Diet of juvenile skipjack herring Alosa chrysochloris : Ontogenetic shifts, predator–prey size ratios and mouth gape allometry - Joshua P. Egan; Peter J. Hundt; Neil P. Rude; Jason A. DeBoer; Benjamin J. Lubinski; Kristopher A. Maxson; Levi E. Solomon; Andrya L. Whitten Harris; Andrew M. Simons (Journal of Fish Biology, 2026)
The skipjack herring Alosa chrysochloris inhabits Gulf of Mexico drainages, primarily the Mississippi River Basin, and estuarine environments in the Gulf of Mexico. The trophic ecology of the skipjack herring is poorly understood, therefore we quantified the length, mouth gape and gut contents of juvenile skipjack herring from the Mississippi River (fish n = 6), Illinois River (fish n = 181) and Ohio River (fish n = 255) and tested for changes in diets and predator–prey size ratios during ontogeny. We identified statistically significant changes in prey type consumption during ontogeny. Aquatic insects dominated the diets of skipjack herring 40 mm SL were primarily composed of fishes. The most prevalent fish species consumed by skipjack herring were invasive bigheaded carps Hypophthalmichthys spp. and preliminary evidence indicated that inter‐annual variation in the consumption of bigheaded carps was driven by variation in juvenile bigheaded carp abundance. Additional research is needed to determine if the enhancement of native skipjack herring populations could be used as a tool to limit bigheaded carp population sizes. Skipjack herring SL and mouth gape were both significantly positively correlated with maximum, median and minimum sizes of prey consumed. There were allometric changes in the mouth gape of juvenile skipjack herring, with the ratio of mouth gape to SL increasing until ~80 mm SL, then gradually declining. Maximum mouth gape to SL ratios corresponded to substantial increases in the consumption of fishes, indicating that mouth gape allometry may facilitate the ontogenetic transition to piscivory in the skipjack herring. This study improves our understanding of skipjack herring ecology and provides data that can be incorporated into future ecological and evolutionary research, such as the development of food web models.

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

PQRI Workshop: Model-Informed Drug Development (MIDD) Approaches in Pediatric Formulation Development - Gilbert J. Burckart; Susan Abdel-Rahman; Caleb Choi; M. Petrea Cober; James E. Cummins; Nikoletta Fotaki; Daniel Gonzalez; David Harris; Neil Parrott; Hardikkumar Patel; Fang Wu; Andreas Abend (The AAPS Journal, 2026)
In February of 2024, the Product Quality Research Institute held a virtual workshop entitled “Model-Informed Drug Development (MIDD) Approaches in Pediatric Formulation Development.” The workshop covered a range of topics related to pediatric formulation development and testing, including dissolution testing and applications to modeling drug absorption in developing pediatric patients. Workshop speakers reviewed the progress that has been made to advance our understanding of ontogeny related processes that drive interactions with product formulations and inform pediatric product development. They discussed recently constructed pediatric biorelevant models that provide more realistic information about drug dissolution in pediatric patients and their use in physiologically based models to produce data for regulatory submissions. Despite the progress, opportunities remain to expand the fund of knowledge on pediatric absorptive processes that will support the development of pediatric-friendly drug formulations. 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.

First evidence of CP violation in beauty baryon to charmonium decays - R. Aaij; A.S.W. Abdelmotteleb; C. Abellan Beteta; F. Abudinén; T. Ackernley; A.A. Adefisoye; B. Adeva; M. Adinolfi; P. Adlarson; C. Agapopoulou; C.A. Aidala; Z. Ajaltouni; et al. (Science Bulletin, 2026)

Vulnerability of marine megafauna to global at‐sea anthropogenic threats - Michelle VanCompernolle; Juliet Morris; Hannah J. Calich; Jorge P. Rodríguez; Sarah A. Marley; Jessica R. Pearce; Briana Abrahms; Katya Abrantes; André S. Afonso; Alex Aguilar; Andrews Agyekumhene; Tomonari Akamatsu; et al. (Conservation Biology, 2026)
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at‐sea threats. The threats we considered included individual fishing gear types, climate‐change‐related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability ( v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.

