1,206 research outputs found

    Using roquefortine C as a biomarker for penitrem A intoxication in a beef herd

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    Fifteen grazing beef cattle and calves presented a history of neurological signs like ataxia, intentional head tremors, muscle twitching. Nervous ketosis, nervous BVD, BHV-1,5, tremorgenic intoxication from hay, and Listeriosis were considered as differential diagnosis. Blood samples were collected. Inspection of hay bales showed large white dusty and moldy areas. Samples were taken and analyzed. Altered hay was immediately removed in all animals’ stock. No alterations were found in blood tests. Food analysis showed high concentrations of Roquefortine C (RC) (345 μg/kg DM). Tremorgenic syndrome has been reported in Penitrem A (PA) intoxication, but PA is difficult to isolate in laboratory conditions. Both RC and PA are produced by Penicillum spp. RC has been associated with PA in tremorgenic toxicosis in dogs and it might be considered a valuable diagnostic marker for PA intoxication. The neurological signs were due to tremorgenic intoxication after feeding of spoiled forage contaminated with mycotoxines

    Procjena kritičnih točaka lezija papaka u mliječnih krava: preliminarno istraživanje novog sustava bodovanja

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    Lameness is a serious animal welfare and production issue in the modern dairy herds. The development of a scoring system that is able to categorize the farm on the basis of its hazard risk level may help clinicians and farmers to identify potential issues and to reduce costs caused by lameness. The aim of this study was to develop an easy and fast score for evaluation of the structural and managerial factors potentially involved in the pathogenesis of foot lesions, and categorization of dairy farms. A total of six free-stall dairy farms were evaluated during a 3 month-period. The score developed in this study was composed of evaluation of the housing system, flooring, the farm design, the use of footbaths, the frequency of hoof trimming, and the continuing education of the employers. For each parameter, a score of 0 to 2 was assigned where the score 0 meant the least appropriate condition, the score 2 represented the best. The Farm Score showed a significant correlation with foot lesion prevalence (P = 0.0011, R2 0.94) and with the theoretical assessment of additional cost per animal (P = 0.001, R2 0.95). The significant correlation between the Farm Score, the foot lesion prevalence and the theoretical assessment of additional costs per animal may underline the potential usefulness of the score designed in this study. The Farm Score may be considered as a cheap and fast way to evaluate the hazard risk level for claw health on a dairy farm.U mliječnim je stadima hromost danas važno pitanje dobrobiti i proizvodnje životinja. Razvoj sustava bodovanja za kategorizaciju farmi na temelju razine rizika od hromosti može pomoći kliničarima, odnosno stočarima, pri utvrđivanju potencijalnih problema i smanjenju troškova uzrokovanih tom bolešću. Cilj ovog istraživanja bio je razviti jednostavan i brz sustav za procjenu strukturnih i upravljačkih čimbenika u proizvodnji koji bi mogli biti uključeni u patogenezu lezija papaka i poslužiti za kategorizaciju mliječnih farmi. Tijekom tri mjeseca istraživano je ukupno šest mliječnih farmi sa slobodnim načinom držanja. Sustav bodovanja farmi uspostavljen u ovom istraživanju uključivao je nastambe za životinje, podove, organizaciju farme, upotrebu kupki za papke, učestalost obrade papaka i kontinuiranom edukaciju zaposlenika. Svakom je pokazatelju dodijeljen bod od 0 do 2, pri čemu 0 označuje najmanje prikladno stanje, a 2 najbolje stanje. Sustav bodovanja na farmi pokazao je znakovit odnos sa prevalencijom lezija papaka (P = 0,0011, R2 0,94) kao i sa teoretskom procjenom dodatnih troškova po životinji (P = 0,001, R2 0,95). Navedeno naglašava potencijalnu korist sustava bodovanja uspostavljenog u ovom istraživanju kao jeftinog i brzog načina procjene razine rizika za zdravlje papaka na mliječnim farmama

    Multivariate factor analysis of milk fatty acid composition in relation to the somatic cell count of single udder quarters

