Maxime Nachit

1.0k total citations
21 papers, 760 citations indexed

About

Maxime Nachit is a scholar working on Physiology, Epidemiology and Hepatology. According to data from OpenAlex, Maxime Nachit has authored 21 papers receiving a total of 760 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Physiology, 13 papers in Epidemiology and 5 papers in Hepatology. Recurrent topics in Maxime Nachit's work include Nutrition and Health in Aging (13 papers), Liver Disease Diagnosis and Treatment (12 papers) and Liver Disease and Transplantation (3 papers). Maxime Nachit is often cited by papers focused on Nutrition and Health in Aging (13 papers), Liver Disease Diagnosis and Treatment (12 papers) and Liver Disease and Transplantation (3 papers). Maxime Nachit collaborates with scholars based in Belgium, France and Switzerland. Maxime Nachit's co-authors include Isabelle Leclercq, Jean‐Paul Thissen, Pierre Tréfois, Audrey Loumaye, Aline van Maanen, Marie de Barsy, Damien Gruson, Pascale Lause, Yves Horsmans and Laure B. Bindels and has published in prestigious journals such as Nature Communications, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.

In The Last Decade

Maxime Nachit

21 papers receiving 753 citations

Peers

Maxime Nachit

PHYSI

EPIDE

HEPAT

SURGE

A Austin United States

Jinyu Shi China

Hideko Ohama Japan

Jiro Nishida Japan

Dan‐Qin Sun China

Miyuki Yokoyama Japan

Michael Festersen Nielsen Denmark

Yasuhiro Sakaguchi Japan

Jung Sik Park South Korea

Alexander Hodge Australia

A Austin United States

Maxime Nachit

143 ×0.3

PHYSI

569 ×1.8

EPIDE

212 ×0.8

195 ×1.7

HEPAT

136 ×1.8

SURGE

Citations per year, relative to Maxime Nachit Maxime Nachit (= 1×) peers A Austin

Countries citing papers authored by Maxime Nachit

Since Specialization

Citations

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

Fields of papers citing papers by Maxime Nachit

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxime Nachit

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

All Works

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20 of 20 papers shown

Nachit, Maxime, Marco Dioguardi Burgio, Anton Abyzov, et al.. (2023). Hepatocellular carcinoma in patients with non-alcoholic fatty liver disease is associated with heterogeneous pattern of fat infiltration in skeletal muscles. European Radiology. 34(3). 1461–1470. 3 indexed citations

Nachit, Maxime, Christopher Montemagno, Mitra Ahmadi, et al.. (2023). Molecular imaging of liver inflammation using an anti-VCAM-1 nanobody. Nature Communications. 14(1). 19 indexed citations

Nachit, Maxime, Yves Horsmans, Ronald M. Summers, Isabelle Leclercq, & Perry J. Pickhardt. (2023). AI-based CT Body Composition Identifies Myosteatosis as Key Mortality Predictor in Asymptomatic Adults. Radiology. 307(5). e222008–e222008. 59 indexed citations

Nachit, Maxime, et al.. (2022). Impact of L-ornithine L-aspartate on non-alcoholic steatohepatitis-associated hyperammonemia and muscle alterations. Frontiers in Nutrition. 9. 1051157–1051157. 11 indexed citations

Carrizosa, María A. Davis‐López de, Maxime Nachit, Nicolas Dubuisson, et al.. (2022). AdipoRon enhances healthspan in middle‐aged obese mice: striking alleviation of myosteatosis and muscle degenerative markers. Journal of Cachexia Sarcopenia and Muscle. 14(1). 464–478. 26 indexed citations

Nachit, Maxime, Wilhelmus J. Kwanten, Jean‐Paul Thissen, et al.. (2021). Muscle fat content is strongly associated with NASH: A longitudinal study in patients with morbid obesity. Journal of Hepatology. 75(2). 292–301. 77 indexed citations

