Automated Author ProfileEscribano, J.
Escribano, J.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Background/Aims: Dietary factors can modify calciuria. We aim to investigate urinary calcium excretion in healthy infants according to their protein. Methods: Secondary data analysis from a randomized clinical trial where healthy term infants were randomized after birth to a higher (HP) or lower (LP) protein content formula that was consumed until age 1 year. A non-randomized group of breastfed (BF) infants was used for reference. Anthropometry, dietary intakes and calciuria (calcium/creatinine ratios) from spot urine samples were assessed at ages 3 and 6 months. At 6 months, the kidney volumes were assessed using ultrasonography, and the serum urea and creatinine levels were determined. Results: BF infants showed the highest calciuria levels, followed by the HP and the LP groups (p < 0.001 for all comparisons). Either protein intakes or formula types modulated the calciuria in linear regression models adjusted for other influencing dietary factors. The usual cut-off values classified 37.8% (BF), 16.8% (HP) and 4.9% (LP) of the infants as hypercalciuric. Conclusions: Feeding types during the first months of life affect calciuria, with BF infants presenting the highest levels. We propose new cut-off values, based on feeding types, to prevent the overestimation in hypercalciuria diagnoses among BF infants.
Authors
- Ferré, N. ;
- Rubio-Torrents, C. ;
- Luque, V. ;
- Closa-Monasterolo, R. ;
- Grote, V. ;
- Koletzko, B. ;
- Socha, P. ;
- Gruszfeld, D. ;
- Langhendries, J.P. ;
- Sengier, A. ;
- Verduci, E. ;
- Escribano, J. ;
- For The European Childhood Obesity Project Group
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Authors
- Aguado, R. ;
- Escribano, J. ;
- Pedrosa, M.R. ;
- De Cian, A. ;
- Arnaiz, R.S.F.J.