Federal Institute for Risk Assessment

Bacteriophage-assisted non-thermal food processing (BANTFP) is a potential biocontrol strategy for reducing foodborne pathogens while preserving product quality. When used simultaneously or sequentially with novel non-thermal food processing technologies, phages can contribute to the reduction of the microbes (typically 1–3 Δlog, but up to 5–8 Δlog in optimized multi-hurdle systems). However, the current evidence is fragmented and strongly biased toward high-pressure studies, whereas data for the use of pulsed electric fields, ultrasound, and cold atmospheric plasma remain limited. Key challenges include phage stability under processing conditions, their interactions with complex food matrices, and the risk of resistance development of the target bacteria. Further research is required to identify optimal treatment sequences, quantify true synergistic effects, and evaluate performance in realistic food environments. Such efforts are essential to refine phage–NTFP combinations, ensuring their efficiency and regulatory acceptance at industrial scale and contributing to safe, innovative and sustainable food processing systems. • Phage biocontrol approaches can assist innovative non-thermal food processing. • New hurdle technologies use synergistic effects in food pathogens inactivation. • Bacteriophage-assisted non- thermal food processing (BANTFP) maintains food quality. • BANTFP selectively targets pathogens while preserving beneficial microorganisms. • BANTFP is an alternative to chemical preservatives and thermal treatments.

BackgroundIt is an established toxicological principle that the inhalation pathogenicity of respirable and biodurable fibres is caused by excessive fibre length as alveolar macrophages fail to uptake and remove such fibres. However, studies on carbon nanotubes showed that this principle needs revision, as thin, flexible variants showed reduced fibre-specific toxicity. One potential explanation is that the low flexural rigidity of thin fibres enables macrophages to bend and internalize even those that are long relative to the cell size. To evaluate this proposed “rigidity hypothesis,” the mechanisms governing the uptake of flexible long fibres that determine a critical threshold value for flexural rigidity require clarification.MethodsWe exposed NR8383 rat alveolar macrophages to three silver nanowire variants differing in diameter and length. Time-lapse microscopy captured fibre uptake processes. Successful internalization of long fibres was found to require fibre bending during uptake. A mechanical model was developed by combining established cytoskeletal biophysics with the observed fibre deformation dynamics. As flexural rigidity describes fibre behaviour under load, our model estimated rigidity by reproducing the observed bent fibre shape. By defining limit cases for physically ‘weak’ and ‘strong’ NR8383 macrophages, i.e., assuming upper bounds on the forces generated by their cytoskeletal nanomachinery, our model enabled us to derive a range for the critical fibre rigidity threshold.Results and conclusionA macrophage was observed bending an exceptionally long fibre (~ 140 μm) first into an arc and then a spiral for full internalization, initiated by a pseudopod extending along the fibre and buckling the internalized segment. Our model can reproduce such behaviour. It yielded a flexural rigidity of 20 mN·nm² for this fibre. Predicted critical rigidity limits for fibres that just fit into NR8383 macrophages range from 3 to 62 mN·nm². Using the conservative lower bound, long and biodurable fibres with a rigidity lower than 3 mN·nm² are expected to be readily phagocytized by this cell line. Although this rigidity scale may not be directly translatable to human alveolar macrophages, our experimental findings and their modeling emphasize the key role of rigidity in fibre–cell interactions. Fibre rigidity is therefore central for material safety aspects and sustainable product design.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12989-026-00666-9.

Objectives: this cross-sectional study investigated the association between the Cardiometabolic Index (CMI) and heart failure (HF) prevalence in hypertensive individuals. Methods: this cross-sectional study analyzed dataset from the National Health and Nutrition Examination Survey (NHANES) 2009-2018, focusing on hypertensive adults with complete information on CMI and HF prevalence, employed CMI based on the following formula: [waist circumference (cm)/height (cm)] × [TG (mmol/L)/HDL-C (mmol/L)]. The relationships between CMI and HF prevalence were assessed using weighted multivariable logistic regression and subgroup analysis. Additionally, the threshold effect was determined by applying a two-piece linear regression model. Results: a total of 3,706 subjects with hypertension were enrolled, with heart failure being reported in 6.77 % of cases. A positive relationship was observed between CMI and HF prevalence. In the fully adjusted model, a one-unit rise in CMI corresponded to a 14 % increased likelihood of HF (OR = 1.14, 95 % CI: 1.03-1.26). Subjects in the top CMI tertile were 49 % more likely to progress to HF than those in the bottom tertile (OR = 1.49, 95 % CI: 1.01-2.21). We did not detect statistically significant interactions across subgroups. An inverted U-shaped correlation was identified between CMI and HF prevalence. The breakpoint was identified at 6.00. On the left of the breakpoint, a positive relationship between CMI and HF prevalence (OR = 1.56, 95 % CI: 1.35-1.79) was observed. Conclusions: these findings suggest a positive association between elevated CMI levels and a higher prevalence of HF in hypertensive adults.

