Nutrient addition hinders microarthropod-driven leaf litter decomposition in Patagonian woodlands - M. M. Fernández; M. W. Kaye; D. M. Eissenstat; N. Pérez-Méndez; L. A. Garibaldi (Plant and Soil, 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.

A comprehensive approach for detecting and locating black carbon in human placentae - Atsuo Chiu; Denise Ivey; Amanda Sanko; Barbara Tisdale; Philip J. Katzman; Thomas G. O’Connor; Kaye Thomas; Tanzy Love; Rogelio Perez-D’Gregorio; Carolyn M. Salafia; Richard K. Miller; Philip K. Hopke (Air Quality, Atmosphere & Health, 2026)

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.

Role of hepatocellular senescence in the development of hepatocellular carcinoma and the potential for therapeutic manipulation - Pramudi Wijayasiri; Stuart Astbury; Grace Needham; Philip Kaye; Mamatha Bhat; Anna M. Piccinini; Aloysious D. Aravinthan (Human Cell, 2025)
Accumulation of senescent hepatocytes is universal in chronic liver disease (CLD). This study investigates an association between hepatocyte senescence and hepatocellular carcinoma (HCC) and explores the therapeutic role of sirolimus. Background liver biopsies from 15 patients with cirrhosis and HCC and 45 patients with cirrhosis were stained for p16, a marker of cell senescence. STAM™ mice were randomized into 3 groups of 5 at 4 weeks of age and administered vehicle ± sirolimus intraperitoneally, thrice weekly, from 4 to 18 weeks of age. Placebo group was an administered vehicle, early sirolimus group was an administered vehicle with sirolimus, late sirolimus group was an administered vehicle from 4 to 12 weeks then vehicle with sirolimus from 12 to 18 weeks. The primary outcome was HCC nodule development. Senescent hepatocyte burden and senescence-associated secretory phenotype (SASP) factors were assessed in mice livers. In the human study, age (OR 1.282, 95% CI 1.086–1.513, p = 0.003) and p16 (OR 1.429, 95% CI 1.112–1.838, p = 0.005) were independently associated with HCC. In the animal study, all three groups exhibited similar MASLD activity scores ( p = 0.39) and fibrosis area ( p = 0.92). The number and the maximum diameter of HCC nodules were significantly lower in the early sirolimus group compared to placebo and late sirolimus group. The gene expression of SASP factors was similar in all groups. Protein levels of some SASP factors (TNFα, IL1β, IL-2, CXCL15) were significantly lower in sirolimus administered groups compared to placebo group. The study demonstrates an independent association between senescent hepatocyte burden and HCC. It indicates a potential chemoprophylactic role for sirolimus through SASP factor inhibition. These early results could inform a future human clinical trial. Graphical abstract

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)

HeartMate 3 for Heart Failure with Preserved Ejection Fraction: In Vitro Hemodynamic Evaluation and Anatomical Fitting - Nina Langer; Andrew F. Stephens; Michael Šeman; David McGiffin; David M. Kaye; Shaun D. Gregory (Annals of Biomedical Engineering, 2024)
Heart failure with preserved ejection fraction (HFpEF) constitutes approximately 50% of heart failure (HF) cases, and encompasses different phenotypes. Among these, most patients with HFpEF exhibit structural heart changes, often with smaller left ventricular cavities, which pose challenges for utilizing ventricular assist devices (VADs). A left atrial to aortic (LA-Ao) VAD configuration could address these challenges, potentially enhancing patient quality of life by lowering elevated mean left atrial pressure (MLAP). This study assessed the anatomical compatibility and left atrial unloading capacity using a simulated VAD-supported HFpEF patient. A HeartMate3-supported HFpEF patient in an LA-Ao configuration was simulated using a cardiovascular simulator. Hemodynamic parameters were recorded during rest and exercise at seven pump flow rates. Computed tomography scans of 14 HFpEF (NYHA II–III) and six heart failure with reduced ejection fraction patients were analysed for anatomical comparisons. HFpEF models were independently assessed for virtual anatomical fit with the HM3 in the LA-Ao configuration. Baseline MLAP was reduced from 15 to 11 mmHg with the addition of 1 L/min HM3 support in the rest condition. In an exercise simulation, 6 L/min of HM3 support was required to reduce the MLAP from 29 to 16 mmHg. The HM3 successfully accommodated six HFpEF patients without causing interference with other cardiac structures, whereas it caused impingement ranging from 4 to 14 mm in the remaining patients. This study demonstrated that the HM3 in an LA-Ao configuration may be suitable for unloading the left atrium and relieving pulmonary congestion in some HFpEF patients where size-related limitations can be addressed through pre-surgical anatomical fit analysis.

