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.

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.

Effect of PLGA raw materials on in vitro and in vivo performance of drug-loaded microspheres - Desheng Liang; Jennifer Walker; Peter S. Schwendeman; Aishwarya Chandrashekar; Rose Ackermann; Karl F. Olsen; Moritz Beck-Broichsitter; Steven P. Schwendeman (Drug Delivery and Translational Research, 2025)

A Transcriptomic Comparative Study of Cranial Vasculature - Jianing Zhang; Jee-Yeon Ryu; Selena-Rae Tirado; Lawrence D. Dickinson; Aviva Abosch; M. Ali Aziz-Sultan; Alan S. Boulos; Daniel L. Barrow; H. Hunt Batjer; Tamar R. Binyamin; Spiros L. Blackburn; Edward F. Chang; et al. (Translational Stroke Research, 2024)

A gendered conjoint analysis of tilapia trait preference rankings among urban consumers in Zambia: Evidence to inform genetic improvement programs - Seamus Murphy; Steven M. Cole; Alexander M. Kaminski; Harrison Charo-Karisa; Rose Komugisha Basiita; Cynthia McDougall; Keagan Kakwasha; Tabitha Mulilo; Surendran Rajaratnam; Wagdy Mekkawy (Aquaculture, 2024)

Farmer perspectives on desired catfish attributes in aquaculture systems in Nigeria. An exploratory focus group study - Timothy Manyise; Rose K. Basiita; Catherine M. Mwema; Olutokunbo Oyesola; Sunil Siriwardena; Bernadette Fregene; Steven M. Cole; Eric B. Dompreh; Rodolfo Dam Lam; Denise L. Lozano; Cristiano M. Rossignoli; John A.H. Benzie (Aquaculture, 2024)

The strategic role of lithium in the green energy transition: Towards an OPEC-style framework for green energy-mineral exporting countries (GEMEC) - Yousef Ghorbani; Steven E. Zhang; Julie E. Bourdeau; Nelson S. Chipangamate; Derek H. Rose; Imraan Valodia; Glen T. Nwaila (Resources Policy, 2024)

Building capacity for climate adaptation planning in protected area management: Options and challenges for World Heritage - Jess Melbourne-Thomas; Brenda B. Lin; Mandy Hopkins; Rosemary Hill; Michael Dunlop; Nicholas MacGregor; Samuel D. Merson; Caitlin Vertigan; Luke Donegan; Marian Sheppard; Jacqui Meyers; Linda Thomas; et al. (Biological Conservation, 2024)

Reasons to Be Skeptical about Sentience and Pain in Fishes and Aquatic Invertebrates - Benjamin K. Diggles; Robert Arlinghaus; Howard I. Browman; Steven J. Cooke; Robin L. Cooper; Ian G. Cowx; Charles D. Derby; Stuart W. Derbyshire; Paul JB Hart; Brian Jones; Alexander O. Kasumyan; Brian Key; et al. (Reviews in Fisheries Science & Aquaculture, 2024)

Embracing a diverse approach to a globally inclusive green energy transition: Moving beyond decarbonisation and recognising realistic carbon reduction strategies - Yousef Ghorbani; Steven E. Zhang; Glen T. Nwaila; Julie E. Bourdeau; Derek H. Rose (Journal of Cleaner Production, 2024)

Data management and protection in occupational and environmental exposome research - A case study from the EU-funded EXIMIOUS project - Manosij Ghosh; Katrijn Broothaerts; Steven Ronsmans; Ingrid Barcena Roig; Jef Scheepers; Mustafa Dikmen; Emily Rose Ciscato; Carolina Blanch; Michelle Plusquin; Unni C. Nygaard; Camilla Sandal Sejbæk; Karin S. Hougaard; et al. (Environmental Research, 2023)

Where should hydrology go? An early-career perspective on the next IAHS Scientific Decade: 2023–2032 - Theresa C. van Hateren; Harro J. Jongen; Hadeel Al-Zawaidah; Joris G.W. Beemster; Judith Boekee; Linda Bogerd; Sijia Gao; Christin Kannen; Ilja van Meerveld; Sjoukje I. de Lange; Felicia Linke; Rose B. Pinto; et al. (Hydrological Sciences Journal, 2023)

