Comparison of manual and automated methods in the hematological evaluation of a frugivorous bat captured in urban green areas

Comparison of manual and automated methods in the hematological evaluation of a frugivorous bat captured in urban green areas | 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 Short Report Comparison of manual and automated methods in the hematological evaluation of a frugivorous bat captured in urban green areas Melissa Harumi Sumiyoshi, Eva Munyque da Cruz, Morgana Maira Hennig, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9237637/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 17 You are reading this latest preprint version Abstract Increasing and unplanned urbanization can intensify wildlife contact with humans and domestic animals, raising concerns about the spillover of zoonotic diseases. Bats play an important ecological role due to their great niche diversity and wide distribution, but they are reservoirs for various pathogens. Despite their importance, hematological values for non-hematophagous bats remain scarce, which makes it difficult to assess their health and physiological responses. Here, we describe hematological values ​​and blood cell morphology of 24 individuals of Artibeus planirostris captured in urban green areas of Cuiabá, Brazil, and compare automated and manual hematological methods. Blood samples were analyzed using an automated hematology analyzer, microhematocrit, cyanmethemoglobin method and blood smear microscopy for differential leukocyte count, platelet estimation and morphological evaluation. The erythrogram showed high hematocrit, hemoglobin, and erythrocyte values and low Mean Corpuscular Volume, which may indicate adaptations to intensified energy metabolism and high oxygen demand to flight. Leukocyte analysis showed an increased neutrophil:lymphocyte ratio in more than half of the individuals, indicating a possible stress response. Significant differences were found between automated and manual methods for hemoglobin, hematocrit, and platelet measurements. Automated hemoglobin values showed lower variability, while manual hematocrit and platelet estimates demonstrated greater precision. These results emphasize the importance of combining automated and microscopic techniques in bat hematology and contribute to the establishment of hematological parameters for A. planirostris in urban environments. Artibeus planirostirs Erythrogram Leukogram Neutrophil:lymphocyte ratio Phyllostomidae Figures Figure 1 Introduction With increasing urbanization and environment changes, wildlife faces habitat loss and closer contact with humans and domestic animals, which can lead to the emergence of zoonotic diseases (Miguel et al. 2019; Tazerji et al. 2022). The order Chiroptera comprises a great diversity of species with morphophysiological variations, being important in the maintenance of ecosystems (Strumpf et al. 2020). However, their wide distribution, dispersion due habitat loss and the stress of adapting to anthropogenic environments makes them potential reservoirs of numerous etiological agents of zoonotic character (Villaba-Alemán et al. 2020). Therefore, understanding their ecology, epidemiology and physiology is important for One Health monitoring (Tazerji et al. 2022; Teles et al. 2023). An important and accessible tool to assess physiological and health status is the hematological evaluation (Miguel et al. 2019; Strumpf et al. 2020; Hansen et al. 2022). However, reference values for wild species, especially non-hematophagous bats, remain scarce (Kuzel et al. 2020; Teles et al. 2023). Although automated analyzers are increasingly used, interspecific variation may affect their accuracy, making microscopic evaluation essential (Hansen et al. 2022). This study aimed to report hematological parameters of 24 individuals of Artibeus planirostris captured in urban green areas of Cuiabá, Brazil, and to perform morphological and quantitative analyses of blood cells through microscopy. Additionally, selected parameters obtained by automated methods, such as hemoglobin, hematocrit and platelets, were compared with manual or semi-automated techniques. These findings may contribute in future studies on health conditions and pathogen dynamics of A. planirostris populations. Materials and Methods Capture, identification and sample collection Bats were captured with mist-nets during two sampling events in January and March 2025 at two locations in Cuiabá, Brazil: the Center for Medicine and Research in Wild Animals of the Federal University of Mato Grosso (UFMT) and Mãe Bonifácia State Park. Individuals were captured and placed individually in cloth bags, then weighed, examined for ectoparasites, sexed and assessed for reproductive status, with pregnant or lactating animals released. Bats were anesthetized by intraperitoneal injection of xylazine hydrochloride (10 mg/kg) and ketamine hydrochloride (60 mg/kg), then the blood was collected by cardiac puncture. Species identification followed established taxonomic keys (Diaz et al. 2021; Gardner 2007). Sample processing Samples were processed at the Veterinary Clinical Pathology Laboratory of UFMT within 2-12 hours after collection and kept refrigerated until analysis. Blood smears were prepared and microhematocrit tubes were filled to determine manual hematocrit. Hemoglobin concentration was measured using the cyanmethemoglobin (CiCN) method and compared with automated results. Samples with clots or large amounts of fibrin were excluded from the analysis. Hematological parameters, including total erythrocytes, leukocytes and platelets, hematocrit and hemoglobin concentration, Mean Corpuscular Volume (MCV) and Mean Corpuscular Hemoglobin Concentration (MCHC) were obtained using an automated analyzer pocH-100iV Diff (Sysmex®), adapted with hematological values of A. lituratus from the study by Kuzel et al. (2020). Hematology analysis Blood smears were analysed under light microscopy for cell morphology and differential leukocyte counts at 100 cells per slide at magnifications of 400× and 1000×. Platelets were estimated in ten random fields and the mean value was multiplied by a factor of 15,000 (Stockham and Scott 2025). Statistical analysis Data were analyzed using descriptive statistics in Microsoft Excel®, including mean, standard deviation and 90% confidence interval, following ASVCP guidelines (Friedrichs et al 2012). Paired comparisons of hemoglobin, hematocrit and platelet measurements were performed using Jamovi® software. The Shapiro–Wilk test was used to assess normality, followed by either the paired T-test or Wilcoxon test as appropriate. Statistical significance was set at p < 0.05. Results Hematological parameters