VERMEER FCM: A tool integrating exposure and hazard modelling for chemicals migrating from food contact materials.

A new tool, VERMEER FCM, was developed to support the risk assessment of single organic chemicals migrating from plastic food contact materials (FCM). The freely available tool is integrated into MERLIN-Expo and has been designed in line with Regulation (EU) No 10/2011 for plastic FCM. Overall, the tool consists of three modules that allow (i) to model the migration of chemicals into food, (ii) to predict toxicological endpoints relevant to risk assessment of FCM chemicals, and (iii) to automatically check whether the chemical of interest is included in Regulation (EU) No 10/2011.

Lung Recruitment Before Surfactant Administration in Extremely Preterm Neonates: 2-Year Follow-Up of a Randomized Clinical Trial.

Importance: A multicenter randomized clinical trial (RCT) showed a lung recruitment maneuver using high-frequency oscillatory ventilation just before surfactant administration (ie, intubate-recruit-surfactant-extubate [IN-REC-SUR-E]) improved the efficacy of treatment compared with the standard intubate-surfactant-extubate (IN-SUR-E) technique without increasing the risk of adverse neonatal outcomes.

Objective: To examine follow-up outcomes at corrected postnatal age (cPNA) 2 years of preterm infants previously enrolled in an RCT and treated with IN-REC-SUR-E or IN-SUR-E in 35 tertiary neonatal intensive care units.

Design, Setting, And Participants: This was a follow-up study of infants recruited into the primary RCT from 2015 to 2018 at 35 tertiary neonatal intensive care units (NICUs) in Italy.

Pediatric ultrasound practice in Italy: an exploratory survey.

Background: The aim of this exploratory survey is to describe the current state of US (ultrasound) technique across different pediatric settings nationwide.

Methods: A questionnaire was emailed to all members of the Italian Society of Pediatrics, including pediatric residents. The survey was open from December 2021 to March 2022.

The VERA software: Implementation of the acute fish toxicity endpoint and its application to pharmaceutical compounds.

The Virtual Extensive Read-Across software (VERA) is a new tool for read-across using a global similarity score, molecular groups, and structural alerts to find clusters of similar substances; these clusters are then used to identify suitable similar substances and make an assessment for the target substance. A beta version of VERA GUI is free and available at vegahub.eu; the source code of the VERA algorithm is available on GitHub.

CD4+ T Cells From Individuals With Type 1 Diabetes Respond to a Novel Class of Deamidated Peptides Formed in Pancreatic Islets.

The β-cell plays a crucial role in the pathogenesis of type 1 diabetes, in part through the posttranslational modification of self-proteins by biochemical processes such as deamidation. These neoantigens are potential triggers for breaking immune tolerance. We report the detection by LC-MS/MS of 16 novel Gln and 27 novel Asn deamidations in 14 disease-related proteins within inflammatory cytokine-stressed human islets of Langerhans.

Interferon-α promotes neo-antigen formation and preferential HLA-B-restricted antigen presentation in pancreatic β-cells.

Interferon (IFN)-α is the earliest cytokine signature observed in individuals at risk for type 1 diabetes (T1D), but its effect on the repertoire of HLA Class I (HLA-I)-bound peptides presented by pancreatic β-cells is unknown. Using immunopeptidomics, we characterized the peptide/HLA-I presentation in resting and IFN-α-exposed β-cells. IFN-α increased HLA-I expression and peptide presentation, including neo-sequences derived from alternative mRNA splicing, post-translational modifications - notably glutathionylation - and protein -splicing.

The VEGA Tool to Check the Applicability Domain Gives Greater Confidence in the Prediction of In Silico Models.

A sound assessment of in silico models and their applicability domain can support the use of new approach methodologies (NAMs) in chemical risk assessment and requires increasing the users' confidence in this approach. Several approaches have been proposed to evaluate the applicability domain of such models, but their prediction power still needs a thorough assessment. In this context, the VEGA tool capable of assessing the applicability domain of in silico models is examined for a range of toxicological endpoints.

Virtual Extensive Read-Across: A New Open-Access Software for Chemical Read-Across and Its Application to the Carcinogenicity Assessment of Botanicals.

Read-across applies the principle of similarity to identify the most similar substances to represent a given target substance in data-poor situations. However, differences between the target and the source substances exist. The present study aims to screen and assess the effect of the key components in a molecule which may escape the evaluation for read-across based only on the most similar substance(s) using a new open-access software: Virtual Extensive Read-Across (VERA).

Recognition of mRNA Splice Variant and Secretory Granule Epitopes by CD4+ T Cells in Type 1 Diabetes.

A recent discovery effort resulted in identification of novel splice variant and secretory granule antigens within the HLA class I peptidome of human islets and documentation of their recognition by CD8+ T cells from peripheral blood and human islets. In the current study, we applied a systematic discovery process to identify novel CD4+ T cell epitopes derived from these candidate antigens. We predicted 145 potential epitopes spanning unique splice junctions and within conventional secretory granule antigens and measured their in vitro binding to DRB1*04:01.

Development of new QSAR models for water, sediment, and soil half-life.

