Combining lipiodol-based indirect radiography and intraoperative methylene blue for sentinel lymph node mapping in canine cutaneous mast cell tumors - Jéssica Francielle Camargo; Simone Passos Bianchi; Haiumy Garcia Cardozo; Caroline Soares Ferrari; Gabriela Foppa; Rodrigo Santos dos Horta; Priscila Beatriz Silva da Serpa; Stella Faria de Valle (Veterinary Research Communications, 2026)
Canine cutaneous mast cell tumor (cMCT) is one of the most common skin neoplasms in dogs, with lymph nodes representing the primary route of metastasis. Accurate sentinel lymph node (SLN) identification is therefore essential for staging and treatment planning. This study evaluated indirect lipiodol lymphography (IL) and intraoperative methylene blue (MB) mapping in 21 dogs, including 26 tumors and 38 excised lymph nodes, to assess SLN detection and its association with tumor characteristics and nodal status. MB identified 34 SLNs, whereas IL detected 29. The two techniques were concordant for 21 SLNs. In five tumors in which IL failed to identify a SLN, MB subsequently detected six axillary SLNs. Concordance with the expected regional lymph node (RLN) was higher for MB (76.9%) than for IL (61.5%) and increased to 84.6% when both techniques were combined, highlighting their complementary value for SLN mapping. MB detected additional axillary nodes, whereas IL aided in identifying some inguinal nodes. Larger tumors were more frequently associated with incomplete surgical margins and higher nodal histologic grades, indicating an increased risk of metastasis. Importantly, 19% of tumors drained to at least one SLN outside the expected regional basin, highlighting lymphatic anatomical variability. The absence of IL opacification did not exclude clinically relevant nodes, as MB identified all such cases, including HN0–HN2 nodes. Although MB stained some non-metastatic nodes, it provided useful intraoperative guidance. Adverse events were uncommon, with two transient reactions after IL and none after MB, and postoperative morbidity was low (13.2%; 5/38). Overall, MB offered higher detection rates, while IL improved anatomical delineation. Combining lipiodol-based indirect radiography and intraoperative MB staining offers a highly effective, complementary approach for identifying the SLN in dogs with cMCTs.

Technical barriers to circular economy implementation in the built environment: A problem-based multi-level review - Marianna Marchesi; Christina Giarma; Adriana Salles; Raluca Buzatu; Ferhat Karaca; Stylianos Yiatros; Viorel Ungureanu; Katerina Tsikaloudaki; Marilena De Simone; Alicia Zaragoza-Benzal; Daniel Ferrandez; Genesis Camila Cervantes Puma; et al. (Sustainable Cities and Society, 2026)

Vulnerability of marine megafauna to global at‐sea anthropogenic threats - Michelle VanCompernolle; Juliet Morris; Hannah J. Calich; Jorge P. Rodríguez; Sarah A. Marley; Jessica R. Pearce; Briana Abrahms; Katya Abrantes; André S. Afonso; Alex Aguilar; Andrews Agyekumhene; Tomonari Akamatsu; et al. (Conservation Biology, 2026)
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at‐sea threats. The threats we considered included individual fishing gear types, climate‐change‐related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability ( v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.

Individual and combined effects of commercial glyphosate, atrazine and 2,4-D herbicides on the gerbil ventral prostate - Stella Bicalho Silva; Vitor Grigio; Thalles Fernando Rocha Ruiz; Marília de Freitas Calmon; Paula Rahal; Fernanda Cristina Alcantara dos Santos; Sebastião Roberto Taboga; Patrícia Simone Leite Vilamaior (Chemosphere, 2024)

