​Department of Biotechnology and Biosciences

The dataset contains field observations of pollinator visitation to 43 ornamental plant species surveyed across seven Italian cities during May. Data include information on plant identity, green area type and habitat characteristics, together with pollinator abundance, richness, and taxonomic/group-level visitation records. The dataset also includes floral trait measurements used to investigate plant–pollinator relationships, including morphological and resource-related traits. These data allow the assessment of the relative attractiveness of ornamental plants for urban pollinators and the role of plant traits and urban habitat context in shaping pollinator communities. Authors contributing to this dataset are: Paolo Biella 1*, Giulia Brambilla 1, Valentina Verduci 2,12, Matteo Annessi 3, Andrea Beltramini 4, Lorenzo Bianco 5, Daniele Calabrese 6, Francesca Romana Dani 4,2, Marta Depetris 7, Andrea Di Giulio 3,2, Andrea Ferrari 8, Jessica Frigerio1, Gianni Henson 6, Martino Maggioni 4,2,12, Francesca Martelli 3, Oana Catalina Moldoveanu 4, Jorge Sanchez Navarro 10,2, Massimo Nepi 2,6, Emily Rose Palm1, Irene Piccini 9,5, Carlo Polidori 8,2, Michelina Pusceddu 10,2, Fausto Ramazzotti 1, Enrico Ruzzier 2,3, Alberto Satta 10,2, Giovanni Scopece 11,2, Carla Sorvillo 2,11, Elena Tafi 6,2, Andrea Galimberti 1,2, Davide Maggioni 1,2, Massimo Labra 1,2 1 Department of Biotechnology and Biosciences, University of Milano-Bicocca, Italy 2 National Biodiversity Future Center, University of Palermo, Italy 3 Department of Science, Roma Tre University, Rome, Italy 4 Department of Biology, University of Florence, Italy 5 Department of Life Sciences and System Biology, University of Turin 6 Department of Life Sciences, University of Siena, Siena, Italy 7 independent researcher, Turin, Italy 8 Department of Environmental science and policy, University of Milano 9 Department of Zoology, Poznań University of Life Sciences, Poznań, Poland 10 Department of Agricultural Sciences, University of Sassari, Sassari, Italy 11 Department of Biology, University of Naples Federico II, Italy 12 Earth and Marine Sciences Department, University of Palermo, Palermo, Italy

Iterative Bleaching Extends Multiplexity (IBEX) immunofluorescence was performed on skin samples collected from CD11c-DOG mice either treated with diphtheria toxin (Skin_CD11cDOG_with_Diphtheria_Toxin) or phosphate-buffered saline (PBS) treated controls (Skin_CD11cDOG_no_Diphtheria_Toxin). For dendritic cell depletion, CD11c-DOG mice received three systemic intravenous injections of diphtheria toxin (16 ng/g body weight) on days −3, −2, and −1. Control mice PBS following the same schedule. In addition, a local subcutaneous injection of diphtheria toxin (16 ng) was administered on day −1 at the site designated for tissue collection. Mice were euthanized on day 0 in accordance with national and international regulations for animal care and use. A square section of flank skin was excised from each mouse at the site of the last intradermal injection. Subcutaneous adipose tissue was mechanically removed using forceps. Skin samples were subsequently processed according to the 2D Manual IBEX protocol for multiplex immunofluorescence imaging.

Here, we focused on the Bombus flavidus species group, cuckoo bumblebees, by characterizing the genetic lineages and variation, investigating morphometrics of wing shape and body parts, and studying the morphology. The data are those used for morfologic analyses. The datasets included here are: 1- Landmarks from digitized male right wings of n=74 specimens of the Bombus flavidus complex (format .TPS) 2. Landmarks from digitized male right wings of n=97 specimens of the Bombus sylvestris complex (format .TPS) 3. A file with malar space ratio of Bombus flavidus complex (females) and labral furrow/labral lamella from Bombus sylvestris complex (females) (format .csv) These data were used for the publication: Integrating evidence to disentangle multiple cryptic speciation events in a cuckoo bumblebee species group Paolo Biella, Davide Maggioni, Martin Streinzer, Paul H. Williams, Alexandr Byvaltsev, Frode Ødegaard, Fausto Ramazzotti, Cory Sheffield, George Japoshvili, Johann Neumayer, Maxim Yu. Proshchalykin, Zong-Xin Ren, Andrea Galimberti Journal of Zoological Systematics and Evolutionary Research

