Felipe Baeza‐Lehnert

1.5k total citations · 1 hit paper
16 papers, 1.1k citations indexed

About

Felipe Baeza‐Lehnert is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Felipe Baeza‐Lehnert has authored 16 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 3 papers in Physiology. Recurrent topics in Felipe Baeza‐Lehnert's work include Mitochondrial Function and Pathology (9 papers), Neuroscience and Neuropharmacology Research (9 papers) and Photoreceptor and optogenetics research (5 papers). Felipe Baeza‐Lehnert is often cited by papers focused on Mitochondrial Function and Pathology (9 papers), Neuroscience and Neuropharmacology Research (9 papers) and Photoreceptor and optogenetics research (5 papers). Felipe Baeza‐Lehnert collaborates with scholars based in Chile, Germany and United States. Felipe Baeza‐Lehnert's co-authors include L. Felipe Barros, Alejandro San Martín, Karin Alegría, Yasna Contreras‐Baeza, Rodrigo Lerchundi, Jillian L. Stobart, Bruno Weber, Matthias T. Wyss, Philipp Mächler and Ignacio Fernández‐Moncada and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Felipe Baeza‐Lehnert

15 papers receiving 1.1k citations

Hit Papers

In Vivo Evidence for a Lactate Gradient from Astrocytes t... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Felipe Baeza‐Lehnert Chile 12 606 428 221 192 146 16 1.1k
Rodrigo Lerchundi Chile 14 660 1.1× 454 1.1× 210 1.0× 206 1.1× 92 0.6× 20 1.1k
Alejandro San Martín Chile 14 894 1.5× 583 1.4× 289 1.3× 270 1.4× 204 1.4× 21 1.5k
Iván Ruminot Chile 17 635 1.0× 580 1.4× 227 1.0× 286 1.5× 61 0.4× 26 1.1k
Elmer Guzman United States 12 665 1.1× 254 0.6× 401 1.8× 219 1.1× 83 0.6× 14 1.2k
David A. Rempe United States 16 559 0.9× 503 1.2× 173 0.8× 284 1.5× 153 1.0× 20 1.2k
Ileana Lorenzini United States 13 710 1.2× 477 1.1× 194 0.9× 378 2.0× 72 0.5× 18 1.6k
Marcus Semtner Germany 19 461 0.8× 479 1.1× 130 0.6× 396 2.1× 70 0.5× 32 1.2k
Nadhim Bayatti United Kingdom 21 543 0.9× 471 1.1× 150 0.7× 136 0.7× 78 0.5× 30 1.3k
Rebecca Mongeon United States 8 548 0.9× 342 0.8× 151 0.7× 100 0.5× 57 0.4× 8 873

Countries citing papers authored by Felipe Baeza‐Lehnert

Since Specialization
Citations

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

Fields of papers citing papers by Felipe Baeza‐Lehnert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Felipe Baeza‐Lehnert. 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 Felipe Baeza‐Lehnert. The network helps show where Felipe Baeza‐Lehnert may publish in the future.

Co-authorship network of co-authors of Felipe Baeza‐Lehnert

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

All Works

16 of 16 papers shown
1.
Straub, Isabelle, Felipe Baeza‐Lehnert, Robert Renden, et al.. (2025). Presynaptic ATP Decreases During Physiological‐Like Activity in Neurons Tuned for High‐Frequency Transmission. Journal of Neurochemistry. 169(9). e70212–e70212.
2.
Schoknecht, Karl, Felipe Baeza‐Lehnert, Johannes Hirrlinger, Jens P. Dreier, & Jens Eilers. (2025). Spreading depolarizations exhaust neuronal ATP in a model of cerebral ischemia. Proceedings of the National Academy of Sciences. 122(19). e2415358122–e2415358122. 1 indexed citations
3.
Baeza‐Lehnert, Felipe, Leanne Noack, Andrea Lewen, et al.. (2025). Lactate Transport via Glial MCT1 and Neuronal MCT2 Is Not Required for Synchronized Synaptic Transmission in Hippocampal Slices Supplied With Glucose. Journal of Neurochemistry. 169(10). e70251–e70251. 1 indexed citations
4.
Kiwi, Miguel, et al.. (2023). Metabolic switch in the aging astrocyte supported via integrative approach comprising network and transcriptome analyses. Aging. 15(19). 9896–9912. 12 indexed citations
5.
Martín, Alejandro San, Robinson Arce‐Molina, Felipe Baeza‐Lehnert, et al.. (2022). Visualizing physiological parameters in cells and tissues using genetically encoded indicators for metabolites. Free Radical Biology and Medicine. 182. 34–58. 13 indexed citations
6.
Barros, L. Felipe, Alejandro San Martín, Iván Ruminot, et al.. (2020). Fluid Brain Glycolysis: Limits, Speed, Location, Moonlighting, and the Fates of Glycogen and Lactate. Neurochemical Research. 45(6). 1328–1334. 16 indexed citations
7.
Baeza‐Lehnert, Felipe, et al.. (2020). Monitoring Lactate Dynamics in Individual Macrophages with a Genetically Encoded Probe. Methods in molecular biology. 2184. 19–30. 1 indexed citations
8.
Barros, L. Felipe, Iván Ruminot, Alejandro San Martín, et al.. (2020). Aerobic Glycolysis in the Brain: Warburg and Crabtree Contra Pasteur. Neurochemical Research. 46(1). 15–22. 59 indexed citations
9.
Contreras‐Baeza, Yasna, Pamela Y. Sandoval, R.A. Alarcon, et al.. (2019). Monocarboxylate transporter 4 (MCT4) is a high affinity transporter capable of exporting lactate in high-lactate microenvironments. Journal of Biological Chemistry. 294(52). 20135–20147. 135 indexed citations
10.
Baeza‐Lehnert, Felipe, Aiman S. Saab, Ladina Hösli, et al.. (2018). Non-Canonical Control of Neuronal Energy Status by the Na+ Pump. Cell Metabolism. 29(3). 668–680.e4. 75 indexed citations
11.
Barros, L. Felipe, Alejandro San Martín, Iván Ruminot, et al.. (2017). Near‐critical GLUT1 and Neurodegeneration. Journal of Neuroscience Research. 95(11). 2267–2274. 34 indexed citations
12.
Mächler, Philipp, Matthias T. Wyss, Maha Elsayed, et al.. (2015). In Vivo Evidence for a Lactate Gradient from Astrocytes to Neurons. Cell Metabolism. 23(1). 94–102. 424 indexed citations breakdown →
13.
Lerchundi, Rodrigo, Ignacio Fernández‐Moncada, Yasna Contreras‐Baeza, et al.. (2015). NH4+ triggers the release of astrocytic lactate via mitochondrial pyruvate shunting. Proceedings of the National Academy of Sciences. 112(35). 11090–11095. 65 indexed citations
14.
Martín, Alejandro San, Sebastián Ceballo, Felipe Baeza‐Lehnert, et al.. (2014). Imaging Mitochondrial Flux in Single Cells with a FRET Sensor for Pyruvate. PLoS ONE. 9(1). e85780–e85780. 140 indexed citations
15.
Martín, Alejandro San, Tamara Sotelo-Hitschfeld, Rodrigo Lerchundi, et al.. (2014). Single-cell imaging tools for brain energy metabolism: a review. Neurophotonics. 1(1). 11004–11004. 44 indexed citations
16.
Barros, L. Felipe, Alejandro San Martín, Tamara Sotelo-Hitschfeld, et al.. (2013). Small is fast: astrocytic glucose and lactate metabolism at cellular resolution. Frontiers in Cellular Neuroscience. 7. 27–27. 49 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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