Epidemiology of Bovine Fascioliasis: Assessing Prevalence and Investigating Hemato-Biochemical Alterations in Katsinaabattoir North Western Nigeria

Epidemiology of Bovine Fascioliasis: Assessing Prevalence and Investigating Hemato-Biochemical Alterations in Katsinaabattoir North Western Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiology of Bovine Fascioliasis: Assessing Prevalence and Investigating Hemato-Biochemical Alterations in Katsinaabattoir North Western Nigeria BUHARI SHINKAFI YUSUF, ABDULHAMID AHMAD, Muhammed suleman, IBRAHIM HAMZA KANKIYA, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3979445/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Bovine fascioliasis, caused by liver flukes Fasciola hepatica and Fasciola gigantica , significantly impacts global cattle health and production. This study aimed to assess the prevalence of bovine fascioliasis and its associated hematobiochemical changes on cattles brought for slaughter at Katsina central abattoir. Fecal and blood samples were collected from total of 134 cattles. Fecal samples were examined using sedimentation technique, revealing an infection prevalence of 3.73%. Notably, females exhibited a higher prevalence (4.55%) compared to males (2.17%), though the difference was not statistically significant (P > 0.05). The age group 2–3 years showed the highest prevalence (25.00%), while those aged 5 and above had the lowest prevalence (1.74%). Among cattle breeds, Wadara had the highest prevalence (20.00%), while White Fulani exhibited the least (4.93%). Concerning body condition score (BCS), medium-conditioned cattle had the highest prevalence (6.67%), and good-conditioned ones showed the least (1.37%). Hematological analysis of Fasciola -infected cattle revealed significant reductions (P > 0.05) in packed cell volume (PCV), hemoglobin (Hb), and total erythrocyte count (RBC) compared to the non-infected ones. Additionally, infected cattle demonstrated a significant decrease in white blood cell (WBC) count, mean cellular volume (MCV), and mean cellular hemoglobin concentration (MCHC) compared to the uninfected. Moreover, differential leukocyte counts indicated a notable increase in neutrophils and a decrease in eosinophils, monocytes, and basophils in infected cattle compared to the uninfected, although the difference is not statistically significant (P > 0.05). Biochemical analysis unveiled significantly elevated levels of alanine transaminase (ALT) and aspartate transaminase (AST), along with increased alkaline phosphatase (ALP) and total bilirubin (TB) in infected cattle (P < 0.05). Conversely, albumin (ALB), total protein (TP), and conjugated bilirubin (CB) levels were significantly reduced among infected than uninfected cattle (P < 0.05). Our findings, further confirmed that Bovine fascioliasis has significant impact on the health and productivity of Cattle bred in Katsina state and elsewhere. Understanding its prevalence and associated heamato-biochemical changes among infected animals is essential for implementing effective control and management strategies. prevalence Bovine Fascioliasis Haematology and Biochemical parameters Figures Figure 1 Figure 2 Introduction Bovine fascioliasis is a parasitic disease that greatly affects the health and production of cattle globally. It is caused primarily by liver flukes namely; Fasciola hepatica and Fasciola gigantica (Hayward, et al., 2021 ). Cattle are the ultimate host in the intricate life cycle of these trematodes, which also involve snail and mammalian hosts (Saijuntha, et al., 2021 ). Geographically, the prevalence of bovine fascioliasis varies, but it is still a major concern in many areas, especially those where the intermediate host, freshwater snails, have favourable environmental circumstances (Siles-Lucas, et al., 2021 ). Infected cattle with this parasite infection experience a variety of hematological and biochemical changes that contribute to both subclinical and clinical symptoms (Villa, et al., 2021 ). Haematology is the study of the numbers and morphology of the blood's cellular components, such as the red blood cells (erythrocytes), white blood cells (leucocytes), and platelets (thrombocytes), and it makes use of the findings to diagnose and track disease (Wajihah, et al. , 2023). According to Chikhaoui, et al., ( 2023 ) biochemical changes include variations in different blood components and serum parameters, whereas hematological changes relate to changes in the makeup of the blood. Comprehending these alterations is crucial for the prompt identification and handling of bovine fascioliasis, in addition to evaluating the general well-being of impacted animals (Caravedo, and Cabada, 2020 ). According to Abdullah ( 2023 ), the life cycle of Fasciola entails the discharge of infectious larvae (metacercariae) onto vegetation, which are then consumed by cattle when they graze. After being consumed, the parasites move through the gastrointestinal tract, arrive in the liver, and settle in the bile ducts (Peters, et al., 2021 ). The liver parenchyma and bile ducts are harmed by the liver flukes' feeding on blood and tissue (Kahl, et al., 2021 ). Hematological and biochemical studies can identify a series of physiological alterations brought on by the host's immune system's reaction to the parasites as well as the direct harm the flukes inflict (Lalor, et al., 2021 ). It has been discovered that the livestock industries have suffered significant financial losses as a result of animal deaths, weight loss from the carcass, decreased milk yield, liver damage, decreased production, subpar performances, and animal exposure to other diseases because of secondary complications, and high treatment costs (Mequaninit, and Mengesha, 2021 ). Few studies have been documented on the prevalence, haematological and biochemical alterations due to naturally acquired bovine fascioliasis in Nigeria. Therefore, this research aims to explore and elucidate the prevalence, haematological and biochemical alterations associated with bovine fascioliasis. The findings from this research will further pave way for veterinarians, researchers, and livestock managers to enhance their ability to diagnose and manage this parasitic infection effectively. Moreover, the insights gained from studying the haematological and biochemical aspects of bovine fascioliasis will contribute to the broader understanding of host-parasite interactions and provide a foundation for developing strategies to control and prevent the spread of this economically significant disease. Materials and methods Study area: This study was carried out in the central abattoir of Katsina town, Katsina State, Nigeria. Katsina town, is the capital city of Katsina state as well as Headquarters of Local government Area, Katsina state, Nigeria. Katsina town is approximately located on latitude 12 o N and longitude 7 o E. (Anonymous 2012). The city is well known as a centre for Agriculture, producing both food and cash crops comprising groundnut, cotton, hides, millet, maize and guinea corn. The city is largely inhabited by the Haausa/Fulani ethnic groups (Anonymous 2012). The climate of the area comprises the Sudan savanna vegetation which is characterized by scattered trees, seasonal rainfall which lasts for about five months annually (June to October) and distinct harmattan season which spans from November to February each year, with reduced temperatures, haze and low humidity (Thor West et al., 2020 ). Collection and examination of faecal samples The samples were collected from the rectum or from the fresh stool of the sampled cattle on the ground, in