of 24 specimens of Artibeus planirostris were described in Table 1. Total manual erythrocyte and leukocyte counts were not performed, but blood smears were used for differential leukocyte counts, platelet estimation and morphological evaluation. Sex-based analysis was not conducted due to the small sample size, but 16.7% (4/24) were females and 83.3% (20/24) were males. Table 1 Hematological parameters of Artibeus planirostris obtained by automated, semi-automated and manual methods in urban areas of Cuiabá, Brazil Parameters (Unit of measurement) n Mean (SD) Variation IC (90%) Method Erythrocytes (10 6 /μL) 24 11.98 (1.47) 8.28-14.24 11.49-12.48 Automated Hemoglobin (g/dL) 24 17.63 (1.60) 14.20-20.40 17.09-18.17 Automated *Hemoglobin (g/dL) 24 21.38 (2.73) 15.13-25.53 20.46-22.30 CiCN Hematocrit (%) 24 59.40 (6.19) 45.90-70.40 57.30-61.40 Automated *Hematocrit (%) 24 52.50 (4.32) 44.00-60.00 51.00-54.00 Microhematocrit MCV (fL) 24 49.70 (2.72) 45.70-56.60 48.80-50.60 Automated MCHC (g/dL) 24 29.70 (0.72) 28.30-30.90 29.50-30.00 Automated Leukocytes (10³/μL) 24 6.50 (3.74) 1.30-13.80 5.20-7.70 Automated Band neutrophils (10³/μL) 24 0.00 (0) 0.00 0.00 Microscopic evaluation Segmented neutrophils (10³/μL) 24 3.00 (1.86) 0.62-6.92 2.40-3.70 Microscopic evaluation Eosinophils (10³/μL) 24 0.10 (0.19) 0.00-0.73 0.10-0.20 Microscopic evaluation Basophils (10³/μL) 24 0.00 (0.03) 0.00-0.11 0.00-0.00 Microscopic evaluation Lymphocytes (10³/μL) 24 3.10 (2.85) 0.48-10.50 2.10-4.00 Microscopic evaluation Monocytes (10³/μL) 24 0.20 (0.25) 0.00-0.89 0.10-0.30 Microscopic evaluation Platelets (10³/µL) 18 864.30 (231.87) 435.00-1326.00 779.00-949.60 Automated *Platelets (10³/µL) 18 500.30 (119.93) 232.00-725.00 456.20-544.40 Microscopic evaluation Total plasma protein (g/dL) 23 5.90 (0.61) 5.00-7.20 5.70-6.10 Refractometer *Hemoglobin: CiCN method. Hematocrit: microhematocrit. Platelets: estimated in blood smears. (SD: Standard Deviation) Echinocytes (Figure 1a) were observed in 41.6% (10/24) of individuals. One bat presented markedly lower erythrocytes, hemoglobin and hematocrit values, respectively 8.28 x 10 6 /μL, 14.20 g/dL and 45.90% (measurement in pocH-100iV Diff); 18.36 g/dL (hemoglobin by CiCN method) and 44.00% (hematocrit by microhematocrit technique) and this one had anisocytosis (Figure 1b). Neutrophils (Figure 1c) were the predominant leukocyte in 58.3% (14/24) of the individuals, while lymphocyte (Figure 1d) predominance was observed in 41.7% (10/24). The mean neutrophil:lymphocyte ratio was 1.68. Other leukocytes, including eosinophils (Figure 1e), basophils (Figure 1f) and monocytes (Figure 1g) were presented in lower numbers. Activated monocytes (Figure 1h) were observed in 25% (6/24) of the individuals, with variable intensity and size of vacuoles. Platelets counts were excluded in six individuals due to moderate to intense platelet aggregation (Figure 1i-j). Additionally, platelet inclusions (Figure 1k) and macroplatelets (Figure 1l) were observed in one individual. Total plasma protein could not be measured due to hemolysis in one sample. Comparisons between automated and manual or semi-automated methods (Table 2) showed significant differences for hemoglobin, hematocrit and platelet counts (p < 0.05). Table 2 Comparison between different methods for three hematological parameters of Artibeus planirostris captured in urban areas of Cuiabá, Brazil Parameter (Unit of measurement) *Other methods pocH-100iV Diff Normality test **Statistics Mean SD Mean SD Hemoglobin (g/dL) 21.38 2.73 17.63 1.60 p = 0.001 p < 0.0001 Hematocrit (%) 52.50 4.32 59.40 6.19 p = 0.001 p < 0.0001 Platelets (10³/µL) 603.80 148.96 976.50 362.12 p = 0.250 p < 0.0001 * Hemoglobin: CiCN method. Hematocrit: microhematocrit. Platelets: estimated in blood smears. ** Hemoglobin and Hematocrit: Wilcoxon test. Platelets: T-test. Discussion Elevated hematocrit, hemoglobin and erythrocyte values observed in bats, including A. planirostris, may indicate physiological adaptations to heightened metabolic demands and oxygen needs inherent in sustained flight (Schinnerl et al. 2011; Miguel et al. 2019; Villalba-Alemán et al. 2020; Kuzel et al. 2020). Similarly, low MCV reflects reduced erythrocyte size, which improves oxygen binding and increases their oxygen-carrying (Almeida et al. 2014). Echinocytes were observed in 41.6% of individuals, a finding also reported in the pteropodid fruit bat Pteropus alecto in Australia (Hansen et al. 2022), and might be associated with preparation artifacts, EDTA excess, dehydration, electrolyte imbalance, intense exercise, or pathological conditions including kidney disease or snakebite poisoning (Thrall et al. 2024). One individual showed lower erythrogram values and anisocytosis, suggesting anemia, a condition also seen in other bat species (Schinnerl et al. 2011; Hansen et al. 2022) . Leukocyte analysis revealed an increased neutrophil:lymphocyte (N:L) ratio in more than half of the individuals, consistent with findings reported for other bat species (Almeida et al. 2014; Hansen et al. 2022; Kuzel et al. 2020; Teles et al. 2023). This pattern may be associated with physiological response to stress mediated by corticosteroids, resulting in lymphopenia and neutrophilia (Stockham and Scott, 2025; Viola et al. 2022). Anesthetic protocols may also influence leukocyte profiles, as xylazine and ketamine can increase total leukocyte count during anesthesia, simulating a stress leukogram (Hanif et al. 2025). In bats, however, information is scarce, and only one study reported increased lymphocyte counts following isoflurane anesthesia (Strumpf et al. 2020). The N:L ratio has been used as an indirect indicator of stress (Viola et al. 2022). Miguel et al. (2019), observed higher N:L ratios in fruit bats, including A. lituratus and A. planirostris, as habitat availability decreased, suggesting that the elevated N:L ratio observed in this study may also be related to smaller amount of habitat, since the bats were captured in urban green areas. Lymphocyte predominance is commonly reported in many species of bats (Schinnerl et al. 2011; Strumpf et al. 2020; Teles et al. 2023; Villalba-Alemán and Muñoz-Romo 2016; Villalba-Alemán et al. 2020) and is known as inverted leukocyte formuls, a pattern also observed in some domestic mammals and possibly related to genetic factors (Villalba-Alemán and Muñoz-Romo 2016). Monocytes showed typical morphology, with activated forms observed in some individuals, as previously reported in other bats (Hansen et al. 2022). These findings may occur in small numbers in domestic animals under normal conditions, but may also indicate inflammatory or infectious processes (Stockham and Scott 2025). Basophilic inclusions