Raw data of the paper by Moukham, Caligaris et al. 2026

Supplementary data and underlying data supporting the finding described in "Production and carbon footprint of microbial oil from waste lemon peel extract". Abstract Background The agricultural sector is one of the leading producers of agro-industrial solid organic waste. This waste is mainly disposed of by incineration or landfilled, representing a huge loss of potential resources, which could be used for the production of high-value chemicals. In this study, a fermentation process for the production of microbial oil from waste lemon extract (LE), an aqueous side stream deriving from waste lemon peel and pulp processing, was developed and assessed for impacts. Microbial oil can have many and diverse applications, from plasticisers in plastic and rubber compounds to moisturizers in cosmetic formulation. Methods and results Characterization of LE revealed that its autoclaving process is effective for increasing the concentration of readily available glucose and fructose, reaching 28.77 ± 0.08 g L-1 and 25.68 ± 0.27 g L-1. Nitrogen content was measured too, revealing a C/N ratio of 85, optimal for triggering lipid accumulation in the selected microbial cell factory. Therefore, the oleaginous yeast Cutaneotrichosporon oleaginosum was cultivated in an unmodified LE-based medium in 2 L bioreactors, resulting in a lipid accumulation of 0.47 ± 0.08 goil gCDW-1. Finally, a new lipid extraction method using green solvents was developed, which allowed to extract and purify 11.29 g of oils, corresponding to 35% of the cell dry weight. The carbon footprint of this laboratory-scale production was estimated to be 71 - 434 kgCO2eq kg-1 microbial oil, with electricity consumption of the fermentation step as the main factor. Simulation of the process in a 300L fermenter suggests that the electricity consumption, and therefore the overall impact, can be drastically reduced with scale-up. Conclusions The proposed process is promising in terms of production and has the advantage of not being in competition with edible resources and land use. However, the microbial oil yield and the extraction process must be optimized to make the process sustainable.

Intestinal microbiota and gut-born T helper-17 (Th17) lymphocytes may act as drivers of smoldering multiple myeloma (SMM) to MM evolution. We demonstrate here that administering the human commensal Prevotella melaninogenica to transgenic Vk*MYC mice affected by Early-MM, mimicking human SMM, significantly delayed evolution to full-blown MM. Mechanistically, P. melaninogenica increased the production of short-chain fatty acids (SCFAs), preventing skew of dendritic cells towards a pro-Th17 phenotype and accumulation of Th17 cells in the bone marrow of treated mice. P. melaninogenica or butyrate synergized with anti-PD-L1 antibodies by restraining Th17 cell expansion while unleashing immune checkpoint blockade (ICB)-induced effector CD8+ T cells. P. melaninogenica also attenuated IL-17-mediated skin lesions that mimicked ICB-induced immune-related adverse events. Thus, modulation of the gut microbiota or SCFAs administration with or without ICB might represent treatment options for patients affected by plasma cell dyscrasias and other hematologic or solid tumors where IL-17 acts as driving force. The present dataset contains: - 1H NMR spectra acquired on control and growth media for PM and PH; - CMP and .exp files created for metabolite quantification in MestreNova software by SMA analysis.

NMR File of the paper "Cleaner synthesis of preclinically validated vaccine adjuvants" in publication on Frontiers in Chemistry

Metabolite libraries built from NMR spectra for the metabolomics analysis of antarctic soils extracts, using the Simple Mixture Analysis (SMA) tool implemented in MestreNova 14.3.0-30573 software.

Metabolite library built from NMR spectra for metabolomic analysis of cheese whey permeate (CWP) using the Simple Mixture Analysis (SMA) tool implemented in MestreNova 14.3 software. Metabolites included: 2,3-Butandiol, Acetate, Alanine, Betaine, Choline, Citrate, Creatine, Creatinine, Ethanol, Fumarate, Hippurate, Lactate, Lactose, Orotate, Succinate, α-D-Galactose, β-D-Galactose Sample CWP in PB 10 mM (10% D2O) pH 7.4, TSP (1mM), Diluition Factor (10%) File included: SMA library .exp files and optimized .cmp files