Identifying and reporting dystocia in laboratory rodents - Paul Barrow; Prägati S. Coder; Rashin Ghaffari; Leah Zorrilla; Christopher J. Bowman; Curtis E. Grace; Jason Manton; Alan Hoberman; Narinder Barraclough; Isabelle Leconte; Nicola Powles-Glover; Connie Chen; et al. (Reproductive Toxicology, 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.

Legacy effects of cover crops on weed biomass and yield of the subsequent corn crop - Barbara Baraibar; Brosi A. Bradley; Mitchell C. Hunter; Charles M. White; Denise M. Finney; Jason P. Kaye; Megan E. Schipanski; David A. Mortensen (European Journal of Agronomy, 2026)

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

Multi-site Milling Strategy Reveals Significant Variation in Biomass Composition of Switchgrass (Panicum virgatum) Grown at Ten Locations - David J. Thomas; Jason Bonnette; Steven D. Masterson; Robert B. Mitchell; Thomas E. Juenger; Laura E. Bartley (BioEnergy Research, 2025)

A standardized nontargeted metabolomics method for cross-laboratory comparison of food profiles - Melanie T. Odenkirk; Cole Michel; Katrina A. Doenges; Katrina L. Leaptrot; Stacy D. Sherrod; Jody C. May; Margaret L. Read; Jacqueline M. Chaparro; Nathan Montgomery; Sarah Brinkley; Arpana Vaniya; Susan B. Mitchell; et al. (Food Chemistry, 2025)

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis - Darice Guittet; Eric Bonnema; Matt Mitchell; Allison Mahvi; Jason Woods (Energy and Buildings, 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.

Distribution and disturbances of ditches across salt marshes of the Northeast U.S. with implications for management and restoration - Erin K. Peck; Julie E. Walker; Katherine V. Ackerman; Joel Carr; Maureen D. Correll; Zafer Defne; Linda A. Deegan; Mitchell J. Eaton; Neil K. Ganju; Mitch Hartley; Catherine Johnson; Jason Mercer; et al. (Journal of Environmental Management, 2025)

Accuracy of Instrumented Mouthguards During Direct Jaw Impacts Seen in Boxing - Jay Venkatraman; Mitchell Z. Abrams; Donald Sherman; Maria Ortiz-Paparoni; Jefferson R. Bercaw; Robert E. MacDonald; Jason Kait; Elizabeth Dimbath; Derek Pang; Alexandra Gray; Jason F. Luck; Cameron R. Bass; et al. (Annals of Biomedical Engineering, 2024)

Expanded Combined Loading Injury Criterion for the Human Lumbar Spine Under Dynamic Compression - Maria Ortiz-Paparoni; Joost Op ‘t Eynde; Christopher Eckersley; Concetta Morino; Mitchell Abrams; Derek Pang; Jason Kait; Frank Pintar; Narayan Yoganandan; Jason Moore; David Barnes; Kathryn Loftis; et al. (Annals of Biomedical Engineering, 2024)

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

Biofidelity and Limitations of Instrumented Mouthguard Systems for Assessment of Rigid Body Head Kinematics - Mitchell Z. Abrams; Jay Venkatraman; Donald Sherman; Maria Ortiz-Paparoni; Jefferson R. Bercaw; Robert E. MacDonald; Jason Kait; Elizabeth D. Dimbath; Derek Y. Pang; Alexandra Gray; Jason F. Luck; Cynthia A. Bir; et al. (Annals of Biomedical Engineering, 2024)

Review of dose setting for the extended one-generation reproductive toxicity studies (OECD TG 443): Considerations on ECHA's dose level selection recommendations - Manon Beekhuijzen; Emily Richmond; Jason Manton; Pragati S. Coder; Katy Goyak; Rashin Ghaffari; Susan L. Makris; Steven Van Cruchten; Leah Zorrilla; Shermaine Mitchell-Ryan (Regulatory Toxicology and Pharmacology, 2024)

Multistate outbreak of Salmonella Oranienburg infections linked to bulb onions imported from Mexico – United States, 2021 - Marvin R. Mitchell; Margaret Kirchner; Ben Schneider; Monica McClure; Karen P. Neil; Asma Madad; Temesgen Jemaneh; Mary Tijerina; Kurt Nolte; Allison Wellman; Daniel Neises; Arthur Pightling; et al. (Food Control, 2024)

The Toxicology Investigators Consortium 2022 Annual Report - Alexandra M. Amaducci; Sharan L. Campleman; Shao Li; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; Rachel E. Culbreth; Paul M. Wax; Jeffrey Brent; Kim Aldy; Jennifer Acciani; et al. (Journal of Medical Toxicology, 2023)