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)

Mechanistic microclimate models and plant pest risk modelling - Jonathan R. Mosedale; Dominic Eyre; Anastasia Korycinska; Matthew Everatt; Sam Grant; Brittany Trew; Neil Kaye; Deborah Hemming; Ilya M. D. Maclean (Journal of Pest Science, 2024)
Climatic conditions are key determining factors of whether plant pests flourish. Models of pest response to temperature are integral to pest risk assessment and management, helping to inform surveillance and control measures. The widespread use of meteorological data as predictors in these models compromises their reliability as these measurements are not thermally coupled to the conditions experienced by pest organisms or their body temperatures. Here, we present how mechanistic microclimate models can be used to estimate the conditions experienced by pest organisms to provide significant benefits to pest risk modelling. These well-established physical models capture how landscape, vegetation and climate interact to determine the conditions to which pests are exposed. Assessments of pest risk derived from microclimate conditions are likely to significantly diverge from those derived from weather station measurements. The magnitude of this divergence will vary across a landscape, over time and according to pest habitats and behaviour due to the complex mechanisms that determine microclimate conditions and their effect on pest biology. Whereas the application of microclimate models was once restricted to relatively homogeneous habitats, these models can now be applied readily to generate hourly time series across extensive and varied landscapes. We outline the benefits and challenges of more routine application of microclimate models to pest risk modelling. Mechanistic microclimate models provide a heuristic tool that helps discriminate between physical, mathematical and biological causes of model failure. Their use can also help understand how pest ecology, behaviour and physiology mediate the relationship between climate and pest response.

Allicin and total phenolic content in ramps (Allium tricoccum Ait.) in relation to phenological stage, morphological traits, and harvest location - R. Teal Jordan; Eric P. Burkhart; Margot Kaye; David Munoz; Joshua D. Lambert (Biochemical Systematics and Ecology, 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)

Identifying predictors of translocation success in rare plant species - Joe Bellis; Oyomoare Osazuwa‐Peters; Joyce Maschinski; Matthew J. Keir; Elliott W. Parsons; Thomas N. Kaye; Michael Kunz; Jennifer Possley; Eric Menges; Stacy A. Smith; Daniela Roth; Debbie Brewer; et al. (Conservation Biology, 2024)
The fundamental goal of a rare plant translocation is to create self‐sustaining populations with the evolutionary resilience to persist in the long term. Yet, most plant translocation syntheses focus on a few factors influencing short‐term benchmarks of success (e.g., survival and reproduction). Short‐term benchmarks can be misleading when trying to infer future growth and viability because the factors that promote establishment may differ from those required for long‐term persistence. We assembled a large ( n = 275) and broadly representative data set of well‐documented and monitored (7.9 years on average) at‐risk plant translocations to identify the most important site attributes, management techniques, and species’ traits for six life‐cycle benchmarks and population metrics of translocation success. We used the random forest algorithm to quantify the relative importance of 29 predictor variables for each metric of success. Drivers of translocation outcomes varied across time frames and success metrics. Management techniques had the greatest relative influence on the attainment of life‐cycle benchmarks and short‐term population trends, whereas site attributes and species’ traits were more important for population persistence and long‐term trends. Specifically, large founder sizes increased the potential for reproduction and recruitment into the next generation, whereas declining habitat quality and the outplanting of species with low seed production led to increased extinction risks and a reduction in potential reproductive output in the long‐term, respectively. We also detected novel interactions between some of the most important drivers, such as an increased probability of next‐generation recruitment in species with greater seed production rates, but only when coupled with large founder sizes. Because most significant barriers to plant translocation success can be overcome by improving techniques or resolving site‐level issues through early intervention and management, we suggest that by combining long‐term monitoring with adaptive management, translocation programs can enhance the prospects of achieving long‐term success.

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)

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)

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)

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.