Lanthier, Nicolas, Julie Rodriguez, Maxime Nachit, et al.. (2021). Publisher Correction: Microbiota analysis and transient elastography reveal new extra-hepatic components of liver steatosis and fibrosis in obese patients. Scientific Reports. 11(1). 6123–6123. 4 indexed citations

Nachit, Maxime, Nicolas Lanthier, Julie Rodriguez, et al.. (2021). A dynamic association between myosteatosis and liver stiffness: Results from a prospective interventional study in obese patients. JHEP Reports. 3(4). 100323–100323. 33 indexed citations

Gillard, Justine, Laure‐Alix Clerbaux, Maxime Nachit, et al.. (2021). Bile acids contribute to the development of non-alcoholic steatohepatitis in mice. JHEP Reports. 4(1). 100387–100387. 70 indexed citations

10.

Lanthier, Nicolas, Julie Rodriguez, Maxime Nachit, et al.. (2021). Microbiota analysis and transient elastography reveal new extra-hepatic components of liver steatosis and fibrosis in obese patients. Scientific Reports. 11(1). 659–659. 43 indexed citations

11.

Nachit, Maxime, Yves Horsmans, & Isabelle Leclercq. (2021). Rationale of adding muscle volume to muscle fat infiltration in the definition of an adverse muscle composition is unclear. JHEP Reports. 3(2). 100235–100235. 2 indexed citations

12.

Tréfois, Pierre, Maxime Nachit, Ralph Crott, et al.. (2020). Non-invasive Quantification of Fat Deposits in Skeletal Muscle Predicts Cardiovascular Outcome in Kidney Failure. Frontiers in Physiology. 11. 130–130. 26 indexed citations

13.

Lanthier, Nicolas, Julie Rodriguez, Maxime Nachit, et al.. (2020). New determinants of liver steatosis and fibrosis in obese patients: results of a prospective clinical study. Clinical Nutrition ESPEN. 40. 438–439. 1 indexed citations

14.

Nachit, Maxime, Jean‐Paul Thissen, Olivier Schakman, et al.. (2020). Myosteatosis rather than sarcopenia associates with non‐alcoholic steatohepatitis in non‐alcoholic fatty liver disease preclinical models. Journal of Cachexia Sarcopenia and Muscle. 12(1). 144–158. 50 indexed citations

15.

Bouzin, Caroline, et al.. (2019). Automated computerized image analysis for the user-independent evaluation of disease severity in preclinical models of NAFLD/NASH. Laboratory Investigation. 100(1). 147–160. 41 indexed citations

16.

Nachit, Maxime, Greetje Vande Velde, Wilhelmus J. Kwanten, et al.. (2019). NON-INVASIVE DETECTION OF MYOSTEATOSIS AS A TOOL TO PREDICT NASH IN THE CONTEXT OF METABOLIC SYNDROME AND OBESITY. 70. 1 indexed citations

17.

Nachit, Maxime & Isabelle Leclercq. (2019). Emerging awareness on the importance of skeletal muscle in liver diseases: time to dig deeper into mechanisms!. Clinical Science. 133(3). 465–481. 57 indexed citations

18.

Loumaye, Audrey, Marie de Barsy, Maxime Nachit, et al.. (2017). Circulating Activin A predicts survival in cancer patients. Journal of Cachexia Sarcopenia and Muscle. 8(5). 768–777. 64 indexed citations

19.

Loumaye, Audrey, Marie de Barsy, Maxime Nachit, et al.. (2016). Circulating Activin A is predictive of survival of cancer patients. Nutrition Clinique et Métabolisme. 30(1). 62–63. 1 indexed citations

20.

Loumaye, Audrey, Marie de Barsy, Maxime Nachit, et al.. (2015). Role of Activin A and Myostatin in Human Cancer Cachexia. The Journal of Clinical Endocrinology & Metabolism. 100(5). 2030–2038. 166 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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