Estimation Of Values Research Articles

Evaluation of MRX PT DOAC as a new screening method for detecting interferences in thrombophilia analyses

Background Direct oral anticoagulants (DOACs) can interfere with coagulation analyses, causing erroneous results such as false-positive lupus anticoagulant and false-normal antithrombin, threatening patient safety when overlooked. A test using a prothrombin time quotient method to detect DOAC presence in plasma samples is now commercially available, the MRX PT DOAC, with the result expressed as Clot Time Ratio (CTR). Objectives Evaluate the ability of MRX PT DOAC to identify interfering apixaban or rivaroxaban concentrations, identify non-interfering or interfering patient samples, and detect whether a patient is on DOAC treatment. Methods An MRX PT DOAC reference interval was established, and MRX PT DOAC results related to FXa inhibitor concentrations. MRX PT DOAC patient plasma results were related to indications of analytical interference with lupus anticoagulant and antithrombin analyses and with the patients’ anticoagulant drug use, according to medical records. Results The MRX PT DOAC CTR reference interval was 0.98–1.38. MRX PT DOAC apixaban and rivaroxaban interference detection sensitivity was 1.00 (0.96 − 1.0). For subgroups from 315 patient plasma samples, the negative predictive values estimates were 0.84 or above (95% confidence interval minimum 0.64) for excluding analysis interference with the lupus anticoagulant and antithrombin analyses and for excluding DOAC treatment as per medical records. All 9 interference-indicating DOAC samples were identified for the lupus anticoagulant analyses, 5 out of 11 for antithrombin. Conclusions The MRX PT DOAC is a potential screening tool for interference. Confirming results in a larger DOAC patient group and further investigating the antithrombin interference detection uncertainty is important.

Multistrap: boosting phylogenetic analyses with structural information

In a phylogeny, trustworthy reliability branch support estimates are as important as the tree itself. We show that reliability support values based on bootstrapping can be improved by combining sequence and structural information from proteins. Our approach relies on the systematic comparison of homologous intra-molecular structural distances. These variations exhibit less saturation than sequence-based Hamming distances and support the computation of tree-like distance matrices resolvable into phylogenetic trees using distance-based methods such as minimum evolution. These trees bear strong similarities to their sequence-based counterparts and allow the estimation of bootstrap support values, but they are sufficiently distinct so that their information content may be combined. The combined sequence and structure bootstrap support values yield improved discrimination between correct and incorrect branches. In this work we show that our approach, named multistrap, is suitable for the improvement of bootstrap branch support values using both predicted and experimental 3D structures.

Evaluation of polygenic risk scores for hormones and receptors levels in patients with vestibulodynia: a case-control study.

Vulvodynia is a multifactorial disease affecting 7%-16% of reproductive-aged women in general population; however, little is still known about the genetics underlying this complex disease. To compare polygenic risk scores for hormones and receptors levels in a case-control study to investigate their role in vulvodynia and their correlation with clinical phenotypes. Our case-control study included patients with vestibulodynia (VBD) and healthy women. All participants underwent a vestibular cotton swab test and the assessment of their: pelvic floor, vestibular trophism, ultrasound vestibular mucosa thickness, and current perception threshold levels (Neurometer CPT device). Shallow whole genome sequencing and polygenic risk score calculations were performed. Linear regression models were applied to predict whether genomic predisposition varied significantly between cases and controls, and to investigate the relationship of polygenic risk scores with clinical endophenotypes. The genomic predisposition to hormones and receptors levels, together with clinical endophenotypes, can support VBD diagnosis and personalized treatment of related pain condition. Thirty women with VBD and 30 controls were recruited. Significant differences between cases and controls were observed for body mass index, vestibular mucosa thickness, vestibular trophic health, pelvic floor hypertone and pain sensitivity (P < .05). Cases showed a genomic predisposition to higher levels of membrane-associated progesterone receptor component 1 compared to controls (P < .05). When considering the clinical endophenotypes, cases showed significant correlations between their polygenic risk scores with several clinical measures: predicted genomic levels of testosterone and estrogen receptor and the vestibular mucosa thickness values (estimates: 9.74E-09 and 9.16E-08, respectively; P < .05); predicted genomic levels of prolactin and Neurometer data at 250Hz (-2.15E-07; P < .05); predicted genomic levels of prolactin, membrane-associated progesterone receptor component 2 and mineralocorticoid receptor and Neurometer data at 5Hz (-3.75E-07, -3.43E-07 and -3.06E-07, respectively; P < .05). Introduction of polygenic risk scores evaluation in clinical practice can assist early diagnosis and personalized therapeutic treatment of VBD. Polygenic risk scores and clinical data allowed the identification of disease endophenotypes and highlighted the possibility of a personalized therapeutic approach. As limitations, these data should be confirmed on a larger cohort and polygenic risk score calculation should be adapted to ancestries other than European. Cases showed significant differences compared to controls on both clinical and genetic data and specific endophenotypes necessary to classify disease development and treatment were identified.

