Data exploration and knowledge extraction: their application to the study of endocrine disrupting chemicals

Interest in computer-aided methods for investigating the biological field has increased significantly. One method is Quantitative Structure-Activity Relationships (QSAR), a valuable technique for predicting the effects of a substance from its chemical structure. A challenging application of QSAR is in characterizing the (bio)activity profiles of chemicals. Endocrine disrupters (EDs) are exogenous substances interfering with the function of the endocrine system and represent an interesting field of application for in silico methods. EDs targets include nuclear receptors, particularly effects mediated by the oestrogen receptor (ER). They are also mentioned as substances requiring a more detailed control and specific authorisation within REACH, the new European legislation on chemicals. QSAR represents a challenging method to approach data gap about EDs since REACH substantially boosted interest on computational chemistry to replace experimental testing. This work: aimed to explore the status, availability and reliability of non-testing methods applied to endocrine disruption via oestrogen receptors and eventually to propose new models easily exploitable in regulatory contexts. The work evaluated existing QSAR models present in literature to assess their validity on the basis of the OECD principles for QSAR validation. Different kinds of models have been analysed and they were externally validated with new data found in the literature. Furthermore, new QSAR binary classifiers have been developed using different data mining techniques (e.g.: classification trees, fuzzy logic, neural networks) based on a very large and heterogeneous dataset of chemical compounds. The focus was given to both binding (RBA) and transcriptional activity (RA) better to characterize the effects of EDs. A possible combination of the models was also explored. A very good accuracy was achieved for both RA and RBA (>85%). These models can be a valuable complement to in vivo and in vitro studies in the toxicological characterisation of chemical compounds

Primary Prevention of Cardiovascular Events With Low-Dose Aspirin and Vitamin E in Type 2 Diabetic Patients

OBJECTIVE—We investigated in general practice the efficacy of antiplatelets and antioxidants in primary prevention of cardiovascular events in people with type 2 diabetes. RESEARCH DESIGN AND METHODS—The Primary Prevention Project (PPP) is a randomized, open trial with a two-by-two factorial design aimed to investigate low-dose aspirin (100 mg/day) and vitamin E (300 mg/day) in the prevention of cardiovascular events in patients with one or more cardiovascular risk factors. The primary end point was a composite end point of cardiovascular death, stroke, or myocardial infarction. A total of 1,031 people with diabetes in the PPP, aged ≥50 years, without a previous cardiovascular event were enrolled by 316 general practitioners and 14 diabetes outpatient clinics. RESULTS—The PPP trial was prematurely stopped (after a median of 3.7 years) by the independent data safety and monitoring board because of a consistent benefit of aspirin compared with the control group in a population of 4,495 patients with one or more major cardiovascular risk factors. In diabetic patients, aspirin treatment was associated with a nonsignificant reduction in the main end point (relative risk [RR] = 0.90, 95% CI 0.50–1.62) and in total cardiovascular events (0.89, 0.62–1.26) and with a nonsignificant increase in cardiovascular deaths (1.23, 0.69–2.19). In nondiabetic subjects, RRs for the main end point, total cardiovascular events, and cardiovascular deaths were 0.59 (0.37–0.94), 0.69 (0.53–0.90), and 0.32 (0.14–0.72), respectively. No significant reduction in any of the end points considered could be found with vitamin E in either diabetic or nondiabetic subjects. CONCLUSIONS—Our data suggest a lower effect of primary prevention of cardiovascular disease (CVD) with low-dose aspirin in diabetic patients as opposed to subjects with other cardiovascular risk factors. If confirmed, these findings might indicate that the antiplatelet effects of aspirin in diabetic patients are overwhelmed by aspirin-insensitive mechanisms of platelet activation and thrombus formation, thus making the balance between benefits and harms of aspirin treatment unfavorable. Further large-scale trials investigating the role of aspirin in the primary prevention of CVD in diabetic patients are urgently needed

Prevalence and determinants of diabetes mellitus in a representative sample of Italian adults

