Molecular fingerprint-derived similarity measures for toxicological read-across: Recommendations for optimal use.

Computational approaches are increasingly used to predict toxicity due, in part, to pressures to find alternatives to animal testing. Read-across is the "new paradigm" which aims to predict toxicity by identifying similar, data rich, source compounds. This assumes that similar molecules tend to exhibit similar activities i.e. molecular similarity is integral to read-across. Various of molecular fingerprints and similarity measures may be used to calculate molecular similarity. This study investigated the value and concordance of the Tanimoto similarity values calculated using six widely used fingerprints within six toxicological datasets. There was considerable variability in the similarity values calculated from the various molecular fingerprints for diverse compounds, although they were reasonably concordant for homologous series acting via a common mechanism. The results suggest generic fingerprint-derived similarities are likely to be optimally predictive for local datasets, i.e. following sub-categorisation. Thus, for read-across, generic fingerprint-derived similarities are likely to be most predictive after chemicals are placed into categories (or groups), then similarity is calculated within those categories, rather than for a whole chemically diverse dataset.

Deep spinal infection in instrumented spinal surgery: diagnostic factors and therapy.

AIM: Postoperative surgical site infections (SSI) are complication of spinal surgery. These complications may lead to a poor outcome with neurological deficits, spinal deformity and chronic pain. The purpose of this study is to explore the statistical value of diagnostic parameters and the proper therapy. METHOD: We retrospectively reviewed 550 patients who underwent spinal instrumentation at our department from January 2011 to December 2015. The SSI was present in 16 patients out of 550 operated. Diagnostic criteria of SSI were the positivity of the surgical wound swab or blood culture, the clinical findings, positivity of laboratory tests and radiological elements. All patients had peri-operative antibiotic prophylaxis. Diagnostic laboratory findings were compared with a homogeneous control group of 16 patients and analyzed by univariate statistical analysis with Chi-square test for the discrete variables. P<0,05 was considered statistically significant. RESULTS: Matching the SSI patients with a group of control, fever was not statistically significant for diagnosis as number of leukocytes, neutrophils and lymphocytes. On the contrary values of ESR and CRP were statistically significant with p <0, 01. The hardware was removed only in 3 patients (18%) out of 16 SSI patients. CONCLUSION: In this study the statistically significant parameters to diagnose SSI are ESR and CRP values. The leucocytes count, number of lymphocytes and presence of fever integrates the data of ESR and CRP with no statistical significance. Most patients with SSI reach clinical healing with favorable outcome by means of target antibiotic therapy without hardware removal.

Spontaneous chronic subdural hematoma in young adult: the role of missing coagulation facto.

AIM: Chronic subdural hematoma (CSDH) is typically in elderly and rarely in young people. To prevent complications and re-bleeding after surgical treatment of CSDH it is important to assess the risk factors as coagulation disorders especially in young patients (below 65 years) with no history of head trauma, alcohol abuse or anticoagulant therapy. PATIENTS AND METHODS: This study consists of 16 patients (12 males, 4 females) with age ranging from 27 to 59 years (median 48,25 years) operated for CSDH. All patients are submitted to routine coagulation parameters pre-operatively and complete screening for unknown coagulation deficit in the follow-up. RESULTS: Factor VII was altered in 6 out of 16 patients and one patient had the alteration of the Von Willebrand factor. Recurrence occurred in 4 out of 16 patients and all of these patients were positive for factor VII deficiency. Three pts were in therapy with ASA. No patients were alcoholists or suffered from hematological disease. CONCLUSION: In this study we documented that the decreased activity of VII factor may play a role in the pathophysiology and recurrence of spontaneous CSDH in young adults. We suggest that for young patients aged under 65 y.o. suffered from CSDH the screening of coagulation factors is useful to planning a safely and correct surgical therapy.

Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project.

Quantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Second Ames/QSAR International Challenge Project (2020-2022) as a successor to the First Project (2014-2017), with 21 teams from 11 countries participating. The DGM/NIHS provided a curated training dataset of approximately 12,000 chemicals and a trial dataset of approximately 1,600 chemicals, and each participating team predicted the Ames mutagenicity of each trial chemical using various Ames/QSAR models. The DGM/NIHS then provided the Ames test results for trial chemicals to assist in model improvement. Although overall model performance on the Second Project was not superior to that on the First, models from the eight teams participating in both projects achieved higher sensitivity than models from teams participating in only the Second Project. Thus, these evaluations have facilitated the development of QSAR models.