Endocrine-disrupting compounds in urban rivers of the southern border of Mexico: Occurrence and ecological risk assessment

The occurrence of seven endocrine-disrupting compounds (EDCs) in four urban rivers on the southern border of Mexico was studied in this work. The selected EDCs were 17β-estradiol (E2), estriol (E3), 17α-ethinylestradiol (EE2), bisphenol A (BPA), bisphenol F (BPF), 4-nonylphenol (4NP) and 4-tert-octylphenol (4TOP). Water samples from the Coatan, Texcuyuapan, Cahoacan, and Coatancito rivers were collected at three different sites on each river and processed by solid phase extraction (SPE). The samples were analyzed by gas chromatography triple quadrupole tandem mass spectrometry (GC-MS/MS) and compounds of interest were identified by dynamic mass reaction monitoring mode (dMRM). Among the target EDCs, E2, BPA, and 4NP were detected in all water samples, with BPA being the most abundant ranging from 4.22 up to 127.96 ng/L. Correlation tests showed significant positive associations between estrogens and BPA, as well as the correlation between alkylphenols and BPA, suggesting common origin emission sources, which were identified as discharges of untreated municipal wastewater. Finally, the estimation of RQ and EEQ values indicated that the presence of E2, E3, EE2, and BPA in all sampled points represents a high risk for aquatic life in these sites, mainly for Texcuyuapan River, where the aquatic organisms may be susceptible to endocrine disruption by chronic exposure to detected compounds.

The Application of Digital PCR as a Reference Measurement Procedure to Support the Accuracy of Quality Assurance for Infectious Disease Molecular Diagnostic Testing.

Nucleic acid amplification tests (NAATs) assist in the diagnosis of numerous infectious diseases. They are typically sensitive and specific and can be quickly developed and adapted. Far more challenging is the development of standards to ensure NAATs are performing within specification; reference materials take time to develop and suitable reference measurement procedures (RMPs) have not been available. This study investigated digital PCR (dPCR) RMP delivery of traceability for NAAT external quality assessment (EQA). Three National Metrology Institutes (NMIs) applied reverse transcription (RT)-dPCR as a candidate RMP to estimate the RNA quantity in 32 independent severe acute respiratory syndrome coronavirus 2 materials. The results were combined to value assign the respective materials: 21 materials were used in 6 rounds of EQA over 17 months for 61 laboratories for COVID-19 testing results compared with reference values. The agreement between the 3 NMIs showed <2-fold difference between laboratories. EQA laboratory reverse transcription quantitative PCR (RT-qPCR) values estimation of viral RNA quantity showed good median agreement with RT-dPCR reference value; however, RT-qPCR differences were generally between 10- and 50-fold between laboratories. This work demonstrates how RT-dPCR can provide reference values for whole virus materials for NAAT quality assurance. RT-dPCR values guided EQA control material selection and provided EQA participants with traceability to RNA copy number delivered through the RMP. This approach can be used to support routine reference material use as well as to standardize quality assurance for NAATs where established reference materials are not available, such as in disease outbreaks.

Application of robust estimation methods in real estate valuation

Motives: Conducting real estate appraisals in well-developed markets presents a multitude of data analysis challenges. Some property price data may contain outliers that can significantly affect the valuation process and, as a result, the estimated value. In the case of real estate valuation regression models, estimation is most often based on the least squares method, where outliers are taken into account just like the rest of the data. Eliminating or minimizing the influence of outliers can lead to more reliable estimation results. Such problems can be solved by implementing robust regression methods. Aim: The main goal is to determine whether robust estimation methods using M-estimators with multiple regression models can provide more accurate estimates of property values. Results: Research has shown that multiple regression models using robust regression methods can be applied to estimate property values. The use of different types of M-estimators allows for the objective elimination of outliers through algorithms that operate on the entire data set. The calculations are carried out iteratively, and at each iteration step the residuals are verified and the observations are re-weighted. The following M-estimators were considered: Huber, Hampel, Tukey, Faire, Cauchy and Welsch. The reference point was the estimation results from the ordinary least squares method (OLS). All analysed M-estimators led to an increase in the coefficient of determination value and a decrease in standard estimation errors. Each algorithm detected the outliers. The valuation results for the selected properties were also more reliable. The results obtained depend on the characteristics of the data, and the choice of the best estimator may vary across different property markets. The selection of the best estimator may even vary within the same local property market, where the valuer makes subjective assessments of the location or other attributes.

