Joaquim Pombo

1.4k total citations
20 papers, 625 citations indexed

About

Joaquim Pombo is a scholar working on Pediatrics, Perinatology and Child Health, Physiology and Endocrine and Autonomic Systems. According to data from OpenAlex, Joaquim Pombo has authored 20 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Pediatrics, Perinatology and Child Health, 11 papers in Physiology and 5 papers in Endocrine and Autonomic Systems. Recurrent topics in Joaquim Pombo's work include Birth, Development, and Health (11 papers), Adipose Tissue and Metabolism (6 papers) and Diet, Metabolism, and Disease (4 papers). Joaquim Pombo is often cited by papers focused on Birth, Development, and Health (11 papers), Adipose Tissue and Metabolism (6 papers) and Diet, Metabolism, and Disease (4 papers). Joaquim Pombo collaborates with scholars based in United Kingdom, Serbia and Netherlands. Joaquim Pombo's co-authors include Paul Taylor, Lucilla Poston, Anne‐Maj Samuelsson, Jude A. Oben, Clive W. Coen, Junpei Soeda, Angelina Mouralidarane, Marco Novelli, Natalia Igosheva and Shona L. Kirk and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Genes & Development.

In The Last Decade

Joaquim Pombo

20 papers receiving 620 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joaquim Pombo United Kingdom 14 309 189 169 131 88 20 625
Mariusz Kuźmicki Poland 18 210 0.7× 162 0.9× 553 3.3× 226 1.7× 132 1.5× 43 982
Gai Liang China 13 296 1.0× 104 0.6× 93 0.6× 60 0.5× 164 1.9× 27 730
María Fernanda Garcés Colombia 16 117 0.4× 168 0.9× 156 0.9× 138 1.1× 81 0.9× 23 595
Surab Vadachkoria United States 12 338 1.1× 79 0.4× 553 3.3× 165 1.3× 133 1.5× 16 759
Ryan Faucette United States 8 279 0.9× 234 1.2× 90 0.5× 69 0.5× 305 3.5× 16 679
Maki Takemura Japan 11 351 1.1× 276 1.5× 250 1.5× 215 1.6× 49 0.6× 14 769
Bok-Ghee Han South Korea 10 146 0.5× 77 0.4× 158 0.9× 60 0.5× 204 2.3× 18 591
Frederick W. Anthony United Kingdom 15 560 1.8× 172 0.9× 401 2.4× 42 0.3× 165 1.9× 20 856
Andrée-Anne Houde Canada 12 429 1.4× 122 0.6× 377 2.2× 72 0.5× 409 4.6× 13 745
MarkéŽta Vaňkov‡á Czechia 15 87 0.3× 109 0.6× 118 0.7× 52 0.4× 125 1.4× 48 642

Countries citing papers authored by Joaquim Pombo

Since Specialization
Citations

This map shows the geographic impact of Joaquim Pombo'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 Joaquim Pombo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joaquim Pombo more than expected).

Fields of papers citing papers by Joaquim Pombo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joaquim Pombo. 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 Joaquim Pombo. The network helps show where Joaquim Pombo may publish in the future.