Exceptional secular variation recorded in Neolithic hearths, Orkney and Swedish lake sediments - Neil Suttie; Sam Harris; Catherine M. Batt; Andreas Nilsson; Ian Snowball; Nick Card; Zoe Outram (Physics of the Earth and Planetary Interiors, 2025)

A Cross-Sectional Study of the Nutrition and Physical Activity Environment in Australian Family Child Care Services - Lieke Vorage; Lisa Vincze; Neil Harris (Journal of the Academy of Nutrition and Dietetics, 2025)

Setting the limit: cold rather than hot temperatures limit intertidal distribution of a coastal foundation species - Kerstin Wasson; Kim Cressman; Kathryn Beheshti; Erin C. Herder; Charlie Endris; Christopher D.G. Harley; Alicia Abadía-Cardoso; Rodrigo Beas-Luna; Joachim Carolsfeld; Andrew L. Chang; Jeffrey A. Crooks; Matthew C. Ferner; et al. (Marine Environmental Research, 2025)

Study of D s 1 ( 2460 ) + → D s + π + π - in B → D ‾ ( * ) D s + π + π - decays - R. Aaij; A.S.W. Abdelmotteleb; C.Abellan Beteta; F. Abudinén; T. Ackernley; A.A. Adefisoye; B. Adeva; M. Adinolfi; P. Adlarson; C. Agapopoulou; C.A. Aidala; Z. Ajaltouni; et al. (Science Bulletin, 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.

Exploiting the “gold of the ocean”: Can live storage solve the paradox of the purse seine fishery for Atlantic bluefin tuna in Norway? - Manu Sistiaga; Neil Anders; Jostein Saltskår; Hermann Pettersen; Michael Breen; Odd-Børre Humborstad; Hector Peña; Pau Muñoz-Benavent; Joaquín Martínez-Peiró; Gabriela Andreu-García; Victor Espinosa; Stein Harris Olsen; et al. (Marine Policy, 2025)

Effectiveness of Interventions Promoting Dietary Intake, Physical Activity, and Healthy Weight Status of Children in Family Child Care: A Systematic Review - Lieke Vorage; Lisa Vincze; Lucy Tudehope; Neil Harris (Journal of Nutrition Education and Behavior, 2024)

Corrigendum to “Scales of development for wheat and barley specific to either single culms or a population of culms” [Eur. J. Agron. 147 (2023) 126824] - Corinne Celestina; James Hunt; Hamish Brown; Neil Huth; Mariana Andreucci; Zvi Hochman; Maxwell Bloomfield; Kenton Porker; Melissa McCallum; Felicity Harris; Mary Matthews; Ben Biddulph; et al. (European Journal of Agronomy, 2023)

Street-scale dispersion modelling framework of road-traffic derived air pollution in Hanoi, Vietnam - Khoi Quang Ngo; Le Anh Hoang; Bang Quoc Ho; Neil R.P. Harris; Gillian H. Drew; Mohammed Iqbal Mead (Environmental Research, 2023)

Corrigendum to “A systematic conservation plan identifying critical areas for improved chondrichthyan protection in South Africa” [Biol. Conserv. 284 (2023) 110163] - Nina Faure-Beaulieu; Amanda T. Lombard; Jennifer Olbers; Victoria Goodall; Charlene da Silva; Ryan Daly; Gareth Jordaan; Sven E. Kerwath; Alison Kock; Bruce Q. Mann; Taryn S. Murray; Patricia Albano; et al. (Biological Conservation, 2023)

A systematic conservation plan identifying critical areas for improved chondrichthyan protection in South Africa - Nina Faure-Beaulieu; Amanda T. Lombard; Jennifer Olbers; Victoria Goodall; Charlene da Silva; Ryan Daly; Gareth Jordaan; Sven E. Kerwath; Alison Kock; Bruce Q. Mann; Taryn S. Murray; Patricia Albano; et al. (Biological Conservation, 2023)

Scales of development for wheat and barley specific to either single culms or a population of culms - Corinne Celestina; James Hunt; Hamish Brown; Neil Huth; Mariana Andreucci; Zvi Hochman; Maxwell Bloomfield; Kenton Porker; Melissa McCallum; Felicity Harris; Mary Matthews; Ben Biddulph; et al. (European Journal of Agronomy, 2023)

3D structural quantification of equine placental villi through multiscale correlative imaging - Davis Laundon; Shelley Harris; Emilie Derisoud; Diana Fanelli; Carlotta Bocci; Franceso Camillo; Neil J Gostling; Pascale Chavatte-Palmer; Rohan M Lewis (Journal of Equine Veterinary Science, 2023)

A cultivar phenology classification scheme for wheat and barley - Corinne Celestina; James Hunt; Haydn Kuchel; Felicity Harris; Kenton Porker; Ben Biddulph; Maxwell Bloomfield; Melissa McCallum; Rick Graham; Peter Matthews; Darren Aisthorpe; Ghazwan Al-Yaseri; et al. (European Journal of Agronomy, 2023)

