Neerupma Silswal

1.2k total citations · 1 hit paper
19 papers, 923 citations indexed

About

Neerupma Silswal is a scholar working on Molecular Biology, Epidemiology and Nephrology. According to data from OpenAlex, Neerupma Silswal has authored 19 papers receiving a total of 923 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 4 papers in Epidemiology and 3 papers in Nephrology. Recurrent topics in Neerupma Silswal's work include Eicosanoids and Hypertension Pharmacology (3 papers), Parathyroid Disorders and Treatments (3 papers) and Ubiquitin and proteasome pathways (3 papers). Neerupma Silswal is often cited by papers focused on Eicosanoids and Hypertension Pharmacology (3 papers), Parathyroid Disorders and Treatments (3 papers) and Ubiquitin and proteasome pathways (3 papers). Neerupma Silswal collaborates with scholars based in United States, Australia and India. Neerupma Silswal's co-authors include Sudip Ghosh, Sangita Mukhopadhyay, Anil Singh, Aruna Battu, Nasreen Z. Ehtesham, Michael Wacker, Jon Andresen, Chad D. Touchberry, Shiqin Zhang and Jason R. Stubbs and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Neerupma Silswal

18 papers receiving 909 citations

Hit Papers

Human resistin stimulates the pro-inflammatory cytokines ... 2005 2026 2012 2019 2005 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Neerupma Silswal United States 11 368 256 217 201 155 19 923
László Bajnok Hungary 18 142 0.4× 254 1.0× 206 0.9× 177 0.9× 75 0.5× 42 989
Ryohei Sekimoto Japan 10 305 0.8× 221 0.9× 220 1.0× 178 0.9× 75 0.5× 13 678
Guangda Xiang China 19 221 0.6× 432 1.7× 64 0.3× 369 1.8× 108 0.7× 46 1.1k
Yuelan Ren United States 7 310 0.8× 240 0.9× 96 0.4× 201 1.0× 206 1.3× 8 797
Yuzuru Ohshiro Japan 13 106 0.3× 238 0.9× 146 0.7× 211 1.0× 50 0.3× 20 784
Zhen Sun China 17 170 0.5× 319 1.2× 93 0.4× 119 0.6× 184 1.2× 41 812
永井 良三 Japan 2 787 2.1× 225 0.9× 188 0.9× 548 2.7× 110 0.7× 2 1.2k
Mizuho Tamura Japan 12 187 0.5× 298 1.2× 409 1.9× 104 0.5× 122 0.8× 15 923
Dao‐Ming Chang Taiwan 10 742 2.0× 199 0.8× 90 0.4× 415 2.1× 93 0.6× 17 1.2k
Fone‐Ching Hsiao Taiwan 18 165 0.4× 241 0.9× 64 0.3× 188 0.9× 128 0.8× 42 848

Countries citing papers authored by Neerupma Silswal

Since Specialization
Citations

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

Fields of papers citing papers by Neerupma Silswal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neerupma Silswal

