Andrew Davis

Jan 14, 2025 | genomemedicine.biomedcentral.com | Bethany Hughes |Andrew Davis |Deborah Milligan |Ryan Wallis |Federica Mossa |Michael Philpott | +3 more

ReferencesHernandez-Segura A, Nehme J, Demaria M. Hallmarks of cellular senescence. Trends Cell Biol. 2018;28:436–53. Article  PubMed  Google Scholar  González-Gualda E, Baker AG, Fruk L, Muñoz-Espín D. A guide to assessing cellular senescence in vitro and in vivo. FEBS J. 2021;288:56–80. Article  PubMed  Google Scholar  Huang W, Hickson LJ, Eirin A, Kirkland JL, Lerman LO. Cellular senescence: the good, the bad and the unknown. Nat Rev Nephrol. 2022;18:611–27.

Aug 12, 2024 | resjournals.onlinelibrary.wiley.com | Andrew Davis |Christina Vu

INTRODUCTION From encounters with predators, to fighting with conspecifics over territory, all species in the animal kingdom must have to deal with occasional stressful events in their lives. Most animals have species-specific behaviours and/or physiological reactions to cope with these events, and ultimately to promote survival (Beehner & Bergman, 2017; Creel, 2018; Romero & Wingfield, 2016; Wingfield & Romero, 2001).

Nov 25, 2023 | delfi.lt | Andrew Davis

Stebėtojui toks srautas daro įspūdį. Tačiau M. A. neatrodo patenkinta: „I Moricci“, savo 19-ojo amžiaus ūkyje ant Toskanos kalvos šlaito už Pečolio, į pietryčius nuo Pizos, ji surinks tik mažą dalį derliaus, surinkto praėjusiais metais, kai purtė tą patį medį. Pavasarį Italijoje siautusios liūtys nukratė daugybę alyvmedžių žiedų nuo 900 M. A. Macchia‘os medžių, dar nespėjus susiformuoti vaisiams, todėl ji spėja, kad šiemet aliejaus gamyba gali sumažėti maždaug trimis ketvirtadaliais.

Oct 23, 2023 | biorxiv.org | Bethany Hughes |Andrew Davis |Ryan Wallis |Deborah Milligan

AbstractSenescence classification is an acknowledged challenge within the field, as markers are cell-type and context dependent. Currently, multiple morphological and immunofluorescence markers are required for senescent cell identification. However, emerging scRNA-seq datasets have enabled increased understanding of the heterogeneity of senescence. Here we present SenPred, a machine-learning pipeline which can identify senescence based on single-cell transcriptomics.

Jun 15, 2023 | journals.plos.org | Alexander Hall |Andrew Davis |Aleeza Sunderji |Heather D. Gallant

G x E interaction predicting right mOFC and lOFC thickness in middle childhood. For our multiple linear regression analysis with right mOFC thickness as the outcome variable, the best fitting model included the main effect of prenatal adversity, the main effect of the 5-HTT-ePRS, their interaction, and MRI scanning site (either Hamilton or Montreal) as a covariate (see Table 5). This model explained nearly 15% of the variance in right mOFC thickness (adj R2 = 0.1499, p = 0.014).