Eimeria species and causes enormous economic losses to the rabbit industry. Coccidia infection has a wide impact on the gut microbiota and intestinal biochemical equilibrium. In the present study, we established a model of Eimeria intestinalis infection in rabbits to evaluate the jejunal microbiota and fecal metabolite profiles.Rabbit coccidiosis is a major disease caused by various 3E. intestinalis oocysts. On the eighth day of infection, jejunal contents and feces were collected for 16S rRNA gene sequencing and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis, respectively. Jejunum tissues were harvested for hematoxylin and eosin (H&E), periodic acid-Schiff (PAS), and immunohistochemistry (IHC) staining.Rabbits in the infected group were orally inoculated with 3 × 10E. intestinalis in a range of life cycle stages, and PAS staining showed that E. intestinalis infection caused extensive loss of goblet cells. IHC staining revealed that TNF-α expression was higher in the E. intestinalis infection group. Moreover, both the jejunal microbiota and metabolites significantly altered after E. intestinalis infection. At the genus level, the abundances of Escherichia and Enterococcus significantly increased in the infected group compared with the control group, while those of Oscillospira, Ruminococcus, Bacteroides, Akkermansia, Coprococcus, and Sarcina significantly decreased. In addition, 20 metabolites and two metabolic pathways were altered after E. intestinalis infection, and the major disrupted metabolic pathway was lipid metabolism.Histopathological analysis showed that the whole jejunum was parasitized by Eimeria intestinalis infection induced intestinal inflammation and destroyed the intestinal homeostasis at the parasitized sites, leading to significant changes in the gut microbiota and subsequent corresponding changes in metabolites. Eimeria species parasitizing the liver and intestinal epithelial cells. It is harmful to rabbits at different ages and seriously affects the development of the rabbit industry  polymer) for 30 min prior to DAB staining and hematoxylin counterstaining. Phosphate-buffered saline (PBS) solution (0.01 mol/l) was used instead of the primary antibody as a control group, and the other steps were the same as described above. The DAB staining intensity was analyzed using Image-Pro Plus (version 6.0) and represented by the mean optical density (MOD) value .The steps for IHC staining were previously described  and are ® High-Fidelity PCR Master Mix (New England Biolabs). The thermal cycling parameters for PCR amplification were set as follows: initial denaturation at 98 °C for 1 min; 30 cycles of denaturation at 98 °C for 10 s, annealing at 50 °C for 30 s, and extension at 72 °C for 60 s; and a final extension step at 72 °C for 5 min. After detection by 2% gel electrophoresis, PCR products were mixed at an equal density ratio, and the mixture was then purified with an AxyPrep DNA Gel Extraction Kit. Sequencing libraries were generated using an NEBNext® Ultra™ DNA Library Prep Kit for Illumina  according to the manufacturer’s recommendations, and index codes were added. Finally, the libraries were sequenced on the Illumina Miseq and HiSeq 2500 platforms.Total genomic DNA from the samples was extracted using the cetrimonium bromide (CTAB) method. The DNA concentration and purity were evaluated on 1% agarose gels. Specific barcoded primers and high-fidelity DNA polymerase were used for polymerase chain reaction (PCR) amplification. The V3-V4 region of the bacterial 16S rRNA gene was amplified using the primers 341F (5′-ACGACGGAGGGCATCCTCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). All PCRs were carried out in a 30 µl reaction volume containing 15 µl of PhusionP < 0.05 were considered to indicate statistical significance.Paired-end reads generated from the original DNA fragments were merged using FLASH. QIIME (V1.7.0) software was used to analyze the sequences and filter the raw data. Chimeric sequences were removed using the UPARSE-OTU and UPARSE-OTUref algorithms, and sequences with ≥ 97% similarity were assigned to the same operational taxonomic units (OTUs). In-house Perl scripts were used to analyze alpha and beta diversity. Unweighted UniFrac distance for principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS) were calculated by QIIME to visually evaluate the overall difference and similarity of bacterial communities. To confirm the differences in the abundances of individual taxonomic units between the infected group and control group, linear discriminant analysis effect size (LEfSe) analysis was used to measure biomarkers within different groups, and LEfSe [linear discriminant analysis effect size] LDA > 2 and g, 4 °C), and the supernatant was dried in a vacuum centrifuge. For LC–MS analysis, samples were redissolved in 100 μl of solvent , vortexed, and centrifuged for 15 min . Quality control samples were prepared by pooling 10 µl of each sample and analyzed together with the other samples. For hydrophilic interaction liquid chromatography (HILIC) separation, samples were analyzed using a 2.1 mm × 100 mm ACQUITY UPLC BEH 1.7 µm column . For both electrospray ionization (ESI)-positive and ESI-negative modes, the mobile phase contained solvent A (25 mM ammonium acetate and 25 mM ammonium hydroxide in water) and solvent B (acetonitrile). The flow rate was 0.5 ml/min, and the elution gradient was as follows: 1 min, 85% B; 11 min, 65% B; 4 min, 40% B; 5 min, 85% B.After the samples were thawed slowly at 4 °C, an appropriate amount of each sample was added to a precooled methanol/acetonitrile/water  solution. The mixture was centrifuged for 15 min  Pathway Database.The raw MS data (wiff.scan files) were converted to mzXML format using ProteoWizard MSConvert and were then imported into publicly available XCMS software. After normalization to the total peak intensity, the processed data were analyzed with an R package (ropls) by orthogonal partial least-squares discriminant analysis (OPLS-DA) and partial least-squares discriminant analysis (PLS-DA). The robustness of the model was evaluated by permutation test. The variable importance in the projection (VIP) value of each variable in the OPLS-DA model was calculated to indicate its contribution to the classification. Student’s Spearman correlation analysis was used to calculate the correlation coefficients between significantly different microbes and metabolites selected from experimental samples. Matrix heatmap, hierarchical clustering, correlation network, and other analyses were performed with the Pearson algorithm in R (version 3.5.1) and with Cytoscape (version 3.5.1) to explore the interactions between the microbiota and the metabolites from multiple perspectives.t-test in SPSS software (version 25) was used for statistical analysis. The values are expressed as the means ± standard errors (SEs), and P < 0.05 was considered significant.Student’s E. intestinalis infection group. The jejunum tissues, from the intestinal villi to the glands, were occupied by a large number of oocysts and other life cycle stages of E. intestinalis, among which schizonts were the most abundant and could be easily seen at 400 × magnification. The villi were completely destroyed, and many discrete hemorrhagic lesions were visible in the lamina propria. The submucosal blood vessels showed severe congestion   Fig. c.Fig. 2TE. intestinalis infection group compared with the control group   based on the weighted UniFrac distance and non-metric multidimensional scaling (NMDS)  Fig. f. TogethDS) Fig. g, h.Fig.E. intestinalis infection group. In contrast, the relative abundance of Firmicutes decreased from 25.3% in the control group to 19.1% in the E. intestinalis infection group , Enterococcus (0.1% vs 4.7%), and SMB53 (9.3%) were significantly more abundant in the infected group than in the control group (P < 0.05), while Oscillospira, Ruminococcus, Bacteroides, Akkermansia, Coprococcus, and Sarcina were significantly less abundant  was the most predominant phylum in the control group, followed by Actinobacteria (10.2%) and TM7 (9.0%). A clear increase in the Proteobacteria (78.8%) abundance was found in the .3% was tE. intestinalis infection group and control group could be clearly separated into distinct clusters . According to the permutation test results, the PLS-DA model was proved to have excellent stability, and there was no over-fitting phenomenon  were successfully identified , while the other 18 metabolites increased (FC > 1.5)   and organic acids and derivatives (13.755%) were the most abundant metabolites. The ers Fig. a, as shonon Fig. b. Twenty3.755% aned Table c, d, as P < 0.05) and the 20 metabolites . A total of 34 genus–metabolite pairs showed a significantly positive correlation, but 58 pairs had a significantly negative correlation. The correlation for 34 of these pairs was extremely significant (P < 0.01). The heatmap showed that Candidatus Koribacter, Lysobacter, Escherichia, Myroides, Jiangella, and Leptolyngbya were negatively correlated with diethanolamine and D-proline, and positively correlated with the other 18 metabolites. The other 8 genera had the opposite correlations with the metabolites. Therefore, the correlations of diethanolamine and D-proline with the gut microbiota were opposite those of the other 18 metabolites . The network diagram showed that Adlercreutzia, Desulfovibrio, Escherichia, and Akkermansia were comparatively important genera. Compared with other metabolites, 11(Z), 14(Z)-eicosadienoic acid, 2-methylbenzoic acid, diethanolamine, and palmitoylethanolamide were more strongly correlated with 14 genera , and the structure of the jejunum was completely destroyed, with many sites of bleeding. Goblet cells are abundant constituents of the epithelium in the intestines and play an important role in mucosal protection [E. intestinalis infection caused extensive loss of goblet cells and reduced glycoprotein secretion. Dkhil [E. papillata infection in the jejunum. TNF-α is the main mediator of the inflammatory response and can regulate both immune and inflammatory responses [E. intestinalis. This indicates that the immune cells and epithelial cells in the intestine produce copious amounts of cytokines  to trigger inflammatory responses after E. intestinalis infection.nd ileum . It was nd ileum . In thisotection . In our n. Dkhil  also fouesponses . The preesponses , which sE. intestinalis infection. Firmicutes and Actinobacteria were the dominant phyla in the jejunum of healthy rabbits, consistent with previous reports [E. intestinalis-infected rabbits, the abundance of Proteobacteria significantly increased compared with that in the control group (from 4.7% to 78.7%), while the abundance of Firmicutes and Actinobacteria decreased. The abundance of Proteobacteria is often found to increase in several intestinal and extraintestinal diseases, most of which exhibit an inflammatory phenotype, and this increase is regarded as a possible microbial signature of disease [Escherichia, belonging to the Proteobacteria, significantly increased. Previous studies have shown that the abundances of opportunistic pathogenic bacteria, such as Escherichia, increased significantly post-Eimeria infection [E. intestinalis might increase the possibility of subsequent infection by other pathogens and exacerbate jejunal injury, resulting in changes in the diversity of the jejunal microbiota.The jejunum is the longest part of the small intestine and has the largest surface area. As the main site for the digestion and absorption of nutrients, the jejunum is of great importance for maintaining normal physiological functions . In this reports . In the  disease . The abunfection , 26, 27.Ruminococcus and Eisenbergiella decreased but that of Intestinimonas increased in rabbits infected with a precocious line of E. intestinalis (EIP8). In the