Abstract Antimicrobial resistance (AMR) is a global public health threat. Mortality and poor treatment outcomes are the hallmark consequences of AMR. Conventional antimicrobial susceptibility testing (AST) is slow, limited in coverage, and dependent on laboratory infrastructure, creating delays in clinical decision-making. In this study, we developed a hybrid deep learning framework for broad-spectrum antimicrobial resistance prediction by analyzing bacterial genome assemblies and paired antimicrobial susceptibility outcomes. Genome assemblies were encoded using 6-mer frequency representations and engineering antimicrobial susceptibility phenotypes into genome–antibiotic pairs for binary prediction. The proposed model integrates convolutional neural networks (CNNs) for local sequence feature extraction, bidirectional long short-term memory (BiLSTM) networks to capture long-range genomic dependencies, and an attention mechanism to improve interpretability. Model evaluation achieved an accuracy of 0.71 and AUROC of 0.77 at a resistance decision threshold of 0.55, with balanced accuracy of 0.70 and AUPRC of 0.49. The results demonstrate variable predictive performance across antibiotics and organism groups, supporting the need for subgroup-level evaluation and threshold tuning. This study demonstrates that a hybrid CNN–BiLSTM–Attention model can rapidly predict antimicrobial resistance from genome-derived k-mer features while incorporating organism and antibiotic metadata for broad-spectrum AST prediction. The framework provides a scalable approach for genome-based susceptibility prediction and supports further development toward clinically deployable AMR decision-support tools.

Thyroid hormone (TH) system-disrupting chemicals can cause adverse effects, including neurodevelopmental deficits. While current in vivo test methods reliably detect disruptions from potent antithyroid drugs such as propylthiouracil (PTU) and methimazole (MMI) through thyroid gland histopathology, they may lack sensitivity for less potent chemicals or those acting through alternative mechanisms. A more systemic, mechanism-based approach may therefore be needed to identify TH system-disrupting capacity. Here, we assessed the effects of the environmental chemicals perfluorooctane sulfonate (PFOS) and tetrabromobisphenol A (TBBPA) on the TH system using in vitro and in vivo approaches. PFOS inhibited the TH transmembrane transporter monocarboxylate transporter 8 (MCT8) and the sodium-iodide symporter (NIS). TBBPA inhibited MCT8, the enzyme activity of all three iodothyronine deiodinases (DIO1/2/3), and thyroperoxidase (TPO). In time-mated rats, in utero and early postnatal exposure to PFOS (0.4 or 0.8 mg/kg bw/day) or TBBPA (250 or 500 mg/kg bw/day) reduced serum TH concentrations in dams and offspring, but neither chemical altered thyroid stimulating hormone (TSH) in offspring. We observed no, or only modest, effects on thyroid gland histology. Both chemicals altered TH metabolism by deiodinase and dehalogenase enzymes and reduced iodine content in the thyroid. In the fetal brain, PFOS increased T3, while TBBPA decreased T4 in the postnatal brain. These findings demonstrate distinct TH-disrupting profiles of PFOS and TBBPA, differing from classic antithyroid compounds PTU and MMI. Our results highlight the need for more comprehensive systems-approaches to capture TH disrupting chemicals acting through diverse mechanisms.

ABSTRACTRecently, cases of human infection with rat hepatitis E virus (ratHEV, Rocahepevirus ratti) have been reported worldwide. Due to the significant genetic differences between ratHEV and human HEV genotypes 1–4 (Paslahepevirus balayani), current HEV diagnostic assays are unable to detect ratHEV. The aim was to establish and validate a laboratory‐developed ratHEV RT‐qPCR assay for use with human plasma and stool samples on a fully automated, high‐throughput platform. Published primers and probes were optimized for use on cobas 5800/6800/8800 systems using European Union In Vitro Diagnostics Regulation (IVDR)‐grade reagents, including an RNA full‐process inhibition control. Analytical sensitivity (21 repeats), linear range (five repeats) and precision (three repeats over 3 days) were evaluated using viral particles from cell culture (MN450851.1). The inclusivity was verified using DNA oligonucleotides and known positive samples (rat liver and human serum). The limits of detection were 98.9 copies/ml in plasma and 60.3 copies/ml in stool, and the assay showed excellent linearity over at least 5 log (r2: 0.991 in plasma and 0.9989 in stool) and high precision (< 0.62 ct). The assay reliably detected different ratHEV C1 subgenotypes, returning positive results for all 11 rat liver samples and one known ratHEV RNA‐positive human plasma sample, while no false positives were detected in the broad cross‐reactivity set (n = 41). In the pilot ratHEV surveillance cohort, 1.1% of plasma samples (n = 1999) were positive for HEV RNA, but none were positive for ratHEV RNA. Our new, fully automated, lab‐developed ratHEV assay can be used in compliance with the IVDR for routine human diagnostics. Further studies are needed to determine the clinical relevance in different human cohorts.