plastic carved sample containers for qualitative and quantitative microscopic examination of Fasciola eggs. Faecal samples were processed using faecal sedimentation method as described by (Rizwan, et al., 2021 ). Samples that are not processed within 24 hours from collection were stored in a refrigerator at 4 0 C. During every faecal sampling, information on sex, breed, approximate age and body condition of the individual animals were recorded (Rizwan, et al., 2021 ). Collection of Blood sample Samples were collected over a period of 12 weeks. During slaughtering, 134 blood samples were collected from Katsina central slaughter house into evacuated EDTA container for haematological analysis and stored at 4°C and into serum separating tubes for biochemical analysis. Sera were frozen in plastic tubes at − 20°C. Samples were analyzed within 12 hours. The samples were transported to Haematology Laboratory at general hospital Daura Katsina State for haematological analysis and postgraduate research laboratory at Umaru Musa Yar’adua University Katsina for Biochemical analysis (Brahmbhatt, et al., 2021 ). Haemato-biochemical studies Blood and serum samples were collected from the Fasciola infected and non infected animals for routine haematological and serum biochemical analysis. A total of four (4) blood and serum samples from Fasciola infected and one hundred and thirty (130) samples from healthy animals were collected during the study and analyzed. Haematological analysis of the blood samples was done by using Sysmex particle counter (Model 210) and biochemical analysis of the serum samples were done by with commercial kit (Randox, UK) respectively (Brahmbhatt, et al., 2021 ). Statistical analysis The data obtained was analyzed using SPSS version 16. Student t-test was used to analyze the data on the haematological and biochemical parameters of the Fasciola- infected and the non-infected samples. Values of P ≤ 0.05 were considered significant. Results were expressed as means ± SD. Results and Discussions The results of coprology showed that, out of the One Hundred and thirty four (134) cattle examined, 5 were infected, representing a prevalence of 3.73 percent, while One hundred and twenty nine (129) were not infected, with a prevalence of 96.3 percent (Table 1 ). Coprology's low prevalence of 3.73% is in line with findings from some previous researches by Akpabio ( 2014 ) and Okonkwo et al. ( 2023 ), who found low prevalence rates of 1.7% and 13.5% respectively. It is not, however, consistent with the results of Njoku-Tony ( 2011 ), Adedokun et al. ( 2008 ) and Abraham and Jude ( 2014 ), who found higher incidences ranging from 23.3–75% in the southern region of the Nigeria. The high prevalence in the southern part of Nigeria may be related to variations in the climate and dense vegetation, which would favor the growth of the snail vector and raise the infection rate. However, the results of researches conducted by Soba et al. (2023) and Njobdi et al. ( 2023 ), although done in Northern Nigeria, reported higher prevalences in Gombe (74.3%) and Benue (48.2%) states respectively, which are at odds with the low prevalence rate reported in this study. The variances in sample size, livestock abundance and climate in various areas could all be contributing factors to the discrepancies in prevalence. The results of sex-specific distribution of the infection showed that females had a higher prevalence, representing 4.55 percent, compared to their male counterparts with a prevalence of 2.17 percent (Table 2 ). The sex distribution analysis results showed that the prevalence was higher in female cattle than in male cattle. The increased susceptibility of females to the illness could be the reason for this. This conclusion is consistent with other research findings (Njok-Tony, 2011; Ardo et al., 2013 ; Uwalaka et al., 2019 ; Shima et al., 2015 ; Banwo et al., 2023 ; Okolugbo et al. , 2023; Sabo et al., 2023 ). It does, however, conflict with the results of some other researchers, like Oladele-Bukola and Odetokun ( 2014 ), Adangs et al. , (2015), Aliyu et al., ( 2014 ) and Ikenna-Ezeh et al., ( 2019 ), who found higher prevalences in males. This discrepancy could be explained by the custom of keeping a higher female-to-male ratio—particularly when it comes to the ratio of cows to oxen—and by keeping female animals around for the purpose of breeding and milk production. The results of age-specific distribution of the infection revealed that the age group 2–3 years old, had the highest prevalence, representing 25 percent, followed by 3–4 years with 6.89 percent. The least prevalence was recorded in the age group 5 years and above with 1.74 percent. No prevalence was recorded in the age groups 0–1 year and 4–5 years, respectively (Table 3 ). Additionally, the study found a greater frequency in the age range of 2–3 years, which is in line with the findings of Uwalake et al. (2019) and Aliyu et al. ( 2014 ), who also found that young calves had a higher prevalence than adult cattle. This goes against the results of some other studies (Ardo et al., 2013 ; Adang et al., 2015 ) that showed a higher prevalence in adults than in young animals. Young cattle may be more susceptible to the high incidence because of their exposure to contaminated pasture, particularly when the pasture is chopped and fed to them. The results of breed-specific distribution of the infection showed that Wadara had the highest prevalence, representing 20 percent, and the least prevalence was recorded in White Fulani (4.93%). Zero prevalence was recorded in Red Bororo and Azwak, respectively (Table 4 ). In addition, the research revealed that the Wadara and White Fulani breeds had a significant prevalence rate of infection, whereas the Red Bororo and Azwak breeds showed no infection. This implies that some breeds are more prone to contracting the fascioliaisis than others, which may be related to how frequently these types are slaughtered at the slaughterhouse. This vulnerability may also be linked to variations in extrinsic (environment and management techniques) and intrinsic (genetic, physiological and immune) host variables. This result is in conflict with the findings of Soba et al. (2023) and Olamelekan et al. (2023), who showed high prevalence in Sokoto Gudali and Red Bororo, but it is consistent with the findings of a study conducted by Ikenna-Ezeh et al. ( 2019 ), who observed no infection in Red Bororo and a high prevalence in White Fulani. The results of body condition score from this study, showed that those with medium condition revealed a high prevalence representing 6.67 percent, followed by those with poor condition (6.45%) and the least prevalence was recorded in those with good body condition (1.37%). The result was shown on (Table 5 ). Our findings are in line with the findings of Meharenet and Shitu ( 2021 ), who found that the medium conditioned animals were more infected in Ethiopia. However, our findings were in contrast to that of Uwalaka et al. ( 2019 ), who reported a higher prevalence among poor conditioned animals in Abia state, Nigeria. The lowest prevalence of infection is consistently recorded among good physical conditioned animals. This suggested that the prevalence of fascioliasis is closely related to body condition, with the medium and poor conditioned being more prone to infection than the good. The results of the hematological indices determined for Fasciola -infected and non-infected cattle indicated that PCV, Hb, and RBC were lower in the infected cattle than in the non-infected ones. On the other hand, WBC, MCV, MCH, and MCHC were