Checking the persistence of a chemical in the environment is extremely important. Regulations like REACH, the European one on chemicals, require the measurements or estimates of the half-life of the chemical in water, sediment, and soil. The use of non-testing methods, like quantitative structure-activity relationship (QSAR) models, is encouraged because it reduces costs and time.

New Models to Predict the Acute and Chronic Toxicities of Representative Species of the Main Trophic Levels of Aquatic Environments.

To assess the impact of chemicals on an aquatic environment, toxicological data for three trophic levels are needed to address the chronic and acute toxicities. The use of non-testing methods, such as predictive computational models, was proposed to avoid or reduce the need for animal models and speed up the process when there are many substances to be tested. We developed predictive models for , , and fish for acute and chronic toxicities.

Dopamine promotes aggression in mice via ventral tegmental area to lateral septum projections.

Septal-hypothalamic neuronal activity centrally mediates aggressive behavior and dopamine system hyperactivity is associated with elevated aggression. However, the causal role of dopamine in aggression and its target circuit mechanisms are largely unknown. To address this knowledge gap, we studied the modulatory role of the population- and projection-specific dopamine function in a murine model of aggressive behavior.

Structure and function differences in the prelimbic cortex to basolateral amygdala circuit mediate trait vulnerability in a novel model of acute social defeat stress in male mice.

Stressful life events are ubiquitous and well-known to negatively impact mental health. However, in both humans and animal models, there is large individual variability in how individuals respond to stress, with some but not all experiencing long-term adverse consequences. While there is growing understanding of the neurobiological underpinnings of the stress response, much less is known about how neurocircuits shaped by lifetime experiences are activated during an initial stressor and contribute to this selective vulnerability versus resilience.

SpheraCosmolife: a new tool for the risk assessment of cosmetic products.

A new, freely available software for cosmetic products has been designed that considers the regulatory framework for cosmetics. The software allows an overall toxicological evaluation of cosmetic ingredients without the need for additional testing and, depending on the product type, it applies defined exposure scenarios to derive risk for consumers. It takes regulatory thresholds into account and uses either experimental values, if available, or predictions.

QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors.

Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure-activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans.

Population-Based Analysis Of The Use Of Radium-223 For Bone-Metastatic Castration-Resistant Prostate Cancer In Ontario, And Of Factors Associated With Treatment Completion And Outcome.

Introduction: Radium-223 (Ra223) prolongs the survival and improves the quality of life of men with metastatic, castration-resistant prostate cancer (mCRPC) to bones. However, compared to other mCRPC therapies, using Ra223 comes with its unique challenges. Hence, we aimed to identify Ra223 utilization patterns under real-world conditions, as well as factors predicting treatment completion and outcome.

Development, validation and integration of in silico models to identify androgen active chemicals.

Humans are exposed to large numbers of environmental chemicals, some of which potentially interfere with the endocrine system. The identification of potential endocrine disrupting chemicals (EDCs) has gained increasing priority in the assessment of environmental hazards. The U.

A large comparison of integrated SAR/QSAR models of the Ames test for mutagenicity.

Results from the Ames test are the first outcome considered to assess the possible mutagenicity of substances. Many QSAR models and structural alerts are available to predict this endpoint. From a regulatory point of view, the recommendation from international authorities is to consider the predictions of more than one model and to combine results in order to develop conclusions about the mutagenicity risk posed by chemicals.

(Eco)toxicological maps: A new risk assessment method integrating traditional and in silico tools and its application in the Ledra River (Italy).

Contaminants giving rise to emerging concern like pharmaceuticals, personal care products, pesticides and Endocrine Disrupting Chemicals (EDCs) have been detected in wastewaters, as reported in the literature, but little is known about their (eco)toxicological effects and consequent human health impact. The present study aimed at overcoming this lack of information through the use of in silico methods integrated with traditional toxicological risk analysis. This is part of a pilot project involving the management of wastewater treatment plants in the Ledra River basin (Italy).

Exposure to aged crumb rubber reduces survival time during a stress test in earthworms (Eisenia fetida).

Solid waste management struggles with the sustainable disposal of used tires. One solution involves shredding used tires into crumb rubber and using the material as infill for artificial turf. However, crumb rubber contains hydrocarbons, organic compounds, and heavy metals, and it travels into the environment.

Integrating computational methods to predict mutagenicity of aromatic azo compounds.

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes.

Integrated strategy for mutagenicity prediction applied to food contact chemicals.

Food contamination due to unintentional leakage of chemicals from food contact materials (FCM) is a source of increasing concern. Since for many of these substances, only limited or no toxicological data are available, the development of alternative methodologies to establish rapidly and cost-efficiently level of safety concern is critical to ensure adequate consumer protection. Computational toxicology methods are considered the most promising solutions to cope with this data gap.

A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts.

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity.

Integrating in silico models to enhance predictivity for developmental toxicity.

Application of in silico models to predict developmental toxicity has demonstrated limited success particularly when employed as a single source of information. It is acknowledged that modelling the complex outcomes related to this endpoint is a challenge; however, such models have been developed and reported in the literature. The current study explored the possibility of integrating the selected public domain models (CAESAR, SARpy and P&G model) with the selected commercial modelling suites (Multicase, Leadscope and Derek Nexus) to assess if there is an increase in overall predictive performance.