Strong phylogenetic signals in global plant bioclimatic envelopes - Claire Harris; Neil Brummitt; Christina A. Cobbold; Richard Reeve (Global Ecology and Biogeography, 2022)
Aim The environmental preferences of species are an important facet of their response to changing conditions, and these have long been thought to exhibit phylogenetic conservatism. However, these bioclimatic envelopes have not previously been imputed from climate records at the date and location of occurrence, and the strength of their phylogenetic signal has not been studied at a broad scale. Here, we combine records from global climate reconstructions with contemporaneous plant occurrences for all available terrestrial plant species and test for phylogenetic niche conservatism in plant climatic traits. Location Global. Time period 1901–2018. Major taxa studied Terrestrial plants. Methods We used >100 million plant records from the Global Biodiversity Information Facility (GBIF) to produce distributions of bioclimatic envelopes for >200,000 species, using a range of climate variables. We matched species observations to historical climate reconstructions from the European Centre for Medium‐Range Weather Forecasting (ECMWF) and compared this with WorldClim climate averages. We tested for phylogenetic signal in a supertree of plants using Pagel's λ. Finally, to investigate how well bioclimatic envelopes could be inferred for poorly known and rare species, we performed cross‐validation by removing occurrence records for some common species to test how accurately their bioclimatic envelopes were estimated. Results We found extremely strong phylogenetic signals (λ > 0.9 in some cases) for climate variables from both climate datasets, including temperature, soil temperature, solar radiation and precipitation. We were also able to impute missing bioclimatic envelopes for artificially removed species, having a correlation with observed data of .7. Main conclusions We reconstructed plant climatic tolerances for >200,000 plant species historically recorded on GBIF using a technique that could be applied to any comparable biodiversity dataset. Although global information on most species is sparse, we explored methods for bias correction and data imputation, with positive results for both.

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.

SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States - Michael V. Cove; Roland Kays; Helen Bontrager; Claire Bresnan; Monica Lasky; Taylor Frerichs; Renee Klann; Thomas E. Lee; Seth C. Crockett; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2021)
With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14‐week period (17 August–24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian’s eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban–wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot‐usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species‐specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.

Opportunities and challenges for herbaria in studying the spatial variation in plant functional diversity - Timothy Harris; Mark Mulligan; Neil Brummitt (Systematics and Biodiversity, 2021)

Modelling the effect of the 2018 summer heatwave and drought on isoprene emissions in a UK woodland - Frederick Otu‐Larbi; Conor G. Bolas; Valerio Ferracci; Zosia Staniaszek; Roderic L. Jones; Yadvinder Malhi; Neil R. P. Harris; Oliver Wild; Kirsti Ashworth (Global Change Biology, 2020)
Projected future climatic extremes such as heatwaves and droughts are expected to have major impacts on emissions and concentrations of biogenic volatile organic compounds (bVOCs) with potential implications for air quality, climate and human health. While the effects of changing temperature and photosynthetically active radiation (PAR) on the synthesis and emission of isoprene, the most abundant of these bVOCs, are well known, the role of other environmental factors such as soil moisture stress are not fully understood and are therefore poorly represented in land surface models. As part of the Wytham Isoprene iDirac Oak Tree Measurements campaign, continuous measurements of isoprene mixing ratio were made throughout the summer of 2018 in Wytham Woods, a mixed deciduous woodland in southern England. During this time, the United Kingdom experienced a prolonged heatwave and drought, and isoprene mixing ratios were observed to increase by more than 400% at Wytham Woods under these conditions. We applied the state‐of‐the‐art FORest Canopy‐Atmosphere Transfer canopy exchange model to investigate the processes leading to these elevated concentrations. We found that although current isoprene emissions algorithms reproduced observed mixing ratios in the canopy before and after the heatwave, the model underestimated observations by ~40% during the heatwave–drought period implying that models may substantially underestimate the release of isoprene to the atmosphere in future cases of mild or moderate drought. Stress‐induced emissions of isoprene based on leaf temperature and soil water content (SWC) were incorporated into current emissions algorithms leading to significant improvements in model output. A combination of SWC, leaf temperature and rewetting emission bursts provided the best model‐measurement fit with a 50% improvement compared to the baseline model. Our results highlight the need for more long‐term ecosystem‐scale observations to enable improved model representation of atmosphere–biosphere interactions in a changing global climate.

Dynamics in the global protected‐area estate since 2004 - Edward Lewis; Brian MacSharry; Diego Juffe‐Bignoli; Nyeema Harris; Georgina Burrows; Naomi Kingston; Neil D. Burgess (Conservation Biology, 2019)
Nations of the world have committed to a number of goals and targets to address global environmental challenges. Protected areas have for centuries been a key strategy in conservation and play a major role in addressing current challenges. The most important tool used to track progress on protected‐area commitments is the World Database on Protected Areas (WDPA). Periodic assessments of the world's protected‐area estate show steady growth over the last 2 decades. However, the current method, which uses the latest version of the WDPA, does not show the true dynamic nature of protected areas over time and does not provide information on sites removed from the WDPA. In reality, this method can only show growth or remain stable. We used GIS tools in an approach to assess protected‐area change over time based on 12 temporally distinct versions of the WDPA that quantify area added and removed from the WDPA annually from 2004 to 2016. Both the narrative of continual growth of protected area and the counter‐narrative of protected area removal were overly simplistic. The former because growth was almost entirely in the marine realm and the latter because some areas removed were reprotected in later years. On average 2.5 million km 2 was added to the WDPA annually and 1.1 million km 2 was removed. Reasons for the inclusion and removal of protected areas in the WDPA database were in part due to data‐quality issues but also to on‐the‐ground changes. To meet the 17% protected‐area component of Aichi Biodiversity Target 11 by 2020, which stood at 14.7% in 2016, either the rate of protected‐area removal must decrease or the rate of protected‐area designation and addition to the WDPA must increase.