present study, the abundances of Oscillospira, Ruminococcus, Bacteroides, Akkermansia, Coprococcus, and Sarcina significantly decreased in rabbits infected with E. intestinalis. In inflammatory diseases, the abundance of Oscillospira is reduced [Oscillospira may be able to secrete the important short-chain fatty acid butyrate using host glycans [n-butyrate can reduce the production of pro-inflammatory mediators such as NO, IL-6, and IL-12 [Oscillospira and Ruminococcus species may play an important role in resistance to coccidia infection by secreting butyrate.Li  found th reduced . Oscillo glycans , and som glycans . Butyrat glycans . Butyrat glycans . Treatmend IL-12 . TherefoAkkermansia muciniphila, belonging to the phylum Verrucomicrobia [Akkermansia muciniphila or its outer membrane protein Amuc_1100 can regulate immune responses in the spleen, intestines, and mesenteric lymph nodes and reduce the level of inflammation in the intestines [A. muciniphila is probably associated with a protective or anti-inflammatory role in E. intestinalis infection. In general, E. intestinalis infection disrupts the intestinal flora in rabbits, increases the abundance of some harmful bacteria, and decreases the abundance of some beneficial bacteria. The abundance changes in the flora may weaken the intestinal barrier and increase the possibility of pathogen invasion.microbia , colonizmicrobia . It is rmicrobia . A recentestines . Thus, AE. intestinalis infection. A total of 20 significantly altered metabolites were found to contribute to the variations between infected and uninfected rabbits. The metabolites significantly altered in response to E. intestinalis infection were lipids. KEGG pathway analysis showed significant dysregulation of lipid metabolism (biosynthesis of fatty acid and unsaturated fatty acids), accompanied by increases in palmitic acid, cis-9-palmitoleic acid, and erucic acid. Lipids are essential structural components of biological membranes and play important roles in the mechanisms of apoptosis, material exchange, energy transfer, and signal transduction [E. intestinalis to the rabbit intestinal tract mainly occurred during the schizogony stage [E. intestinalis infection, leading to dysfunction of absorption.Fecal metabolomics has been used to assess metabolic phenotype variations associated with gut microbiota perturbations in disease development . In thissduction , 41. Theny stage , with deE. intestinalis infection group. Proline can promote epithelial cell proliferation, maintain intestinal integrity and improve barrier function after stress injury [Eimeria falciformis. The majority of glycerophospholipids were significantly reduced in response to Schistosoma japonicum infection [All 20 significantly altered metabolites except for diethanolamine and D-proline, the other metabolites increased in the s injury . Huang [s injury  also repnfection . Here, nE. intestinalis infection. Moreover, pathogenic bacteria in the gut can produce uracil, which activates host dual oxidase to produce antimicrobial reactive oxygen species [Cryptosporidium parvum.Palmitoylethanolamide can inhibit mitochondrial dysfunction, reduce cytokine production, ameliorate the inflammatory state, and limit oxidative stress . Vincami species . However species  reportedE. intestinalis-infected rabbits occurred in the positive direction. Adlercreutzia, Akkermansia, Desulfovibrio, Escherichia, Oscillospira, and Lysobacter were the important genera located at key nodes in the network. For example, vitamin E (a-tocopherol) consumption affects the Proteobacteria and Verrucomicrobia composition, corresponding to that of Escherichia coli and Akkermansia muciniphila at the species level [E. intestinalis infection increased intestinal inflammation and destroyed intestinal homeostasis at the parasitized sites, causing significant changes in the gut microbiota, which in turn led to corresponding changes in metabolites.The above analysis indicates that the alterations in the gut microbiota and metabolites in es level . In concE. intestinalis oocysts and other life cycle stages. E. intestinalis infection destroyed the jejunal structure, caused extensive loss of goblet cells, reduced glycoprotein secretion, and increased the expression of TNF-α. It was demonstrated that both the gut microbiota and metabolites were significantly altered in rabbits infected with E. intestinalis. Eimeria intestinalis infection reduced the diversity of the jejunal microbiota and was related to 14 different jejunal microbiota at the genus level. Metabolomics analysis showed that E. intestinalis infection altered 20 metabolites and two metabolic pathways, with lipid metabolism as the major disrupted metabolic pathway. In addition, Spearman correlation analysis revealed that 92 genus–metabolites pairs had a significant correlation. In conclusion, E. intestinalis infection damaged the jejunal structure, increased intestinal inflammation, and perturbed the gut microbiota and metabolic homeostasis. The altered microbiota and fecal metabolites may become potential biomarkers and provide a reference for the diagnosis of coccidiosis infection.In the present study, jejunal epithelial cells were parasitized by a large number of


Huntington’s disease (HD) is a progressive genetic neurodegenerative disease accompanied by mental and neurocognitive disabilities, which requires long-term and comprehensive treatment and care. Information on the health and economic burden of HD is scarce, but essential for conducting health economic analyses, in light of the prospect of new therapies for HD. In this study, we aim to identify values for Health-Related Quality of Life (HRQoL), describe service utilization and costs, and their associations with clinical and socio-demographic variables across all phases of HD.A cross-sectional study including 86 patients across all phases of HD. Values of HRQoL were calculated based on EQ-5D-3L index scores. Additionally, health care and societal costs were estimated based on service utilization collected using the Client Service Receipt Inventory (CSRI) and data from the patients’ interviews. Total societal costs included costs of primary and secondary health care services, informal care and productivity loss of the patients. Multiple regression analyses were used to investigate associations between socio-demographic and clinical variables on HRQoL and costs.HRQoL values declined, while total costs increased across disease severity. Total six-month healthcare costs and total societal costs were € 18,538 and € 66,789 respectively. Healthcare and societal costs doubled from early to middle phase, and tripled from middle to advanced disease phase. Main six-month cost components for the three disease phases were informal care costs  accounting for approximately half the total societal costs, and costs due to production loss  being slightly higher than the total healthcare costs. Disease severity and gender were found to have the strongest effect on both values of HRQoL and costs.Reported values of HRQoL and costs including costs for production loss may be used in modelling the cost-effectiveness of treatment for HD. Our results highlight the crucial role the informal caregivers play in the care provided to HD patients in all disease phases. Future research should focus on the estimation of productivity loss among informal caregivers.The online version contains supplementary material available at 10.1186/s12913-022-08881-8. HTT gene located on chromosome 4, affecting people in the middle of adult life usually between 30 and 50 years of age [Huntington’s disease (HD) is a genetic neurodegenerative disorder, caused by an expanded CAG repeat in the s of age , 2. HD iThe course of HD requires complex long term multidisciplinary treatment and care in the absence of disease modifying treatments , 6–8. HDStudies on health related quality of life (HRQoL) in patients with HD based on generic measurements  andIn the present paper we aim to a) describe HRQoL values using EQ-5D-3L across all phases of HD measured by Unified Huntington’s Disease Rating Scale – total functional capacity scale, b) describe service utilization, c) to assess the costs and cost composition for HD, based on information of service utilization, and d) to explore associations between EQ-5D-3L estimates, costs, socio-demographic and clinical characteristics in a cross-sectional study of a Norwegian population of patients with HD across early to advanced HD.In the present cross-sectional study, eligible patients that a) had a clinical diagnosis of HD and b) resided in the South-Eastern region of Norway were identified and invited through Oslo University Hospital and rehabilitation centres with programs for HD patients. All eligible patients received a written invitation, containing study information and an informed consent form. After receiving the signed consent form, the patient or carer was contacted and an appointment for the study visit was scheduled. Out of 158 eligible patients, 88 patients consented to participate in a survey of healthcare service utilisation and needs for healthcare services. Two out of the 88 participants were excluded because clinical diagnostic criteria were not fully met, resulting in 86 out of 158 (54.4%) participants being included in the analyses. Two patients did not return a HRQoL questionnaire (EQ-5D-3L), resulting in 84 patients included in analyses of HRQoL data.The study was approved by the Regional Committees for Medical and Health Research Ethics South East Norway (ref. 2013/2089) and performed in accordance with the Declaration of Helsinki. For participants who were unable to provide informed consent themselves, consent was obtained from the primary caregiver or legal representative.Two clinical raters, experienced in the field of HD (MRvW and EIH), collected data from January to August 2014 through survey interviews during an outpatient study visit (38%) or at the patients’ home (62%). About one third of the visits were conducted with the patient alone (31%), while the remaining interviews were done with the patient and primary informal and/or formal carer, or with the informant only (69%). Background information including socio-demographic and clinical information and disease characteristics were recorded. We calculated disease duration in years as the date of formally obtained clinical diagnosis of HD subtracted by the date of the study visit. Moreover, a clinical functional evaluation was performed, assessment of needs was conducted, and the use of healthcare services was recorded. At the end of the study visit we requested patients to complete the EQ-5D-3L. Primary carers assisted participants who were unable to fill out the questionnaire independently and were specifically informed to assist reflecting the participants’ own rating of their health status, as this is a self-report measure.In order to assess participants’ functional status and disease phase, we used the UHDRS-Functional assessment  comprisiMobility, Self-Care, Usual Activities, Pain/Discomfort and Anxiety/Depression, and within each dimension there are three levels of severity: no problems, some problems and extreme problems, summarizing to 243 possible health states. Patients are asked to report the level for each of the 5 dimensions, which describes the patients’ current health state. Each health state is assigned a HRQoL value between 0 and 1, reflecting the severity of the health state, where 0 refers to death and 1 to perfect health. The Danish tariff was used to estimate the HRQoL values, as a Norwegian tariff is currently not available .In order to assess study participants’ HRQoL and to calculate individual HRQoL values, the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) was used . The EQ-Data on healthcare and social services utilization were recorded using the Client Services