0.01 ± 0.01
|0.002 ± 0.002
|0.02 ± 0.02
|0.01 ± 0.02
|Cu (ppm)
|0.03 ± 0.03
|0.03 ± 0.02
|0.03 ± 0.03
|0.03 ± 0.03
|0.03 ± 0.03
|0.0544 ± 0.027
|Cr (ppm)
|0.003 ± 0.002
|0.01 ± 0.01
|0.01 ± 0.01
|0.01 ± 0.01
|0.05 ± 0.06
|0.10 ± 0.15
|Hg (ppm)
|0.0000 ± 0.001
|0.0004 ± 0.001
|0.0005 ± 0.001
|0.0009 ± 0.001
|0.002 ± 0.001
|0.003 ± 0.001
Table 1: Physicochemical parameters of the water samples collected from different sites along the whole course of the river Nile, Egypt (n=108 samples).
Hematological variables
The mean values of RBCs, Hb, Hct, MCV, MCH, MCHC, and thrombocyte of Nile tilapia and African catfish are shown in Table 2. The statistical analysis of these variables exhibited significant differences among the selected sites for both fish species. The mean values of RBCs, Hb, Hct, MCV in the blood of Nile tilapia and African catfish decreased significantly (p<0.01) from Aswan to Rosetta and Damietta sites (Table 2). In the same way, mean concentration of thrombocyte decreased in the blood of fish collected from Rosetta and Damietta (Table 2). In contrast, MCH and MCHC in the peripheral blood of both fish species increased significantly (p<0.01) from upstream to downstream river Nile.
|RBCs (X106/ µL)
|Oreochromis niloticus
|2.24 ± 0.35
|2.39 ± 0.35
|2.05 ± 0.38
|1.88 ± 0.37**
|1.49 ± 0.33**
|1.51 ± 0.4**
|Clarias gariepinus
|2.51 ± 0.4
|2.49 ± 0.35
|2.21 ± 0.41*
|2.02 ± 0.35**
|1.66 ± 0.39**
|1.57 ± 0.39**
|Hb (g/dL)
|Oreochromis niloticus
|11.55 ± 0.88
|11.37 ± 0.77
|10.47 ± 0.98*
|9.81 ± 1.38**
|8.39 ± 1.32**
|7.97 ± 1.11**
|Clarias gariepinus
|11.65 ± 0.79
|11.59 ± 0.96
|10.82 ± 1.24*
|10.39 ± 1.02**
|8.63 ± 1.23**
|8.11 ± 1.19**
|Oreochromis niloticus
|38.76 ± 4.28
|37.58 ± 3.72
|31.89 ± 5.59**
|28.2 ± 4.03**
|21.59 ± 5.26**
|20.49 ± 5.48**
|Clarias gariepinus
|38.98 ± 4.59
|38.57 ± 4.15
|33.9 ± 6.17**
|29.59 ± 4.89**
|22.89 ± 5.0**
|20.78 ± 5.29**
|MCV (fL)
|Oreochromis niloticus
|175.58 ± 21.30
|159.16 ± 18.69*
|156.41 ± 19.58**
|153.07 ± 24.73**
|145.95 ± 26.77**
|140.39 ± 31.19**
|Clarias gariepinus
|157.1 ± 16.38
|156.53 ± 19.93
|154.71 ± 22.88
|147.28 ± 13.85*
|140.08 ± 24.88**
|135.53 ± 33.58**
|MCH (Pg)
|Oreochromis niloticus
|52.41 ± 5.85
|48.25 ± 5.24*
|51.85 ± 5.74
|53.01 ± 6.31
|57.33 ± 9.48*
|55.17 ± 10.15
|Clarias gariepinus
|47.33 ± 5.56
|47.08 ± 4.77
|49.65 ± 5.53
|52.31 ± 4.91*
|53.38 ± 7.14**
|53.54 ± 9.68**
|MCHC (g/dL)
|Oreochromis niloticus
|30.11 ± 2.07
|30.45 ± 1.67
|33.46 ± 3.69*
|35.08 ± 3.85**
|40.01 ± 6.94**
|40.9 ± 9.03**
|Clarias gariepinus
|30.2 ± 2.39
|30.18 ± 1.34
|32.5 ± 4.03
|35.87 ± 3.71**
|38.79 ± 6.52**
|40.87 ± 7.23**
|T (X103/µL)
|Oreochromis niloticus
|473.69 ± 53.08
|467.99 ± 72.46
|429.86 ± 45.40
|393.19 ± 60.71
|351.24 ± 59.88
|321.88 ± 62.5*
|Clarias gariepinus
|425.13 ± 99.64
|404.65 ± 51.62
|408.74 ± 46.75
|386.25 ± 70.29
|307.45 ± 64.48*
|371.93 ± 72.83
Table 2: Mean values ± SD of red-blood-cells (RBCs) count, hemoglobin (Hb) content, hematocrit (HCT) value, mean corpuscular value (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and thrombocytes (T) concentrations of Nile tilapia and African catfish collected from the whole course of the river Nile, Egypt.
Table 3 shows the mean leukocytes, monocytes, lymphocytes, neutrophils and eosinophils concentrations in the peripheral blood of Nile tilapia and African catfish collected from the river Nile, Egypt. The number of WBCs decreased significantly (p<0.01) from upstream to downstream river Nile recording the lowest values at Rosetta and/or Damietta (Table 3). In the same way, significant (p<0.01) reductions in the percentage distribution of lymphocytes and monocytes were observed from upstream to downstream river Nile (Table 3). In contrast, the percentage distribution of neutrophils and eosinophils increased significantly (p<0.01) from upstream to downstream river Nile recording the highest values in the blood of fish sampled from Rosetta (Table 3). The mean number of leukocytes and the mean percentage distribution of neutrophils, monocytes, lymphocytes and eosinophils were higher in the blood of African catfish than those in the blood of Nile tilapia collected from the same sites and at the same sampling time (Table 3).
|Oreochromis niloticus
|47.22 ± 10.89
|50.65 ± 8.15
|46.41 ± 7.44
|42.59 ± 7.64*
|35.67 ± 7.55**
|36.29 ± 9.2**
|Claris gariepinus
|53.13 ± 8.94
|59.16 ± 8.22
|49.57 ± 6.8
|47.21 ± 9.01*
|39.21 ± 7.58**
|37.94 ± 8.05**
|Lymphocytes (%)
|Oreochromis niloticus
|59.5 ± 4.17
|59.4 ± 5.21
|59.3 ± 4.61
|59.6 ± 4.53
|57 ± 4.98*
|56.6 ± 5.64**
|Claris gariepinus
|61.4 ± 6.83
|60.5 ± 4.45
|59.9 ± 4.79
|59.1 ± 5.49
|56.1 ± 5.06
|54.7 ± 4.39
|Monocytes (%)
|Oreochromis niloticus
|14.47 ± 4.06
|13.15 ± 4.08
|10.51 ± 3.24**
|8.09 ± 2.96**
|5.59 ± 2.01**
|4.78 ± 1.72**
|Claris gariepinus
|16.29 ± 9.28
|13.73 ± 3.78
|10.33 ± 3.19**
|8.35 ± 2.11**
|5.97 ± 1.83**
|4.93 ± 1.66**
|Neutrophils (%)
|Oreochromis niloticus
|24.22 ± 4.12
|25.64 ± 5.02
|28.22 ± 3.97
|30.11 ± 4.49**
|35.2 ± 4.26**
|36.79 ± 5.44**
|Claris gariepinus
|25.7 ± 8.81
|23.94 ± 4.43
|27.82 ± 2.97
|30.34 ± 4.61
|35.87 ± 5.46**
|38.35 ± 4.2**
|Eosinophils (%)
|Oreochromis niloticus
|1.8 ± 0.95
|1.79 ± 0.87
|1.93 ± 0.72
|2.16 ± 0.87
|2.23 ± 0.79**
|1.9 ± 1.01**
|Claris gariepinus
|1.79 ± 8.3
|1.88 ± 0.94
|1.98 ± 0.86
|2.17 ± 1.08
|2.1 ± 0.91**
|1.98 ± 0.87**
Table 3: Mean values ± SD WBCs count, lymphocytes, monocytes, neutrophils and eosinophils concentration of Nile tilapia and African catfish collected from the whole course of the river Nile, Egypt
Erythron profile
In the circulating blood of Nile tilapia and African catfish, erythrocytes in various stages of differentiation were recorded; mature, intermediate and immature (Figure 2A and 2B). Significant differences (p<0.01) were recorded in the relative abundance of the three maturity stages in the peripheral blood of both fish species among the selected sites (Figure 2C and 2D). The percentage of the immature stages increased significantly (p<0.01) from upstream to downstream river Nile recording the highest values in the blood of fish sampled from Rosetta site (Figure 2C and 2D). In contrast, the percentage distribution of the mature erythrocyte recording the highest value in the blood of fish collected from Kena at upstream river Nile (Figure 2C and 2D).
Figure 2: Erythrocytes in various stages of differentiation from Nile tilapia (A) and African catfish (B) IM: immature, IN: intermediate, M: mature. Giemsa and H&E stains. Relative abundance of immature (blue), intermediate (brawn), and mature (green) erythrocytes from Nile tilapia (C) and African catfish (D) collected from the whole course of the river Nile, Egypt. Significant compared to Aswan at (*p<0.05, **p<0.01).
The following classification for erythrocytes were found in the circulating blood of both fish species: karyorrhectic or degenerating erythrocytes (Figure 3A and 3B), dividing erythrocytes (Figure 3C), and enucleate erythrocytes (Figure 3D). Three forms of karyorrhectic or degenerating erythrocytes were observed during the present study in the blood of Nile tilapia and African catfish namely cytoplasmic swelling, membrane disintegration (nuclear deformation), and nuclear shadow (smudge cell remaining after cell death) (Figure 3A and 3B). Significant differences (p<0.05) in the mean numbers of karyorrhectic erythrocytes were recorded among the selected sites (Table 4) for both fish species. The highest number of karyorrhectic erythrocytes were recorded in the blood of fish sampled from Rosetta compared to other sites. Few numbers of the divided erythrocytes were recorded in the blood of Nile tilapia and African catfish along the whole course of the river Nile. No significant differences in the number of dividing erythrocytes were observed among the selected sites for both fish species (Table 4). Enucleate erythrocytes were rarely observed in the blood of fish during the period of the current work. Enucleate cells completely disappeared in the blood of fish sampled form upstream river Nile (Aswan and Kena). Significant differences (p<0.01) in the mean number of enucleate erythrocytes in the blood of Nile tilapia and African catfish among the selected sites were recorded (Table 4). The mean numbers of the malformed erythrocytes (karyorrhectic, dividing and enucleate) were higher in the blood of Nile tilapia than those in the blood of African catfish collected from the same sites and at the same sampling time.