Buoyancy distribution in a filling box segmented by a planar jet - N. Kaye; N. Williamson; D. Huang; S. W. Armfield (Environmental Fluid Mechanics, 2021)

Drought timing and local climate determine the sensitivity of eastern temperate forests to drought - Loïc D'Orangeville; Justin Maxwell; Daniel Kneeshaw; Neil Pederson; Louis Duchesne; Travis Logan; Daniel Houle; Dominique Arseneault; Colin M. Beier; Daniel A. Bishop; Daniel Druckenbrod; Shawn Fraver; et al. (Global Change Biology, 2018)
Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi‐arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America ( ENA ) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA , representing 24 species and 346 stands, to determine the broad‐scale drivers of drought sensitivity for the dominant trees in ENA . Here we show that two factors—the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET )—are stronger drivers of drought sensitivity than soil and stand characteristics. Drought‐induced reductions in tree growth were greatest when the droughts occurred during early‐season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET ). Further, mean species trait values (rooting depth and ψ 50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early‐season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors.

Interspecific variation in growth responses to climate and competition of five eastern tree species - Christine R. Rollinson; Margot W. Kaye; Charles D. Canham (Ecology, 2016)
Climate and competition are often presented from two opposing views of the dominant driver of individual tree growth and species distribution in temperate forests, such as those in the eastern United States. Previous studies have provided abundant evidence indicating that both factors influence tree growth, and we argue that these effects are not independent of one another and rather that interactions between climate, competition, and size best describe tree growth. To illustrate this point, we describe the growth responses of five common eastern tree species to interacting effects of temperature, precipitation, competition, and individual size using maximum likelihood estimation. Models that explicitly include interactions among these four factors explained over half of the variance in annual growth for four out of five species using annual climate. Expanding temperature and precipitation analyses to include seasonal interactions resulted in slightly improved models with a mean R 2 of 0.61 ( SD 0.10). Growth responses to individual factors as well their interactions varied greatly among species. For example, growth sensitivity to temperature for Quercus rubra increased with maximum annual precipitation, but other species showed no change in sensitivity or slightly reduced annual growth. Our results also indicate that three‐way interactions among individual stem size, competition, and temperature may determine which of the five co‐occurring species in our study could have the highest growth rate in a given year. Continued consideration and quantification of interactions among climate, competition, and individual‐based characteristics are likely to increase understanding of key biological processes such as tree growth. Greater parameterization of interactions between traditionally segregated factors such as climate and competition may also help build a framework to reconcile drivers of individual‐based processes such as growth with larger‐scale patterns of species distribution.

The role of participation sampling and statistical analysis in medical research - Ngoc Vo; Xiulu Ruan; Alan D. Kaye (European Journal of Applied Physiology, 2016)

Microclimate and ecological threshold responses in a warming and wetting experiment following whole tree harvest - M. D. McDaniel; R. J. Wagner; C. R. Rollinson; B. A. Kimball; M. W. Kaye; J. P. Kaye (Theoretical and Applied Climatology, 2014)

Climate change interactions affect soil carbon dioxide efflux and microbial functioning in a post-harvest forest - M. D. McDaniel; J. P. Kaye; M. W. Kaye; M. A. Bruns (Oecologia, 2014)

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)

Autonomic Control of the Aging Heart - David M. Kaye; Murray D. Esler (NeuroMolecular Medicine, 2008)

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.

F2-Isoprostanes as Biomarkers of Late-onset Alzheimer’s Disease - Thomas J. Montine; Joseph Quinn; Jeffrey Kaye; Jason D. Morrow (Journal of Molecular Neuroscience, 2007)

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)

Obesity and the risk of prostate cancer (United States) - Brian D. Bradbury; Jemma B. Wilk; James A. Kaye (Cancer Causes & Control, 2005)

Targeted mapping of a sugarcane rust resistance gene (Bru1) using bulked segregant analysis and AFLP markers - C. Asnaghi; D. Roques; S. Ruffel; C. Kaye; J.-Y. Hoarau; H. Télismart; J. C. Girard; L. M. Raboin; A. M. Risterucci; L. Grivet; A. D’Hont (Theoretical and Applied Genetics, 2004)

Phenotypic expression of the systemic toxicity of cocaine in genetically epilepsy-prone rats - Bing Shi; James E. Heavner; Charles E. Reigel; Y. James Kao; Alan D. Kaye (Naunyn-Schmiedeberg's Archives of Pharmacology, 2000)

Application of synteny across Poaceae to determine the map location of a sugarcane rust resistance gene - C. Asnaghi; F. Paulet; C. Kaye; L. Grivet; M. Deu; J. C. Glaszmann; A. D’Hont (Theoretical and Applied Genetics, 2000)

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)

Effects on mouse embryos of in utero exposure to saccharin: teratogenic and chromosome effects - R. H. Dropkin; D. F. Salo; S. M. Tucci; G. I. Kaye (Archives of Toxicology, 1985)