Receipt Inventory (CSRI) . The CSRPrimary care , Home care , Nursing homes, Specialists  or Secondary care . We estimated the cost of Informal care, Social worker and Out-of-pocket . Lastly, we included production loss for the patient.Service utilization costs were calculated based on the resource use estimates for a 6 month period as measured by CSRI. Costs and resource utilization related to HD were included. Health care costs were categorized as The unit costs of primary healthcare services, imaging costs and laboratory tests  were obtained from the List of reimbursement fees  for 2019. The unit costs for outpatient visits and hospital admissions were based on the diagnosis related groups (DRGs). Each visit or admission was assigned a DRG weight reflecting the resource need relative to an average hospital patient. The unit cost was derived by multiplying the DRG weight with per DRG point. Informal care categories were taken from the CSRI. These costs were calculated as the average hourly wage rate multiplied by the number of hours of care per week and scaled up to 6 months (Statistics Norway 2019). Cost of nursing homes for a six-month period were based on average costs in a Norwegian database (KOSTRA) with administrative information on municipal and county activities . To estimate the out-of-pocket costs for services, such as dental care, aromatherapy, foot zone therapy and foot care, we used prices reported online. The unit costs in Euro’s based on a conversion rate of 10.6 NOK per Euro, are reported in Table Costs related to production loss were calculated as the difference between the six-month salary of a patient with HD and that of the general population in the same age group , adjusted for the proportion in part-time positions. Production loss was not estimated for patients older than 65 years, as this is the retirement age in Norway. To estimate the monthly salary of the study population, working hours were calculated and adjusted to each patients’ percent of a full- time position . The working hours were then multiplied by the age-adjusted hourly rate to estimate the monthly earnings and scaled up to 6 months. An overview of the workforce and earnings for patients with HD and for the general population are shown in Additional file The socio-demographic and clinical disease characteristics served as independent variables. They were reported by means of descriptive statistics  across the complete sample and across the three disease phases. Marital status group “single” included participants who were single, widowed, or separated, while the married group included those who were married of partner. HRQoL values across disease stages were also described using mean values and standard deviations. Healthcare service utilization as recorded by the CSRI was presented using the proportion of participants that used the different healthcare services divided according to use due to HD and due to other conditions. Type of informal care provided to patients was reported using proportions and hours per week. All calculated costs are presented using descriptive statistics of mean values with standard deviation and range for the above described cost groups for the whole population and across the three disease phases (disease severity).Univariate and multiple regression analyses were applied to investigate associations between disease severity, represented by disease phase and disease duration and HRQoL values and costs. As costs are non-negative and typically right skewed, we applied a log-linear regression for costs. To adjust for underlying health condition and risk, patient characteristics such as age, gender, comorbidities and marital status were included. Goodness of fit statistics (adjusted R-squared) were calculated for the multiple regression models. All analyses were conducted using STATA 16.1.Patient and clinical characteristics across disease phases  are reported in Table n = 34): mean = 0.84 (SD = 0.13), middle phase (n = 19): mean = 0.74 (SD = 0.10) and advanced phase (n = 31): mean = 0.65 (SD = 0.5). Results of the univariate and multiple regressions are displayed in Table p = 0.050) and disease progression from early to middle HD (p = 0.003) and from early to advanced HD (p < 0.001), indicating that both longer duration of disease and disease progression was associated with lower HRQoL values. We found a significant association* between higher HRQoL values and male gender (p = 0.045). Univariate regression analyses further showed a significant association between HRQoL values and marital status indicating slightly higher values for married participants (p = 0.029). However, this association disappeared in the multiple regression analyses.Mean HRQoL values declined across disease phases for the 84 participants; early phase n = 4: mean =Table Further, we found that between 22 and 42% of our participants received some form of informal care in addition to formal resource utilization . The average hours per week used by informal carers to provide this care varied from 1.5 hours for help outside the home to up to the equivalent of two working days based on a 7.5 our day (15 hours per week) for personal care with great variation , Help at home: mean = 11 hours per week (SD = 62.5), Help outside the home: mean = 1.5 hours per week (SD = 3.6), Other help: mean = 2.3 hours per week (SD = 8)).Total healthcare costs, care costs and societal costs related to HD are reported according to cost category in Table Further looking at costs across the three disease phases, total healthcare costs more than doubled from early to middle phase and more than doubled again from middle to advanced disease phase. Total care costs showed a similar pattern but tripled from early to middle phase and were eight times higher in advanced phase compared to middle phase. As for total societal costs, costs doubled from early to middle phase, and more than tripled from middle to advanced phase disease  with the total societal costs being about twice as high when comparing the early € 22,005) to the middle phase , and approximately 3.5 times higher from the middle phase to the advanced phase . This increase of costs for all three cost groups  across disease phases is in line with other available studies on estimated costs and economic burden of HD and reflect increasing service utilization of HD patients across disease phases reported in other studies , 20–22. ,005 to tIn addition to informal care, production loss constituted a large proportion of costs with €18,907 on average for the complete sample, and especially high in the early and middle phases of disease. Production loss being the largest cost component, about double of the total cumulative cost types in the early phase of HD is striking. This may point to the effect of early HD symptoms on work capacity and may also indicate that health care and support needs are unmet and not provided. Overall, this confirms the severity of HD and its remarkable impact on the workforce and disability rates. To our knowledge, no previous studies have included estimations of production loss based on data regarding patients’ work-force.The present study also shows that the majority of various types of healthcare costs reported are highest in the middle phase of HD compared to both early and advanced phase HD. This may reflect a higher need for broad healthcare services reflected by the wide variety in symptom presentation and progression in this phase. These patients are likely to benefit from more medical interventions, compared to early and advanced phases . FurtherFurthermore, rehabilitation costs are found to be a substantial part of costs in early and middle HD and include specific HD rehabilitation programs offered to HD patients in these phases as part of secondary health care in Norway. Possibly they partly substitute needs for secondary care, specialists and hospital health care services.Contrary to previously published studies, we investigated potential relationships between costs and socio-demographic and clinical characteristics. Associations found confirmed the strong effect of disease severity (disease phase). Being male was associated with lower total societal costs. This gender effect may be explained by men being more and longer in the work force in our sample.To our knowledge this is the first study to include patients’ production loss complementing costs input related to informal care in order to estimate the societal costs related to HD. Including costs due to production loss in calculations of total societal costs emphasizes the importance of the economic burden for both the patient and caregiver and provide a more accurate outlook of HD for future policy decision making. In addition, the information collected in our study, could be used in an economic evaluation from a societal perspective, which would broaden the current healthcare perspective. The inclusion of productivity losses related to caregivers, as informal care is the most important cost driver in HD, could also have been an important factor to include in the estimation of social costs. Inclusion of productivity loss in future studies could provide more valid “real life” costs for HD and improve decision making. Furthermore, HRQoL values may also be reduced for caregivers, at least part of the disease trajectory, as balancing work life and providing informal care is challenging and a psychological burden. Future studies on the health and economic consequences of HD, should focus on a broader perspective on informal caregivers to account for the total HD burden.One strength of this study lies on the use of individual patient data to calculate costs and HRQoL values avoiding the bias that comes from using external sources as basis for the analysis. The study population in the present study covers the whole spectrum of HD, with a relatively large number of patients in advanced stages compared to other studies, hence providing a more realistic estimation of HD costs.Limitations of this study include the small sample size, limiting statistical power of associations between patient characteristics and costs or HRQoL. Furthermore, the cross-sectional design implies inability to make inferences of causal relationships between the investigated variables. Future studies on health economics should include larger samples and be based on longitudinal data. Moreover, information for pharmacological treatment, adaptations and aids, were not systematically recorded as part of this study contrary to other available studies on costs and economic burden –22. Due The present study reports data that may be used in modelling the cost effectiveness of new treatments for HD patients, informing stakeholders and policy makers. In line with previous studies, we found that disease severity (HD phase) is associated with decreased HRQoL and increased costs in middle and advanced phases of HD. Moreover, the present study highlights the important contribution of the informal care provided by partners, other family members or friends to the treatment of HD patients. These costs may be considered especially high considering that Norway is a welfare state. Although we included estimations of productivity loss, further efforts should be made to estimate productivity loss for informal caregivers, given the fact that they provide substantial care to their loved-ones. Given that the present study did not include estimations of costs for medication and aids, our results are likely still to be an underestimation of the total economic burden of HD in Norway. Based on general information about disease duration and care needed, it is important to consider that the health and economic burden for society as well as for the individual patient and his/her family members of HD, is likely to be present over many years.Additional file 1.Additional file 2.Additional file 3.