Background: Diabetes mellitus is a dramatic epidemic worldwide. This study providea an updated estimate of itsprevalence and determinants among Italian adults. Methods: Data were derived from a face-to-face survey conducted in 2013 on 2901 individuals (1391 men, 1510 women) aged ≥18 years, representative of the general adult Italian population. Odds ratios (OR) for diabetes versus non diabetes in relation to selected risk factors were derived using multiple logistic regression models. Results: Overall, 135 out of 2901 adults (4.7%) reported a diagnosis of diabetes, with similar prevalence in men (4.8%) and in women (4.5%). Diabetes increased with age (0.6% at age 18-44, 5.1% at age 45-64, and 11.3% at age ≥65 years; p-trend <0.001) and decreased with increasing level of education (12.8% for low, 7.8% for middle, and 1.4% for high education; p-trend <0.001). Prevalence was higher among obese subjects (10.8%) compared to normal weight subjects (3.1%; OR=2.46; p-trend=0.001), among individuals reporting a physical activity <30 minutes of walk/day (5.6%) compared to those reporting >60 minutes of walk/day (3.8%; OR=1.43), and among ex-smokers (11.6%) compared to never smokers (4.2%; OR=2.51); moreover, it was lower among moderate drinkers (3.1%) than among abstainers (6.1%; OR=0.57; p-trend=0.016). Prevalence of diabetes was 16.1% in individuals with a diagnosis of hypertension (OR=4.66), 15.2% in those with high cholesterol (OR=3.84), and 21.6% among aspirin users (OR=4.46). Conclusion: Although diabetes prevalence in Italy is still comparatively low, effective clinical and preventive intervention strategies – focused on major risk behaviors – should be implemented to control the diffusion of this condition

Ensemble Methods for Multi-Organ Segmentation in CT Series

In the medical images field, semantic segmentation is one of the most important, yet difficult and time-consuming tasks to be performed by physicians. Thanks to the recent advancement in the Deep Learning models regarding Computer Vision, the promise to automate this kind of task is getting more and more realistic. However, many problems are still to be solved, like the scarce availability of data and the difficulty to extend the efficiency of highly specialised models to general scenarios. Organs at risk segmentation for radiotherapy treatment planning falls in this category, as the limited data available negatively affects the possibility to develop general-purpose models; in this work, we focus on the possibility to solve this problem by presenting three types of ensembles of single-organ models able to produce multi-organ masks exploiting the different specialisations of their components. The results obtained are promising and prove that this is a possible solution to finding efficient multi-organ segmentation methods

CORAL: the prediction of biodegradation of organic compounds with optimal SMILES-based descriptors

Abstract CORAL software (http:/www.insilico.eu/coral) has been used to build up quantitative structure-biodegradation relationships (QSPR). The normalized degradation percentage has been used as the measure of biodegradation (for diverse organic compounds, n=445). Six random splits into sub-training, calibration, and test sets were examined. For each split the QSPR one-variable linear regression model based on the SMILES-based optimal descriptors has been built up. The average values of numbers of compounds and the correlation coefficients (r2) between experimental and calculated biodegradability values of these six models for the test sets are n=88.2±11.7 and r2=0.728±0.05. These six models were further tested against a set of chemicals (n=285) for which only categorical values (biodegradable or not) were available. Thus we also evaluated the use of the model as a classifier. The average values of the sensitivity, specificity, and accuracy were 0.811±0.019, 0.795±0.024, and 0.803±0.008, respectively

Human-BasedNewApproachMethodologiesin DevelopmentalToxicityTesting:AStepAheadfromtheState oftheArtwithaFeto–PlacentalOrgan-on-ChipPlatform