in platelets compatible with Anaplasma sp. were observed in one individual, similar to findings in urban bats in Colombia (Villalba-Alemán et al. 2020). However, due to their similarity to dye precipitates or nuclear fragments, diagnostic confirmation must be performed by PCR (Stockham and Scott 2025). Macroplatelets were also identified in the same animal. Although their clinical significance in bats is unknown, in dogs they are associated with increased platelet regeneration, whereas in cats they may occur as a physiological finding (Thrall et al. 2024). Significant differences between automated and manual methods for hematocrit, hemoglobin and platelet counts highlight limitations of automated analyzers not validated for bats, since the device used in this study is standardized for domestic mammals (Riond et al. 2011). These differences likely reflect species-specific blood characteristics and methodological differences. The hematological values used in the analyzer were obtained from the study by Kuzel et al. (2020), which evaluated bats of the same genus, but another species, A. lituratus . Considering confidence interval and standard deviation, automated hemoglobin showed lower variation, whereas manual hematocrit and platelet estimates obtained by microscopy indicated greater precision. The CiCN method is recognized as a reference method for hemoglobin concentration and is widely used for calibration of other analytical methods (Whitehead et al. 2019). However, differences observed between CiCN and automated methods may occur due to methodological principles, sample type, processing time, equipment calibration and quality control. Manual hematocrit measures packed cell volume directly, while automated hematocrit is calculated from erythrocyte count and MCV, which may lead to overestimation in samples with erythrocyte morphological alterations or EDTA storage effects (Thrall et al. 2024; Stockham and Scott 2025). Although samples with fibrin or clots were excluded, differences between automated platelet counts and microscopy estimates may still be associated with platelet aggregates, which can interfere with automated measurements, especially in stressful situations (Stockham and Scott 2025). The characterization of hematological parameters in bats, particularly species inhabiting urban areas such as A. planirostris , is important for monitoring population health, identifying stress through N:L ratio and supporting studies on physiology, immunity and conservation. The comparison of methods indicates that automated analysis may provide more stable hemoglobin measurements, while manual methods reduce interference in hematocrit calculation and platelet counts. As automated hematology is not yet standardized for non-hematophagous bats, integrated interpretation using automated, semi-automated and manual methods, especially microscopic evaluation, is recommended. Further studies with larger sample sizes are needed to standardize automated techniques and establish more consistent and representative hematological parameters for these animals in anthropized environments. Declarations Author contributions Melissa Harumi Sumiyoshi: Investigation, data curation, writing-original draft, sample processing, hematology analysis and statistical analysis. Eva Munyque da Cruz, Kayana Mota Caribé de Figueiredo and Nathália Soares Lima Rabelo: Sample processing and hematology analysis. Morgana Maira Hennig: Capture, sample collection, investigation and writing-review. Marcela Natacha Aparecida Rocha: Methodology, sample processing, statistical analysis and writing-review. Gabriel de Mello, Glenda Akimi Ota, Guilherme Ratts de Almeida, Jéssica Inácio Gomes, Jhonathan França Bello and Mylene Karolina da Silva de Jesus: Capture, identification and sample collection. Alan Eriksson: Capture, identification, writing-review and funding acquisition. Richard de Campos Pacheco: Supervision, writing-review and funding acquisition. Rosa Helena dos Santos Ferraz: Sample processing, supervision, methodology, writing-review and editing. Adriane Jorge Mendonça: Supervision, methodology, formal analysis, writing-review and editing. All authors have read and agreed to the final version of the submitted manuscript. Funding This work was supported by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) and MEC (Ministério da Educação). Ethical approval The study was approved by the Ethics Committee on the Use of Animals (CEUA/UFMT) and registered under protocol number 23108.022778/2024-52. Competing interests The authors declare no competing interests. References Almeida MF, Trezza-Netto J, Aires CC, Barros RF, Rosa AR, Massad E (2014) Hematologic profile of hematophagous Desmodus rotundus bats before and after experimental infection with rabies virus. Rev Soc Bras Med Trop 47:371–373. https://doi.org/10.1590/0037-8682-0169-2013 Diaz M, Solari S, Gregorin R, Aguirre LF, Barquez RM (2021) Clave de identificación de los murciélagos neotropicales. 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Grosso","correspondingAuthor":false,"prefix":"","firstName":"Jhonathan","middleName":"França","lastName":"Bello","suffix":""},{"id":617883809,"identity":"6088cc20-3578-401b-93ac-4d311c0d508f","order_by":11,"name":"Mylene Karoline Silva de Jesus","email":"","orcid":"","institution":"Federal University of Mato Grosso","correspondingAuthor":false,"prefix":"","firstName":"Mylene","middleName":"Karoline Silva","lastName":"de Jesus","suffix":""},{"id":617883814,"identity":"181d574c-42c0-4aba-90a4-b8f66a575a47","order_by":12,"name":"Alan Eriksson","email":"","orcid":"","institution":"Federal University of Mato Grosso","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Eriksson","suffix":""},{"id":617883817,"identity":"a9b3c8f3-cc15-4a4a-aff3-f4f7321abede","order_by":13,"name":"Richard de Campos Pacheco","email":"","orcid":"","institution":"Federal University of Mato Grosso","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"de Campos","lastName":"Pacheco","suffix":""},{"id":617883820,"identity":"a62d1621-fff0-478b-a9ba-30de033a70e4","order_by":14,"name":"Rosa Helena dos Santos Ferraz","email":"","orcid":"","institution":"Federal University of Mato Grosso","correspondingAuthor":false,"prefix":"","firstName":"Rosa","middleName":"Helena dos Santos","lastName":"Ferraz","suffix":""},{"id":617883823,"identity":"e1e03cc8-098e-467f-a31a-016e7ef957eb","order_by":15,"name":"Adriane Jorge Mendonça","email":"","orcid":"","institution":"Federal University of Mato Grosso","correspondingAuthor":false,"prefix":"","firstName":"Adriane","middleName":"Jorge","lastName":"Mendonça","suffix":""}],"badges":[],"createdAt":"2026-03-26 19:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9237637/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9237637/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106345126,"identity":"c98a00b1-7e98-47b3-becd-0f4da1e67476","added_by":"auto","created_at":"2026-04-07 16:18:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1901722,"visible":true,"origin":"","legend":"\u003cp\u003ePhotomicrographs of erythrocytes, leukocytes and platelets morphology in blood smears of \u003cem\u003eArtibeus planirostris \u003c/em\u003estained with Romanowsky-type stain and observed at 1000× magnification. (\u003cstrong\u003ea\u003c/strong\u003e) echinocytes, (\u003cstrong\u003eb\u003c/strong\u003e) anisocytosis, (\u003cstrong\u003ec\u003c/strong\u003e) neutrophil, (\u003cstrong\u003ed\u003c/strong\u003e) lymphocyte, (\u003cstrong\u003ee\u003c/strong\u003e) eosinophil, (\u003cstrong\u003ef\u003c/strong\u003e) basophil, (\u003cstrong\u003eg\u003c/strong\u003e) monocyte, (h) activated monocyte, (\u003cstrong\u003ei-j\u003c/strong\u003e) platelet clumps, (\u003cstrong\u003ek\u003c/strong\u003e) basophilic inclusions in platelets, (\u003cstrong\u003el\u003c/strong\u003e) macroplatelet\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9237637/v1/7ae58155836ac226f6f33e75.png"},{"id":106345245,"identity":"ac1f307f-42c4-4410-894a-5faa844a310c","added_by":"auto","created_at":"2026-04-07 16:18:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3026882,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9237637/v1/552442c8-5a31-46e4-82aa-1009f7b2436b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of manual and automated methods in the hematological evaluation of a frugivorous bat captured in urban green areas","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith increasing urbanization and environment changes, wildlife faces habitat loss and closer contact with humans and domestic animals, which can lead to the emergence of zoonotic diseases (Miguel et al. 2019; Tazerji et al. 2022). The order Chiroptera comprises a great diversity of species with morphophysiological variations, being important in the maintenance of ecosystems (Strumpf et al. 2020). However, their wide distribution, dispersion due habitat loss and the stress of adapting to anthropogenic environments makes them potential reservoirs of numerous etiological agents of zoonotic character (Villaba-Alem\u0026aacute;n et al. 2020). Therefore, understanding their ecology, epidemiology and physiology is important for One Health monitoring (Tazerji et al. 2022; Teles et al. 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAn important and accessible tool to assess physiological and health status is the hematological evaluation (Miguel et al. 2019; Strumpf et al. 2020; Hansen et al. 2022). However, reference values for wild species, especially non-hematophagous bats, remain scarce (Kuzel et al. 2020; Teles et al. 2023). Although automated analyzers are increasingly used, interspecific variation may affect their accuracy, making microscopic evaluation essential (Hansen et al. 2022).\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;aimed to report hematological parameters of 24 individuals of \u003cem\u003eArtibeus planirostris\u003c/em\u003e captured in urban green areas of Cuiab\u0026aacute;, Brazil, and to perform morphological and quantitative analyses of blood cells through microscopy. Additionally, selected parameters obtained by automated methods, such as hemoglobin, hematocrit and platelets, were compared with manual or semi-automated techniques. These findings may contribute in future studies on health conditions and pathogen dynamics of \u003cem\u003eA. planirostris\u0026nbsp;\u003c/em\u003epopulations.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eCapture, identification and sample collection\u003c/p\u003e\n\u003cp\u003eBats were captured with mist-nets during two sampling events in January and March 2025 at two locations in Cuiab\u0026aacute;, Brazil: the Center for Medicine and Research in Wild Animals of the Federal University of Mato Grosso (UFMT) and M\u0026atilde;e Bonif\u0026aacute;cia State Park. Individuals were captured and placed individually in cloth bags, then weighed, examined for ectoparasites, sexed and assessed for reproductive status, with pregnant or lactating animals released. Bats were anesthetized by intraperitoneal injection of xylazine hydrochloride (10 mg/kg) and ketamine hydrochloride (60 mg/kg), then the blood was collected by cardiac puncture. Species identification followed established taxonomic keys (Diaz et al. 2021; Gardner 2007).\u003c/p\u003e\n\n\u003cp\u003eSample processing\u003c/p\u003e\n\u003cp\u003eSamples were processed at the Veterinary Clinical Pathology Laboratory of UFMT within 2-12 hours after collection and kept refrigerated until analysis. Blood smears were prepared and microhematocrit tubes were filled to determine manual hematocrit. Hemoglobin concentration was measured using the cyanmethemoglobin (CiCN) method and compared with automated results. Samples with clots or large amounts of fibrin were excluded from the analysis.\u003c/p\u003e\n\u003cp\u003eHematological parameters, including total erythrocytes, leukocytes and platelets, hematocrit and hemoglobin concentration, Mean Corpuscular Volume (MCV) and Mean Corpuscular Hemoglobin Concentration (MCHC) were obtained using an automated analyzer pocH-100iV Diff (Sysmex\u0026reg;), adapted with hematological values of \u003cem\u003eA. lituratus\u003c/em\u003e from the study by Kuzel et al. (2020).\u003c/p\u003e\n\u003cp\u003eHematology analysis\u003c/p\u003e\n\u003cp\u003eBlood smears were analysed under light microscopy for cell morphology and differential leukocyte counts at 100 cells per slide at magnifications of 400\u0026times; and 1000\u0026times;. Platelets were estimated in ten random fields and the mean value was multiplied by a factor of 15,000 (Stockham and Scott 2025).\u003c/p\u003e\n\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eData were analyzed using descriptive statistics in Microsoft Excel\u0026reg;, including mean, standard deviation and 90% confidence interval, following ASVCP guidelines (Friedrichs et al 2012). Paired comparisons of hemoglobin, hematocrit and platelet measurements were performed using Jamovi\u0026reg; software. The Shapiro\u0026ndash;Wilk test was used to assess normality, followed by either the paired T-test or Wilcoxon test as appropriate. Statistical significance was set at p \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eHematological parameters of 24 specimens of \u003cem\u003eArtibeus planirostris\u0026nbsp;\u003c/em\u003ewere described in Table 1. Total manual erythrocyte and leukocyte counts were not performed, but blood smears were used for differential leukocyte counts, platelet estimation and morphological evaluation. Sex-based analysis was not conducted due to the small sample size, but 16.7% (4/24) were females and 83.3% (20/24) were males.