We identified factors associated with healthcare costs and health-related quality of life (HRQoL) of multimorbid older adults with polypharmacy.Using data from the OPERAM  trial, we described the magnitude and composition of healthcare costs, and time trends of HRQoL, during 1-year after an acute-care hospitalization. We performed a cluster analysis to identify groups with different cost and HRQoL trends. Using multilevel models, we also identified factors associated with costs and HRQoL.Two months after hospitalization monthly mean costs peaked (CHF 7′124) and HRQoL was highest (0.67). They both decreased thereafter. Age, falls, and comorbidities were associated with higher 1-year costs. Being female and housebound were negatively associated with HRQoL, while moderate alcohol consumption had a positive association. Being independent in daily activities was associated with lower costs and higher HRQoL.Although only some identified potential influences on costs and HRQoL are modifiable, our observations support the importance of prevention before health deterioration in older people with multimorbid illness and associated polypharmacy. One of the main causes of this phenomenon is the continuous rise of new and more expensive technologies and, to a less clear extent, an aging population.59 Two recent reviews demonstrated the substantial economic burden which results from multimorbidity.11High healthcare costs also reflect that more than half of older people experience several chronic conditions (multimorbidity), meaning that a large proportion of current healthcare spending is on multimorbid older adults.1217 Previous studies have examined the associations between multimorbidity and lower HRQoL in adults, highlighting how higher levels of multimorbidity result in lower HRQoL.1218 Overall, the lack of good-quality information on costs and effectiveness data in the field of multimorbidity, used to inform decision making, remains of concern.20 Despite the importance of this issue and its impact on healthcare spending, in-depth analyses of healthcare costs and health-related quality of life (HRQoL) in older patients with comorbidities are still lacking. Therefore, it is important to seek to better understand costs and HRQoL in this population.Chronic conditions  not only increase healthcare costs, but also generally result in worse health outcomes and health-related quality of life (HRQoL).assess the healthcare costs and HRQoL of multimorbid older adults with polypharmacy in the year following an acute-care hospitalization. In particular, we aimed to characterize how healthcare costs and HRQoL are distributed over time and to elucidate whether they may be associated with modifiable factors that could potentially enable saving healthcare resources or improving HRQoL over time. To explore the different trends in healthcare costs and HRQoL for different groups of patients, we also performed a cluster analysis.This study aims to OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid older people (OPERAM) clinical trial .21 OPERAM was a European cluster-randomized trial conducted between 2016 and 2019, aimed at reducing preventable drug-related hospital admissions in a population of older people with multimorbidity, through improving pharmacotherapy.23 The intervention was initiated during an acute hospitalization for any cause, with exclusion of patients who were directly admitted to palliative care (<24 hours after admission). Each cluster corresponded to a group of patients treated by the same consultant in the same ward. Clusters were randomized to usual care or to the structured pharmacotherapy optimization intervention. The post-randomization observation period of the OPERAM trial was 12 months and the trial was conducted in 4 centers, located in Belgium, Ireland, the Netherlands and Switzerland. The trial participants (N = 2008) were aged 70 years and older with both multimorbidity (experiencing 3 or more chronic conditions concurrently) and polypharmacy (taking 5 or more different regular drugs).21 At baseline, and during 3 subsequent follow-up telephone calls , all trial participants were asked to complete questionnaires to elicit a range of trial outcomes. Participants were asked about their use of healthcare services . Furthermore, patients were asked to assess their HRQoL in 5 dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression using the 5-level version of the European Quality of Life-5 Dimensions questionnaire (EQ-5D-5L), and visual analog scale (EQ-VAS).2430The analyses of this manuscript used data collected in the 32by combining the EQ-5D-5L responses with the applicable valuation algorithm for Germany.34 EQ-5D valuation algorithms are often selected on the basis of geographic proximity35 and the majority of our patients were recruited in the German-speaking city of Bern. For patients who died during the trial, we set utility to 0 from the date of death.Utility scores represent HRQoL on a linear scale from 0 (death) to 1 . Negative values can also occur for conditions that are perceived to be worse than death. Given the absence of a Swiss valuation algorithm, we calculated utility scoresFor comparison, we also analyzed quality-adjusted life years according to the EQ-VAS. Values ranged from 0 to 100, hence were divided by 100 to be comparable with the EQ-5D-5L.3639 We converted all local unit costs into one common currency , using purchasing power parities (PPP),40 as recommended in the literature.3741 The cost of index hospitalization was not included in the estimates. More detailed information on the sources and methods of unit cost data collection can be found in Salari et al.42A healthcare system perspective was adopted in the main analysis. The following cost items were included in the main analysis: costs of hospitalizations, rehabilitation facilities, medical visits , nursing visits at home, stays at a nursing home, and drugs. Furthermore, we approximated a societal perspective by additionally including the costs of informal care, defined as the opportunity cost of time provided by family caregivers under the retirement age . We applied local unit costs for the year 2018 to each country, like previous studies.We first computed basic descriptive statistics  of patient characteristics, of indicators of quality of life and for the different categories of healthcare costs (standardized to 1 month). To explore patient heterogeneity and assess whether similar cost trends and health-related quality of life results could be linked to similar patient characteristics, we performed a hierarchical cluster analysis. Finally, we performed regression-based analyses to assess associations between patient characteristics and costs, and associations between patient characteristics/healthcare use and HRQoL.44 We selected the partition with 4 clusters as optimal, based on the graphical representation of the dendrogram, and also the elbow method which is a method that helps to choose the number of clusters corresponding to an elbow of the scree plot of the within deviance versus the number of clusters.44 To detect potentially similar trends in costs and HRQoL in different groups of patients, we computed the trends of HRQoL and healthcare costs for each cluster.We grouped patients into clusters according to their baseline characteristics related to age, sex, BMI, number of falls, amount of alcohol consumption, smoking status, level of education, number of comorbidities, dementia, type of ward they were hospitalized in , whether or not they were living a nursing home, and Barthel Index score. We performed a hierarchical cluster analysis with Gower distance, a metric that measures the dissimilarity of 2 items which is appropriate for a set of variables including both categorical and continuous variables.To assess associations between patients’ baseline characteristics and 1-year healthcare costs in multimorbid adults aged 70 years or older, we applied the i in cluster j at baseline , smoker (Y/N), number of falls occurred in the previous year, alcohol consumption, dementia (Y/N), number of comorbidities, Barthel index of activities of daily living , and a dichotomous variable indicating whether at enrollment, the person was hospitalized in a medical or surgical ward. CFE is a vector of country fixed effects. The sample was cluster randomized: each cluster (cluster j in the equation) represented a group of patients treated by the same consultant in the same ward.where Secondly, we used the following i in cluster j, at baseline, as in where t) were baseline, follow-up period (FUP) 1, FUP 2 and FUP 3 . At each FUP people were asked about healthcare service use which occurred in the period starting from the previous time point (t-1) up to the time of the interview (t). Time intervals (u) represent the time between 2 consecutive time points, namely between t-1 and t.Time points  representing the main reason for hospitalization when the patient was enrolled, and one dichotomous variable indicating whether the patient died during the trial. The analyses were run on complete observations. The use of multilevel models on longitudinal data to estimate HRQoL adjusted for the potential bias resulting from missing values.Given the skewed nature of cost data and skewed distribution of HRQoL values, we also ran multilevel GLM models with a Gamma distribution and log link function as robustness checks for both equations. Additionally, as a further robustness check, we ran the model on costs excluding outliers .Stata, 15th edition.47All analyses were run using the software ⩾82 years) and women were slightly underrepresented (45%). A small percentage of the participants smoked (8%) or suffered from dementia (5%). Housebound people represented 16% of the study population and those living in a nursing home at the time of the enrollment represented 5.5%. Most patients were recruited in medical  wards (79%), and many had a number of comorbidities between 7 and 10 (34%). Patients tended to be overweight (35%) or obese (30%). Approximately 49% of the sample experienced at least 1 fall in the year before study inclusion and the majority (59%) did not drink alcohol in the year before study inclusion.The mean total costs were higher after the index hospitalization (CHF 7124 at FUP 1) and dropped to CHF 3996 and CHF 3480 at FUP 2 and 3, respectively .Costs of rehabilitation was the highest cost component in the first FUP , and it became a much smaller component in the second and third FUP . Costs for hospitalization was the second highest component in FUP 1, and remained quite stable over time in relative terms  with a smaller and decreasing monetary value . The cost of nursing homes was also important, especially in the second (23.7%) and third (27.9%) FUP. The relative weight of costs for nurses at home were also increasing over time from FUP 1 to FUP 2 to FUP 3 , as well as costs for drugs  and cost of informal care . Finally, cost for medical visits and physiotherapy remained the smallest components over time.The distinction of 4 clusters was identified as optimal. Cluster 1 could be described as “mostly female in a slightly below-average health state.” It included mainly females (90%). 