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Theologidis, I.

Publications and source records attributed to Theologidis, I..

3 recordsLinked to original sources

In vitro EAS-mediated activity of Alternaria toxins

Alternaria mycotoxins represent an emerging concern due to their frequent occurrence in food and feed. However, available toxicological data remain limited. Under the current EU regulatory framework, and in line with the EFSA/ECHA/JRC guidance for the identification of endocrine disruptors (EDs), assessment of endocrine activity relies on standardized assays performed according to OECD Test Guidelines (TGs) for the estrogen-, androgen- and steroidogenesis- (EAS) modalities. Within the framework of the European Partnership for the Assessment of Risks from Chemicals (PARC), standardized in vitro methods of regulatory relevance were performed for six chemically characterized Alternaria toxins, aiming to address current regulatory gaps on EAS-mediated activity. Alternariol (AOH), alternariol monomethyl ether (AME), tenuazonic acid (TeA), altertoxin-I (ATX-I), tentoxin (TEN) and altenuene (ALT) were assessed over a broad concentration range, from 0.001 up to 60 M, depending on cytotoxicity and solubility profile of each compound. Our findings indicate estrogenic activity for AOH (PC50: 3.9 - 4.6 {micro}M) and AME (PC50: 5.2 - 8.5 {micro}M) in the estrogen receptor transactivation assay (OECD TG 455), as well as an anti-estrogenic activity for ATX-I (IC30: 0.27 - 0.37 {micro}M). Minimal positive responses were observed at high concentrations for AOH (from the dose of 3 {micro}M) and for AME (from the dose of 10 {micro}M) in the agonistic part of the androgen receptor transactivation assay (OECD TG 458), which may also reflect glucocorticoid receptor activation. No effects on estradiol or testosterone production were observed for any of the tested Alternaria compounds in the steroidogenesis assay (OECD TG 456).

pharmacology and toxicology↗

Analytical Choices Drive Toxicogenomic Potency Estimates: A Systematic Evaluation of Transcriptomic Points of Departure

Omics technologies are increasingly integrated into next-generation risk assessment, yet quantitative toxicogenomics outcomes remain highly dependent on analytical choices, motivating a systematic evaluation of how bioinformatics workflows influence hazard characterization and transcriptomic Points of Departure (tPOD). Here, we applied five independent transcriptomics pipelines to a shared dataset of RPTEC-TERT1 kidney cells exposed to cisplatin across multiple concentrations and timepoints, comparing effects of pre-processing, benchmark concentration modeling, and pathway-based interpretation strategies. Across workflows, substantial variability was observed in gene-level benchmark concentrations (BMCs), primarily driven by differences in normalization, filtering, and especially the modeling software used. Despite this variability, convergence increased at later timepoints as transcriptional responses strengthened, with 24 h consistently identified as the most sensitive timepoint at the gene level. Aggregation of gene-level BMCs into pathway-based metrics reduced variability but did not eliminate it, with pathway definition emerging as a major determinant of sensitivity estimates. Notably, distinct pathway resources showed minimal gene overlap, and smaller, biologically coherent gene sets (e.g., co-expression modules and biomarker panels) produced lower and less dispersed BMCs compared with broader pathway annotations. Furthermore, direct modeling of pathway activity scores yielded systematically different sensitivity estimates relative to median-based aggregation, with method-dependent conservativeness influenced by pathway coverage and response strength. Overall, our findings demonstrate that both analytical workflow design and pathway selection critically shape toxicogenomic-derived potency estimates, highlighting the need for harmonized, transparent methodologies to enable robust application of transcriptomics in chemical safety assessment and regulatory decision-making.

bioinformatics↗

Partial selfing eliminates inbreeding depression while maintaining genetic diversity

Classical theory on the origin and evolution of selfing and outcrossing relies on the role of inbreeding depression created by unlinked partially-deleterious recessive alleles to predict that individuals from natural populations predominantly self or outcross. Comparative data indicates, however, that maintenance of partial selfing and outcrossing at intermediate frequencies is common in nature. In part to explain the presence of mixed reproductive modes within populations, several hypotheses regarding the evolution of inbreeding depression have been put forward based on the complex interaction of linkage and identity disequilibrium among fitness loci, together with Hill-Robertson effects. We here ask what is the genetic basis of inbreeding depression so that populations with intermediate selfing rates can eliminate it while maintain potentially adaptive genetic diversity. For this, we use experimental evolution in the nematode C. elegans under partial selfing and compare it to the experimental evolution of populations evolved under exclusive selfing and predominant outcrossing. We find that the ancestral risk of extinction upon enforced inbreeding by selfing is maintained when populations evolve under predominant outcrossing, but reduced when populations evolve under partial or exclusive selfing. Analysis of genome-wide single-nucleotide polymorphism (SNP) during experimental evolution and after enforced inbreeding suggests that, under partial selfing, populations were purged of unlinked deleterious recessive alleles that segregate in the ancestral population, which in turn allowed the expression of unlinked overdominant fitness loci. Taken together, these observations indicate that populations evolving under partial selfing gain the short-term benefits of selfing, in purging deleterious recessive alleles, but also the long-term benefits of outcrossing, in maintaining genetic diversity that may important for future adaptation.

evolutionary biology↗