Figure 3: Karyorrhectic erythrocytes in the peripheral blood of Nile tilapia (A) and African catfish (B) 1. Cytoplasmic swelling 2. Membrane disintegration 3. Nuclear shadow. C&D show representative enucleate (En) and dividing (Div) erythrocytes in the peripheral blood of Nile tilapia. Giemsa and H&E stains.
|karyorrhectic erythrocytes Per 7 fields
|Oreochromis niloticus
|7.94 ± 2.24
|9.47 ± 2.95
|10.1 ± 2.58
|13.41 ± 3.09*
|20.57 ± 4.15**
|24.7 ± 4.75**
|Claris gariepinus
|9.44 ± 2.32
|7.75 ± 2.55
|8.84 ± 2.53
|13.78 ± 3.25*
|19.3 ± 3.79**
|23 ± 4.58**
|Dividing erythrocytes Per 7 fields
|Oreochromis niloticus
|1.13 ± 0.84
|1.91 ± 1.04
|3.28 ± 1.12
|3.38 ± 1.29
|3.63 ± 1.16
|4.58 ± 1.89
|Claris gariepinus
|2.03 ± 1.09
|1.19 ± 0.81
|2.31 ± 1.22
|3.19 ± 1.07
|3.63 ± 1.28
|3.99 ± 1.58
|Enucleate erythrocytes Per 7 fields
|Oreochromis niloticus
|0.094 ± 0.20
|0.22 ± 0.36
|0.51 ± 0.63*
|0.76 ± 0.79**
|Claris gariepinus
|0.031 ± 0.09
|0.38 ± 0.56**
|0.48 ± 0.59**
|0.69 ± 0.82**
Table 4: Mean number ± SD of karyorrhectic, dividing and enucleate erythrocytes of Nile tilapia and African catfish collected from the whole course of the river Nile, Egypt
Measurements of cellular and nuclear major and minor axis length, cellular and nuclear area, and cellular and nuclear shape factor were exhibited remarkable variations in size and shape of the erythrocytes among sites (Table 5). The lower cellular and nuclear area and the lower cellular and nuclear shape factor were recorded in the blood of fish collected from Damietta and Rosetta sites compared to other sites (Table 5). Cellular factor shape of the erythrocytes inversely correlated (R=-0.72, p=0.0002) with immature erythrocytes and directly correlated (R=0.070, p=0.0002) with mature erythrocytes of Nile tilapia and African catfish collected from the whole course of the river Nile.
|Major axis (μm)
|Oreochromis niloticus
|Claris gariepinus
|Minor axis(μm)
|Oreochromis niloticus
|Claris gariepinus
|Oreochromis niloticus
|Claris gariepinus
|Shape factor
|Oreochromis niloticus
|Claris gariepinus
|Major axis (μm)
|Oreochromis niloticus
|Claris gariepinus
|Minor axis (μm)
|Oreochromis niloticus
|Claris gariepinus
|Area (μm2)
|Oreochromis niloticus
|Claris gariepinus
|Shape factor
|Oreochromis niloticus
|Claris gariepinus
Table 5: Means ± SD of major and minor axis length, area, and shape factor of red blood cells and their nuclei of Nile tilapia and African catfish collected from the whole course of the river Nile, Egypt.
Biochemical variables
The mean concentrations of cholesterol, triglyceride, total protein, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glucose, calcium (Ca), chloride (Cl), uric acid, creatinine, urea and sodium (Na) in blood serum of Nile tilapia and African catfish are shown in Table 6. Significant (p<0.01) differences were observed in the mean values of all the detected biochemical variables for both fish species among the selected sites. The mean concentrations of all the biochemistry parameters increased significantly (p<0.01) in the blood serum of fish collected from downstream river Nile compared to those sampled from upstream sites (Table 6).
|Cholesterol (mg/dl)
|Oreochromis niloticus
|117.4 ± 13.27
|123.1 ± 18.9
|157.9 ± 15.8*
|178.3 ± 20.3**
|226.9 ± 23.9**
|204.9 ± 22.7**
|Clarias gariepinus
|162.1 ± 20.9
|178.6 ± 13.3
|195.2 ± 21.1*
|227.1 ± 15.8**
|229.5 ± 22.7**
|261.7 ± 22.8**
|Triglycerides (mg/dl)
|Oreochromis niloticus
|111.6 ± 11.13
|122.9 ± 15.4
|155.6 ± 12.2**
|182.2 ± 16.5**
|204.7 ± 18.9**
|200.2 ± 18.4**
|Clarias gariepinus
|129.6 ± 10.95
|149.14 ± 10.9
|175.79 ± 16.3**
|181.6 ± 16.5**
|176.7 ± 13.12**
|195.2 ± 21.9**
|Total protein (g /dl)
|Oreochromis niloticus
|5.26 ± 0.94
|5.1 ± 0.99
|5.65 ± 1.22
|6.1 ± 0.96*
|6.69 ± 1.1**
|6.9 ± 0.99**
|Clarias gariepinus
|5.44 ± 1.03
|6.31 ± 0.92
|6.64 ± 0.93**
|6.1 ± 1.33**
|6.7 ± 1.95**
|7.0 ± 1.2**
|Alanine aminotransferase (ALT) U/I
|Oreochromis niloticus
|8.41 ± 2.47
|8.97 ± 2.76
|14.55 ± 3.73**
|19.09 ± 3.68**
|28.3 ± 4.55**
|31.14 ± 5.99**
|Clarias gariepinus
|10.16 ± 3.07
|11.38 ± 3.07
|14.94 ± 4.3**
|19.47 ± 4.48**
|24.28 ± 4.35**
|26.3 ± 5.28**
|Aspartate aminotransferase (AST) U/I
|Oreochromis niloticus
|11.34 ± 3.58
|15.34 ± 4.43
|21.59 ± 3.99*
|25.63 ± 5.6**
|39.97 ± 5.87**
|39.39 ± 6.43**
|Clarias gariepinus
|13.53 ± 3.1
|15.8 ± 4.15
|22.34 ± 4.08**
|27.88 ± 5.15**
|34.6 ± 4.97**
|35.84 ± 6.8**
|Alkaline phosphates (ALP) mg/dl
|Oreochromis niloticus
|90.36 ± 10.99
|85.01 ± 9.51
|105.9 ± 13.3*
|110.9 ± 8.75**
|137.4 ± 12.6**
|136.2 ± 16.6**
|Clarias gariepinus
|83.24 ± 8.45
|95.1 ± 10.84
|109.1 ± 9.97**
|128.2 ± 12.3**
|147.6 ± 15.3**
|150.7 ± 17.8**
|Uric acid
|Oreochromis niloticus
|4.57 ± 0.84
|3.9 ± 0.71
|4.18 ± 0.9
|4.8 ± 1.1
|4.88 ± 0.92
|4.8 ± 0.94
|Clarias gariepinus
|4.03 ± 0.75
|4.5 ± 0.94
|4.73 ± 0.78
|5.23 ± 1.16**
|4.84 ± 0.94*
|5.46 ± 1.1**
|Oreochromis niloticus
|11.67 ± 3.37
|14.09 ±2.63
|21.98 ± 4.3**
|33.3 ± 5.1**
|31.19 ± 5.69**
|39.29 ± 7.5**
|Clarias gariepinus
|17.1 ± 4.89
|15.97 ± 4.07
|32.11 ± 5.57**
|41.03 ± 6.71**
|41.96 ± 6.04**
|48.5 ± 9.1**
|Oreochromis niloticus
|81.2 ± 8.5
|83.34 ± 9.39
|80.29 ± 11.4
|98.89 ± 12.90**
|99.6 ± 10.57**
|114.3 ± 13.9**
|Clarias gariepinus
|91.65 ± 8.9
|88.67 ± 11.01
|87.38 ± 14.42
|106.64 ± 11.9
|116.5 ± 8.8**
|111.8 ± 12.57
|Creatinine (mg/dl)
|Oreochromis niloticus
|0.66 ± 0.15
|0.61 ± 0.14
|0.85 ± 0.22
|1.55 ± 0.45
|2.28 ± 0.61*
|2.69 ± 0.57**
|Clarias gariepinus
|4.14 ± 0.69
|6.11 ± 1.3
|5.19 ± 1.14
|6.03 ± 1.23
|6.8 ± 1.85
|8.98 ± 2.3**
|Urea (mg/dl)
|Oreochromis niloticus
|18.71 ± 2.92
|15.89 ± 3.85
|21.57 ± 4.36
|27.09 ± 5.79**
|31.08 ± 6.11**
|34.57 ± 6.2**
|Clarias gariepinus
|20.44 ± 3.84
|21.17 ± 3.65
|21.44 ± 5.54
|27.2 ± 4.24
|31.58 ± 6.49**
|33.22 ± 6.5**
|Glucose (mg/dl)
|Oreochromis niloticus
|73.39 ± 10.22
|65.91 ± 12.04
|108 ± 24.1**
|111.9 ± 11.9**
|144.9± 16.35**
|159.3 ± 17.2**
|Clarias gariepinus
|77.2 ± 15.41
|74.19 ± 15.5
|116.3± 20.3**
|132.6 ± 9.87**
|154.9 ± 15.8**
|146.5 ± 16.3**
|Sodium (mmol/L)
|Oreochromis niloticus
|98.1 ± 9.84
|97.6 ± 10.78
|118.13 ± 9.4**
|147.1 ± 7.69**
|146.5 ± 7.6**
|150.6 ± 8.12**
|Clarias gariepinus
|98.7 ± 11.41
|97.2 ± 10.98
|119.7± 7.95**
|135.7 ± 7.57**
|136.9 ± 8.4**
|147.7 ± 8.1**
Table 6: Mean concentrations ± SD of the selected biochemical parameters in blood serum of Nile tilapia and African catfish collected from different sites along the whole course of the river Nile, Egypt.
