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.

Pre-Clinical Models of Heart Failure with Preserved Ejection Fraction: Advancing Knowledge for Device Based Therapies - Nina Langer; Andreas Escher; Caglar Ozturk; Andrew F. Stephens; Ellen T. Roche; Marcus Granegger; David M. Kaye; Shaun D. Gregory (Annals of Biomedical Engineering, 2025)
Heart failure with preserved ejection fraction (HFpEF) is a growing health problem worldwide, accounting for half of all heart failure cases. HFpEF patients present with diverse underlying causes and symptoms, making diagnosis and treatment challenging. Current pharmacological therapies are inadequate, while approved device-based therapies have shown limited success due to patient heterogeneity. This underscores the need for improved pre-clinical models, critical for guiding the design and development of effective therapeutic devices. This paper presents an overview of current pre-clinical HFpEF models, including in-silico, in-vitro, ex-vivo, and in-vivo approaches, aimed at advancing the understanding of HFpEF physiology and the development of device-based therapies. We examined each model's ability to replicate key HFpEF characteristics, discuss their respective strengths and limitations, and highlight their role in supporting the creation of clinically relevant solutions. Additionally, the potential of emerging advancements is explored.

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)

Transferability of ecological forecasting models to novel biotic conditions in a long‐term experimental study - Patricia Kaye T. Dumandan; Juniper L. Simonis; Glenda M. Yenni; S. K. Morgan Ernest; Ethan P. White (Ecology, 2024)
Ecological forecasting models play an increasingly important role for managing natural resources and assessing our fundamental knowledge of processes driving ecological dynamics. As global environmental change pushes ecosystems beyond their historical conditions, the utility of these models may depend on their transferability to novel conditions. Because species interactions can alter resource use, timing of reproduction, and other aspects of a species' realized niche, changes in biotic conditions, which can arise from community reorganization events in response to environmental change, have the potential to impact model transferability. Using a long‐term experiment on desert rodents, we assessed model transferability under novel biotic conditions to better understand the limitations of ecological forecasting. We show that ecological forecasts can be less accurate when the models generating them are transferred to novel biotic conditions and that the extent of model transferability can depend on the species being forecast. We also demonstrate the importance of incorporating uncertainty into forecast evaluation with transferred models generating less accurate and more uncertain forecasts. These results suggest that how a species perceives its competitive landscape can influence model transferability and that when uncertainties are properly accounted for, transferred models may still be appropriate for decision making. Assessing the extent of the transferability of forecasting models is a crucial step to increase our understanding of the limitations of ecological forecasts.

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.

Mapping canopy cover for municipal forestry monitoring: Using free Landsat imagery and machine learning - Mitchell T. Bonney; Yuhong He; Jody Vogeler; Tenley Conway; Esther Kaye (Urban Forestry & Urban Greening, 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)

Non-avian dinosaur eggshell calcite can contain ancient, endogenous amino acids - Evan T. Saitta; Jakob Vinther; Molly K. Crisp; Geoffrey D. Abbott; Lucy Wheeler; Samantha Presslee; Thomas G. Kaye; Ian Bull; Ian Fletcher; Xinqi Chen; Daniel Vidal; Fernando Sanguino; et al. (Geochimica et Cosmochimica Acta, 2024)

Shifts in competitive structures can drive variation in species' phenology - Patricia Kaye T. Dumandan; Glenda M. Yenni; S. K. Morgan Ernest (Ecology, 2023)
For many species, a well documented response to anthropogenic climate change is a shift in various aspects of its life history, including its timing or phenology. Often, these phenological shifts are associated with changes in abiotic factors used as proxies for resource availability or other suitable conditions. Resource availability, however, can also be impacted by competition, but the impact of competition on phenology is less studied than abiotic drivers. We fit generalized additive models (GAMs) to a long‐term experimental dataset on small mammals monitored in the southwestern United States and show that altered competitive landscapes can drive shifts in breeding timing and prevalence, and that, relative to a dominant competitor, other species exhibit less specific responses to environmental factors. These results suggest that plasticity of phenological responses, which is often described in the context of annual variation in abiotic factors, can occur in response to biotic context as well. Variation in phenological responses under different biotic conditions shown here further demonstrates that a more nuanced understanding of shifting biotic interactions is useful to better understand and predict biodiversity patterns in a changing world.

Consequences of fire and other prairie management treatments for macrofungi in the Pacific Northwest of the U. S. A. - Bitty A. Roy; Sarah T. Hamman; Hannah Soukup; Wes Messinger; Roo Vandegrift; Keyyana Blount; Denise E.L. Giles; Thomas N. Kaye (Fungal Ecology, 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)

Microplastics in surface water of Laguna de Bay: first documented evidence on the largest lake in the Philippines - Cris Gel Loui A. Arcadio; Carl Kenneth P. Navarro; Kaye M. Similatan; Sherley Ann T. Inocente; Sheila Mae B. Ancla; Marybeth Hope T. Banda; Rey Y. Capangpangan; Armi G. Torres; Hernando P. Bacosa (Environmental Science and Pollution Research, 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.