Data-Driven Predictive Modeling of Lithofacies and Fe In-Situ Grade in the Assen Fe Ore Deposit of the Transvaal Supergroup (South Africa) and Implications on the Genesis of Banded Iron Formations - Glen T. Nwaila; Steven E. Zhang; Julie E. Bourdeau; Elekanyani Negwangwatini; Derek H. Rose; Mark Burnett; Yousef Ghorbani (Natural Resources Research, 2022)
The Assen Fe ore deposit is a banded iron formation (BIF)-hosted orebody, occurring in the Penge Formation of the Transvaal Supergroup, located 50 km northwest of Pretoria in South Africa. Most BIF-hosted Fe ore deposits have experienced post-depositional alteration including supergene enrichment of Fe and low-grade regional metamorphism. Unlike most of the known BIF-hosted Fe ore deposits, high-grade hematite (> 60% Fe) in the Assen Fe ore deposit is located along the lithological contacts with dolerite intrusions. Due to the variability in alteration levels, identifying the lithologies present within the various parts of the Assen Fe ore deposit, specifically within the weathering zone, is often challenging. To address this challenge, machine learning was applied to enable the automatic classification of rock types identified within the Assen Fe ore mine and to predict the in-situ Fe grade. This classification is based on geochemical analyses, as well as petrography and geological mapping. A total of 21 diamond core drill cores were sampled at 1 m intervals, covering all the lithofacies present at Assen mine. These were analyzed for major elements and oxides by means of X-ray fluorescence spectrometry. Numerous machine learning algorithms were trained, tested and cross-validated for automated lithofacies classification and prediction of in-situ Fe grade, namely (a) k-nearest neighbors, (b) elastic-net, (c) support vector machines (SVMs), (d) adaptive boosting, (e) random forest, (f) logistic regression, (g) Naïve Bayes, (h) artificial neural network (ANN) and (i) Gaussian process algorithms. Random forest, SVM and ANN classifiers yield high classification accuracy scores during model training, testing and cross-validation. For in-situ Fe grade prediction, the same algorithms also consistently yielded the best results. The predictability of in-situ Fe grade on a per-lithology basis, combined with the fact that CaO and SiO 2 were the strongest predictors of Fe concentration, support the hypothesis that the process that led to Fe enrichment in the Assen Fe ore deposit is dominated by supergene processes. Moreover, we show that predictive modeling can be used to demonstrate that in this case, the main differentiator between the predictability of Fe concentration between different lithofacies lies in the strength of multivariate elemental associations between Fe and other oxides. Localized high-grade Fe ore along with lithological contacts with dolerite intrusion is indicative of intra-basinal fluid circulation from an already Fe-enriched hematite. These findings have a wider implication on lithofacies classification in weathered rocks and mobility of economic valuable elements such as Fe.

Constraints on the Geometry and Gold Distribution in the Black Reef Formation of South Africa Using 3D Reflection Seismic Data and Micro-X-ray Computed Tomography - Glen T. Nwaila; Musa S. D. Manzi; Steven E. Zhang; Julie E. Bourdeau; Lunga C. Bam; Derek H. Rose; Kebone Maselela; David L. Reid; Yousef Ghorbani; Raymond J. Durrheim (Natural Resources Research, 2022)

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)

Closing the knowledge‐action gap in conservation with open science - Dominique G. Roche; Rose E. O'Dea; Kecia A. Kerr; Trina Rytwinski; Richard Schuster; Vivian M. Nguyen; Nathan Young; Joseph R. Bennett; Steven J. Cooke (Conservation Biology, 2022)
The knowledge‐action gap in conservation science and practice occurs when research outputs do not result in actions to protect or restore biodiversity. Among the diverse and complex reasons for this gap, three barriers are fundamental: knowledge is often unavailable to practitioners and challenging to interpret or difficult to use or both. Problems of availability, interpretability, and useability are solvable with open science practices. We considered the benefits and challenges of three open science practices for use by conservation scientists and practitioners. First, open access publishing makes the scientific literature available to all. Second, open materials (detailed methods, data, code, and software) increase the transparency and use of research findings. Third, open education resources allow conservation scientists and practitioners to acquire the skills needed to use research outputs. The long‐term adoption of open science practices would help researchers and practitioners achieve conservation goals more quickly and efficiently and reduce inequities in information sharing. However, short‐term costs for individual researchers (insufficient institutional incentives to engage in open science and knowledge mobilization) remain a challenge. We caution against a passive approach to sharing that simply involves making information available. We advocate a proactive stance toward transparency, communication, collaboration, and capacity building that involves seeking out and engaging with potential users to maximize the environmental and societal impact of conservation science.

