Dynamic proportional loss of functional connectivity revealed change of left superior frontal gyrus in subjective cognitive decline: an explanatory study based on Chinese and Western cohorts - Luyao Wang; Wenjing Hu; Fan Dong; Can Sheng; Jinglong Wu; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2025)

Local molecular and connectomic contributions of tau-related neurodegeneration - Fardin Nabizadeh; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; John Q. Trojanowski; Arthur W. Toga; Laurel Beckett; Robert C. Green; Andrew J. Saykin; John Morris; et al. (GeroScience, 2024)

Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer’s disease: an exploratory study of 18F-FDG-PET - Qi Zhang; Chunqiu Fan; Luyao Wang; Taoran Li; Min Wang; Ying Han; Jiehui Jiang; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2023)

Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment - Jiehui Jiang; Can Sheng; Guanqun Chen; Chunhua Liu; Shichen Jin; Lanlan Li; Xueyan Jiang; Ying Han; Michael W. Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 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.

Estuarine Ecosystem Response Captured Using a Synoptic Climatology - David G. Kimmel; W. David Miller; Lawrence W. Harding; Edward D. Houde; Michael R. Roman (Estuaries and Coasts, 2009)

Anthropogenic and climatic influences on the eutrophication of large estuarine ecosystems - Hans W. Paerl; Lexia M. Valdes; Benjamin L. Peierls; Jason E. Adolf; Lawrence Jr. W. Harding (Limnology and Oceanography, 2006)
We examined the effects of anthropogenic and climatic perturbations on nutrient—phytoplankton interactions and eutrophication in the waters of the largest estuarine systems in the U.S.A., the Chesapeake Bay (CB), Maryland/ Virginia, and the Neuse River Estuary/Pamlico Sound (NRE/PS) system, North Carolina. Both systems have experienced large post‐World War II increases in nitrogen (N) and phosphorus (P) loading, and nutrient reductions have been initiated to alleviate symptoms of eutrophication. However, ecosystem‐level effects of these nutrient reductions are strongly affected by hydrologic variability, including severe droughts and a recent increase in Atlantic hurricane activity. Phytoplankton community responses to these hydrologic perturbations, including storm surges and floods, were examined and when possible, compared for these systems. In both systems, the resulting variability in water residence time strongly influenced seasonal and longer‐term patterns of phytoplankton biomass and community composition. Fast‐growing diatoms were favored during years of high discharge and short residence time in CB, whereas this effect was not observed during high discharge conditions in the longer residence time NRE/ PS. In the NRE/PS, all phytoplankton groups except summer cyanobacterial populations showed decreased abundance during elevated flow years when compared to low flow years. Although hurricanes affected the CB less frequently than the NRE/PS, they nonetheless influenced floral composition in both systems. Seasonally, hydrologic perturbations, including droughts, floods, and storm‐related deep mixing events, overwhelmed nutrient controls on floral composition. This underscores the difficulty in predicting seasonal and longer‐term phytoplankton production and compositional responses to nutrient input reductions aimed at controlling eutrophication of large estuarine ecosystems.

Phytoplankton production, biomass and community structure following a summer nutrient pulse in Chesapeake Bay - Christina L.J. Yeager; Lawrence W. Harding; Michael E. Mallonee (Aquatic Ecology, 2005)