higher in the infected cattle compared to the uninfected animals. Statistical analysis revealed highly significant differences between the PCV, Hb, and RBC of the infected and non-infected cattle ( p < 0.05), and significant differences between the WBC, MCV, and MCH of both groups ( p < 0.05). However, no significant differences were observed between the MCHC of the infected cattle and the uninfected ones (Table 6 ). In comparison to the uninfected cattle, the haematological changes among the infected cattle, resulted in a substantial drop in the mean values of WBC, RBC, HGB, HCT, and MCH and a significant increase in the mean values of MCV and MCHC. The present discovery aligns with multiple other studies that have documented a decline in the same parameters' (Wyk et al., 2012 ; Egbu et al., 2013 and Brahmbhatt et al., 2021 ). But the lower values of RBC, WBC, HGB, and HCT in infected cows may be the result of an adult fluke's blood-sucking behavior as well as blood loss from hemorrhages brought on by the immature parasite's extensive migration through the bile duct and liver parenchyma as earlier suggested (Etim et al., 2014 and Brahmbhatt et al., 2021 ). The present study's findings regarding the significant increase in MCHC in infected cattle are consistent with those of Brahmbhatt et al. ( 2021 ). The differential counts of Fasciola-infected cattle and the uninfected ones revealed a perceptible increase in the neutrophils of the infected cattle and a clear decrease in the levels of eosinophils, monocytes, lymphocytes, and basophils in the infected cattle. The differences in the neutrophils, eosinophils, monocytes, and lymphocytes of both groups were highly significant at P ≤ 0.05. According to the current findings, peripheral blood from infected animals had higher neutrophil counts than from uninfected animals, suggesting that neutropilia developed during the Fasciola infection of cows. A substantial rise in monocytes, basophils, and eosinophils is indicative of a parasite infection. This is consistent with a research finding by Brahmbhatt et al. ( 2021 ), which reported that between infected and non-infected Gir cattle, there were low levels of eosonophils, monocytes, and basophils and high levels of neutrophils. However, these results conflict with those of Egbu (2013) and Matanovic et al. (2007), who found that the infected group had significantly higher neutrophil and eosinophil counts compared to the uninfected, and that the infected group had significantly, lower levels of monocytes and lymphocytes. The variations in the differential counts could be the result of a toxin-mediated lesion of the bone marrow or a body defence mechanism against the obstructive effects of Fasciola as earlier suggested (Egbu et al., 2013 ). The results of the biochemical changes indicated that the means and standard deviations of ALT, AST, ALP, and TB were higher in the infected cattle than the uninfected ones, while ALB, TP, and CB were higher in uninfected cattle than their infected counterparts (Table 8 ). An additional sign of internal organ injury is observed from the results of biochemical analysis. ALB, TP (total protein), and CB levels considerably decreased among the infecrted cattle ( p < 0.05) in the current study, while ALT, AST, ALP, and total bilirubin levels increased also among the infected ( p < 0.05). These discoveries agreed with the results from other researches (Brahmbhatt et al., 2021 ; Ellah et al., 2014 ; Kitila Megersa, 2014). Higher AST and ALT activity is typically seen in cases of Fasciola infection because the parasite damages the liver through migratory activity, which in turn triggers the activation of inflammatory cells that produce fibrosis and necrosis and increases AST and ALT activity. The cause of the hypoproteinemia is a severe liver infection that destroyed the liver parenchyma and drastically changed the protein value. Reduced albumin production brought on by liver injury could be the cause of the hypoalbuminemia. 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Archive of Applied Mechanics , 93(5), 1771-1796. https://doi.org/10.1007/s00419-023-02368-6 van Wyk IC, Goddard A, de C Bronsvoort BM, Coetzer JA, Booth C, Hanotte O, Jennings A, Kiara H, Mashego P, Muller C, Pretorius G, Poole EJ, Thumbi SM, Toye PG, Woolhouse, ME, Penzhorn BL, (2012) Hematological profile of East African short-hornzebu calves from birth to 51 weeks of age. Comp Clin Path , 22(5):1029-1036. https://doi.org/10.1007/s00580-012-1522-6 Tables Table 1: Prevalence of Fasciolisis in Katsina Abattoir Cattle No. Examined Prevalence (%) No. positive 05 3.73 No. negative 129 96.27 Total 134 3.73 Table 2: Sex Specific Distribution of Fascioliasis in Katsina Abattoir Sex No. Examined No. Infected Prevalence (%) Male 46 01 2.17 Female 88 04 4.55 TOTAL 134 05 3.73 Table 3: Age Specific Distribution of Fascioliasis in Katsina Abattoir Age group (years) No. Examined No. Infected Prevalence (%) 0-1 00 00 00 2-3 04 01 25 3-4 29 02 6.89 4-5 42 00 00 >5 59 01 1.74 TOTAL 134 05 3.73 Table 4: Breed Specific Distribution of Fascioliasis in Katsina Abattoir Breed No. Examined No. Infected Prevalence (%) WF 81 04 4.93 RB 38 00 00 WD 05 01 20.00 AZ 10 00 00 TOTAL 134 05 3.73 Table 5: Body Condition Score Specific Distribution of Fascioliasis in Katsina Abattoir Bcs No. Examined No. Infected Prevalence (%) Good 73 01 1.37 Medium 30 02 6.67 Poor 31 02 6.45 Total 134 05 3.73 Table 6: Mean±SD of heamatological changes between infected and un infected cattle at Katsina abattoir Haematological Parameters Infected(n=5) Range Uninfected(n=5) Range WBC X 10 3 /UL 4.8 ± 3.18 a 9600 – 17500 6.7 ± 1.13a 6300 – 12100 RBC X 10 6 /UL 6.3 ± 4.64 a 3.0 – 4.89 7.4 ± 0.45 b 5.51 – 8.9 HGB (g/dl) 9.8 ± 8.70 a 5.7 – 9.6 13.2 ± 3.39 b 8.5 – 13.6 HCT (%) 27.8 ± 21.43 a 19.5 – 29 36.6 ± 9.83 b 30 – 50 MCV (µm 3 )* 43.5 ± 1.97 a 61 – 69 48.8 ± 10.27 a 46 – 56 MCH (pg)* 14.3 ± 3.26 a 17 – 22 17.6 ± 3.50 a 12 – 18 MCHC (%) 32.8 ± 6.00 a 28 – 36 36.2 ± 0.44 a 26 – 33 Values in rows with different superscripts are significantly different ( P <0.05). SD= Standard deviation b n Size of sample Table 7: Mean±SD of differentials changes between infected and un infected cattle at Katsina abattoir Differential counts (%) Infected(n=5) Range Uninfected(n=5) Range Lymphocytes 32.8 ± 1.34 a 29 – 68 46.4 ± 12.94a 45 – 63 Esonophils 8.6 ± 4.03 a 2 – 8 18.2 ± 9.76 a 0.49 – 1.11 Neutrphils 77.6 ± 31.68 a 36 – 59 38.5 ± 8.56 b 26 – 40.5 Monocytes 4.3 ± 2.02 a 0.4 – 3 9.1 ± 4.88 b 0.83 – 8.58 Basophils 2.1 ± 1.01 a 00 5.7 ± 0.80 a 00 Values in rows with different superscripts are significantly different ( P <0.05). SD= Standard deviation b n Size of sample Table 8: Mean±SD of biochemical changes between infected and un infected cattle at Katsina abattoir Biochemical parameter Infected cattle un infected cattle ALT 62.93±18.86 61.68±30.66 AST 203.53±97.60 78.93±2.72 ALB 7.69±13.23 31.51±8.10 ALP 43.38±16.70 32.891±17.84 TP 43.38±16.70 49.66±40.40 CB 0.5±0.30 1.08±0.73 TB 5.61±3.20 2.61±0.28 ALT = Alanine aminotransferase, AST = Aspartate aminotransferase, ALB= Albumin ALP = Alkaline phophatase, TP = Total protein, CB= Conjugated bilirubin and TB = Total bilirubin Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3979445","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":275399717,"identity":"9efa5ddb-924d-4f38-a6ed-5c55c63ab7d5","order_by":0,"name":"BUHARI SHINKAFI