Mitigating municipal solid waste fouling in biofuel conversion via screw surface modifications - Xin He; Jens T. Darsell; Jaya Shankar Tumuluru; Wenbo Wang; Harry M. Meyer; James R. Keiser; Aashish Rohatgi; Daniel T. Howe; Jun Qu (Biomass and Bioenergy, 2024)

The unexpected influence of legacy conspecific density dependence - Lukas J. Magee; Joseph A. LaManna; Amy T. Wolf; Robert W. Howe; Yuanming Lu; Denis Valle; Daniel J. B. Smith; Robert Bagchi; David Bauman; Daniel J. Johnson (Ecology Letters, 2024)
When plants die, neighbours escape competition. Living conspecifics could disproportionately benefit because they are freed from negative intraspecific processes; however, if the negative effects of past conspecific neighbours persist, other species might be advantaged, and diversity might be maintained through legacy effects. We examined legacy effects in a mapped forest by modelling the survival of 37,212 trees of 23 species using four neighbourhood properties: living conspecific, living heterospecific, legacy conspecific (dead conspecifics) and legacy heterospecific densities. Legacy conspecific effects proved nearly four times stronger than living conspecific effects; changes in annual survival associated with legacy conspecific density were 1.5% greater than living conspecific effects. Over 90% of species were negatively impacted by legacy conspecific density, compared to 47% by living conspecific density. Our results emphasize that legacies of trees alter community dynamics, revealing that prior research may have underestimated the strength of density dependent interactions by not considering legacy effects.

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.

Addressing the welfare needs of farmed lumpfish: Knowledge gaps, challenges and solutions - Carlos Garcia de Leaniz; Carolina Gutierrez Rabadan; Sara I. Barrento; Rebecca Stringwell; Paul N. Howes; Ben A. Whittaker; Jessica F. Minett; Robert G. Smith; Craig L. Pooley; Ben J. Overland; Leigh Biddiscombe; Richard Lloyd; et al. (Reviews in Aquaculture, 2022)
Lumpfish ( Cyclopterus lumpus L.) are increasingly being used as cleaner fish to control parasitic sea lice, one of the most important threats to salmon farming. However, lumpfish cannot survive feeding solely on sea lice, and their mortality in salmon net‐pens can be high, which has welfare, ethical and economic implications. The industry is under increasing pressure to improve the welfare of lumpfish, but little guidance exists on how this can be achieved. We undertook a knowledge gap and prioritisation exercise using a Delphi approach with participants from the fish farming sector, animal welfare, academia and regulators to assess consensus on the main challenges and potential solutions for improving lumpfish welfare. Consensus among participants on the utility of 5 behavioural and 12 physical welfare indicators was high (87–89%), reliable (Cronbach's alpha = 0.79, 95CI = 0.69–0.92) and independent of participant background. Participants highlighted fin erosion and body damage as the most useful and practical operational welfare indicators, and blood parameters and behavioural indicators as the least practical. Species profiling revealed profound differences between Atlantic salmon and lumpfish in relation to behaviour, habitat preferences, nutritional needs and response to stress, suggesting that applying a common set of welfare standards to both species cohabiting in salmon net‐pens may not work well for lumpfish. Our study offers 16 practical solutions for improving the welfare of lumpfish and illustrates the merits of the Delphi approach for achieving consensus among stakeholders on welfare needs, targeting research where is most needed and generating workable solutions.

Tree‐mycorrhizal associations detected remotely from canopy spectral properties - Joshua B. Fisher; Sean Sweeney; Edward R. Brzostek; Tom P. Evans; Daniel J. Johnson; Jonathan A. Myers; Norman A. Bourg; Amy T. Wolf; Robert W. Howe; Richard P. Phillips (Global Change Biology, 2016)
A central challenge in global ecology is the identification of key functional processes in ecosystems that scale, but do not require, data for individual species across landscapes. Given that nearly all tree species form symbiotic relationships with one of two types of mycorrhizal fungi – arbuscular mycorrhizal ( AM ) and ectomycorrhizal ( ECM ) fungi – and that AM ‐ and ECM ‐dominated forests often have distinct nutrient economies, the detection and mapping of mycorrhizae over large areas could provide valuable insights about fundamental ecosystem processes such as nutrient cycling, species interactions, and overall forest productivity. We explored remotely sensed tree canopy spectral properties to detect underlying mycorrhizal association across a gradient of AM ‐ and ECM ‐dominated forest plots. Statistical mining of reflectance and reflectance derivatives across moderate/high‐resolution Landsat data revealed distinctly unique phenological signals that differentiated AM and ECM associations. This approach was trained and validated against measurements of tree species and mycorrhizal association across ~130 000 trees throughout the temperate United States. We were able to predict 77% of the variation in mycorrhizal association distribution within the forest plots ( P

Premorbid diet in relation to survival from prostate cancer (Canada) - Daniel J. Kim; Richard P. Gallagher; T. Gregory Hislop; Eric J. Holowaty; Geoffrey R. Howe; Meera Jain; John R. McLaughlin; Chong-Ze Teh; Thomas E. Rohan (Cancer Causes & Control, 2000)