Development and prevalidation of a list of structure-activity relationship rules to be used in expert systems for prediction of the skin-sensitising properties of chemicals

The new European Union (EU) chemicals policy, as described in the White Paper entitled Strategy for a Future Chemicals Policy, has identified a need for computer-based tools suitable for predicting the hazardous properties of chemicals. Two sets of structural alerts (fragments of chemical structure) for the prediction of skin sensitisation hazard classification ("R43, may cause sensitisation by skin contact") have been drawn up, based on sensitising chemicals from a regulatory database (containing data for the EU notification of new chemicals). These alerts comprise 15 rules for chemical structures deemed to be sensitising by direct action of the chemicals with cells or proteins within the skin, and three rules for substructures that act indirectly, i.e. requiring chemical or biochemical transformation. The predictivity rates of the rules were found to be good (positive predictivity, 88%; false-positive rate, 1%; specificity, 99%; negative predictivity, 74%; false-negative rate, 80%; sensitivity, 20%). Because of the confidential nature of the regulatory database, the rules are supported by examples of sensitising chemicals taken from the "Allergenliste" now held by the Federal Institute for Risk Assessment (BfR) and the DEREK for Windows expert system. The rules were prevalidated against data not used for their development. As a result of the prevalidation study, it is proposed that the two sets of structural alerts should be taken forward for formal validation, with a view to incorporating them into regulatory guidelines.     

Biobanking and international interoperability: samples

In terms of sample exchange, international collaborations between biobanks, or between biobanks and their research partners, have two important aspects. First, the donors’ consent usually implies that the scope and purpose of any sample transfer to third parties is subject to major constraints. Since the legal, ethical and political framework of biobanking may differ substantially, even between countries of comparable jurisdictional systems, general rules for the international sharing of biomaterial are difficult, if not impossible, to define. Issues of uncertainty include the right to transfer the material, the scope of research allowed, and intellectual property rights. Since suitable means of international law enforcement may not be available in the context of biobanking, collaborators are advised to clarify any residual uncertainty by means of bilateral contracts, for example, in the form of material transfer agreements. Second, biobank partners may rightly expect that the biomaterial they receive for further analysis attains a certain level of quality. This implies that a biobank has to implement stringent quality control measures covering, in addition to the material transfer itself, the whole process of material acquisition, transport, pre-analytical handling and storage. Again, it may be advisable for biobank partners to claim contractual warranties for the type and quality of the biomaterial they wish to acquire.     

Tackling the toxics in plastics packaging

The widespread use of plastic packaging for storing, transporting, and conveniently preparing or serving foodstuffs is significantly contributing to the global plastic pollution crisis. This has led to many efforts directed toward amending plastic packaging’s end of life, such as recycling, or alternative material approaches, like increasingly using paper for food packaging. But these approaches often neglect the critical issue of chemical migration: When contacting foodstuffs, chemicals that are present in packaging transfer into food and thus unwittingly become part of the human diet. Hazardous chemicals, such as endocrine disrupters, carcinogens, or substances that bioaccumulate, are collectively referred to as “chemicals of concern.” They can transfer from plastic packaging into food, together with other unknown or toxicologically uncharacterized chemicals. This chemical transfer is scientifically undisputed and makes plastic packaging a known, and avoidable, source of human exposure to synthetic, hazardous, and untested chemicals. Here, I discuss this issue and highlight aspects in need of improvement, namely the way that chemicals present in food packaging are assessed for toxicity. Further, I provide an outlook on how chemical contamination from food packaging could be addressed in the future. Robust innovations must attempt systemic change and tackle the issue of plastic pollution and chemical migration in a way that integrates all existing knowledge.

The widespread use of plastic packaging for storing, transporting, and conveniently preparing or serving foodstuffs is significantly contributing to the global plastic pollution crisis. This Essay exhorts us to change the conversation about plastic packaging and address the chemicals that migrate into food.     

