Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction.

Assessing chemical safety is essential to evaluate the potential risks of chemical exposure to human health and the environment. Traditional methods relying on animal testing are being replaced by 3R (reduction, refinement, and replacement) principle-based alternatives, mainly depending on in vitro test methods and the Adverse Outcome Pathway framework. However, these approaches often focus on the properties of the compound, missing the broader chemical-biological interaction perspective. Currently, the lack of comprehensive molecular characterization of the in vitro test system results in limited real-world representation and contextualization of the toxicological effect under study. Leveraging omics data strengthens the understanding of the responses of different biological systems, emphasizing holistic chemical-biological interactions when developing in vitro methods. Here, we discuss the relevance of meticulous test system characterization on two safety assessment relevant scenarios and how omics-based, data-driven approaches can improve the future generation of alternative methods.

Soil Fertility and Phosphorus Leaching in Irrigated Calcareous Soils of the Mediterranean Region.

To ensure soil quality and soil health, it is necessary to improve fertilization practices while minimizing environmental impacts. The aim of this study was to record the state of the art on soil fertility related to fertilization management (organic and/or mineral) and to detect environmental challenges in highly productive fields. A soil survey was set up in a new irrigated area (c. 20 years old), in the north-eastern part of Spain, which is mainly devoted to double annual crop rotations of cereals and maize. The area also supports an important animal rearing activity. The survey covered 733 ha of calcareous soils, owned by 35 farmers. At each farm, fertilization management was recorded, and soil was analyzed for nutrients and heavy metals. Multivariate analyses were performed. Total N, P, Cu and Zn, and available P, Cu, Zn and Mn soil concentrations were associated to the use of organic amendments. Heavy metals concentrations were below established thresholds. Available P (Olsen-P) was identified as an indicator of the previously adopted fertilization management and of the potential of P leaching towards deeper soil layers. Regression analyses were performed. A displacement of available P from the uppermost layer (0-0.3 m) occurs in the breakpoint of 86 mg P kg-1 soil. Preventative actions might be established from 53 mg P kg-1 soil due to the slowdown in P immobilization. Our results reinforce the importance of setting up P threshold soil levels for best practices of fertilization, as a basis for sustainable agriculture intensification.

Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation.

The pharmacological arsenal against the COVID-19 pandemic is largely based on generic anti-inflammatory strategies or poorly scalable solutions. Moreover, as the ongoing vaccination campaign is rolling slower than wished, affordable and effective therapeutics are needed. To this end, there is increasing attention toward computational methods for drug repositioning and de novo drug design. Here, multiple data-driven computational approaches are systematically integrated to perform a virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the list of prioritized drugs, a subset of representative candidates to test in human cells is selected. Two compounds, 7-hydroxystaurosporine and bafetinib, show synergistic antiviral effects in vitro and strongly inhibit viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, the relevant chemical substructures of the identified drugs are extracted to provide a chemical vocabulary that may help to design new effective drugs.

A unifying concept for the dependence of whole-crop N : P ratio on biomass: theory and experiment.

BACKGROUND AND AIMS: Numerous estimates have been made of the concentrations of N and P required for good growth of crop species but they have not been defined by any unifying model. The aim of the present study was to develop such a model for the dependence of the N : P ratio on crop mass, to test its validity and to use it to identify elements of similarity between different crop species and wild plants. METHODS: A model was derived between plant N : P ratio (Rw) and its dry biomass per unit area (W) during growth with near optimum nutrition by considering that plants consist of growth-related tissue and storage-related tissue with N : P ratios Rg and Rs, respectively. Testing and calibration against experimental data on different crop species led to a simple equation between Rw and W which was tested against independent experimental data. KEY RESULTS: The validity of the model and equation was supported by 365 measurements of Rw in 38 field experiments on crops. Rg and Rs remained approximately constant throughout growth, with average values of 11.8 and 5.8 by mass. The model also approximately predicted the relationships between leaf N and P concentrations in 124 advisory estimates on immature tissues and in 385 wild species from published global surveys. CONCLUSIONS: The N : P ratio of the biomass of very different crops, during growth with near optimum levels of nutrients, is defined entirely in terms of crop biomass, an average N : P ratio of the storage/structure-related tissue of the crop and an average N : P ratio of the growth-related tissue. The latter is similar to that found in leaves of many wild plant species, and even micro-organisms and terrestrial and freshwater autotrophs.