Chromogranin A and S100A12 protein measurement in hair of pigs: assay validation, changes across different production stages and comparison with other hair biomarkers - María Botía; Damián Escribano; Fernando Tecles; Silvia Martínez-Subiela; José Joaquín Cerón (Veterinary Research Communications, 2026)
Hair has emerged as a non-invasive matrix for retrospective assessment of health status in pigs. While hair cortisol and sulphate dehydroepiandrosterone (DHEA-S) have been used as biomarkers of the hypothalamic-pituitary-adrenal (HPA) axis, indicators of the sympathetic-adrenomedullary (SAM) axis and innate immunity, such as chromogranin A (CgA) and S100A12, have not yet been measured in hair. This study aimed to (1) evaluate if CgA and S100A12 could be detected in pig hair, and (2) analyse possible longitudinal changes in their concentration across key production stages of growing pigs (lactation, nursery, and fattening in 20 pigs sampled longitudinally) and compare their values with cortisol and DHEA-S. For CgA and S100A12 measurements, AlphaLisa technology was used, while cortisol and DHEA-S were quantified using an automated chemiluminescence assay. Validation showed the immunoreactive detectability of CgA and S100A12 in hair extracts, with a high precision (CVs < 15%), linearity after serial sample dilution (R 2 = 0.99), and adequate recovery (94.1–109.1%). During a productive cycle in fattening pigs, CgA concentrations increased progressively throughout the cycle, having higher values at the end of the fattening period (p=0.022), while S100A12 concentrations peaked significantly at the end of nursery ( p = 0.0004). . Cortisol was highest at end of nursery, whereas DHEA-S increased significantly at the end offattening ( p = 0.0002). This report provides evidence for the immunoreactive detectability of CgA and S100A12 in pig hair extracts, opening a new window into the potential evaluation of these analytes in this matrix.

A protocol for external biosecurity assessment against wildlife in intensive pig farms: Are we ready for African Swine Fever? - Mario Sebastián-Pardo; Eduardo Laguna; María Cruz Arnal; José Casanovas; Pelayo Acevedo; Vidal Montoro; Fernando Escribano; Carlos Martínez-Carrasco; Gregorio Mentaberre; Joaquín Vicente (Preventive Veterinary Medicine, 2026)

Body mass index and prognosis of infective endocarditis - Raquel Frías-García; Patricia Muñoz García; Marina Machado Vilchez; Gregorio Cuerpo Caballero; Raquel Rodríguez-García; M Ángeles Rodríguez-Esteban; M Carmen Fariñas-Álvarez; José M. Miró Meda; Andrea Gutiérrez Villanueva; Guillermo Ojeda-Burgos; Ane Josune Goikoetxea-Agirre; Marina Bernal Palacios; et al. (Infectious Diseases, 2025)

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Spatially-explicit effects of small-scale clear-cutting on soil fungal communities in Pinus sylvestris stands - Giada Centenaro; Sergio de-Miguel; José Antonio Bonet; Fernando Martínez Peña; Ruben Escribano Gil De Gomez; Ángel Ponce; Svetlana Dashevskaya; Josu G. Alday (Science of The Total Environment, 2024)

Gaining knowledge about biomarkers of the immune system and inflammation in the saliva of pigs: The case of myeloperoxidase, S100A12, and ITIH4 - María Botía; Alba Ortín-Bustillo; María J. López-Martínez; Pablo Fuentes; Damián Escribano; Antonio González-Bulnes; Edgar G. Manzanilla; Silvia Martínez-Subiela; Asta Tvarijonaviciute; Marina López-Arjona; José J. Cerón; Fernando Tecles; et al. (Research in Veterinary Science, 2023)

Cattail (Typha domingensis) silage improves feed intake, blood profile, economics of production, and growth performance of beef cattle - Makinde Olayinka John; Musa Ahmad Rufai; Alao Johnson Sunday; Escribano Fernando; Kohn Richard; Iglesias Eva; Aminu Maidala; Maina Amos; Mohammad Chana; Charles Hannatu; Okunade Sunday A (Tropical Animal Health and Production, 2022)

Health-promoting properties of oleocanthal and oleacein: Two secoiridoids from extra-virgin olive oil - Julián Lozano-Castellón; Anallely López-Yerena; José Fernando Rinaldi de Alvarenga; Jaume Romero del Castillo-Alba; Anna Vallverdú-Queralt; Elvira Escribano-Ferrer; Rosa M. Lamuela-Raventós (Critical Reviews in Food Science and Nutrition, 2020)

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

A new large-scale index (AcED) for assessing traffic noise disturbance on wildlife: stress response in a roe deer (Capreolus capreolus) population - Carlos Iglesias-Merchan; Fernando Horcajada-Sánchez; Luis Diaz-Balteiro; Gema Escribano-Ávila; Carlos Lara-Romero; Emilio Virgós; Aimara Planillo; Isabel Barja (Environmental Monitoring and Assessment, 2018)

Biological Activities of Plant Pigments Betalains - Fernando Gandía-Herrero; Josefa Escribano; Francisco García-Carmona (Critical Reviews in Food Science and Nutrition, 2016)

Structural implications on color, fluorescence, and antiradical activity in betalains - Fernando Gandía-Herrero; Josefa Escribano; Francisco García-Carmona (Planta, 2010)

Betaxanthins as pigments responsible for visible fluorescence in flowers - Fernando Gandía-Herrero; Josefa Escribano; Francisco García-Carmona (Planta, 2005)

Characterization of the monophenolase activity of tyrosinase on betaxanthins: the tyramine-betaxanthin/dopamine-betaxanthin pair - Fernando Gandía-Herrero; Josefa Escribano; Francisco García-Carmona (Planta, 2005)