Water quality is the major factor responsible for individual variation in fish hematology. Water quality assessment along the whole course of the river Nile concluded higher mean values of nearly all the detected physicochemical parameters in water collected from sampling sites downstream river Nile compared to those collected from upstream river Nile. Such increase proves the presence of large quantities of organic and inorganic pollutants in Rosetta and Damietta water. Mean values of conductivity, chemical oxygen demand, total organic carbon, ammonia, nitrate, total solid, sulphate, chloride, and orthophosphate were recorded to be significantly (p<0.05) higher in the water of downstream sites compared to other sampled sites. Also most of the detected heavy metals exhibited highest values at Damietta and Rosetta sites. The levels of chemical oxygen demand, phenol, Pb, Cd, Cr and Hg were above the permissible limits in the water of downstream river Nile (Rosetta and/or Damietta sites. This finding was expected due to the fact that the level of contamination is greater downstream river Nile, compared to upstream sampling sites, where more domestic and industrial effluents have been released into the Nile without adequate treatment (Osman and Kloas, 2010). It was estimated that the aquatic environment of downstream areas receives more than 3 million cubic meters daily of untreated or partially treated domestic, industrial wastes, and, in addition, agricultural drainage water (El-Naggar et al., 2009).
Hematological variables
Since hematological and blood biochemical parameters are influenced by a variety of environmental stressors, they have the potential to be used as biomarkers of the detected river Nile pollution. Their evaluation in fish has become an important means of understanding the toxicological impacts of exposure hazards (Borges et al., 2007; Sudova et al., 2009; Li et al., 2011). In the present study significant reductions in the values of RBCs, Hb, Hct and MCV were observed in the blood of Nile tilapia and African catfish collected from downstream sites (polluted sites) compared to those collected from less polluted upstream areas. The present results find supports from Summarwar (2012) who recorded remarkable reduction in the levels of RBCs, Hb, Hct and MCV in the blood of Clarias batrachus inhabiting polluted sites compared to those caught from clean site. Numerous studies have shown that the peripheral RBCs, Hb, Hct and MCV of fish displayed decrease incidence after exposure to different pollutants under field and lab conditions (Svoboda et al., 2001; Singh and Tandon, 2009; Vinodhini and Narayanan, 2009; Zutshi et al., 2010; Mekkawy et al., 2011; Gupta and Chandra, 2013). The observed reduction in RBCs, Hb, Hct and MCV values may be attributed to one or more of the following factors: (i) heam-dilution of blood due to damage and later bleeding in the gills (Heath 1996) (ii) the destruction of mature RBCs and the inhibition of erythrocyte production (Musa et al., 2013) (iii) hemolytic crisis that results in severe anemia in fish exposed to heavy metals (Desai and Parikh, 2012).
MCH and MCHC values increased in blood of Nile tilapia and African catfish collected from the estuaries of the river Nile at Damietta and Rosetta sites (contaminated sites) compared to upstream sites. Similarly, Adeyemo (2007) found significant increase in MCH and MCHC values of African catfish exposed to lead. The increase in MCH with decrease in RBC, Hb and MCV values (observed here) was previously recorded by Mukherjee and Shiha (1993) for major carp exposed to cadmium. The perturbation in these blood indices may be attributed to a defense reaction against toxicity.
Thrombocytes are comparable to mammalian blood platelets and play an important role in blood clotting and general defense mechanisms (Kayode and Shamusideen, 2010). It has been reported that the exposure of fish to heavy metals such as lead (Adeyemo, 2007), zinc (Kori-Siakpere and Ubogu, 2008) mercury (Mekkawy et al., 2010) usually decrease thrombocytes indices. In the present study, a lowest concentration of thrombocytes was recorded in the blood of Nile tilapia and African catfish collected from contaminated sites (downstream river Nile) compared to other sites. The present results were supported by the results of Seriani et al. (2011) who recorded a remarkable reduction in thrombocytes of Nile tilapia collected at the polluted pond. Secombes et al. (1992) also found that the thrombocyte fraction has been significantly reduced after exposure to sewage sludge.
Hematological variables in the peripheral blood of Oreochromis niloticus niloticus and Clarias gariepinus exhibited significant (p<0.05) correlation with nearly all the detected chemical and physical parameters along the Nile course. The mean values of RBCs, Hb, Hct and MCV of Nile tilapia and African catfish were inversely correlated (R=from -0.51 to-0.85, p<0.01) with nearly all the detected physico-chemical variables. Non-significant correlations (R=from 0.1 to 0.36) were recorded between the mean concentration of thrombocytes and the mean values of nearly all the detected chemical and physical water parameters (excluding conductivity (R=-0.66, p<0.01), total solid (R=-0.61, p<0.01), chloride (R=-0.59, p<0.01) for Nile tilapia and/or African catfish).
White blood cells play a major role in the defense mechanism in fish. In the present study, leukocytes count in blood collected from Nile tilapia and African catfish was significantly (p<0.01) decreased in contaminated sites (Rosetta and Damietta branch) compared to other sites. Similarly, Jeronimo et al. (2009) observed a reduction in the WBC count in fishes collected from polluted river. Significant reductions in white blood cell count were previously reported in the common carp after acute exposure to diazinon-based pesticide (Adedeji et al., 2009). Also, the white blood cells count was decreased in Nile tilapia and African catfish after exposure to nickel (Ololade and Oginni, 2010). The reduction in white blood cells may result from bioaccumulation of the pollutants in the liver (Agrawal and Srivastava, 1980). It was evident previously (Osman and Kloas, 2010; Osman, 2012) that the liver of Nile tilapia and African catfish was the site of maximum accumulation for the heavy metals examined. On the other hand, some authors (Singh and Tandon, 2009; Zutshi et al., 2010; Musa et al., 2013) observed a remarkable increase in the number of WBC in fishes collected from polluted sites, which mean an opposite answer to the present work. Possibly, the African catfish and Nile tilapia are well adapted and more resistant to water quality parameters at downstream rive Nile. In the present work, Significant correlations (R=from -0.51 to-0.82, p<0.01) between WBCs count and nearly all the detected chemical and physical parameters (excluding chemical oxygen demand) were recorded.
Changes in differential leukocyte count are recognized as a sensitive indicator of environmental stress (Cole et al., 2001; Li et al., 2011). The lymphocytes are reported to be responsible for immune response (Singh and Tandon, 2009) producing antibodies and chemical substances serving as a defense against infection (Musa et al., 2013). An increase in lymphocyte numbers may be a compensatory response of lymphoid tissues to the destruction of circulating lymphocytes (Shah and Altindag, 2005). Singh and Tandon (2009) observed a high number of lymphocytes in fishes collected from polluted river. However, our study registered different responses when compared to the one above, since significant decrease in the number of lymphocytes were recorded in the blood of Nile tilapia and African catfish collected from the contaminated sites compared to other sites. This trend may be related to fish that live in the polluted site as it, in fact, occurred in the polluted area (Jeronimo et al., 2009). This fact is supported by Hoeger et al. (2004) who showed that fish exposed to sewage effluent had a decrease in circulating lymphocytes.
