Diet-dependent, beneficial and adverse effects of rapamycin on life span of Drosophila melanogaster - Lauren N. Jackson; Azriel M. Boles; Caitlyn T. Frye; Isha A. Patel; Robin J. Mockett (GeroScience, 2026)
Rapamycin supplementation has been reported to extend life spans in numerous species, including Drosophila melanogaster , but a recent study in this laboratory revealed a marked life-shortening effect in y w male flies. The experiments reported here were performed to characterize conditions under which rapamycin could extend or shorten life spans in five fly strains. On a cornmeal/torula yeast-based medium, rapamycin extended life in one experiment, had no effect in six and was harmful in 19. On a nutrient-rich brewer’s yeast medium favored by 4/5 strains for egg-laying, rapamycin was beneficial in eight, neutral in 14 and not significantly harmful in any experiment. Effects on median life span ranged from -51.3 to + 5.4% and were sex- and strain-specific, with limited differences for rapamycin dissolved in ethanol vs dimethylsulfoxide and for mated vs unmated flies. The life-shortening effect in y w males on the torula medium was greater when food was provided within 1–3 days after preparation vs 4–9 days, but similar under constant darkness vs 12 h light:12 h darkness. As an antifungal agent, rapamycin was expected to rescue shortened life spans when acids and methyl 4-hydroxybenzoate were omitted from the media, but removing these preservatives did not diminish the life span. Rapamycin was not consistently aversive for egg-laying, except in Dahomey flies at 200 µM. It prevented development to adulthood at 10–200 µM and delayed it at 0.1–1 µM concentrations. The results confirm the adverse effects of rapamycin during development and demonstrate its potential to switch between beneficial and harmful effects on adult life span depending on other components of the diet.

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.

Clarifying the role of the resist–accept–direct framework in supporting resource management planning processes - Gregor W. Schuurman; Wylie Carr; Cat Hawkins Hoffman; David J. Lawrence; Brian W. Miller; Erik A. Beever; Jean Brennan; Katherine R. Clifford; Scott Covington; Shelley D. Crausbay; Amanda E. Cravens; John Gross; et al. (Conservation Biology, 2025)

Worldwide Soundscapes: A Synthesis of Passive Acoustic Monitoring Across Realms - Kevin F. A. Darras; Rodney A. Rountree; Steven L. Van Wilgenburg; Anna F. Cord; Frederik Pitz; Youfang Chen; Lijun Dong; Agnès Rocquencourt; Camille Desjonquères; Patrick Mauritz Diaz; Tzu‐Hao Lin; Théophile Turco; et al. (Global Ecology and Biogeography, 2025)
Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.

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.

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups - John F. Benson; David A. Keiter; Peter J. Mahoney; Benjamin L. Allen; Lee Allen; Francisco Álvares; Morgan L. Anderson; Shannon M. Barber‐Meyer; Adi Barocas; James C. Beasley; Linda Behrendorff; Jerrold L. Belant; et al. (Ecology, 2025)
Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group‐level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids ( Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

Early Aboriginal pottery production and offshore island occupation on Jiigurru (Lizard Island group), Great Barrier Reef, Australia - Sean Ulm; Ian J. McNiven; Glenn R. Summerhayes; Pei-hua Wu; Magdalena M.E. Bunbury; Fiona Petchey; Quan Hua; Robert Skelly; Ariana B.J. Lambrides; Cassandra Rowe; Kelsey M. Lowe; Christian H. Reepmeyer; et al. (Quaternary Science Reviews, 2024)

Trapping and bypassing of suspended particulate matter, particulate nutrients and faecal indicator organisms in the river-estuary transition zone of a shallow macrotidal estuary - Colin Jago; Peter Robins; Eleanor Howlett; Francis Hassard; Paulina Rajko-Nenow; Suzanna Jackson; Nguyen Chien; Shelagh Malham (Science of The Total Environment, 2024)

Spatial and temporal variability of common cuttlefish, Sepia officinalis, L. spawning grounds off North Europe - Vladimir Laptikhovsky; Gavan Cooke; Christian Drerup; Angus Jackson; Eleanor MacLeod; Jean-Paul Robin (Fisheries Research, 2023)

Portable gamma spectrometry for rapid assessment of soil texture, organic carbon and total nitrogen in agricultural soils - Alex Taylor; Alice Kalnins; Martha Koot; Robin Jackson; Arsenio Toloza; Hami Said Ahmed; Rupert Goddard; William H. Blake (Journal of Soils and Sediments, 2023)

Spatial–Temporal Growth, Distribution, and Diffusion of Marine Microplastic Research and National Plastic Policies - Lyda S. T. Harris; Jackson Fennell; Robin J. Fales; Emily Carrington (Water, Air, & Soil Pollution, 2021)

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.