Production technique and multi-analytical characterization of a paint-plastered ceiling from the Late Antique villa of Negrar (Verona, Italy) - Simone Dilaria; Clelia Sbrolli; Federica Stella Mosimann; Anna Favero; Michele Secco; Lisa Santello; Monica Salvadori (Archaeological and Anthropological Sciences, 2024)
The research focuses on analyzing the production techniques and materials of a Roman paint-plastered ceiling from a Late Antique Roman villa near Negrar (Verona, Italy), recently uncovered. Stylistic features of the decoration, found in reworked collapse debris during the villa ’s excavation, date the ceiling to the original construction phase in the 4 th century CE. The paper presents the protocol we adopted for recovering and analyzing the painted decoration of the villa , which was in-laboratory recomposed in its original layout after a meticulous and systematic retrieval of fragmented materials. Microsamples of mortar and pigment were then taken to fully reconstruct the execution technique and raw materials used in the paint-plastered ceiling, detailing the application of the tectorium and pigment preparation. Mortar samples were analyzed to define preparatory layer properties, using various analytical techniques including Transmitted-Light Polarized Optical Microscopy (TL-OM) and Scanning Electron Microscopy with Energy Dispersive X-Ray Analysis (SEM-EDS). Optical reflected-light microscopy detected guide incisions on the preparatory mortar, while Reflected-Light Optical Microscopy (RL-OM) revealed the microstratigraphy of pictorial micro-layers. Micro-samplings of painted decorations were conducted to define pigment palettes, determining their mineralogical composition through X-Ray Powder Diffraction (XRPD) analysis coupled with micro-Raman analyses for the determination of carbon-based compounds. The research aims to establish a comprehensive protocol for future endeavors, integrating archaeological reassembly with precise micro-analyses of pigments and mortars, deciphering the intricate layout of ancient, fragmented decorations. This study is the first of its kind in Northern Italy, overcoming challenges posed by fragmented and reworked artifacts in previous research, enabling detailed analytical studies like those conducted here. Moreover, this study of the paint-plastered ceiling of the Late Roman villa of Negrar aims to provide a new impulse for the knowledge of Late Antique painting techniques and materials, which were only marginally considered within Roman painting tradition so far.

Impacts of heavy metal exposure on the prostate of murine models: Mechanisms of toxicity - Stella Bicalho Silva; Thalles Fernando Rocha Ruiz; Fernanda Cristina Alcantara dos Santos; Sebastião Roberto Taboga; Patricia Simone Leite Vilamaior (Reproductive Toxicology, 2023)

Analysis of critical water flow and solute transport parameters in different soils mixed with a synthetic zeolite - Alessandro Comegna; Claudia Belviso; Anna Rita Rivelli; Antonio Coppola; Giovanna Dragonetti; Ameneh Sobhani; Simone di Prima; Antonio Satriani; Francesco Cavalcante; Stella Lovelli (CATENA, 2023)

Demystifying image-based machine learning: a practical guide to automated analysis of field imagery using modern machine learning tools - Byron T. Belcher; Eliana H. Bower; Benjamin Burford; Maria Rosa Celis; Ashkaan K. Fahimipour; Isabela L. Guevara; Kakani Katija; Zulekha Khokhar; Anjana Manjunath; Samuel Nelson; Simone Olivetti; Eric Orenstein; et al. (Frontiers in Marine Science, 2023)
Image-based machine learning methods are becoming among the most widely-used forms of data analysis across science, technology, engineering, and industry. These methods are powerful because they can rapidly and automatically extract rich contextual and spatial information from images, a process that has historically required a large amount of human labor. A wide range of recent scientific applications have demonstrated the potential of these methods to change how researchers study the ocean. However, despite their promise, machine learning tools are still under-exploited in many domains including species and environmental monitoring, biodiversity surveys, fisheries abundance and size estimation, rare event and species detection, the study of animal behavior, and citizen science. Our objective in this article is to provide an approachable, end-to-end guide to help researchers apply image-based machine learning methods effectively to their own research problems. Using a case study, we describe how to prepare data, train and deploy models, and overcome common issues that can cause models to underperform. Importantly, we discuss how to diagnose problems that can cause poor model performance on new imagery to build robust tools that can vastly accelerate data acquisition in the marine realm. Code to perform analyses is provided at https://github.com/heinsense2/AIO_CaseStudy .