Monocytes and neutrophils are important white blood cells to protect the body through their phagocytic activities against bacterial infection in damaged cells (Singh and Tandon, 2009). The percentage of monocytes and neutrophil generally decreases after exposure to pollutants (Nussey et al., 2000). In the present study, significant decreases in the number of monocytes were recorded in the blood of Nile tilapia and African catfish collected from the contaminated sites compared to other sites. Significant increases (p<0.01) of neutrophil counts were recorded in the present work in the blood of both fish species collected from the contaminated sites (Rosetta and Damietta branch). The same results were previously recorded by Davis et al. (2008) and Mekkawy et al. (2011). In contrast, (Rowan, 2007) reported significant reduction in the neutrophil numbers in brown bullheads collected from a contaminated site compared to a reference site. Eosinophils are considered to play a role in defense mechanism, phagocytizing activities, and inflammation (Matos et al., 2014). They display the same trend as neutrophils are being increased from upstream to downstream river Nile.
Lymphocytes and eosinophils showed non-significant (R=from 0.06 to 0.32, p>0.05) correlation with nearly all the detected water quality parameters. Most of the detected water quality parameters exhibited significant correlation (R=from -0.44 to-0.79, p<0.01) with monocytes and neutrophil in the blood of Nile tilapia and African catfish. Many studies have shown a relationship between the fish leukocytes variables and the exposure to single pollutant (Mekkawy et al., 2010; Osman et al., 2010b; Musa et al., 2013). The river Nile in this work is contaminated with a variety of pollutants (multiple stressors). So, the differential leukocytes count may be not suitable as stand-alone biomarkers of aquatic pollution, but it is a sensitive biomarker of detecting immunological changes in fishes if combined to other non-invasive biomarkers (Valon et al., 2012).
Erythron profile
Various environmental factors play an important role in determining the erythrocyte size (Altman and Dittmer, 1961). The concentrations of water and sediment contaminants were negatively associated with the erythrocyte cellular and nuclear area and positively associated with ratio of immature erythrocytes (Rowan, 2007). In the present study, lower cellular areas and cellular shape factors were recorded in the erythrocytes of fish collected from Damietta and Rosetta branch compared to those sampled from Aswan and Kena (upstream). This was confirmed by higher immature ratios of red cells in the blood of fish sampled from downstream sites. These relationships indicated that pollution might have stimulated erythropoiesis and increased the abundance of immature red blood cells in the circulation of fish collected from contaminated locations. Rowan (2007) also recorded a positive correlation between the ratios of immature cells in blood of Ameiurus nebulosus collected from contaminated sites.
Three forms of karyorrhectic or degenerating erythrocytes were observed during the present study in the blood of Nile tilapia and African catfish namely cytoplasmic swelling, membrane disintegration (nuclear deformation), and nuclear shadow (smudge cell remaining after cell death). The swollen blood cells were recorded as common alteration. Degeneration of erythrocytes can be described as pathological conditions in fishes exposed to toxicants (Buckley et al., 1976). It was previously reported in fishes after exposure to sub lethal concentrations of pesticides (Adedeji et al., 2009) and heavy metals (Adeyemo, 2007; Ololade and Oginni, 2010). The present study, however, showed significant correlations (R=from 0.47 to 0.82, p<0.01) between karyorrhectic erythrocytes and physico-chemical parameters in water samples collected from the whole course of the river Nile. Karyorrhectic cells in the blood of Nile tilapia and African catfish were higher in Rosetta and Damietta sites (contaminated sites) compared to other sites. Similarly, Rowan (2007) and Valon et al. (2012) reported an increase in karyorrhectic erythrocyte in blood of fish collected from contaminated sites. Also, Houston et al. (1993) reported an increased number of karyorrhectic erythrocytes in goldfish (Carassius auratus) due to chronic exposure to cadmium. According to the available literatures, the presence of karyorrhectic erythrocytes (degenerated) is an indicator of chronic pollution in the site (Valon et al., 2012). This fact is supported in the present study by the increased number of neutrophils and decreased number of leukocytes observed in the downstream sites (contaminated).
In the present study very few numbers of dividing erythrocytes were recorded in the blood of Nile tilapia and African catfish collected from the whole course of the river Nile. The presence of dividing erythrocytes in peripheral blood of fish were previously reported by Murad and Houston (1992) and Rowan (2007). According to the present result, dividing cells do not show the classic characteristics of eukaryotic mitosis. More research is needed to determine the exact mechanism of the dividing erythrocytes formation. Since the numbers of dividing cells were not correlated (R=from -0.1 to-0.37, p>0.05) with water quality parameters collected from the selected sites, it seems unlikely that dividing cells could be useful indicator of contaminant exposure.
It is known that fish have, normally, nucleated erythrocytes in their peripheral blood (Niimi and Imada, 2008) representing a special mechanism for the increasing oxygen carrying efficiency, particularly in contaminated water, by improving surface and/ or volume ratio (Valon et al., 2012). In the present work, enucleate red cells were recorded only in the blood of Nile tilapia and African catfish collected from downstream river Nile and absent in the blood of fish collected from upstream areas. Enucleated erythrocytes were significantly correlated (R=from 0.54 to 0.91, p<0.05) with physiochemical parameters collected from the same sites and at the same sampling time.
Biochemical parameters
To see if there was any correlation between fish altered physiological fitness and environmental stress, we measured serum biochemical variables namely; AST, ALT, ALP, total protein, cholesterol and triglyceride concentration, glucose level, creatinine, and uric acid. According the available literatures, alteration of fish blood biochemistry is indicative of unsuitable environmental conditions or the presence of stress factors (Yang and Chen, 2003; Barcellos et al., 2004; Kamal and Omar, 2011). Therefore the measurement of serum biochemical parameters is useful for biomarkers in toxicology (McDonald and Grosell, 2006).
