David A. MacIntyre

9.2k total citations · 4 hit papers
105 papers, 5.0k citations indexed

About

David A. MacIntyre is a scholar working on Epidemiology, Microbiology and Immunology. According to data from OpenAlex, David A. MacIntyre has authored 105 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Epidemiology, 37 papers in Microbiology and 31 papers in Immunology. Recurrent topics in David A. MacIntyre's work include Preterm Birth and Chorioamnionitis (43 papers), Reproductive tract infections research (37 papers) and Reproductive System and Pregnancy (30 papers). David A. MacIntyre is often cited by papers focused on Preterm Birth and Chorioamnionitis (43 papers), Reproductive tract infections research (37 papers) and Reproductive System and Pregnancy (30 papers). David A. MacIntyre collaborates with scholars based in United Kingdom, United States and Australia. David A. MacIntyre's co-authors include Phillip R. Bennett, Yun Sok Lee, Julian R. Marchesi, T. Teoh, Ann Smith, Lynne Sykes, Maria Kyrgiou, Anita Mitra, Elaine Holmes and Lindsay Kindinger and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Nature Communications.

In The Last Decade

David A. MacIntyre

99 papers receiving 4.9k citations

Hit Papers

The vaginal microbiome during pregnancy and the postpartu... 2015 2026 2018 2022 2015 2015 2016 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David A. MacIntyre United Kingdom 36 2.6k 1.8k 1.4k 1.1k 811 105 5.0k
Peter Husslein Austria 43 2.3k 0.9× 919 0.5× 810 0.6× 1.3k 1.2× 2.0k 2.5× 275 7.6k
Cecilia Avila United States 26 2.8k 1.1× 416 0.2× 990 0.7× 1.7k 1.6× 1.5k 1.9× 50 5.7k
Chiara Azzari Italy 38 2.7k 1.0× 540 0.3× 387 0.3× 589 0.6× 524 0.6× 251 5.1k
Alan Bocking Canada 39 1.1k 0.4× 528 0.3× 478 0.3× 448 0.4× 654 0.8× 117 3.9k
Irina A. Buhimschi United States 47 2.5k 1.0× 297 0.2× 920 0.7× 1.3k 1.2× 2.2k 2.8× 272 7.4k
Suhas G. Kallapur United States 47 3.0k 1.2× 537 0.3× 609 0.4× 1.2k 1.1× 1.0k 1.2× 183 7.5k
Siobhan Sutcliffe United States 35 995 0.4× 517 0.3× 1.2k 0.8× 609 0.6× 422 0.5× 164 5.5k
Nardhy Gomez‐Lopez United States 51 4.1k 1.6× 542 0.3× 975 0.7× 4.1k 3.8× 2.9k 3.6× 210 8.4k
Marián Kacerovský Czechia 37 2.8k 1.1× 517 0.3× 251 0.2× 763 0.7× 1.8k 2.2× 217 4.2k
James D. Connor United States 45 3.3k 1.3× 350 0.2× 723 0.5× 371 0.3× 507 0.6× 152 6.1k

Countries citing papers authored by David A. MacIntyre

Since Specialization
Citations

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

Fields of papers citing papers by David A. MacIntyre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. MacIntyre. 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 David A. MacIntyre. The network helps show where David A. MacIntyre may publish in the future.

