Jaroslav Macášek

549 total citations
21 papers, 453 citations indexed

About

Jaroslav Macášek is a scholar working on Surgery, Nutrition and Dietetics and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Jaroslav Macášek has authored 21 papers receiving a total of 453 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Surgery, 7 papers in Nutrition and Dietetics and 6 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Jaroslav Macášek's work include Fatty Acid Research and Health (5 papers), Diet, Metabolism, and Disease (4 papers) and Pancreatitis Pathology and Treatment (4 papers). Jaroslav Macášek is often cited by papers focused on Fatty Acid Research and Health (5 papers), Diet, Metabolism, and Disease (4 papers) and Pancreatitis Pathology and Treatment (4 papers). Jaroslav Macášek collaborates with scholars based in Czechia. Jaroslav Macášek's co-authors include Zák A, Barbora Staňková, M. Zeman, Lucie Vávřová, Jana Kodydková, E Tvrzická, T Krechler, Roman Jirák, Marek Vecka and M Jáchymová and has published in prestigious journals such as Nutrition and Cancer, Clinical Biochemistry and Prostaglandins Leukotrienes and Essential Fatty Acids.

In The Last Decade

Jaroslav Macášek

21 papers receiving 440 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaroslav Macášek Czechia 10 120 95 76 68 66 21 453
Lucie Vávřová Czechia 11 140 1.2× 94 1.0× 74 1.0× 78 1.1× 42 0.6× 17 615
Vesna Stojiljković Serbia 11 173 1.4× 46 0.5× 73 1.0× 81 1.2× 36 0.5× 43 607
Amr M. Abbas Egypt 15 112 0.9× 45 0.5× 50 0.7× 125 1.8× 23 0.3× 32 600
Trine Henriksen Denmark 15 337 2.8× 111 1.2× 36 0.5× 142 2.1× 20 0.3× 25 777
Chuying Zhou China 19 303 2.5× 102 1.1× 80 1.1× 72 1.1× 47 0.7× 32 812
Ángel Ortega Colombia 11 145 1.2× 29 0.3× 23 0.3× 110 1.6× 33 0.5× 23 503
Mary S. Sutphin United States 14 173 1.4× 87 0.9× 57 0.8× 95 1.4× 27 0.4× 17 639
Chang-Nan Wang China 10 233 1.9× 63 0.7× 41 0.5× 85 1.3× 12 0.2× 14 514
Chih-Cheng Wu Taiwan 16 219 1.8× 37 0.4× 18 0.2× 65 1.0× 62 0.9× 37 723
Weina Chen United States 10 250 2.1× 27 0.3× 76 1.0× 121 1.8× 26 0.4× 16 827

Countries citing papers authored by Jaroslav Macášek

Since Specialization
Citations

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

Fields of papers citing papers by Jaroslav Macášek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaroslav Macášek