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eHematological parameters of Artibeus planirostris obtained by automated, semi-automated and manual methods in urban areas of Cuiab\u0026aacute;, Brazil\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters (Unit of measurement)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIC (90%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eErythrocytes (10\u003csup\u003e6\u0026nbsp;\u003c/sup\u003e/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e11.98 (1.47)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e8.28-14.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e11.49-12.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e17.63 (1.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e14.20-20.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e17.09-18.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e*Hemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e21.38 (2.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e15.13-25.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e20.46-22.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eCiCN\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eHematocrit (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e59.40 (6.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e45.90-70.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e57.30-61.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e*Hematocrit (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e52.50 (4.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e44.00-60.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e51.00-54.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicrohematocrit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMCV\u0026nbsp;(fL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e49.70 (2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e45.70-56.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e48.80-50.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMCHC (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e29.70 (0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e28.30-30.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e29.50-30.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eLeukocytes (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.50 (3.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e1.30-13.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.20-7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eBand neutrophils (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.00 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eSegmented neutrophils (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e3.00 (1.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.62-6.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.40-3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eEosinophils (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.10 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.00-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.10-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eBasophils (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.00 (0.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.00-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.00-0.00\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eLymphocytes (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e3.10 (2.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.48-10.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.10-4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMonocytes (10\u0026sup3;/\u0026mu;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.20 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.00-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.10-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePlatelets (10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e864.30 (231.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e435.00-1326.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e779.00-949.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eAutomated\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e*Platelets (10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e500.30 (119.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e232.00-725.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e456.20-544.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eMicroscopic evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eTotal plasma protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.90 (0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e5.00-7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.70-6.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eRefractometer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Hemoglobin: CiCN method. Hematocrit: microhematocrit. Platelets: estimated in blood smears.\u003c/p\u003e\n\u003cp\u003e(SD: Standard Deviation)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEchinocytes (Figure 1a) were observed in 41.6% (10/24) of individuals. One bat presented markedly lower erythrocytes, hemoglobin and hematocrit values, respectively 8.28\u0026nbsp;x 10\u003csup\u003e6\u003c/sup\u003e/\u0026mu;L, 14.20 g/dL and 45.90% (measurement in pocH-100iV Diff); 18.36 g/dL (hemoglobin by CiCN method) and 44.00% (hematocrit by microhematocrit technique) and this one had anisocytosis (Figure 1b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNeutrophils (Figure 1c) were the predominant leukocyte in 58.3% (14/24) of the individuals, while lymphocyte (Figure 1d) predominance was observed in 41.7% (10/24). The mean neutrophil:lymphocyte ratio was 1.68. Other leukocytes, including eosinophils (Figure 1e), basophils (Figure 1f) and monocytes (Figure 1g) were presented in lower numbers. Activated monocytes (Figure 1h) were observed in 25% (6/24) of the individuals, with variable intensity and size of vacuoles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePlatelets counts were excluded in six individuals due to moderate to intense platelet aggregation (Figure 1i-j). Additionally, platelet inclusions (Figure 1k) and macroplatelets (Figure 1l) were observed in one individual. Total plasma protein could not be measured due to hemolysis in one sample.