Co-authorship network of co-authors of David A. MacIntyre

This figure shows the co-authorship network connecting the top 25 collaborators of David A. MacIntyre. A scholar is included among the top collaborators of David A. MacIntyre 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 David A. MacIntyre. David A. MacIntyre 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
2.
Decout, Alexiane, Lauren A. Roberts, Julian R. Marchesi, et al.. (2024). Lactobacillus crispatus S-layer proteins modulate innate immune response and inflammation in the lower female reproductive tract. Nature Communications. 15(1). 10879–10879. 15 indexed citations
3.
Marchesi, Julian R., et al.. (2024). Microbial signatures and continuum in endometrial cancer and benign patients. Microbiome. 12(1). 118–118. 13 indexed citations
4.
Odendaal, Joshua, Naomi Black, Phillip R. Bennett, et al.. (2024). The endometrial microbiota and early pregnancy loss. Human Reproduction. 39(4). 638–646. 30 indexed citations
5.
6.
Corbett, Gillian A., Siobhan Corcoran, Conor Feehily, et al.. (2024). Preterm-birth-prevention with Lactobacillus crispatus oral probiotics: Protocol for a double blinded randomised placebo-controlled trial (the PrePOP study). Contemporary Clinical Trials. 149. 107776–107776. 2 indexed citations
7.
MacIntyre, David A., Denise Chan, Yun Jung Lee, et al.. (2023). ABO blood group antigens and preterm birth risk. Journal of Reproductive Immunology. 159. 104083–104083. 1 indexed citations
8.
Huang, Caizhi, Jennifer M. Fettweis, Betsy Foxman, et al.. (2023). Meta-analysis reveals the vaginal microbiome is a better predictor of earlier than later preterm birth. BMC Biology. 21(1). 199–199. 21 indexed citations
9.
Kalliala, Ilkka, Olivia Raglan, Sarah Bowden, et al.. (2022). Risk Factors for Ovarian Cancer: An Umbrella Review of the Literature. Cancers. 14(11). 2708–2708. 13 indexed citations
10.
Chan, Denise, Phillip R. Bennett, Yun Sok Lee, et al.. (2022). Microbial-driven preterm labour involves crosstalk between the innate and adaptive immune response. Nature Communications. 13(1). 975–975. 60 indexed citations
11.
Kundu, Samit, Sung Hye Kim, Asuka Inoue, et al.. (2022). Functional rewiring of G protein-coupled receptor signaling in human labor. Cell Reports. 40(10). 111318–111318. 6 indexed citations
12.
Haslam, Stuart M., Anne Dell, Ten Feizi, et al.. (2021). Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome. npj Biofilms and Microbiomes. 7(1). 49–49. 15 indexed citations
13.
Tzafetas, Menelaos, Anita Mitra, Maria Paraskevaidi, et al.. (2020). The intelligent knife (iKnife) and its intraoperative diagnostic advantage for the treatment of cervical disease. Proceedings of the National Academy of Sciences. 117(13). 7338–7346. 67 indexed citations
14.
Mitra, Anita, David A. MacIntyre, Ann Smith, et al.. (2020). The vaginal microbiota associates with the regression of untreated cervical intraepithelial neoplasia 2 lesions. Nature Communications. 11(1). 1999–1999. 148 indexed citations
15.
Kim, Sung Hye, David A. MacIntyre, Joanna R. Cook, et al.. (2020). Maternal plasma miRNAs as potential biomarkers for detecting risk of small-for-gestational-age births. EBioMedicine. 62. 103145–103145. 37 indexed citations
16.
Mahendru, Amita A., Giulia Masini, Abigail Fraser, et al.. (2018). Association Between Prepregnancy Cardiovascular Function and Subsequent Preeclampsia or Fetal Growth Restriction. Hypertension. 72(2). 442–450. 120 indexed citations
17.
Mitra, Anita, David A. MacIntyre, Vishakha Mahajan, et al.. (2017). Comparison of vaginal microbiota sampling techniques: cytobrush versus swab. Scientific Reports. 7(1). 9802–9802. 27 indexed citations
18.
Migale, Roberta, Bronwen Herbert, Yun Sok Lee, et al.. (2015). Specific Lipopolysaccharide Serotypes Induce Differential Maternal and Neonatal Inflammatory Responses in a Murine Model of Preterm Labor. American Journal Of Pathology. 185(9). 2390–2401. 65 indexed citations
19.
Jiménez, Beatriz, David A. MacIntyre, Rufus Cartwright, et al.. (2014). Hippuric acid: A Biomarker for Bladder Pain Syndrome.. Neurourology and Urodynamics. 1 indexed citations
20.
Bisits, Andrew, Roger Smith, Sam Mesiano, et al.. (2005). Inflammatory Aetiology of Human Myometrial Activation Tested Using Directed Graphs. PLoS Computational Biology. 1(2). e19–e19. 37 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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