Download PDFsettingsOrder Article Reprints Open AccessReview Human-Based New Approach Methodologies in Developmental Toxicity Testing: A Step Ahead from the State of the Art with a Feto–Placental Organ-on-Chip Platform by Michaela Luconi 1,2,†ORCID,Miguel A. Sogorb 3,†ORCID,Udo R. Markert 4ORCID,Emilio Benfenati 5,Tobias May 6,Susanne Wolbank 7ORCID,Alessandra Roncaglioni 5,Astrid Schmidt 4,Marco Straccia 8ORCID andSabrina Tait 9,*ORCID 1 Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, Viale Pieraccini 6, 50139 Florence, Italy 2 I.N.B.B. (Istituto Nazionale Biostrutture e Biosistemi), Viale Medaglie d’Oro 305, 00136 Rome, Italy 3 Instituto de Bioingeniería, Universidad Miguel Hernández de Elche, Avenida de la Universidad s/n, 03202 Elche, Spain 4 Placenta Lab, Department of Obstetrics, University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany 5 Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milan, Italy 6 InSCREENeX GmbH, Inhoffenstr. 7, 38124 Braunschweig, Germany 7 Ludwig Boltzmann Institut for Traumatology, The Research Center in Cooperation with AUVA, Austrian Cluster for Tissue Regeneration, Donaueschingenstrasse 13, 1200 Vienna, Austria 8 FRESCI by Science&Strategy SL, C/Roure Monjo 33, Vacarisses, 08233 Barcelona, Spain 9 Centre for Gender-Specific Medicine, Istituto Superiore di Sanità, 00161 Rome, Italy * Author to whom correspondence should be addressed. † These authors contributed equally to this work. Int. J. Environ. Res. Public Health 2022, 19(23), 15828; https://doi.org/10.3390/ijerph192315828 Submission received: 24 October 2022 / Revised: 20 November 2022 / Accepted: 25 November 2022 / Published: 28 November 2022 (This article belongs to the Section Toxicology and Public Health) Downloadkeyboard_arrow_down Browse Figures Review Reports Versions Notes Abstract Developmental toxicity testing urgently requires the implementation of human-relevant new approach methodologies (NAMs) that better recapitulate the peculiar nature of human physiology during pregnancy, especially the placenta and the maternal/fetal interface, which represent a key stage for human lifelong health. Fit-for-purpose NAMs for the placental–fetal interface are desirable to improve the biological knowledge of environmental exposure at the molecular level and to reduce the high cost, time and ethical impact of animal studies. This article reviews the state of the art on the available in vitro (placental, fetal and amniotic cell-based systems) and in silico NAMs of human relevance for developmental toxicity testing purposes; in addition, we considered available Adverse Outcome Pathways related to developmental toxicity. The OECD TG 414 for the identification and assessment of deleterious effects of prenatal exposure to chemicals on developing organisms will be discussed to delineate the regulatory context and to better debate what is missing and needed in the context of the Developmental Origins of Health and Disease hypothesis to significantly improve this sector. Starting from this analysis, the development of a novel human feto–placental organ-on-chip platform will be introduced as an innovative future alternative tool for developmental toxicity testing, considering possible implementation and validation strategies to overcome the limitation of the current animal studies and NAMs available in regulatory toxicology and in the biomedical field

Effects of aspirin on risks of vascular events and cancer according to bodyweight and dose:analysis of individual patient data from randomised trials

