Matthew Triolo

1.1k total citations · 1 hit paper
15 papers, 780 citations indexed

About

Matthew Triolo is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Matthew Triolo has authored 15 papers receiving a total of 780 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Physiology and 8 papers in Epidemiology. Recurrent topics in Matthew Triolo's work include Muscle Physiology and Disorders (9 papers), Autophagy in Disease and Therapy (8 papers) and Adipose Tissue and Metabolism (8 papers). Matthew Triolo is often cited by papers focused on Muscle Physiology and Disorders (9 papers), Autophagy in Disease and Therapy (8 papers) and Adipose Tissue and Metabolism (8 papers). Matthew Triolo collaborates with scholars based in Canada, United States and Italy. Matthew Triolo's co-authors include David A. Hood, Ashley N. Oliveira, Jonathan M. Memme, Yuho Kim, Avigail T. Erlich, Rita Kumari, Mireille Khacho, Kaitlyn Beyfuss, Nicole M. Baker and Michael A. Rudnicki and has published in prestigious journals such as The Journal of Physiology, Scientific Reports and Journal of Applied Physiology.

In The Last Decade

Matthew Triolo

15 papers receiving 773 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.

Maintenance of Skeletal Muscle Mitochondria in Health, Exercise, and Aging

2018 387 citations David A. Hood, Jonathan M. Memme et al. Annual Review of Physiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Triolo Canada	10	508	430	183	118	80	15	780
Ashley N. Oliveira Canada	10	404 0.8×	396 0.9×	138 0.8×	138 1.2×	85 1.1×	17	675
Heather N. Carter Canada	9	434 0.9×	405 0.9×	179 1.0×	127 1.1×	73 0.9×	9	661
Jonathan M. Memme Canada	11	520 1.0×	515 1.2×	150 0.8×	179 1.5×	113 1.4×	15	882
Avigail T. Erlich Canada	11	478 0.9×	451 1.0×	248 1.4×	139 1.2×	114 1.4×	13	793
Marion Pauly Canada	10	457 0.9×	331 0.8×	227 1.2×	88 0.7×	67 0.8×	15	672
Jens Frey Halling Denmark	14	572 1.1×	425 1.0×	179 1.0×	93 0.8×	89 1.1×	19	1.0k
Liam D. Tryon Canada	8	343 0.7×	351 0.8×	157 0.9×	113 1.0×	105 1.3×	10	572
Giulia Uguccioni Canada	8	399 0.8×	380 0.9×	88 0.5×	103 0.9×	91 1.1×	8	581
Julianna Huang Canada	5	456 0.9×	408 0.9×	82 0.4×	139 1.2×	71 0.9×	7	603
Linda M.‐D. Nguyen United States	8	350 0.7×	371 0.9×	76 0.4×	92 0.8×	80 1.0×	13	656

Countries citing papers authored by Matthew Triolo

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Triolo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Triolo

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

All Works

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15 of 15 papers shown

Triolo, Matthew & Mireille Khacho. (2024). Protocol to monitor live-cell, real-time, mitochondrial respiration in mouse muscle cells using the Resipher platform. STAR Protocols. 5(4). 103330–103330. 1 indexed citations

Triolo, Matthew, et al.. (2024). Optic atrophy 1 mediates muscle differentiation by promoting a metabolic switch via the supercomplex assembly factor SCAF1. iScience. 27(3). 109164–109164. 6 indexed citations

Picca, Anna, Matthew Triolo, Stephanie E. Wohlgemuth, et al.. (2023). Relationship between Mitochondrial Quality Control Markers, Lower Extremity Tissue Composition, and Physical Performance in Physically Inactive Older Adults. Cells. 12(1). 183–183. 18 indexed citations

Triolo, Matthew, et al.. (2023). Evaluating mitochondrial length, volume, and cristae ultrastructure in rare mouse adult stem cell populations. STAR Protocols. 4(1). 102107–102107. 4 indexed citations

Vainshtein, Anna, Arthur J. Cheng, Jonathan M. Memme, et al.. (2022). Scientific meeting report: International Biochemistry of Exercise 2022. Journal of Applied Physiology. 133(6). 1381–1393. 1 indexed citations

Triolo, Matthew, et al.. (2022). Time‐dependent changes in autophagy, mitophagy and lysosomes in skeletal muscle during denervation‐induced disuse. The Journal of Physiology. 600(7). 1683–1701. 32 indexed citations

Triolo, Matthew, Ashley N. Oliveira, Rita Kumari, & David A. Hood. (2022). The influence of age, sex, and exercise on autophagy, mitophagy, and lysosome biogenesis in skeletal muscle. Skeletal Muscle. 12(1). 13–13. 44 indexed citations

Baker, Nicole M., Matthew Triolo, Sarah Larrigan, et al.. (2022). The mitochondrial protein OPA1 regulates the quiescent state of adult muscle stem cells. Cell stem cell. 29(9). 1315–1332.e9. 55 indexed citations

Triolo, Matthew, Debasmita Bhattacharya, & David A. Hood. (2022). Denervation induces mitochondrial decline and exacerbates lysosome dysfunction in middle-aged mice. Aging. 14(22). 8900–8913. 2 indexed citations

10.

Triolo, Matthew & David A. Hood. (2021). Manifestations of Age on Autophagy, Mitophagy and Lysosomes in Skeletal Muscle. Cells. 10(5). 1054–1054. 36 indexed citations

11.

Triolo, Matthew & David A. Hood. (2018). Mitochondrial breakdown in skeletal muscle and the emerging role of the lysosomes. Archives of Biochemistry and Biophysics. 661. 66–73. 28 indexed citations

12.

Kim, Yuho, Matthew Triolo, Avigail T. Erlich, & David A. Hood. (2018). Regulation of autophagic and mitophagic flux during chronic contractile activity-induced muscle adaptations. Pflügers Archiv - European Journal of Physiology. 471(3). 431–440. 26 indexed citations

13.

Beyfuss, Kaitlyn, Avigail T. Erlich, Matthew Triolo, & David A. Hood. (2018). The Role of p53 in Determining Mitochondrial Adaptations to Endurance Training in Skeletal Muscle. Scientific Reports. 8(1). 14710–14710. 27 indexed citations

14.

Hood, David A., Jonathan M. Memme, Ashley N. Oliveira, & Matthew Triolo. (2018). Maintenance of Skeletal Muscle Mitochondria in Health, Exercise, and Aging. Annual Review of Physiology. 81(1). 19–41. 387 indexed citations breakdown →

15.

Kim, Yuho, Matthew Triolo, & David A. Hood. (2017). Impact of Aging and Exercise on Mitochondrial Quality Control in Skeletal Muscle. Oxidative Medicine and Cellular Longevity. 2017(1). 3165396–3165396. 113 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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