Auditory stimuli suppress contextual fear responses in safety learning independent of a possible safety meaning.

Safety learning allows the identification of non-threatening situations, a learning process instrumental for survival and psychic health. In contrast to fear learning, in which a sensory cue (conditioned stimulus, CS) is temporally linked to a mildly aversive stimulus (US), safety learning is studied by presenting the CS and US in an explicitly unpaired fashion. This leads to conditioned inhibition of fear responses, in which sensory cues can acquire a safety meaning (CS-).

Distinct Roles of Medial Prefrontal Cortex Subregions in the Consolidation and Recall of Remote Spatial Memories.

It is a common belief that memories, over time, become progressively independent of the hippocampus and are gradually stored in cortical areas. This view is mainly based on evidence showing that prefrontal cortex (PFC) manipulations impair the retrieval of remote memories, while hippocampal inhibition does not. More controversial is whether activity in the medial PFC is required immediately after learning to initiate consolidation.

Prediction of Endocrine-Disrupting Chemicals Related to Estrogen, Androgen, and Thyroid Hormone (EAT) Modalities Using Transcriptomics Data and Machine Learning.

Endocrine-disrupting chemicals (EDCs) are chemicals that can interfere with homeostatic processes. They are a major concern for public health, and they can cause adverse long-term effects such as cancer, intellectual impairment, obesity, diabetes, and male infertility. The endocrine system is a complex machinery, with the estrogen (E), androgen (A), and thyroid hormone (T) modes of action being of major importance.

Can "Hazard-Cost-Effectiveness Analysis" improve the risk management of chemicals under REACH?

Cost-Effectiveness Analysis (CEA) is a decision-making framework to prioritize policy decisions for chemicals. Differences in hazard profiles among chemicals are not integrated in CEA under the EU REACH Regulation, which could limit its relevance. Another concern is that two different economic decision support methods (CEA for chemicals considered as PBTs or vPvBs from a regulatory perspective and Cost Benefit Analysis (CBA) for others) are used under REACH.

A peripheral signature of Alzheimer's disease featuring microbiota-gut-brain axis markers.

Background: Increasing evidence links the gut microbiota (GM) to Alzheimer's disease (AD) but the mechanisms through which gut bacteria influence the brain are still unclear. This study tests the hypothesis that GM and mediators of the microbiota-gut-brain axis (MGBA) are associated with the amyloid cascade in sporadic AD.

Methods: We included 34 patients with cognitive impairment due to AD (CI-AD), 37 patients with cognitive impairment not due to AD (CI-NAD), and 13 cognitively unimpaired persons (CU).

Transcriptomics and miRNomics data integration in lymphoblastoid cells highlights the key role of immune-related functions in lithium treatment response in Bipolar disorder.

Background: Bipolar Disorder (BD) is a complex mental disease characterized by recurrent episodes of mania and depression. Lithium (Li) represents the mainstay of BD pharmacotherapy, despite the narrow therapeutic index and the high variability in treatment response. However, although several studies have been conducted, the molecular mechanisms underlying Li therapeutic effects remain unclear.

Read-across and new approach methodologies applied in a 10-step framework for cosmetics safety assessment - A case study with parabens.

Parabens are esters of para-hydroxybenzoic acid that have been used as preservatives in many types of products for decades including agrochemicals, pharmaceuticals, food and cosmetics. This illustrative case study with propylparaben (PP) demonstrates a 10-step read-across (RAX) framework in practice. It aims at establishing a proof-of-concept for the value added by new approach methodologies (NAMs) in read-across (RAX) for use in a next-generation risk assessment (NGRA) in order to assess consumer safety after exposure to PP-containing cosmetics.

In Silico Prediction of Chemically Induced Mutagenicity: A Weight of Evidence Approach Integrating Information from QSAR Models and Read-Across Predictions.

Information on genotoxicity is an essential piece of information in the framework of several regulations aimed at evaluating chemical toxicity. In this context, QSAR models that can predict Ames genotoxicity can conveniently provide relevant information. Indeed, they can be straightforwardly and rapidly used for predicting the presence or absence of genotoxic hazards associated with the interactions of chemicals with DNA.

The Complex Molecular Picture of Gut and Oral Microbiota-Brain-Depression System: What We Know and What We Need to Know.

Major depressive disorder (MDD) is a complex mental disorder where the neurochemical, neuroendocrine, immune, and metabolic systems are impaired. The microbiota-gut-brain axis is a bidirectional network where the central and enteric nervous systems are linked through the same endocrine, immune, neural, and metabolic routes dysregulated in MDD. Thus, gut-brain axis abnormalities in MDD patients may, at least in part, account for the symptomatic features associated with MDD.

Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action.

Read-across approaches often remain inconclusive as they do not provide sufficient evidence on a common mode of action across the category members. This read-across case study on thirteen, structurally similar, branched aliphatic carboxylic acids investigates the concept of using human-based new approach methods, such as in vitro and in silico models, to demonstrate biological similarity. Five out of the thirteen analogues have preclinical in vivo studies.