The ultrasonic vocalizations (USVs) of house mice (Mus musculus) have a surprisingly complex structure and have been actively studied as a model for applied questions in biomedical science. Despite this, the functional significance of different USV types and their use during natural social behaviour in diverse groups remains unclear. In this pilot long-term study, we examined the ultrasound activity of female mice housed in stable groups within an enriched environment, focusing on how behavioural context influences USV time-frequency characteristics, call type occurrence, and nonlinear phenomena. Our findings show that USVs are mainly produced in bouts, and bouts containing ten or more variable calls always accompanying direct social interactions. USV variables and types varied markedly depending on the interaction context. During aggressive encounters, USVs and entire bouts became longer, vocalization time and frequency modulation increased, while peak and minimum fundamental frequencies decreased. Additionally, aggressive context was characterized by a higher prevalence of multi-component and complex-low USVs (with peak frequency < 50 kHz), and increased nonlinear phenomena. These results suggest that USV features closely reflect emotional arousal (intensity) and probably also valence (positive/negative) in female mice during social hierarchy formation and maintenance. Notably, the relationship between arousal and nonlinear vocal phenomena in mice USVs follows patterns observed in audible vocalizations of other mammals (increase with arousal). In the future, complex-low USVs could potentially serve as non-invasive indicators of negative emotional expression in groups of female mice. This opens new possibilities for acoustic home-cage monitoring aimed at welfare assessment and other applied uses.

Cell Painting (CP) is a widely used imaging-based method for untargeted high-throughput phenotypic profiling (HTPP) of compounds or genetic perturbations that lead to morphological changes in cells. Here, we describe the Cell Painting PLUS (CPP) method, an efficient, robust, and broadly applicable HTPP approach that overcomes certain boundaries of the standard CP method. In CPP, an elution buffer enables iterative staining, elution, and re-staining of the same cells with at least seven fluorescent dyes labeling nine cellular compartments and organelles. In this way, CPP provides higher flexibility in selecting and combining various fluorescent dyes for customized multiplexing of phenotypic profiling screens. The separate imaging and analysis of single dyes in individual channels ensures a high specificity of the generated phenotypic profiles and thus enables precise insights into cellular processes and dysfunction. This chapter describes the process of generating CPP phenotypic profiling data that is based on automated staining and imaging procedures as well as a customized image analysis pipeline using the Harmony software. The resulting data can be further processed and visualized using customized KNIME software-based pipelines as described in von Coburg et al. (Nat Commun 16:3857, 2025) for unbiased and in-depth characterization of the modes-of-action of compounds or genetic perturbations in toxicology and biomedical research.

Plasticizers like di-(2-ethylhexyl) phthalate (DEHP) are commonly used in medical devices to enhance plastic flexibility. DEHP is classified as a CMR1b substance due to its adverse effects on reproduction and fertility, and it has been linked to neurodevelopmental disorders such as ADHD, autism spectrum disorder, and learning disabilities. While DEHP is scheduled for phase-out by 2030, data on the developmental neurotoxicity (DNT) of alternative plasticizers remain scarce. We evaluated the DNT potential of DEHP and three alternative plasticizers: di-(2-ethylhexyl) terephthalate (DEHT), di-(2-ethylhexyl) adipate (DEHA), and tris-(2-ethylhexyl) trimellitate (TOTM), aiming to identify safer substitutes, particularly for neonates in neonatal intensive care units (NICUs). The human Neurosphere Assay was used to assess plasticizer effects on seven key neurodevelopmental processes: neural progenitor cell (NPC) proliferation, migration of radial glia, neurons, and oligodendrocytes, neurite outgrowth, and differentiation of neurons and oligodendrocytes. Concentration-response analyses provided benchmark concentrations (BMCs) and lowest observed adverse effect concentrations (LOAECs). Gene expression profiling provided mechanistic insights, and toxicity was ranked using the most sensitive endpoint (MSE) and ToxPi Tool. DEHP and TOTM showed the highest DNT potential, with NPC proliferation as the MSE. DEHT impacted oligodendrocyte differentiation, while no BMC was determined for DEHA within the tested concentrations. Considering an exposure scenario in NICUs, the estimated neonatal DEHP plasma levels exceeded the LOAEC for NPC proliferation, raising concerns for DNT. Overall, DEHA emerged as the least hazardous alternative for neurodevelopment, highlighting the value of combined human-relevant in vitro phenomics and human biomonitoring for DNT hazard evaluation.