A computational study of synaptic mechanisms of partial memory transfer in cerebellar vestibulo-ocular-reflex learning

There is a debate regarding whether motor memory is stored in the cerebellar cortex, or the cerebellar nuclei, or both. Memory may be acquired in the cortex and then be transferred to the cerebellar nuclei. Based on a dynamical system modeling with a minimal set of variables, we theoretically investigated possible mechanisms of memory transfer and consolidation in the context of vestibulo-ocular reflex learning. We tested different plasticity rules for synapses in the cerebellar nuclei and took robustness of behavior against parameter variation as the criterion of plausibility of a model variant. In the most plausible scenarios, mossy-fiber nucleus-neuron synapses or Purkinje-cell nucleus-neuron synapses are plastic on a slow time scale and store permanent memory, whose content is passed from the cerebellar cortex storing transient memory. In these scenarios, synaptic strengths are potentiated when the mossy-fiber afferents to the nuclei are active during a pause in Purkinje-cell activities. Furthermore, assuming that mossy fibers create a limited variety of signals compared to parallel fibers, our model shows partial memory transfer from the cortex to the nuclei.     

A deductive method of haplotype analysis in pedigrees.

Derivation of haplotypes from pedigree data by means of likelihood techniques requires large computational resources and is thus highly limited in terms of the complexity of problems that can be analyzed. The present paper presents 20 rules of logic that are both necessary and sufficient for deriving haplotypes by means of nonstatistical techniques. As a result, automated haplotype analysis that uses these rules is fast and efficient, requiring computer memory that increases only linearly (rather than exponentially) with family size and the number of factors under analysis. Some error analysis is also possible. The rules are completely general with regard to any system of completely linked, discrete genetic markers that are autosomally inherited. There are no limitations on pedigree structure or the amount of missing data, although the existence of incomplete data usually reduces the fraction of haplotypes that can be completely determined.     

A Model for Transfer of P-Glycoproteins in MCF-7 Breast Cancer Cell Line with Multiple Transfer Rules

In this paper, we consider a direct protein transfer process between cells in co-culture. Assuming that cells continually encounter each other, and from some hypotheses on cell-to-cell rules of transfer, we derive discrete and continuous Boltzmann-like integro-differential equations. The novelty of this model is to take into account multiple transfer rules. This new transfer model is used to fit the experimental data of cell-to-cell protein transfer in breast cancer.     

Improving the reliability of chemical manufacturing life cycle inventory constructed using secondary data

This study proposes methods to improve data mining workflows for modeling chemical manufacturing life cycle inventory. Secondary data sources can provide valuable information about environmental releases during chemical manufacturing. However, the often facility‐level nature of the data challenges their utility for modeling specific processes and can impact the quality of the resulting inventory. First, a thorough data source analysis is performed to establish data quality scoring and create filtering rules to resolve data selection issues when source and species overlaps arise. A method is then introduced to develop context‐based filter rules that leverage process metadata within data sources to improve how facility air releases are attributed to specific processes and increase the technological correlation and completeness of the inventory. Finally, a sanitization method is demonstrated to improve data quality by minimizing the exclusion of confidential business information (CBI). The viability of the methods is explored using case studies of cumene and sodium hydroxide production in the United States. The attribution of air releases using process context enables more sophisticated filtering to remove unnecessary flows from the inventory. The ability to sanitize and incorporate CBI is promising because it increases the sample size, and therefore representativeness, when constructing geographically averaged inventories. Future work will focus on expanding the application of context‐based data filtering to other types and sources of environmental data.     

Barley lipid transfer protein, LTP1, contains a new type of lipid-like post-translational modification.