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eComparisons between automated and manual or semi-automated methods (Table 2) showed significant differences for hemoglobin, hematocrit and platelet counts (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Comparison between different methods for three hematological parameters of \u003cem\u003eArtibeus planirostris\u0026nbsp;\u003c/em\u003ecaptured in urban areas of Cuiab\u0026aacute;, Brazil\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter (Unit of measurement)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*Other methods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epocH-100iV Diff\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormality test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e**Statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e21.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e17.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep = 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003eHematocrit (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e52.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e59.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e6.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep = 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003ePlatelets (10\u0026sup3;/\u0026micro;L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e603.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e148.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e976.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e362.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep = 0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Hemoglobin: CiCN method.\u0026nbsp;Hematocrit: microhematocrit. Platelets: estimated in blood smears.\u003c/p\u003e\n\u003cp\u003e** Hemoglobin and Hematocrit: Wilcoxon test. Platelets: T-test.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eElevated hematocrit, hemoglobin and erythrocyte values observed in bats, including \u003cem\u003eA. planirostris,\u003c/em\u003e may indicate physiological adaptations to heightened metabolic demands and oxygen needs inherent in sustained flight (Schinnerl et al. 2011; Miguel et al. 2019; Villalba-Alem\u0026aacute;n et al. 2020; Kuzel et al. 2020). Similarly, low MCV reflects reduced erythrocyte size, which\u0026nbsp;improves oxygen binding and increases their oxygen-carrying (Almeida et al. 2014).\u003c/p\u003e\n\u003cp\u003eEchinocytes were observed in 41.6% of individuals, a finding also reported in the pteropodid fruit bat \u003cem\u003ePteropus alecto\u003c/em\u003e in Australia (Hansen et al. 2022), and might be associated with preparation artifacts, EDTA excess, dehydration, electrolyte imbalance, intense exercise, or pathological conditions including kidney disease or snakebite poisoning (Thrall et al. 2024). One individual showed\u0026nbsp;lower erythrogram values and anisocytosis, suggesting anemia, a condition also seen in other bat species (Schinnerl et al. 2011; Hansen et al. 2022)\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLeukocyte analysis revealed an increased neutrophil:lymphocyte (N:L) ratio in more than half of the individuals, consistent with findings reported for other bat species (Almeida et al. 2014; Hansen et al. 2022; Kuzel et al. 2020; Teles et al. 2023). This pattern may be associated with physiological response to stress mediated by corticosteroids, resulting in lymphopenia and neutrophilia (Stockham and Scott, 2025; Viola et al. 2022). Anesthetic protocols may also influence leukocyte profiles, as xylazine and ketamine can increase total leukocyte count during anesthesia, simulating a stress leukogram (Hanif et al. 2025).\u0026nbsp;In bats, however, information is scarce, and only one study reported increased lymphocyte counts following isoflurane anesthesia (Strumpf et al. 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;N:L ratio has been used as an indirect indicator of stress (Viola et al. 2022). Miguel et al. (2019), observed higher\u0026nbsp;N:L ratios in fruit bats, including \u003cem\u003eA. lituratus\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;A. planirostris,\u003c/em\u003e as habitat availability decreased, suggesting that the elevated N:L ratio observed in this study may also be related to smaller amount of habitat, since the bats were captured in urban green areas.\u003c/p\u003e\n\u003cp\u003eLymphocyte predominance is commonly reported in many species of bats (Schinnerl et al. 2011; Strumpf et al. 2020; Teles et al. 2023; Villalba-Alem\u0026aacute;n and Mu\u0026ntilde;oz-Romo 2016; Villalba-Alem\u0026aacute;n et al. 2020) and is known as inverted leukocyte formuls, a pattern also observed in some domestic mammals and possibly related to genetic factors (Villalba-Alem\u0026aacute;n and Mu\u0026ntilde;oz-Romo 2016). Monocytes showed typical morphology, with activated forms observed in some individuals, as previously reported in other bats (Hansen et al. 2022). These findings may occur in small numbers in domestic animals under normal conditions, but may also indicate inflammatory or infectious processes (Stockham and Scott 2025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBasophilic inclusions in platelets compatible with \u003cem\u003eAnaplasma\u003c/em\u003e sp. were observed in one individual, similar to findings in urban bats in Colombia (Villalba-Alem\u0026aacute;n et al. 2020). However, due to their similarity to dye precipitates or nuclear fragments, diagnostic confirmation must be performed by PCR (Stockham and Scott 2025). Macroplatelets were also identified in the same animal. Although their clinical significance in bats is unknown, in dogs they are associated with increased platelet regeneration, whereas in cats they may occur as a physiological finding (Thrall et al. 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSignificant differences between automated and manual methods for hematocrit, hemoglobin and platelet counts highlight limitations of automated analyzers not validated for bats, since the device used in this study is standardized for domestic mammals (Riond et al. 2011). These differences likely reflect species-specific blood characteristics and methodological differences. The hematological values used in the analyzer were obtained from the study by Kuzel et al. (2020), which evaluated bats of the same genus, but another species, \u003cem\u003eA. lituratus\u003c/em\u003e. Considering confidence interval and standard deviation, automated hemoglobin showed lower variation, whereas manual hematocrit and platelet estimates obtained by microscopy indicated greater precision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe CiCN method is recognized as a reference method for hemoglobin concentration and is widely used for calibration of other analytical methods (Whitehead et al. 2019). However, differences observed between CiCN and automated methods may occur due to methodological principles, sample type, processing time, equipment calibration and quality control. Manual hematocrit measures packed cell volume directly, while automated hematocrit is calculated from erythrocyte count and MCV, which may lead to overestimation in samples with erythrocyte morphological alterations or EDTA storage effects (Thrall et al. 2024; Stockham and Scott 2025).