scholarly journals The New Model of Carcinogenic Activity of Polycyclic Hydrocarbons

2021 ◽  
Vol 18 ◽  
pp. 150-169
Author(s):  
Vladimir K. Mukhomorov
Keyword(s):  
Chemical Compounds ◽  
Carcinogenic Activity ◽  
Polycyclic Hydrocarbons ◽  
Polycyclic Compounds ◽  
New Model ◽  
Explanatory Variables ◽  
Observable Data

A model is proposed that allows one to interpret the carcinogenic properties of polycyclic chemical compounds. Electronic, informational and structural molecular factors that characterize the molecule as a whole are proposed as explanatory variables. The factors limiting the carcinogenic activity of polycyclic compounds are analyzed. The model fully interprets all observable data that were used to support previous early models

Size and carcinogenic activity of the polycyclic hydrocarbons

1955 ◽  
Vol 42 (22) ◽  
pp. 608-608 ◽  
Author(s):  
Joseph C. Arcos ◽  
Martha Arcos
Keyword(s):  
Carcinogenic Activity ◽  
Polycyclic Hydrocarbons

scholarly journals A New Model For Predicting Boiling Points of Alkanes

2021 ◽  
Author(s):  
Simon Mukwembi ◽  
Farai Nyabadza
Keyword(s):  
Experimental Data ◽  
Boiling Point ◽  
Chemical Compounds ◽  
Single Parameter ◽  
New Model ◽  
Boiling Points ◽  
Lubricant Performance

Abstract A general perception among researchers is that boiling points, which is a key property in the optimization of lubricant performance, are difficult to predict successfully using a single-parameter model [5, 6]. In this contribution, we propose a new graph parameter which we call, for lack of better terminology , the conduction of a graph. We exploit the conduction of a graph to develop a single-parameter model for predicting the boiling point of any given alkane. The accuracy of our model compares favourably to the accuracy of experimental data in literature. Our results have significant implications on the estimation of boiling points of chemical compounds in the absence of experimental data.

A New Model for Predicting Behavioral Intentions: An Alternative to Fishbein

1980 ◽  
Vol 17 (2) ◽  
pp. 153-172 ◽  
Author(s):  
Paul R. Warshaw
Keyword(s):  
Behavioral Intentions ◽  
High Stability ◽  
New Model ◽  
Explanatory Variables ◽  
Independent Variables ◽  
Equal Concern

The Fishbein intention model often produces weak and inconsistent predictions in marketing applications. Of equal concern, high multicollinearity between independent variables is typical. A new intention model was developed and tested. Results show high stability, reliability, and predictiveness across diverse test products, with very low intercorrelations between explanatory variables.

scholarly journals Increase of efficiency of QSAR — the analysis of carcinogenic activity of halogeneted hydrocarbons

2005 ◽  
Vol 3 (2) ◽  
pp. 5-14
Author(s):  
Aleksey V Tarasov ◽  
Serikbay K Abilev ◽  
Ramis M Velibekov ◽  
Valentin A Tarasov
Keyword(s):  
Biological Activity ◽  
Computer Program ◽  
Chemical Compounds ◽  
Carcinogenic Activity ◽  
Structural Descriptors ◽  
Selection Of

The new principle of analysis of structureactivity of carcinogenic compounds is offered. It is basis on use a compound structural descriptors representing a combination untied among themselves of structural fragments of a molecule. The computer program is developed, allowing to generate every possible structural fragments of molecules of chemical compounds and their  combinations and to carry out selection of the compound descriptors statistically significantly influencing their biological activity. In work it is used the samples consisting of 89 halogeneted hydrocarbons for which their carcinogenic activity on rodents is investigated.

scholarly journals Validation of a spatial liver fluke model under field conditions in Ireland