In plants a group of proteins termed nonspecific lipid transfer proteins are found. These proteins bind and catalyze transfer of lipids in vitro, but their in vivo function is unknown. They have been suggested to be involved in different aspects of plant physiology and cell biology, including the formation of cutin and involvement in stress and pathogen responses, but there is yet no direct demonstration of an in vivo function. We have found and characterized a novel post-translational modification of the barley nonspecific lipid transfer protein, LTP1. The protein-modification bond is of a new type in which an aspartic acid in LTP1 is bound to the modification through what most likely is an ester bond. The chemical structure of the modification has been characterized by means of two-dimensional homo- and heteronuclear nuclear magnetic resonance spectroscopy as well as mass spectrometry and is found to be lipid-like in nature. The modification does not resemble any standard lipid post-translational modification but is similar to a compound with known antimicrobial activity.     

Determination of the fractal dimension of membrane protein aggregates using fluorescence energy transfer.

It is demonstrated that fluorescence resonance energy transfer may be used to determine the fractal dimension of aggregates of membrane-bound proteins. Theoretical and experimental results are presented for two different experimental designs: energy transfer between proteins and energy transfer from lipids to proteins. For energy transfer between proteins the lattice spacing must be known independently for a fractal dimension to be uniquely determined, and this represents a disadvantage to this experimental design. Results are presented for the calcium ATPase and a fractal dimension of 1.9 is estimated for ATPase aggregates by assuming a lattice spacing of 50 A. Energy transfer from lipids to protein provides a means of estimating the length of the "coast-line" of the aggregate. In this case the fractal dimension is uniquely determined from a log-log plot. An analysis of data for bacteriohodopsin reconstituted in phospholipid vesicles gives a fractal dimension of 1.6. The structural basis of the value for the fractal dimension is discussed for these two systems. These techniques provide a means of assessing the nature of protein-protein interactions in membranous systems.     

Sequential spiking neural P systems with exhaustive use of rules

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes, where neurons work in parallel in the sense that each neuron that can fire should fire, but the work in each neuron is sequential in the sense that at most one rule can be applied at each computation step. In this work, we consider SN P systems with the restriction that at most one neuron can fire at each step, and each neuron works in an exhaustive manner (a kind of local parallelism - an applicable rule in a neuron is used as many times as possible). Such SN P systems are called sequential SN P systems with exhaustive use of rules. The computation power of sequential SN P systems with exhaustive use of rules is investigated. Specifically, characterizations of Turing computability and of semilinear sets of numbers are obtained, as well as a strict superclass of semilinear sets is generated. The results show that the computation power of sequential SN P systems with exhaustive use of rules is closely related with the types of spiking rules in neurons.     

Prediction of peptide structure: How far are we?

Rational design of peptides is a challenge, which would benefit from a better knowledge of the rules of sequence-structure-function relationships. Peptide structures can be approached by spectroscopy and NMR techniques but data from these approaches too frequently diverge. Structures can also be calculated in silico from primary sequence information using three algorithms: Pepstr, Robetta, and PepLook. The most recent algorithm, PepLook introduces indexes for evaluating structural polymorphism and stability. For peptides with converging experimental data, calculated structures from PepLook and, to a lesser extent from Pepstr, are close to NMR models. The PepLook index for polymorphism is low and the index for stability points out possible binding sites. For peptides with divergent experimental data, calculated and NMR structures can be similar or, can be different. These differences are apparently due to polymorphism and to different conditions of structure assays and calculations. The PepLook index for polymorphism maps the fragments encoding disorder. This should provide new means for the rational design of peptides.     

Spike timing dependent synaptic plasticity in biological systems

 Association of a presynaptic spike with a postsynaptic spike can lead to changes in synaptic efficacy that are highly dependent on the relative timing of the pre- and postsynaptic spikes. Different synapses show varying forms of such spike-timing dependent learning rules. This review describes these different rules, the cellular mechanisms that may be responsible for them, and the computational consequences of these rules for information processing and storage in the nervous system. Received: 16 January 2002 / Accepted: 3 June 2002 Acknowledgements. This research is supported in part by a National Science Foundation grant IBN 98-08887 (awarded to PDR), and by National Institutes of Health grants R01-MH49792 (awarded to CCB), R01-MH60996 (awarded to CCB), and R01-MH60996 (awarded to PDR). Correspondence to: P. D. Roberts (e-mail: robertpa@ohsu.edu)     

Mining Rare Associations between Biological Ontologies

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.     