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)

From Surface Water to the Deep Sea: A Review on Factors Affecting the Biodegradation of Spilled Oil in Marine Environment - Hernando Pactao Bacosa; Sheila Mae B. Ancla; Cris Gel Loui A. Arcadio; John Russel A. Dalogdog; Dioniela Mae C. Ellos; Heather Dale A. Hayag; Jiza Gay P. Jarabe; Ahl Jimhar T. Karim; Carl Kenneth P. Navarro; Mae Princess I. Palma; Rodolfo A. Romarate; Kaye M. Similatan; et al. (Journal of Marine Science and Engineering, 2022)
Over the past century, the demand for petroleum products has increased rapidly, leading to higher oil extraction, processing and transportation, which result in numerous oil spills in coastal-marine environments. As the spilled oil can negatively affect the coastal-marine ecosystems, its transport and fates captured a significant interest of the scientific community and regulatory agencies. Typically, the environment has natural mechanisms (e.g., photooxidation, biodegradation, evaporation) to weather/degrade and remove the spilled oil from the environment. Among various oil weathering mechanisms, biodegradation by naturally occurring bacterial populations removes a majority of spilled oil, thus the focus on bioremediation has increased significantly. Helping in the marginal recognition of this promising technique for oil-spill degradation, this paper reviews recently published articles that will help broaden the understanding of the factors affecting biodegradation of spilled oil in coastal-marine environments. The goal of this review is to examine the effects of various environmental variables that contribute to oil degradation in the coastal-marine environments, as well as the factors that influence these processes. Physico-chemical parameters such as temperature, oxygen level, pressure, shoreline energy, salinity, and pH are taken into account. In general, increase in temperature, exposure to sunlight (photooxidation), dissolved oxygen (DO), nutrients (nitrogen, phosphorous and potassium), shoreline energy (physical advection—waves) and diverse hydrocarbon-degrading microorganisms consortium were found to increase spilled oil degradation in marine environments. In contrast, higher initial oil concentration and seawater pressure can lower oil degradation rates. There is limited information on the influences of seawater pH and salinity on oil degradation, thus warranting additional research. This comprehensive review can be used as a guide for bioremediation modeling and mitigating future oil spill pollution in the marine environment by utilizing the bacteria adapted to certain conditions.

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.

Shared functional traits explain synchronous changes in long‐term count trends of migratory raptors - Patricia Kaye T. Dumandan; Keith L. Bildstein; Laurie J. Goodrich; Andrii Zaiats; T. Trevor Caughlin; Todd E. Katzner (Global Ecology and Biogeography, 2021)
Aim Assessing long‐term shifts in faunal assemblages is important to understand the consequences of ongoing global environmental change. One approach to assess drivers of assemblage changes is to identify the traits associated with synchronous shifts in count trends among species. Our research identified traits influencing trends in 73 years of count data on migrating raptors recorded in the north‐eastern USA. Location Pennsylvania, USA. Time period 1946–2018. Major taxa studied Birds of prey/raptors. Methods Migrating raptors were counted during autumn, following a standardized protocol. We used a hierarchical breakpoint model to identify when count trends shifted and to assess the role of traits in driving these trends before and after the breakpoint. Specifically, we quantified the probability of the direction (PD) of an effect of body mass, habitat or dietary specialization, migratory behaviour and susceptibility to dichlorodiphenyltrichloroethane (DDT) on count trends. Results We documented an assemblage‐wide mean shift in count trends of migrating raptors in 1974. In general, species that exhibited negative count trends before the breakpoint exhibited positive count trends afterwards. We found that traits associated with resource use (diet and habitat specialization) had high probabilities of affecting count trends, pre‐ and post‐breakpoint (> 90%). Moreover, the direction of their effects differed during both periods. Unexpectedly, other traits we evaluated, including DDT susceptibility, had relatively weaker associations with count trends. Main conclusions Trait‐based frameworks have promise for testing generalized assumptions about drivers of population trajectories. Historically, DDT was considered a key driver of changes in raptor population trends. However, our analysis suggests that other factors were also relevant. Moreover, the positive association between count trends and generalist behaviour depended on the temporal context. This result has implications for other settings where demographic trends can be linked to traits and help to identify drivers of biodiversity change.