Influence of Iodine Chemistry in I2 Scrubbing Modeling

With the scrubbing of molecular iodine (I2) from gas streams in water pools at an accident site (boiling water reactor wetwell, filtered containment venting systems, etc.), some discernible impact of the aqueous radiochemistry on the I2 decontamination factor (DF) is expected, sometimes with hardly any effect on aerosol scrubbing. In the frame of the NUGENIA Integration of Pool Scrubbing Research to Enhance Source-Term Calculations (IPRESCA) project, the Central Research Institute of Electric Power Industry (CRIEPI) in Japan performed a series of tests to study the I2 scrubbing behavior at high pH values, with changing pH in the course of the tests. We used these data for our simulation analyses, and we obtained sensible estimates of the experimental DF values in many calculated cases. The employed tool for our simulations was a modified version of the SPARC code inside MELCOR. This program was used for the IPRESCA benchmark parametric calculations, where the pH-dependent effect of the iodine chemistry equilibria at the bubble-water interface was predicted to be significant. The same was true for our simulations in the CRIEPI experiments. We have now modeled not just the interface equilibria, but also some slower (kinetic-driven) chemical interactions in water, which would transform, at these high pH values, most of the I2 into nonvolatile aqueous iodine species. The overall chemistry effect is quite pronounced, like in the experiments, though the description of the bubble thermal hydraulics was at least of the same importance for modeling. Many open questions remain, one of the trickiest of which being the employment of radiochemistry models (relevant to real accident conditions) for explanations of experiments driven by the normal (thermal) chemistry of iodine.

NUMERICAL-ANALYTICAL METHOD OF DECOMPOSITION-AUTOCOMPENSATION FOR SOLVING THE SIGNAL RECOGNITION PROBLEM BASED ON INACCURATE OBSERVATIONS

A numerical-analytical method is developed to solve the problem of optimal recognition of a set of possible signals observed as an additive mixture containing not only a fluctuation observation error (with an unknown statistical distribution) but also a singular interference (with parametric uncertainty). The method allows for both the detection of signals present in the mixture and the estimation of their parameters within a specified quality criterion and associated constraints. The proposed method, based on the idea of generalized invariant-unbiased estimation of linear functional values, enables decomposition of the computational procedure and autocompensation of singular interference without resorting to the traditional expansion of the state space. Linear spectral decompositions in specified functional bases are used for the parametric finite-dimensional representation of signals and interference, while knowledge of the correlation matrix of the observation error is sufficient for error description. Random and systematic errors are analyzed, and an illustrative example is provided.

Study on Fire Characteristics of Flame-Retardant Polycarbonate Under Low Pressure

This work presents experimental and numerical research on the pyrolysis and combustion characteristics of flame-retardant polycarbonate under low ambient pressure. A novel experimental low-pressure combustion platform was constructed to determine the heat release rate, a key combustion parameter of polycarbonate. The ignition process of polycarbonate under external radiation was analyzed, and an ignition time prediction model was developed. In addition, theoretical calculations of the main gas components and concentrations during the pyrolysis stage of polycarbonate and estimations of the calorific values of the combustible gas components produced during pyrolysis were carried out, providing a new explanation for the phenomenon of advancing ignition time in low-pressure environments.