YUSUF","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYBACAwYeMAkGHz5ARSWI1cI4cwbxWiCAcTaMjVeLuUTuwc8VBQyJG86fMWy2bduWuOEA88HbPAx37BpwaLGckZcsecYAqOVGjmFzbtttoBa2ZGsehmfJuLQY3MgxkGwAa+ExfwzRwmMmzcNwOBmnX27kGP8EawE5zBKshf8bIS1mEFsOAB3GCLGFDaTFDpcWy543ZpYNBhLGM2+kFTb2nLttPPMwm7HlHIPDCbi0mLPnGN9s+GMj23f+8MaGH2W3ZfuONz+88abisD0uLVAg4dgAZTk2MIMdzJDYgFM1BNjjZoyCUTAKRsGIBwAsV13L/1z86gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0004-6658-9732","institution":"Umaru Musa Yar'Adua University","correspondingAuthor":true,"prefix":"","firstName":"BUHARI","middleName":"SHINKAFI","lastName":"YUSUF","suffix":""},{"id":275399718,"identity":"1e4a1c81-d6f8-49f4-8130-803f8499cd4b","order_by":1,"name":"ABDULHAMID AHMAD","email":"","orcid":"","institution":"Umaru Musa Yar'Adua University","correspondingAuthor":false,"prefix":"","firstName":"ABDULHAMID","middleName":"","lastName":"AHMAD","suffix":""},{"id":275399719,"identity":"06bbe3be-6871-457a-9f65-e87f74b22125","order_by":2,"name":"Muhammed suleman","email":"","orcid":"","institution":"Umaru Musa Yar'Adua University","correspondingAuthor":false,"prefix":"","firstName":"Muhammed","middleName":"","lastName":"suleman","suffix":""},{"id":275399720,"identity":"fbaba42a-f9fd-49c2-8763-548266465a2f","order_by":3,"name":"IBRAHIM HAMZA KANKIYA","email":"","orcid":"","institution":"Umaru Musa Yar'Adua University","correspondingAuthor":false,"prefix":"","firstName":"IBRAHIM","middleName":"HAMZA","lastName":"KANKIYA","suffix":""},{"id":275399721,"identity":"9932e2d4-380e-4ba9-9fe5-9297a747f156","order_by":4,"name":"AMINU YABO BALA","email":"","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":false,"prefix":"","firstName":"AMINU","middleName":"YABO","lastName":"BALA","suffix":""},{"id":275399722,"identity":"48950ff3-f966-4e64-b1fe-720528481728","order_by":5,"name":"TUKUR ADAMU","email":"","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":false,"prefix":"","firstName":"TUKUR","middleName":"","lastName":"ADAMU","suffix":""}],"badges":[],"createdAt":"2024-02-22 18:21:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3979445/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3979445/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51969449,"identity":"d632dd81-9740-40ed-a737-5010a34fd257","added_by":"auto","created_at":"2024-03-04 18:40:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEggs of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eFasciola\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e observed under compound microscope during Bovine faecal examination ( X 100 magnification)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3979445/v1/51ae4cd6c298844033cbe176.jpg"},{"id":51969448,"identity":"2ca83923-d19d-4dc6-94cb-b234c1d13e23","added_by":"auto","created_at":"2024-03-04 18:40:36","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":215113,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUnnumbered image in the Materials and methods.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Unnumber.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3979445/v1/b8b2e8c11005c0fa8be6e099.jpeg"},{"id":58532037,"identity":"12de476b-3a7d-46e8-9a84-1e12dd01a5c2","added_by":"auto","created_at":"2024-06-18 01:11:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1100101,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3979445/v1/3cf29e3a-0776-4e43-9db1-196398a3c912.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eEpidemiology of Bovine Fascioliasis: Assessing Prevalence and Investigating Hemato-Biochemical Alterations in Katsinaabattoir North Western Nigeria\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBovine fascioliasis is a parasitic disease that greatly affects the health and production of cattle globally. It is caused primarily by liver flukes namely; \u003cem\u003eFasciola hepatica\u003c/em\u003e and \u003cem\u003eFasciola gigantica\u003c/em\u003e (Hayward, et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cattle are the ultimate host in the intricate life cycle of these trematodes, which also involve snail and mammalian hosts (Saijuntha, et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Geographically, the prevalence of bovine fascioliasis varies, but it is still a major concern in many areas, especially those where the intermediate host, freshwater snails, have favourable environmental circumstances (Siles-Lucas, et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInfected cattle with this parasite infection experience a variety of hematological and biochemical changes that contribute to both subclinical and clinical symptoms (Villa, et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Haematology is the study of the numbers and morphology of the blood's cellular components, such as the red blood cells (erythrocytes), white blood cells (leucocytes), and platelets (thrombocytes), and it makes use of the findings to diagnose and track disease (Wajihah, \u003cem\u003eet al.\u003c/em\u003e, 2023). According to Chikhaoui, et al., (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) biochemical changes include variations in different blood components and serum parameters, whereas hematological changes relate to changes in the makeup of the blood. Comprehending these alterations is crucial for the prompt identification and handling of bovine fascioliasis, in addition to evaluating the general well-being of impacted animals (Caravedo, and Cabada, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to Abdullah (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the life cycle of \u003cem\u003eFasciola\u003c/em\u003e entails the discharge of infectious larvae (metacercariae) onto vegetation, which are then consumed by cattle when they graze. After being consumed, the parasites move through the gastrointestinal tract, arrive in the liver, and settle in the bile ducts (Peters, et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The liver parenchyma and bile ducts are harmed by the liver flukes' feeding on blood and tissue (Kahl, et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Hematological and biochemical studies can identify a series of physiological alterations brought on by the host's immune system's reaction to the parasites as well as the direct harm the flukes inflict (Lalor, et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt has been discovered that the livestock industries have suffered significant financial losses as a result of animal deaths, weight loss from the carcass, decreased milk yield, liver damage, decreased production, subpar performances, and animal exposure to other diseases because of secondary complications, and high treatment costs (Mequaninit, and Mengesha, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Few studies have been documented on the prevalence, haematological and biochemical alterations due to naturally acquired bovine fascioliasis in Nigeria. Therefore, this research aims to explore and elucidate the prevalence, haematological and biochemical alterations associated with bovine fascioliasis. The findings from this research will further pave way for veterinarians, researchers, and livestock managers to enhance their ability to diagnose and manage this parasitic infection effectively. Moreover, the insights gained from studying the haematological and biochemical aspects of bovine fascioliasis will contribute to the broader understanding of host-parasite interactions and provide a foundation for developing strategies to control and prevent the spread of this economically significant disease.