Felipe Henriques

1.0k total citations
18 papers, 641 citations indexed

About

Felipe Henriques is a scholar working on Physiology, Epidemiology and Molecular Biology. According to data from OpenAlex, Felipe Henriques has authored 18 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Physiology, 12 papers in Epidemiology and 3 papers in Molecular Biology. Recurrent topics in Felipe Henriques's work include Adipose Tissue and Metabolism (16 papers), Adipokines, Inflammation, and Metabolic Diseases (11 papers) and Nutrition and Health in Aging (6 papers). Felipe Henriques is often cited by papers focused on Adipose Tissue and Metabolism (16 papers), Adipokines, Inflammation, and Metabolic Diseases (11 papers) and Nutrition and Health in Aging (6 papers). Felipe Henriques collaborates with scholars based in United States, Brazil and France. Felipe Henriques's co-authors include Michael Czech, Adı́lson Guilherme, Alexander H. Bedard, Miguél L. Batista, Mark Kelly, Batuhan Yenilmez, Rodrigo Xavier das Neves, Marília Seelaender, Jason K. Kim and Magno A. Lopes and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Felipe Henriques

18 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Felipe Henriques United States 15 431 227 207 79 68 18 641
Rea P. Anunciado‐Koza United States 11 424 1.0× 197 0.9× 197 1.0× 73 0.9× 62 0.9× 13 652
Anja Böhm Germany 16 350 0.8× 192 0.8× 292 1.4× 81 1.0× 44 0.6× 31 763
Jessica C. Hogan United States 8 417 1.0× 268 1.2× 252 1.2× 93 1.2× 54 0.8× 8 729
Montserrat Cairó Spain 14 496 1.2× 320 1.4× 215 1.0× 110 1.4× 80 1.2× 18 764
Olof Dallner United States 9 390 0.9× 227 1.0× 272 1.3× 77 1.0× 46 0.7× 11 697
Ruping Pan China 14 379 0.9× 198 0.9× 261 1.3× 117 1.5× 104 1.5× 19 818
Stine Ringholm Denmark 17 635 1.5× 262 1.2× 393 1.9× 54 0.7× 144 2.1× 26 926
David J. Pedersen Australia 12 379 0.9× 245 1.1× 277 1.3× 66 0.8× 66 1.0× 14 794
Cintia B. Ueta United States 12 276 0.6× 121 0.5× 143 0.7× 50 0.6× 50 0.7× 14 733
Cristina M. Zingaretti Italy 6 382 0.9× 182 0.8× 249 1.2× 136 1.7× 35 0.5× 6 594

Countries citing papers authored by Felipe Henriques

Since Specialization
Citations

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

Fields of papers citing papers by Felipe Henriques

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Felipe Henriques

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

All Works

18 of 18 papers shown
1.
Rowland, Leslie A., Adı́lson Guilherme, Felipe Henriques, et al.. (2023). De novo lipogenesis fuels adipocyte autophagosome and lysosome membrane dynamics. Nature Communications. 14(1). 1362–1362. 28 indexed citations
2.
Guilherme, Adı́lson, Leslie A. Rowland, Alexander H. Bedard, et al.. (2023). Acetyl-CoA carboxylase 1 is a suppressor of the adipocyte thermogenic program. Cell Reports. 42(5). 112488–112488. 14 indexed citations
3.
Picoli, Caroline C., Felipe Henriques, Magno A. Lopes, et al.. (2020). Resistance exercise training induces subcutaneous and visceral adipose tissue browning in Swiss mice. Journal of Applied Physiology. 129(1). 66–74. 23 indexed citations
4.
Guilherme, Adı́lson, Batuhan Yenilmez, Alexander H. Bedard, et al.. (2020). Control of Adipocyte Thermogenesis and Lipogenesis through β3-Adrenergic and Thyroid Hormone Signal Integration. Cell Reports. 31(5). 107598–107598. 40 indexed citations
5.
Henriques, Felipe, Alexander H. Bedard, Adı́lson Guilherme, et al.. (2020). Single-Cell RNA Profiling Reveals Adipocyte to Macrophage Signaling Sufficient to Enhance Thermogenesis. Cell Reports. 32(5). 107998–107998. 57 indexed citations
6.
7.
Guilherme, Adı́lson, Felipe Henriques, Alexander H. Bedard, & Michael Czech. (2019). Molecular pathways linking adipose innervation to insulin action in obesity and diabetes mellitus. Nature Reviews Endocrinology. 15(4). 207–225. 126 indexed citations
8.
Henriques, Felipe, Magno A. Lopes, Alexander H. Bedard, et al.. (2018). Toll-Like Receptor-4 Disruption Suppresses Adipose Tissue Remodeling and Increases Survival in Cancer Cachexia Syndrome. Scientific Reports. 8(1). 18024–18024. 34 indexed citations
9.
Guilherme, Adı́lson, David J. Pedersen, Felipe Henriques, et al.. (2018). Neuronal modulation of brown adipose activity through perturbation of white adipocyte lipogenesis. Molecular Metabolism. 16. 116–125. 29 indexed citations
10.
Lopes, Magno A., et al.. (2018). LLC tumor cells-derivated factors reduces adipogenesis in co-culture system. Heliyon. 4(7). e00708–e00708. 8 indexed citations
11.
Shen, Yuefei, Jessica Cohen, Sarah M. Nicoloro, et al.. (2018). CRISPR-delivery particles targeting nuclear receptor–interacting protein 1 (Nrip1) in adipose cells to enhance energy expenditure. Journal of Biological Chemistry. 293(44). 17291–17305. 47 indexed citations
12.
Guilherme, Adı́lson, David J. Pedersen, Elizabeth Henchey, et al.. (2017). Adipocyte lipid synthesis coupled to neuronal control of thermogenic programming. Molecular Metabolism. 6(8). 781–796. 47 indexed citations
13.
Moraes, Maria Nathália, Leonardo Vinícius Monteiro de Assis, Felipe Henriques, et al.. (2017). Cold-sensing TRPM8 channel participates in circadian control of the brown adipose tissue. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1864(12). 2415–2427. 28 indexed citations
14.
Henriques, Felipe, Rogério Antônio Laurato Sertié, Rodrigo Xavier das Neves, et al.. (2017). Early suppression of adipocyte lipid turnover induces immunometabolic modulation in cancer cachexia syndrome. The FASEB Journal. 31(5). 1976–1986. 15 indexed citations
15.
Lopes, Magno A., et al.. (2017). Cancer cachexia differentially regulates visceral adipose tissue turnover. Journal of Endocrinology. 232(3). 493–500. 12 indexed citations
16.
Preite, Nailliw Z., Cynthia R. Muller, Fabiana S. Evangelista, et al.. (2016). Disruption of beta3 adrenergic receptor increases susceptibility to DIO in mouse. Journal of Endocrinology. 231(3). 259–269. 26 indexed citations
17.
Peres, Sidney Barnabé, Felipe Henriques, Rogério Antônio Laurato Sertié, et al.. (2015). Pioglitazone Treatment Increases Survival and Prevents Body Weight Loss in Tumor–Bearing Animals: Possible Anti-Cachectic Effect. PLoS ONE. 10(3). e0122660–e0122660. 26 indexed citations
18.
Batista, Miguél L., Felipe Henriques, Rodrigo Xavier das Neves, et al.. (2015). Cachexia-associated adipose tissue morphological rearrangement in gastrointestinal cancer patients. Journal of Cachexia Sarcopenia and Muscle. 7(1). 37–47. 78 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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