2,3,7,8-Tetrachlorodibenzo-p-dioxin Induces Vascular Dysfunction That is Dependent on Perivascular Adipose and Cytochrome P4501A1 Expression - Mary T. Walsh-Wilcox; Joel Kaye; Efrat Rubinstein; Mary K. Walker (Cardiovascular Toxicology, 2019)

Acute prazosin administration does not reduce stressor reactivity in healthy adults - Jesse T Kaye; Gaylen E Fronk; Aleksandra E Zgierska; Maireni R Cruz; David Rabago; John J Curtin (Psychopharmacology, 2019)

Imperatives for Conservation in a Threatened Center of Biodiversity - Marine Servonnat; Ryan Kaye; Fernando P. Siringan; Jeffrey Munar; Helen T. Yap (Coastal Management, 2019)

Rhizosphere priming and plant-mediated cover crop decomposition - Steven T. Rosenzweig; Meagan E. Schipanski; Jason P. Kaye (Plant and Soil, 2017)

A Diagnostic Decision Support System for BMP Selection in Small Urban Watershed - Yan Wang; Hubert J. Montas; Kaye L. Brubaker; Paul T. Leisnham; Adel Shirmohammadi; Victoria Chanse; Amanda K. Rockler (Water Resources Management, 2017)

Independent risk factors for the co-colonization of vancomycin-resistant Enterococcus faecalis and methicillin-resistant Staphylococcus aureus in the region most endemic for vancomycin-resistant Staphylococcus aureus isolation - K. Hayakawa; D. Marchaim; P. Bathina; E. T. Martin; J. M. Pogue; B. Sunkara; S. Kamatam; K. Ho; L. B. Willis; M. Ajamoughli; D. Patel; A. Khan; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2013)

Incident radiation and the allocation of nitrogen within A rctic plant canopies: implications for predicting gross primary productivity - Lorna E. Street; Gaius R. Shaver; Edward B. Rastetter; Mark T. van Wijk; Brooke A. Kaye; Mathew Williams (Global Change Biology, 2012)
Arctic vegetation is characterized by high spatial variability in plant functional type ( PFT ) composition and gross primary productivity ( P ). Despite this variability, the two main drivers of P in sub‐ A rctic tundra are leaf area index ( L T ) and total foliar nitrogen ( N T ). L T and N T have been shown to be tightly coupled across PFT s in sub‐Arctic tundra vegetation, which simplifies up‐scaling by allowing quantification of the main drivers of P from remotely sensed L T . Our objective was to test the L T – N T relationship across multiple Arctic latitudes and to assess L T as a predictor of P for the pan‐ A rctic. Including PFT ‐specific parameters in models of L T – N T coupling provided only incremental improvements in model fit, but significant improvements were gained from including site‐specific parameters. The degree of curvature in the L T – N T relationship, controlled by a fitted canopy nitrogen extinction co‐efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass ( N M ), and we show for the first time that L T – N T coupling is achieved across latitudes via canopy‐scale trade‐offs between N M and leaf mass per unit leaf area ( L M ). Site‐specific parameters provided small but significant improvements in models of P based on L T and moss cover. Our results suggest that differences in L T – N T coupling between sites could be used to improve pan‐Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.

Tobacco withdrawal components and their relations with cessation success - Megan E. Piper; Tanya R. Schlam; Jessica W. Cook; Megan A. Sheffer; Stevens S. Smith; Wei-Yin Loh; Daniel M. Bolt; Su-Young Kim; Jesse T. Kaye; Kathryn R. Hefner; Timothy B. Baker (Psychopharmacology, 2011)

Persistence and expansion of ponderosa pine woodlands in the west‐central Great Plains during the past two centuries - Margot W. Kaye; Connie A. Woodhouse; Stephen T. Jackson (Journal of Biogeography, 2010)
Aim Woody plant expansion and infilling in grasslands and savannas are occurring across a broad range of ecosystems around the globe and are commonly attributed to fire suppression, livestock grazing, nutrient enrichment and/or climate variability. In the western Great Plains, ponderosa pine ( Pinus ponderosa ) woodlands are expanding across broad geographical and environmental gradients. The objective of this study was to reconstruct the establishment of ponderosa pine in woodlands in the west‐central Great Plains and to identify whether it was mediated by climate variability. Location Our study took place in a 400‐km wide region from the base of the Front Range Mountains ( c . 105° W) to the central Great Plains ( c . 100° W) and from Nebraska (43° N) to northern New Mexico (36° N), USA. Methods Dates for establishment of ponderosa pine were reconstructed with tree rings in 11 woodland sites distributed across the longitudinal and latitudinal gradients of the study area. Temporal trends in decadal pine establishment were compared with summer Palmer Drought Severity Index (PDSI). Annual trends in pine establishment from 1985 to 2005 were compared with seasonal PDSI, temperature and moisture availability. Results Establishment of ponderosa pine occurred in the study area in all but one decade (1770s) between the 1750s and the early 2000s, with over 35% of establishment in the region occurring after 1980. Pine establishment was highly variable among sites. Across the region, decadal pine establishment was persistently low from 1940 to 1960, when PDSI was below average. Annual pine establishment from 1985 to 2005 was positively correlated with summer PDSI and inversely correlated with minimum spring temperatures. Main conclusions Most ponderosa pine woodlands pre‐date widespread Euro‐American settlement of the region around c . ad 1860 and currently have stable tree populations. High variability in the timing of establishment of pine among sites highlights the multiplicity of factors that can drive woodland dynamics, including land use, fire history, CO 2 enrichment, tree population dynamics and climate. Since the 1840s, the influence of climate was most notable across the study area during the mid‐20th century, when the establishment of pine was suppressed by two significant droughts. The past sensitivity of establishment of ponderosa pine to drought suggests that woodland expansion will be negatively affected by predicted increases in temperature and drought in the Great Plains.

