Automated Author Profile

Conte, Caterina

Department of Human Sciences and Promotion of the Quality of Life, San Raffaele Roma Open University, Rome, Italy; Department of Endocrinology, Nutrition and Metabolic Diseases, IRCCS MultiMedica, Milan, Italy
0000-0001-7066-5292

Current S-Index

0.9

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.4

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

41.3%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

A novel methodological approach to simultaneously extract high quality total RNA and proteins from cortical and trabecular bone

Molecular differences between cortical and trabecular bone, of relevance to understand the pathophysiological bases of bone diseases, can be determined only throughout effective isolation methods for RNA and proteins. Here we present a TRIzol-based method, combining bone pulverization and homogenization, to extract simultaneously total RNA and proteins from human cortical and trabecular bone from the same carrot. RNA integrity and purity were determined as the 260-to-280 nm and 260-to-230 nm absorbance- ratios, and 28S-to-18S rRNA ratio. Protein integrity and quality were evaluated by Comassie Blue staining. RT-qPCR and immunoblotting for bone-specific genes and proteins were performed to verify the suitability of the isolated material in downstream applications. 260-to-280 nm and 260-to-230 nm absorbance ratios were, on average, ≥1.8. Bands on agarose gel were consistent to an intact RNA, with mean 28S-to-18S ratios of1.68±0.35 and 1.88±0.10 for cortical and trabecular bone, respectively. Band patterns after Comassie Blue staining confirmed protein integrity. Successful gene and protein expression analysis, with relevant differences between the two compartments, highlighted the suitability of the material in downstream applications. The method here presented is appropriate and effective for the study of human bone.

Authors

  • Faraldi, Martina ;
  • Mangiavini, Laura ;
  • Conte, Caterina ;
  • Banfi, Giuseppe ;
  • Napoli, Nicola ;
  • Giovanni, Lombardi
0 Citations0 Mentions69% FAIR0.7 Dataset Index
10.5281/zenodo.5749901December 2021

A novel methodological approach to simultaneously extract high quality total RNA and proteins from cortical and trabecular bone

Molecular differences between cortical and trabecular bone, of relevance to understand the pathophysiological bases of bone diseases, can be determined only throughout effective isolation methods for RNA and proteins. Here we present a TRIzol-based method, combining bone pulverization and homogenization, to extract simultaneously total RNA and proteins from human cortical and trabecular bone from the same carrot. RNA integrity and purity were determined as the 260-to-280 nm and 260-to-230 nm absorbance- ratios, and 28S-to-18S rRNA ratio. Protein integrity and quality were evaluated by Comassie Blue staining. RT-qPCR and immunoblotting for bone-specific genes and proteins were performed to verify the suitability of the isolated material in downstream applications. 260-to-280 nm and 260-to-230 nm absorbance ratios were, on average, ≥1.8. Bands on agarose gel were consistent to an intact RNA, with mean 28S-to-18S ratios of1.68±0.35 and 1.88±0.10 for cortical and trabecular bone, respectively. Band patterns after Comassie Blue staining confirmed protein integrity. Successful gene and protein expression analysis, with relevant differences between the two compartments, highlighted the suitability of the material in downstream applications. The method here presented is appropriate and effective for the study of human bone.

Authors

  • Faraldi, Martina ;
  • Mangiavini, Laura ;
  • Conte, Caterina ;
  • Banfi, Giuseppe ;
  • Napoli, Nicola ;
  • Giovanni, Lombardi
0 Citations0 Mentions13% FAIR0.1 Dataset Index
10.5281/zenodo.5749900December 2021