Predictive models for carcinogenicity and mutagenicity: frameworks, state-of-the-art, and perspectives.

Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include Vitotox, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-throughput assays combined with innovative data-mining and in silico methods. Various initiatives in this regard have begun, including CAESAR, OSIRIS, CHEMOMENTUM, CHEMPREDICT, OpenTox, EPAA, and ToxCast. In silico methods can be used for priority setting, mechanistic studies, and to estimate potency. Ultimately, such efforts should lead to improvements in application of in silico methods for predicting carcinogenicity to assist industry and regulators and to enhance protection of public health.

Cervical lordosis after subaxial spinal trauma surgery: relationship with neck pain and stiffness.

BACKGROUND: The objective of this retrospective study is to evaluate how neck pain is influenced by post-operative cervical alignment in patients operated for cervical spinal trauma. PATIENTS AND METHODS: From January 2013 to June 2017, at our department we operated 34 patients with cervical spinal trauma, 22 males and 12 females. Age, sex, level and type of fractures, surgical approach, fixation levels (cervical or cervico-dorsal), preoperative and postoperative CT scan, cervical (C2-C7) Cobb angle (lordotic > +10°, straight 0 /+10°, kyphotic < 0°) at X-rays on sitting position 3 months after surgery, postoperative self-reported neck stiffness scale, preoperative and follow-up ASIA score, pre and postoperative VAS value were evaluated for each patient. Statistical analysis was performed according to the Mann-Whitney and T-test. RESULTS: In this series, 22 patients were operated by anterior approach, 7 patients by posterior approach and 5 by combined approach. Postoperative chronic cervical pain was not correlated with cervical sagittal alignment after surgery, fracture type, surgical approach, fixation level and postoperative ASIA score but is correlated with the presence of neck stiffness (P=0,001). Patients treated with posterior approach (P=0,022) and fracture type C (P=0,026) had higher significantly neck stiffness compared to patients who underwent anterior approach for type B fractures. CONCLUSIONS: The presence of abnormal cervical lordosis after surgery for cervical spinal trauma does not correlate with neck pain. Patients treated with posterior fixation had higher neck stiffness and related chronic pain.

Understanding genetic toxicity through data mining: the process of building knowledge by integrating multiple genetic toxicity databases.

ABSTRACT Genetic toxicity data from various sources were integrated into a rigorously designed database using the ToxML schema. The public database sources include the U.S. Food and Drug Administration (FDA) submission data from approved new drug applications, food contact notifications, generally recognized as safe food ingredients, and chemicals from the NTP and CCRIS databases. The data from public sources were then combined with data from private industry according to ToxML criteria. The resulting "integrated" database, enriched in pharmaceuticals, was used for data mining analysis. Structural features describing the database were used to differentiate the chemical spaces of drugs/candidates, food ingredients, and industrial chemicals. In general, structures for drugs/candidates and food ingredients are associated with lower frequencies of mutagenicity and clastogenicity, whereas industrial chemicals as a group contain a much higher proportion of positives. Structural features were selected to analyze endpoint outcomes of the genetic toxicity studies. Although most of the well-known genotoxic carcinogenic alerts were identified, some discrepancies from the classic Ashby-Tennant alerts were observed. Using these influential features as the independent variables, the results of four types of genotoxicity studies were correlated. High Pearson correlations were found between the results of Salmonella mutagenicity and mouse lymphoma assay testing as well as those from in vitro chromosome aberration studies. This paper demonstrates the usefulness of representing a chemical by its structural features and the use of these features to profile a battery of tests rather than relying on a single toxicity test of a given chemical. This paper presents data mining/profiling methods applied in a weight-of-evidence approach to assess potential for genetic toxicity, and to guide the development of intelligent testing strategies.

Molecular similarity matrices and quantitative structure-activity relationships: a case study with methodological implications.

