Daniel Pisera

1.4k total citations
59 papers, 1.2k citations indexed

About

Daniel Pisera is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Reproductive Medicine. According to data from OpenAlex, Daniel Pisera has authored 59 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Endocrinology, Diabetes and Metabolism, 21 papers in Molecular Biology and 17 papers in Reproductive Medicine. Recurrent topics in Daniel Pisera's work include Growth Hormone and Insulin-like Growth Factors (23 papers), Hypothalamic control of reproductive hormones (16 papers) and Stress Responses and Cortisol (12 papers). Daniel Pisera is often cited by papers focused on Growth Hormone and Insulin-like Growth Factors (23 papers), Hypothalamic control of reproductive hormones (16 papers) and Stress Responses and Cortisol (12 papers). Daniel Pisera collaborates with scholars based in Argentina, United States and France. Daniel Pisera's co-authors include Adriana Seilicovich, Gabriela Jaita, Jimena Ferraris, Mercedes Lasaga, Marianela Candolfi, Verónica Zaldivar, B. Duvilanski, Valéria Rettori, María Susana Theas and Beatriz H. Duvilanski and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.

In The Last Decade

Daniel Pisera

58 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Pisera Argentina 21 423 329 231 192 182 59 1.2k
D.A. Leong United States 24 597 1.4× 524 1.6× 196 0.8× 178 0.9× 447 2.5× 36 1.6k
William J. DeVito United States 20 344 0.8× 295 0.9× 79 0.3× 98 0.5× 140 0.8× 52 986
M. Motta Italy 23 472 1.1× 420 1.3× 73 0.3× 433 2.3× 463 2.5× 73 1.5k
Françoise Mounier France 18 278 0.7× 340 1.0× 134 0.6× 79 0.4× 77 0.4× 38 1.0k
A. Bartke United States 23 627 1.5× 467 1.4× 655 2.8× 285 1.5× 163 0.9× 49 1.7k
Judith L. Turgeon United States 18 418 1.0× 242 0.7× 65 0.3× 444 2.3× 326 1.8× 35 1.0k
Willhart Knepel Germany 26 289 0.7× 651 2.0× 98 0.4× 211 1.1× 86 0.5× 58 1.5k
Amal K. Mukhopadhyay Germany 25 401 0.9× 846 2.6× 147 0.6× 256 1.3× 426 2.3× 69 2.0k
Estelle Louiset France 25 1.1k 2.5× 750 2.3× 100 0.4× 153 0.8× 78 0.4× 97 2.1k
Miklós Sárvári Hungary 15 131 0.3× 202 0.6× 94 0.4× 152 0.8× 100 0.5× 27 658

Countries citing papers authored by Daniel Pisera

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Pisera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Pisera