AST and ALT belong to the plasma nonfunctional enzymes, which are normally localized within the cells of liver, heart, gills, kidneys, muscle and other organs (Hadi et al., 2009). ALP enzyme is a sensitive biomarker for metallic salts since it is a membrane bound enzyme related to the transport of various metabolites (Lakshmi et al., 1991). In the present study, ALT, AST and ALP concentrations in blood serum of Nile tilapia and African catfish were significantlyy higher (p<0.01) in the contaminated sites (Rosetta and Damietta branch). Environmental contamination with heavy metals and other sources, recorded in Rosetta and Damietta branches (Osman and Kloas, 2010), could lead to such elevation in ALT, AST, ALP concentration in the blood of both fish species. The same results were previously recorded in the blood of Nile tilapia and African catfish after exposure to pesticides (Adedeji et al., 2009), heavy metals (Oner et al., 2008; Mekkawy et al., 2010), nonylphenols (Mekkawy et al., 2011) and UV rays (Osman et al., 2010b). Increased levels of ALT indicate an adaptive response to its leakage into the blood stream due to the presence of water toxicity. It has been reported that alterations in enzymes activities in the serum directly indicates major pathologic changes or liver damage (Bhattacharya et al., 2008). Previously Osman (2012) recorded a severe cellular degeneration and necrosis in the livers of Nile tilapia collected from downstream river Nile, explaining the remarkable increase in the level of AST, ALT, and ALP observed in the present work.
The protein synthesis of an organism is of important diagnostic significance because of its involvement in enzymes, hormones, and antibodies. Thus, the influence of toxicants on total protein concentration of fish has been taken into consideration to evaluate the response to stressors and consequently the increasing demand for energy (Hadi et al., 2009). In the present study, the total protein concentration in the blood of Nile tilapia and African catfish were significantly increased from upstream to downstream sites (Rosetta and Damietta branch). Such increase in total protein reflects liver dysfunction due to higher heavy metal concentrations (Zaki et al., 2010). The levels of Pb, Cd, Cr and Hg were above the permissible limits in the water of downstream river Nile (Rosetta and/or Damietta sites) explaining higher total protein level in the blood of fish sampled from downstream areas.
Cholesterol is the most important sterol occurring in animal fats. Change in the blood cholesterol and triglyceride concentration is a sensitive indicator of liver dysfunction because homeostasis of lipids is one of the principle liver functions (Sayed et al., 2011). It has been reported that exposure of fish to heavy metals (Vinodhini and Narayanan, 2009) increased cholesterol and triglyceride concentrations in the blood. In the present work, the blood cholesterol and triglyceride levels were significantly (p<0.05) higher in Nile tilapia and African catfish collected from the contaminated sites (downstream areas) as compared to upstream areas. Such increase could be explained as a result of liver damage previously detected in fish sampled from downstream river Nile (Osman 2012), leading to inhibition of enzymes that converts cholesterol into bile acid (Murray et al. 1991).
Blood glucose level has been used as an indicator of environmental stress to reflect changes in carbohydrate metabolism under stress conditions (Kamal and Omar, 2011). The levels of glucose were significantly higher in the blood of African catfish and Nile tilapia collected from downstream river Nile (polluted area) compared to upstream sites. The chemical pollutants such as heavy metals modulate the metabolism of carbohydrates, causing hyperglycemia by stimulating the glycogenolysis in fish (Levesque et al., 2002). This was supported by higher level of all the detected heavy metals in downstream river Nile. Increased levels of glucose were previously recorded in blood of fishes exposed to ultraviolet radiation (Sayed et al., 2007; Osman et al., 2010b), heavy metals (Levesque et al., 2002; Mekkawy et al., 2010), and other pollutants (Poléo and Hytteørd, 2003; Adedeji et al., 2009). This can be attributed to the alteration in the activity of glucose-6-phosphate dehydrogenase and lactate dehydrogenase previously detected by (Osman et al., 2010a).
The results of the present work exhibited higher levels of creatinine, urea and uric acid in the blood of fish sampled from polluted sites. Similar findings were reported by Zaki et al. (2009) who recorded a significant increase in these parameters in Nile tilapia due to cadmium exposure. Increased levels of plasma creatinine and uric acid can be used as rough indicators of glomerular filtration rate and kidney functions (Abu et al., 2009; Zaki et al., 2010; Kamal and Omar, 2011).
Concentrations of individual ions and total osmolarity in blood plasma are physiological variables that have been used as indicators of the effects of pollution on fish (Abel, 1989). Ions are very important for any organism because they involved in most biological processes (Sayed et al., 2011), and responsible for the maintenance of osmotic pressure in blood (Mohanty and Mishra, 1983). In the present study, the levels of calcium, sodium, chloride were significantly increased from upstream to downstream sites in correlation with the increase in the level of physico-chemical variables in these sites. Similarly, significant increase in sodium and chloride, were recorded in the blood of Prochilodus lineatus collected from contaminated site compared to reference one (Camargo and Martinez, 2006). The observed increase in the levels of ions and blood sugar in the blood of fish collected from polluted sites lead to an increase in osmolarity. This probably reflects the high conductivity of the water found at this site, which is usually associated with the discharge of large quantities of salt (Winkaler et al., 2001). Increased plasma ion concentrations are due to altered enzyme activities (Osman et al., 2010a) and it has been an indicator of impending death (Woodling, 1999).
The selection of fish species is a critical issue in routine application of blood biomarkers for bio monitoring purposes. Rodriguez-Cea et al. (2003) noted that some fish species are more sensitive to aquatic pollutants than other species. This hypothesis is supported by data in this study. Species specific differences between polluted and non-polluted sites were obtained for Nile tilapia and African catfish. The number of leucocytes was higher in the blood of African catfish than that in the blood of Nile tilapia collected from the same site and at the same sampling time. This indicates that African catfish are more resistant than Nile tilapia toward environmental stress. At the same time the frequency distribution of erythrocytes malformation was recorded to be higher in the blood of Nile tilapia than that in the blood of African catfish, indicating Nile tilapia was more sensitive to aquatic pollutants than African catfish.
This work was partially supported by Science and Technology development fund (STDF), Egypt (Project ID 448). The first author is grateful for the continuous support from the Alexander von Humboldt Foundation, Germany.
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Camp Fire: Two men arrested for allegedly burglarizing Cal Fire station
Photo: Butte County Sheriff's Office
Two Concow men were arrested for trying to steal from a Cal Fire station in the wake of the catastrophic Camp Fire, officials said Monday.
Robert DePalma and William Erlbacher are facing five felony counts including vehicle theft, looting during an emergency and possession of stolen property, according to a joint statement by Cal Fire and the Butte County Fire Department.
The two men are each being held in Butte County Jail on $250,000 bail.
Last week authorities arrested six people accused of looting in the area near the Camp Fire, according to the Sheriff's Office.
Gwendolyn Wu is a San Francisco Chronicle staff writer. Email: email@example.com Twitter: @gwendolynawu