13% of cluster 1 participants were nursing home residents, and 11% had a dementia diagnosis. A slightly higher mean number of comorbidities was estimated in cluster 1 relative to the other clusters, as was a slightly lower mean Barthel Index score (indicating a worse autonomy in daily activities), and the lowest alcohol consumption of all the clusters.Cluster 2 could be described as “men in relatively better health.” This cluster contained only men, no smokers and participants in this cluster showed more independence in activities of daily living as measured with the Barthel Index, than the other groups.Cluster 3 could be identified as “mainly men who smoke and drink.” It included mainly men (64%). This cluster had a slightly younger mean age and 7% of cluster 3 participants were nursing home resident and there was a higher rate of falls. All of cluster 3 participants were smokers, and a high percentage were alcohol drinkers.Finally, cluster 4 could be labeled as “surgical patients at index hospitalization” and in this cluster were generally people in relatively good health, as they reported fewer comorbidities and fewer falls than the other groups and were hospitalized in a surgical  ward.Overall, graphs show no large differences in healthcare costs or HRQoL between the clusters. However, some differences can be described. People belonging to cluster 4 had the highest cost per month at FUP1. Costs in FUP2 and FUP 3 were very similar for clusters 2 and 3, higher for cluster 1 and lower for cluster 4. Participants in cluster 4 also experienced the highest HRQoL over all the FUPs. Patients in cluster 3 had the lowest HRQoL at baseline, but a quite high HRQoL level over the 3 FUPs. Cluster 1 experienced a low HRQoL over time.supplementary material, . For technical reasons they were computed with cluster fixed (rather than random) effects. They were similar to the main findings in terms of significance; coefficients were generally slightly greater. Results obtained excluding outliers  were also consistent with the main results, with the exception of dementia, which showed a significant and positive coefficient .Results of the average marginal effects of the multilevel GLM model for healthcare costs, with a Gamma distribution and log link function are reported in the Supplemental Table S3). Results obtained with GLM model with a Gamma distribution and log link function were similar to the main results, but the coefficients for GP and specialist visits, as well as for living in a nursing home, were not significant (supplementary table S4). Observed effects on the EQ-VAS were all in the same direction as those based on the EQ-5D-5L, but with some difference in terms of statistical significance. For example, we found a gradient effect in the number of comorbidities (supplementary table S5). Furthermore, coefficients for being older than 85 years, high school education and being recruited in a medical ward became significant with the EQ-VAS. However, those for female and living in a nursing homes were no longer significant with the EQ-VAS as they were with the EQ-5D-5L.Among the variables representing the use of healthcare services, having had medical visits was negatively associated with HRQoL . Living in a nursing home was positively associated with HRQoL (0.042), while being hospitalized (−0.017), the number of informal care hours received (−0.0008 per hour), and the number of drugs taken  were all negatively associated with HRQoL. In the multilevel analysis where the set of variables representing the use of healthcare services was left out, number of comorbidities was significantly negatively associated with HRQoL, as was having being recruited from a medical  ward  were higher after the index hospitalization and lower at FUP 2 and FUP 3. These estimates show that costs increased after the index hospitalization when the acute problem may still have required medical resource consumption.Results of the descriptive analyses broken down by cost categories may be considered consistent with expectations for an elderly multimorbid population. Namely, that high rehabilitation costs followed immediately after an index hospitalization (FUP1), but subsequently rehabilitation costs decreased in FUP2 and FUP3 , although nursing home costs increased slightly in FUP2 and FUP3.Cluster analysis revealed 4 distinct groups of patients. Relative to the generally poor health of the patients in our sample, we identified patients in cluster 1 as being in “below-average health” as they showed prevalence of dementia, a slightly above-average number of comorbidities, and a worse autonomy in daily activities. Their HRQoL declined slightly over time, despite their increasing healthcare costs. We assume that even extensive use of healthcare services did not allow to counterbalance their poor health status and only delayed further deterioration. In contrast, we identified people in cluster 2 as being “in relatively better health” since this group included no smokers and more autonomous people. In both clusters 1 and 2 there was hardly any HRQoL improvement after the index hospitalization. This might indicate that the general health conditions of these people did not allow a substantial improvement of HRQoL, or alternatively that the medical problems for which they were hospitalized were less serious compared to the other people. The latter explanation may be more likely as cluster 1 and cluster 2 show the highest mean HRQoL at baseline. Cluster 3 was slightly harder to interpret, showing higher levels of smoking and alcohol together with a higher number of falls. Hypothetically, these people may be in relatively better health despite falls, as they can drink alcohol and smoke. This would also explain why their HRQoL increases substantially after the index hospitalization. However, we did not have enough information to characterize them better nor to understand why their HRQoL at baseline was quite low. Cluster 4 was clear-cut in that it only included surgical care patients. These patients tended to recover better than the other patients. Despite the highest costs at the beginning, they showed the lowest costs over time and the best HRQoL. We identified factors associated with higher healthcare costs, namely, older age (⩾85 years), having ⩾2 falls over the previous year, having a high number of comorbidities , and having greater dependence in activities of daily living as measured with the Barthel Index.4851 activity limitations,53 and comorbidities.59 Overall, it is difficult to counteract these potentially cost-driving factors through specific interventions. However, previous research has stressed the importance of preventing rapid physical deterioration and falls to prevent a general decline in a person’s health. Suggested solutions to prevent falls may address environmental factors or induce behavioral changes.5457 Furthermore, a recent network meta-analysis from the OPERAM group found that medication review in combination with medication reconciliation, patient education, professional education and transitional care, was associated with a lower risk of hospital re-admissions compared to usual care.58 Results from a societal perspective showed higher coefficients, indicating that the association with costs is even higher when informal care is considered, meaning that informal caregivers play an important role in the life of our sample patients.These results align with previous studies which found an association of high healthcare costs with number of falls,Regarding determinants of HRQoL the number of falls showed a negative association with HRQoL, as well as a housebound status. Similarly, a higher Barthel Index (which indicates a higher independence in activities of daily living) corresponded to a higher HRQoL.5963 More research would be needed to better understand the relationship of alcohol and HRQoL in a multimorbid population. Being female was negatively associated with HRQoL. This result is consistent with the literature that already looked at a potential gender role in determining HRQoL.6467 Both GP and specialist visits showed a negative correlation with HRQoL, as well as taking more drugs and receiving more informal care hours. This is not surprising as all of these variables can be interpreted as proxy measures of overall health status. The only exception was nursing home residence, which was positively correlated with HRQoL. An explanation for this could be that admission to a nursing home means receiving constant care that may help alleviate some health problems that would not be managed equally well at home. However, the coefficient for nursing home residence was not statistically significant in the robustness checks as shown in the supplementary materials.Drinking less than 1 unit of alcohol per day (but being not abstinent) was associated with a better HRQoL. Here, we cannot exclude a situation of reverse causality association: sicker people with a lower HRQoL may stop drinking alcohol. Yet, this result is consistent with other studies that found that for older people a moderate consumption of alcohol was associated with a better HRQoL.This study has some limitations. Firstly, it was not possible to identify a causal relationship between baseline characteristics, and healthcare costs or HRQoL. Secondly, the choice of explanatory variables was limited to the information collected over the course of the trial such that it was not possible to control for patients’ income, which is generally closely correlated with both HRQoL and healthcare costs. Thirdly, this study was characterized by a very diverse population in terms of comorbidities, general health conditions and types of hospitalization. The database recruited patients with at least 3 comorbidities of any kind during one hospitalization for almost any reason. Although this could be seen as a limitation since results cannot be applied to a specific category of patients , it could also be seen as an advantage as our conclusions apply to a general older post-hospitalized multimorbid population and constitute a solid basis for further and more specific research.Our sample consisted of patients aged 70 years or higher, suffering from at least 3 comorbidities and taking at least 5 daily long-term drugs, after an episode of acute hospitalization. Cluster analysis indicated that surgical patients had the highest costs at the beginning but the lowest costs and highest HRQoL at FUP 1 and subsequently. Age, falls, and comorbidities were associated with higher 1-year costs. Being female and housebound were associated with lower HRQoL. Being dependent in daily activities was associated with both. Overall, our results indirectly support the importance of prevention and action before health status deteriorates . They are relevant for policy makers who must define targeted programs for multimorbid elderly patients to prevent some of the factors responsible for higher costs and lower HRQoL. More research could help further identify the patterns of costs and HRQoL of other groups of patients, as well as other factors that might have a role in reducing healthcare costs.Click here for additional data file.Supplemental material, sj-docx-1-his-10.1177_11786329231153278 for Healthcare Costs and Health-Related Quality of Life in Older Multimorbid Patients After Hospitalization by Paola Salari, Séverine Henrard, Cian O’Mahony, Paco Welsing, Arjun Bhadhuri, Katharina Tabea Jungo, Thomas Beck, Denis O’Mahony, Stephen Byrne, Anne Spinewine, Wilma Knol, Nicolas Rodondi and Matthias Schwenkglenks in Health Services Insights