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Pisera. A scholar is included among the top collaborators of Daniel Pisera 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 Daniel Pisera. Daniel Pisera 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.
Asad, Antonela S., et al.. (2020). Anterior pituitary gland synthesises dopamine from l ‐3,4‐dihydroxyphenylalanine ( l ‐dopa). Journal of Neuroendocrinology. 32(7). e12885–e12885. 4 indexed citations
2.
Asad, Antonela S., Alejandro J. Nicola Candia, Nazareno González, et al.. (2019). Prolactin and its receptor as therapeutic targets in glioblastoma multiforme. Scientific Reports. 9(1). 19578–19578. 17 indexed citations
3.
Jaita, Gabriela, et al.. (2015). Estradiol Upregulates c-FLIPlong Expression in Anterior Pituitary Cells. Hormone and Metabolic Research. 48(4). 275–279. 1 indexed citations
4.
Zaldivar, Verónica, Sandra Zárate, Gabriela Jaita, et al.. (2011). Estradiol Increases the Expression of TNF-α and TNF Receptor 1 in Lactotropes. Neuroendocrinology. 93(2). 106–113. 16 indexed citations
5.
Ferraris, Jimena, Daniela Radl, Sandra Zárate, et al.. (2011). N-Terminal Prolactin-Derived Fragments, Vasoinhibins, Are Proapoptoptic and Antiproliferative in the Anterior Pituitary. PLoS ONE. 6(7). e21806–e21806. 11 indexed citations
6.
Radl, Daniela, et al.. (2011). Dopamine-Induced Apoptosis of Lactotropes Is Mediated by the Short Isoform of D2 Receptor. PLoS ONE. 6(3). e18097–e18097. 35 indexed citations
7.
Seilicovich, Adriana, Daniel Pisera, Sandra A. Sciascia, et al.. (2005). Gene Therapy for Pituitary Tumors. Current Gene Therapy. 5(6). 559–572. 5 indexed citations
8.
Candolfi, Marianela, Gabriela Jaita, Verónica Zaldivar, et al.. (2004). Progesterone Antagonizes the Permissive Action of Estradiol on Tumor Necrosis Factor-α-Induced Apoptosis of Anterior Pituitary Cells. Endocrinology. 146(2). 736–743. 35 indexed citations
9.
Pisera, Daniel, Marianela Candolfi, Sandra Navarra, et al.. (2004). Estrogens sensitize anterior pituitary gland to apoptosis. American Journal of Physiology-Endocrinology and Metabolism. 287(4). E767–E771. 34 indexed citations
10.
Candolfi, Marianela, Gabriela Jaita, Verónica Zaldivar, et al.. (2004). Tumor Necrosis Factor-Alpha-Induced Nitric Oxide Restrains the Apoptotic Response of Anterior Pituitary Cells. Neuroendocrinology. 80(2). 83–91. 21 indexed citations
11.
Laurentiis, Andrea De, Daniel Pisera, Carla Caruso, et al.. (2002). Lipopolysaccharide- and Tumor Necrosis Factor-α-Induced Changes in Prolactin Secretion and Dopaminergic Activity in the Hypothalamic-Pituitary Axis. NeuroImmunoModulation. 10(1). 30–39. 38 indexed citations
12.
Candolfi, Marianela, Verónica Zaldivar, Andrea De Laurentiis, et al.. (2002). TNF-α Induces Apoptosis of Lactotropes from Female Rats. Endocrinology. 143(9). 3611–3617. 35 indexed citations
13.
Pisera, Daniel, et al.. (2000). Effect of Interleukin-6 and Tumor Necrosis Factor-α on GABA Release from Mediobasal Hypothalamus and Posterior Pituitary. NeuroImmunoModulation. 7(2). 77–83. 30 indexed citations
14.
Duvilanski, B., et al.. (2000). Interaction between substance P and TRH in the control of prolactin release. Journal of Endocrinology. 166(2). 373–380. 6 indexed citations
15.
Lasaga, Mercedes, Macarena Pampillo, Daniel Pisera, et al.. (1998). The effect of excitatory aminoacids on GABA release from mediobasal hypothalamus of female rats. Neuroscience Letters. 247(2-3). 119–122. 8 indexed citations
16.
Theas, María Susana, et al.. (1998). Effect of Lipopolysaccharide on Tumor Necrosis Factor and Prolactin Release from Rat Anterior Pituitary Cells. Endocrine. 8(3). 241–246. 28 indexed citations
17.
18.
Duvilanski, Beatriz H., et al.. (1996). Role of Nitric Oxide/Cyclic GMP Pathway in the Inhibitory Effect of GABA and Dopamine on Prolactin Release. Journal of Neuroendocrinology. 8(12). 909–913. 35 indexed citations
19.
Pisera, Daniel, et al.. (1996). Neurokinin A affects the tubero-hypophyseal gabaergic system. Neuroreport. 7(13). 2236–2240. 5 indexed citations
20.
Lasaga, Mercedes, et al.. (1994). Involvement of hypothalamic substance P in the effect of prolactin on dopamine release. Neuroreport. 5(14). 1752–1754. 9 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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