Modelling marine microplastics accumulation zones through freshwater discharge sources: Simulated release from the Onkaparinga River and Torrens River, South Australia - Kyle B. Mitchell; Charles James; Jason Gascooke; Sophie C. Leterme (Marine Pollution Bulletin, 2023)

Animal population decline and recovery after severe fire: Relating ecological and life history traits with expert estimates of population impacts from the Australian 2019-20 megafires - Michelle Ensbey; Sarah Legge; Chris J. Jolly; Stephen T. Garnett; Rachael V. Gallagher; Mark Lintermans; Dale G. Nimmo; Libby Rumpff; Ben C. Scheele; Nick S. Whiterod; John C.Z. Woinarski; Shane T. Ahyong; et al. (Biological Conservation, 2023)

Automatic classification of distal radius fracture using a two-stage ensemble deep learning framework - Hang Min; Yousef Rabi; Ashish Wadhawan; Pierrick Bourgeat; Jason Dowling; Jordy White; Ayden Tchernegovski; Blake Formanek; Michael Schuetz; Gary Mitchell; Frances Williamson; Craig Hacking; et al. (Physical and Engineering Sciences in Medicine, 2023)
Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures. Compared with extra-articular DRFs which spare the joint surface, intra-articular DRFs extend to the articular surface and can be more difficult to treat. Identification of articular involvement can provide valuable information about the characteristics of fracture patterns. In this study, a two-stage ensemble deep learning framework was proposed to differentiate intra- and extra-articular DRFs automatically on posteroanterior (PA) view wrist X-rays. The framework firstly detects the distal radius region of interest (ROI) using an ensemble model of YOLOv5 networks, which imitates the clinicians’ search pattern of zooming in on relevant regions to assess abnormalities. Secondly, an ensemble model of EfficientNet-B3 networks classifies the fractures in the detected ROIs into intra- and extra-articular. The framework achieved an area under the receiver operating characteristic curve of 0.82, an accuracy of 0.81, a true positive rate of 0.83 and a false positive rate of 0.27 (specificity of 0.73) for differentiating intra- from extra-articular DRFs. This study has demonstrated the potential in automatic DRF characterization using deep learning on clinically acquired wrist radiographs and can serve as a baseline for further research in incorporating multi-view information for fracture classification.

Melanism in a Wild Sifaka Population: Darker Where Cold and Fragmented - Elizabeth Tapanes; Jason M. Kamilar; Maanas A. Nukala; Mitchell T. Irwin; Brenda J. Bradley (International Journal of Primatology, 2023)

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

The conservation impacts of ecological disturbance: Time‐bound estimates of population loss and recovery for fauna affected by the 2019–2020 Australian megafires - Sarah Legge; Libby Rumpff; John C. Z. Woinarski; Nick S. Whiterod; Michelle Ward; Darren G. Southwell; Ben C. Scheele; Dale G. Nimmo; Mark Lintermans; Hayley M. Geyle; Stephen T. Garnett; Brittany Hayward‐Brown; et al. (Global Ecology and Biogeography, 2022)
Aim After environmental disasters, species with large population losses may need urgent protection to prevent extinction and support recovery. Following the 2019–2020 Australian megafires, we estimated population losses and recovery in fire‐affected fauna, to inform conservation status assessments and management. Location Temperate and subtropical Australia. Time period 2019–2030 and beyond. Major taxa Australian terrestrial and freshwater vertebrates; one invertebrate group. Methods From > 1,050 fire‐affected taxa, we selected 173 whose distributions substantially overlapped the fire extent. We estimated the proportion of each taxon’s distribution affected by fires, using fire severity and aquatic impact mapping, and new distribution mapping. Using expert elicitation informed by evidence of responses to previous wildfires, we estimated local population responses to fires of varying severity. We combined the spatial and elicitation data to estimate overall population loss and recovery trajectories, and thus indicate potential eligibility for listing as threatened, or uplisting, under Australian legislation. Results We estimate that the 2019–2020 Australian megafires caused, or contributed to, population declines that make 70–82 taxa eligible for listing as threatened; and another 21–27 taxa eligible for uplisting. If so‐listed, this represents a 22–26% increase in Australian statutory lists of threatened terrestrial and freshwater vertebrates and spiny crayfish, and uplisting for 8–10% of threatened taxa. Such changes would cause an abrupt worsening of underlying trajectories in vertebrates, as measured by Red List Indices. We predict that 54–88% of 173 assessed taxa will not recover to pre‐fire population size within 10 years/three generations. Main conclusions We suggest the 2019–2020 Australian megafires have worsened the conservation prospects for many species. Of the 91 taxa recommended for listing/uplisting consideration, 84 are now under formal review through national processes. Improving predictions about taxon vulnerability with empirical data on population responses, reducing the likelihood of future catastrophic events and mitigating their impacts on biodiversity, are critical.