A comprehensive analysis of the tail-dependent structure of wind loads and its engineering applications

Wind load field characteristics on the roof surface of low-rise buildings based on field measurements have crucial engineering guidance value. In the background, tail-dependence structure from measured wind loads can assist in modeling the joint tail distribution of multivariate wind loads. In this study, the non-parameter estimation method, multi-copula function model and multivariate peak over threshold model are applied to estimate its precise value. The upper tail dependence coefficient's value is around 0.20 when the quantile for p(y) = 0.75. When p(y) = 0.95, the Gumbel copula overestimates the tail-dependence value slightly. Additionally, the lower tail-dependence values estimated by the Clayton copula are around 0.19 at 0.25 quantile. For extreme tail-dependence coefficients, little difference exists in the estimated results by the non-parameter estimation method and the peak over threshold model, in which its value varies from 0.80 to 0.90. Under roof pitch = 5°, its value exhibits some dispersion at different locations. An area weight function is applied to estimate the extreme tail-dependence value between critical regions. Then, the expectation function of tail dependence reaches the peak value in p(x) = 0.50, p(y) = 0.50 and it has different gradients for different variables and tail regions. Additionally, the lower tail dependence structure is significantly stronger than the upper tail dependence for wind loads with negative skewness. For application in wind engineering, potential applications in risk analysis for roof structures, extreme value estimation for local region block wind load, and wind load forecast for unmonitored locations are proposed.

Bandwidth selection methods for non parametric regression with spatially correlated data

. In non parametric regression estimation, a critical and unavoidable step is to choose the smoothing parameters (bandwidth) to control the smoothness of the curve estimate. In the presence of spatially correlated errors, the traditional data-driven bandwidth selection methods, such as cross-validation and generalized cross-validation, do not work well for providing efficient bandwidth values. Moreover, the existing methods are based on estimation of correlation structure. As errors are unobservable, estimation of correlation is a big challenge. This article studies bandwidth selection methods for local linear regression (LLR) in the presence of correlated errors. For this purpose, we derive the weighted mean average square errors (WMASE) and use it along with bias-correlated generalized cross-validation (GCV) as bandwidth selection criterion. We then get the estimates of bandwidth by two ways: by minimizing the weighted mean average square errors (WMASE) and by using the bias-correlated generalized cross-validation (GCV) criterion. Due to its good properties, the composite likelihood (CL) is used to estimate the correlation. The results show that composite likelihood provides better estimates than maximum likelihood (ML) in the sense of producing more reasonable estimates of correlation parameters and bandwidth values. Also, our methods appear reasonably robust to the misspecification of the parametric correlation model. Moreover, the proposed methods work much better than ignoring the correlation and applying traditional methods. Finally, we apply our methods on water chemistry data collected about lakes in the Northeastern United States.

Inference of record failure times from unit generalized Rayleigh distribution

ABSTRACT In this paper, problems of estimation and prediction for record values are discussed for a two-parameter unit generalized Rayleigh distribution. Maximum likelihood estimators of model parameters along with their existence and uniqueness are established, and corresponding approximate confidence intervals are constructed based on asymptotic theory. In addition, alternative generalized inferential approach is provided for comparison based on the proposed pivotal quantities. Further, prediction intervals of remaining useful life are also presented under classical and generalized inferential methods when the unit generalized Rayleigh record values are available. Extensive numerical studies and two real-life examples are conducted to show the performance of the proposed methods. The results indicate that both classical and generalized estimation methods work satisfactorily and the proposed generalized inferential approach performs superior to traditional estimates in general.

Reduction of surface roughness in selectively etched microchannels in lithium niobate

By post-etching annealing, the roughness of microchannels fabricated by fs laser assisted selective etching could be reduced to values of 2 nm. The influence of inscription parameters and annealing conditions on the microchannels’ roughness and the evolution of their shape with annealing temperature and time have been investigated. A functional dependence enabling the estimation of roughness values resulting from certain processing parameters was determined. The low surface roughness achieved enables the transport of fluids with very low friction factors and optical-grade surfaces for the combination of microfluidic channels with optical waveguides, allowing the acousto-optical, electro-optical, and (nonlinear) optical properties of lithium niobate to be utilized for future monolithic optofluidic devices.

Regional calibration of the Hargreaves model for estimation of reference evapotranspiration

