Diogo Jesús

933 total citations
30 papers, 515 citations indexed

About

Diogo Jesús is a scholar working on Rheumatology, Immunology and Molecular Biology. According to data from OpenAlex, Diogo Jesús has authored 30 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Rheumatology, 8 papers in Immunology and 5 papers in Molecular Biology. Recurrent topics in Diogo Jesús's work include Systemic Lupus Erythematosus Research (15 papers), Atherosclerosis and Cardiovascular Diseases (4 papers) and Pharmacological Effects of Natural Compounds (3 papers). Diogo Jesús is often cited by papers focused on Systemic Lupus Erythematosus Research (15 papers), Atherosclerosis and Cardiovascular Diseases (4 papers) and Pharmacological Effects of Natural Compounds (3 papers). Diogo Jesús collaborates with scholars based in Portugal, Italy and France. Diogo Jesús's co-authors include Luís Inês, José António Pereira da Silva, Andrea Doria, Maddalena Larosa, Luca Iaccarino, Margherita Zen, Ana Matos, Carla Henriques, Mariele Gatto and Elisabetta Zanatta and has published in prestigious journals such as Annals of the Rheumatic Diseases, Experimental Biology and Medicine and Frontiers in Pharmacology.

In The Last Decade

Diogo Jesús

27 papers receiving 507 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Diogo Jesús Portugal 12 362 202 87 79 51 30 515
Rasho Rashkov Bulgaria 12 250 0.7× 173 0.9× 47 0.5× 74 0.9× 50 1.0× 47 475
Румен Стоилов Bulgaria 12 287 0.8× 223 1.1× 50 0.6× 79 1.0× 45 0.9× 45 542
G. Schett Germany 12 257 0.7× 246 1.2× 61 0.7× 248 3.1× 89 1.7× 51 644
Haruka Tsuchiya Japan 14 188 0.5× 196 1.0× 40 0.5× 111 1.4× 52 1.0× 31 512
Thomas Grader‐Beck United States 13 146 0.4× 151 0.7× 37 0.4× 75 0.9× 88 1.7× 30 537
Gary V. Gordon United States 7 269 0.7× 80 0.4× 37 0.4× 63 0.8× 35 0.7× 13 421
Rahul Patel United States 9 213 0.6× 226 1.1× 38 0.4× 111 1.4× 39 0.8× 15 554
J Schedel Germany 12 136 0.4× 81 0.4× 29 0.3× 94 1.2× 41 0.8× 22 366
Christiane Reindl Germany 6 288 0.8× 341 1.7× 27 0.3× 67 0.8× 46 0.9× 7 581