This figure shows the co-authorship network connecting the top 25 collaborators of Jaroslav Macášek. A scholar is included among the top collaborators of Jaroslav Macášek 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 Jaroslav Macášek. Jaroslav Macášek 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.
Macášek, Jaroslav, Barbora Staňková, Zák A, et al.. (2024). Associations of plasma phospholipid cis-vaccenic acid with insulin resistance markers in non-diabetic men with hyperlipidemia. Nutrition and Diabetes. 14(1). 73–73. 2 indexed citations
2.
Macášek, Jaroslav, M. Zeman, Zák A, Barbora Staňková, & Marek Vecka. (2021). Altered Indices of Fatty Acid Elongases ELOVL6, ELOVL5, and ELOVL2 Activities in Patients with Impaired Fasting Glycemia. Metabolic Syndrome and Related Disorders. 19(7). 386–392. 7 indexed citations
3.
Staňková, Barbora, Jaroslav Macášek, M. Zeman, et al.. (2019). Polymorphisms rs2167444 and rs508384 in the SCD1 Gene Are Linked with High ApoB-48 Levels and Adverse Profile of Cardiometabolic Risk Factors. Folia Biologica. 65(4). 159–169. 3 indexed citations
4.
Zeman, M., Marek Vecka, Michal Burda, et al.. (2017). Fatty Acid Composition of Plasma Phosphatidylcholine Determines Body Fat Parameters in Subjects with Metabolic Syndrome-Related Traits. Metabolic Syndrome and Related Disorders. 15(7). 371–378. 6 indexed citations
5.
A, Zák, E Tvrzická, M Jáchymová, et al.. (2017). [Desaturases of fatty acids (FADS) and their physiological and clinical implication].. PubMed. 155(2). 15–21. 6 indexed citations
6.
Zeman, M., Jaroslav Macášek, Michal Burda, et al.. (2016). Chronic pancreatitis and the composition of plasma phosphatidylcholine fatty acids. Prostaglandins Leukotrienes and Essential Fatty Acids. 108. 38–44. 11 indexed citations
7.
Vecka, Marek, M Jáchymová, Jaroslav Macášek, et al.. (2016). Osteopontin as a discriminating marker for pancreatic cancer and chronic pancreatitis. Cancer Biomarkers. 17(1). 55–65. 25 indexed citations
8.
Vávřová, Lucie, Jana Kodydková, M. Zeman, et al.. (2013). Altered Activities of Antioxidant Enzymes in Patients with Metabolic Syndrome. Obesity Facts. 6(1). 39–47. 40 indexed citations
9.
Kodydková, Jana, Lucie Vávřová, Barbora Staňková, et al.. (2013). Antioxidant Status and Oxidative Stress Markers in Pancreatic Cancer and Chronic Pancreatitis. Pancreas. 42(4). 614–621. 72 indexed citations
10.
Vecka, Marek, M Jáchymová, Lucie Vávřová, et al.. (2012). Paraoxonase-1 (PON1) Status in Pancreatic Cancer: Relation to Clinical Parameters. Folia Biologica. 58(6). 231–237. 14 indexed citations
11.
Macášek, Jaroslav, Marek Vecka, Zák A, et al.. (2012). Plasma Fatty Acid Composition in Patients with Pancreatic Cancer: Correlations to Clinical Parameters. Nutrition and Cancer. 64(7). 946–955. 40 indexed citations
12.
Vecka, Marek, Roman Jirák, E Tvrzická, et al.. (2012). Plasma fatty acid profile in depressive disorder resembles insulin resistance state.. PubMed. 33 Suppl 2. 83–6. 9 indexed citations
13.
Krechler, T, Jan Ulrych, M. Zeman, et al.. (2011). [Current status of pancreatic cancer diagnosis].. PubMed. 150(11). 587–93. 7 indexed citations
14.
Macášek, Jaroslav, M. Zeman, Marek Vecka, et al.. (2011). [Reactive oxygen and nitrogen species in the clinical medicine].. PubMed. 150(8). 423–32. 1 indexed citations
15.
Krechler, T, M. Zeman, Marek Vecka, et al.. (2010). Leptin and adiponectin in pancreatic cancer: connection with diabetes mellitus. Neoplasma. 58(1). 58–64. 31 indexed citations
16.
Zeman, M., Marek Vecka, Roman Jirák, et al.. (2010). MS256 FEATURES OF METABOLIC SYNDROME IN DEPRESSIVE DISORDER. Atherosclerosis Supplements. 11(2). 161–161. 1 indexed citations
17.
Zeman, M., Roman Jirák, Marek Vecka, et al.. (2010). MS247 LEPTIN, ADIPONECTIN AND LEPTIN TO ADIPONECTIN RATIO IN DEPRESSIVE WOMEN. Atherosclerosis Supplements. 11(2). 159–159. 5 indexed citations
18.
Kodydková, Jana, Lucie Vávřová, M. Zeman, et al.. (2009). Antioxidative enzymes and increased oxidative stress in depressive women. Clinical Biochemistry. 42(13-14). 1368–1374. 159 indexed citations
19.
Jirkovská, Marie, Jiřı́ Janáček, Tomáš Kučera, et al.. (2005). Three-dimensional reconstructions from non-deparaffinized tissue sections. Anatomy and Embryology. 210(3). 163–173. 11 indexed citations
20.
Macášek, Jaroslav, et al.. (2004). The Miami Red Blade: An Autonomous Lawn Mower. 390–400. 2 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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