Co-authorship network of co-authors of Joaquim Pombo

This figure shows the co-authorship network connecting the top 25 collaborators of Joaquim Pombo. A scholar is included among the top collaborators of Joaquim Pombo 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 Joaquim Pombo. Joaquim Pombo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pombo, Joaquim, Bin Sun, Suchira Gallage, et al.. (2024). Detection of senescence using machine learning algorithms based on nuclear features. Nature Communications. 15(1). 1041–1041. 39 indexed citations
2.
Gallage, Suchira, Elaine E. Irvine, Jose Efren Barragan Avila, et al.. (2024). Ribosomal S6 kinase 1 regulates inflammaging via the senescence secretome. Nature Aging. 4(11). 1544–1561. 11 indexed citations
3.
Veland, Nicolás, Karen Brown, Alessandro Sardini, et al.. (2024). Bioluminescence imaging of Cyp1a1-luciferase reporter mice demonstrates prolonged activation of the aryl hydrocarbon receptor in the lung. Communications Biology. 7(1). 442–442. 2 indexed citations
4.
McHugh, Domhnall, Bin Sun, Carmen Gutiérrez‐Muñoz, et al.. (2023). COPI vesicle formation and N-myristoylation are targetable vulnerabilities of senescent cells. Nature Cell Biology. 25(12). 1804–1820. 26 indexed citations
5.
Innes, Andrew J., Bin Sun, Verena Wagner, et al.. (2021). XPO7 is a tumor suppressor regulating p21CIP1-dependent senescence. Genes & Development. 35(5-6). 379–391. 14 indexed citations
6.
7.
Naylor, M.N., Georgia Papacleovoulou, Émilie Stolarczyk, et al.. (2020). Supplementation with a prebiotic (polydextrose) in obese mouse pregnancy improves maternal glucose homeostasis and protects against offspring obesity. International Journal of Obesity. 44(12). 2382–2393. 16 indexed citations
8.
Pombo, Joaquim, et al.. (2018). Pravastatin therapy during preeclampsia prevents long-term adverse health effects in mice. JCI Insight. 3(8). 36 indexed citations
9.
10.
Maicas, Nuria, Joaquim Pombo, Hendrik Gremmels, et al.. (2017). Extravascular renal denervation ameliorates juvenile hypertension and renal damage resulting from experimental hyperleptinemia in rats. Journal of Hypertension. 35(12). 2537–2547. 12 indexed citations
11.
Cordero, Paúl, Jiawei Li, Vi Nguyen, et al.. (2017). Developmental Programming of Obesity and Liver Metabolism by Maternal Perinatal Nutrition Involves the Melanocortin System. Nutrients. 9(9). 1041–1041. 10 indexed citations
12.
Mullier, Amandine, Nuria Maicas, T. V. Novoselova, et al.. (2016). Central role for melanocortin-4 receptors in offspring hypertension arising from maternal obesity. Proceedings of the National Academy of Sciences. 113(43). 12298–12303. 32 indexed citations
13.
Soeda, Junpei, Angelina Mouralidarane, Paúl Cordero, et al.. (2016). Maternal obesity alters endoplasmic reticulum homeostasis in offspring pancreas. Journal of Physiology and Biochemistry. 72(2). 281–291. 24 indexed citations
14.
Mouralidarane, Angelina, Junpei Soeda, Shuvra Ray, et al.. (2014). Non-Alcoholic Fatty Pancreas Disease Pathogenesis: A Role for Developmental Programming and Altered Circadian Rhythms. PLoS ONE. 9(3). e89505–e89505. 38 indexed citations
15.
Mouralidarane, Angelina, Junpei Soeda, Anne‐Maj Samuelsson, et al.. (2013). Maternal obesity programs offspring nonalcoholic fatty liver disease by innate immune dysfunction in mice. Hepatology. 58(1). 128–138. 116 indexed citations
16.
Clark, Jane, Olena Rudyk, Michael J. Shattock, et al.. (2013). Experimental Hyperleptinemia in Neonatal Rats Leads to Selective Leptin Responsiveness, Hypertension, and Altered Myocardial Function. Hypertension. 62(3). 627–633. 38 indexed citations
17.
Matthews, Phillippa A., Anne‐Maj Samuelsson, Paul T. Seed, et al.. (2011). Fostering in mice induces cardiovascular and metabolic dysfunction in adulthood. The Journal of Physiology. 589(16). 3969–3981. 41 indexed citations
18.
Oben, Jude A., Angelina Mouralidarane, Phillippa A. Matthews, et al.. (2010). Maternal obesity programmes offspring development of non-alcoholic fatty pancreas disease. Biochemical and Biophysical Research Communications. 394(1). 24–28. 44 indexed citations
19.
Samuelsson, Anne‐Maj, Natalia Igosheva, Shona L. Kirk, et al.. (2009). Evidence for Sympathetic Origins of Hypertension in Juvenile Offspring of Obese Rats. Hypertension. 55(1). 76–82. 100 indexed citations
20.
Armitage, Jane, et al.. (2005). Offspring of rats fed saturated fat rich diet during pregnancy and suckling demonstrate programmed reductions in Na+, K+-ATPase activity. Pediatric Research. 58(5). 1041–1041. 1 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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