Transport Processes in the Gulf of Mexico Along the River-Estuary-Shelf-Ocean Continuum: a Review of Research from the Gulf of Mexico Research Initiative - Dubravko Justić; Villy Kourafalou; Giulio Mariotti; Songjie He; Robert Weisberg; Yannis Androulidakis; Christopher Barker; Annalisa Bracco; Brian Dzwonkowski; Chuanmin Hu; Haosheng Huang; Gregg Jacobs; et al. (Estuaries and Coasts, 2022)
Estuarine and coastal geomorphology, biogeochemistry, water quality, and coastal food webs in river-dominated shelves of the Gulf of Mexico (GoM) are modulated by transport processes associated with river inputs, winds, waves, tides, and deep-ocean/continental shelf interactions. For instance, transport processes control the fate of river-borne sediments, which in turn affect coastal land loss. Similarly, transport of freshwater, nutrients, and carbon control the dynamics of eutrophication, hypoxia, harmful algal blooms, and coastal acidification. Further, freshwater inflow transports pesticides, herbicides, heavy metals, and oil into receiving estuaries and coastal systems. Lastly, transport processes along the continuum from the rivers and estuaries to coastal and shelf areas and adjacent open ocean (abbreviated herein as “river-estuary-shelf-ocean”) regulate the movements of organisms, including the spatial distributions of individuals and the exchange of genetic information between distinct subpopulations. The Gulf of Mexico Research Initiative (GoMRI) provided unprecedented opportunities to study transport processes along the river-estuary-shelf-ocean continuum in the GoM. The understanding of transport at multiple spatial and temporal scales in this topographically and dynamically complex marginal sea was improved, allowing for more accurate forecasting of the fate of oil and other constituents. For this review, we focus on five specific transport themes: (i) wetland, estuary, and shelf exchanges; (ii) river-estuary coupling; (iii) nearshore and inlet processes; (iv) open ocean transport processes; and (v) river-induced fronts and cross-basin transport. We then discuss the relevancy of GoMRI findings on the transport processes for ecological connectivity and oil transport and fate. We also examine the implications of new findings for informing the response to future oil spills, and the management of coastal resources and ecosystems. Lastly, we summarize the research gaps identified in the many studies and offer recommendations for continuing the momentum of the research provided by the GoMRI effort. A number of uncertainties were identified that occurred in multiple settings. These include the quantification of sediment, carbon, dissolved gasses and nutrient fluxes during storms, consistent specification of the various external forcings used in analyses, methods for smooth integration of multiscale advection mechanisms across different flow regimes, dynamic coupling of the atmosphere with sub-mesoscale and mesoscale phenomena, and methods for simulating finer-scale dynamics over long time periods. Addressing these uncertainties would allow the scientific community to be better prepared to predict the fate of hydrocarbons and their impacts to the coastal ocean, rivers, and marshes in the event of another spill in the GoM.

