Daniela L. Papademetrio

9.0k total citations
18 papers, 436 citations indexed

About

Daniela L. Papademetrio is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, Daniela L. Papademetrio has authored 18 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Immunology and 5 papers in Epidemiology. Recurrent topics in Daniela L. Papademetrio's work include Autophagy in Disease and Therapy (4 papers), Proteoglycans and glycosaminoglycans research (4 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Daniela L. Papademetrio is often cited by papers focused on Autophagy in Disease and Therapy (4 papers), Proteoglycans and glycosaminoglycans research (4 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Daniela L. Papademetrio collaborates with scholars based in Argentina, France and Italy. Daniela L. Papademetrio's co-authors include Silvina Lompardía, Élida Álvarez, Susana N. Costantino, Élida Álvarez, Silvia E. Hajos, Alejandro Ropolo, Valeria P. Sülsen, Andrea Lo Ré, Cendrine Archange and Claudio González and has published in prestigious journals such as PLoS ONE, Scientific Reports and Molecules.

In The Last Decade

Daniela L. Papademetrio

17 papers receiving 433 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela L. Papademetrio Argentina 13 249 141 102 82 67 18 436
Chunwei Cheng China 15 299 1.2× 124 0.9× 56 0.5× 41 0.5× 74 1.1× 19 633
Caroline O. Facey United States 10 274 1.1× 105 0.7× 145 1.4× 89 1.1× 74 1.1× 19 468
Maura McDonnell United States 2 320 1.3× 317 2.2× 75 0.7× 61 0.7× 70 1.0× 4 522
Chia‐Hui Huang Taiwan 14 398 1.6× 94 0.7× 34 0.3× 75 0.9× 61 0.9× 32 580
Pei Yen Yeh Taiwan 8 351 1.4× 88 0.6× 52 0.5× 148 1.8× 137 2.0× 9 540
Theresa Reno United States 8 537 2.2× 56 0.4× 82 0.8× 72 0.9× 97 1.4× 10 766
Huailong Xu China 14 398 1.6× 134 1.0× 57 0.6× 107 1.3× 158 2.4× 17 658
Xianfang Liu China 13 427 1.7× 91 0.6× 63 0.6× 142 1.7× 87 1.3× 22 584
Sha Li China 12 244 1.0× 39 0.3× 71 0.7× 120 1.5× 35 0.5× 29 466
Giovanni Tonelli France 7 392 1.6× 365 2.6× 53 0.5× 139 1.7× 122 1.8× 10 609

Countries citing papers authored by Daniela L. Papademetrio

Since Specialization
Citations

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

Fields of papers citing papers by Daniela L. Papademetrio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela L. Papademetrio. 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 Daniela L. Papademetrio. The network helps show where Daniela L. Papademetrio may publish in the future.

Co-authorship network of co-authors of Daniela L. Papademetrio

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

All Works

18 of 18 papers shown
1.
Mantovani, Stefania, Daniela L. Papademetrio, Sergio I. Nemirovsky, et al.. (2025). Imiquimod, a Promising Broad-Spectrum Antiviral, Prevents SARS-CoV-2 and Canine Coronavirus Multiplication Through the MAPK/ERK Signaling Pathway. Viruses. 17(6). 801–801.
2.
Garcia, María Noé, et al.. (2022). Sesquiterpene Lactones as Promising Candidates for Cancer Therapy: Focus on Pancreatic Cancer. Molecules. 27(11). 3492–3492. 18 indexed citations
3.
Álvarez, Élida, et al.. (2021). 4-Methylumbelliferone induces antitumor effects independently of hyaluronan synthesis inhibition in human acute leukemia cell lines. Life Sciences. 287. 120065–120065. 11 indexed citations
4.
Papademetrio, Daniela L., María Noé Garcia, Daniel Grasso, & Élida Álvarez. (2021). Autophagy-Mediated Exosomes as Immunomodulators of Natural Killer Cells in Pancreatic Cancer Microenvironment. Frontiers in Oncology. 10. 622956–622956. 11 indexed citations
5.
Grasso, Daniel, Daniela L. Papademetrio, Mirna Biglione, et al.. (2021). Autophagy in Human T-Cell Leukemia Virus Type 1 (HTLV-1) Induced Leukemia. Frontiers in Oncology. 11. 641269–641269. 12 indexed citations
6.
Lompardía, Silvina, et al.. (2019). Hyaluronan abrogates imatinib-induced senescence in chronic myeloid leukemia cell lines. Scientific Reports. 9(1). 10930–10930. 15 indexed citations
7.
Papademetrio, Daniela L., et al.. (2017). Role of 20-Hydroxyeicosatetraenoic Acid (20-HETE) in Androgen-Mediated Cell Viability in Prostate Cancer Cells. Hormones and Cancer. 8(4). 243–256. 7 indexed citations
8.
Sülsen, Valeria P., et al.. (2016). Mode of Action of the Sesquiterpene Lactones Psilostachyin and Psilostachyin C on Trypanosoma cruzi. PLoS ONE. 11(3). e0150526–e0150526. 44 indexed citations
9.
Lompardía, Silvina, et al.. (2016). 4-methylumbelliferone and imatinib combination enhances senescence induction in chronic myeloid leukemia cell lines. Investigational New Drugs. 35(1). 1–10. 19 indexed citations
10.
Lompardía, Silvina, et al.. (2015). Hyaluronan oligomers sensitize chronic myeloid leukemia cell lines to the effect of Imatinib. Glycobiology. 26(4). 343–352. 22 indexed citations
11.
Papademetrio, Daniela L., et al.. (2015). Inhibition of Survival Pathways MAPK and NF-kB Triggers Apoptosis in Pancreatic Ductal Adenocarcinoma Cells via Suppression of Autophagy. Targeted Oncology. 11(2). 183–195. 56 indexed citations
12.
Papademetrio, Daniela L., et al.. (2013). Interplay between autophagy and apoptosis in pancreatic tumors in response to gemcitabine. Targeted Oncology. 9(2). 123–134. 36 indexed citations
13.
14.
Lompardía, Silvina, et al.. (2013). Human leukemic cell lines synthesize hyaluronan to avoid senescence and resist chemotherapy. Glycobiology. 23(12). 1463–1476. 45 indexed citations
15.
Papademetrio, Daniela L., et al.. (2013). The catechin flavonoid reduces proliferation and induces apoptosis of murine lymphoma cells LB02 through modulation of antiapoptotic proteins. Revista Brasileira de Farmacognosia. 23(3). 455–463. 13 indexed citations
16.
Papademetrio, Daniela L., et al.. (2010). Haemostatic and immune role of cellular clotting in the sipunculan Themiste petricola. Cell and Tissue Research. 339(3). 597–611. 5 indexed citations
17.
Pardo, Romina, Andrea Lo Ré, Cendrine Archange, et al.. (2010). Gemcitabine Induces the VMP1 -Mediated Autophagy Pathway to Promote Apoptotic Death in Human Pancreatic Cancer Cells. Pancreatology. 10(1). 19–26. 84 indexed citations
18.
Papademetrio, Daniela L., Mario Alejandro Lorenzetti, Pamela Valva, et al.. (2009). Caffeic Acid Phenylethyl Ester and MG-132 Have Apoptotic and Antiproliferative Effects on Leukemic Cells But Not on Normal Mononuclear Cells. Translational Oncology. 2(1). 46–IN3. 22 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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