Recently, statistical analysis of molecular similarity matrices has been applied to the quantitative structure-activity relationship (QSAR) analysis of a number of molecular series. This paper addresses a number of methodological issues relative to the similarity matrices. A series of halogenated aliphatic hydrocarbons, for which the mutation (aneuploidy) induction ability had previously been determined, was used as test bench. The chemical information carried by the similarity matrices was shown to overlap to a considerable extent the information carried by the classical descriptors (physical chemical and quantum mechanical parameters). A good QSAR was obtained on the basis of the similarity matrices, in analogy with that obtained with the classical descriptors; however, the similarity matrices neither complemented the classical descriptors nor were able to improve on their performance. The effect of the compound's spatial orientation on the similarity values was also investigated.

Deriving a quantitative chirality measure from molecular similarity indices.

A versatile new method has been developed as a continuous symmetry measure for chiral compounds. The application of principal component analysis (PCA) to the complete N x N pairwise similarity matrices (electrostatic potential and shape indices) of a series of dihydropyridine calcium channel antagonists allowed to single out a chirality component and to compute a chirality score in terms of the between-enantiomers difference on the component value. The possibility to have chirality defined continuously at the series level could be of importance in eudismic analyses where the relative potency of two enantiomers is studied as well as in QSAR studies dealing with chiral molecules in order to improve the power of the generated models.

Mathematical models for exploring different aspects of genotoxicity and carcinogenicity databases.

One great obstacle to understanding and using the information contained in the genotoxicity and carcinogenicity databases is the very size of such databases. Their vastness makes them difficult to read; this leads to inadequate exploitation of the information, which becomes costly in terms of time, labor, and money. In its search for adequate approaches to the problem, the scientific community has, curiously, almost entirely neglected an existent series of very powerful methods of data analysis: the multivariate data analysis techniques. These methods were specifically designed for exploring large data sets. This paper presents the multivariate techniques and reports a number of applications to genotoxicity problems. These studies show how biology and mathematical modeling can be combined and how successful this combination is.

Prediction of rodent carcinogenicity of further 30 chemicals bioassayed by the U.S. National Toxicology Program.

Recently the U.S. National Toxicology Program (NTP) sponsored a comparative exercise in which different prediction approaches (both biologically and chemically based) were challenged for their predictive abilities of rodent carcinogenicity of a common set of chemicals. The exercise enjoyed remarkable scientific success and stimulated NTP to sponsor a second challenging round of tests, inviting participants to present predictions relative to the rodent carcinogenicity of a further 30 chemicals; these are currently being tested. In this article, we present our predictions based on structure-activity relationship considerations. In our procedure, first each chemical was assigned to an activity mechanism class and then, with semiquantitative considerations, was assigned a probability carcinogenicity score, taking into account simultaneously the hypothesized action mechanism and physical chemical parameters.

The sex difference in tumor incidence is related to the female condition: models for Europe and Italy.

A remarkable aspect of cancer distribution in Europe is the large spatial variability of the male-female incidence ratio, from no difference up to 50%. Given the evidence of the predominantly environmental origin of cancer, we studied the ability of a set of socioeconomic indicators of the female condition to model the spatial variability of the sex difference in tumor incidence at two different scales: between countries (Europe) and between provinces (Italy). The sex difference in tumor incidence correlated with female socioeconomic condition indicators at the same extent (r = 0.73) in both situations, but in opposite directions. In the European study the higher the sexual social equality the lower the differential tumor incidence, whereas the opposite result was shown by the between-provinces Italian study. We also investigated the relation of the female condition indicator with other social and cultural descriptors of the same populations, and we suggest explanatory models linking female condition and pathology at the continental and local scales. Overall, our analysis supports the predominantly environmental origin of cancer and stresses the importance of relating cancer patterns to societal determinants. Our analysis also suggests that the sex difference in tumor incidence is a very useful probe for exploring the social-economic cultural correlates of cancer in human populations. We emphasize the need for a thorough analysis of the empirical correlations highlighted in ecologic studies.

Sensitivity of lymphocytes from vulcanizers to the in vitro induction of sister chromatid exchanges.