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Amalia Naranjo Lucena ◽  
María Pía Munita Corbalán ◽  
Ana María Martínez-Ibeas ◽  
Guy McGrath ◽  
Riona Sayers ◽  
...  
Keyword(s):  
Risk Factors ◽  
Predictive Value ◽  
Liver Fluke ◽  
Fasciola Hepatica ◽  
Vegetation Indices ◽  
Baseline Risk ◽  
New Model ◽  
Explanatory Variables ◽  
Wide Range ◽  
Fluke Infection

Fasciola hepatica is the causative agent of fasciolosis, a global disease of a wide range of mammals, particularly sheep and cattle. Liver fluke infection causes annual losses estimated at around €2.5 billion to livestock and food industries worldwide. Various models have been developed to define risk factors and predict exposure to this liver fluke in ruminants in European countries, most of them based exclusively on data from dairy herds. The aim of this study was to validate a published theoretical baseline risk map of liver fluke exposure and cluster maps in Ireland, by including further explanatory variables and additional herd types that are spatially more widespread. Three approaches were employed: i) comparison of predicted and actual exposure; ii) comparison of cluster distribution of hotspots and coldspots; and iii) development of a new model to compare predicted spatial distribution and risk factors. Based on new survey data, the published baseline predictive map was found to have a sensitivity of 94.7%, a specificity of 5%, a positive predictive value of 60% and a negative predictive value of 38.2%. In agreement with the original model, our validation highlighted temperature and rainfall among the main risk factors. In addition, we identified vegetation indices as important risk factors. Both the previously published and our new model predict that exposure to Fasciola is higher in the western parts of Ireland. However, foci of high probability do not match completely, nor do the location of clusters of hotspots and coldspots.

scholarly journals The Unique Australian Flora, A Veritable Pandora’s Pharmacopeia of Compounds with Therapeutic Biomedical Potential: Are the Chalcones the Geni in The Box?

2021 ◽  
pp. 77-97
Author(s):  
James Melrose
Keyword(s):  
Medicinal Chemistry ◽  
Chemical Compounds ◽  
Climatic Conditions ◽  
Flowering Plants ◽  
Full Spectrum ◽  
Polycyclic Compounds ◽  
Australian Continent ◽  
Australian Flora ◽  
Biomedical Potential ◽  
Large Repertoire

The aim of this review was to highlight the unique biodiversity of the flowering plants and shrubs of Australia and their component chemicals that evolved during the separation of the Australian continent from Gondwanaland. The chemicals produced by these flowering plants provided protection ensuring the survival of the Australian flora which had to contend with often harsh Australian climatic conditions. The diversity of plant phytochemicals produced by these flowering plants reflects the unique diversity of the Australian Flora and these represent a Pharmacological goldmine. It was beyond the scope of this review to cover the full spectrum of these chemical compounds present in Australian plants instead we focused on the chalcones in this review. This compound has a special status in medicinal chemistry as a base intermediate for the synthesis of a large repertoire of polycyclic compounds that display anti-bacterial, antifungal, anti-viral and anti-tumour properties and these are thus of considerable interest in Biomedicine.

scholarly journals A new model for predicting boiling points of alkanes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Mukwembi ◽  
Farai Nyabadza
Keyword(s):  
Experimental Data ◽  
Test Data ◽  
Boiling Point ◽  
Chemical Compounds ◽  
Single Parameter ◽  
Coefficient Of Determination ◽  
New Model ◽  
Boiling Points ◽  
Lubricant Performance

AbstractA general perception among researchers is that boiling points, which is a key property in the optimization of lubricant performance, are difficult to predict successfully using a single-parameter model. In this contribution, we propose a new graph parameter which we call, for lack of better terminology, the conduction of a graph. We exploit the conduction of a graph to develop a single-parameter model for predicting the boiling point of any given alkane. The model was used to predict the boiling points for three sets of test data and predicted with a coefficient of determination, $$R^2=0.7516,~0.7898$$ R 2 = 0.7516 , 0.7898 and 0.6488, respectively. The accuracy of our model compares favourably to the accuracy of experimental data in the literature. Our results have significant implications on the estimation of boiling points of chemical compounds in the absence of experimental data.

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