Automated methods to accelerate fungal red listing: a case study for North American macrofungi - Vida J. Svahnström; Steven Bachman; Cátia Canteiro; Eimear Nic Lughadha; A. Martyn Ainsworth; Jessica L. Allen; Scott T. Bates; Matilda J.M. Brown; Susana P. Cunha; Anders Dahlberg; Susana C. Gonçalves; Tom W. May; et al. (Fungal Ecology, 2026)

The H, C and N abundances and isotopic compositions of samples with outer Solar System heritage: asteroid Bennu and the Tarda and Tagish Lake meteorites - Dionysis I. Foustoukos; Conel M. O’D. Alexander; George D. Cody; Jennifer C. Stern; Steven M. Bates; Yoshihiro Furukawa; Toshiki Koga; Daniel P. Glavin; Jason P. Dworkin; Jessica J. Barnes; Ann N. Nguyen; Harold C. Connolly; et al. (Geochimica et Cosmochimica Acta, 2026)

Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Transient glacio-eustatic fall and its climato-environmental effects during the Frasnian-Famennian transition - Thomas J. Algeo; Mariano N. Remírez; He Zhao; Lorenz Schwark; Gwyneth Gordon; Ariel Anbar; Steven Bates; Timothy Lyons; D. Jeffrey Over; Brad Sageman (Global and Planetary Change, 2026)

Enhancing carbon flux estimation in a crop growth model by integrating UAS-derived leaf area index - Xuerui Guo; Bagher Bayat; Jordan Steven Bates; Michael Herbst; Marius Schmidt; Harry Vereecken; Carsten Montzka (Agricultural and Forest Meteorology, 2025)

Host Transcriptomics Reveal Reduction in Defence‐Reproduction Trade‐Offs During Coinfection - Ian Will; Emily J. Stevens; Kayla C. King; Kieran A. Bates (Molecular Ecology, 2025)
During infection, hosts may shift resources away from reproduction towards immune defence. It is unclear to what degree these costly trade‐offs can be alleviated during protective coinfections, whereby antagonism between parasites reduces disease severity. We used transcriptomics to assess the extent to which host gene expression reflected the effect of protection and whether reducing or increasing investment in immunity carried costs to reproduction. Virulent infections by Leucobacter musarum bacteria elicited greater trade‐offs in nematode hosts compared to the naturally coinfecting ‘protective parasite’ Leucobacter celer . We further found that coinfection attenuated host investment in pro‐immune trade‐offs, without significantly changing which host genes were involved. We then sought to understand if this attenuated host response would be consistent with possible mechanisms of inter‐parasite competition. Our chromosome length genome assemblies for both parasite species revealed that protective coinfection may operate by competition for public goods, such as siderophore‐mediated uptake of metal ions (e.g., iron) or colonisation of the host cuticle. Ultimately, we show that competition between coinfecting parasites can complement endogenous host defences and ease the reproductive costs of fighting harmful infection.

Surface-based morphometry reveals divergent aging trajectories in veterans with and without traumatic brain injury - Michelle C. Eliason; Amrutha Bindu Nagella; Cristian Cuadra; David S. Wack; Ghazala T. Saleem; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowki; Arthur W. Toga; et al. (GeroScience, 2025)