The genetic basis for panicle trait variation in switchgrass (Panicum virgatum) - Li Zhang; Alice MacQueen; Xiaoyu Weng; Kathrine D. Behrman; Jason Bonnette; John L. Reilley; Francis M. Rouquette; Philip A. Fay; Yanqi Wu; Felix B. Fritschi; Robert B. Mitchell; David B. Lowry; et al. (Theoretical and Applied Genetics, 2022)
Key message We investigate the genetic basis of panicle architecture in switchgrass in two mapping populations across a latitudinal gradient, and find many stable, repeatable genetic effects and limited genetic interactions with the environment. Abstract Grass species exhibit large diversity in panicle architecture influenced by genes, the environment, and their interaction. The genetic study of panicle architecture in perennial grasses is limited. In this study, we evaluate the genetic basis of panicle architecture including panicle length, primary branching number, and secondary branching number in an outcrossed switchgrass QTL population grown across ten field sites in the central USA through multi-environment mixed QTL analysis. We also evaluate genetic effects in a diversity panel of switchgrass grown at three of the ten field sites using genome-wide association (GWAS) and multivariate adaptive shrinkage. Furthermore, we search for candidate genes underlying panicle traits in both of these independent mapping populations. Overall, 18 QTL were detected in the QTL mapping population for the three panicle traits, and 146 unlinked genomic regions in the diversity panel affected one or more panicle trait. Twelve of the QTL exhibited consistent effects (i.e., no QTL by environment interactions or no QTL × E), and most (four of six) of the effects with QTL × E exhibited site-specific effects. Most (59.3%) significant partially linked diversity panel SNPs had significant effects in all panicle traits and all field sites and showed pervasive pleiotropy and limited environment interactions. Panicle QTL co-localized with significant SNPs found using GWAS, providing additional power to distinguish between true and false associations in the diversity panel.

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)

Tropical cyclone precipitation regimes since 1750 and the Great Suppression of 1843–1876 along coastal North Carolina, USA - Paul A. Knapp; Peter T. Soulé; Justin T. Maxwell; Jason T. Ortegren; Tyler J. Mitchell (International Journal of Climatology, 2021)
Latewood ring widths of longleaf pine ( Pinus palustris Mill.) are effective recorders of annual variability of tropical cyclone (TC) precipitation (TCP), accounting for approximately half of the explained variance. Based on a regional chronology comprised of data from five sites in coastal North Carolina, we reconstructed TCP during 1750–2015 to examine temporal variability of multidecadal dry and wet TCP regimes, the synoptic controls that contributed to an exceptionally dry phase in 1843–1876, and the effectiveness of using latewood to identify droughts independent of TCP. We found six phases of alternating dry/wet phases occurred during the 250+ years in the reconstruction (duration range = 17–62 years) and the 1843–1876 period of exceptionally narrow latewood widths and low TCP values (i.e., the Great Suppression) was unique during the past quarter millennium. The Great Suppression coincided with a period of anomalously low pressure (relative mean hPa deviation = −60 DAM) over the eastern USA at 500 hPa heights, which strongly affects the steering of TCs. We found that while each dry phase was characterized by a persistence of these steering lows, including the most recent (2006–2016) period absent of major landfalling TCs in the United States, the Great Suppression was unmatched in intensity. Finally, we determined that variability in longleaf pine latewood widths do not reflect overall soil‐moisture conditions, as neither narrow nor wide latewood widths are coincident with variations in non‐TC‐related precipitation. Rather, latewood growth flushes are associated with ephemeral periods of elevated water tables following high‐intensity TC‐related rainfall events.