subset: commoncrawl


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This article covers one method of transferring game files for Minecraft for mobile devices, Windows 10, Switch, VR and Xbox consoles. If you need help with moving Minecraft: Java Edition, go here.
Due to how files are stored on these devices, it can be difficult to "copy and paste" them from one device to another. It is possible to transfer worlds between these devices using Minecraft Realms however.
You will need an active Minecraft Realm in order to do this. If you have not yet used your Realms trial, you can use that to transfer your worlds. For information about Minecraft Realms and how to start a Realm, go here.
Once you have created a Realm, follow these instructions:
- From the first device, please do the following:
- Select the pen icon next to your Realm from the Realms list
- Select "Replace World" and confirm
- Choose the world you would like to transfer
- Wait for the upload and select "Let's go!"
- Access Minecraft from the second device and do the following:
- Select the pen icon next to your Realm from the Realms list
- Select "Download World"
- Wait for the download and select "Let's go!"
Your world has now been transferred from one device to another! If you wish to transfer more than one world, you can repeat the same process.
Please note that you will need to use the same Edition of Minecraft and the same Xbox Live account in order for this to work.


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Various Directions To Pay Attention To During Do-It-Yourself Spray Foam Insulation
There is no doubt that they do it yourself market is doing very well and within a few years, it will surpass 14 billion dollars in revenue. There are so many do-it-yourself tutorials that can be found online and project suppliers are producing low cost materials. You will find that individuals can finish a complicated project using only one afternoon. If you are looking for a cheap solution when it comes to weatherizing your home it is good that you consider do-it-yourself spray foam insulation. A lot of energy cost is related to heating and cooling homes, and if you invest in sound insulation, you will be able to keep in the cold during hot periods and heat during the cold months. This will significantly save your lot of cash annually. This article is going to talk about the different steps that you can take during the do-it-yourself spray foam insulation.
It is possible for you to achieve the best results if you are entirely ready for the procedure. It is recommended that you have protective gear during this process because spray foam insulation has fumes that are capable of damaging what you are wearing. It is advised that you buy a mask to help you not breathe the fumes and an overall to shield your clothing. It is wise for you to protect your windows because you will have a tough time to remove the insulation after it gets dried out. Moisture is one of the causes of preventing the form from holding on the surface and should be avoided at all cost website .
It is recommended that you pay attention to the frame first before you begin with the walls. This is the best option if you want to get perfect results from the job. It is encouraged that you take your time when you are conducting the procedure so that the layers are allowed enough period to dry. Your work will be useless if you lessen the amount of time to dry between the layers. It is important for you to maintain two inches at a go so that you let it dry accordingly. Take the instructions of the time of lift seriously for every company is unique. If you follow the above steps, you will be happy with the results and make your work easier in the procedure click here for more .


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Delbert D. Deschner, 90, formerly of Natoma, died Wednesday, Dec. 27, 2017, in Wichita.
He was born Dec. 6, 1927, north of Natoma to Martin and Emma (Blank) Deschner. He was a 1945 graduate of Natoma High School.
He married Barbara Griffin on Sept. 7, 1956. She preceded him in death April 5, 1970. He later married Charlotte (Young) Meyers. She preceded him in death April 15, 2008. He was a farmer.
Survivors include four sons, Michael Deschner, Scott City, Bruce Deschner and Michael L. Meyers, both of Topeka, and Bradley Deschner, Great Bend; two daughters, Kim Davis, Manhattan, and Lori Wangsgard, Wichita; a sister, Delphine Atkinson, Excelsior Springs, Mo.; 10 grandchildren; and 10 great-grandchildren.
He was preceded in death by a grandson.
Services will be at 10:30 a.m. Saturday at Peace Lutheran Church, Natoma; cremation has been selected by the family and inurnment will follow at Natoma Lutheran Cemetery.
Family will greet guests at the church the day of the service.
Memorials are suggested to Peace Lutheran Church or Natoma Heritage Seekers Museum in care of Pohlman-Varner-Peeler Mortuary, Natoma.


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Pittsfield Township woman fatally shot
Woman was allegedly shot by her romantic partner, authorities say
PITTSFIELD TOWNSHIP, Mich. – A woman was detained Saturday after the fatal shooting of a Pittsfield Township resident.
According to authorities, police responded to a complaint regarding a gun going off. Shortly after officers arrived, the situation was reported to police to asa confirmed shooting.
The victim has been identified as Shantel Johnson-Jackson, a 27-year-old resident of Pittsfield Township. She was transported to St. Joseph Mercy Hospital and died shortly after.
The suspect is 27-year-old Ashley Somerville, who was involved in a romantic relationship with Jackson and had called to report the shooting, according to police. She has been taken into custody pending arraignment.
If anyone has any information regarding this case, please contact the Pittsfield Township Department of Public Safety at 734-822-4911. If you would like to remain anonymous, please call the Pittsfield Township Department of Public Safety's tip line at 734-822-4958.
Copyright 2017 by WDIV ClickOnDetroit - All rights reserved.


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Home > Homes
Indulgent Is An Understatement At Our Los Cabos Mexico Resort
Exquisite Villas & Penthouses suites offering infinite ocean views and luxury appointments welcome you at the Homes & Villas by Grand Solmar. Artfully crafted for the vacationer seeking a more private experience, our spacious villas or Penthouses are designed with luxury living in mind. Ideal for families and groups of friends, our villas & penthouses let you get swept away with endless views of the Pacific. Let your creativity soar in your gourmet kitchen with a wet bar. Here, marble floors, open spaces and authentic Mexican décor set the stage for unforgettable memories.


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Starting Electronics Needs Your Help!
It is that time of the year when we need to pay for web hosting and buy new components and equipment for new tutorials. You can help by making a donation. Contribute to this website by clicking the Donate button. The total will be updated once daily. (You may need to clear your browser cache to see the updates.)
Target Amount: $2000
Amount Raised: $1960
Donations Received
Top Donor: C.C. $100
Created on: 30 July 2012
The schematic symbol for a crystal is shown below.
Crystals used in electronics are housed in metal cases as shown in the photo below. They usually have values that are in the megahertz range (MHz) except for crystals that are used with time/date circuits that are usually 32.768kHz crystals (32.768 kilohertz).
The photo shows a 11.0592MHz crystal in a metal can package on the left. Low profile crystals are shown in the centre. Two different sized 32.768kHz watch crystals are shown on the right.


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San Diego, CA (PRWEB) October 31, 2016
Gables Residential has been giving back to its communities in many ways around the country. One of the most significant ways has taken place over the past 16 years by dedicating a day where all associates come together in their respective regions to focus on giving back to a worthy cause. Gables Day encompasses a full day in each region throughout the fall where approximately 1,000 associates come together to volunteer their time and share in the experience of this special day. Since 2000, Gables Day has resulted in contributions of over $1.2 million in goods and services and approximately 125,000 hours of labor and dedication by Gables associates.
In San Diego, Gables Day recently took place at the San Diego Habitat for Humanity, which brings people together to build homes, communities, and hope. Gables associates spent the day building and repairing aspects of a family home that was in need of assistance.
According to Armando Vieira, Regional Manager for Gables, "This year we chose to dedicate our resources to Habitat for Humanity in San Diego. Neighborhood Revitalization was our assigned project. Our team served a hardworking family that needed home improvements. Gables Day in San Diego encouraged existing residents of the Logan Heights neighborhood to be active participants in the revitalization of their own community. The goal of the Neighborhood Revitalization project is to build a legacy - block by block - not just for one family at a time, but for an entire community. It's really nice to put out so much energy and effort that you know is going to a good cause."
"Gables Residential really knocked it out of the park! The team worked so incredibly hard that they got a full day's work done in just a few hours. We are so thankful for such hard working volunteers who understand and support our mission. We cannot wait to work with Gables again!" said Shandy Arwood, Director of Community Engagement for Habitat for Humanity.
Habitat homes are built with donations of money, materials and labor. Gables, along with several of their preferred vendors, donated a full day of just that, in order to provide a safe and comfortable place for the assigned family to live.
About Gables Residential
Gables Residential is an award-winning, vertically integrated, real estate company and privately held REIT specializing in the development, construction, ownership, acquisition, financing and management of multifamily and mixed-use communities. Gables Residential owns, develops and manages communities in high-growth U.S. markets such as Atlanta, Austin, Boston, Dallas, Denver, Houston, South Florida, Southern California and metropolitan Washington, D.C. Gables also provides third party management services in the New York, Baltimore, Frederick, Tampa, Phoenix, Seattle, Charlotte, Central and North Florida markets.
Gables manages over 31,000 apartment homes and approximately 550,000 square feet of retail space and has received national recognition for excellence in development, construction, management, sales, marketing, learning and development, benefits and corporate accommodations. These achievements reflect the impact of our experienced and dedicated team members, our superior knowledge of the markets served, and our expertise in development and management.