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    The present study investigated whether the fatty acid composition of milk changes in relation to an increase in the milk somatic cell count (SCC) of separate udder quarters. We investigated the potential of multivariate factor analysis to extract metabolic evidence from data on the quantity and quality of milk of quarters characterized by different SCC levels. We collected data from individual milk samples taken from single quarters of 49 Italian Holstein cows from the same dairy farm. Factor analysis was carried out on 64 individual fatty acids. In line with a previous study on multivariate factor analysis, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. Seven factors were extracted that explained the following groups of fatty acids or functions: de novo synthesis, energy balance, uptake of dietary fatty acids, biohydrogenation, short-chain fatty acids, very long chain fatty acids, and odd- and branched-chain fatty acids. An ANOVA of factor scores highlighted the significant effects of the SCC level on de novo fatty acids and biohydrogenation. The de novo fatty acid factor decreased significantly with a high level of SCC, from just 10,000 cells/mL, whereas the biohydrogenation factor showed a significantly higher level in quarters with SCC levels greater than 400,000 cells/mL. This statistical approach enabled us to reduce the number of variables to a few latent factors with biological significance and to represent groups of fatty acids with a common origin and function. Multivariate factor analysis could therefore be key to studying the influence of SCC on the lipid metabolism of single quarters. This approach also demonstrated the metabolic differences between quarters of the same animal showing a different level of SCC

    Stable and actionable explanations of black-box models through factual and counterfactual rules

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    Recent years have witnessed the rise of accurate but obscure classification models that hide the logic of their internal decision processes. Explaining the decision taken by a black-box classifier on a specific input instance is therefore of striking interest. We propose a local rule-based model-agnostic explanation method providing stable and actionable explanations. An explanation consists of a factual logic rule, stating the reasons for the black-box decision, and a set of actionable counterfactual logic rules, proactively suggesting the changes in the instance that lead to a different outcome. Explanations are computed from a decision tree that mimics the behavior of the black-box locally to the instance to explain. The decision tree is obtained through a bagging-like approach that favors stability and fidelity: first, an ensemble of decision trees is learned from neighborhoods of the instance under investigation; then, the ensemble is merged into a single decision tree. Neighbor instances are synthetically generated through a genetic algorithm whose fitness function is driven by the black-box behavior. Experiments show that the proposed method advances the state-of-the-art towards a comprehensive approach that successfully covers stability and actionability of factual and counterfactual explanations

    Designing statistical models for holstein rearing heifers’ weight estimation from birth to 15 months old using body measurements

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    Body measurements could be used to estimate body weight (BW) with no need for a scale. The aim was to estimate heifers weight based on their body dimension characteristics. Twenty-five Holstein heifers represent the study group (SG); another 13 animals were evaluated as a validation group (VG). All the heifers were weighed (BW) and their wither height (WH), shin circumference (SC), heart girth circumference (HG), body length (BL), hip width (HW) and body condition score (BCS) were measured immediately after birth, and then weekly until 2 months and monthly until 15 months old. Equations were built with a stepwise regression in order to estimate the BW at each time using body measures for the SG. A linear regression was applied to evaluate the relationship between the estimated BW and the real BW. Equations found were to be statistically significant (r2 = 0.688 to 0.894; p < 0.0001). Three variables or fewer were needed for BW estimation a total of 11/23 times. Regression analysis indicated that the use of HG was promising in all the equations built for BW estimation. These models were feasible in the field; further studies will evaluate possible modifications to our equations based on different growing rate targets

    Hepatic adrenal rest tumor in a patient with multifactorial liver cirrhosis: a case report with CT and MRI findings and pathologic correlation

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    AbstractBackgroundAdrenal rest tumor is an ectopic collection of adrenocortical cells in an extra-adrenal site, more frequently located around the kidney, retroperitoneum, spermatic cord, para-testicular region and broad ligament, but very rarely occurring also in the liver. Hepatic adrenal rest tumor poses a diagnostic challenge in differentiating it from hepatocellular carcinoma, particularly in a cirrhotic liver.Case presentationAn 83-years-old male was referred to our hospital by his family doctor for hepatological evaluation due to multifactorial liver cirrhosis. Ultrasound revealed a centimetric hypoechoic nodule in the VI hepatic segment in the context of a liver with signs of cirrhosis and steatosis. The patient first underwent MRI and then CT, which showed a fat containing focal liver lesion in the subcapsular location of the right lobe, strictly adjacent to the homolateral adrenal gland. The nodule was hypervascular in the arterial phase, washed out in the portal-venous and transitional phases, resulting hypointense in the hepato-biliary phase at MR imaging. In the suspicion of a hepatocellular carcinoma, the nodule was surgically removed, and the patient's postoperative course was unremarkable. The final histopathological diagnosis was of adrenal rest tumor of the liver.ConclusionsHepatic adrenal rest tumor is an extremely rare hepatic tumor, often without any clinical manifestation, that can also occur in the cirrhotic liver as in our case. Although there are not specific imaging findings, the possible diagnosis of HART should be considered when we observe a well-defined lesion in the subcapsular location of the right lobe, with fat containing, hypervascularity after contrast medium injection and vascular supply from the right hepatic artery

    Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

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    Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.

    MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

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    Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

    Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

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    The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe

    Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

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    A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe
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