Development and validation of a ddPCR & viability PCR assay for enhancing eDNA benthic surveys: A deep-sea case study - Olivier Laroche; Patrick Downes; Mathias Middelboe; Bryan O'Malley; Jacob Thompson-Laing; Jack Sissons; Ulla von Ammon (Marine Environmental Research, 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.

The Toxicology Investigators Consortium 2024 Annual Report - Kim Aldy; Shao Li; Mari Costantini; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; Michael Abesamis; Faiz Ahmed; Salman Ahsan; Peter Akpunonu; Adam Algren; et al. (Journal of Medical Toxicology, 2026)

Population Genetics and Invasion History of the European Starling Across Aotearoa New Zealand - Bryan Thompson; Kamolphat Atsawawaranunt; Melissa C. Nehmens; William S. Pearman; E. Owen Perkins; Pavel Pipek; Lee A. Rollins; Hui Zhen Tan; Annabel Whibley; Anna W. Santure; Katarina C. Stuart (Molecular Ecology, 2025)
The expansion of human settlements over the past few centuries is responsible for an unprecedented number of invasive species introductions globally. An important component of biological invasion management is understanding how introduction history and postintroduction processes have jointly shaped present‐day distributions and patterns of population structure, diversity and adaptation. One example of a successful invader is the European starling ( Sturnus vulgaris ), which was intentionally introduced to numerous countries in the 19th century, including Aotearoa New Zealand, where it has become firmly established. We used reduced representation sequencing to characterise the genetic population structure of the European starling in New Zealand, comparing it to that present in sampling locations in the native range and invasive Australian range. The population structure and genetic diversity patterns we found suggested restricted gene flow from the majority of New Zealand to the northmost sampling location (Auckland). We also profiled genetic bottlenecks and shared outlier genomic regions, which supported historical accounts of translocations between both Australian subpopulations and New Zealand, and provided evidence of which documented translocation events were more likely to have been successful. Using these results as well as historic demographic patterns, we demonstrate how genomic analysis complements even well‐documented invasion histories to better understand invasion processes, with direct implications for understanding contemporary gene flow and informing invasion management.

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)

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)

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.

The Toxicology Investigators Consortium 2023 Annual Report - Adrienne Hughes; Alexandra Amaducci; Sharan L. Campleman; Shao Li; Mari Costantini; Meghan B. Spyres; Hannah Spungen; Jessica Kent; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; et al. (Journal of Medical Toxicology, 2024)

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)

Challenges and Strategies for Knowledge Co-Production in Ecosystem and Natural Hazards Research - Sarah Kolesar; Peter Ruggiero; Desirée Tullos; Jenna Tilt; Bryan Tilt; Brook Thompson (Oceanography, 2024)
The grand environmental challenges society faces cannot be solved without knowledge contributions from communities that are touched by the outcomes and impacts of research. Recognizing and valuing these sources, a research method known as co-production of knowledge involves collaboration of interested parties and knowledge owners in activities ranging from identifying research needs to study design, data collection, interpretation, and evaluation. We present a novel approach to the administrative and financial support for knowledge co-production developed by Oregon Sea Grant and provide examples from two funded project teams. We summarize barriers to these approaches, discuss points of symmetry, and propose good practices. One project emphasized equitable alternative strategies for chronic and acute coastal hazard adaptation and mitigation. The other project looked beyond dam removal in the Klamath River Basin to generate place-based and generalizable understanding of, and equitable decisions around, water quality and socio-ecological systems undergoing change. Both projects provide high-level lessons regarding opportunities and challenges encountered in the engaged research process, highlighting flexibility and adaptability as two important considerations.

The Toxicology Investigators Consortium 2022 Annual Report - Alexandra M. Amaducci; Sharan L. Campleman; Shao Li; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; Rachel E. Culbreth; Paul M. Wax; Jeffrey Brent; Kim Aldy; Jennifer Acciani; et al. (Journal of Medical Toxicology, 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)

Population structure and reproductive states of the dogwhelk Nucella lapillus differ between artificial structures and natural rocky shores - Bryan Thompson; Paul R. Brooks; Veronica Farrugia Drakard; Fiona Kubin; Hannah S. Earp; Ignacio Alvarez-Cienfuegos; Pippa J. Moore; Tasman P. Crowe (Marine Environmental Research, 2023)

Evidence for Pleistocene gene flow through the ice-free corridor from extinct horses and camels from Natural Trap Cave, Wyoming - Kieren J. Mitchell; Pere Bover; Alexander T. Salis; Caitlin Mudge; Holly Heiniger; Mary Thompson; Bryan Hockett; Laura S. Weyrich; Alan Cooper; Julie A. Meachen (Quaternary International, 2023)

The population structure, sex ratio and reproductive potential of limpets (Patella spp.) on natural shores and artificial structures in the Irish Sea - Hannah S. Earp; Ruby George; Paul R. Brooks; Veronica Farrugia Drakard; Bryan J. Thompson; Benjamin Fisher; Róisín Hayden; Tasman P. Crowe; Pippa J. Moore (Marine Environmental Research, 2023)

The Toxicology Investigators Consortium Case Registry—the 2021 Annual Report - Jennifer S. Love; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; HoanVu Nguyen; Sharan L. Campleman; Shao Li; Paul M. Wax; Jeffery Brent; Kim Aldy; Michael Abesamis; et al. (Journal of Medical Toxicology, 2022)

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.

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.