Observable, low-order dynamical controls on thresholds of the Atlantic meridional overturning circulation - Richard A. Wood; José M. Rodríguez; Robin S. Smith; Laura C. Jackson; Ed Hawkins (Climate Dynamics, 2019)

Late Quaternary sea‐level change and evolution of Belfast Lough, Northern Ireland: new offshore evidence and implications for sea‐level reconstruction - Ruth M. K. Plets; S. Louise Callard; J. Andrew G. Cooper; Joseph T. Kelley; Daniel F. Belknap; Robin J. Edwards; Antony J. Long; Rory J. Quinn; Derek W. T. Jackson (Journal of Quaternary Science, 2019)
The interplay of eustatic and isostatic factors causes complex relative sea‐level (RSL) histories, particularly in paraglacial settings. In this context the past record of RSL is important in understanding ice‐sheet history, earth rheology and resulting glacio‐isostatic adjustment. Field data to develop sea‐level reconstructions are often limited to shallow depths and uncertainty exists as to the veracity of modelled sea‐level curves. We use seismic stratigraphy, 39 vibrocores and 26 radiocarbon dates to investigate the deglacial history of Belfast Lough, Northern Ireland, and reconstruct past RSL. A typical sequence of till, glacimarine and Holocene sediments is preserved. Two sea‐level lowstands (both max. −40 m) are recorded at c. 13.5 and 11.5k cal a bp . Each is followed by a rapid transgression and subsequent periods of RSL stability. The first transgression coincides temporally with a late stage of Meltwater Pulse 1a and the RSL stability occurred between c. 13.0 and c. 12.2k cal a bp (Younger Dryas). The second still/slowstand occurred between c. 10.3 and c. 11.5k cal a bp . Our data provide constraints on the direction and timing of RSL change during deglaciation. Application of the Depth of Closure concept adds an error term to sea‐level reconstructions based on seismic stratigraphic reconstructions.

Adapting clonally propagated crops to climatic changes: a global approach for taro (Colocasia esculenta (L.) Schott) - V. Lebot; V. Tuia; A. Ivancic; G. V. H. Jackson; F. Saborio; G. Reyes; S. Rodriguez; G. Robin; R. Traoré; L. Aboagye; J. Onyeka; W. van Rensburg; et al. (Genetic Resources and Crop Evolution, 2018)

Neglect of Genetic Diversity in Implementation of the Convention on Biological Diversity - LINDA LAIKRE; FRED W. ALLENDORF; LAUREL C. ARONER; C. SCOTT BAKER; DAVID P. GREGOVICH; MICHAEL M. HANSEN; JENNIFER A. JACKSON; KATHERINE C. KENDALL; KEVIN McKELVEY; MAILE C. NEEL; ISABELLE OLIVIERI; NILS RYMAN; et al. (Conservation Biology, 2010)

Microbial responses and nitrous oxide emissions during wetting and drying of organically and conventionally managed soil under tomatoes - Martin Burger; Louise E. Jackson; Erica J. Lundquist; Dianne T. Louie; Robin L. Miller; Dennis E. Rolston; Kate M. Scow (Biology and Fertility of Soils, 2005)

Potential Improvements in the Characterization of Forest Canopy Gaps Caused by Windthrow Using Fine Spatial Resolution Multispectral Data: Comparing Hard and Soft Classification Techniques - Giles M. Foody; Robin G. Jackson; Christopher P. Quine (Forest Science, 2003)
Gaps often form in forest canopies due to windthrow and have important management and ecological implications. Remote sensing has considerable potential for the provision of information on gap properties but this has not been fully realized. This is largely due to the use of conventional (hard, one-pixel one-class) image analysis techniques and imagery with a relatively coarse spatial resolution. This article investigates the potential to extract information on gap properties from fine spatial resolution airborne thematic mapper imagery using soft classification techniques that allow image pixels to have multiple and partial class membership. It is shown that a standard hard maximum likelihood classification may be used to derive an accurate map of the land cover of a forested site (95.1%) from which gaps in a canopy of Sitka spruce were accurately identified (94.5%). The maximum likelihood classification was also softened by outputting probabilities of class membership for each pixel. Softening the classification increased the information on gap properties that could be extracted from the data. In particular, the accuracy with which key gap properties, such as gap area, perimeter length and shape, were estimated was higher in the outputs of the softened than hard classification. Thus, while strong correlations between the remotely sensed and ground data estimates of gap area (r ≥ 0.96) and perimeter (r ≥ 0.87), based on a sample of 36 gaps, were derived from all classifications, the accuracy with which gap properties were estimated was generally highest when a soft classification was used. For example, the use of a soft rather than hard classification resulted in the root mean square error in estimating gap area declining from 144.90 to 132.87 m2. Furthermore, the soft classification allowed the sharpness of the gap boundary to be estimated, enabling further gap properties to be inferred. In particular, the soft classification output enabled the direction of the wind event causing the initial damage to be estimated, and it may aid the definition of sites with a future risk of windthrow. FOR. SCI. 49(3):444–454.

CYP3A4-V and prostate cancer in African Americans: causal or confounding association because of population stratification? - Rick A. Kittles; Weidong Chen; Ramesh K. Panguluri; Chiledum Ahaghotu; Aaron Jackson; Clement A. Adebamowo; Robin Griffin; Tyisha Williams; Flora Ukoli; Lucile Adams-Campbell; John Kwagyan; William Isaacs; et al. (Human Genetics, 2002)