4 research outputs found

    Severity scoring of manganese health effects for categorical regression

    Get PDF
    Characterizing the U-shaped exposure response relationship for manganese (Mn) is necessary for estimating the risk of adverse health from Mn toxicity due to excess or deficiency. Categorical regression has emerged as a powerful tool for exposure-response analysis because of its ability to synthesize relevant information across multiple studies and species into a single integrated analysis of all relevant data. This paper documents the development of a database on Mn toxicity designed to support the application of categorical regression techniques. Specifically, we describe (i) the conduct of a systematic search of the literature on Mn toxicity to gather data appropriate for dose-response assessment; (ii) the establishment of inclusion/exclusion criteria for data to be included in the categorical regression modeling database; (iii) the development of a categorical severity scoring matrix for Mn health effects to permit the inclusion of diverse health outcomes in a single categorical regression analysis using the severity score as the outcome variable; and (iv) the convening of an international expert panel to both review the severity scoring matrix and assign severity scores to health outcomes observed in studies (including case reports, epidemiological investigations, and in vivo experimental studies) selected for inclusion in the categorical regression database. Exposure information including route, concentration, duration, health endpoint(s), and characteristics of the exposed population was abstracted from included studies and stored in a computerized manganese database (MnDB), providing a comprehensive repository of exposure-response information with the ability to support categorical regression modeling of oral exposure data

    Motivation-Value Component of FirstYear Student’s Subjectivity

    No full text
    This article discusses one of the main components of subjectivity of a university student. According to the research, that is a motivation-value one. It presupposes the presence of a sustain motivation of the subject, leading to active educational and cognitive activity with elements of creativity. On the condition of cognitive activity based on the true interest students can get new knowledge and professional interest. Thus, we distinguish the following criteria of this component: awareness in the choice of profession, interest in educational and cognitive activity, stable professional motivation, aspiration for creative, professional self-realization. It has a pronounced focus on professional and personal development. The article reveals the problem of cognitive and professional motivation of first-year students, as well as ways of their development. Particular attention is paid to a pedagogical interaction process that is based on pedagogical support (facilitation) and is aimed at revealing and realizing the student’s personal potential, expanding his/her cognitive and professional interests and needs

    Motivation-Value Component of FirstYear Student’s Subjectivity

    No full text
    This article discusses one of the main components of subjectivity of a university student. According to the research, that is a motivation-value one. It presupposes the presence of a sustain motivation of the subject, leading to active educational and cognitive activity with elements of creativity. On the condition of cognitive activity based on the true interest students can get new knowledge and professional interest. Thus, we distinguish the following criteria of this component: awareness in the choice of profession, interest in educational and cognitive activity, stable professional motivation, aspiration for creative, professional self-realization. It has a pronounced focus on professional and personal development. The article reveals the problem of cognitive and professional motivation of first-year students, as well as ways of their development. Particular attention is paid to a pedagogical interaction process that is based on pedagogical support (facilitation) and is aimed at revealing and realizing the student’s personal potential, expanding his/her cognitive and professional interests and needs

    Modeling U-shaped dose-response curves for manganese using categorical regression

    No full text
    Introduction: Manganese is an essential nutrient which can cause adverse effects if ingested to excess or in insufficient amounts, leading to a U-shaped exposure-response relationship. Methods have recently been developed to describe such relationships by simultaneously modeling the exposure-response curves for excess and deficiency. These methods incorporate information from studies with diverse adverse health outcomes within the same analysis by assigning severity scores to achieve a common response metric for exposure-response modeling. Objective: We aimed to provide an estimate of the optimal dietary intake of manganese to balance adverse effects from deficient or excess intake. Methods: We undertook a systematic review of the literature from 1930 to 2013 and extracted information on adverse effects from manganese deficiency and excess to create a database on manganese toxicity following oral exposure. Although data were available for seven different species, only the data from rats was sufficiently comprehensive to support analytical modelling. The toxicological outcomes were standardized on an 18-point severity scale, allowing for a common analysis of all available toxicological data. Logistic regression modelling was used to simultaneously estimate the exposure-response profile for dietary deficiency and excess for manganese and generate a U-shaped exposure-response curve for all outcomes. Results: Data were available on the adverse effects of 6113 rats. The nadir of the U-shaped joint response curve occurred at a manganese intake of 2.70. mg/kg. bw/day with a 95% confidence interval of 2.51-3.02. The extremes of both deficient and excess intake were associated with a 90% probability of some measurable adverse event. Conclusion: The manganese database supports estimation of optimal intake based on combining information on adverse effects from systematic review of published experiments. There is a need for more studies on humans. Translation of our results from r
    corecore