An Ecological Accounting System for Integrated Aquatic Planning and Habitat Banking with Case Study on the Toronto Waterfront, Ontario, Canada - Susan E. Doka; Charles K. Minns; Brent G. Valere; Steven J. Cooke; Rick J. Portiss; Thomas F. Sciscione; Alwyn Rose (Environmental Management, 2022)
A key aspect of contemporary fish habitat management is the need to account for losses and gains associated with development and offsetting measures while protecting high quality features. We propose an ecological accounting framework for aquatic ecosystems using habitat equivalents scaled to aquatic productivity, and using fish-to-habitat associations by life stage, based on local fish community needs. The framework uses both landscape-scale and site-level evaluations of pre- and post-project habitat changes to assign and track habitat parcels, using ecological baselines and fish-habitat target setting. Concepts of natural capital reserves and productivity-based ecotypes are used for trading losses and gains between impacts from development projects and offsets, including restoration actions, while maintaining ecologically important areas intact. Traditional accounting terms such as deposits, withdrawals, and transfers are defined using scaled habitat-equivalents as the currency. Other key features of the framework include setting a service area that is ecologically meaningful, and conducting habitat transactions guided by habitat conservation, protection, and restoration ( habitat CPR ) principles. The nearshore area of the Toronto and Region is used as a case study to illustrate the eco-accounting framework and how habitat banking could be incorporated along with planned restoration to remediate this degraded but continually developed area. The framework represents significant advances in managing cumulative habitat effects in an integrated way, moving away from a focus on only project- or site-level assessments. We feel this approach could be adapted to other ecosystem types in addition to the lake, nearshore area example provided here.

Global biomass supply modeling for long-run management of the climate system - Steven K. Rose; Alexander Popp; Shinichiro Fujimori; Petr Havlik; John Weyant; Marshall Wise; Detlef van Vuuren; Thierry Brunelle; Ryna Yiyun Cui; Vassilis Daioglou; Stefan Frank; Tomoko Hasegawa; et al. (Climatic Change, 2022)
Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.

Development and characterization of composition-equivalent formulations to the Sandostatin LAR® by the solvent evaporation method - Avital Beig; Linglin Feng; Jennifer Walker; Rose Ackermann; Justin K. Y. Hong; Tinghui Li; Yan Wang; Steven P. Schwendeman (Drug Delivery and Translational Research, 2022)

The contribution of bioenergy to the decarbonization of transport: a multi-model assessment - Florian Leblanc; Ruben Bibas; Silvana Mima; Matteo Muratori; Shogo Sakamoto; Fuminori Sano; Nico Bauer; Vassilis Daioglou; Shinichiro Fujimori; Matthew J. Gidden; Estsushi Kato; Steven K. Rose; et al. (Climatic Change, 2022)

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland - Moira Hough; Samantha McCabe; S. Rose Vining; Emily Pickering Pedersen; Rachel M. Wilson; Ryan Lawrence; Kuang‐Yu Chang; Gil Bohrer; William J. Riley; Patrick M. Crill; Ruth K. Varner; Steven J. Blazewicz; et al. (Global Change Biology, 2022)
Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

Relationship between Papillomavirus vaccine, vaginal microbiome, and local cytokine response: an exploratory research - Paulo Cesar Giraldo; José Marcos Sanches; Luiz Gustavo Sparvolli; Rose Amaral; Isabel Migliorini; Cristiane Damas Gil; Carla Romano Taddei; Steven S. Witkin; Michelle Garcia Discacciati (Brazilian Journal of Microbiology, 2021)

Strandings provide insight into social group structure of Atlantic white‐sided dolphins - Katie R. Pugliares‐Bonner; Kate LaSpina; Kathryn S. Rose; Steven E. Travis; Kristina M. Cammen (Marine Mammal Science, 2021)
Atlantic white‐sided dolphins ( Lagenorhynchus acutus ) are highly social odontocetes with a poorly understood tendency to mass strand. With limited capacity to study social ecology in the open ocean, mass strandings provide an opportunity to improve our understanding of group structure. Our study of 32 mass stranding events that occurred on Cape Cod, Massachusetts, between 1999 and 2009 identifies aspects of social ecology that vary across the year. A greater number of mass stranding events occurred outside of the breeding season and there was evidence of age‐structuring during the breeding season. We find generally low average intragroup pairwise relatedness assessed across eight microsatellite loci in a subset of 16 mass stranding events. Mass stranded groups do not show higher than expected relatedness when compared to a baseline estimate derived from single‐stranded individuals. Overall, our integration of genetic estimates of relatedness with data on sex and maturity‐class from stranded specimens suggests that Atlantic white‐sided dolphins fall near the more fluid end of the continuum from short‐term, highly fluid social associations to long‐term, stable groups represented among the odontocetes. Despite their tendency to mass strand, stable, kin‐based associations are not a defining feature of social group structure in this species.