Abstract Estimation of reference evapotranspiration values is crucial in climatological and hydrological research, agricultural engineering, and irrigation design. The Penman-Monteith method, endorsed by the Food and Agriculture Organization (FAO) of the United Nations and numerous research studies, is widely regarded as the gold standard. However, its extensive data requirements limit its applicability in regions with sparse meteorological networks or limited measurement capabilities. The Hargreaves method, which requires only basic air temperature inputs, offers an alternative solution. The aims of this study were to calibrate the Hargreaves model for Central European climate conditions, considering altitudinal dependence, and to evaluate the temporal stability of the model parameters. In the first part of the research, we regionalized the Hargreaves coefficients using a curve-fitting method to ensure the best accuracy across 60 climatological stations in Slovakia. The regionalization of the Hargreaves coefficient improved accuracy by 10.1%, reducing the weighted absolute percentage error (WAPE) to 17.9%. However, our results showed that the accuracy of the modified Hargreaves model decreased with the increasing altitude of a climatological station. Incorporating altitude into the Hargreaves equation significantly improved model accuracy in stations at higher altitudes, providing a consistent level of accuracy across all climatological stations, regardless of their location and altitude. The results also indicated that the optimal model coefficient values change over time, showing a decreasing trend of –0.5 for the B coefficient and –0.1 for the C coefficient between the periods 1981–2000 and 2001–2020. Although regionalizing the Hargreaves model coefficients for local conditions can achieve good model performance, the model’s accuracy is not stable over time. Thus, periodic validation of the model is necessary for short-term applications.

Automated estimation of cementitious sorptivity via computer vision

Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements, as outlined in ASTM C1585. To address this issue, we introduce a custom computer vision model trained on 6234 images, consisting of 4000 real and 2234 synthetic, that automatically detects the water level in prismatic samples absorbing water. This model provides accurate and frequent estimations of water penetration values every minute. After training the model on 1440 unique data points, including 15 paste mixtures with varying water-to-cement ratios from 0.4 to 0.8 and curing periods of 1 to 7 days, we can now predict initial and secondary sorptivities in real time with high confidence, achieving R² > 0.9. Finally, we demonstrate its application on mortar and concrete systems, opening a pathway toward low-cost and automated durability assessment of construction materials.

Human Values Estimation on Articles by Extracting and Concatenating of Opinion Expressions

Human Values Estimation on Articles by Extracting and Concatenating of Opinion Expressions

Esophageal pressure as estimation of pleural pressure: a study in a model of eviscerated chest

BackgroundTranspulmonary pressure is the effective pressure across the lung parenchyma and has been proposed as a guide for mechanical ventilation. The pleural pressure is challenging to directly measure in clinical setting and esophageal manometry using esophageal balloon catheters was suggested for estimation. However, the accuracy of using esophageal pressure to estimate pleural pressure is debated due to variability in the mechanical properties of respiratory system, esophagus and esophageal catheter. Furthermore, while a vertical pleural pressure gradient exists across lung regions, esophageal pressure balloon provides a single value, representing, at most, the pressure surrounding the esophagus.MethodsIn a swine model with a preserved esophagus and a single homogenous, easily measurable intrathoracic pressure, we evaluated esophageal pressure’s agreement with intrathoracic pressure at different positive end-expiratory pressure (PEEP) levels (0, 5, 10, 15 cmH2O). We assessed the improvement of measurement accuracy by correcting absolute esophageal values using a previously described technique, that accounts for the pressure generated by the esophageal wall in response to esophageal balloon inflation.The study involved five swine, wherein two different esophageal catheters were used alongside the four distinct PEEP levels. Swings, uncorrected and corrected absolute esophageal pressures (end-inspiratory, end-expiratory) were compared with their respective intrathoracic pressures. The effect of correction technique was assessed with manual incremental step inflation procedure.ResultsWe found that both catheters significantly overestimated absolute esophageal pressure compared to intrathoracic pressure (5.01 ± 3.32 and 6.06 ± 5.62 cmH2O at end-expiration and end-inspiration, respectively), with error increasing at higher positive end-expiratory pressure levels (end-expiration: 2.36 ± 2.03, 3.77 ± 1.37, 6.24 ± 2.51 and 7.69 ± 4.02 for each PEEP level, P < 0.0001; end-inspiration: 1.71 ± 2.10, 3.70 ± 1.73, 7.67 ± 3.62 and 11.14 ± 7.60 for each PEEP level, P = 0.0004).Applying the correction technique significantly improved agreement for absolute values (0.82 ± 1.62 and 1.86 ± 3.94 cmH2O at end-expiration and end-inspiration, respectively). Esophageal pressure swings accurately estimated intrathoracic pressure swings at low-medium intrathoracic pressures (-0.64 ± 0.62, -0.07 ± 0.53, 1.43 ± 1.51, and 3.45 ± 3.94 at PEEP 0, 5, 10 and 15 cmH2O, respectively; P = 0.0197).ConclusionsThe correction technique, based on the mechanical response of esophageal wall to the balloon inflation, is fundamental for obtaining reliable estimations of absolute intrathoracic pressure values, and for ensuring its correct application in clinical setting.