It is believed that the virions of a virus infecting a host may share the identical viral genome and characteristics. However, the role of genomic heterogeneity of the virions of a virus in virus infection has not been extensively explored. To address this issue, white spot syndrome virus (WSSV), a DNA virus infecting crustaceans, was characterized in the current study. In WSSV, differences in two nucleotides of the viral genome generated two types of WSSV, forming a virus population that consisted of Type A WSSV (encoding WSSV lncRNA-24) and Type B WSSV (encoding the wsv195 gene) at a ratio of 1:3. The virus populations in all virus-infected cells and tissues of different hosts exhibited a stable 1:3 structure. WSSV lncRNA-24 in Type A WSSV promoted virus infection by binding to shrimp and WSSV miRNAs, while the wsv195 gene in Type B WSSV played an essential role in virus infection. Loss of Type A WSSV or Type B WSSV in the WSSV population led to a 100-fold decrease in viral copy number in shrimp. Simultaneous loss of both types of WSSV prevented virus infection. These results indicated that the virus infection process was completed by two types of WSSV encoding different functional genes, revealing the complementary effects of WSSV population. Therefore, our study highlights the importance of the complementarity of virus population components in virus infection. RNA-seq data revealed that the ratio of WSSV lncRNA-24 to wsv195 mRNA contents was 1:3  . The strProcambarus clarkii) and mud crabs (Scylla paramamosain). The results again revealed a 1:3 ratio (Type A WSSV : Type B WSSV) in different tissues or organs of virus-infected crayfish  into shrimp d shrimp . The sild shrimp  and virud shrimp  comparedTo explore the underlying mechanism of WSSV lncRNA-24, the protein and DNA molecules that interact with WSSV lncRNA-24 were screened, but no binding protein or DNA molecules were found. Thus, the miRNAs interacting with WSSV lncRNA-24 were characterized.The prediction analysis showed that WSSV lncRNA-24 can target shrimp miRNAs  and WSSV miRNAs  . To evalTo characterize the interactions between WSSV lncRNA-24 and WSSV miRNAs, WSSV lncRNA-24 was cotransfected with WSSV-miR-77, WSSV-miR-158, WSSV-miR-164 or WSSV-miR-212 into insect cells. The data showed that WSSV lncRNA-24 interacted with WSSV-miR-77, WSSV-miR-158 and WSSV-miR-164 .To reveal the roles of miRNA interactions with WSSV lncRNA-24, the expression levels of miRNAs in the haemocytes of WSSV-infected shrimp were examined. Northern blots indicated that shrimp miR-2a, shrimp miR-184, WSSV-miR-77, WSSV-miR-158, and WSSV-miR-164 were significantly upregulated in shrimp in response to WSSV infection , suggestTaken together, the findings revealed that Type A WSSV in the virus population promoted virus infection by encoding WSSV lncRNA-24 to suppress the expressions of shrimp and WSSV miRNAs .To elucidate the role of Type B WSSV encoding wsv195 mRNA in virus infection, the expression of the wsv195 gene was knocked down by injecting a sequence-specific siRNA (wsv195-siRNA) into shrimp. The results confirmed that the expression of wsv195 was silenced by wsv195-siRNA in WSSV-infected shrimp compared with controls . WesternThe results showed that silencing wsv195 expression significantly decreased the WSSV copy numbers in WSSV-infected shrimp compared with controls . In addiTo further evaluate the role of the virus population in virus infection, the expression of WSSV lncRNA-24 encoded by Type A WSSV or/and the wsv195 gene encoded by Type B WSSV was silenced in WSSV-infected shrimp before examination of virus infection. Northern blots indicated that the expression of WSSV lncRNA-24 was completely silenced in the WSSV-infected shrimp . The resTo reveal the impact of Type B WSSV in virus population on virus infection, the expression of wsv195 was silenced in WSSV-infected shrimp. When Type B WSSV was completely depleted , the WSSTo further explore the impact of the simultaneous loss of Type A and Type B WSSVs on virus infection, the expressions of WSSV lncRNA-24 and wsv195 were simultaneously completely suppressed in shrimp . The WSSThe above data demonstrated that the virus infection process was completed by different types of virus encoding different functional genes that exerted complementary effects in the virus population .Viruses have very small genomes, limiting the genes needed to complete their life cycle in host cells . In ordeIn this study, the results demonstrated that the loss of Type A WSSV or Type B WSSV in the WSSV population resulted in a 100-fold decrease of viral copies in hosts. When both types of WSSV in the virus population were simultaneously depleted, the virus was not able to infect its hosts. Therefore there was a complementary effect between different viral types in the WSSV population, resulting from different functional genes encoded by different viral types. In the process of virus infection, the virions with varied viral genomes proliferated in the same host cells, thus benefiting from cooperative interactions among co-infecting virions with heterogeneous viral genomes. Every type of virions could function as a helper virus to the other types of virions of the virus based on the differences in their viral genomic sequences. The existence of virus population, which allowed permissive genomic mutations to reside in different virions, was indispensable for the propagation of the virus. The consequences of the complementary effect of virus population discussed here would not be exclusive to WSSV, raising the possibility that similar considerations existed in all viruses as well. Interestingly, pleomorphism is common among enveloped viruses, with filamentous morphology common in the filoviridae, pneumoviridae, and paramyxoviridae families . More geMarsupenaeus japonicus) about 10 g/shrimp, crayfish (Procambarus clarkii) about 20 g/crayfish and mud crab (Scylla paramamosain) about 50 g/crab were cultured in tanks containing 80 liters of aerated seawater at room temperature (25°C), respectively. Based on PCR detection using WSSV-specific primers (5′-TATTGTCTC TCCTGACGTAC-3′ and 5′-CACATTCTTCACGAGTCTAC-3′), shrimp, crayfish and crab were WSSV-free prior to experimental infection. The virus-free shrimp, crayfish and crab were infected with WSSV (105 virus copies/ml) by injection at 100 μl WSSV/animal, respectively. At different times postinfection, three shrimp, crayfishes or crabs were randomly collected for each treatment. The hemocytes of shrimp, crayfishes or crabs were mixed for later use.Shrimp  were used  following the manufacturer’s procedure. The extracted RNAs were subjected to RNA-seq and then analyzed by LC Sciences . The sequences were mapped to the WSSV genome to find lncRNAs of WSSV. To predict WSSV lncRNAs, two independent computational algorithms CNCIere used .® 1st Strand cDNA Synthesis Kit  with Oligo dT as the primer. U6 was used as a control. The expression levels of WSSV lncRNA-24 and wsv195 mRNA were examined using quantitative real-time PCR with specific primers (5′-GGAAGGGTTA AAGAAATCG-3′ and 5′-CTCGTTCCTCTTCATTCA-3′) and sequence-specific probe . Quantitative real-time PCR was performed using a 2 × SYBR Premix Ex Taq Kit  according to the manufacturer’s manual. PCR was conducted at 95°C for 3 min, followed by 40 cycles at 95°C for 15 s and 60°C for 30 s.Total RNAs were extracted from WSSV-infected shrimp using RNAprep Pure Tissue Kit  according to the manufacturer’s instructions. The first strand of cDNA was synthesized using PrimeScript For examination of WSSV encoding WSSV lncRNA-24 or wsv195 mRNA, the WSSV genome was extracted from virus-infected shrimp using an SQ Tissue DNA Kit . The viral genomic DNA was subjected to quantitative real-time PCR as described above.5 copies/ml) were co-injected into virus-free shrimp at 100 μl/shrimp. At 12 h after co-injection, the siRNA (15 μg) was injected into the same shrimp (100 μl/shrimp). WSSV alone (105 copies/ml) and phosphate buffered saline (PBS) were included in injections as controls. For each treatment, 20 shrimps were used. At different time after injection, the shrimp were collected for later use. The assays were biologically repeated three times.To silence gene expression, siRNA specifically targeting a gene was synthesized according to the design rule for siRNA with a commercial kit according to the manufacturer’s instructions . The siRNAs used were WSSV lncRNA-24 siRNA (5′-CCTGAAGGAGGAGACCTAT-3′) and wsv195 siRNA (5′-G CGGCGACAGAGACTCATT-3′). As controls, the siRNA sequences were scrambled, generating WSSV lncRNA-24-siRNA-scrambled (5′-GGCGGTACGCACGAATTAA -3′) and wsv195-siRNA-scrambled (5′-GCGCAGACGCGACGTATA-3′). RNA Interference (RNAi) assay in shrimp was conducted by injecting siRNA (30 μg/shrimp) into the lateral area of the fourth abdominal segment of shrimp using a 1-ml sterile syringe. The siRNA (15 μg) and WSSV  and then subjected to quantitative real-time PCR using WSSV-specific primers (5′-TTGGTTT CAGCCCGAGATT-3′ and 5′-CCTTGGTCAGCCCCTTGA-3′) and TaqMan probe (5′-FAM-TGCTGCCGTCTCCAA-TAMRA-3′). A linearized plasmid with a 1,400-bp DNA fragment of WSSV genome was used as an internal standard for quantitative real-time PCR. PCR was conducted at 95°C for 1 min, followed by 45 cycles at 95°C for 30 s, 52°C for 30 s, and 72°C for 30 s.Proteins were separated by 12% SDS-polyacrylamide gel electrophoresis and then transferred onto a nitrocellulose membrane. After blocking with 5% non-fat milk in TBST  for 2 h at room temperature, the membrane was incubated with a primary antibody overnight, followed by incubation with horseradish peroxidase-conjugated secondary antibody  for 2 h at room temperature. The primary antibodies were prepared in our laboratory. Subsequently the membrane was detected using a Western Lightning Plus-ECL kit .in vitro transcription T7 kit . All transfections were carried out in triplicate with Cellfectin transfection reagent (Invitrogen) according to the manufacturer’s protocol. At 48 h after transfection, the fluorescence of cells was examined with a Flex Station II microplate reader  at 490 and 510 nm for excitation and emission, respectively. The fluorescence values were corrected by subtracting the auto fluorescence of cells not expressing EGFP. All the experiments were repeated biologically three times.Insect High Five cells  were cultured at 27°C in Express Five serum-free medium (Invitrogen) containing l-glutamine (Invitrogen). The cells at about 70% confluence were co-transfected with a synthesized WSSV or shrimp miRNA (300 nM) and a plasmid consisting of the EGFP gene and WSSV lncRNA-24. The miRNAs were synthesized with the D6140 Total RNAs were extracted from shrimp hemocytes with mirVana miRNA isolation kit . After separation on a denaturing 15% polyacrylamide gel containing 7 M urea, the RNAs were transferred to a Hybond-N+ nylon membrane, followed by ultraviolet cross-linking. The membrane was prehybridized in DIG (digoxigenin) Easy Hyb granule buffer  for 0.5 h at 42°C and then hybridized with a DIG-labeled miRNA  at 42°C overnight. Subsequently the detection was performed with the DIG High Prime DNA labeling and detection starter kit II (Roche).5 copies/ml) were co-injected into virus-free shrimp at a 100 μl/shrimp. At 12 h after the co-injection, AMO (10 nM) was injected into the same shrimp. As controls, AMO-miR -2a-scrambled (5′-TTGCATGTCTGTCGAG-3′), AMO-miR-184-scrambled (5′-TTG CATGTCTGTCGAG-3′), AMO-WSSV-miR-77-scrambled (5′-TTGCATGTCTGTC GAG-3′), AMO-WSSV-miR-158-scrambled (5′-TTGCATGTCTGTCGAG-3′), AMO-WSSV-miR-164-scrambled (5′-TTGCATGTCTGTCGAG-3′), WSSV alone (105 copies/ml) and phosphate buffered saline (PBS) were included in the injections. At different time after injection, the shrimp hemocytes were collected for later use.To knock down the expression of miR-2a, miR-184, WSSV-miR-77, WSSV-miR-158 or WSSV-miR-164 in shrimp, a sequence-specific anti-miRNA oligonucleotide (AMO) was injected into WSSV-infected shrimp. AMO-miR-2a (5′-CGCTCATCAAAGCTGGCTGTGATA-3′), AMO-miR-184 (5′-GCCCTTATCA GTTCTCCGTCCA-3′), AMO-WSSV-miR-77 (5′-ACATCTTCATCATTATAAGAA A-3′), AMO-WSSV-miR-158 (5′-GAAGAAGAAGAAAAAGGAGAAG-3′) and AMO-WSSV-miR-164 (5′-TAGAGAAGAA AAAGAAGGAAG-3′) were synthesized  with a phosphorothioate backbone and a 2′-O-methyl modification at the 12th nucleotide. AMO (10 nM) and WSSV . The differences between treatments were analyzed by SRR18218566.The data presented in the study are deposited in the NCBI repository, accession number XZ and YS conceptualized the study and designed the experiments. YS and YZ performed the experiments. XZ and YS wrote the manuscript with contributions from all authors.