Collagen lattice effects on fibroblast arachidonic acid metabolism

Fibroblasts are routinely maintained in vitro on tissue culture plastic, in an environment which is devoid of collagen, the most abundant extracellular protein in dermis. Recent work has shown that by seeding fibroblasts into a collagen matrix, many aspects of their metabolism change dramatically: they stop proliferation, organize and contract the collagen matrix, and secrete much larger quantities of the usual extracellular matrix components. Because so many fibroblast functions are dramatically altered by the presence of the collagen matrix, matrix effects on fibroblast metabolism of arachidonic acid were examined. The studies presented here show that during the period of matrix contraction, metabolism of arachidonate to prostaglandins by fibroblasts is increased sixfold compared to cells plated on plastic, and that this increase is correlated with contraction but does not regulate it. The increase in prostaglandin synthesis is due in part to an increased new synthesis of the rate-limiting enzyme in prostaglandin synthesis, cyclooxygenase. No change in the profile of products the fibroblasts synthesize from arachidonate is induced by the presence of the matrix. After the lattice contraction is complete, the basal arachidonate metabolism of matrix-embedded cells have the same capacity to synthesize PGE2 in response to IL-1 as do cells grown on plastic. However, the response to the hormone agonist bradykinin by the matrix-embedded cells is present on day 1 but not on day 3, the time when cells grown on plastic are most responsive. These data indicate that while basal prostaglandin metabolism is unaffected in quiescent fibroblasts which have been embedded in a collagen matrix, response to hormone agonists may be greatly attenuated. The changes in the metabolism of arachidonate which occur during the process of matrix contraction and organization may play a part in the regulation of wound repair.     

Development and assessment of ecological models in the context of the European Water Framework Directive: Key issues for trainers in data-driven modeling approaches

Teaching students to develop data-driven models is a challenging task as a good balance has to be found between the theoretical background of the models, the ecological relevance of the knowledge rules inferred and their socio-economic applicability. In this context it is unclear which aspects of the modeling process are easily understood by students, and in particular, how theoretical issues interfere with practical boundary conditions and socio-economic relevance (ecosystem protection, water management, policy development, ecological engineering). In order to fill this knowledge gap, students developed static data-driven models and tutors assessed students' performances. Criteria such as the theoretical, ecological and socio-economic relevance of the derived knowledge rules were used to select the most optimal models.We noticed an inverse relationship between the complexity of the subtasks and the number of students that succeeded. Students evaluated their models with respect to the theoretical reliability, but were not likely to consider the other two criteria. Half of the students succeeded in assessing the models based on their ecological relevance and only 17% of the students checked the socio-economic relevance of the knowledge rules. Four groups out of seven assessed their models merely based on the predictive power of the models. Only one group integrated the theoretical, ecological and socio-economic relevance to assess the models.The key findings of our research can be used to optimize the efficiency of data mining courses. We reveal which aspects of the modeling process students seem to overemphasize and give recommendations about the topics trainers should emphasize in the future to ensure that students develop advanced skills. Based on our results the theory–practice dichotomy in higher education can be further reduced. Our learning-by-doing approach showed students how to solve common problems in ecological data sets (e.g. missing data, outliers, collinearity, non-normal distribution, parameterization, uncertainty, etc.), which are often only briefly discussed in basic statistical courses.     