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Though you may not (yet!) be as dynamic as your favorite lecturers, philosophers, authors, or comedians, you probably draw some form of inspiration from them. Perhaps you've observed their use of charts and graphs and noticed that you can indeed present data in a compelling manner. Maybe you admire the way they use working scale models to bring their ideas to life. Or, possibly, you've noted their decision not to rely on hundred-slide presentation decks in a forum that's usually packed with laser-pointer-wielding speakers. As a result, you've now added new tools and techniques to your repertoire.
Just as you want to inspire your audience and leave it wanting more, your students will also feel rewarded when they give a presentation that engages their fellow students and earns them a satisfying (or even impressive) grade.
You may require students to incorporate the use of presentation aids into their assignments. They may also opt to include these of their own volition. Of course, as you've learned for yourself, it's not always easy to know which tools to use; but, with some thoughtful planning, their sights, sounds, and speech content can come together and result in a pleasing performance. So, whether they're planning to use informative slides that help others follow along with their message, videos that capture the audience's attention, tech tools that engage people and get them actively involved, or "props" that demonstrate the concepts they're addressing in their presentations, their mission is to choose the aids that enhance, rather than detract from, their work.
If you'd like to help your students start the planning process off on solid footing, share this exercise from William Keith and Christian O. Lundberg's Public Speaking: Choice and Responsibility, which encourages students to consider what tools and techniques best supplement their speeches and presentations:
Think about the speech you are currently working on. Make a list of the elements that might be strengthened by some kind of presentation aid or supplemental media. Next to each, write the medium that would be most appropriate and which goal for your speech it might advance. Were you able to find a goal for each presentation aid? (240)
Reference: Keith, William and Lundberg, Christian O. 2014. Public Speaking: Choice and Responsibility. Boston, MA: Wadsworth, Cengage Learning.
Do you assign presentations in your course? Share some of your students' innovative ideas with us! Comment below.


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Of all the job-related websites and resources, LinkedIn will give you the most bang for the buck. If used to its potential, it can absorb more than thirty percent of your job search/resource load. With LinkedIn, you can search and study almost every company in existence—including its corporate ladder—from entry-level employees to higher-level managers. Now that MOST people in the working sphere utilize LinkedIn, it provides unlimited opportunities to see who's who and who's where. But how can you BEST use LinkedIn in your job search? Here's a few tips:
Looking now? Go to: Search for my dream job


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Welcome to FS-Maschinenbau GmbH
FSMB is your partner, for realization and manufacturing of new CNC- and Special Machines. Designed and engineered for our Customers requirements.
Our Headquarter is located in Gmunden (Austria), wherefrom we take care of our worldwide Customers with our Products and Service.
We are looking forward to your request!
|Range of Services


text: Navigating the Gap Between Risk Management and Crisis Response - 5 PitfallsMay 15, 2018 Anne Ristic As the risk landscape grows, we're all stepping up both our enterprise risk management plans, and our crisis response preparedness. But we still need help navigating 5 pitfalls that fall between theoretical risks on the one hand, and actual crises on the other. Take a closer look at how to distinguish red flags from red herrings. The Growing Risk Landscape We face an increasing battery of risks these days. The number of cyber attacks in western economies in 2017 reportedly increased by 25% over 2016, U.S. foreign corrupt practices investigations nearly tripled between 2015 and 2016, and reports of harassment proliferate as the #MeToo movement expands. These are just a few examples of risks that are top of mind for legal leaders right now. We tackle these multiplying risks on two fronts. First, organizations are stepping up enterprise risk management practices so as to better "protect and prevent". Second, crisis response plans have moved out of the theoretical and into real-life scenarios, where the goal is "damage control" if an incident does occur. There is no shortage of resources to help you implement an enhanced enterprise risk management plan, or guide you if a crisis occurs. The Gap Between Risk and Crisis But there's a gap in the middle where it feels lonely. The gap falls between the theoretical risks you're managing, and a full-blown crisis where a risk has become reality. Someone has raised a small red flag in a sensitive area that could turn out to be a bigger problem, but is far more likely to be a normal course business blip. You don't have many facts, you don't want to bury your head in the sand, but nor do you want to overreact and create a crisis where none existed. These little red flags are not uncommon, even for businesses with robust enterprise risk management plans. A technology glitch, an HR complaint, a client query about a mistake, an irregularity in how someone has followed a policy - every crisis begins with some such red flag. But the converse is not true - not every red flag signifies a crisis. In fact, most red flags signify honest mistakes or irregularities that can be easily fixed at the operational level. It would not be practical or wise to invoke your crisis response plan for every situation. So how do you navigate through the gap to the right outcome? There isn't an easy answer. It's a gray area full of judgment calls based on imperfect information, with lots of second-guessing yourself along the way. We'd love to learn from the experiences of others, so please join the conversation if you have observations. In the meantime, to spark the discussion, let me share some common pitfalls. Bridging the Gap – 5 Pitfalls 1. You don't recognize or surface the red flag in the first place. I think this pitfall is more common than we realize. Along with our teams, we might need to get better at recognizing real, "micro" risks that have already happened, as opposed to theoretical colour-coded entries on our risk-management spreadsheets. This is easier said than done because of the sheer number of risks, functional areas, people and geographic locations in many organizations. Ironically, the problem is exacerbated if you have capable empowered people, because they're good at solving operational problems in the trenches without much management intervention. The HR team resolves a complaint, the IT team patches a glitch, the legal team settles a claim in the normal course of their job. The issue does not get flagged as a 'risk' because the focus is on successfully resolving the immediate problem. But other potential risks (reputational, security, financial or legal) outside the person's immediate sphere might go unflagged. To counter this, we're all thinking about upgrading the tools we and our front line people need in order to recognize and assess "micro" risks. My own personal mental checklist when assessing whether an issue is a "micro" risk needing further assessment, or whether it's a normal course problem I should just fix and move on, is: Could there be a safety or ethical issue? Could there be harm to a client? Could any of these facts give rise to significant legal liability, financial loss or reputational risk? Has the person or team been involved in previous issues? Is this issue outside my field of experience so that I need expert advice to assess its significance? Could this issue impact the firm's core values or culture? If the answer to any of these questions is "yes" then I think the issue is a red flag requiring further assessment. 2. You don't provide "early warning" to individual(s) who need to know about the red flag now – or you tell too many people. Resist the urge to investigate without a plan. There are pitfalls to investigations (see below) and they should be handled carefully. Instead you should decide who needs to know this now, consult those individuals, and decide together how to navigate the next steps. The question of who needs to know what when is a judgment call. It's particularly hard at the outset when, as is often the case, there is the possibility of serious risk, but you don't actually think it is likely. On the one hand, you don't want to immediately consult everyone who would be part of a crisis response team, because you don't know whether it's a crisis, the information you do have is probably sensitive, and you don't want to throw anyone under the bus based on a remote possibility and potentially damaging, as yet unfounded material. But on the other hand, you shouldn't be overly protective of people or information involved, to the point where you don't have the tools to assess the issue, or other leaders would be sandbagged if the information later comes out. This topic is rife for second-guessing but my own feeling is that a very small 'early warning' team is better at the outset. Even though you may need to bring others into the loop as things progress (and those people might say 'why am I just hearing this now') I think it's best to start with one or two experienced senior people with good judgment who can help navigate all the thorny issues from here. 3. There isn't a clear "issue owner". Your goal with the 'early warning team' is to get as efficiently as possible to a place where you can make an informed decision on whether your red flag is a red alert to be elevated to a crisis response, or a red herring to be fixed and defused. Most red flags can be resolved without reaching a crisis stage. However, there are several steps to navigate and boxes to check on the risk management checklist before you can make this decision. As with every issue involving many moving parts, it's important to have someone capable and accountable to take ownership of guiding the process and getting to a good result. Often the most effective issue owner is a senior leader on the team where the issue has arisen. Sometimes the issue owner has to be you. But 'role clarity' is important here to ensure the appropriate risk management practices get followed and to avoid a lot of unproductive wheel-spinning. 4. You haven't clearly defined the issue and potential risks. Some time ago I was on a panel with a senior in-house lawyer from an organization with stellar risk management practices. He emphasized the importance of having an 'issue brief' when a potential risk comes up. I listened to him thinking (in the vein of 'you can always learn and improve') that I had never actually written down a concise summary of the facts and risks when dealing with my little red flags over the years – I would simply carry these around in my head. Similarly other team members would have in their heads their own version of the facts and risks, which might have been slightly different. All this led to cross-purposes discussions, wheel-spinning and covering old ground at meetings. There are some pitfalls relating to record-keeping (described below) which are important to avoid. Having said that, there is a lot to be gained by having an outline of the issues, which can then frame a common approach for everyone involved. My own approach now tends towards a "less is more" page of point-form notes covering: What are the facts we know now? What is the 'bad story' that might be drawn from these facts? What is the 'good story'? What additional facts do we need in order to determine which story is most likely? Based on the outline, your early warning team might conclude you have enough facts to decide whether or not the issue should be elevated to a crisis response, so no further fact-finding is needed. Often, however, more facts are needed and in this case the issue brief will evolve. If the red flag does get escalated, then your factual summary, the 'bad story' and the 'good story' will all form a good foundation for the crisis communications that will be needed. 5. In the process of internal fact-finding you can create legal problems down the road. There are a few pitfalls to avoid in the fact-finding stage. Confidentiality of sensitive information is harder to maintain as more people are drawn into the fact-finding loop so it's important to keep the loop as small as possible, move quickly, and caution people about the importance of confidentiality. Litigation counsel will advise you that any work product created during your internal fact-finding could be produceable, and not necessarily subject to privilege, if subsequent litigation arises out of the facts. Any records and any conclusions you've drawn could be subject to intense scrutiny down the road. It's a judgment call on how much fact-finding (if any) you should do internally before engaging outside counsel. On the one hand outside counsel's investigations and work product should be privileged which is a good thing. On the other hand engaging counsel can trigger practical issues relating to broader communications and other aspects of your crisis response plan that you need to be prepared for – so there can be a delicate balance between doing some internal fact-finding and engaging outside advisors. Deciding Between Red Alert or Red Herring Ultimately, you have to decide whether your red flag is a red alert that should be escalated. Here again you are making a judgment call, still without perfect information. The range of factors to consider depends on circumstances and the team needs to give this careful thought. My own thought process is certainly to re-assess the same factors referred to in the context of surfacing the red flag (see above), revisiting them through the lens of new information and analysis. If any of these factors is present, I would think it wise to escalate. If you decide that the problem is not a potential crisis but rather a normal course business issue to be fixed, the 'early warning team' will want to carefully consider all the circumstances and options in determining the fix. Some common considerations are: Are training or process changes needed to prevent similar issues going forward? Are reporting or record-keeping requirements triggered by the issue or the fix? What else did we learn? What follow up communications are required? What makes these real life risk-but-not-yet-crisis issues so challenging, but also so interesting and such valuable experience, is that despite everything I've said above, there isn't really a 'playbook'. There are so many judgment calls, so many points where you have to draw on all your past experience, and so many times where you have to think laterally and analogize because it has never happened before. The best you can do is fine-tune your antennae to the red flags, ask questions, use good judgment, and work with a trusted team to help you navigate the pitfalls. Recognizing that circumstances are fact-specific and often also very sensitive, we'd love to hear if you have practical strategies you've used to navigate red flag situations. We'll include any new ideas you're comfortable sharing in a future post. More from Stikeman Elliott Lorna Cuthbert and Tamara Ticoll, Workplace Sexual Harassment: Ontario Overview (a guide to Ontario's "Bill 132" legislation). Vanessa Coiteux and David Elder, Data Security and Cybercrime FAQ. Danielle Royal et al., Canada Promotes Good Corporate Citizenship (an analysis of Canada's new Deferred Prosecution Agreement (or "Remediation Agreement") program and its enhanced Integrity Regime). Stikeman Elliott, Crisis & Risk Management description of our practice, with links to related practice areas, including: Canadian Anti-Spam Legislation Cybersecurity Privacy & Data Protection White Collar Crime DISCLAIMER: This publication is intended to convey general information about legal issues and developments as of the indicated date. It does not constitute legal advice and must not be treated or relied on as such. Please read our full disclaimer at www.stikeman.com/legal-notice.