The role of rhizofiltration and allelopathy on the removal of cyanobacteria in a continuous flow system - Ana Teresa Castro-Castellon; Jocelyne Mary Rose Hughes; Daniel Steven Read; Yaldah Azimi; Michael James Chipps; Nicholas Peter Hankins (Environmental Science and Pollution Research, 2021)

An overview of the Energy Modeling Forum 33rd study: assessing large-scale global bioenergy deployment for managing climate change - Steven K Rose; Nico Bauer; Alexander Popp; John Weyant; Shinichiro Fujimori; Petr Havlik; Marshall Wise; Detlef P van Vuuren (Climatic Change, 2020)

Bioenergy technologies in long-run climate change mitigation: results from the EMF-33 study - Vassilis Daioglou; Steven K. Rose; Nico Bauer; Alban Kitous; Matteo Muratori; Fuminori Sano; Shinichiro Fujimori; Matthew J. Gidden; Etsushi Kato; Kimon Keramidas; David Klein; Florian Leblanc; et al. (Climatic Change, 2020)
Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

EMF-33 insights on bioenergy with carbon capture and storage (BECCS) - Matteo Muratori; Nico Bauer; Steven K. Rose; Marshall Wise; Vassilis Daioglou; Yiyun Cui; Etsushi Kato; Matthew Gidden; Jessica Strefler; Shinichiro Fujimori; Ronald D. Sands; Detlef P. van Vuuren; et al. (Climatic Change, 2020)

Global energy sector emission reductions and bioenergy use: overview of the bioenergy demand phase of the EMF-33 model comparison - Nico Bauer; Steven K. Rose; Shinichiro Fujimori; Detlef P. van Vuuren; John Weyant; Marshall Wise; Yiyun Cui; Vassilis Daioglou; Matthew J. Gidden; Etsushi Kato; Alban Kitous; Florian Leblanc; et al. (Climatic Change, 2020)

Reverse Engineering the 1-Month Lupron Depot® - Jia Zhou; Keiji Hirota; Rose Ackermann; Jennifer Walker; Yan Wang; Stephanie Choi; Anna Schwendeman; Steven P. Schwendeman (The AAPS Journal, 2018)

Role of hypocretin/orexin receptor blockade on drug-taking and ultrasonic vocalizations (USVs) associated with low-effort self-administration of cathinone-derived 3,4-methylenedioxypyrovalerone (MDPV) in rats - Steven J. Simmons; Rose Martorana; Helene Philogene-Khalid; Fionya H. Tran; Taylor A. Gentile; Xinyan Xu; Shu Su; Scott M. Rawls; John W. Muschamp (Psychopharmacology, 2017)

The Paris Agreement and next steps in limiting global warming - Steven K. Rose; Richard Richels; Geoffrey Blanford; Thomas Rutherford (Climatic Change, 2017)

Using citizen science data to identify the sensitivity of species to human land use - Brian D. Todd; Jonathan P. Rose; Steven J. Price; Michael E. Dorcas (Conservation Biology, 2016)
Conservation practitioners must contend with an increasing array of threats that affect biodiversity. Citizen scientists can provide timely and expansive information for addressing these threats across large scales, but their data may contain sampling biases. We used randomization procedures to account for possible sampling biases in opportunistically reported citizen science data to identify species’ sensitivities to human land use. We analyzed 21,044 records of 143 native reptile and amphibian species reported to the Carolina Herp Atlas from North Carolina and South Carolina between 1 January 1990 and 12 July 2014. Sensitive species significantly associated with natural landscapes were 3.4 times more likely to be legally protected or treated as of conservation concern by state resource agencies than less sensitive species significantly associated with human‐dominated landscapes. Many of the species significantly associated with natural landscapes occurred primarily in habitats that had been nearly eradicated or otherwise altered in the Carolinas, including isolated wetlands, longleaf pine savannas, and Appalachian forests. Rare species with few reports were more likely to be associated with natural landscapes and 3.2 times more likely to be legally protected or treated as of conservation concern than species with at least 20 reported occurrences. Our results suggest that opportunistically reported citizen science data can be used to identify sensitive species and that species currently restricted primarily to natural landscapes are likely at greatest risk of decline from future losses of natural habitat. Our approach demonstrates the usefulness of citizen science data in prioritizing conservation and in helping practitioners address species declines and extinctions at large extents.