Biodiversity and climate determine the functioning of Neotropical forests - Lourens Poorter; Masha T. van der Sande; Eric J. M. M. Arets; Nataly Ascarrunz; Brian Enquist; Bryan Finegan; Juan Carlos Licona; Miguel Martínez‐Ramos; Lucas Mazzei; Jorge A. Meave; Rodrigo Muñoz; Christopher J. Nytch; et al. (Global Ecology and Biogeography, 2018)

Biodiversity and climate determine the functioning of Neotropical forests - Lourens Poorter; Masha T. van der Sande; Eric J. M. M. Arets; Nataly Ascarrunz; Brian J. Enquist; Bryan Finegan; Juan Carlos Licona; Miguel Martínez‐Ramos; Lucas Mazzei; Jorge A. Meave; Rodrigo Muñoz; Christopher J. Nytch; et al. (Global Ecology and Biogeography, 2017)
Aim Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community‐mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance). Location Neotropics. Methods We used data from 26 sites, 201 1‐ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community‐weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics. Results Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community‐mean traits were good predictors of biomass stocks and dynamics. Main conclusions Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community‐weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper‐diverse tropical forests.

Age constraints on the hydrothermal history of the Prominent Hill iron oxide copper-gold deposit, South Australia - Bryan Bowden; Geoff Fraser; Garry J Davidson; Sebastien Meffre; Roger Skirrow; Stuart Bull; Jay Thompson (Mineralium Deposita, 2017)

Integrated Assessment of Wind Effects on Central California’s Pelagic Ecosystem - Marisol García-Reyes; William J. Sydeman; Sarah Ann Thompson; Bryan A. Black; Ryan R. Rykaczewski; Julie A. Thayer; Steven J. Bograd (Ecosystems, 2013)

Genomic analysis of oceanic cyanobacterial myoviruses compared with T4‐like myoviruses from diverse hosts and environments - Matthew B. Sullivan; Katherine H. Huang; Julio C. Ignacio‐Espinoza; Aaron M. Berlin; Libusha Kelly; Peter R. Weigele; Alicia S. DeFrancesco; Suzanne E. Kern; Luke R. Thompson; Sarah Young; Chandri Yandava; Ross Fu; et al. (Environmental Microbiology, 2010)
Summary T4‐like myoviruses are ubiquitous, and their genes are among the most abundant documented in ocean systems. Here we compare 26 T4‐like genomes, including 10 from non‐cyanobacterial myoviruses, and 16 from marine cyanobacterial myoviruses (cyanophages) isolated on diverse Prochlorococcus or Synechococcus hosts. A core genome of 38 virion construction and DNA replication genes was observed in all 26 genomes, with 32 and 25 additional genes shared among the non‐cyanophage and cyanophage subsets, respectively. These hierarchical cores are highly syntenic across the genomes, and sampled to saturation. The 25 cyanophage core genes include six previously described genes with putative functions ( psbA , mazG , phoH , hsp20 , hli03 , cobS ), a hypothetical protein with a potential phytanoyl‐CoA dioxygenase domain, two virion structural genes, and 16 hypothetical genes. Beyond previously described cyanophage‐encoded photosynthesis and phosphate stress genes, we observed core genes that may play a role in nitrogen metabolism during infection through modulation of 2‐oxoglutarate. Patterns among non‐core genes that may drive niche diversification revealed that phosphorus‐related gene content reflects source waters rather than host strain used for isolation, and that carbon metabolism genes appear associated with putative mobile elements. As well, phages isolated on Synechococcus had higher genome‐wide %G+C and often contained different gene subsets (e.g. petE , zwf , gnd , prnA , cpeT ) than those isolated on Prochlorococcus . However, no clear diagnostic genes emerged to distinguish these phage groups, suggesting blurred boundaries possibly due to cross‐infection. Finally, genome‐wide comparisons of both diverse and closely related, co‐isolated genomes provide a locus‐to‐locus variability metric that will prove valuable for interpreting metagenomic data sets.

A hydrogeochemical survey of Kilimanjaro (Tanzania): implications for water sources and ages - Jeffrey M. Mckenzie; Bryan G. Mark; Lonnie G. Thompson; Ulrich Schotterer; Ping-Nan Lin (Hydrogeology Journal, 2010)

Long Wavelength Fluorescence Lifetime Standards for Front-Face Fluorometry - Bryan J. McCranor; Richard B. Thompson (Journal of Fluorescence, 2010)

ATF3 transcription factor and its emerging roles in immunity and cancer - Matthew R. Thompson; Dakang Xu; Bryan R. G. Williams (Journal of Molecular Medicine, 2009)

Hydrogen isotope ratios of individual lipids in lake sediments as novel tracers of climatic and environmental change: a surface sediment test - Yongsong Huang; Bryan Shuman; Yi Wang; Thompson Webb (Journal of Paleolimnology, 2004)

Gene Expression Analyzed by Microarrays in HSV-1 Latent Mouse Trigeminal Ganglion Following Heat Stress - James M. Hill; Walter J. Lukiw; Bryan M. Gebhardt; Shiro Higaki; Jeannette M. Loutsch; Marvin E. Myles; Hilary W. Thompson; Byoung S. Kwon; Nicolas G. Bazan; Herbert E. Kaufman (Virus Genes, 2001)

s of papers presented at the 81st annual meeting of The Potato Association of America Charlottetown, P.E.I., Canada August 3 – 7, 1997 - S. T. Ali-Khan; C. Hetner; L. Ladislav; V. Currie; Walter J. Arsenault; A. Naseer Aziz; Janet E. A. Seabrook; George C. C. Tai; J. B. Bamberg; Alfonso H. del Rio; Max Martin; J. B. Bamberg; et al. (American Journal of Potato Research, 1997)