Evaluation of the OECD QSAR toolbox automatic workflow for the prediction of the acute toxicity of organic chemicals to fathead minnow.

Regulatory frameworks require information on acute fish toxicity to ensure environmental protection. The experimental assessment of this property relies on a substantial number of fish to be tested and it is in conflict with the current drive to replace in vivo testing. For this reason, alternatives to in vivo testing have been proposed during the past years.

Prediction of the Partition Coefficient between Adipose Tissue and Blood for Environmental Chemicals: From Single QSAR Models to an Integrated Approach.

The adipose tissue:blood partition coefficient is a key-endpoint to predict the pharmacokinetics of chemicals in humans and animals, since other organ:blood affinities can be estimated as a function of this parameter. We performed a search in the literature to select all the available rat in vivo data. This approach resulted into two improvements to existing models: a homogeneous definition of the endpoint and an expanded data collection.

Short-Chain Fatty Acids and Lipopolysaccharide as Mediators Between Gut Dysbiosis and Amyloid Pathology in Alzheimer's Disease.

Background: Metagenomic data support an association between certain bacterial strains and Alzheimer's disease (AD), but their functional dynamics remain elusive.

Objective: To investigate the association between amyloid pathology, bacterial products such as lipopolysaccharide (LPS) and short chain fatty acids (SCFAs: acetate, valerate, butyrate), inflammatory mediators, and markers of endothelial dysfunction in AD.

Methods: Eighty-nine older persons with cognitive performance from normal to dementia underwent florbetapir amyloid PET and blood collection.

Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples.

Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples.

QSAR Modeling of ToxCast Assays Relevant to the Molecular Initiating Events of AOPs Leading to Hepatic Steatosis.

Nonalcoholic hepatic steatosis is a worldwide epidemiological concern since it is among the most prominent hepatic diseases. Indeed, research in toxicology and epidemiology has gathered evidence that exposure to endocrine disruptors can perturb cellular homeostasis and cause this disease. Therefore, assessing the likelihood of a chemical to trigger hepatic steatosis is a matter of the utmost importance.

Adverse outcome pathways: opportunities, limitations and open questions.

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established.

In Silico Prediction of Chemically Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results.

Information on genotoxicity is an essential piece of information gathering for a comprehensive toxicological characterization of chemicals. Several QSAR models that can predict Ames genotoxicity are freely available for download from the Internet and they can provide relevant information for the toxicological profiling of chemicals. Indeed, they can be straightforwardly used for predicting the presence or absence of genotoxic hazards associated with the interactions of chemicals with DNA.

Results of a round-robin exercise on read-across.

A round-robin exercise was conducted within the CALEIDOS LIFE project. The participants were invited to assess the hazard posed by a substance, applying in silico methods and read-across approaches. The exercise was based on three endpoints: mutagenicity, bioconcentration factor and fish acute toxicity.

Evaluation of QSAR models for the prediction of ames genotoxicity: a retrospective exercise on the chemical substances registered under the EU REACH regulation.

We evaluated the performance of seven freely available quantitative structure-activity relationship models predicting Ames genotoxicity thanks to a dataset of chemicals that were registered under the EU Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation. The performance of the models was estimated according to Cooper's statistics and Matthew's Correlation Coefficients (MCC). The Benigni/Bossa rule base originally implemented in Toxtree and re-implemented within the Virtual models for property Evaluation of chemicals within a Global Architecture (VEGA) platform displayed the best performance (accuracy = 92%, sensitivity = 83%, specificity = 93%, MCC = 0.

Photolysis of estrone generates estrogenic photoproducts with higher activity than the parent compound.

In the present study, we aimed to evaluate the effect of UV-visible irradiation on the estrogenicity of an estrone aqueous solution by using chemical analysis associated with an in vitro bioassay and in silico analysis. An estrone aqueous solution was irradiated with an UV-visible high-pressure mercury lamp. By using the MELN in vitro cellular bioassay, based on the induction of a luciferase reporter gene upon the activation of the estrogen receptor by chemicals, we showed that the estrogenic potency of the solution increased after irradiation.

A physiologically based toxicokinetic model for the zebrafish Danio rerio.

Zebrafish (Danio rerio) is a widely used model for toxicological studies, in particular those related to investigations on endocrine disruption. The development and regulatory use of in vivo and in vitro tests based on this species can be enhanced by toxicokinetic modeling. For this reason, we propose a physiologically based toxicokinetic (PBTK) model for zebrafish describing the uptake and disposition of organic chemicals.

Modelling Structure Activity Landscapes with Cliffs: a Kernel Regression-Based Approach.

Quantitative Structure-Activity Relationship (QSAR) models are increasingly used in hazard and risk assessment. Even when models with linear relationships between activity and a small number of descriptors are built and validated regarding predictivity and statistical assumptions, similar structures can exhibit large differences in activity known as similarity paradoxes or activity cliffs. In order to reduce the impact that similarity paradoxes can have on predictions we have devised a statistical method based on Nadaraya-Watson kernel regression.