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Anaplasma marginale-challenged bulls were observed for clinical disease and infection progression and changes in breeding soundness compared to uninfected control bulls for 16 weeks.Natural service breeding is common in U.S. cow-calf operations. Diseases impacting bull reproductive performance have significant economic consequences for producers. Anaplasmosis may be an underappreciated cause of poor reproductive performance in bulls. The primary systemic effects of bovine anaplasmosis including anemia, fever, and weight loss, can all result in unsatisfactory reproductive performance. The objective of this pilot study was to evaluate breeding soundness examination (BSE) outcomes and clinical changes in bulls during and upon resolution of clinical anaplasmosis. Anaplasma marginale-challenged bulls were PCR-positive, seropositive, and showed clinical signs by 3-, 17-, and 24-days post-challenge, respectively. Clinical signs of anaplasmosis included pallor, icterus, fever (≥ 40.2 °C), and weight loss. Acute anemia was observed in all challenged bulls with PCV nadirs ≤ 18% and peak percent parasitized erythrocyte ≥ 50%. Decreased scrotal circumference and poor semen quality , were initially observed within days after onset of clinical anaplasmosis signs and continued weeks beyond disease resolution. Control bulls remained negative for A. marginale.All This pilot study demonstrates that clinical anaplasmosis reduces breeding soundness in beef bulls. Anaplasmosis should be considered as a differential for bulls with decreased semen quality, especially within endemic areas. A 90 day or greater retest window is recommended for bulls of unsatisfactory breeding potential recently recovered from clinical anaplasmosis.The online version contains supplementary material available at 10.1186/s12917-022-03470-7. Bull fertility is a key component to success and profitability in commercial cow-calf operations. In July 2021, the United States Department of Agriculture’s National Agricultural Statistics Services reported an estimated 2.1 million beef bulls in the United States (U.S.) and 40.9 million beef cows of calving age , highligAnaplasma marginale. Anaplasmosis in cattle causes anemia, fever, weight loss, lethargy, and death in severe acute cases [Fertility is five times more valuable than production traits such as beef merit or average daily gain in a beef cow-calf herd . Subfertte cases –15. Few te cases ; but, ante cases , 17, 18.te cases –22. Fevete cases –25. Weigte cases , all of te cases . Finallyte cases , 28.A. marginale is expansive, present in tropical, subtropical, and temperate regions worldwide [A. marginale has been reported in most continental states, and is most prevalent in the Gulf Coast, Midwest and Western regions—some of the highest cattle-producing regions in the country [A. marginale [A. marginale and developing clinical anaplasmosis. Therefore, the objective of this study was to determine the effects of acute A. marginale infection on overall breeding soundness examination (BSE) pass rate, including sperm morphology and progressive motility, and scrotal circumference in commercial beef bulls during and upon resolution of clinical anaplasmosis. We hypothesized that bulls with clinical anaplasmosis, including disease-associated anemia and fever, would have reduced semen quality and, subsequently, lower BSE pass rates. Information on how clinical anaplasmosis negatively affects bull breeding soundness will inform strategic anaplasmosis and herd management decisions, including BSE recommendations for bulls in anaplasmosis-endemic areas.The distribution of orldwide , 30. In  country , 29, 30. country –33. Furtarginale . The exp≥24-months of age; sound breeding potential (met minimum standards of a complete BSE on two separates dates within 3 months of study start date); negative for A. marginale via PCR; and negative for A. marginale-specific antibodies via serum cELISA testing. At the time of the study, bull weights ranged from 454 to 799 kg . Bull ages ranged from 24- to 48-months old (median = 24-months old).Six crossbred beef bulls from the Kansas State University Western Kansas Agricultural Research and Extension Center herd  were enrolled in this pilot study. Requirements for bull enrollment included: healthy on initial physical examination; ad libitum access to fresh water and were fed a standard ration of grain at 0.5% body weight per day with ad libitum access to hay.Bulls in the same treatment group were co-housed in an outdoor dry lot pen for approximately six months. During that time, bulls had A. marginale were re-tested for these possible co-infections at peak fever and all maintained their pre-study status for BTV, BLV and BVDV, indicating that these co-infections had minimal to no contribution on study outcomes. Furthermore, previous work has demonstrated that positive serologic status for these infections in bulls has not demonstrated unsatisfactory semen quality [As the bulls originated from a working herd of cattle, the potential for other common comorbidities in study bulls was evaluated. All bulls were tested for potential co-infection of Bluetongue virus (BTV), Bovine Leukemia Virus (BLV), and Bovine Viral Diarrhea Virus (BVDV). No bulls demonstrated clinical signs associated with any of these potential co-infections at study enrollment. At study enrollment, all bulls were seropositive by ELISA but PCR negative for BTV; bulls 8553, 9431, 9600, and 7532 were seropositive for BLV; and all bulls were negative for BVDV by antigen capture ELISA. Bulls that were subsequently challenged with  quality –37.All animal studies were carried out under an approved Institutional Animal Care and Use protocol (IACUC 4476) and an approved Institutional Biosafety Committee protocol (IBC 1495) on file at the University Research Compliance Office at Kansas State University, Manhattan, KS. All methods were carried out in accordance with relevant guidelines and regulations in compliance with ARRIVE guidelines.A. marginale challenge group (ANA) and were inoculated on Day 0 with blood from a persistently infected donor cow . The other three bulls  were included in the unchallenged control group (CON). Breeding soundness examinations were performed weekly on all bulls starting two weeks prior to Day 0 and weekly through Day 84. Two additional BSEs were performed on all bulls on Day 98 and Day 112, 14- and 16-weeks post-inoculation, respectively.Enrolled bulls were blocked by weight and allocated randomly into two equally sized groups using the RAND function in a spread-sheet program . Three bulls  were included in the ≥ 25% of their respective baseline value (baseline determined from the mean of three time points prior to inoculation) [Blood samples were collected from all bulls (ANA and CON) once weekly for 3 weeks prior to inoculation; twice weekly post-inoculation (Day 0 to Day 41); once weekly from Day 42 to 84; and on Day 98 and 112. At each blood collection time point, approximately 20 mL of blood was obtained from the coccygeal vein and distributed between evacuated tubes  containing EDTA (1.8 mg/mL whole blood) and tubes with no anticoagulant. Anemia was assessed by quantifying packed cell volume (PCV) from whole blood collected into EDTA tubes and then centrifuged in microhematocrit capillary tubes for 5 min . A bull was considered anemic if their PCV was reduced by ulation) , 39. A rulation) . All bul≤ 15%, fever (≥ 40.8 °C), and any combination of pale or icteric mucous membranes, lethargy, anorexia, or loss of body condition. If two or more of these clinical signs were appreciated on daily health checks or at time of blood draw, the bull was administered oxytetracycline subcutaneously  at a dose rate of 20 mg/kg of body weight for up to 3 doses given once every 48 h. The number of oxytetracycline doses administered depended on an individual bull’s clinical status.Severe clinical anaplasmosis included a decrease in PCV of 7% or greater in < 48 h, a PCV All bulls were treated every two weeks with 30 mL of a topical permethrin  applied across the topline to control pre-existing lice and for the control of any potential arthropod vectors.A. marginale inoculate used as challenge material was obtained from an apparently healthy, persistently infected, mature donor cow  from the Kansas State University Western Kansas Agricultural Research and Extension Center Cow-Calf Unit in Hays, Kansas. The donor was confirmed positive for A. marginale via PCR prior to the beginning of the study. This cow was also seropositive but PCR negative for BTV and seropositive for BLV. To collect blood, the donor jugular site was clipped and aseptically prepped with povidone iodine scrub and alcohol. A 14-gauge needle was placed in the right jugular vein and attached to a blood collection set, and approximately 400 mL of blood was collected into a heparinized, 450-mL blood collection bag. The blood was placed on ice for transport and maintained at 4 °C until the time of inoculation the next morning. The three bulls in the ANA group were inoculated with 40 mL of donor cow whole blood by direct venipuncture into the right jugular vein. Bulls were monitored for 15 min after inoculation for any signs of hypersensitivity reaction or anaphylaxis.The A. marginale in the donor cow was identified by amplifying, cloning, and sequencing the variable region of the Major Surface Protein 1a gene to determine the Msp1a genotype(s) as previously described [A. marginale challenge strain was confirmed in each experimentally infected bull. Sequences from this study were submitted to GenBank and are available at the following accession numbers: ON597854-ON97859.The strain of escribed . The A. Society for Theriogenology Manual for Breeding Soundness Examination of Bulls, 2nd Edition guidelines [All BSEs were performed by the same veterinarian using the idelines . To perfGeneral physical examination included an overall health assessment with specific evaluation of foot and leg soundness, evaluation of vision, palpation of external genitalia, and rectal palpation of internal genitalia. Body condition score (BCS) assessment was considered part of the general physical exam, and was assigned based on a 9-point scoring system . All exaSperm morphology was evaluated from a minimum of 100 sperm cells via microscopy using eosin-nigrosin stain  under 1,000X magnification in oil. Each sperm cell was categorized into “normal”, “head abnormality”, “midpiece abnormality”, or “tail abnormality,” with a minimum of 70% morphologically normal sperm cells required for passing. Examples of sperm head abnormalities include pyriform heads and nuclear vacuolations. Examples of sperm midpiece abnormalities include proximal droplets and distal midpiece reflections (DMRs). Examples of sperm tail abnormalities include coiled tails. Presence or absence of other abnormal cells in the ejaculate, such as white cells  or immature sperm cells — spermatocytes — was assessed with Wright-Giemsa-stained semen smears  under 1,000X magnification in oil. Minimal to no white blood cells or spermatocytes in the semen were required for satisfactory breeding potential.Sperm motility was assessed chute-side using a compound microscope at 100X magnification , and scored on a percentage basis, with a minimum of 30% sperm moving in a forward linear motion per high powered field required to pass this metric. Warm, sterile, phosphate-buffered saline (PBS) was incorporated into a drop of neat semen to dilute the sample for more accurate evaluation of sperm cell progressive motility.≥ 34 cm scrotal circumference; iv) ≥ 70% sperm cells of normal morphology; and v) ≥ 30% of sperm with progressive motility. Bulls were considered of unsatisfactory breeding potential if they did not meet minimum requirements in any of the above categories.Collectively, bulls were considered of satisfactory breeding potential if they had: (i) no abnormalities on general physical examination; (ii) no abnormalities on assessment of internal and external genitalia; iii) A. marginale Msp5 gene [A. marginale bactermia. PCR mastermix preparations were set up in 20 µL reaction volumes, each containing 0.2 µM of each primer (Am msp5 F: ATA CCT GCC TTT CCC ATT GAT GAG GTA CAT and Am msp5R AGG CGA AGA AGC AGA CAT AAA GAG CGT), 10 µL of SsoAdvanced Universal SYBR Green Supermix , and 2 µL gDNA. Reaction cycling was performed using a CFX Connect Real-Time PCR System (Bio-Rad), using the following cycling parameters: one cycle of 98 °C for 2 min; followed by 40 cycles at 98 °C for 5 s, 60 °C for 5 s and 74 °C for 15 s; and a final melt curve cycle of 65 – 95 °C with increasing 0.5 °C temperature steps at 10 s/step. Real-time qPCR data was visualized and analyzed using CFX Maestro Software v1.1 (Bio-Rad).Total genomic DNA (gDNA) was extracted from 100 µL of whole blood collected into EDTA tubes using the Quick-DNA Miniprep Kit  according to manufacturer instructions, and the resulting gDNA was eluted in 35 µL of DNA Elution Buffer. Genomic DNA was stored at -20 °C. A quantitative, real-time PCR (qPCR) assay targeting a portion of the single-copy sp5 gene  was usedA. marginale was assessed via microscopic examination of Wright-Giemsa-stained blood smears . Total red blood cells in a monolayer were counted microscopically under 1,000X magnification. The number of A. marginale-infected red blood cells were divided by the total number of evaluated red blood cells, and that value multiplied by 100 to determine the PPE. A minimum of 200 red blood cells were evaluated per sample.The percentage of red blood cells infected with A. marginale serological screening using a commercial cELISA that detects