Not a melting pot: Plant species aggregate in their non‐native range - Gisela C. Stotz; James F. Cahill; Jonathan A. Bennett; Cameron N. Carlyle; Edward W. Bork; Diana Askarizadeh; Sandor Bartha; Carl Beierkuhnlein; Bazartseren Boldgiv; Leslie Brown; Marcelo Cabido; Giandiego Campetella; et al. (Global Ecology and Biogeography, 2020)
Aim Plant species continue to be moved outside of their native range by human activities. Here, we aim to determine whether, once introduced, plants assimilate into native communities or whether they aggregate, thus forming mosaics of native‐ and alien‐rich communities. Alien species might aggregate in their non‐native range owing to shared habitat preferences, such as their tendency to establish in high‐biomass, species‐poor areas. Location Twenty‐two herbaceous grasslands in 14 countries, mainly in the temperate zone. Time period 2012–2016. Major taxa studied Plants. Methods We used a globally coordinated survey. Within this survey, we found 46 plant species, predominantly from Eurasia, for which we had co‐occurrence data in their native and non‐native ranges. We tested for differences in co‐occurrence patterns of 46 species between their native (home) and non‐native (away) range. We also tested whether species had similar habitat preferences, by testing for differences in total biomass and species richness of the patches that species occupy in their native and non‐native ranges. Results We found the same species to show different patterns of association depending on whether they were in their native or non‐native range. Alien species were negatively associated with native species; instead, they aggregated with other alien species in species‐poor, high‐biomass communities in their non‐native range compared with their native range. Main conclusions The strong differences between the native (home) and non‐native (away) range in species co‐occurrence patterns are evidence that the way in which species associate with resident communities in their non‐native range is not species dependent, but is instead a property of being away from their native range. These results thus highlight that species might undergo important ecological changes when introduced away from their native range. Overall, we show origin‐dependent associations that result in novel communities, in which alien‐rich patches exist within a mosaic of native‐dominated communities.

Contrasting scales of local persistence between monsoonal and arid biomes in closely related, low‐dispersal vertebrates - Sally Potter; Ana C. Afonso Silva; Jason G. Bragg; Sarah R. Catalano; Stephen Donnellan; Paul Doughty; Mitchell L. Scott; Craig Moritz (Journal of Biogeography, 2019)
Aim Focussing on pairs of sister species across three genera of scincid lizards, we use genomic evidence to test for larger‐scale, late‐Pleistocene changes in distributions of lizards in the Australian arid zone (AZ) than in the adjacent monsoonal tropics (MT). Location Northern and central Australia. Taxon Scincidae: Squamata. Methods We sequenced ~2000 nuclear exons and one mitochondrial gene across the distributions of species with primarily MT or AZ distributions from three genera of lizards. Using phylogenetic analysis and population structure analyses we identified major phylogeographic lineages and then compared the spatial scale of structuring and tested for recent demographic expansions. Results Two genera in particular, Proablepharus and Morethia , showed deeper and more geographically localized phylogeographic diversity in the MT than the AZ. In the MT, localized diversity was prevalent in the relatively mesic regions. By contrast, the AZ was characterized by widespread and often genetically uniform lineages and a higher proportion of these had signals of recent population expansion. Main conclusions Consistent with other recent, but mostly less genetically extensive studies, our results point to deeper and more localized diversity in MT compared to AZ. In turn, this suggests higher local persistence in more mesic and topographically diverse biome through the late Quaternary climate fluctuations. For the AZ, geographically extensive range expansions have likely contributed to the low spatial turnover of this exceptionally rich lizard fauna.

A genome‐wide search for local adaptation in a terrestrial‐breeding frog reveals vulnerability to climate change - Deanne Cummins; W. Jason Kennington; Tabitha Rudin‐Bitterli; Nicola J. Mitchell (Global Change Biology, 2019)
Terrestrial‐breeding amphibians are likely to be vulnerable to warming and drying climates, as their embryos require consistent moisture for successful development. Adaptation to environmental change will depend on sufficient genetic variation existing within or between connected populations. Here, we use Single Nucleotide Polymorphism (SNP) data to investigate genome‐wide patterns in genetic diversity, gene flow and local adaptation in a terrestrial‐breeding frog ( Pseudophryne guentheri) subject to a rapidly drying climate and recent habitat fragmentation. The species was sampled across 12 central and range‐edge populations (192 samples), and strong genetic structure was apparent, as were high inbreeding coefficients. Populations showed differences in genetic diversity, and one population lost significant genetic diversity in a decade. More than 500 SNP loci were putatively under directional selection, and 413 of these loci were correlated with environmental variables such as temperature, rainfall, evaporation and soil moisture. One locus showed homology to a gene involved in the activation of maturation in Xenopus oocytes, which may facilitate rapid development of embryos in drier climates. The low genetic diversity, strong population structuring and presence of local adaptation revealed in this study shows why management strategies such as targeted gene flow may be necessary to assist isolated populations to adapt to future climates.