This figure shows the co-authorship network connecting the top 25 collaborators of Neerupma Silswal. A scholar is included among the top collaborators of Neerupma Silswal 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 Neerupma Silswal. Neerupma Silswal 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.
Bengtson, Charles D., Neerupma Silswal, Nathalie Baumlin, et al.. (2022). The CFTR Amplifier Nesolicaftor Rescues TGF-β1 Inhibition of Modulator-Corrected F508del CFTR Function. International Journal of Molecular Sciences. 23(18). 10956–10956. 11 indexed citations
2.
Jaumotte, Juliann D., Alexis L. Franks, Heather Menden, et al.. (2021). Ciclesonide activates glucocorticoid signaling in neonatal rat lung but does not trigger adverse effects in the cortex and cerebellum. Neurobiology of Disease. 156. 105422–105422. 7 indexed citations
4.
Franks, Alexis L., et al.. (2018). Statins impact primary embryonic mouse neural stem cell survival, cell death, and fate through distinct mechanisms. PLoS ONE. 13(5). e0196387–e0196387. 12 indexed citations
5.
Silswal, Neerupma & Nilofer Qureshi. (2017). Resveratrol: Proteasome Inhibitor and Immunomodulator. The FASEB Journal. 31(S1).
7.
Grabner, Alexander, Karla Schramm, Neerupma Silswal, et al.. (2017). FGF23/FGFR4-mediated left ventricular hypertrophy is reversible. Scientific Reports. 7(1). 1993–1993. 100 indexed citations
8.
Silswal, Neerupma, et al.. (2017). Resveratrol Downregulates Biomarkers of Sepsis Via Inhibition of Proteasome's Proteases. Shock. 50(5). 579–588. 19 indexed citations
9.
Silswal, Neerupma, et al.. (2016). Resveratrol Modulates Cytokine Expression in LPS‐induced Human Monocytes: Role of Proteasome Subunits. The FASEB Journal. 30(S1). 2 indexed citations
10.
Silswal, Neerupma, Júlia Reis, Asaf A. Qureshi, Christopher J. Papasian, & Nilofer Qureshi. (2016). Of Mice and Men. Shock. 47(4). 445–454. 12 indexed citations
11.
Wacker, Michael, Chad D. Touchberry, Neerupma Silswal, et al.. (2016). Skeletal Muscle, but not Cardiovascular Function, Is Altered in a Mouse Model of Autosomal Recessive Hypophosphatemic Rickets. Frontiers in Physiology. 7. 173–173. 20 indexed citations
12.
Silswal, Neerupma, Nikhil K. Parelkar, Jon Andresen, & Michael Wacker. (2015). Restoration of Endothelial Function inPparα−/−Mice by Tempol. PPAR Research. 2015. 1–9. 8 indexed citations
13.
Touchberry, Chad D., et al.. (2014). Cardiac thromboxane A2 receptor activation does not directly induce cardiomyocyte hypertrophy but does cause cell death that is prevented with gentamicin and 2-APB. BMC Pharmacology and Toxicology. 15(1). 73–73. 13 indexed citations
14.
Silswal, Neerupma, Chad D. Touchberry, Shiqin Zhang, et al.. (2014). FGF23 directly impairs endothelium-dependent vasorelaxation by increasing superoxide levels and reducing nitric oxide bioavailability. American Journal of Physiology-Endocrinology and Metabolism. 307(5). E426–E436. 143 indexed citations
15.
Silswal, Neerupma, Nikhil K. Parelkar, Michael Wacker, Mostafa Z. Badr, & Jon Andresen. (2012). PPARα-Independent Arterial Smooth Muscle Relaxant Effects of PPARαAgonists. PPAR Research. 2012. 1–10. 6 indexed citations
16.
Silswal, Neerupma, Nikhil K. Parelkar, Michael Wacker, Marco Brotto, & Jon Andresen. (2011). Phosphatidylinositol 3,5-bisphosphate increases intracellular free Ca2+in arterial smooth muscle cells and elicits vasocontraction. American Journal of Physiology-Heart and Circulatory Physiology. 300(6). H2016–H2026. 13 indexed citations
17.
Brotto, Leticia, Neerupma Silswal, Chad D. Touchberry, et al.. (2010). Evidence for pathophysiological crosstalk between bones, cardiac, skeletal and smooth muscles. The FASEB Journal. 24(S1). 2 indexed citations
18.
Parelkar, Nikhil K., et al.. (2009). 2,2,2-Trichloroethanol Activates a Nonclassical Potassium Channel in Cerebrovascular Smooth Muscle and Dilates the Middle Cerebral Artery. Journal of Pharmacology and Experimental Therapeutics. 332(3). 803–810. 8 indexed citations
19.
Silswal, Neerupma, Anil Singh, Aruna Battu, et al.. (2005). Human resistin stimulates the pro-inflammatory cytokines TNF-α and IL-12 in macrophages by NF-κB-dependent pathway. Biochemical and Biophysical Research Communications. 334(4). 1092–1101. 513 indexed citations breakdown →

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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