Users' perception of the OH-EpiCap evaluation tool based on its application to nine national antimicrobial resistance surveillance systems.

Introduction: Antimicrobial resistance (AMR) is a One Health (OH) challenge. To achieve or maintain an effective and efficient AMR surveillance system, it is crucial to evaluate its performance in meeting the proposed objectives, while complying with resource restrictions. The OH-EpiCap tool was created to evaluate the degree of compliance of hazard surveillance activities with essential OH concepts across the following dimensions: organization, operational activities, and impact of the surveillance system.

Helping to heal nature and ourselves through human-rights-based and gender-responsive One Health.

The health of our planet and humanity is threatened by biodiversity loss, disease and climate crises that are unprecedented in human history, driven by our insatiable consumption and unsustainable production patterns, particularly food systems. The One Health approach is a pathway to synergistically addressing outcomes in term of health and sustainability, but gender issues at the One Health and biodiversity nexus are largely ignored. By examining the roles and responsibilities of Indigenous and Local People, and especially women, in conserving natural resources, and the social costs of living at the Human-Animal-Environment interface under current conservation strategies, we show that women bear a disproportionate health, poverty and climate burden, despite having pivotal roles in conserving biodiversity.

Probabilistic approach for assessing cancer risk due to benzo[a]pyrene in barbecued meat: Informing advice for population groups.

Background: Consumption of meat prepared by barbecuing is associated with risk of cancer due to formation of carcinogenic compounds including benzo[a]pyrene (BaP). Assessment of a population's risk of disease and people's individual probability of disease given specific consumer attributes may direct food safety strategies to where impact on public health is largest. The aim of this study was to propose a model that estimates the risk of cancer caused by exposure to BaP from barbecued meat in Denmark, and to estimate the probability of developing cancer in subgroups of the population given different barbecuing frequencies.

A Systems Approach to Evaluate One Health Initiatives.

Challenges calling for integrated approaches to health, such as the One Health (OH) approach, typically arise from the intertwined spheres of humans, animals, and ecosystems constituting their environment. Initiatives addressing such wicked problems commonly consist of complex structures and dynamics. As a result of the EU COST Action (TD 1404) "Network for Evaluation of One Health" (NEOH), we propose an evaluation framework anchored in systems theory to address the intrinsic complexity of OH initiatives and regard them as subsystems of the context within which they operate.

Framework to Define Structure and Boundaries of Complex Health Intervention Systems: The ALERT Project.

Health intervention systems are complex and subject to multiple variables in different phases of implementation. This constitutes a concrete challenge for the application of translational science in real life. Complex systems as health-oriented interventions call for interdisciplinary approaches with carefully defined system boundaries.

Application of ERICA index to evaluation of soil ecosystem health according to sustainability threshold for chemical impact.

The aim of the improved ERICA model for risk assessment (Boriani et al., 2010) is to give an instrument able to measure the effect of xenobiotics introduced into the environment. This will be of great help for "green" processes and sustainable industries and may help to advertise their products as safe for the environment following impact assessment.

Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF) in fish.

Background: Bioconcentration factor (BCF) describes the behaviour of a chemical in terms of its likelihood of concentrating in organisms in the environment. It is a fundamental property in recent regulations, such as the European Community Regulation on chemicals and their safe use or the Globally Harmonized System for classification, labelling and packaging. These new regulations consider the possibility of reducing or waiving animal tests using alternative methods, such as in silico methods.

ERICA: A multiparametric toxicological risk index for the assessment of environmental healthiness.

A risk assessment strategy considering the impact of chemicals on the whole ecosystem has been developed in order to create a sound and useful method for quantifying and comparing the global risk posed by the main different hazardous chemicals found in the environment. This index, called Environmental Risk Index for Chemical Assessment (ERICA), merges in a single number the environmental assessment, the human health risk assessment and the uncertainty due to missing or uncertain data. ERICA uses a dedicated scoring system with parameters for the main characteristics of the pollutants.

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF).

The aim was to develop a reliable and practical quantitative structure-activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models.

Structural features of diverse ligands influencing binding affinities to estrogen alpha and estrogen beta receptors. Part I: Molecular descriptors calculated from minimal energy conformation of isolated ligands.

We report a neural network modeling approach combined with genetic algorithm for prediction of experimental binding affinity to human Estrogen Receptor alpha and beta (ER-alpha and ER-beta) of a diverse set of chemicals. The counterpropagation artificial neural network is used as a modeling method. Structural features of ligands having the strongest influence to the binding affinities were investigated.

Structural features of diverse ligands influencing binding affinities to estrogen alpha and estrogen beta receptors. Part II. Molecular descriptors calculated from conformation of the ligands in the complex resulting from previous docking study.

A QSAR study is reported, in which the relationship between chemical structure of a set of compounds and the binding affinity to human estrogen receptor alpha and beta (ER-alpha and ER-beta) is modelled. Counterpropagation neural networks are used to predict experimental binding affinity of a range of substances. Several compounds as estrogenic chemicals, phytoestrogens, and natural and synthetic estrogens are treated with a structure-based approach that involves the protein structure.

Regulatory perspectives in the use and validation of QSAR. A case study: DEMETRA model for Daphnia toxicity.

The DEMETRA acute toxicity model toward the water flea (Daphnia magna)was used as a case studyto outline a validation method compatible with regulatory use. Reliability, predictive power, uncertainty, and applicability were verified with an external test set of pesticides. Predictions for this external set using the DEMETRA model, developed ad hoc for pesticides, were compared with the results using ECOSAR and TOPKAT as benchmarks.

A protocol to select high quality datasets of ecotoxicity values for pesticides.

The key to any QSAR model is the underlying dataset. In order to construct a reliable dataset to develop a QSAR model for pesticide toxicity, we have derived a protocol to critically evaluate the quality of the underlying data. In developing an appropriate protocol that would enable data to be selected in constructing a QSAR, we concentrated on one toxicity end point, the 96 h LC50 from the acute rainbow trout study.