Infection risk decreases with increasing mismatch in host and pathogen environmental tolerances - A. Justin Nowakowski; Steven M. Whitfield; Evan A. Eskew; Michelle E. Thompson; Jonathan P. Rose; Benjamin L. Caraballo; Jacob L. Kerby; Maureen A. Donnelly; Brian D. Todd (Ecology Letters, 2016)
The fungal pathogen Batrachochytrium dendrobatidis ( Bd ) has caused the greatest known wildlife pandemic, infecting over 500 amphibian species. It remains unclear why some host species decline from disease‐related mortality whereas others persist. We introduce a conceptual model that predicts that infection risk in ectotherms will decrease as the difference between host and pathogen environmental tolerances (i.e. tolerance mismatch) increases. We test this prediction using both local‐scale data from Costa Rica and global analyses of over 11 000 Bd infection assays. We find that infection prevalence decreases with increasing thermal tolerance mismatch and with increasing host tolerance of habitat modification. The relationship between environmental tolerance mismatches and Bd infection prevalence is generalisable across multiple amphibian families and spatial scales, and the magnitude of the tolerance mismatch effect depends on environmental context. These findings may help explain patterns of amphibian declines driven by a global wildlife pandemic.

Evaluation of a DLA-79 allele associated with multiple immune-mediated diseases in dogs - Steven G. Friedenberg; Greg Buhrman; Lhoucine Chdid; Natasha J. Olby; Thierry Olivry; Julien Guillaumin; Theresa O’Toole; Robert Goggs; Lorna J. Kennedy; Robert B. Rose; Kathryn M. Meurs (Immunogenetics, 2016)

Global climate, energy, and economic implications of international energy offsets programs - Katherine Calvin; Steven Rose; Marshall Wise; Haewon McJeon; Leon Clarke; Jae Edmonds (Climatic Change, 2015)

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data - Paul M. Thompson; Jason L. Stein; Sarah E. Medland; Derrek P. Hibar; Alejandro Arias Vasquez; Miguel E. Renteria; Roberto Toro; Neda Jahanshad; Gunter Schumann; Barbara Franke; Margaret J. Wright; Nicholas G. Martin; et al. (Brain Imaging and Behavior, 2014)

The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies - Elmar Kriegler; John P. Weyant; Geoffrey J. Blanford; Volker Krey; Leon Clarke; Jae Edmonds; Allen Fawcett; Gunnar Luderer; Keywan Riahi; Richard Richels; Steven K. Rose; Massimo Tavoni; et al. (Climatic Change, 2014)

Bioenergy in energy transformation and climate management - Steven K. Rose; Elmar Kriegler; Ruben Bibas; Katherine Calvin; Alexander Popp; Detlef P. van Vuuren; John Weyant (Climatic Change, 2014)

Non-Kyoto radiative forcing in long-run greenhouse gas emissions and climate change scenarios - Steven K. Rose; Richard Richels; Steve Smith; Keywan Riahi; Jessica Strefler; Detlef P. van Vuuren (Climatic Change, 2014)

Land-use transition for bioenergy and climate stabilization: model comparison of drivers, impacts and interactions with other land use based mitigation options - Alexander Popp; Steven K. Rose; Katherine Calvin; Detlef P. Van Vuuren; Jan Phillip Dietrich; Marshall Wise; Elke Stehfest; Florian Humpenöder; Page Kyle; Jasper Van Vliet; Nico Bauer; Hermann Lotze-Campen; et al. (Climatic Change, 2014)

Trade-offs between mitigation costs and temperature change - Geoffrey Blanford; James Merrick; Richard Richels; Steven Rose (Climatic Change, 2014)