Background A one-dose-fits-all approach to use of aspirin has yielded only modest benefits in long-term prevention of cardiovascular events, possibly due to underdosing in patients of large body size and excess dosing in patients of small body size, which might also affect other outcomes. Methods Using individual patient data, we analysed the modifying effects of bodyweight (10 kg bands) and height (10 cm bands) on the effects of low doses (≤100 mg) and higher doses (300–325 mg or ≥500 mg) of aspirin in randomised trials of aspirin in primary prevention of cardiovascular events. We stratified the findings by age, sex, and vascular risk factors, and validated them in trials of aspirin in secondary prevention of stroke. Additionally, we assessed whether any weight or height dependence was evident for the effect of aspirin on 20-year risk of colorectal cancer or any in-trial cancer. Results Among ten eligible trials of aspirin in primary prevention (including 117 279 participants), bodyweight varied four-fold and trial median weight ranged from 60·0 kg to 81·2 kg (pand#60;0·0001). The ability of 75–100 mg aspirin to reduce cardiovascular events decreased with increasing weight (pinteraction=0·0072), with benefit seen in people weighing 50–69 kg (hazard ratio [HR] 0·75 [95% CI 0·65–0·85]) but not in those weighing 70 kg or more (0·95 [0·86–1·04]; 1·09 [0·93–1·29] for vascular death). Furthermore, the case fatality of a first cardiovascular event was increased by low-dose aspirin in people weighing 70 kg or more (odds ratio 1·33 [95% CI 1·08–1·64], p=0·0082). Higher doses of aspirin (≥325 mg) had the opposite interaction with bodyweight (difference pinteraction=0·0013), reducing cardiovascular events only at higher weight (pinteraction=0·017). Findings were similar in men and women, in people with diabetes, in trials of aspirin in secondary prevention, and in relation to height (pinteraction=0·0025 for cardiovascular events). Aspirin-mediated reductions in long-term risk of colorectal cancer were also weight dependent (pinteraction=0·038). Stratification by body size also revealed harms due to excess dosing: risk of sudden death was increased by aspirin in people at low weight for dose (pinteraction=0·0018) and risk of all-cause death was increased in people weighing less than 50 kg who were receiving 75–100 mg aspirin (HR 1·52 [95% CI 1·04–2·21], p=0·031). In participants aged 70 years or older, the 3-year risk of cancer was also increased by aspirin (1·20 [1·03–1·47], p=0·02), particularly in those weighing less than 70 kg (1·31 [1·07–1·61], p=0·009) and consequently in women (1·44 [1·11–1·87], p=0·0069). Interpretation Low doses of aspirin (75–100 mg) were only effective in preventing vascular events in patients weighing less than 70 kg, and had no benefit in the 80% of men and nearly 50% of all women weighing 70 kg or more. By contrast, higher doses of aspirin were only effective in patients weighing 70 kg or more. Given that aspirin's effects on other outcomes, including cancer, also showed interactions with body size, a one-dose-fits-all approach to aspirin is unlikely to be optimal, and a more tailored strategy is required

Lower risk of death and cardiovascular events in patients with diabetes initiating glucagon-like peptide-1 receptor agonists or sodium-glucose cotransporter-2 inhibitors: A real-world study in two Italian cohorts

Aim: To examine the efficacy and safety of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 (SGLT2) inhibitors compared with other antihyperglycaemic agents (AHAs) in large and unselected populations of the Lombardy and Apulia regions in Italy. Materials and Methods: An observational cohort study of first-time users of GLP-1RAs, SGLT2 inhibitors or other AHAs was conducted from 2010 to 2018. Death and cardiovascular (CV) events were evaluated using conditional Cox models in propensity-score-matched populations. Adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated for each region and in a meta-analysis for pooled risks. Results: After propensity-score matching, the Lombardy cohort included 18 716 and 11 683 patients and the Apulia cohort 9772 and 6046 patients for the GLP-1RA and SGLT2 inhibitor groups, respectively. Use of GLP-1RAs was associated with lower rates of death (HR 0.61, CI 0.56-0.65, Lombardy; HR 0.63, CI 0.55-0.71, Apulia), cerebrovascular disease and ischaemic stroke (HR 0.70, CI 0.63-0.79; HR 0.72, CI 0.60-0.87, Lombardy), peripheral vascular disease (HR 0.72, CI 0.64-0.82, Lombardy; HR 0.80, CI 0.67-0.98, Apulia), and lower limb complications (HR 0.67, CI 0.56-0.81, Lombardy; HR 0.69, CI 0.51-0.93, Apulia). Compared with other AHAs, SGLT2 inhibitor use decreased the risk of death (HR 0.47, CI 0.40-0.54, Lombardy; HR 0.43, CI 0.32-0.57, Apulia), cerebrovascular disease (HR 0.75, CI 0.61-0.91, Lombardy; HR 0.72, CI 0.54-0.96, Apulia), and heart failure (HR 0.56, CI 0.46-0.70, Lombardy; HR 0.57, CI 0.42-0.77, Apulia). In the pooled cohorts, a reduction in heart failure was also observed with GLP-1RAs (HR 0.89, 95% CI 0.82-0.97). Serious adverse events were quite low in frequency. Conclusion: Our findings from real-world practice confirm the favourable effect of GLP-1RAs and SGLT2 inhibitors on death and CV outcomes across both regions consistently. Thus, these drug classes should be preferentially considered in a broad type 2 diabetes population beyond those with CV disease

