Jaime D. Blais

4.5k total citations · 2 hit papers
41 papers, 3.3k citations indexed

About

Jaime D. Blais is a scholar working on Genetics, Molecular Biology and Nephrology. According to data from OpenAlex, Jaime D. Blais has authored 41 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Genetics, 16 papers in Molecular Biology and 8 papers in Nephrology. Recurrent topics in Jaime D. Blais's work include Genetic and Kidney Cyst Diseases (19 papers), Endoplasmic Reticulum Stress and Disease (7 papers) and Pancreatic function and diabetes (6 papers). Jaime D. Blais is often cited by papers focused on Genetic and Kidney Cyst Diseases (19 papers), Endoplasmic Reticulum Stress and Disease (7 papers) and Pancreatic function and diabetes (6 papers). Jaime D. Blais collaborates with scholars based in United States, Netherlands and Switzerland. Jaime D. Blais's co-authors include David Ron, Heather P. Harding, Frank S. Czerwiec, John C. Bell, Vicente E. Torres, Constantinos Koumenis, John Ouyang, Olivier Devuyst, Arlene B. Chapman and Ronald D. Perrone and has published in prestigious journals such as New England Journal of Medicine, Journal of Biological Chemistry and The Journal of Cell Biology.

In The Last Decade

Jaime D. Blais

40 papers receiving 3.3k citations

Hit Papers

ER stress‐regulated translation increases tolerance to ex... 2005 2026 2012 2019 2005 2017 100 200 300 400 500

Peers

Jaime D. Blais
John Li United States
Animesh Nandi United States
Andrey Sorokin United States
Yi Cai China
Benjamin J. Wilkins United States
Oliver Tschopp Switzerland
Kazuhiro Oka United States
Frank Park United States
Hueng-Sik Choi South Korea
John Li United States
Jaime D. Blais
Citations per year, relative to Jaime D. Blais Jaime D. Blais (= 1×) peers John Li

Countries citing papers authored by Jaime D. Blais

Since Specialization
Citations

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

Fields of papers citing papers by Jaime D. Blais

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaime D. Blais. 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 Jaime D. Blais. The network helps show where Jaime D. Blais may publish in the future.

Co-authorship network of co-authors of Jaime D. Blais

This figure shows the co-authorship network connecting the top 25 collaborators of Jaime D. Blais. A scholar is included among the top collaborators of Jaime D. Blais 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 Jaime D. Blais. Jaime D. Blais 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.
Sarraju, Ashish, George L. Bakris, Christopher P. Cannon, et al.. (2022). Cardiovascular Effects of Canagliflozin in Relation to Renal Function and Albuminuria. Journal of the American College of Cardiology. 80(18). 1721–1731. 4 indexed citations
2.
Rodríguez, Fátima, Joseph Vasey, Robert A. Bailey, et al.. (2021). Real-World Diagnosis and Treatment of Diabetic Kidney Disease. Advances in Therapy. 38(8). 4425–4441. 22 indexed citations
4.
Neuen, Brendon L., Toshiaki Ohkuma, Bruce Neal, et al.. (2020). Relative and Absolute Risk Reductions in Cardiovascular and Kidney Outcomes With Canagliflozin Across KDIGO Risk Categories: Findings From the CANVAS Program. American Journal of Kidney Diseases. 77(1). 23–34.e1. 50 indexed citations
5.
Gansevoort, Ron T., Maatje D.A. van Gastel, Arlene B. Chapman, et al.. (2019). Plasma copeptin levels predict disease progression and tolvaptan efficacy in autosomal dominant polycystic kidney disease. Kidney International. 96(1). 159–169. 54 indexed citations
7.
Torres, Vicente E., Olivier Devuyst, Arlene B. Chapman, et al.. (2017). Rationale and Design of a Clinical Trial Investigating Tolvaptan Safety and Efficacy in Autosomal Dominant Polycystic Kidney Disease. American Journal of Nephrology. 45(3). 257–266. 18 indexed citations
8.
Devuyst, Olivier, Arlene B. Chapman, Susan E. Shoaf, Frank S. Czerwiec, & Jaime D. Blais. (2017). Tolerability of Aquaretic-Related Symptoms Following Tolvaptan for Autosomal Dominant Polycystic Kidney Disease: Results From TEMPO 3:4. Kidney International Reports. 2(6). 1132–1140. 36 indexed citations
9.
Kline, Timothy L., Panagiotis Korfiatis, Marie E. Edwards, et al.. (2017). Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys. Journal of Digital Imaging. 30(4). 442–448. 108 indexed citations
10.
Gall, Émilie Cornec-Le, Jaime D. Blais, María V. Irazabal, et al.. (2017). Can we further enrich autosomal dominant polycystic kidney disease clinical trials for rapidly progressive patients? Application of the PROPKD score in the TEMPO trial. Nephrology Dialysis Transplantation. 33(4). 645–652. 32 indexed citations
11.
Devuyst, Olivier, Arlene B. Chapman, Ron T. Gansevoort, et al.. (2016). Urine Osmolality, Response to Tolvaptan, and Outcome in Autosomal Dominant Polycystic Kidney Disease: Results from the TEMPO 3:4 Trial. Journal of the American Society of Nephrology. 28(5). 1592–1602. 65 indexed citations
12.
Casteleijn, Niek F., Jaime D. Blais, Arlene B. Chapman, et al.. (2016). Tolvaptan and Kidney Pain in Patients With Autosomal Dominant Polycystic Kidney Disease: Secondary Analysis From a Randomized Controlled Trial. American Journal of Kidney Diseases. 69(2). 210–219. 29 indexed citations
13.
Irazabal, María V., Jaime D. Blais, Ronald D. Perrone, et al.. (2016). Prognostic Enrichment Design in Clinical Trials for Autosomal Dominant Polycystic Kidney Disease: The TEMPO 3:4 Clinical Trial. Kidney International Reports. 1(4). 213–220. 37 indexed citations
15.
Phillips, Michael, Jaime D. Blais, Graham Bothamley, et al.. (2012). Point-of-care breath test for biomarkers of active pulmonary tuberculosis. Tuberculosis. 92(4). 314–320. 145 indexed citations
16.
Blais, Jaime D., Ester Zito, Yuhong Zhang, et al.. (2010). A Small Molecule Inhibitor of Endoplasmic Reticulum Oxidation 1 (ERO1) with Selectively Reversible Thiol Reactivity. Journal of Biological Chemistry. 285(27). 20993–21003. 90 indexed citations
17.
Cloutier, M., et al.. (2006). Internal Ribosome Entry Site-mediated Translation of Apaf-1, but Not XIAP, Is Regulated during UV-induced Cell Death. Journal of Biological Chemistry. 281(22). 15155–15163. 34 indexed citations
18.
Park, Eun‐Hee, Joseph M. Lee, Jaime D. Blais, John C. Bell, & Jerry Pelletier. (2005). Internal Translation Initiation Mediated by the Angiogenic Factor Tie2. Journal of Biological Chemistry. 280(22). 20945–20953. 25 indexed citations
19.
Bi, Meixia, Christine Naczki, Marianne Koritzinsky, et al.. (2005). ER stress‐regulated translation increases tolerance to extreme hypoxia and promotes tumor growth. The EMBO Journal. 24(19). 3470–3481. 574 indexed citations breakdown →
20.
Blais, Jaime D., Meixia Bi, Heather P. Harding, et al.. (2004). Activating Transcription Factor 4 Is Translationally Regulated by Hypoxic Stress. Molecular and Cellular Biology. 24(17). 7469–7482. 359 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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