Sustainability reporting and ESG performance in the utilities sector - Francesca Imperiale; Simone Pizzi; Stella Lippolis (Utilities Policy, 2023)

Computational electrophysiology of the coronary sinus branches based on electro-anatomical mapping for the prediction of the latest activated region - Christian Vergara; Simone Stella; Massimiliano Maines; Pasquale Claudio Africa; Domenico Catanzariti; Cristina Demattè; Maurizio Centonze; Fabio Nobile; Alfio Quarteroni; Maurizio Del Greco (Medical & Biological Engineering & Computing, 2022)
This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. We considered the Eikonal-diffusion equation and to recover the electrical activation maps in the myocardium. The model was calibrated by using activation times acquired in the coronary sinus (CS) branches or in the CS solely with an electroanatomic mapping system (EAMS) during cardiac resynchronization therapy (CRT). We applied our computational tool to ten patients founding an excellent accordance with EAMS measures; in particular, the error for LEAS location was less than 4 mm. We also calibrated our model using only information in the CS, still obtaining an excellent agreement with the measured LEAS. The proposed tool was able to accurately reproduce the electrical activation maps and in particular LEAS location in the CS branches, with an almost real-time computational effort, regardless of the presence of myocardial fibrosis, even when information only at CS was used to calibrate the model. This could be useful in the clinical practice since LEAS is often used as a target site for the left lead placement during CRT. Graphical abstract Overall picture of the computational pipeline for the estimation of LEAS

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Analysis of RNA Expression Profiles Identifies Dysregulated Vesicle Trafficking Pathways in Creutzfeldt-Jakob Disease - Anna Bartoletti-Stella; Patrizia Corrado; Nicola Mometto; Simone Baiardi; Pascal F. Durrenberger; Thomas Arzberger; Richard Reynolds; Hans Kretzschmar; Sabina Capellari; Piero Parchi (Molecular Neurobiology, 2019)

Toll-Like Receptor 2-Mediated Glial Cell Activation in a Mouse Model of Cuprizone-Induced Demyelination - Stefan Esser; Larissa Göpfrich; Kai Bihler; Eugenia Kress; Stella Nyamoya; Simone C. Tauber; Tim Clarner; Matthias B. Stope; Thomas Pufe; Markus Kipp; Lars-Ove Brandenburg (Molecular Neurobiology, 2018)

Formyl Peptide Receptor 1-Mediated Glial Cell Activation in a Mouse Model of Cuprizone-Induced Demyelination - Kai Bihler; Eugenia Kress; Stefan Esser; Stella Nyamoya; Simone C. Tauber; Tim Clarner; Matthias B. Stope; Thomas Pufe; Lars-Ove Brandenburg (Journal of Molecular Neuroscience, 2017)

Where is the best site for wave energy exploitation? Case study along the coast of northern Latium (ITALY) - Francesco Paladini de Mendoza; Simone Bonamano; Giuseppe Stella; Monica Giovacchini; Dario Capizzi; Fulvio Fraticelli; Sergio Muratore; Calogero Burgio; Sergio Scanu; Maximo A. Peviani; Marco Marcelli (Journal of Coastal Conservation, 2016)

8-Isoprostane, prostaglandin E2, C-reactive protein and serum amyloid A as markers of inflammation and oxidative stress in antiphospholipid syndrome: a pilot study - Savino Sciascia; Dario Roccatello; Maria Tiziana Bertero; Debora Di Simone; Domenico Cosseddu; Antonella Vaccarino; Mario Bazzan; Daniela Rossi; Cesar Garcia-Fernandez; Leticia Ceberio; Stefania Stella; Elisa Menegatti; et al. (Inflammation Research, 2012)

Administration of Bacillus coagulans in calves: recovery from faecal samples and evaluation of functional aspects of spores - Barbara Ripamonti; Alessandro Agazzi; Antonella Baldi; Claudia Balzaretti; Carla Bersani; Silvia Pirani; Raffaella Rebucci; Giovanni Savoini; Simone Stella; Alberta Stenico; Cinzia Domeneghini (Veterinary Research Communications, 2009)