Prediction Of The Neurotoxic Potential Of Chemicals Based On Modelling Of Molecular Initiating Events Upstream Of The Adverse Outcome Pathways Of (Developmental) Neurotoxicity

Developmental and adult/ageing neurotoxicity are an area needing alternative methods for chemical risk assessment. The formulation of a strategy to screen large numbers of chemicals is highly relevant due to potential exposure to compounds that may have long-term adverse health consequences on the nervous system, leading to neurodegeneration. Adverse Outcome Pathways (AOPs) provide information on relevant molecular initiating events (MIEs) and key events (KEs) that could inform the development of computational alternatives for these complex effects. We propose a screening method integrating multiple Quantitative Structure–Activity Relationship (QSAR) models. The MIEs of existing AOP networks of developmental and adult/ageing neurotoxicity were modelled to predict neurotoxicity. Random Forests were used to model each MIE. Predictions re-turned by single models were integrated and evaluated for their capability to predict neurotoxicity. Specifically, MIE predictions were used within various types of classifiers and compared with other reference standards (chemical descriptors and structural fingerprints) to benchmark their predictive capability. Overall, classifiers based on MIE predictions returned predictive performances compa-rable to those based on chemical descriptors and structural fingerprints. The integrated computa-tional approach described here will be beneficial for large-scale screening and prioritisation of chem-icals as a function of their potential to cause long-term neurotoxic effects

Is global cardiovascular risk considered in current practice? Treatment and control of hypertension, hyperlipidemia, and diabetes according to patients’ risk level

Daria Roccatagliata1, Fausto Avanzini1, Lara Monesi1, Vittorio Caimi2, Davide Lauri1, Paolo Longoni3, Roberto Marchioli4, Massimo Tombesi2, Gianni Tognoni1, Maria Carla Roncaglioni1, on behalf of the Collaborative Group Risk and Prevention Study*1Istituto di Ricerche Farmacologiche “Mario Negri”, Milano, Italy; 2CSeRMEG Centro Studi e Ricerca in Medicina Generale, Monza, Italy; 3CoS Consorzio Sanità, Milano, Italy; 4Consorzio Mario Negri Sud, S. Maria Imbaro, Italy *A full list of investigators is reported in the AppendixObjectives: To assess the pharmacological treatment and the control of major modifiable cardiovascular risk factors in everyday practice according to the patients’ cardiovascular risk level.Methods: In a cross-sectional study general practitioners (GPs) had to identify a random sample of their patients with cardiovascular risk factors or diseases and collect essential data on the pharmacological treatment and control of hypertension, hyperlipidemia, and diabetes according to the patients’ cardiovascular risk level and history of cardiovascular disease. Participants were subjects of both sexes, aged 40–80 years, with at least one known cardiovascular risk factor or a history of cardiovascular diseases.Results: From June to December 2000, 162 Italian GPs enrolled 3120 of their patients (2470 hypertensives, 1373 hyperlipidemics, and 604 diabetics). Despite the positive association between the perceived level of global cardiovascular risk and lipid-lowering drug prescriptions in hyperlipidemic subjects (from 26% for lowest risk to 56% for highest risk p < 0.0001) or the prescription of combination therapy in hypertensives (from 41% to 70%, p < 0.0001) and diabetics (from 24% to 43%, p = 0.057), control was still inadequate in 48% of diabetics, 77% of hypertensives, and 85% of hyperlipidemics, with no increase in patients at highest risk. Trends for treatment and control were similar in patients with cardiovascular diseases.Conclusions: Even in high-risk patients, despite a tendency towards more intensive treatment, pharmacological therapy is still under used and the degree of control of blood pressure, cholesterol level and diabetes is largely unsatisfactory.Keywords: global cardiovascular risk, hypertension, hyperlipideamia, diabetes, general practice