Deeply conserved susceptibility in a multi‐host, multi‐parasite system - Lisa N. Barrow; Sabrina M. McNew; Nora Mitchell; Spencer C. Galen; Holly L. Lutz; Heather Skeen; Thomas Valqui; Jason D. Weckstein; Christopher C. Witt (Ecology Letters, 2019)
Variation in susceptibility is ubiquitous in multi‐host, multi‐parasite assemblages, and can have profound implications for ecology and evolution in these systems. The extent to which susceptibility to parasites is phylogenetically conserved among hosts can be revealed by analysing diverse regional communities. We screened for haemosporidian parasites in 3983 birds representing 40 families and 523 species, spanning ~ 4500 m elevation in the tropical Andes. To quantify the influence of host phylogeny on infection status, we applied Bayesian phylogenetic multilevel models that included a suite of environmental, spatial, temporal, life history and ecological predictors. We found evidence of deeply conserved susceptibility across the avian tree; host phylogeny explained substantial variation in infection status, and results were robust to phylogenetic uncertainty. Our study suggests that susceptibility is governed, in part, by conserved, latent aspects of anti‐parasite defence. This demonstrates the importance of deep phylogeny for understanding present‐day ecological interactions.

Development and Evaluation of a Family of Human Face and Upper Airway Models for the Laboratory Testing of Orally Inhaled Products - Mark W. Nagel; Jason A. Suggett; Dominic P. Coppolo; Jolyon P. Mitchell (AAPS PharmSciTech, 2017)

Pre-operative Screening and Manual Drilling Strategies to Reduce the Risk of Thermal Injury During Minimally Invasive Cochlear Implantation Surgery - Neal P. Dillon; Loris Fichera; Kyle Kesler; M. Geraldine Zuniga; Jason E. Mitchell; Robert J. Webster; Robert F. Labadie (Annals of Biomedical Engineering, 2017)

Clinically Relevant In Vitro Testing of Orally Inhaled Products—Bridging the Gap Between the Lab and the Patient - Jolyon P. Mitchell; Jason Suggett; Mark Nagel (AAPS PharmSciTech, 2016)

The effect of incubation temperatures on nest success of flatback sea turtles (Natator depressus) - Stephanie van Lohuizen; Jason Rossendell; Nicola J. Mitchell; Michele Thums (Marine Biology, 2016)

Characterization of T gene sequence variants and germline duplications in familial and sporadic chordoma - Michael J. Kelley; Jianxin Shi; Bari Ballew; Paula L. Hyland; Wen-Qing Li; Melissa Rotunno; David A. Alcorta; Norbert J. Liebsch; Jason Mitchell; Sara Bass; David Roberson; Joseph Boland; et al. (Human Genetics, 2014)

Developing Ways to Evaluate in the Laboratory How Inhalation Devices Will Be Used by Patients and Care-Givers: The Need for Clinically Appropriate Testing - Jolyon P. Mitchell; Jason A. Suggett (AAPS PharmSciTech, 2014)

The new sequencer on the block: comparison of Life Technology’s Proton sequencer to an Illumina HiSeq for whole-exome sequencing - Joseph F. Boland; Charles C. Chung; David Roberson; Jason Mitchell; Xijun Zhang; Kate M. Im; Ji He; Stephen J. Chanock; Meredith Yeager; Michael Dean (Human Genetics, 2013)

Differential patterns of mono- and sesquiterpenes with leaf ontogeny influence pharmaceutical oil yield in Eucalyptus polybractea R.T. Baker - Jason Q. D. Goodger; Madeline C. Mitchell; Ian E. Woodrow (Trees, 2013)

Remucal et al. Respond: - Jonathan M. Remucal; Jason D. McGee; Matthew M. Fehrenbacher; Constance Best; Robert J. Mitchell (Journal of Forestry, 2013)

Non-native fishes and native species diversity in freshwater fish assemblages across the United States - Alison L. Mitchell; Jason H. Knouft (Biological Invasions, 2009)

Purification and characterization of rhodobactin: a mixed ligand siderophore from Rhodococcus rhodochrous strain OFS - Suraj Dhungana; Ryszard Michalczyk; Hakim Boukhalfa; Joseph G. Lack; Andrew T. Koppisch; Jason M. Fairlee; Mitchell T. Johnson; Christy E. Ruggiero; Seth G. John; Matthew M. Cox; Cindy C. Browder; Jennifer H. Forsythe; et al. (BioMetals, 2007)

Storms, Investor Decisions, and the Economic Impacts of Sea Level Rise - J. Jason West; Mitchell J. Small; Hadi Dowlatabadi (Climatic Change, 2001)