Exploring college students’ assessments of racially-coded language - Mandi Bates Bailey; Kiana Johnson; Steven P. Nawara (The Social Science Journal, 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.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Voxel-wise insights into early Alzheimer’s disease pathology progression: the association with APOE and memory decline - Maha Wybitul; Nicolas Langer; Christoph Hock; Anton Gietl; Valerie Treyer; Michael Weiner; Paul Aisen; Ronald-Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; et al. (GeroScience, 2025)
Longitudinal investigation of the Apolipoprotein E (APOE) genotype’s impact on Alzheimer’s disease (AD) biomarker progression, focusing on amyloid beta (Aβ) accumulation and gray matter (GM) atrophy, integrating cognitive decline and baseline levels. Longitudinal florbetapir-PET and T1-weighted MRI data from 100 cognitively normal (CN) and mild cognitive impaired (MCI) participants both with considerable global Aβ accumulation (“high Aβ accumulators”) were analyzed using a voxel-wise approach. Associations of APOE genotype and memory decline with Aβ accumulation and GM atrophy were examined separately for each neuroimaging modality, controlling for baseline Aβ levels and diagnosis. Alternatively, the effect of baseline diagnosis, while controlling for memory decline, was investigated. A multimodal analysis evaluated interactions between genotype, memory decline, and GM atrophy on Aβ accumulation. High Aβ accumulators displayed extensive Aβ pathology predominantly in the medial orbito-frontal cortex, cingulate cortex, and precuneus, along with GM atrophy in temporal, occipital, orbito-frontal, and parietal areas. ɛ4 carriers with memory decline exhibited greater Aβ accumulation and GM atrophy in selective regions compared to non-carriers with memory decline, while no genotype difference was observed in individuals without decline. No interaction effect was observed for MCI diagnosis. Regional associations between the two biomarkers were similarly dependent on genotype and memory decline. ɛ4 carriers exhibiting memory decline present an accelerated neurobiological pattern at predementia stages, supporting early ɛ4 carrier monitoring and interventions in this at-risk group. Importantly, memory decline might be more informative than MCI regarding AD pathology progression emphasizing the importance of repeated cognitive assessments.

Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts - Luyao Wang; Wenjing Hu; Fan Dong; Can Sheng; Jinglong Wu; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2025)

Marine Fish Passage—Underappreciated Threats to Connectivity Within the Marine Environment - Robert J. Lennox; Kim Birnie‐Gauvin; Caitlin Bate; Steven J. Cooke; Tormod Haraldstad; Saron Berhe; Heather D. Penney; Charles W. Bangley; Knut Wiik Vollset; Morgan L. Piczak (Marine Ecology, 2025)
Habitat fragmentation is a major threat to aquatic biodiversity loss. However, much of the focus is on the connectivity of freshwaters, with much less attention given to marine ecosystems. We contend that coastal infrastructure including bridges, causeways, tidal turbines, land infilling and harbours, wharfs, quays, piers and docks have resulted in underappreciated impacts on the connectivity of fish movements resulting in passage challenges at sea. For each type of marine infrastructure, we synthesised the present status of knowledge to characterise the problems and future challenges and also identify mitigation options and passage solutions to restore connectivity for fishes. Bridges can disrupt currents, generate light and noise/vibration, and emit electromagnetic signals, so more work is needed to modify in‐water designs to minimise the negative impacts on fishes. Causeways involve infilling, resulting in full in‐water barriers, requiring fishes to circumnavigate these structures and there is limited research on mitigation (e.g., fishways). Tidal turbines are placed in areas with high currents, which can hinder movements and result in entrainment; however, monitoring fish movements is challenging in these unique areas. Offshore energy has grown in recent years and can impact fish connectivity via altered sediment dynamics and water currents, as well as through the generation of noise pollution and electromagnetic fields. Land filling results not only in habitat loss but also in fragmentation, and it will be imperative to identify important habitats and corridors to minimise impacts there. Finally, infrastructure associated with boats (e.g., harbours, docks) negatively impacts nearshore habitat, which can alter movement trajectories. In the collective, we found evidence that diverse types of marine infrastructure can impact connectivity and, ultimately, fish movement and migrations. Interestingly,bespoke fish passage solutions in marine environments seem rare. As coastal development will increase in the future, it is imperative that we assess the potential connectivity issues resulting from marine infrastructure and that we generate solutions to mitigate these issues for marine organisms.

Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction - Andreas Engvig; Karl Trygve Kalleberg; Lars T. Westlye; Esten Høyland Leonardsen; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; et al. (GeroScience, 2024)
DNA methylation age (MA), brain age (BA), and frailty index (FI) are putative aging biomarkers linked to dementia risk. We investigated their relationship and combined potential for prediction of cognitive impairment and future dementia risk using the ADNI database. Of several MA algorithms, DunedinPACE and GrimAge2, associated with memory, were combined in a composite MA alongside BA and a data-driven FI in predictive analyses. Pairwise correlations between age- and sex-adjusted measures for MA (aMA), aBA, and aFI were low. FI outperformed BA and MA in all diagnostic tasks. A model including age, sex, and aFI achieved an area under the curve (AUC) of 0.94 for differentiating cognitively normal controls (CN) from dementia patients in a held-out test set. When combined with clinical biomarkers (apolipoprotein E ε4 allele count, memory, executive function), a model including aBA and aFI predicted 5-year dementia risk among MCI patients with an out-of-sample AUC of 0.88. In the prognostic model, BA and FI offered complementary value (both β s 0.50). The tested MAs did not improve predictions. Results were consistent across FI algorithms, with data-driven health deficit selection yielding the best performance. FI had a stronger adverse effect on prognosis in males, while BA’s impact was greater in females. Our findings highlight the complementary value of BA and FI in dementia prediction. The results support a multidimensional view of dementia, including an intertwined relationship between the biomarkers, sex, and prognosis. The tested MA’s limited contribution suggests caution in their use for individual risk assessment of dementia.

Local molecular and connectomic contributions of tau-related neurodegeneration - Fardin Nabizadeh; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; Robert C. Green; Andrew J. Saykin; John Morris; et al. (GeroScience, 2024)

Sex differences in interacting genetic and functional connectivity biomarkers in Alzheimer’s disease - Jordan N. Williamson; Shirley A. James; Sean P. Mullen; Bradley P. Sutton; Tracey Wszalek; Beni Mulyana; Peter Mukli; Andriy Yabluchanskiy; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2024)

Productivity and organic carbon loading control uranium isotope behavior in ancient reducing settings: Implications for the paleoredox proxy - Randolph L. Rutledge; Geoffrey J. Gilleaudeau; Mariano N. Remírez; Alan J. Kaufman; Timothy W. Lyons; Steven Bates; Thomas J. Algeo (Geochimica et Cosmochimica Acta, 2024)

Co-designing a multi-criteria approach to ranking hazards to and from Australia’s emerging offshore blue economy - Mischa P. Turschwell; Christopher J. Brown; Myriam Lacharité; Jess Melbourne-Thomas; Keith R. Hayes; Rodrigo H. Bustamante; Jeffrey M. Dambacher; Karen Evans; Pedro Fidelman; Darla Hatton MacDonald; Ingrid Van Putten; Graham Wood; et al. (Environmental Science & Policy, 2023)

Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer’s disease: an exploratory study of 18F-FDG-PET - Qi Zhang; Chunqiu Fan; Luyao Wang; Taoran Li; Min Wang; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2023)

The ecological relevance of critical thermal maxima methodology for fishes - Jessica E. Desforges; Kim Birnie‐Gauvin; Fredrik Jutfelt; Kathleen M. Gilmour; Erika J. Eliason; Terra L. Dressler; David J. McKenzie; Amanda E. Bates; Michael J. Lawrence; Nann Fangue; Steven J. Cooke (Journal of Fish Biology, 2023)
Critical thermal maxima methodology (CTM) has been used to infer acute upper thermal tolerance in fishes since the 1950s, yet its ecological relevance remains debated. In this study, the authors synthesize evidence to identify methodological concerns and common misconceptions that have limited the interpretation of critical thermal maximum (CT max ; value for an individual fish during one trial) in ecological and evolutionary studies of fishes. They identified limitations of, and opportunities for, using CT max as a metric in experiments, focusing on rates of thermal ramping, acclimation regimes, thermal safety margins, methodological endpoints, links to performance traits and repeatability. Care must be taken when interpreting CTM in ecological contexts, because the protocol was originally designed for ecotoxicological research with standardized methods to facilitate comparisons within study individuals, across species and contexts. CTM can, however, be used in ecological contexts to predict impacts of environmental warming, but only if parameters influencing thermal limits, such as acclimation temperature or rate of thermal ramping, are taken into account. Applications can include mitigating the effects of climate change, informing infrastructure planning or modelling species distribution, adaptation and/or performance in response to climate‐related temperature change. The authors’ synthesis points to several key directions for future research that will further aid the application and interpretation of CTM data in ecological contexts.

