G. Sachse

1.1k total citations · 1 hit paper
19 papers, 792 citations indexed

About

G. Sachse is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Surgery. According to data from OpenAlex, G. Sachse has authored 19 papers receiving a total of 792 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Endocrinology, Diabetes and Metabolism and 6 papers in Surgery. Recurrent topics in G. Sachse's work include Metabolism, Diabetes, and Cancer (6 papers), Pancreatic function and diabetes (5 papers) and Diabetes Management and Research (4 papers). G. Sachse is often cited by papers focused on Metabolism, Diabetes, and Cancer (6 papers), Pancreatic function and diabetes (5 papers) and Diabetes Management and Research (4 papers). G. Sachse collaborates with scholars based in United Kingdom, Germany and Sweden. G. Sachse's co-authors include M Hanefeld, B. Willms, Frances M. Ashcroft, Roger Cox, Elizabeth Haythorne, Patrik Rorsman, Maria Rohm, Andrei I. Tarasov, Jeremy Sanderson and Mengdi Li and has published in prestigious journals such as Nature Communications, The Journal of Physiology and Diabetes.

In The Last Decade

G. Sachse

16 papers receiving 766 citations

Hit Papers

Diabetes causes marked inhibition of mitochondrial metabo... 2019 2026 2021 2023 2019 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. Sachse United Kingdom 10 408 210 209 168 124 19 792
Elaine Hillas United States 13 286 0.7× 116 0.6× 486 2.3× 115 0.7× 104 0.8× 21 961
Chintan N. Koyani Austria 14 403 1.0× 114 0.5× 163 0.8× 86 0.5× 42 0.3× 19 830
Caterina Constantinou Greece 16 287 0.7× 103 0.5× 170 0.8× 139 0.8× 36 0.3× 32 636
Traci E. LaMoia United States 6 391 1.0× 144 0.7× 198 0.9× 141 0.8× 34 0.3× 8 690
Hong Du China 14 354 0.9× 113 0.5× 109 0.5× 148 0.9× 34 0.3× 35 714
C R Kahn United States 10 538 1.3× 160 0.8× 131 0.6× 349 2.1× 30 0.2× 13 901
Denis Blache France 14 177 0.4× 174 0.8× 171 0.8× 100 0.6× 32 0.3× 21 642
Daniela Tomie Furuya Brazil 13 196 0.5× 120 0.6× 100 0.5× 144 0.9× 25 0.2× 16 476
Inmaculada Ruz‐Maldonado United Kingdom 15 355 0.9× 278 1.3× 253 1.2× 213 1.3× 168 1.4× 21 740
Abass M. Conteh United States 14 158 0.4× 175 0.8× 121 0.6× 85 0.5× 51 0.4× 22 490

Countries citing papers authored by G. Sachse

Since Specialization
Citations

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

Fields of papers citing papers by G. Sachse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Sachse

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

All Works

19 of 19 papers shown
1.
Sachse, G., Nikolaos Pagonas, Philipp Hillmeister, et al.. (2025). Calpain Inhibition in a Transgenic Model of Calpastatin Overexpression Facilitates Reversal of Myocardial Hypertrophy. ESC Heart Failure. 12(3). 2256–2266.
2.
Haythorne, Elizabeth, John Walsby-Tickle, Andrei I. Tarasov, et al.. (2022). Altered glycolysis triggers impaired mitochondrial metabolism and mTORC1 activation in diabetic β-cells. Nature Communications. 13(1). 6754–6754. 64 indexed citations
3.
Sachse, G., Elizabeth Haythorne, Thomas G. Hill, et al.. (2021). The KCNJ11-E23K Gene Variant Hastens Diabetes Progression by Impairing Glucose-Induced Insulin Secretion. Diabetes. 70(5). 1145–1156. 13 indexed citations
4.
Haythorne, Elizabeth, Maria Rohm, Martijn van de Bunt, et al.. (2019). Diabetes causes marked inhibition of mitochondrial metabolism in pancreatic β-cells. Nature Communications. 10(1). 2474–2474. 244 indexed citations breakdown →
5.
Sachse, G., et al.. (2019). Systematisierung und Standardisierung manueller Untersuchungs- und Behandlungstechniken. Manuelle Medizin. 57(5). 341–347. 1 indexed citations
6.
Sachse, G., Chris Church, Michelle Stewart, et al.. (2017). FTO demethylase activity is essential for normal bone growth and bone mineralization in mice. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1864(3). 843–850. 25 indexed citations
7.
Proks, Peter, et al.. (2016). Running out of time: the decline of channel activity and nucleotide activation in adenosine triphosphate-sensitive K-channels. Philosophical Transactions of the Royal Society B Biological Sciences. 371(1700). 20150426–20150426. 10 indexed citations
8.
Merkestein, Myrte, Samantha Laber, Fiona McMurray, et al.. (2015). FTO influences adipogenesis by regulating mitotic clonal expansion. Nature Communications. 6(1). 6792–6792. 194 indexed citations
9.
O’Çonnell, Susan, Peter Proks, Holger Kramer, et al.. (2015). The value of in vitro studies in a case of neonatal diabetes with a novel Kir6.2‐W68G mutation. Clinical Case Reports. 3(10). 884–887. 3 indexed citations
10.
Sachse, G., Jörg Faulhaber, Anika Seniuk, Heimo Ehmke, & Olaf Pongs. (2014). Smooth muscle BK channel activity influences blood pressure independent of vascular tone in mice. The Journal of Physiology. 592(12). 2563–2574. 16 indexed citations
11.
Sachse, G., Elana Maser, & K. Federlin. (2008). Kombinationstherapie mit Insulin und Sulfonylharnstoffen bei Sekundärversagen der Sulfonylharnstofftherapie?. DMW - Deutsche Medizinische Wochenschrift. 109(11). 419–421. 1 indexed citations
12.
Sachse, G., et al.. (2008). Langzeittherapie mit Humaninsulin: Klinische Erfahrungen. DMW - Deutsche Medizinische Wochenschrift. 110(11). 403–406.
13.
Hanefeld, M & G. Sachse. (2002). The effects of orlistat on body weight and glycaemic control in overweight patients with type 2 diabetes: a randomized, placebo‐controlled trial. Diabetes Obesity and Metabolism. 4(6). 415–423. 115 indexed citations
14.
Sachse, G., et al.. (1985). Continuous subcutaneous insulin infusion therapy (CSII) influences cardiovascular responses to graded exercise in patients with autonomic diabetic neuropathy of the cardiovascular system (ADNCS).. PubMed. 3 Suppl 1. 530–4. 1 indexed citations
15.
Sachse, G., et al.. (1981). Effect of Glucose and Arginine on L-Enkephalin Secretion of the Isolated Perfused Rat Pancreas. Hormone and Metabolic Research. 13(6). 360–360. 1 indexed citations
16.
Sachse, G. & H. Laube. (1980). Leucin-Enkephalin Plasma Levels after an Oral or Intravenous Arginine Stimulation in Rats. Hormone and Metabolic Research. 12(8). 416–417. 4 indexed citations
17.
Sachse, G. & B. Willms. (1980). Efficacy of thioctic acid in the therapy of peripheral diabetic neuropathy.. PubMed. 9. 105–7. 35 indexed citations
18.
Sachse, G., B. Willms, & R. H. A. Becker. (1979). [Interaction between naproxen and tolbutamide on metabolism in diabetics].. PubMed. 29(5). 835–6. 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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