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area:\u003c/h2\u003e \u003cp\u003eThis study was carried out in the central abattoir of Katsina town, Katsina State, Nigeria. Katsina town, is the capital city of Katsina state as well as Headquarters of Local government Area, Katsina state, Nigeria. Katsina town is approximately located on latitude 12\u003csup\u003eo\u003c/sup\u003e N and longitude 7\u003csup\u003eo\u003c/sup\u003e E. (Anonymous 2012). The city is well known as a centre for Agriculture, producing both food and cash crops comprising groundnut, cotton, hides, millet, maize and guinea corn. The city is largely inhabited by the Haausa/Fulani ethnic groups (Anonymous 2012). The climate of the area comprises the Sudan savanna vegetation which is characterized by scattered trees, seasonal rainfall which lasts for about five months annually (June to October) and distinct harmattan season which spans from November to February each year, with reduced temperatures, haze and low humidity (Thor West et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCollection and examination of faecal samples\u003c/h2\u003e \u003cp\u003eThe samples were collected from the rectum or from the fresh stool of the sampled cattle on the ground, in plastic carved sample containers for qualitative and quantitative microscopic examination of \u003cem\u003eFasciola\u003c/em\u003e eggs. Faecal samples were processed using faecal sedimentation method as described by (Rizwan, et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Samples that are not processed within 24 hours from collection were stored in a refrigerator at 4\u003csup\u003e0\u003c/sup\u003e C. During every faecal sampling, information on sex, breed, approximate age and body condition of the individual animals were recorded (Rizwan, et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCollection of Blood sample\u003c/h2\u003e \u003cp\u003eSamples were collected over a period of 12 weeks. During slaughtering, 134 blood samples were collected from Katsina central slaughter house into evacuated EDTA container for haematological analysis and stored at 4\u0026deg;C and into serum separating tubes for biochemical analysis. Sera were frozen in plastic tubes at \u003cem\u003e\u0026minus;\u003c/em\u003e\u0026thinsp;20\u0026deg;C. Samples were analyzed within 12 hours. The samples were transported to Haematology Laboratory at general hospital Daura Katsina State for haematological analysis and postgraduate research laboratory at Umaru Musa Yar\u0026rsquo;adua University Katsina for Biochemical analysis (Brahmbhatt, et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHaemato-biochemical studies\u003c/h2\u003e \u003cp\u003eBlood and serum samples were collected from the \u003cem\u003eFasciola\u003c/em\u003e infected and non infected animals for routine haematological and serum biochemical analysis. A total of four (4) blood and serum samples from \u003cem\u003eFasciola\u003c/em\u003e infected and one hundred and thirty (130) samples from healthy animals were collected during the study and analyzed. Haematological analysis of the blood samples was done by using Sysmex particle counter (Model 210) and biochemical analysis of the serum samples were done by with commercial kit (Randox, UK) respectively (Brahmbhatt, et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data obtained was analyzed using SPSS version 16. Student t-test was used to analyze the data on the haematological and biochemical parameters of the \u003cem\u003eFasciola-\u003c/em\u003einfected and the non-infected samples. Values of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered significant. Results were expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and Discussions","content":"\u003cp\u003eThe results of coprology showed that, out of the One Hundred and thirty four (134) cattle examined, 5 were infected, representing a prevalence of 3.73 percent, while One hundred and twenty nine (129) were not infected, with a prevalence of 96.3 percent (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Coprology's low prevalence of 3.73% is in line with findings from some previous researches by Akpabio (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Okonkwo et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who found low prevalence rates of 1.7% and 13.5% respectively. It is not, however, consistent with the results of Njoku-Tony (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Adedokun et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and Abraham and Jude (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who found higher incidences ranging from 23.3\u0026ndash;75% in the southern region of the Nigeria. The high prevalence in the southern part of Nigeria may be related to variations in the climate and dense vegetation, which would favor the growth of the snail vector and raise the infection rate. However, the results of researches conducted by Soba \u003cem\u003eet al.\u003c/em\u003e (2023) and Njobdi et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), although done in Northern Nigeria, reported higher prevalences in Gombe (74.3%) and Benue (48.2%) states respectively, which are at odds with the low prevalence rate reported in this study. The variances in sample size, livestock abundance and climate in various areas could all be contributing factors to the discrepancies in prevalence.\u003c/p\u003e \u003cp\u003eThe results of sex-specific distribution of the infection showed that females had a higher prevalence, representing 4.55 percent, compared to their male counterparts with a prevalence of 2.17 percent (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The sex distribution analysis results showed that the prevalence was higher in female cattle than in male cattle. The increased susceptibility of females to the illness could be the reason for this. This conclusion is consistent with other research findings (Njok-Tony, 2011; Ardo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Uwalaka et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shima et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Banwo et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Okolugbo \u003cem\u003eet al.\u003c/em\u003e, 2023; Sabo et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It does, however, conflict with the results of some other researchers, like Oladele-Bukola and Odetokun (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), Adangs \u003cem\u003eet al.\u003c/em\u003e, (2015), Aliyu et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Ikenna-Ezeh et al., (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who found higher prevalences in males. This discrepancy could be explained by the custom of keeping a higher female-to-male ratio\u0026mdash;particularly when it comes to the ratio of cows to oxen\u0026mdash;and by keeping female animals around for the purpose of breeding and milk production.\u003c/p\u003e \u003cp\u003eThe results of age-specific distribution of the infection revealed that the age group 2\u0026ndash;3 years old, had the highest prevalence, representing 25 percent, followed by 3\u0026ndash;4 years with 6.89 percent. The least prevalence was recorded in the age group 5 years and above with 1.74 percent. No prevalence was recorded in the age groups 0\u0026ndash;1 year and 4\u0026ndash;5 years, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, the study found a greater frequency in the age range of 2\u0026ndash;3 years, which is in line with the findings of Uwalake \u003cem\u003eet al.\u003c/em\u003e (2019) and Aliyu et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who also found that young calves had a higher prevalence than adult cattle. This goes against the results of some other studies (Ardo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Adang et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) that showed a higher prevalence in adults than in young animals. Young cattle may be more susceptible to the high incidence because of their exposure to contaminated pasture, particularly when the pasture is chopped and fed to them.