Efficiency of phosphate fertilizers containing growth promoters in plant fertilization - Rafael Lucas Coca Cuesta; Edson Marcio Mattiello; Gustavo Franco de Castro; Patrícia Cardoso Matias; Thalita Suelen Avelar Monteiro; Leandro Grassi de Freitas (Biocatalysis and Agricultural Biotechnology, 2024)

Conversion of foliar residues of Sansevieria trifasciata into adsorbents: dye adsorption in continuous and discontinuous systems - Patrícia Grassi; Matias Schadeck Netto; Sérgio Luiz Jahn; Jordana Georgin; Dison S. P. Franco; Mika Sillanpää; Lucas Meili; Luis F. O. Silva (Environmental Science and Pollution Research, 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.

Application of Thermally Treated Water Treatment Sludge as a Remarkable Adsorbent Towards Emerging Pollutant Removal from Aqueous Solution - Patrícia Grassi; Edson Luiz Foletto; Guilherme Luiz Dotto; Dison Stracke Pfingsten Franco; Sérgio Luiz Jahn (Water, Air, & Soil Pollution, 2021)

Application of Cordia trichotoma sawdust as an effective biosorbent for removal of crystal violet from aqueous solution in batch system and fixed-bed column - Patrícia Grassi; Fernanda Caroline Drumm; Jordana Georgin; Dison Stracke Pfingsten Franco; Guilherme Luiz Dotto; Edson Luiz Foletto; Sérgio Luiz Jahn (Environmental Science and Pollution Research, 2021)

Macro-fungal (Agaricus bisporus) wastes as an adsorbent in the removal of the acid red 97 and crystal violet dyes from ideal colored effluents - Fernanda Caroline Drumm; Dison Stracke Pfingsten Franco; Jordana Georgin; Patrícia Grassi; Sérgio Luiz Jahn; Guilherme Luiz Dotto (Environmental Science and Pollution Research, 2021)

Applicability of Coal Bottom Ash from Thermoelectric Power Plant as an Alternative Heterogeneous Catalyst in Photo-Fenton Reaction - Fernanda Caroline Drumm; Patrícia Grassi; Aline Alexia Sulkovski; Dison Stracke Pfingsten Franco; Jordana Georgin; Guilherme Luiz Dotto; Edson Luiz Foletto; Sérgio Luiz Jahn (Water, Air, & Soil Pollution, 2019)

Potential of Cedrella fissilis bark as an adsorbent for the removal of red 97 dye from aqueous effluents - Jordana Georgin; Dison S. P. Franco; Patricia Grassi; Denise Tonato; Daniel G. A. Piccilli; Lucas Meili; Guilherme L. Dotto (Environmental Science and Pollution Research, 2019)

Hemispheric asymmetries and bimanual asynchrony in left- and right-handers - Paolo Viviani; D. Perani; Franco Grassi; Valentino Bettinardi; Ferruccio Fazio (Experimental Brain Research, 1998)