Can fish really feel pain? - J D Rose; R Arlinghaus; S J Cooke; B K Diggles; W Sawynok; E D Stevens; C D L Wynne (Fish and Fisheries, 2014)
We review studies claiming that fish feel pain and find deficiencies in the methods used for pain identification, particularly for distinguishing unconscious detection of injurious stimuli (nociception) from conscious pain. Results were also frequently misinterpreted and not replicable, so claims that fish feel pain remain unsubstantiated. Comparable problems exist in studies of invertebrates. In contrast, an extensive literature involving surgeries with fishes shows normal feeding and activity immediately or soon after surgery. C fiber nociceptors, the most prevalent type in mammals and responsible for excruciating pain in humans, are rare in teleosts and absent in elasmobranchs studied to date. A‐delta nociceptors, not yet found in elasmobranchs, but relatively common in teleosts, likely serve rapid, less noxious injury signaling, triggering escape and avoidance responses. Clearly, fishes have survived well without the full range of nociception typical of humans or other mammals, a circumstance according well with the absence of the specialized cortical regions necessary for pain in humans. We evaluate recent claims for consciousness in fishes, but find these claims lack adequate supporting evidence, neurological feasibility, or the likelihood that consciousness would be adaptive. Even if fishes were conscious, it is unwarranted to assume that they possess a human‐like capacity for pain. Overall, the behavioral and neurobiological evidence reviewed shows fish responses to nociceptive stimuli are limited and fishes are unlikely to experience pain.

Increased Generation of Cyclopentenone Prostaglandins after Brain Ischemia and Their Role in Aggregation of Ubiquitinated Proteins in Neurons - Hao Liu; Wenjin Li; Muzamil Ahmad; Marie E. Rose; Tricia M. Miller; Mei Yu; Jie Chen; Jordan L. Pascoe; Samuel M. Poloyac; Robert W. Hickey; Steven H. Graham (Neurotoxicity Research, 2013)

How much land‐based greenhouse gas mitigation can be achieved without compromising food security and environmental goals? - Pete Smith; Helmut Haberl; Alexander Popp; Karl‐heinz Erb; Christian Lauk; Richard Harper; Francesco N. Tubiello; Alexandre de Siqueira Pinto; Mostafa Jafari; Saran Sohi; Omar Masera; Hannes Böttcher; et al. (Global Change Biology, 2013)
Feeding 9–10 billion people by 2050 and preventing dangerous climate change are two of the greatest challenges facing humanity. Both challenges must be met while reducing the impact of land management on ecosystem services that deliver vital goods and services, and support human health and well‐being. Few studies to date have considered the interactions between these challenges. In this study we briefly outline the challenges, review the supply‐ and demand‐side climate mitigation potential available in the Agriculture, Forestry and Other Land Use AFOLU sector and options for delivering food security. We briefly outline some of the synergies and trade‐offs afforded by mitigation practices, before presenting an assessment of the mitigation potential possible in the AFOLU sector under possible future scenarios in which demand‐side measures codeliver to aid food security. We conclude that while supply‐side mitigation measures, such as changes in land management, might either enhance or negatively impact food security, demand‐side mitigation measures, such as reduced waste or demand for livestock products, should benefit both food security and greenhouse gas ( GHG ) mitigation. Demand‐side measures offer a greater potential (1.5–15.6 Gt CO 2 ‐eq. yr −1 ) in meeting both challenges than do supply‐side measures (1.5–4.3 Gt CO 2 ‐eq. yr −1 at carbon prices between 20 and 100 US$ t CO 2 ‐eq. yr −1 ), but given the enormity of challenges, all options need to be considered. Supply‐side measures should be implemented immediately, focussing on those that allow the production of more agricultural product per unit of input. For demand‐side measures, given the difficulties in their implementation and lag in their effectiveness, policy should be introduced quickly, and should aim to codeliver to other policy agenda, such as improving environmental quality or improving dietary health. These problems facing humanity in the 21st Century are extremely challenging, and policy that addresses multiple objectives is required now more than ever.

