Southern Flounder: Major Milestones and Remaining Knowledge Gaps in Their Biology, Ecology, and Fishery Management - Stephen R. Midway; Frederick S. Scharf; Michael A. Dance; Nancy J. Brown-Peterson; Joseph C. Ballenger; Nicolette S. Beeken; Russell J. Borski; Tanya L. Darden; Kenneth A. Erickson; Troy M. Farmer; Ashley Fincannon; John Godwin; et al. (Reviews in Fisheries Science & Aquaculture, 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)

Evaluating Thin-Layer Sediment Placement as a Tool for Enhancing Tidal Marsh Resilience: a Coordinated Experiment Across Eight US National Estuarine Research Reserves - Kenneth B. Raposa; Andrea Woolfolk; Charlie A. Endris; Monique C. Fountain; Gregg Moore; Megan Tyrrell; Rebecca Swerida; Scott Lerberg; Brandon J. Puckett; Matthew C. Ferner; Jeffrey Hollister; David M. Burdick; et al. (Estuaries and Coasts, 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)

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.

Predicting complete winter ice coverage at Lake George, New York - Campbell D. Watson; Guillaume Auger; Mukul Tewari; Lloyd A. Treinish; Kenneth E. Johnston (International Journal of Climatology, 2021)
Ice records at Lake George, an oligotrophic and dimictic freshwater lake in upstate New York, United States reveal that it has failed to freeze over completely 13 times since 1990. This transition from annual to intermittent ice cover is analogous to many other dimictic freshwater lakes globally. Over 60 years of meteorological observations from a nearby airport are analysed and a complicated picture emerges when considering the specific characteristics of each year. For example, Lake George froze over in 1983 and 2007 despite the air temperature having a net warming effect on the lake in the month prior to ice‐in. Simple machine learning classifiers are trained using local weather data to predict the presence of complete ice coverage on Lake George and are found to perform adequately compared to observations, with one configuration having an accuracy of 91%. Using downscaled data from a coupled‐climate model through to 2,100, projections with the trained classifiers suggest complete ice coverage will be a phenomenon of the past by the mid‐to‐late 21st Century. Furthermore, by 2080–2,100 the mean air temperature is projected to warm up to +8.0 C under Representative Concentration Pathway 8.5. These projections will be of concern to the communities and policy makers of Lake George responsible for the management of the ecological and socio‐economic systems.

Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care - Matthew Barrett; Josiane Boyne; Julia Brandts; Hans-Peter Brunner-La Rocca; Lieven De Maesschalck; Kurt De Wit; Lana Dixon; Casper Eurlings; Donna Fitzsimons; Olga Golubnitschaja; Arjan Hageman; Frank Heemskerk; et al. (EPMA Journal, 2019)
Heart failure (HF) is one of the most complex chronic disorders with high prevalence, mainly due to the ageing population and better treatment of underlying diseases. Prevalence will continue to rise and is estimated to reach 3% of the population in Western countries by 2025. It is the most important cause of hospitalisation in subjects aged 65 years or more, resulting in high costs and major social impact. The current “one-size-fits-all” approach in the treatment of HF does not result in best outcome for all patients. These facts are an imminent threat to good quality management of patients with HF. An unorthodox approach from a new vision on care is required. We propose a novel predictive, preventive and personalised medicine approach where patients are truly leading their management, supported by an easily accessible online application that takes advantage of artificial intelligence. This strategy paper describes the needs in HF care, the needed paradigm shift and the elements that are required to achieve this shift. Through the inspiring collaboration of clinical and high-tech partners from North-West Europe combining state of the art HF care, artificial intelligence, serious gaming and patient coaching, a virtual doctor is being created. The results are expected to advance and personalise self-care, where standard care tasks are performed by the patients themselves, in principle without involvement of healthcare professionals, the latter being able to focus on complex conditions. This new vision on care will significantly reduce costs per patient while improving outcomes to enable long-term sustainability of top-level HF care.

On the Future of Argo: A Global, Full-Depth, Multi-Disciplinary Array - Dean Roemmich; Matthew H. Alford; Hervé Claustre; Kenneth Johnson; Brian King; James Moum; Peter Oke; W. Brechner Owens; Sylvie Pouliquen; Sarah Purkey; Megan Scanderbeg; Toshio Suga; et al. (Frontiers in Marine Science, 2019)

Source relationships between streambank soils and streambed sediments in a mercury-contaminated stream - Johnbull O. Dickson; Melanie A. Mayes; Scott C. Brooks; Tonia L. Mehlhorn; Kenneth A. Lowe; Jennifer K. Earles; Leroy Goñez-Rodriguez; David B. Watson; Mark J. Peterson (Journal of Soils and Sediments, 2019)

Development and Application of a Method to Identify Salt Marsh Vulnerability to Sea Level Rise - Marci L. Cole Ekberg; Kenneth B. Raposa; Wenley S. Ferguson; Kevin Ruddock; Elizabeth Burke Watson (Estuaries and Coasts, 2017)

Wetland Loss Patterns and Inundation-Productivity Relationships Prognosticate Widespread Salt Marsh Loss for Southern New England - Elizabeth Burke Watson; Cathleen Wigand; Earl W. Davey; Holly M. Andrews; Joseph Bishop; Kenneth B. Raposa (Estuaries and Coasts, 2017)

A Climate Change Adaptation Strategy for Management of Coastal Marsh Systems - Cathleen Wigand; Thomas Ardito; Caitlin Chaffee; Wenley Ferguson; Suzanne Paton; Kenneth Raposa; Charles Vandemoer; Elizabeth Watson (Estuaries and Coasts, 2017)

Gas chromatography–mass spectrometry analysis of fatty acid profiles of Antarctic and non-Antarctic yeasts - Mohammad Bhuiyan; David Tucker; Kenneth Watson (Antonie van Leeuwenhoek, 2014)

Cold-adapted yeasts from Antarctica and the Italian Alps—description of three novel species: Mrakia robertii sp. nov., Mrakia blollopis sp. nov. and Mrakiella niccombsii sp. nov. - Skye Robin Thomas-Hall; Benedetta Turchetti; Pietro Buzzini; Eva Branda; Teun Boekhout; Bart Theelen; Kenneth Watson (Extremophiles, 2010)

TheGus-e locus regulates estrogen repression of androgen-induced β-glucuronidase expression in mouse kidney - Gordon Watson; Rolf Jaussi; Dorothy Tabron; Kenneth Paigen (Biochemical Genetics, 1993)

TheGus-e locus regulates estrogen repression of androgen-induced β-glucuronidase expression in mouse kidney - Gordon Watson; Rolf Jaussi; Dorothy Tabron; Kenneth Paigen (Biochemical Genetics, 1993)

Expression of ?-glucuronidase haplotypes in prototype and congenic mouse strains - Kurt Pfister; Kenneth Paigen; Gordon Watson; Verne Chapman (Biochemical Genetics, 1982)

Segregation of genetic determinants for murine glucuroinidase synthesis and loss in CXB recombinant-inbred strains - Gordon Watson; Kenneth Paigen (Biochemical Genetics, 1978)