John d’Aigle

945 total citations · 1 hit paper
16 papers, 636 citations indexed

About

John d’Aigle is a scholar working on Neurology, Molecular Biology and Immunology. According to data from OpenAlex, John d’Aigle has authored 16 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Neurology, 7 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in John d’Aigle's work include Neuroinflammation and Neurodegeneration Mechanisms (9 papers), Gut microbiota and health (4 papers) and Immune cells in cancer (3 papers). John d’Aigle is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (9 papers), Gut microbiota and health (4 papers) and Immune cells in cancer (3 papers). John d’Aigle collaborates with scholars based in United States and Puerto Rico. John d’Aigle's co-authors include Louise D. McCullough, Pedram Honarpisheh, Bhanu Priya Ganesh, Liang Zhu, Juneyoung Lee, Robert M. Bryan, David J. Durgan, Ahmad Hassan, Nagireddy Putluri and Louise Atadja and has published in prestigious journals such as Circulation Research, Stroke and American Journal Of Pathology.

In The Last Decade

John d’Aigle

14 papers receiving 627 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Gut Microbiota–Derived Short-Chain Fatty Acids Promote Poststroke Recovery in Aged Mice

2020 367 citations Juneyoung Lee, John d’Aigle et al. Circulation Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John d’Aigle United States	9	366	275	149	104	87	16	636
Monica Spychala United States	6	326 0.9×	246 0.9×	166 1.1×	108 1.0×	78 0.9×	9	651
Katarzyna Winek Germany	12	389 1.1×	314 1.1×	126 0.8×	74 0.7×	72 0.8×	21	711
Xiqun Zhu China	6	272 0.7×	200 0.7×	101 0.7×	110 1.1×	68 0.8×	8	617
Pedram Honarpisheh United States	15	609 1.7×	350 1.3×	277 1.9×	125 1.2×	161 1.9×	20	1.0k
Louise Atadja United States	4	283 0.8×	139 0.5×	124 0.8×	38 0.4×	51 0.6×	7	421
Congcong Sun China	15	413 1.1×	186 0.7×	171 1.1×	74 0.7×	45 0.5×	38	771
Meiyu Shang China	7	336 0.9×	121 0.4×	125 0.8×	38 0.4×	87 1.0×	13	622
Jingwen Ning China	7	336 0.9×	121 0.4×	125 0.8×	38 0.4×	87 1.0×	13	622
Mahmoud L. Soliman United States	11	314 0.9×	97 0.4×	183 1.2×	47 0.5×	116 1.3×	16	551
Xiaohang Qian China	11	363 1.0×	77 0.3×	241 1.6×	73 0.7×	148 1.7×	23	621

Countries citing papers authored by John d’Aigle

Since Specialization

Citations

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

Fields of papers citing papers by John d’Aigle

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John d’Aigle. 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 John d’Aigle. The network helps show where John d’Aigle may publish in the future.

Co-authorship network of co-authors of John d’Aigle

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

All Works

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16 of 16 papers shown

Ahnstedt, Hilda, Anthony Patrizz, Anjali Chauhan, et al.. (2020). Sex differences in T cell immune responses, gut permeability and outcome after ischemic stroke in aged mice. Brain Behavior and Immunity. 87. 556–567. 70 indexed citations

Honarpisheh, Pedram, Juneyoung Lee, Anik Banerjee, et al.. (2020). Potential caveats of putative microglia-specific markers for assessment of age-related cerebrovascular neuroinflammation. Journal of Neuroinflammation. 17(1). 366–366. 61 indexed citations

Chauhan, Anjali, Pedram Honarpisheh, Hilda Ahnstedt, et al.. (2020). Age-dependent involvement of gut mast cells and histamine in post-stroke inflammation. Journal of Neuroinflammation. 17(1). 160–160. 45 indexed citations

Honarpisheh, Pedram, Frank W. Blixt, John d’Aigle, et al.. (2020). Peripherally-sourced myeloid antigen presenting cells increase with advanced aging. Brain Behavior and Immunity. 90. 235–247. 16 indexed citations

Lee, Juneyoung, John d’Aigle, Louise Atadja, et al.. (2020). Gut Microbiota–Derived Short-Chain Fatty Acids Promote Poststroke Recovery in Aged Mice. Circulation Research. 127(4). 453–465. 367 indexed citations breakdown →

Honarpisheh, Pedram, John d’Aigle, Frank W. Blixt, et al.. (2020). Abstract TP108: Dendritic Cells Mediate the Detrimental Effects of Age-related Gut Dysbiosis After Stroke. Stroke. 51(Suppl_1). 1 indexed citations

d’Aigle, John, et al.. (2020). Lactoferrin reduces mycobacterial M1-type inflammation induced with trehalose 6,6′-dimycolate and facilitates the entry of fluoroquinolone into granulomas. Biochemistry and Cell Biology. 99(1). 73–80. 9 indexed citations

Howe, Matthew D., Yashasvee Munshi, Meaghan Roy-O’Reilly, et al.. (2019). Transforming growth factor-β promotes basement membrane fibrosis, alters perivascular cerebrospinal fluid distribution, and worsens neurological recovery in the aged brain after stroke. GeroScience. 41(5). 543–559. 31 indexed citations

d’Aigle, John, et al.. (2019). Mycobacterial Trehalose 6,6′-Dimycolate–Induced M1-Type Inflammation. American Journal Of Pathology. 190(2). 286–294. 12 indexed citations

10.

Koellhoffer, Edward C., John d’Aigle, Diego Morales‐Scheihing, & Louise D. McCullough. (2019). Abstract 23: Circulating Peripheral Factors Induce Age-Related Epigenetic Changes in Microglia Which Induces a Primed Phenotype. Stroke. 50(Suppl_1). 1 indexed citations

11.

d’Aigle, John, et al.. (2017). Social stress in early puberty has long-term impacts on impulsive action.. Behavioral Neuroscience. 131(3). 249–261. 8 indexed citations

12.

Zuo, Yan, John d’Aigle, Anjali Chauhan, & Jeffrey A. Frost. (2017). Genetic deletion of the Rho GEFNet1impairs mouse macrophage motility and actin cytoskeletal organization. Small GTPases. 11(4). 293–300. 7 indexed citations

13.

Koellhoffer, Edward C., Diego Morales‐Scheihing, John d’Aigle, & Louise D. McCullough. (2017). Abstract WP122: Heterochronic Parabiosis Reverses the Epigenetic Imbalance of the Aged Central Nervous System. Stroke. 48(suppl_1). 2 indexed citations

14.

Koellhoffer, Edward C., John d’Aigle, & Louise D. McCullough. (2017). Abstract WP101: Hypoxia Drives Anti-inflammatory Polarization of Microglia in Ischemic Stroke. Stroke. 48(suppl_1).

15.

d’Aigle, John. (2006). Human Immune System Simulation: A Survey of Current Approaches. 5 indexed citations

16.

d’Aigle, John, et al.. (1992). Modelling and training of artificial neural networks. 6(1). 7–20. 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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