Università Cattolica del Sacro Cuore Showcase

Supplementary table 1. Least squares means and associated SEM for reproductive parameters in lactating Holstein cows from 7 to 56 DIM (n = 10/group; Control = CTR; Mycotoxin = MTX; Mycotoxin-deactivating product = MDP). Three primiparous (P) and 7 multiparous (M) (lactation no.: CTR = 3.33±1.50, MTX = 3.67 ±1.33, MDP 3.5±1.15) cows were enrolled per group. The CTR diet was supplemented with a placebo (0.34% DM), the MTX ration was added a mycotoxin contaminated culture medium (0.19%) and placebo (0.19%), whereas the MDP was supplemented with the culture medium (0.19%) and MDP product (Mycofix, BIOMIN Holding, GmbH, Tulln, Austria; 0.15%), a mycotoxin-deactivating product. Different letters indicate statistical differences (a-b-c P  0.05).

This dataset accompanies and expands upon the article "The Rise of Computational Images: The Role of Star-Targeting Photospectroscopy", offering a systematic reorganization of the key concepts, sources, and research questions emerging from a historical-epistemological investigation of nineteenth-century spectroscopy, interpreted through the lens of computational imaging and media archaeology. From a media-archaeological perspective, the dataset reconstructs the complex interplay of visual practices and technical-scientific apparatuses that, throughout the nineteenth century, contributed to the emergence of a regime of visibility grounded in automatic registration, the minimization of subjective interpretation, and the rise of "operative invisuality". Particular focus is placed on spectral maps and optical instruments as tools of standardization, codification, and pattern recognition, thus highlighting the transition from visual observation to diagrammatic computation. The dataset includes: - Diagram_ (.jpg): A visual rendering of the core conceptual relations articulated in the paper, useful to trace continuities, discontinuities, and critical transitions from spectroscopic images to algorithmic vision. - Nodes_ (.pdf): A structured vocabulary of epistemic concepts drawn from the article, each accompanied by a short definition. This conceptual mapping outlines the visual and technical genealogy of spectroscopy as a precursor to computational imaging. - QA_ (.pdf): A document collecting theoretical annotations, open questions, and epistemological reflections on image standards, algorithmic visibility, and computational mediation, within a broader historical framework. - Quotations Tags_ (.pdf): A curated selection of excerpts from primary and secondary sources used in the article, annotated and tagged according to visual-semiotic and media categories (e.g., representation, instrumentation, printing techniques, standardization, visibility), in line with a media-archaeological methodology. This dataset is intended for scholars and researchers in the fields of scientific visualization, history of optics and spectroscopy, computational imaging, and visual epistemology. It provides a conceptual and archival foundation for further studies on the operational logics, representational infrastructures, and epistemic functions of scientific images across the nineteenth and twenty-first centuries.

Supplementary Table S1. Excel file containing the following sheets: a) plasma metabolites annotated by UHPLC-HRMS analysis; b) RSD (%) of the different annotated metabolites in pooled QC samples; c) VIP discriminant compounds included in the significant metabolomic pathways and resulting from the pairwise comparison "MDP vs MTX"; d) VIP discriminant compounds included in the significant metabolomic pathways and resulting from the pairwise comparison "MDP vs CTR"; e) VIP discriminant compounds included in the significant metabolomic pathways and resulting from the pairwise comparison "MTX vs CTR"; f) Exclusive VIP discriminant compounds for the different pairwise comparisons and resulting from the Venn diagram.

Heavy metal (HM) contamination in agricultural soils significantly threatens soil health and plant productivity. This study investigates cadmium (Cd) and zinc (Zn) stress impact on tomato plants (Solanum lycopersicum) while exploring the mitigation potential of microbial biostimulants (MBs)—arbuscular mycorrhizal fungi (AMF) and Pseudomonas fluorescens So_08 (PGPR)— employing multi-omics approaches. Specifically, the investigation delves deeply into soil-plant communication mechanisms mediated by root exudates and rhizosphere microbial communities. Root exudate profiling revealed distinct metabolic changes under HM stress, which compromised soil-plant interactions. Under Cd stress, key classes of metabolites, including phenylpropanoids, lipids, and isoprenoids, show reduced secretion. These metabolites play crucial roles in antioxidative defense, suggesting a shift in resource allocation mechanisms. Moreover, Cd negatively impacted rhizosphere fungal populations. Conversely, Zn stress prompted an increased exudation of lipids, including sphingolipids and sterols, reflecting an adaptive strategy to preserve membrane integrity and functionality. This stress also influenced rhizobacterial community structures. The MB application mitigated HM-induced stress by enhancing specialized metabolite syntheses, including cinnamic acids, terpenoids, and flavonoids, which promoted crop resilience. MBs also reshaped microbial diversity, fostering beneficial species like Portibacter spp., Alkalitalea saponilacus under Cd stress, and stimulating rhizobacteria like Aggregatilinea spp. under Zn stress. Multi-omics data integration combined with network analysis highlighted key features associated with improved nutrient availability and reduced HM toxicity under MB treatments, including metabolites and microbial taxa linked to sulfur cycling, nitrogen metabolism, and iron reduction pathways. These findings demonstrate that MBs can modulate plant metabolic responses and restore rhizosphere microbial communities under Cd and Zn stress, with PGPR showing broader metabolomic recovery effects and AMF influencing specific metabolite pathways. This study provides new insights into plant-microbe interactions in HM-contaminated environments, supporting the potential application of biostimulants for sustainable soil remediation and plant health improvement.

Supplemental Table S1. Excel file containing the following sheets: a) rumen metabolites annotated by UHPLC-HRMS analysis; b) milk metabolites annotated by UHPLC-HRMS analysis; c) Correlation Network resulting from data fusion of rumen and milk metabolites; d) Log2FC values of the VIP compounds discriminating the rumen metabolomic profile for the pairwise comparison 3-NOP vs CTR groups; e) Log2FC values of the VIP compounds discriminating the milk metabolomic profile for the pairwise comparison 3-NOP vs CTR group.

Supplementary material of manuscript - A Pseudomonas Plant Growth Promoting Rhizobacterium and Arbuscular Mycorrhiza differentially modulate the growth, photosynthetic performance, nutrients allocation, and stress response mechanisms triggered by a mild Zinc and Cadmium stress in tomato

RNA-seq raw count matrix from Orthotopic human immune system reconstituted (HIR) patient-derived xenograft (PDX) PDAC mouse models. metadata file match sample IDs and treatment conditions

Supplementary table 1. Diet ingredient formulation considering the different nutritional strategy-based clusters (Gallo et al., 2022).

dataset of the manuscript "A new metabolomics insight for origin and processing authentication of thyme by comprehensive UHPLC-HRMS fingerprinting and chemometrics" by Araceli Rivera-Pérez, Pascual García-Pérez, Roberto Romero-González, Antonia Garrido Frenich, and Luigi Lucini The data are produced by LC-HRMS foodomics and include annotated features, Ms and MS/MS spectra, as well as individual abundance across samples and treatments.

Supplementary material 3: metabolomics dataset