\u0026nbsp;Although samples with fibrin or clots were excluded, differences between automated platelet counts and microscopy estimates may still be associated with platelet aggregates, which can interfere with automated measurements, especially in stressful situations (Stockham and Scott 2025).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe characterization of hematological parameters in bats, particularly species inhabiting urban areas such as \u003cem\u003eA. planirostris\u003c/em\u003e, is important for monitoring population health, identifying stress through N:L ratio and supporting studies on physiology, immunity and conservation. The comparison of methods indicates that automated analysis may provide more stable hemoglobin measurements, while manual methods reduce interference in hematocrit calculation and platelet counts. As automated hematology is not yet standardized for non-hematophagous bats, integrated interpretation using automated, semi-automated and manual methods, especially microscopic evaluation, is recommended. Further studies with larger sample sizes are needed to standardize automated techniques and establish more consistent and representative hematological parameters for these animals in anthropized environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMelissa Harumi Sumiyoshi:\u0026nbsp;Investigation, data curation, writing-original draft, sample processing, hematology analysis and statistical analysis. Eva Munyque da Cruz, Kayana Mota Carib\u0026eacute; de Figueiredo\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand Nath\u0026aacute;lia Soares Lima Rabelo: Sample processing and hematology analysis. Morgana Maira Hennig: Capture, sample collection, investigation and writing-review. Marcela Natacha Aparecida Rocha:\u003csup\u003e\u0026nbsp;\u003c/sup\u003eMethodology, sample processing, statistical analysis and writing-review. Gabriel de Mello, Glenda Akimi Ota, Guilherme Ratts de Almeida, J\u0026eacute;ssica In\u0026aacute;cio Gomes, Jhonathan Fran\u0026ccedil;a Bello and Mylene Karolina da Silva de Jesus: Capture, identification and sample collection. Alan Eriksson: Capture, identification, writing-review and funding acquisition. Richard de Campos Pacheco:\u003csup\u003e\u0026nbsp;\u003c/sup\u003eSupervision, writing-review and funding acquisition. Rosa Helena dos Santos Ferraz: Sample processing, supervision, methodology, writing-review and editing. Adriane Jorge Mendon\u0026ccedil;a: Supervision, methodology, formal analysis, writing-review and editing. All authors have read and agreed to the final version of the submitted manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by CNPq (Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico) and MEC (Minist\u0026eacute;rio da Educa\u0026ccedil;\u0026atilde;o).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee on the Use of Animals (CEUA/UFMT) and registered under protocol number 23108.022778/2024-52.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlmeida MF, Trezza-Netto J, Aires CC, Barros RF, Rosa AR, Massad E (2014) Hematologic profile of hematophagous \u003cem\u003eDesmodus rotundus\u003c/em\u003e bats before and after experimental infection with rabies virus. Rev Soc Bras Med Trop 47:371\u0026ndash;373. https://doi.org/10.1590/0037-8682-0169-2013\u003c/li\u003e\n \u003cli\u003eDiaz M, Solari S, Gregorin R, Aguirre LF, Barquez RM (2021) Clave de identificaci\u0026oacute;n de los murci\u0026eacute;lagos neotropicales. Publicaci\u0026oacute;n Especial 4, Programa de Conservaci\u0026oacute;n de los Murci\u0026eacute;lagos de Argentina, Tucum\u0026aacute;n\u003c/li\u003e\n \u003cli\u003eFriedrichs KR, Harr KE, Freeman KP, Szladovits B, Walton RM, Barnhart KF, Blanco-Chavez J (2012) ASVCP reference interval guidelines: determination of de novo reference intervals in veterinary species and other related topics. Vet Clin Pathol 41:441\u0026ndash;453. https://doi.org/10.1111/vcp.12006\u003c/li\u003e\n \u003cli\u003eGardner AL (2007) Mammals of South America, vol 1: Marsupials, xenarthrans, shrews, and bats. University of Chicago Press, Chicago\u003c/li\u003e\n \u003cli\u003eHanif SM, Hossain MF, Arafat Y, Simu NS, Sarkar N, Bala A, Ahmed MS (2025) Effects of xylazine-ketamine anesthesia with atropine premedication on hematological parameters in puppies. Bangladesh J Vet Med 23:21\u0026ndash;27. https://doi.org/10.33109/bjvmjj2025sam2\u003c/li\u003e\n \u003cli\u003eHansen D, Hunt BE, Falvo CA, Ruiz-Aravena M, Kessler MK, Hall J, Thompson P, Rose K, Jones DN, Lunn TJ (2022) Morphological and quantitative analysis of leukocytes in free-living Australian black flying foxes (\u003cem\u003ePteropus alecto\u003c/em\u003e). PLoS One 17:e0268549. https://doi.org/10.1371/journal.pone.0268549\u003c/li\u003e\n \u003cli\u003eKuzel MAA, Tavares JA, Fernandes PA, Alves B, Costa Neto SF, Lacorte C, Borges MS, Bonna ICF, Andreazzi CS, Moratelli R (2020) Hematological values for free-living great fruit-eating bats, \u003cem\u003eArtibeus lituratus\u003c/em\u003e (Chiroptera: Phyllostomidae). Braz J Vet Res Anim Sci 57:1\u0026ndash;9. https://doi.org/10.11606/issn.1678-4456.bjvras.2020.168582\u003c/li\u003e\n \u003cli\u003eMiguel PH, Kerches-Rogeri P, Niebuhr BB, Cruz RAS, Ribeiro MC, Cruz Neto AP (2019) Habitat amount partially affects physiological condition and stress level in Neotropical fruit-eating bats. Comp Biochem Physiol A Mol Integr Physiol 237:110537. https://doi.org/10.1016/j.cbpa.2019.110537\u003c/li\u003e\n \u003cli\u003eRiond B, Weissenbacher S, Hofmann-Lehmann R, Lutz H (2011) Performance evaluation of the Sysmex pocH-100iV Diff hematology analyzer for analysis of canine, feline, equine, and bovine blood. Vet Clin Pathol 40:484\u0026ndash;495. https://doi.org/10.1111/j.1939-165X.2011.00372.x\u003c/li\u003e\n \u003cli\u003eSchinnerl M, Aydinonat D, Schwarzenberger F, Voigt CC (2011) Hematological survey of common Neotropical bat species from Costa Rica. J Zoo Wildl Med 42:382\u0026ndash;391. https://doi.org/10.1638/2010-0060.1\u003c/li\u003e\n \u003cli\u003eStockham SL, Scott MA (2025) Fundamentals of veterinary clinical pathology, 3rd ed. John Wiley \u0026amp; Sons, Hoboken\u003c/li\u003e\n \u003cli\u003eStrumpf AA, Malmlov A, Ayers JD, Schountz T, Kendall LV (2020) Hematologic