G. Riccardi

498 total citations
8 papers, 355 citations indexed

About

G. Riccardi is a scholar working on Physiology, Nutrition and Dietetics and Molecular Biology. According to data from OpenAlex, G. Riccardi has authored 8 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Physiology, 3 papers in Nutrition and Dietetics and 2 papers in Molecular Biology. Recurrent topics in G. Riccardi's work include Diet and metabolism studies (4 papers), Fatty Acid Research and Health (3 papers) and Nutritional Studies and Diet (2 papers). G. Riccardi is often cited by papers focused on Diet and metabolism studies (4 papers), Fatty Acid Research and Health (3 papers) and Nutritional Studies and Diet (2 papers). G. Riccardi collaborates with scholars based in Italy, Sweden and Denmark. G. Riccardi's co-authors include Matti Uusitupa, Lars Berglund, Kjeld Hermansen, Bengt Vessby, Angela A. Rivellese, Linda C Tapsell, Eva Ringdal Pedersen, Birthe M. Rasmussen, Brunella Capaldo and Giovanni Annuzzi and has published in prestigious journals such as American Journal of Clinical Nutrition, Journal of Nutrition and Atherosclerosis.

In The Last Decade

G. Riccardi

8 papers receiving 345 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
G. Riccardi Italy	6	188	118	110	93	57	8	355
M. Elizabeth Tejero United States	11	180 1.0×	162 1.4×	106 1.0×	91 1.0×	39 0.7×	15	446
AC Beynen Netherlands	8	248 1.3×	135 1.1×	52 0.5×	107 1.2×	62 1.1×	8	448
Ada Maffettone Italy	8	224 1.2×	149 1.3×	139 1.3×	78 0.8×	70 1.2×	17	383
Yuki Kuromori Japan	10	139 0.7×	111 0.9×	115 1.0×	54 0.6×	57 1.0×	20	342
AJ Sinclair United Kingdom	10	137 0.7×	107 0.9×	60 0.5×	92 1.0×	41 0.7×	21	395
Susanne H. F. Vermunt Netherlands	7	189 1.0×	75 0.6×	125 1.1×	62 0.7×	62 1.1×	10	385
Christopher K. Armah United Kingdom	8	196 1.0×	87 0.7×	61 0.6×	67 0.7×	48 0.8×	13	343
Ingrid Løvold Mostad Norway	11	273 1.5×	207 1.8×	121 1.1×	101 1.1×	83 1.5×	22	520
L Winstanley United Kingdom	5	193 1.0×	119 1.0×	44 0.4×	118 1.3×	48 0.8×	5	335
Lavinia Abedin Australia	7	310 1.6×	111 0.9×	74 0.7×	80 0.9×	70 1.2×	7	478

Countries citing papers authored by G. Riccardi

Since Specialization

Citations

This map shows the geographic impact of G. Riccardi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by G. Riccardi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Riccardi more than expected).

Fields of papers citing papers by G. Riccardi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. Riccardi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by G. Riccardi. The network helps show where G. Riccardi may publish in the future.

Co-authorship network of co-authors of G. Riccardi

This figure shows the co-authorship network connecting the top 25 collaborators of G. Riccardi. A scholar is included among the top collaborators of G. Riccardi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with G. Riccardi. G. Riccardi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

Meroño, Tomás, Raúl Zamora‐Ros, Agnetha Linn Rostgaard‐Hansen, et al.. (2024). Metabolome biomarkers linking dietary fibre intake with cardiometabolic effects: results from the Danish Diet, Cancer and Health-Next Generations MAX study. Food & Function. 15(3). 1643–1654. 5 indexed citations

Turco, Anna, Michele Guescini, Carlo Colosimo, et al.. (2013). Dietary fat differentially modulate the mRNA expression levels of oxidative mitochondrial genes in skeletal muscle of healthy subjects. Nutrition Metabolism and Cardiovascular Diseases. 24(2). 198–204. 2 indexed citations

Melis, Daniela, Roberto Della Casa, Alessandra Romano, et al.. (2008). Myasthenia gravis in a patient affected by glycogen storage disease type Ib: A further manifestation of an increased risk for autoimmune disorders?. Journal of Inherited Metabolic Disease. 31(S2). 227–231. 12 indexed citations

Nälsén, Cecilia, Bengt Vessby, Lars Berglund, et al.. (2006). Dietary (n-3) Fatty Acids Reduce Plasma F2-Isoprostanes but Not Prostaglandin F2α in Healthy Humans. Journal of Nutrition. 136(5). 1222–1228. 70 indexed citations

Rasmussen, Birthe M., Bengt Vessby, Matti Uusitupa, et al.. (2006). Effects of dietary saturated, monounsaturated, and n−3 fatty acids on blood pressure in healthy subjects. American Journal of Clinical Nutrition. 83(2). 221–226. 151 indexed citations

Annuzzi, Giovanni, Stefano Del Prato, Luca Benzi, et al.. (2001). Preprandial combination of lispro and NPH insulin improves overall blood glucose control in type 1 diabetic patients: a multicenter randomized crossover trial.. PubMed. 11(3). 168–75. 25 indexed citations

Parillo, M. & G. Riccardi. (1995). Dietary carbohydrates and glucose metabolism in diabetic patients.. PubMed. 21(6). 391–401. 7 indexed citations

Annuzzi, Giovanni, A.A. Rivellese, Brunella Capaldo, et al.. (1991). A controlled study on the effects of n − 3 fatty acids on lipid and glucose metabolism in non-insulin-dependent diabetic patients. Atherosclerosis. 87(1). 65–73. 83 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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