Methods for reactive oxygen species (ROS) detection in aqueous environments - Justina M. Burns; William J. Cooper; John L. Ferry; D. Whitney King; Brian P. DiMento; Kristopher McNeill; Christopher J. Miller; William L. Miller; Barrie M. Peake; Steven A. Rusak; Andrew L. Rose; T. David Waite (Aquatic Sciences, 2012)

PAH contamination in shellfish: modelling to estimate exposure - Aileen C. Mill; Steven P. Rushton; Alistair W. A. Murray; Martin Rose (Ecotoxicology, 2012)

The representative concentration pathways: an overview - Detlef P. van Vuuren; Jae Edmonds; Mikiko Kainuma; Keywan Riahi; Allison Thomson; Kathy Hibbard; George C. Hurtt; Tom Kram; Volker Krey; Jean-Francois Lamarque; Toshihiko Masui; Malte Meinshausen; et al. (Climatic Change, 2011)

One-set resistance training elevates energy expenditure for 72 h similar to three sets - Timothy Heden; Curt Lox; Paul Rose; Steven Reid; Erik P. Kirk (European Journal of Applied Physiology, 2011)

Research priorities in land use and land‐cover change for the Earth system and integrated assessment modelling - Kathy Hibbard; Anthony Janetos; Detlef P. van Vuuren; Julia Pongratz; Steven K. Rose; Richard Betts; Martin Herold; Johannes J. Feddema (International Journal of Climatology, 2010)
This special issue has highlighted recent and innovative methods and results that integrate observations and modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land‐cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land‐cover change to understand and quantify the interactions and feedbacks with the climate and socio‐economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land‐cover change for improved collaboration across modelling, observing and measurement communities. Major research topics in land use and land‐cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land‐cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies). Copyright © 2010 Royal Meteorological Society and Crown Copyright.

Designing science web sites - Kica Worrilow; Todd King; Raymond Walker; Mark E. Rose; William Moore; Steven Joy (Earth Science Informatics, 2010)

Individual Tree and Stand Level Influences on the Growth, Vigor, and Decline of Red Oaks in the Ozarks - Steven L. Voelker; Rose-Marie Muzika; Richard P. Guyette (Forest Science, 2008)
Repeated oak decline and mortality events have occurred in the Ozark region for decades and probably longer. We sampled an age sequence of 1,259 black and scarlet oaks (Quercus velutina Lam. and Quercus coccinea Muench.) to better describe the process of oak decline and mortality in the red oak group (subgenera Erythrobalanus). Trend in basal area increment (BAI) over the most recent 40 years was used to establish three vigor classes for trees with decreasing, stable, or increasing growth (Declining, Stable, or Healthy). We compared crown condition measures with absolute BAI and boundary line BAI, a measure of radial growth adjusted for tree size. A pulse of mortality was found to occur just subsequent to the most recent drought, although decline often started decades previously. Time series of individual tree BAI suggests that half of all oak decline events were incited by one or two drought-related step-changes in growth and variance. Predisposing factors to decline generally showed significant but weak relationships with crown conditions. Surviving oaks growing in high-mortality stands had poorer crown conditions and grew more slowly than trees in low-mortality stands. When recently dead trees were accounted for, the same high-mortality stands had significantly greater predecline basal area and stocking than low-mortality stands. Thus, a less competitive growth environment may afford some buffer to drought stress before oak decline but does not appear to help afflicted stands improve their growth and vigor.

Preliminary studies on the anti-angiogenic potential of pomegranate fractions in vitro and in vivo - Masakazu Toi; Hiroko Bando; Cheppail Ramachandran; Steven J. Melnick; Atsushi Imai; Rose S. Fife; Raymond Eric Carr; Tsutomu Oikawa; Ephraim Philip Lansky (Angiogenesis, 2003)

An Economic Analysis of Flexible Permit Trading in the Kyoto Protocol - Adam Rose; Brandt Stevens (International Environmental Agreements: Politics, Law and Economics, 2001)

Real Time Processing of Affective and Cognitive Stimuli in the Human Brain Extracted from MEG Signals - Andreas A. Ioannides; Lichan Liu; Dionyssios Theofilou; Jürgen Dammers; Tom Burne; TimAmbler Ambler; Steven Rose (Brain Topography, 2000)

Training-dependent biphasic effects of corticosterone in memory formation for a passive avoidance task in chicks - C. Sandi; Steven P. R. Rose (Psychopharmacology, 1997)