host antibody produced against A. marginale Msp5 . Animals with a percent inhibition score ≥ 30% were considered seropositive for A. marginale.Blood samples collected into tubes without anticoagulant were centrifuged at 3,000 rpm for 10 min at 20 °C to separate and collect serum. Serum samples were aliquoted and stored at -80 °C before testing. Serum samples were submitted to the Iowa State University Veterinary Diagnostic Laboratory  for Packed cell volume percent change and scrotal circumference percent change from baseline were analyzed separately at each post-challenge study day under the linear model with treatment being the fixed effect. Percent normal morphology and percent progressive motility were analyzed separately at each post-challenge study day, under the linear model with treatment being the fixed effect and baseline average being the covariate. All hypothesis tests were 2-sided tests. Statistical analysis was performed using Statistical Analysis Software  MIXED procedure.A. marginale was used to challenge ANA group bulls. The PCV and A. marginale bacteremia of the donor was 32% and 1.15E + 06 A. marginale/mL blood, respectively. The A. marginale Msp1a genotype identified in the donor cow was: A B B B.Blood from a healthy, 4-year-old, Angus-cross cow persistently infected with A. marginale inoculated bulls developed anemia and fever. Time to initial signs of clinical anaplasmosis  ranged from 21 to 24 days post-challenge   through at least Day 42 (14 days beyond ANA PCV nadir). All bulls in the ANA group developed fevers  which peaked 24 to 28 days after inoculation  for the duration of the study Fig. .A. marginale/mL blood . All ANA bulls transitioned into the PI disease state with resolution of clinical signs. On the last day of the study, average bacteremia was 2.40E + 07 A. marginale/mL blood . All bulls remained infected with A. marginale, despite treatment with oxytetracycline . All CON bulls remained qPCR negative for A. marginale throughout the study.Bacteremia was first detected via qPCR in all ANA bulls by 3 days post-inoculation. Bacteremia peaked 21 to 26 days post-inoculation. The average bacteremia peak was 8.75E + 08 A. marginale parasitized erythrocytes were ever observed in CON bulls at any point in the study.Percent parasitized erythrocytes evaluation began 26 days after inoculation . By 17 days post-inoculation, all bulls in the ANA group  had seroconverted and remained seropositive for the remainder of the study. All CON bulls remained negative for A. marginale inoculation), incubation period , clinical disease , recovery , and resolution .Breeding soundness examination results are presented overlaid with different periods of clinical anaplasmosis progression: baseline , bull 8553 returned to satisfactory breeding potential 72 days after initial failure, and bull 9528 returned to a satisfactory breeding potential 28 days after initial failure. The CON bulls 7532 and 9600 maintained satisfactory breeding soundness throughout the study, while one bull in the CON group (9550) had unsatisfactory BSE results 67 days after study start and never returned to passing. This bull had changes in testicular texture and size consistent with insult related to extreme cold temperatures experienced during the study period. This bull remained negative for A. marginale throughout the study.The occurrence of clinical anaplasmosis coincided with loss of breeding soundness for a variable but extended time period. All ANA bulls fell below satisfactory breeding potential standards beginning 28 days post-inoculation with None of the ANA nor the CON bulls developed abnormalities related to feet, legs, or eyes. None of the ANA nor the CON bulls developed any internal genitalia abnormalities at any time point via examination by rectal palpation. All ANA and CON bulls started with and maintained their ability to extend their penis, acquire an erection, and ejaculate via electroejaculation. Although not specifically measured, additional physical response changes were observed in some ANA bulls during clinical disease including prolonged reaction time (time to produce ejaculate) and poor erection response. Two bulls in the ANA group  developed weak erection response  during peak bacteremia (24 days post-inoculation) but returned to satisfactory response within 21 days of peak bacteremia (45 days post-inoculation).All ANA bulls had decreased body condition from baseline Fig. , with trP = 0.487), but were significant after resolution of clinical disease on Day 70  (Table P = 0.134), but were significant on Day 70  and neared significance on Day 63 . None of the ANA bulls returned to baseline scrotal circumference by the end of the study despite meeting minimum satisfactory standards by the end of the study. One ANA bull (9431) had consistently soft testicles on palpation starting 14 days after inoculation which remained abnormal for approximately 63 days through the end of the study.Each ANA bull had decreases in scrotal circumference from baseline Table . Peak re3) Table . CompareThroughout the study among CON bulls, the mean change in scrotal circumference varied 1 – 5% above baseline. Two CON bulls  had overall scrotal growth from baseline by the end of the study, which was expected as these were younger and still maturing bulls. One CON bull (9550) had an overall 4 cm decrease in scrotal circumference during the study, with consistent decreases most notably in the left testicle starting at Day 77. Despite abnormal testicular palpation, the overall scrotal circumference for this bull met minimum satisfactory standards during the study.P = 0.049, 0.013, 0.026, respectively; Table Loss of morphologically normal sperm was observed in all ANA bulls Fig. . All ANACollectively, unsatisfactory percentages of sperm head, midpiece, and tail abnormalities were observed in ANA bulls Fig. . The mosFor CON bulls 7532 and 9600, the percentage of morphologically normal sperm remained above 70% throughout the study , and for 35 days after that  of the ANA bulls.In this pilot study, we demonstrate that clinical anaplasmosis negatively impacts beef bull breeding potential in animals previously determined of satisfactory breeding potential. Further, loss of satisfactory breeding potential occurred for an extended time period in bulls newly infected with Efficient spermatogenesis requires healthy testicular tissue, hormone balance, overall bull health, and appropriate environmental conditions , 26, 44.Theileria orientalis, another tick-borne pathogen that causes anemia and fever, in Friesian bulls in New Zealand, found no effect on sperm quality parameters despite reductions in libido [Anaplasmosis causes a hemolytic anemia through removal of infected red blood cells by the reticuloendothelial system . Anemic n libido . PossiblBos indicus x Bos Taurus bulls with insulated scrota and elevated testicular temperature [As with classic clinical anaplasmosis, all ANA bulls developed acute fever Fig. . Increasperature . In thatperature .Most bulls of satisfactory breeding potential will have some proportion of morphologically abnormal sperm, though this value should always be less than 30%. These expected abnormalities can be due to post-ejaculate sample handling or cold shock of the sample. Ejaculate with > 30% morphologically abnormal sperm likely indicates a change in bull health status and a reduced likelihood of reproductive success  , 55. TheA. marginale organism visually detected in any stained semen preparations. Interestingly, A. marginale was inconsistently detected via qPCR in several ANA bull semen samples (semen was tested by qPCR out of curiosity). As A. marginale resides in red blood cells, these findings are curious, and may simply be due to sample contamination; however, contamination of semen samples with frank blood was never observed. Further research is required to identify whether PCR-positive semen from infected bulls poses a transmission risk.Presence of other abnormal cell types were also observed in ANA bull ejaculates. Spermatocytes Fig.  J, or imAnnual breeding soundness examination, including assessment of physical exam parameters, sperm morphology, and progressive sperm motility is one of the most cost-effective measures to confirm satisfactory bull breeding potential , 7, 64. A. marginale inoculated bulls in that study demonstrated improvements in sperm morphology after clinical disease resolved, similar to the outcome for the bulls in our study. Swift et al. further observed reduced libido response to cycling cows by bulls during peak clinical disease. Bull behavior around cycling females was not investigated in our study. Despite a difference of 40 years, differences in equipment and reagents, and likely different A. marginale strains, our study and the Swift study had remarkably similar outcomes. Despite a small sample size, our findings agree with those of Swift et al. on how anemia and fever can reduce bull breeding potential.Our findings are similar to an earlier study examining the impact of anaplasmosis on bull breeding soundness by Swift et al. in 1979 . In thatA. marginale DNA in semen samples also warrants effort into whether semen directly, or breeding activities that can cause reproductive mucosal damage, contribute to disease transmission. Finally, whether bulls with chronic anaplasmosis exhibit lower satisfactory semen quality parameters, would be useful to assess as most cattle that survive clinical anaplasmosis develop chronic anaplasmosis.Building on the results of this pilot study, future studies are needed to mechanistically address how individual hallmark clinical signs of anaplasmosis (e.g. anemia and fever) specifically affect semen quality and reproductive success. Additional variables that could further affect clinical anaplasmosis outcomes and contribute to bull breeding soundness include bull signalment, nutrition status, and co-morbidities. Incorporation of testicular histopathology, ultrasonography, and thermography would enable characterization of anaplasmosis-associated testicular degeneration and injury as prognostication for return to breeding soundness. This is especially important for veterinarians offering recommendations to producers to consider a longer bull retesting window. If the damage caused to the testicle is reversible, retaining bulls longer for retesting is more economic than culling valuable bulls capable of producing viable sperm. However, if testicular damage from disease is irreversible and the bull is retained in the herd for the sake of a longer retesting window, the cost the producer incurs waiting to cull an infertile bull is counted as a loss. Additionally, detection of A. marginale-infected bulls. Anaplasmosis should be considered as a differential-diagnosis for bulls with unsatisfactory BSE results or poor reproductive performance in anaplasmosis-endemic areas, especially if there is evidence of recent seroconversion. Veterinarians performing BSEs should consider a longer retesting window of 90 days or longer for deferred bulls, and anaplasmosis testing for breeding bulls in anaplasmosis-endemic areas. Producers should take caution when introducing anaplasmosis-naïve, reproductively sound bulls into an anaplasmosis-endemic herd. The results of our study demonstrate the detrimental effects of clinical anaplasmosis on bull breeding potential, thus it is imperative that cow-calf herd management, testing, and treatment protocols for A. marginale consider risks and impacts of the disease in both females and bulls.Pervasive and expanding infectious diseases of cattle such as bovine anaplasmosis hampers the potential for profitable beef production. Under the conditions of our pilot study, we demonstrate that clinical anaplasmosis causes reduced breeding potential through reduced semen quality, scrotal circumference, and body condition in bulls with previous satisfactory breeding potential. The most striking reductions were in sperm motility and morphology. Although clinical anaplasmosis was associated with reductions in several breeding soundness evaluation metrics, this loss was temporary and a return to satisfactory breeding potential was observed for two of three Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6Supplementary Material 7Supplementary Material 8