1,721,014 research outputs found
Identification of a mitochondrial inhibitor of rat liver L-threonine dehydrogenase
No full textIn a previous paper, we showed inhibition of rat liver L-threonine dehydrogenase by a preparation obtained by dialysis and concentration from rat liver mitochondria stored at -20 degrees C for 7-10 days (Pagani, R., Leoncini, R., Guerranti, R. and Marinello, E. (1990) It. J. Biochem. 39, 106-114). The chemical composition of the fraction containing the unknown 'inhibitor' has now been studied and identified as D-3-hydroxybutyrate (D3HB)
Introduction to Big Data and Artificial Intelligence in Laboratory Medicine
No full textCurrently, thanks to the growing computing capacity and the increasing availability of digital data, Data Science is playing an important role in the future development of Laboratory Medicine. However, the concepts of Big Data (BD) and Artificial Intelligence (AI) can still be interpreted in various ways. Clinical laboratories are certainly among the health care organizations producing an important number of data that can be considered BD and it is certainly not a coincidence that they are among the first health organizations to have implemented computer systems within their workflows. Through a process called Data Mining it is possible to extract useful information from BD using automatic or semi-automatic methods that must be preceded by Data Cleaning in order to ensure the cleanliness and correctness of the data themself. Regarding Data Analysis, several Machine Learning or Deep Learning techniques based on different algorithms or on the functioning principle of neural networks can be used; for the development of these techniques, R and Python programming languages are really useful. Although many applications can be useful in Laboratory Medicine, there are still some obstacles to overcome, including poor harmonization of data or fragmentation of sources; moreover, the issue of data accessibility must be managed considering patient's privacy as a priority. Finally, there is an increase apprehension related to the awareness of the inevitable innovation in the Laboratory Medicine field in the near future, because of these new approaches. To face these challenges, it is necessary that these topics become familiar to the professionals of Laboratory Medicine. Aim of this Document is to share information about BD and AI in order to contribute to the introduction and development of these methodologies in the field of Laboratory Medicine
Protein sequential fractionation based on solubility criteria of protein bodies isolated from Mucuna pruriens L.DC. seeds
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FMECA e business analytics software, due strumenti per la gestione di un processo critico in un CoreLab: analisi del mismatch provetta-etichetta FMECA and business analytics software, two instruments for the management of a critical process in CoreLab: test tube-label mismatch.
No full textActivation and inhibition of rat liver L-threonine dehydrogenase
No full textWe have studied some characteristics of mitochondrial rat liver L-threonine dehydrogenase during freezing: the enzyme shows a net increase in activity and a "shift" in the pH optimum after storage at -20 degrees C of mitochondrial preparations. An unknown effector, which inhibited significantly the dehydrogenase activity, was isolated from the same preparations kept for 7-10 days at -20 degrees C. Some properties of the inhibitor have been determined
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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