Regional variability in peatland burning at mid-to high-latitudes during the Holocene - Thomas G. Sim; Graeme T. Swindles; Paul J. Morris; Andy J. Baird; Angela V. Gallego-Sala; Yuwan Wang; Maarten Blaauw; Philip Camill; Michelle Garneau; Mark Hardiman; Julie Loisel; Minna Vӓliranta; et al. (Quaternary Science Reviews, 2023)

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.

Quantifying global greenhouse gas emissions from land‐use change for crop production - Helen C. Flynn; Llorenç Milà i. Canals; Emma Keller; Henry King; Sarah Sim; Astley Hastings; Shifeng Wang; Pete Smith (Global Change Biology, 2012)
Many assessments of product carbon footprint ( PCF ) for agricultural products omit emissions arising from land‐use change ( LUC ). In this study, we developed a framework based on IPCC national greenhouse gas inventory methodologies to assess the impacts of LUC from crop production using oil palm, soybean and oilseed rape as examples. Using ecological zone, climate and soil types from the top 20 producing countries, calculated emissions for transitions from natural vegetation to cropland on mineral soils under typical management ranged from −4.5 to 29.4 t CO 2 ‐eq ha −1 yr −1 over 20 years for oil palm and 1.2–47.5 t CO 2 ‐eq ha −1 yr −1 over 20 years for soybeans. Oilseed rape showed similar results to soybeans, but with lower maximum values because it is mainly grown in areas with lower C stocks. GHG emissions from other land‐use transitions were between 62% and 95% lower than those from natural vegetation for the arable crops, while conversions to oil palm were a sink for C . LUC emissions were considered on a national basis and also expressed per‐tonne‐of‐oil‐produced. Weighted global averages indicate that, depending on the land‐use transition, oil crop production on newly converted land contributes between −3.1 and 7.0 t CO 2 ‐eq t oil production −1 yr −1 for palm oil, 11.9–50.6 t CO 2 ‐eq t oil production −1 yr −1 for soybean oil, and 7.7–31.4 t CO 2 ‐eq t oil production −1 yr −1 for rapeseed oil. Assumptions made about crop and LUC distribution within countries contributed up to 66% error around the global averages for natural vegetation conversions. Uncertainty around biomass and soil C stocks were also examined. Finer resolution data and information (particularly on land management and yield) could improve reliability of the estimates but the framework can be used in all global regions and represents an important step forward for including LUC emissions in PCF s.

Linkage disequilibrium between the CYP2C19*17 allele and wildtype CYP2C8 and CYP2C9 alleles: identification of CYP2C haplotypes in healthy Nordic populations - Rasmus S. Pedersen; Charlotte Brasch-Andersen; Sarah C. Sim; Troels K. Bergmann; Jónrit Halling; Maria S. Petersen; Pál Weihe; Hege Edvardsen; Vessela N. Kristensen; Kim Brøsen; Magnus Ingelman-Sundberg (European Journal of Clinical Pharmacology, 2010)

Molecular genetics and epigenetics of the cytochrome P450 gene family and its relevance for cancer risk and treatment - Cristina Rodriguez-Antona; Alvin Gomez; Maria Karlgren; Sarah C. Sim; Magnus Ingelman-Sundberg (Human Genetics, 2010)

Kinetics of omeprazole and escitalopram in relation to the CYP2C19*17 allele in healthy subjects - Staffan Ohlsson Rosenborg; Jessica Mwinyi; Maria Andersson; R. Michael Baldwin; Rasmus Steen Pedersen; Sarah C. Sim; Leif Bertilsson; Magnus Ingelman-Sundberg; Erik Eliasson (European Journal of Clinical Pharmacology, 2008)