Landsat Instrument Suite (LandIS) sensor design for the Landsat 10 mission - Matthew Montanaro; Jeffrey Yee; Edmond Chung; Julie Montoya; Benjamin Turk; Eric Johnson; Andrew Pozo; Evan Haas; Steven Persh; Shawn Serbin; Thomas R. Holmes; Phillip W. Dabney; et al. (Remote Sensing of Environment, 2026)

Decarbonization and non-cooperating strategies: A case for Mexico - Alejandra Salazar; Jae Edmonds; Stefano Battiston; Serafin Martinez-Jaramillo; Matthew Zwerling (Energy and Climate Change, 2026)

Assessing the evidence for active volcanism on Venus: current limitations and prospects for future investigations - Justin Filiberto; Mikhail Yu. Zolotov; Erika Kohler; Piero D'Incecco; Dmitry A. Gorinov; Sriram S. Bhiravarasu; Matthew B. Weller; Jeremy F. Brossier; Iván López; Philippa J. Mason; Jemila A. Edmond; Nicola Mari; et al. (Geochemistry, 2025)

Bioenergy pathways within United States net-zero CO2 emissions scenarios in the Energy Modeling Forum 37 study - Ronald D. Sands; Liz Wachs; Patrick Lamers; Olivier Bahn; Robert H. Beach; Matthew Binsted; Geoffrey Blanford; Yongxia Cai; Francisco De La Chesnaye; James A. Edmonds; Leonard Göke; Chioke Harris; et al. (Energy and Climate Change, 2025)

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts - John E.T. Bistline; Matthew Binsted; Geoffrey Blanford; Gale Boyd; Morgan Browning; Yongxia Cai; Jae Edmonds; Allen A. Fawcett; Jay Fuhrman; Ruying Gao; Chioke Harris; Christopher Hoehne; et al. (Energy and Climate Change, 2025)

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal - Matthew Binsted; Ellie Lochner; Jae Edmonds; José Benitez; John Bistline; Morgan Browning; Francisco De La Chesnaye; Jay Fuhrman; Leonard Göke; Gokul Iyer; Kathleen Kennedy; Page Kyle; et al. (Energy and Climate Change, 2024)

Agrobacterium-mediated transformation, selection and regeneration of Vanilla pompona - Vovener de Verlands Edmond; Pamela A. Moon; Matthew Bremgartner; Xingbo Wu; Elias Bassil (Plant Cell, Tissue and Organ Culture (PCTOC), 2024)

Net-zero CO2 by 2050 scenarios for the United States in the Energy Modeling Forum 37 study - Morgan Browning; James McFarland; John Bistline; Gale Boyd; Matteo Muratori; Matthew Binsted; Chioke Harris; Trieu Mai; Geoff Blanford; Jae Edmonds; Allen A. Fawcett; Ozge Kaplan; et al. (Energy and Climate Change, 2023)

Reproductive and margin of safety of a fixed-dose combination injectable endectocide (0.2 mg/kg doramectin; 6.0 mg/kg levamisole hydrochloride) in cattle - Matthew J. Krautmann; Matthew Edmonds; Jenifer Edmonds; Nicholas K. Van Engen; Kevin Esch; Rodney K. Frank; Erin Quist; Jezaniah Kira Tena; Kayla M. Saad; Noelle Cotey; Andrew A. DeRosa (Veterinary Parasitology, 2023)

Extinction risk of the endemic vascular flora of Kauai, Hawaii, based on IUCN assessments - Nina Rønsted; Seana K. Walsh; Margaret Clark; Merlin Edmonds; Tim Flynn; Scott Heintzman; Alexander Loomis; David Lorence; Uma Nagendra; Ben Nyberg; Michael Opgenorth; Lauren Weisenberger; et al. (Conservation Biology, 2022)
The International Union for Conservation of Nature's Red List of Threatened Species (IUCN Red List) is the world's most comprehensive information source on the global conservation status of species. Governmental agencies and conservation organizations increasingly rely on IUCN Red List assessments to develop conservation policies and priorities. Funding agencies use the assessments as evaluation criteria, and researchers use meta‐analysis of red‐list data to address fundamental and applied conservation science questions. However, the circa 143,000 IUCN assessments represent a fraction of the world's biodiversity and are biased in regional and organismal coverage. These biases may affect conservation priorities, funding, and uses of these data to understand global patterns. Isolated oceanic islands are characterized by high endemicity, but the unique biodiversity of many islands is experiencing high extinction rates. The archipelago of Hawaii has one of the highest levels of endemism of any floristic region; 90% of its 1367 native vascular plant taxa are classified as endemic. We used the IUCN's assessment of the complete single‐island endemic (SIE) vascular plant flora of Kauai, Hawaii, to assess the proportion and drivers of decline of threatened plants in an oceanic island setting. We compared the IUCN assessments with federal, state, and other local assessments of Kauai species or taxa of conservation concern. Finally, we conducted a preliminary assessment for all 1044 native vascular plants of Hawaii based on IUCN criterion B by estimating area of occupancy, extent of occurrence, and number of locations to determine whether the pattern found for the SIE vascular flora of Kauai is comparable to the native vascular flora of the Hawaiian Islands. We compared our results with patterns observed for assessments of other floras. According to IUCN, 256 SIE vascular plant taxa are threatened with extinction and 5% are already extinct. This is the highest extinction risk reported for any flora to date. The preliminary assessment of the native vascular flora of Hawaii showed that 72% (753 taxa) is threatened. The flora of Hawaii may be one of the world's most threatened; thus, increased and novel conservation measures in the state and on other remote oceanic islands are urgently needed.

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

US energy system transitions under cumulative emissions budgets - Felipe Feijoo; Gokul Iyer; Matthew Binsted; James Edmonds (Climatic Change, 2020)

Spatial variation in the origin and reactivity of dissolved organic matter in Oregon-Washington coastal waters - YueHan Lu; Jennifer W. Edmonds; Youhei Yamashita; Bin Zhou; Andrea Jaegge; Matthew Baxley (Ocean Dynamics, 2015)

The diversity of arbuscular mycorrhizas of selected Australian Fabaceae - Mark Tibbett; Megan H. Ryan; Susan J. Barker; Yinglong Chen; Matthew D. Denton; Tamara Edmonds-Tibbett; Christopher Walker (Plant Biosystems, 2008)

Spatial variability of soil properties in cypress domes surrounded by different land uses - Matthew J. Cohen; Edmond J. Dunne; Gregory L. Bruland (Wetlands, 2008)