\u003c/p\u003e \u003cp\u003eThe results of breed-specific distribution of the infection showed that Wadara had the highest prevalence, representing 20 percent, and the least prevalence was recorded in White Fulani (4.93%). Zero prevalence was recorded in Red Bororo and Azwak, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In addition, the research revealed that the Wadara and White Fulani breeds had a significant prevalence rate of infection, whereas the Red Bororo and Azwak breeds showed no infection. This implies that some breeds are more prone to contracting the fascioliaisis than others, which may be related to how frequently these types are slaughtered at the slaughterhouse. This vulnerability may also be linked to variations in extrinsic (environment and management techniques) and intrinsic (genetic, physiological and immune) host variables. This result is in conflict with the findings of Soba \u003cem\u003eet al.\u003c/em\u003e (2023) and Olamelekan \u003cem\u003eet al.\u003c/em\u003e (2023), who showed high prevalence in Sokoto Gudali and Red Bororo, but it is consistent with the findings of a study conducted by Ikenna-Ezeh et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who observed no infection in Red Bororo and a high prevalence in White Fulani.\u003c/p\u003e \u003cp\u003eThe results of body condition score from this study, showed that those with medium condition revealed a high prevalence representing 6.67 percent, followed by those with poor condition (6.45%) and the least prevalence was recorded in those with good body condition (1.37%). The result was shown on (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Our findings are in line with the findings of Meharenet and Shitu (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who found that the medium conditioned animals were more infected in Ethiopia. However, our findings were in contrast to that of Uwalaka et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who reported a higher prevalence among poor conditioned animals in Abia state, Nigeria. The lowest prevalence of infection is consistently recorded among good physical conditioned animals. This suggested that the prevalence of fascioliasis is closely related to body condition, with the medium and poor conditioned being more prone to infection than the good.\u003c/p\u003e \u003cp\u003eThe results of the hematological indices determined for \u003cem\u003eFasciola\u003c/em\u003e-infected and non-infected cattle indicated that PCV, Hb, and RBC were lower in the infected cattle than in the non-infected ones. On the other hand, WBC, MCV, MCH, and MCHC were higher in the infected cattle compared to the uninfected animals. Statistical analysis revealed highly significant differences between the PCV, Hb, and RBC of the infected and non-infected cattle (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and significant differences between the WBC, MCV, and MCH of both groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no significant differences were observed between the MCHC of the infected cattle and the uninfected ones (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In comparison to the uninfected cattle, the haematological changes among the infected cattle, resulted in a substantial drop in the mean values of WBC, RBC, HGB, HCT, and MCH and a significant increase in the mean values of MCV and MCHC. The present discovery aligns with multiple other studies that have documented a decline in the same parameters' (Wyk et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Egbu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e and Brahmbhatt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). But the lower values of RBC, WBC, HGB, and HCT in infected cows may be the result of an adult fluke's blood-sucking behavior as well as blood loss from hemorrhages brought on by the immature parasite's extensive migration through the bile duct and liver parenchyma as earlier suggested (Etim et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e and Brahmbhatt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The present study's findings regarding the significant increase in MCHC in infected cattle are consistent with those of Brahmbhatt et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe differential counts of Fasciola-infected cattle and the uninfected ones revealed a perceptible increase in the neutrophils of the infected cattle and a clear decrease in the levels of eosinophils, monocytes, lymphocytes, and basophils in the infected cattle. The differences in the neutrophils, eosinophils, monocytes, and lymphocytes of both groups were highly significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05. According to the current findings, peripheral blood from infected animals had higher neutrophil counts than from uninfected animals, suggesting that neutropilia developed during the \u003cem\u003eFasciola\u003c/em\u003e infection of cows. A substantial rise in monocytes, basophils, and eosinophils is indicative of a parasite infection. This is consistent with a research finding by Brahmbhatt et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which reported that between infected and non-infected Gir cattle, there were low levels of eosonophils, monocytes, and basophils and high levels of neutrophils. However, these results conflict with those of Egbu (2013) and Matanovic \u003cem\u003eet al.\u003c/em\u003e (2007), who found that the infected group had significantly higher neutrophil and eosinophil counts compared to the uninfected, and that the infected group had significantly, lower levels of monocytes and lymphocytes. The variations in the differential counts could be the result of a toxin-mediated lesion of the bone marrow or a body defence mechanism against the obstructive effects of \u003cem\u003eFasciola\u003c/em\u003e as earlier suggested (Egbu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results of the biochemical changes indicated that the means and standard deviations of ALT, AST, ALP, and TB were higher in the infected cattle than the uninfected ones, while ALB, TP, and CB were higher in uninfected cattle than their infected counterparts (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). An additional sign of internal organ injury is observed from the results of biochemical analysis. ALB, TP (total protein), and CB levels considerably decreased among the infecrted cattle (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the current study, while ALT, AST, ALP, and total bilirubin levels increased also among the infected (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These discoveries agreed with the results from other researches (Brahmbhatt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ellah et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kitila Megersa, 2014). Higher AST and ALT activity is typically seen in cases of \u003cem\u003eFasciola\u003c/em\u003e infection because the parasite damages the liver through migratory activity, which in turn triggers the activation of inflammatory cells that produce fibrosis and necrosis and increases AST and ALT activity. The cause of the hypoproteinemia is a severe liver infection that destroyed the liver parenchyma and drastically changed the protein value. Reduced albumin production brought on by liver injury could be the cause of the hypoalbuminemia. Biliary blockage, values, and cholangitis are caused by fasciolosis infections. Reduced albumin production brought on by liver injury could be the cause of the hypoalbuminemia. Cholangitis, biliary obstruction, fibrosis and loss of hepatic tissue, and anemia are all caused by fascilococcal infections as earlier reported (Brahmbhatt, 2021).