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Chemo Absorbent Products - Chemotherapy Towels - Prep Mat
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Because our price on this item is lower than the manufacturer's suggested retail price, the manufacturer does not allow us to show you our price until you place the item in your shopping cart. Retailers like Allegro Medical have the legal right to sell products at prices we set. However, adding the item to your cart allows us to show you our lower price consistent with our promise of always offering you the lowest possible prices on the widest selection of medical supplies, medical equipment and life enhancing products.
Adding this item to your shopping cart won't require you to buy it. However, our prices do change. If you decide to purchase this item now you are guaranteed the price now displayed in your shopping cart. Complete your purchase by clicking on the "checkout" button or simply remove the product from your cart if you decide not to make your purchase at this time.


text: Being a first-time manager is exciting, but also incredibly terrifying. You want to be an effective boss that gets things done, while being liked and respected by your team. As a top staffing agency in Las Vegas, PrideStaff Las Vegas understands the pressure first-time managers are under. Learning to juggle your new responsibilities will take… Read more »


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Motor Trade Insurance
The motor trade covers a wide spectrum of businesses from one man band mobile mechanics to large main dealerships of prestige vehicle brands.
Wherever you fit into this spectrum, there is a motor trade insurance product for you. All you need is some guidance from Glentworth as to which one is the most suitable.
What can a Motor Trade Insurance policy cover me for?
- Comprehensive or 3rd party only cover for vehicle risks
- Business use for my vehicles plus social domestic and pleasure
- Ability to drive customer vehicles for business purposes including testing, collection and delivery etc.
- Courtesy and demonstrator use for customers
- Flexibility to add and remove vehicles
- Cover for customer vehicles in my custody or control
- Cover for all of my business assets including buildings, contents, ramps, tools and stock
- Cover for all of my legal liabilities including public, products and Employers Liability insurance
- Cover for cash including transportation to and from the bank
- Personal accident and sickness cover for all employees - possibly under a separate policy
- Defective workmanship and sales indemnity
- Wrongful conversion
- Arrangement for the Statutory Inspection of your lifting and pressure plant


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How To Stream Miss America 2018 Online To Find Out Who'll Be The Next To Wear The Crown, Be The Crown
Watching the Miss America pageant is a time-honored tradition for some, but watching any program or event live on a television is too "traditional" for many folks in 2017. The 2018 pageant airs Sept. 10 at 9 p.m. ET on ABC, if you can be in front of a TV by then. Fortunately, there are many ways to stream Miss America 2018 online if you can't. Just because you prefer Netflix to primetime, might be on the go come Sunday, or don't have access to a TV set, doesn't mean you have to miss out on the next coronation.
Co-hosted again by the powerhouse duo of Chris Harrison and Sage Steele, People reports that this year's pageant includes Jordin Sparks and Tara Lipinski as judges. As of Sept. 7, the pageant is already taking place, and finalists have already been selected for most of the major scholarships. But the main event is still Sunday night and you won't want to miss it. So here are a few ways to check it out:
With your cable login information, you can always stream ABC on their website — or app, if you're on a device. Your cable company may have a mobile streaming option as well. Newer services like Sling TV and Hulu Live also offer the ability to stream television as it airs, without a traditional remote and tube situation.
If you're unavailable to watch the pageant final on Sunday and don't have a DVR, check your OnDemand to stream it the next day. Hulu will likely either have the full show or clips up Monday night as well, either directly from the source at ABC or as highlights in entertainment news coverage. Youtube is a great resource as well, if you're looking to stream clips and highlights after the fact.
If all else fails, keep your eyes on social media Sunday night. There are sure to be plenty of Instagrams, live tweets, clips, gifs, photos, and so many hot takes to make you feel as if you're really there at the Miss America pageant in prime time.


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Ubisoft has revealed that Far Cry 5 will take players to Hope County, Montana. In addition to revealing the game's setting, Ubisoft released four teaser trailer for the game that show off several different enviroments.
Far Cry 5 will be officially revealed this Friday, May 26th. The game is in development for PS4, Xbox One and PC, and is set to release before March 31, 2018.


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Our educational resources on Nelson Mandela includes information on his life history with an informative biography and quotes from his famous speeches.
Our resources help teach children and young people what it means to be a global citizen. There are a number of different topics covered within our wide range of resources for primary and secondary schools.
Nelson Mandela Children's Fund UK School AssembliesNelson Mandela Children's Fund UK is always delighted to visit schools and colleges throughout the United Kingdom....
Nelson Mandela Children's Fund UK Workshops
Nelson Mandela Children's Fund UK offers workshops to schools and colleges throughout the UK.
Alternatively we can provide res...