Vascular Organoids Derived from Capillary malformation-induced Pluripotent Stem Cells Exhibit Disease-Relevant Phenotypes - Vi Nguyen; Anna Harper; Mackenzie Azuero; Isabella Castellanos; Siwuxie He; Marcelo L. Hochman; Camilla F. Wenceslau; Dong-bao Chen; Anil G. Jegga; Yunguan Wang; Daping Fan; J. Stuart Nelson; et al. (Stem Cell Reviews and Reports, 2026)
Capillary malformation (CM) is a congenital vascular anomaly that affects the skin, mucosa, eye, and brain. A major obstacle to mechanistic and drug screening studies for CM has been the lack of preclinical models. In this study, we established vascular organoids (VOs) generated through the self-assembly of vascular lineages of endothelial cells and smooth muscle cells differentiated from CM-induced pluripotent stem cells (iPSC). Within these VOs induced endothelial cells and smooth muscle cells organized into juxtapositions to form vascular branches. CM patient iPSC-derived VOs showed a higher density of endothelial and smooth muscle cell populations and greater vascular branch lengths as compared with VOs derived from iPSCs generated from healthy skin biopsies. Overall, this study represents the first disease-relevant VO model of CM, providing a valuable platform for future mechanistic studies and drug screening.

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.

Associations between MASLD, atrial fibrillation, cardiovascular events, mortality and aspirin use in older adults - Daniel Clayton-Chubb; Stuart K. Roberts; Ammar Majeed; Robyn L. Woods; Andrew M. Tonkin; Mark R. Nelson; Andrew T. Chan; Joanne Ryan; Cammie Tran; Alexander Hodge; John S. Lubel; Hans G. Schneider; et al. (GeroScience, 2024)

Defining an ageing-related pathology, disease or syndrome: International Consensus Statement - Emma Short; Ian M. Adcock; Bilal Al-Sarireh; Ann Ager; Ramzi Ajjan; Naveed Akbar; Michael A. Akeroyd; Ghada Alsaleh; Ghada Al-Sharbatee; Kambiz Alavian; Winfried Amoaku; Julie Andersen; et al. (GeroScience, 2024)
Around the world, individuals are living longer, but an increased average lifespan does not always equate to an increased health span. With advancing age, the increased prevalence of ageing-related diseases can have a significant impact on health status, functional capacity and quality of life. It is therefore vital to develop comprehensive classification and staging systems for ageing-related pathologies, diseases and syndromes. This will allow societies to better identify, quantify, understand and meet the healthcare, workforce, well-being and socioeconomic needs of ageing populations, whilst supporting the development and utilisation of interventions to prevent or to slow, halt or reverse the progression of ageing-related pathologies. The foundation for developing such classification and staging systems is to define the scope of what constitutes an ageing-related pathology, disease or syndrome. To this end, a consensus meeting was hosted by the International Consortium to Classify Ageing-Related Pathologies (ICCARP), on February 19, 2024, in Cardiff, UK, and was attended by 150 recognised experts. Discussions and voting were centred on provisional criteria that had been distributed prior to the meeting. The participants debated and voted on these. Each criterion required a consensus agreement of ≥ 70% for approval. The accepted criteria for an ageing-related pathology, disease or syndrome were (1) develops and/or progresses with increasing chronological age; (2) should be associated with, or contribute to, functional decline or an increased susceptibility to functional decline and (3) evidenced by studies in humans. Criteria for an ageing-related pathology, disease or syndrome have been agreed by an international consortium of subject experts. These criteria will now be used by the ICCARP for the classification and ultimately staging of ageing-related pathologies, diseases and syndromes.

Small-scale oxygen distribution patterns in a coral reef - Adam S. Candy; Shannara K. Taylor Parkins; Fleur C. Van Duyl; Benjamin Mueller; Milou G. I. Arts; Will Barnes; Marie Carstensen; Yun J. H. Scholten; Yusuf C. El-Khaled; Christian Wild; Linda Wegley Kelly; Craig E. Nelson; et al. (Frontiers in Marine Science, 2023)
One mechanism giving fleshy algae a competitive advantage over corals during reef degradation is algal-induced and microbially-mediated hypoxia (typically less than 69.5 µmol oxygen L −1 ). During hypoxic conditions oxygen availability becomes insufficient to sustain aerobic respiration in most metazoans. Algae are more tolerant of low oxygen conditions and may outcompete corals weakened by hypoxia. A key question on the ecological importance of this mechanism remains unanswered: How extensive are local hypoxic zones in highly turbulent aquatic environments, continuously flushed by currents and wave surge? To better understand the concert of biological, chemical, and physical factors that determine the abundance and distribution of oxygen in this environment, we combined 3D imagery, flow measurements, macro- and micro-organismal abundance estimates, and experimentally determined biogenic oxygen and carbon fluxes as input values for a 3D bio-physical model. The model was first developed and verified for controlled flume experiments containing coral and algal colonies in direct interaction. We then developed a three-dimensional numerical model of an existing coral reef plot off the coast of Curaçao where oxygen concentrations for comparison were collected in a small-scale grid using fiberoptic oxygen optodes. Oxygen distribution patterns given by the model were a good predictor for in situ concentrations and indicate widespread localized differences exceeding 50 µmol L -1 over distances less than a decimeter. This suggests that small-scale hypoxic zones can persist for an extended period of time in the turbulent environment of a wave- and surge- exposed coral reef. This work highlights how the combination of three-dimensional imagery, biogenic fluxes, and fluid dynamic modeling can provide a powerful tool to illustrate and predict the distribution of analytes (e.g., oxygen or other bioactive substances) in a highly complex system.

De novo mutations in the BMP signaling pathway in lambdoid craniosynostosis - Andrew T. Timberlake; Emre Kiziltug; Sheng Chih Jin; Carol Nelson-Williams; Erin Loring; August Allocco; Arnaud Marlier; Siddharth Banka; Helen Stuart; Maria Rita Passos-Buenos; Rafael Rosa; Silvia R. Rogatto; et al. (Human Genetics, 2023)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

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.

An Overview of Three Promising Mechanical, Optical, and Biochemical Engineering Approaches to Improve Selective Photothermolysis of Refractory Port Wine Stains - Guillermo Aguilar; Bernard Choi; Mans Broekgaarden; Owen Yang; Bruce Yang; Pedram Ghasri; Jennifer K. Chen; Rick Bezemer; J. Stuart Nelson; Anne Margreet van Drooge; Albert Wolkerstorfer; Kristen M. Kelly; et al. (Annals of Biomedical Engineering, 2012)

Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions - Larry D. Hinzman; Neil D. Bettez; W. Robert Bolton; F. Stuart Chapin; Mark B. Dyurgerov; Chris L. Fastie; Brad Griffith; Robert D. Hollister; Allen Hope; Henry P. Huntington; Anne M. Jensen; Gensuo J. Jia; et al. (Climatic Change, 2005)