\u003c/p\u003e "},{"header":"Declarations","content":" \u003cp\u003e\u003cstrong\u003eCompliance with ethical standard\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThere is no complicit of interest with any person or organization\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003eWe highly thankful to TEDFUND and Head of Laboratory Department General hospital Daura Katsina State for funding the research and allowing me to use their facilities for the study respectively.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdullah, S. H. (2023). Fascioliasis. One Health Triad, Unique Scientific Publishers, Faisalabad, Pakistan, 3, 78-85.\u003c/li\u003e\n\u003cli\u003eAbraham, J. T., \u0026amp; Jude, I. B. 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A review on non-Newtonian fluid models for multi-layered blood rheology in constricted arteries. \u003cem\u003eArchive of Applied Mechanics\u003c/em\u003e, 93(5), 1771-1796. https://doi.org/10.1007/s00419-023-02368-6\u003c/li\u003e\n\u003cli\u003evan Wyk IC, Goddard A, de C Bronsvoort BM, Coetzer JA, Booth C, Hanotte O, Jennings A, Kiara H, Mashego P, Muller C, Pretorius G, Poole EJ, Thumbi SM, Toye PG, Woolhouse, ME, Penzhorn BL, (2012) Hematological profile of East African short-hornzebu calves from birth to 51 weeks of age. \u003cem\u003eComp Clin Path\u003c/em\u003e, 22(5):1029-1036. https://doi.org/10.1007/s00580-012-1522-6\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Prevalence of Fasciolisis in Katsina Abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCattle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. negative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e96.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Sex Specific Distribution of Fascioliasis in Katsina Abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Infected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e2.17 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Age Specific Distribution of Fascioliasis in Katsina Abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Infected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0-1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2-3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3-4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4-5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Breed Specific Distribution of Fascioliasis in Katsina Abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBreed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Infected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTAL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Body Condition Score Specific Distribution of Fascioliasis in Katsina Abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBcs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Examined\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Infected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e6.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e134\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e05\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6: Mean\u0026plusmn;SD of heamatological changes between infected and un infected cattle at Katsina abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHaematological Parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfected(n=5)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUninfected(n=5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eWBC \u0026nbsp; \u0026nbsp; X 10\u003csup\u003e3\u003c/sup\u003e/UL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e4.8 \u0026plusmn; 3.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e9600 \u0026ndash; 17500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e6.7 \u0026plusmn; 1.13a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e6300 \u0026ndash; 12100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eRBC \u0026nbsp; \u0026nbsp; X 10\u003csup\u003e6\u003c/sup\u003e/UL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e6.3 \u0026plusmn; 4.64\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e3.0 \u0026ndash; 4.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e7.4 \u0026plusmn; 0.45\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e5.51 \u0026ndash;\u0026nbsp;8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eHGB (g/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e9.8 \u0026plusmn; 8.70\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e5.7 \u0026ndash;\u0026nbsp;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e13.2 \u0026plusmn; 3.39\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e8.5 \u0026ndash;\u0026nbsp;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eHCT (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e27.8 \u0026plusmn; 21.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e19.5 \u0026ndash;\u0026nbsp;29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e36.6 \u0026plusmn; 9.83\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e30 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eMCV\u0026nbsp;(\u0026micro;m\u003csup\u003e3\u003c/sup\u003e)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e43.5 \u0026plusmn; 1.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e61 \u0026ndash;\u0026nbsp;69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e48.8 \u0026plusmn; 10.27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e46 \u0026ndash;\u0026nbsp;56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eMCH\u0026nbsp;(pg)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e14.3 \u0026plusmn; 3.26\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e17 \u0026ndash;\u0026nbsp;22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"top\"\u003e\n \u003cp\u003e17.6 \u0026plusmn; 3.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e12 \u0026ndash;\u0026nbsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.975609756097562%\" valign=\"top\"\u003e\n \u003cp\u003eMCHC\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.8 \u0026plusmn; 6.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e28 \u0026ndash;\u0026nbsp;36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.83739837398374%\" valign=\"bottom\"\u003e\n \u003cp\u003e36.2 \u0026plusmn; 0.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.67479674796748%\" valign=\"top\"\u003e\n \u003cp\u003e26 \u0026ndash;\u0026nbsp;33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues in rows with different superscripts are significantly different (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eSD=\u003cem\u003e\u0026nbsp;\u003c/em\u003eStandard deviation\u003c/p\u003e\n\u003cp\u003eb \u003cem\u003en\u0026nbsp;\u003c/em\u003eSize of sample\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7: Mean\u0026plusmn;SD of differentials changes between infected and un infected cattle at Katsina abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"622\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDifferential counts (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfected(n=5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUninfected(n=5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003eLymphocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e32.8 \u0026plusmn; 1.34\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e29 \u0026ndash; 68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e46.4 \u0026plusmn; 12.94a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e45 \u0026ndash; 63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003eEsonophils\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e8.6 \u0026plusmn; 4.