Potatoes are a source of glycoalkaloids (GAs) represented primarily by alpha-solanine and alpha-chaconine (about 95%). Content of GAs in tubers is usually 10-100 mg/kg and maximum levels do not exceed 200 mg/kg. GAs can be hazardous for human health. Poisoning involve gastrointestinal ailments and neurological symptoms. A single intake of >1-3 mg/kg b.w. is considered a critical effect dose (CED). Probabilistic modelling of acute and chronic (usual) exposure to GAs was performed in the Czech Republic, Sweden and The Netherlands. National databases on individual consumption of foods, data on concentration of GAs in tubers (439 Czech and Swedish results) and processing factors were used for modelling. Results concluded that potatoes currently available at the European market may lead to acute intakes >1 mg GAs/kg b.w./day for upper tail of the intake distribution (0.01% of population) in all three countries. 50 mg GAs/kg raw unpeeled tubers ensures that at least 99.99% of the population does not exceed the CED. Estimated chronic (usual) intake in participating countries was 0.25, 0.29 and 0.56 mg/kg b.w./day (97.5% upper confidence limit). It remains unclear if the incidence of GAs poisoning is underreported or if assumptions are the worst case for extremely sensitive persons.
- MeSH
- Humans MeSH
- Eating MeSH
- Solanine analogs & derivatives analysis MeSH
- Solanum tuberosum chemistry MeSH
- Models, Statistical MeSH
- Environmental Exposure analysis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
The probabilistic two-stage model of cell killing by ionizing radiation enables to represent both damage induction by radiation and its repair by the cell. The model properties and applications as well as possible interpretation of the underlying damage classification are discussed. Analyses of published survival data for V79 hamster cells irradiated by protons and He, C, O, and Ne ions are reported, quantifying the variations in radiation quality with increasing charge and linear energy transfer of the ions.
- MeSH
- Cell Death radiation effects MeSH
- Cells radiation effects MeSH
- Financing, Organized MeSH
- Helium MeSH
- Radiation, Ionizing MeSH
- Ions MeSH
- Cricetinae MeSH
- Oxygen MeSH
- Neon MeSH
- Protons MeSH
- Models, Statistical MeSH
- Carbon MeSH
- Cell Survival radiation effects MeSH
- Animals MeSH
- Check Tag
- Cricetinae MeSH
- Animals MeSH
- MeSH
- Apoptosis radiation effects MeSH
- Models, Biological MeSH
- Cell Line MeSH
- Cricetulus MeSH
- DNA radiation effects MeSH
- Fibroblasts physiology radiation effects MeSH
- Financing, Organized MeSH
- Radiation, Ionizing MeSH
- Guinea Pigs MeSH
- Computer Simulation MeSH
- DNA Damage radiation effects MeSH
- Models, Statistical MeSH
- Cell Survival radiation effects MeSH
- Animals MeSH
- Check Tag
- Guinea Pigs MeSH
- Animals MeSH
- MeSH
- Humans MeSH
- Lung Neoplasms mortality MeSH
- Risk Factors MeSH
- Models, Statistical methods MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH
- Geographicals
- Czech Republic MeSH
Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model's confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmacophore models were proposed. Both approaches to some extent correspond to commonly used consensus approaches like the common hit approach or the one based on a logical OR operation uniting hit lists of individual models. Unlike some known approaches, the proposed ones can rank compounds retrieved by multiple models. These approaches were benchmarked on multiple ChEMBL datasets used for ligand-based pharmacophore modeling and externally validated on corresponding DUD-E datasets. The influence of complexity of pharmacophores and their performance on a calibration set on results of virtual screening was analyzed. It was shown that Max and Mean approaches have superior early enrichment to the commonly used approaches. Thus, a well-performing, easy-to-implement, and probabilistic alternative to existing approaches for pharmacophore-based virtual screening was proposed.
- MeSH
- Models, Chemical MeSH
- Pharmaceutical Preparations analysis MeSH
- Humans MeSH
- Ligands MeSH
- Molecular Conformation MeSH
- Models, Molecular MeSH
- Computer Simulation MeSH
- Drug Evaluation, Preclinical methods MeSH
- Machine Learning MeSH
- Protein Binding MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- MeSH
- Academies and Institutes history organization & administration utilization MeSH
- Bayes Theorem MeSH
- Research Support as Topic MeSH
- Financing, Organized MeSH
- Risk Assessment methods utilization MeSH
- Humans MeSH
- Monte Carlo Method MeSH
- Probability MeSH
- Air Pollution, Radioactive analysis adverse effects MeSH
- Models, Statistical MeSH
- Environmental Pollution analysis adverse effects MeSH
- Check Tag
- Humans MeSH
... Contents -- 1 Introduction 1 -- 2 Key aspects of decision modelling for economic evaluation 15 -- 3 Further ... ... developments in decision analytic models for economic evaluation 45 -- 4 Making decision models probabilistic ... ... 77 -- 5 Analysing and presenting simulation output from probabilistic models 121 -- 6 Decision-making ... ... information 165 -- 7 Efficient research design 201 -- 8 Future challenges for cost-effectiveness modelling ...
237 s. 237 s. ; cm