Countries citing papers authored by Diogo Jesús

Since Specialization
Citations

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

Fields of papers citing papers by Diogo Jesús

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diogo Jesús

This figure shows the co-authorship network connecting the top 25 collaborators of Diogo Jesús. A scholar is included among the top collaborators of Diogo Jesús 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 Diogo Jesús. Diogo Jesús 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.
2.
Jesús, Diogo, Mariele Gatto, Margherita Zen, et al.. (2023). The SLE-DAS provides an accurate and feasible flare tool in the clinical setting: a validation study. Lara D. Veeken. 63(4). 1123–1129. 5 indexed citations
3.
Inês, Luís, et al.. (2023). What is the best instrument to measure disease activity in SLE? – SLE-DAS vs Easy BILAG. Autoimmunity Reviews. 23(1). 103428–103428. 11 indexed citations
4.
5.
Pires, Gabriel, et al.. (2022). A new error-monitoring brain–computer interface based on reinforcement learning for people with autism spectrum disorders. Journal of Neural Engineering. 19(6). 66032–66032. 10 indexed citations
6.
Jesús, Diogo, et al.. (2021). OP0293 OPTIMIZING A TOOL TO IDENTIFY LUPUS FLARES IN DAILY CLINICAL PRACTICE: SLE-DAS FLARE VERSUS SELENA FLARE INDEX. Annals of the Rheumatic Diseases. 80. 179–180. 1 indexed citations
7.
Larosa, Maddalena, N. Costedoat‐Chalumeau, G. Guettrot-Imbert, et al.. (2021). SLE-DAS in the First Trimester of Gestation Predicts Maternal Lupus Flares Later in Pregnancy. Frontiers in Pharmacology. 12. 660123–660123. 10 indexed citations
8.
Jesús, Diogo, Maddalena Larosa, Carla Henriques, et al.. (2021). Systemic Lupus Erythematosus Disease Activity Score (SLE-DAS) enables accurate and user-friendly definitions of clinical remission and categories of disease activity. Annals of the Rheumatic Diseases. 80(12). 1568–1574. 33 indexed citations
9.
Jesús, Diogo, et al.. (2021). High patient global assessment scores in patients with rheumatoid arthritis otherwise in remission do not reflect subclinical inflammation. Joint Bone Spine. 88(6). 105242–105242. 16 indexed citations
10.
Jesús, Diogo, Maddalena Larosa, Carla Henriques, et al.. (2021). Definition of low disease activity state based on the SLE-DAS: derivation and validation in a multicentre real-life cohort. Lara D. Veeken. 61(8). 3309–3316. 18 indexed citations
11.
Matteo, Andrea Di, Emilio Filippucci, Edoardo Cipolletta, et al.. (2019). Ultrasound and clinical features of hip involvement in patients with gout. Joint Bone Spine. 86(5). 633–636. 12 indexed citations
12.
Larosa, Maddalena, Margherita Zen, Mariele Gatto, et al.. (2019). IL-12 and IL-23/Th17 axis in systemic lupus erythematosus. Experimental Biology and Medicine. 244(1). 42–51. 75 indexed citations
13.
Jesús, Diogo, Ana Matos, Carla Henriques, et al.. (2019). Derivation and validation of the SLE Disease Activity Score (SLE-DAS): a new SLE continuous measure with high sensitivity for changes in disease activity. Annals of the Rheumatic Diseases. 78(3). 365–371. 96 indexed citations
14.
Jesús, Diogo, Ana Matos, Carla Henriques, et al.. (2019). THU0267 THE SLE DISEASE ACTIVITY SCORE (SLE-DAS) ENABLES ACCURATE DEFINITIONS OF SLE REMISSION AND LDA AS ACHIEVABLE TARGETS IN DISEASE MANAGEMENT. Annals of the Rheumatic Diseases. 78. 411–412. 2 indexed citations
15.
Araújo, Filipe, Alexandre Sepriano, Filipa Teixeira, et al.. (2018). The Portuguese Society of Rheumatology position paper on the use of biosimilars - 2017 update.. PubMed. 42(3). 219–228. 6 indexed citations
16.
Luís, Mariana, Diogo Jesús, Tânia Santiago, et al.. (2018). The many faces of IgG4-related disease: report of a case with inaugural recurrent aortic aneurism ruptures and literature review. Rheumatology International. 38(8). 1565–1570. 7 indexed citations
17.
Jesús, Diogo, et al.. (2017). Central nervous system vasculitis in systemic lupus erythematosus: a case series report in a tertiary referral centre. Lupus. 26(13). 1440–1447. 24 indexed citations
18.
Jesús, Diogo & Adekola O. Alao. (2013). 810 – Zolpidem-induced Galactorrhea Via Gabaergic Inhibition of Dopamine: a Case Report. European Psychiatry. 28(S1).
19.
Jean, Myriam, Mohamad‐Gabriel Alameh, Diogo Jesús, et al.. (2011). Chitosan-based therapeutic nanoparticles for combination gene therapy and gene silencing of in vitro cell lines relevant to type 2 diabetes. European Journal of Pharmaceutical Sciences. 45(1-2). 138–149. 64 indexed citations
20.
Clancy, R L, et al.. (1977). Characteristics of the Immune Response in a Patient with Whipple's Disease. Australian and New Zealand Journal of Medicine. 7(3). 294–298. 11 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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