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e2 \u0026ndash; 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e18.2 \u0026plusmn; 9.76\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e0.49 \u0026ndash; 1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003eNeutrphils\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e77.6 \u0026plusmn; 31.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e36 \u0026ndash; 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e38.5 \u0026plusmn; 8.56\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e26 \u0026ndash; 40.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003eMonocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e4.3 \u0026plusmn; 2.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e0.4 \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e9.1 \u0026plusmn; 4.88\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e0.83 \u0026ndash; 8.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.824476650563607%\" valign=\"top\"\u003e\n \u003cp\u003eBasophils\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.96779388083736%\" valign=\"top\"\u003e\n \u003cp\u003e2.1 \u0026plusmn; 1.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.908212560386474%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.357487922705314%\" valign=\"top\"\u003e\n \u003cp\u003e5.7 \u0026plusmn; 0.80\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.942028985507246%\" valign=\"top\"\u003e\n \u003cp\u003e00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues in rows with different superscripts are significantly different (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eSD=\u003cem\u003e\u0026nbsp;\u003c/em\u003eStandard deviation\u003c/p\u003e\n\u003cp\u003eb \u003cem\u003en\u0026nbsp;\u003c/em\u003eSize of sample\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8: Mean\u0026plusmn;SD of biochemical changes between infected and un infected cattle at Katsina abattoir\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiochemical parameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfected cattle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eun infected cattle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e62.93\u0026plusmn;18.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e61.68\u0026plusmn;30.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e203.53\u0026plusmn;97.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e78.93\u0026plusmn;2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e7.69\u0026plusmn;13.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e31.51\u0026plusmn;8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e43.38\u0026plusmn;16.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e32.891\u0026plusmn;17.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e43.38\u0026plusmn;16.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e49.66\u0026plusmn;40.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e0.5\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.08\u0026plusmn;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.58278145695364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.13907284768212%\" valign=\"top\"\u003e\n \u003cp\u003e5.61\u0026plusmn;3.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.27814569536424%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.61\u0026plusmn;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eALT = Alanine aminotransferase, AST = Aspartate aminotransferase, ALB= Albumin ALP = Alkaline phophatase, TP = Total protein, CB= Conjugated bilirubin and TB = Total bilirubin\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"prevalence, Bovine, Fascioliasis, Haematology and Biochemical parameters","lastPublishedDoi":"10.21203/rs.3.rs-3979445/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3979445/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBovine fascioliasis, caused by liver flukes \u003cem\u003eFasciola hepatica\u003c/em\u003e and \u003cem\u003eFasciola gigantica\u003c/em\u003e, significantly impacts global cattle health and production. This study aimed to assess the prevalence of bovine fascioliasis and its associated hematobiochemical changes on cattles brought for slaughter at Katsina central abattoir. Fecal and blood samples were collected from total of 134 cattles. Fecal samples were examined using sedimentation technique, revealing an infection prevalence of 3.73%. Notably, females exhibited a higher prevalence (4.55%) compared to males (2.17%), though the difference was not statistically significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The age group 2\u0026ndash;3 years showed the highest prevalence (25.00%), while those aged 5 and above had the lowest prevalence (1.74%). Among cattle breeds, Wadara had the highest prevalence (20.00%), while White Fulani exhibited the least (4.93%). Concerning body condition score (BCS), medium-conditioned cattle had the highest prevalence (6.67%), and good-conditioned ones showed the least (1.37%). Hematological analysis of \u003cem\u003eFasciola\u003c/em\u003e-infected cattle revealed significant reductions (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in packed cell volume (PCV), hemoglobin (Hb), and total erythrocyte count (RBC) compared to the non-infected ones. Additionally, infected cattle demonstrated a significant decrease in white blood cell (WBC) count, mean cellular volume (MCV), and mean cellular hemoglobin concentration (MCHC) compared to the uninfected. Moreover, differential leukocyte counts indicated a notable increase in neutrophils and a decrease in eosinophils, monocytes, and basophils in infected cattle compared to the uninfected, although the difference is not statistically significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Biochemical analysis unveiled significantly elevated levels of alanine transaminase (ALT) and aspartate transaminase (AST), along with increased alkaline phosphatase (ALP) and total bilirubin (TB) in infected cattle (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Conversely, albumin (ALB), total protein (TP), and conjugated bilirubin (CB) levels were significantly reduced among infected than uninfected cattle (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Our findings, further confirmed that Bovine fascioliasis has significant impact on the health and productivity of Cattle bred in Katsina state and elsewhere. Understanding its prevalence and associated heamato-biochemical changes among infected animals is essential for implementing effective control and management strategies.\u003c/p\u003e","manuscriptTitle":"Epidemiology of Bovine Fascioliasis: Assessing Prevalence and Investigating Hemato-Biochemical Alterations in Katsinaabattoir North Western Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-04 18:40:32","doi":"10.21203/rs.3.rs-3979445/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b46af150-aecb-4891-a177-33a2c0a38767","owner":[],"postedDate":"March 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-18T01:02:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-04 18:40:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3979445","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3979445","identity":"rs-3979445","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}