Spontaneous frequencies of sister chromatid exchanges (SCEs) and SCEs induced in vitro by chemicals with different mechanisms of action such as mitomycin C, 4-nitroquinoline oxide, and 3-aminobenzamide were examined in phytohemagglutinin-stimulated peripheral blood lymphocytes from a group of workers in a rubber plant and a control group, both of which had been analyzed for levels of spontaneous SCEs 2 years earlier. An interindividual variability in the induction of SCEs was found after in vitro treatments with the different mutagens, which did not correlate with occupational exposure. This variability in the sensitivity to the induction of SCEs might be correlated to genetic differences among individuals, which have to be taken into account in environmental monitoring programs.

Rational approach to the quantification of genotoxicity.

The question of how many and which short-term tests (STT) are necessary for a satisfactory characterization of the genotoxic properties of chemicals is still open. The answer is important for both basic mutagenicity research and risk assessment. This paper, aimed at giving a rational answer to the problem, analyzes with multivariate statistical methods the data generated by the International Program for the Evaluation of Short-Term Tests for Carcinogens (IPESTTC). Although it has been found that this data base has a limited reliability for assessing the ability of STTs to predict carcinogenicity, the IPESTTC results are an important source of information on the relationships among different assays, and their ability to identify genotoxic chemicals. A scale of genotoxicity of the chemicals was established by studying with factor analysis their results in 20 IPESTTC tests. The next step of the analysis consisted in the identification of the STT batteries which are the most able to reproduce the genotoxicity scale based on the entire set of STTs. Different batteries were ranked according to their ability to quantify genotoxicity. As a general conclusion, this study indicated that an articulated range of STTs is necessary, and it is not possible to use only one assay (e.g., Salmonella) as an exhaustive indicator of genotoxicity.

Statistical exploration of four major genotoxicity data bases: an overview.

This report puts into perspective a series of exploratory statistical analyses carried out on the major genotoxicity data bases. While large compilations of data, even though computerized, suffer from their own size and are quite intractable to scientific reflection and judgement, the multivariate data analysis methods used by us are specifically designed for reorganising the information in a rational way and highlighting the underlying regularities of the data. The analyses reported here refer to the following data bases: the International Program for the Evaluation of Short-Term Tests for Carcinogens, the International Program on Chemical Safety Collaborative Study on In Vitro Assays, the Gene-Tox data base, and a subset of the U.S. National Toxicology Program data. Although the various data bases consisted of different sets of chemicals and had different underlying rationales, a number of invariant associations among short-term test performances were highlighted. The overall evidence indicated that the traditional classification of assays (according to the criteria of genetic end-point and phylogenetic position of the assays) was in contrast with the actual, operational similarities among assay performances, in that the experimental responses of the tests to the large variety of chemicals under consideration pointed to an alternative classification scheme. This consisted of three major classes: 1) a class comprising the in vivo assays; 2) a class grouping together many of the most widely used in vitro assays (Salmonella, chromosomal aberrations, and sister chromatid exchanges in Chinese hamster ovary cells, the various mutation tests in mammalian cell systems, etc.); 3) a second in vitro assay class (with Syrian hamster embryo cell transformation, Saccharomyces cerevisiae XV185-14C, B. subtilis rec-, Escherichia coli pol A). Such classes had clearly differentiated features with respect to carcinogenicity prediction. The implications of these findings for the current debate on mutagenicity testing are discussed.

Relationships among in vitro mutagenicity assays: quantitative vs. qualitative test results.

In previous investigations, we studied the relationships between the profiles of the qualitative responses of in vitro short-term tests (mutation in Salmonella typhimurium, chromosomal aberrations in CHO cells, sister chromatid exchanges in CHO cells, and mutation in mouse lymphoma cells) and common sets of chemicals. In this paper, we address the study of the quantitative responses (potency). We show that two analyses point to similar patterns of relationships: the mutation in mouse lymphoma cells assay is most similar to the CHO sister chromatid exchange assay, and the Salmonella assay is most similar to the CHO chromosomal aberrations assay.

QSAR models for both mutagenic potency and activity: application to nitroarenes and aromatic amines.