values of Jamaican fruit bats (\u003cem\u003eArtibeus jamaicensis\u003c/em\u003e) and the effects of isoflurane anesthesia. J Am Assoc Lab Anim Sci 59:275\u0026ndash;281. https://doi.org/10.30802/aalas-jaalas-19-000056\u003c/li\u003e\n \u003cli\u003eTazerji SS, Nardini R, Safdar M, Shehata AA, Duarte PM (2022) An overview of anthropogenic actions as drivers for emerging and re-emerging zoonotic diseases. Pathogens 11:1376. https://doi.org/10.3390/pathogens11111376\u003c/li\u003e\n \u003cli\u003eTeles LP, Silva JVR, Lima FJO, Subrinho SRF, Aguiar JS, Pedersoli MA, Messias MR, Mesquita EA (2023) Resposta imune inata de quir\u0026oacute;pteros em ambientes antropizados: infec\u0026ccedil;\u0026atilde;o por Haemosporida na Amaz\u0026ocirc;nia Brasileira. Rev Foco 16:3208\u0026ndash;3226. https://doi.org/10.54751/revistafoco.v16n9-194\u003c/li\u003e\n \u003cli\u003eThrall MA, Weiser G, Allison RW, Campbell TW (2024) Hematologia, citologia e bioqu\u0026iacute;mica cl\u0026iacute;nica veterin\u0026aacute;ria, 3rd ed. Roca, S\u0026atilde;o Paulo\u003c/li\u003e\n \u003cli\u003eVillalba-Alem\u0026aacute;n E, Mu\u0026ntilde;oz-Romo M (2016) Estudio de la variaci\u0026oacute;n de perfiles hematol\u0026oacute;gicos de murci\u0026eacute;lagos. Rev Mex Mastozool (Nueva \u0026Eacute;poca) 6:8. https://doi.org/10.22201/ie.20074484e.2016.6.1.216\u003c/li\u003e\n \u003cli\u003eVillalba-Alem\u0026aacute;n E, Bustos X, Crisante G, Jes\u0026uacute;s R, Mata J, Pereira F, Mu\u0026ntilde;oz-Romo M (2020) Hematological characterization of common bats in urban areas from M\u0026eacute;rida (Venezuela), and observations on possible hemopathogens. Acta Chiropterol 22:449\u0026ndash;459. https://doi.org/10.3161/15081109ACC2020.22.2.017\u003c/li\u003e\n \u003cli\u003eViola MF, Herrera LGM, Cruz-Neto AP (2022) The acute phase response in bats (\u003cem\u003eCarollia perspicillata\u003c/em\u003e) varies with time and dose of the immune challenge. J Exp Biol 225:jeb244583. https://doi.org/10.1242/jeb.244583\u003c/li\u003e\n \u003cli\u003eWhitehead RD, Mei Z, Mapango C, Jefferds MED (2019) Methods and analyzers for hemoglobin measurement in clinical laboratories and field settings. Ann N Y Acad Sci 1450:147\u0026ndash;171. https://doi.org/10.1111/nyas.14124\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Artibeus planirostirs, Erythrogram, Leukogram, Neutrophil:lymphocyte ratio, Phyllostomidae","lastPublishedDoi":"10.21203/rs.3.rs-9237637/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9237637/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Increasing and unplanned urbanization can intensify wildlife contact with humans and domestic animals, raising concerns about the spillover of zoonotic diseases. Bats play an important ecological role due to their great niche diversity and wide distribution, but they are reservoirs for various pathogens. Despite their importance, hematological values for non-hematophagous bats remain scarce, which makes it difficult to assess their health and physiological responses. Here, we describe hematological values ​​and blood cell morphology of 24 individuals of Artibeus planirostris captured in urban green areas of Cuiabá, Brazil, and compare automated and manual hematological methods. Blood samples were analyzed using an automated hematology analyzer, microhematocrit, cyanmethemoglobin method and blood smear microscopy for differential leukocyte count, platelet estimation and morphological evaluation. The erythrogram showed high hematocrit, hemoglobin, and erythrocyte values and low Mean Corpuscular Volume, which may indicate adaptations to intensified energy metabolism and high oxygen demand to flight. Leukocyte analysis showed an increased neutrophil:lymphocyte ratio in more than half of the individuals, indicating a possible stress response. Significant differences were found between automated and manual methods for hemoglobin, hematocrit, and platelet measurements. Automated hemoglobin values showed lower variability, while manual hematocrit and platelet estimates demonstrated greater precision. These results emphasize the importance of combining automated and microscopic techniques in bat hematology and contribute to the establishment of hematological parameters for A. planirostris in urban environments.","manuscriptTitle":"Comparison of manual and automated methods in the hematological evaluation of a frugivorous bat captured in urban green areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 16:16:59","doi":"10.21203/rs.3.rs-9237637/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-14T20:18:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T11:45:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T10:20:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T16:19:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-07T12:03:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-05T07:50:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259209886733984515098273782942617929936","date":"2026-04-04T13:22:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T17:28:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331147518375556180436503687998383916831","date":"2026-04-03T11:43:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258089249719325183300556944408757357260","date":"2026-04-02T04:41:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260416640808109329837587742041736238061","date":"2026-04-02T02:20:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128881206752205049795913280763855378503","date":"2026-04-01T22:24:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120792590199441539719961578433654153746","date":"2026-04-01T17:44:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T17:31:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-01T08:00:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T08:00:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Veterinary Research Communications","date":"2026-03-26T19:26:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"veterinary-research-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"verc","sideBox":"Learn more about [Veterinary Research Communications](https://www.springer.com/journal/11259)","snPcode":"11259","submissionUrl":"https://submission.nature.com/new-submission/11259/3","title":"Veterinary Research Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7fe1f2b8-3b53-4863-9102-f4dee55f3906","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T20:24:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 16:16:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9237637","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9237637","identity":"rs-9237637","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}