Early diagenetic processes in an iron-dominated marine depositional system - Maria C. Figueroa; Sebastiaan J. van de Velde; Daniel D. Gregory; Sydnie Lemieux; Jeana Drake; Tina Treude; Nathaniel Kemnitz; William Berelson; Konstantin Choumiline; Steven Bates; Ravi Kukkadapu; Marilyn Fogel; et al. (Geochimica et Cosmochimica Acta, 2023)

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment - Jiehui Jiang; Can Sheng; Guanqun Chen; Chunhua Liu; Shichen Jin; Lanlan Li; Xueyan Jiang; Ying Han; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2022)

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Consensus guidelines for the use and interpretation of angiogenesis assays - Patrycja Nowak-Sliwinska; Kari Alitalo; Elizabeth Allen; Andrey Anisimov; Alfred C. Aplin; Robert Auerbach; Hellmut G. Augustin; David O. Bates; Judy R. van Beijnum; R. Hugh F. Bender; Gabriele Bergers; Andreas Bikfalvi; et al. (Angiogenesis, 2018)

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.

The carboxyl terminus of VEGF-A is a potential target for anti-angiogenic therapy - James G. Carter; Melissa V. R. Gammons; Gopinath Damodaran; Amanda J. Churchill; Steven J. Harper; David O. Bates (Angiogenesis, 2015)

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide - Suzanne M. Prober; Jonathan W. Leff; Scott T. Bates; Elizabeth T. Borer; Jennifer Firn; W. Stanley Harpole; Eric M. Lind; Eric W. Seabloom; Peter B. Adler; Jonathan D. Bakker; Elsa E. Cleland; Nicole M. DeCrappeo; et al. (Ecology Letters, 2015)
Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty‐five 1 m 2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

Modelled and measured concentrations of peroxy radicals and nitrate radical in the U.S. Gulf Coast region during TexAQS 2006 - Roberto Sommariva; Tim S. Bates; Daniel Bon; Daniel M. Brookes; Joost A. de Gouw; Jessica B. Gilman; Scott C. Herndon; William C. Kuster; Brian M. Lerner; Paul S. Monks; Hans D. Osthoff; Alex E. Parker; et al. (Journal of Atmospheric Chemistry, 2011)

A Role for the Endothelial Glycocalyx in Regulating Microvascular Permeability in Diabetes Mellitus - Rachel M. Perrin; Steven J. Harper; David O. Bates (Cell Biochemistry and Biophysics, 2007)

The tylosin-biosynthetic genes of Streptomyces fradiae - Eric Cundliffe; Neil Bate; Andrew Butler; Steven Fish; Atul Gandecha; Louise Merson-Davies (Antonie van Leeuwenhoek, 2001)

Structural and functional characterization of the mouse Hlx homeobox gene - Michael D. Bates; Lynn C. Schatzman; Thierry Lints; Philip E. Hamlin; Richard P. Harvey; S. Steven Potter (Mammalian Genome, 2000)

Footprinting of the spinach nitrite reductase gene promoter reveals the preservation of nitrate regulatory elements between fungi and higher plants - Rajeev Rastogi; Nicholas J. Bate; Sobhana Sivasankar; Steven J. Rothstein (Plant Molecular Biology, 1997)