We studied the molecular determinants that discriminate between mutagenic and inactive compounds for: a) aromatic and heteroaromatic amines; b) nitroarenes. Mutagenic activity (data from literature) had been previously assessed in Salmonella typhimurium and Escherichia coli (SOS repair). The Quantitative Structure-Activity Relationships (QSAR) found were compared with those obtained in the laboratory of Professor C. Hansch for the mutagenic potency of the same compounds. It appears that there is a dramatic difference between the QSARs for potency, and those for yes/no activity: hydrophobicity played a major role in determining the potency of the active compounds, whereas mainly electronic factors differentiated the actives from the inactives. The electronic factors were those expected on the basis of the hypothesized metabolic pathways of the chemicals. Our interpretation is that the electronic factors (together with size/shape, possibly) determine the minimum requirement for the chemicals to be metabolized, whereas the hydrophobicity determines the extent of activity of chemicals that can be metabolized (actives). Moreover, the different QSARs found for the Salmonella strains TA98 and TA100 were discussed in the light of recent progress in the understanding of the molecular mechanisms of mutagenicity in these organisms. It is concluded that the nonlinear relationship observed for these chemicals between the two types of QSAR should be taken into account both when planning QSAR studies, and when using mutagenicity data for risk assessment.

QSAR models for discriminating between mutagenic and nonmutagenic aromatic and heteroaromatic amines.

In a previous article, we demonstrated that the structure-activity relationship model for the mutagenic potency of aromatic amines is different from that for discriminating between mutagens and nonmutagens. In this work, we present further analyses on the molecular determinants of the mutagenicity of aromatic amines. Based on the use of various methodological approaches, our results indicate that mutagenic activity is influenced by different molecular characteristics in different subclasses of aromatic amines. Thus, the general lesson of this article is that 1) in genetic toxicology, it is necessary to separately investigate the structure-activity relationships for discrimination between positive and negative chemicals, and the structure-activity relationships for the potency of the positive chemicals; 2) in structure-activity studies, it is necessary to investigate the degree of homogeneity (congenericity) of apparently similar chemicals in order to assess and describe the various mechanisms of action that may be elicited by the chemicals.

The cultural heritage shapes the pattern of tumour profiles in Europe: a correlation study.

STUDY OBJECTIVE: This study investigates the spatial pattern of tumours in Europe to check the feasibility of a large scale ecological epidemiology approach to cancer in Europe. SETTING: The tumour types relative frequencies and cancer incidence (for men and women) reported in the European cancer registries were investigated by exploratory data analysis techniques. Socioeconomical descriptors of the female condition were considered as well. MAIN RESULTS: The classification of the European regional areas covered by the cancer registries followed almost exactly the boundaries set by the long and intermingled European history in terms of life styles and cultural heritage. This result supports the notion of a predominant role of environmental factors in cancer induction. Further support to the above result was given by the finding of a correlation between differential male-female cancer incidence, and socioeconomic descriptors of the female condition. CONCLUSIONS: From a methodological point of view, the consistency of these results pointed to the feasibility of an ecological approach to tumour epidemiology.

Toxicology of halogenated aliphatic hydrocarbons: structural and molecular determinants for the disturbance of chromosome segregation and the induction of lipid peroxidation.

The induction of mitotic chromosome malsegregation, mitotic arrest and lethality by a set of 55 halogenated hydrocarbons was investigated. To this aim, genetic assays in the mould Aspergillus nidulans, able to provide precise quantitative information on the end-points studied, were used throughout the work. The experimental data obtained were used to develop QSAR models for the induction of aneuploidy, which pointed to a major role of electrophilicity as molecular determinant for the aneugenic potential of the halogenated hydrocarbons investigated. Within the hypothesis of a link between the electrophilicity of haloalkanes and their propensity to undergo a reductive biotransformation, with production of free radical species, a subset of 27 compounds was also tested for the ability to induce lipid peroxidation in rat liver microsomes in vitro. The results obtained indicate a partial coincidence between the abilities to initiate lipid peroxidation and to disturb chromosome segregation at mitosis. The data base obtained was also used to investigate the relationship between chemical structure and peroxidative potential. The analysis indicated that electronic and structural parameters related to the ease of homolitic cleavage of the carbon-halogen bond play a pivotal role as determinants for the peroxidative character of haloalkanes.