Numerical taxonomic study of some tribes of Brassicaceae from Egypt

 A systematic study of 45 taxa belonging to 23 genera of tribes Arabideae, Euclidieae, Hesperideae, Lunarieae, Matthioleae and Sisymbrieae of Brassicaceae from Egypt was conducted by means of numerical analysis based on sixty two morphological characters, including vegetative parts, pollen grains and seeds. On the basis of UPGMA clustering and PCO analysis, four main groups are recognised: Lunarieae, Euclidieae, Matthioleae and a mixed group. Representatives of these groups are clustered together based on characters with high factor loading in the PCO analysis. The tribe Euclidieae is the most homogeneous group, and the tribe Arabideae is the most heterogeneous one. Received November 9, 2001; accepted February 21, 2002 Published online: October 14, 2002 Addresses of the authors: K. Abdel Khalik, (e-mail: kadry.elsayedabdelkhalik@wur.nl), L. J. G. van der Maesen (e-mail: jos.vandermaesen@ wur.nl), W. J. M. Koopman, R. G. van der Berg, Group of Biosystematics, Gen. Foulkesweg 37, NL-6703 BL Wageningen, The Netherlands.     

Robot predators in virtual ecologies: the importance of memory in mimicry studies

An important means of investigating gains and losses to prey caused by mimicry is through mathematical or computer constructs which represent and explore limited aspects of mimicry situations. Such studies use virtual predators which are usually simple automata, 'robots' that, through simple rules, vary virtual attack rates on virtual insect prey. In this paper I consider the effect of variations in predator memory and learning on mimicry dynamics. When there is mimicry between unequally noxious prey, the way that memory is modelled is shown to be crucial. If forgetting rates are fixed, an increase in the density of the least defended prey produces monotonic gains or losses in protection. However, if forgetting rate is inversely related in some way to degree of noxiousness of the prey then attack rates initially rise with the density of the least defended prey, reach a cusp and then fall. I show that the generation of this highly unconventional up-down result appears to be independent of variations in learning rate. This work shows how sensitive the predictions of virtual predators may be to relatively small changes in behavioural rules. Copyright 1999 The Association for the Study of Animal Behaviour.     

Oxygen transfer in slurry bioreactors

The oxygen transfer in bioreactors with slurries having a yield stress was investigated. The volumetric mass transfer coefficients in a 40-L bubble column with simulated fermentation broths, the Theological properties of which were represented by the Casson model, were measured. Experimental data were compared with a theoretical correlation developed on the basis of a combination of Higbie's penetration theory and Kolmogoroff's theory of isotropic turbulence. Comparisons between the proposed correlation and data for the simulated broths show good agreement. The mass transfer data for actual mycelial fermentation broths reported previously by the authors were re-examined. Their Theological data was correlated by the Bingham plastic model. The oxygen transfer rate data in the mycelial fermentation broths fit the predictions of the proposed theoretical correlation.     

Plastic versus glass capillaries for rapid-cycle PCR

Rapid-cycle PCR uses fast temperature transitions and minimal denaturation and annealing times of "0" s to complete 30 cycles in 10 to 30 min. The most popular platform amplifies samples in glass capillaries arranged around a carousel with circulating air for temperature control. Recently, plastic capillary replacements for glass capillaries became available. We compared the performance of plastic and glass capillaries for rapid-cycle PCR. Heat transfer into plastic capillaries was slowed by thicker walls, lower thermal conductivity, and a lower surface area-to-volume ratio than glass capillaries. Whereas the denaturation and annealing target temperatures were reached by samples in glass capillaries, samples in plastic capillaries fell short of these target temperatures by 6 degrees -7 degrees C. Rapid-cycle PCR was performed on two human genomic targets (APOE and ACVRL1) and one plasmid (pBR322) to amplify fragments of 225-300 bp in length with melting temperatures of 90.3 degrees -93.1 degrees C. Real-time amplification data, end-point melting curves, and end-point gel analysis revealed strong, specific amplification of samples in glass and complete amplification failure in plastic. Only the APOE target was successfully amplified by extending the denaturation and annealing times to 5 or 10 s. A 20 s holding period was necessary to reach target temperatures in plastic capillaries.