ANALYSIS OF THE POSSIBILITIES OF MANUFACTURING FUNCTIONAL ELEMENTS USING THE FFF METHOD

The article presents the course and results of research aimed at assessing the strength and practical usability of a furniture hinge additively manufactured from thermoplastic material. The research activities included: development of design assumptions, adoption of target geometry, creation of a 3D-CAD model, preliminary strength analysis in the FEM environment, prototype manufacturing using FFF method with thermoplastic material (pet-g), and conducting tests under conditions similar to real ones. The hinge geometry was based on typical market-available design solutions, while considering the specifics of the adopted manufacturing method. Strength analysis via FEM was conducted on the 3D-CAD model, allowing estimation of stress values and determination of the suitability of the developed geometry for testing on a real model. Subsequently, research models were produced using FFF technology with various infill patterns: linear 30%, hexagonal 30%, linear 60%, hexagonal 60%, and solid 100%. Bench tests were conducted to determine the maximum load-bearing capacity of the hinge under perpendicular loading to the axis and to assess hinge wear under conditions simulating real-life door usage. The results revealed that the hinge with solid infill safely carried a load of 160 kg without damage, while the hinge with hexagonal 30% infill exhibited the lowest load-bearing capacity, failing at 85 kg. To determine the hinge's durability, the clearance at two reference points on the doors was measured.

Determination of geochemical stability of swamp ecosystems of the taiga zone of Western Siberia to anthropogenic impact

Relevance. The need for scientifically based regulation of impacts on wetland ecosystems taking into account their specificity and geochemical stability. Aim. To determine the geochemical stability of wetlands in the taiga zone of Western Siberia to pollutants for two typical cases associated with: 1) operation of sludge pits; 2) discharge of domestic and industrial wastewater. Methods. Mathematical modeling, statistical methods. Results and conclusions. The authors have carried out the analysis of the results of studies of the chemical composition of wetland waters and extracts from peat and mineral soils of wetlands in the taiga zone of Western Siberia (mainly in the Tomsk region, as well as in the adjacent territories of the Khanty-Mansiysk Autonomous Okrug, Novosibirsk and Omsk regions). They obtained the estimates of the average values of geochemical indicators of wetland waters and peat by the depth of the peat deposit in peat bogs with varying degrees of anthropogenic impact. The paper introduces the method for assessing the anthropogenic impact of wastewater discharge and geomigration on swamps in areas where oil and gas facilities are located (permissible concentrations in wastewater entering swamp ecosystems), taking into account the «geochemical background» and sorption capacity of peat. In particular, the authors substantiated and tested the method for assessing the values of permissible concentrations, which should be considered as a «relatively safe» level of impact on swamp ecosystems, at which secondary pollution of swamp waters is not expected. It is shown that anthropogenic changes are mainly limited vertically by the upper layer of the peat deposit up to 1–2 m, and horizontally (within the active horizon of the peat deposit) – by areas up to 100–200 m.

Comparison of Three Different IBD Vaccination Protocols in Broiler Chicken-Efficacy, Serological Baselines and Histo-Pathological Lesions in the Bursa of Fabricius.

Infectious bursal disease (IBD) is a highly infectious disease of chicken found in all latitudes, due to the very high resistance to environmental conditions and commonly used disinfectants of the IBD virus (IBDV). This study was conducted to evaluate three IBD vaccination protocols in broiler chicken in terms of their effectiveness (clinical observations and production performance of the flock), estimation of serological baseline values (with the use of two different commercial ELISA kits) and the degree of progression of BF lesions (histopathological lesion score (HLS)) after vaccination. The three protocols were (I) single vaccination using an intermediate plus vaccine, (II) double vaccination with an intermediate vaccine and (III) double vaccination with an intermediate plus vaccine. Birds on farms vaccinated with protocol II were characterized by the lowest antibody titers in both ELISA tests and the lowest average HLS. The highest IDEXX titers were obtained in birds vaccinated with protocol III, while in the BIOCHEK test the highest titers were obtained for birds vaccinated with protocol I. Protocols I and III were characterized by similar HLSs. Birds vaccinated with protocols I and III had higher immune uniformity. The estimated serological baseline values and the degree of HLSs presents a clear picture of the differences between the different vaccination protocols and allows their adaptation for different farms depending on the current IBD epidemiological situation.