Meta-analysis identifies mitochondrial DNA sequence variants associated with walking speed - Todd M. Manini; Thomas W. Buford; John A. Kairalla; Mary M. McDermott; Carlos A. Vaz Fragoso; Roger A. Fielding; Fang-Chi Hsu; Neil Johannsen; Stephen Kritchevsky; Tamara B. Harris; Anne B. Newman; Steven R. Cummings; et al. (GeroScience, 2018)

Consensus guidelines for the use and interpretation of angiogenesis assays - Patrycja Nowak-Sliwinska; Kari Alitalo; Elizabeth Allen; Andrey Anisimov; Alfred C. Aplin; Robert Auerbach; Hellmut G. Augustin; David O. Bates; Judy R. van Beijnum; R. Hugh F. Bender; Gabriele Bergers; Andreas Bikfalvi; et al. (Angiogenesis, 2018)

Spatial-temporal variations in surface ozone over Ushuaia and the Antarctic region: observations from in situ measurements, satellite data, and global models - Mohd Shahrul Mohd Nadzir; Matthew J. Ashfold; Md Firoz Khan; Andrew D. Robinson; Conor Bolas; Mohd Talib Latif; Benjamin M. Wallis; Mohammed Iqbal Mead; Haris Hafizal Abdul Hamid; Neil R. P. Harris; Zamzam Tuah Ahmad Ramly; Goh Thian Lai; et al. (Environmental Science and Pollution Research, 2018)

Progress and Challenges in Coupled Hydrodynamic-Ecological Estuarine Modeling - Neil K. Ganju; Mark J. Brush; Brenda Rashleigh; Alfredo L. Aretxabaleta; Pilar del Barrio; Jason S. Grear; Lora A. Harris; Samuel J. Lake; Grant McCardell; James O’Donnell; David K. Ralston; Richard P. Signell; et al. (Estuaries and Coasts, 2016)

Fine mapping of the Asian soybean rust resistance gene Rpp2 from soybean PI 230970 - Neil Yu; Myungsik Kim; Zachary R. King; Donna K. Harris; James W. Buck; Zenglu Li; Brian W. Diers (Theoretical and Applied Genetics, 2015)

Volatile halocarbon emissions by three tropical brown seaweeds under different irradiances - Fiona Seh-Lin Keng; Siew-Moi Phang; Noorsaadah Abd Rahman; Emma C. Leedham; Claire Hughes; Andrew D. Robinson; Neil R. P. Harris; John A. Pyle; William T. Sturges (Journal of Applied Phycology, 2013)

Potential climatic transitions with profound impact on Europe - Anders Levermann; Jonathan L. Bamber; Sybren Drijfhout; Andrey Ganopolski; Winfried Haeberli; Neil R. P. Harris; Matthias Huss; Kirstin Krüger; Timothy M. Lenton; Ronald W. Lindsay; Dirk Notz; Peter Wadhams; et al. (Climatic Change, 2012)

Poster abstracts - J. Ferrie; M. Shipley; F. Cappuccio; E. Brunner; M. Miller; M. Kumari; M. Marmot; A. Coenen; J. L. Castillo; F. Araya; G. Bustamante; L. Montecino; et al. (Sleep and Biological Rhythms, 2007)

A Microarray-based Detection System for Genetically Modified (GM) Food Ingredients - Serge Leimanis; Marta Hernández; Sophie Fernández; Francine Boyer; Malcolm Burns; Shirin Bruderer; Thomas Glouden; Neil Harris; Othmar Kaeppeli; Patrick Philipp; Maria Pla; Pere Puigdomènech; et al. (Plant Molecular Biology, 2006)

The regulation of virulence in phytopathogenic Erwinia species: quorum sensing, antibiotics and ecological considerations - Neil A. Whitehead; Joseph T. Byers; Paul Commander; Mark J. Corbett; Sarah J. Coulthurst; Lee Everson; Abigail K.P. Harris; Clare L. Pemberton; Natalie J.L. Simpson; Holly Slater; Debra S. Smith; Martin Welch; et al. (Antonie van Leeuwenhoek, 2002)

The research potential of tissue from a cadaveric donor - Christopher Womack; Neil M. Gray; Lesley J. Howes; Michael D. Harris (Cell and Tissue Banking, 2002)