Long‐term impact of a stand‐replacing fire on ecosystem CO 2 exchange of a ponderosa pine forest - S. DORE; T. E. KOLB; M. MONTES‐HELU; B. W. SULLIVAN; W. D. WINSLOW; S. C. HART; J. P. KAYE; G. W. KOCH; B. A. HUNGATE (Global Change Biology, 2008)
Ponderosa pine ( Pinus ponderosa ) forests of the southwestern United States are a mosaic of stands where undisturbed forests are carbon sinks, and stands recovering from wildfires may be sources of carbon to the atmosphere for decades after the fire. However, the relative magnitude of these sinks and sources has never been directly measured in this region, limiting our understanding of the role of fire in regional and US carbon budgets. We used the eddy covariance technique to measure the CO 2 exchange of two forest sites, one burned by fire in 1996, and an unburned forest. The fire was a high‐intensity stand‐replacing burn that killed all trees. Ten years after the fire, the burned site was still a source of CO 2 to the atmosphere [109±6 (SEM) g C m −2 yr −1 ], whereas the unburned site was a sink (−164±23 g C m −2 yr −1 ). The fire reduced total carbon storage and shifted ecosystem carbon allocation from the forest floor and living biomass to necromass. Annual ecosystem respiration was lower at the burned site (480±5 g C m −2 yr −1 ) than at the unburned site (710±54 g C m −2 yr −1 ), but the difference in gross primary production was even larger (372±13 g C m −2 yr −1 at the burned site and 858±37 g C m −2 yr −1 at the unburned site). Water availability controlled carbon flux in the warm season at both sites, and the burned site was a source of carbon in all months, even during the summer, when wet and warm conditions favored respiration more than photosynthesis. Our study shows that carbon losses following stand‐replacing fires in ponderosa pine forests can persist for decades due to slow recovery of the gross primary production. Because fire exclusion is becoming increasingly difficult in dry western forests, a large US forest carbon sink could shift to a decadal‐scale carbon source.

Poster abstracts - J. Ferrie; M. Shipley; F. Cappuccio; E. Brunner; M. Miller; M. Kumari; M. Marmot; A. Coenen; J. L. Castillo; F. Araya; G. Bustamante; L. Montecino; et al. (Sleep and Biological Rhythms, 2007)

FatalLegionella longbeachae infection following heart transplantation - T. M. Korman; A. Fuller; J. Ibrahim; D. Kaye; P. Bergin (European Journal of Clinical Microbiology & Infectious Diseases, 1998)

The effects of increasing CO 2 and temperature on oak leaf palatability and the implications for herbivorous insects - S. J. Dury; J. E. G. Good; C. M. Perrins; A. Buse; T. Kaye (Global Change Biology, 1998)
Rising levels of atmospheric CO 2 are expected to perturb forest ecosystems, although the extent to which specific ecological interactions will be modified is unclear. This research evaluates the effects of elevated CO 2 and temperature, alone and in combination, on the leaf nutritional quality of Pendunculate oak ( Quercus robur L. ), and the implications for herbiverous insect defoliators are discussed. A 3 °C temperature rise reduced leaf nutritional quality, by reducing foliar nitrogen concentration and increasing condensed tannin content. Doubling atmospheric CO 2 temporarily increased total phenolics, but also reduced leaf toughness. The nutritional quality of the second leaf flush (lammas growth) was considerably reduced at elevated CO 2 . It is concluded that larval development of spring‐feeding defoliators and hence adult fecundity may be adversely affected by increased temperatures.

Molecular characterization of a bean α-amylase inhibitor that inhibits the α-amylase of the Mexican bean weevil Zabrotes subfasciatus - M. Fatima Grossi de Sa; T. Erik Mirkov; Masao Ishimoto; Gabriella Colucci; Kaye S. Bateman; Maarten J. Chrispeels (Planta, 1997)