Statistical assessment of feeding corn with higher oil content to piglets in the starter phase

The aim of this study was to assess the digestibility coefficients (DC) of corn [maize] with an oil content above 3.46% and its effects on the performance of piglets when fed as dry grain (DG) and as rehydrated corn grain silage (RCGS). In Experiment I, 15 piglets (22.51 + 2.39 kg) were allocated to a reference diet (RD) and to two test diets in which corn in the RD was replaced with DG or RCGS. There were five replications of each treatment. Experiment II involved 36 piglets (14.76 ± 2.72 kg), which were assigned to a control diet with common corn grain and to diets in which DG or RCGS replaced the common corn. There were six replications of each treatment. Data were analysed with four statistical models. Model 1 included only the effect of treatment. Model 2 was similar to Model 1 but included initial bodyweight as a covariate. Model 3 was similar to model 1 but included the interaction of diet and period. Model 4 was similar to Model 3 but included the covariate. The more complicated models were generally preferred to Model 1 as they controlled more of the nuisance variation. Feeding a diet that contained RCGS reduced feed intake and improved feed conversion ratio (FCR)

Reusing a declarative specification to check the conformance of different CIGs

Several Computer Interpretable Guidelines (CIGs) languages have been proposed by the health community. Even though these CIG languages share common ideas each language has to be provided with his own mechanism of verification. In an earlier work we have shown that a DECLARE model can be used for checking the conformance of a PROforma CIG. In this paper, we show that the same model can also be used for checking the conformance of a similar CIG expressed in the GLIF language. Besides, as the GLIF model has been expressed in terms of a Coloured Petri Net (CPN), we also elaborate on the experiences obtained when applying the model checking techniques supported by CPN tools

Semantic-based conformance checking of computer interpretable medical guidelines

Medical recommendations are generally expressed in natural language and therefore their ambiguity can lead to miss interpretations and medical errors. In this paper we propose an approach to 1) disambiguate medical recommendations by specifying them in a declarative language and 2) check the conformance of Computer Interpretable Guidelines (CIGs) with respect to the declarative specification of the medical recommendations. Our approach is based on semantic process mining techniques. Furthermore, we explain two ways to further exploit the information provided by the semantic conformance checker. To increase the accuracy of the model checker we suggest medical scenarios that were not considered for the enactment of the CIG and could show a violation of the medical constraints. Moreover, we discover scenarios which were not covered by the CIG but were considered for the medical recommendations

Argumentation-logic for creating and explaining medical hypotheses

<p>Objective: While EIRA has proved to be successful in the detection of anomalous patient responses to treatments in the Intensive Care Unit, it could not describe to clinicians the rationales behind the anomalous detections. The aim of this paper is to address this problem.</p> <p>Methods: Few attempts have been made in the past to build knowledge-based medical systems that possess both argumentation and explanation capabilities. Here we propose an approach based on Dung's seminal calculus of opposition.</p> <p>Results: We have developed a new tool, arguEIRA, which is an extension of the existing EIRA system. In this paper we extend EIRA by providing it with an argumentation-based justification system that formalizes and communicates to the clinicians the reasons why a patient response is anomalous.</p> <p>Conclusion: Our comparative evaluation of the EIRA system against the newly developed tool highlights the multiple benefits that the use of argumentation-logic can bring to the field of medical decision support and explanation.</p&gt

The vesicular acetylcholine transporter is present in melanocytes and keratinocytes in the human epidermis

NoThe human epidermis holds the full machinery for cholinergic signal transduction. However, the presence of the vesicular transporter (vesicular acetylcholine (ACh) transporter (VAChT)) for both choline and ACh has never been shown in this compartment. The results of this study confirm the presence of VAChT in cutaneous nerves and in both epidermal melanocytes and keratinocytes as well as in their nuclei using immunofluorescence labelling in situ and in vitro, Western blot analysis of cellular and nuclear extracts and reverse transcription-PCR. These results underline that ACh/choline transport in the non-neuronal epidermis is no different from the neuronal pathway. However, the function of VAChT in the nucleus remains to be shown

Formalizing and Understanding Collaborative Decision Making in the Intensive Care Unit (ICU)

No abstract available

Semantic-based conformance checking of computer interpretable medical guidelines

Medical recommendations are generally expressed in natural language and therefore their ambiguity can lead to miss interpretations and medical errors. In this paper we propose an approach to 1) disambiguate medical recommendations by specifying them in a declarative language and 2) check the conformance of Computer Interpretable Guidelines (CIGs) with respect to the declarative specification of the medical recommendations. Our approach is based on semantic process mining techniques. Furthermore, we explain two ways to further exploit the information provided by the semantic conformance checker. To increase the accuracy of the model checker we suggest medical scenarios that were not considered for the enactment of the CIG and could show a violation of the medical constraints. Moreover, we discover scenarios which were not covered by the CIG but were considered for the medical recommendations

Reusing a declarative specification to check the conformance of different CIGs

Several Computer Interpretable Guidelines (CIGs) languages have been proposed by the health community. Even though these CIG languages share common ideas each language has to be provided with his own mechanism of verification. In an earlier work we have shown that a DECLARE model can be used for checking the conformance of a PROforma CIG. In this paper, we show that the same model can also be used for checking the conformance of a similar CIG expressed in the GLIF language. Besides, as the GLIF model has been expressed in terms of a Coloured Petri Net (CPN), we also elaborate on the experiences obtained when applying the model checking techniques supported by CPN tools