May S.K. Sutherland

1.0k total citations
15 papers, 833 citations indexed

About

May S.K. Sutherland is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, May S.K. Sutherland has authored 15 papers receiving a total of 833 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Oncology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in May S.K. Sutherland's work include Multiple Myeloma Research and Treatments (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Acute Myeloid Leukemia Research (3 papers). May S.K. Sutherland is often cited by papers focused on Multiple Myeloma Research and Treatments (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Acute Myeloid Leukemia Research (3 papers). May S.K. Sutherland collaborates with scholars based in United States and Canada. May S.K. Sutherland's co-authors include Changpu Yu, Peter D. Senter, Bernd Stein, L.G. Rao, John N. Wylie, Che‐Leung Law, Alan F. Wahl, Charles G. Cerveny, Timothy S. Lewis and Svetlana O. Doronina and has published in prestigious journals such as Journal of Biological Chemistry, Blood and Endocrinology.

In The Last Decade

May S.K. Sutherland

15 papers receiving 784 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
May S.K. Sutherland United States	9	439	402	251	126	110	15	833
Chin Pan United States	13	516 1.2×	639 1.6×	132 0.5×	134 1.1×	47 0.4×	31	1.2k
D. Fan United States	14	359 0.8×	404 1.0×	128 0.5×	62 0.5×	43 0.4×	23	804
Donald C. Paul United States	12	479 1.1×	289 0.7×	36 0.1×	59 0.5×	33 0.3×	14	811
Sandra Hermann Germany	15	181 0.4×	310 0.8×	61 0.2×	48 0.4×	104 0.9×	40	752
Michelle D. Martin United States	9	499 1.1×	348 0.9×	50 0.2×	67 0.5×	26 0.2×	14	796
Timothy McDonnell United States	12	406 0.9×	343 0.9×	52 0.2×	45 0.4×	186 1.7×	19	866
Gemma Shay United States	9	320 0.7×	299 0.7×	52 0.2×	57 0.5×	30 0.3×	10	637
Barbara Castella Italy	17	405 0.9×	265 0.7×	51 0.2×	162 1.3×	57 0.5×	28	947
Christina Wunrau Germany	6	161 0.4×	339 0.8×	40 0.2×	104 0.8×	29 0.3×	12	777
Shiro Kataoka Japan	13	219 0.5×	480 1.2×	78 0.3×	52 0.4×	36 0.3×	27	717

Countries citing papers authored by May S.K. Sutherland

Since Specialization

Citations

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

Fields of papers citing papers by May S.K. Sutherland

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by May S.K. Sutherland. 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 May S.K. Sutherland. The network helps show where May S.K. Sutherland may publish in the future.

Co-authorship network of co-authors of May S.K. Sutherland

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

All Works

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15 of 15 papers shown

Sutherland, May S.K., Changpu Yu, Christine O’Day, et al.. (2015). SGN-CD33A in Combination with Hypomethylating Agents Is Highly Efficacious in Preclinical Models of AML. Blood. 126(23). 3785–3785. 8 indexed citations

Sutherland, May S.K., Changpu Yu, Roland B. Walter, et al.. (2015). SGN-CD123A, a Pyrrolobenzodiazepine Dimer Linked Anti-CD123 Antibody Drug Conjugate, Demonstrates Effective Anti-Leukemic Activity in Multiple Preclinical Models of AML. Blood. 126(23). 330–330. 17 indexed citations

Sutherland, May S.K., Changpu Yu, Martha E. Anderson, et al.. (2014). SGN-CD33A in Combination with Cytarabine or Hypomethylating Agents Demonstrates Enhanced Anti-Leukemic Activity in Preclinical Models of AML. Blood. 124(21). 3739–3739. 2 indexed citations

Sutherland, May S.K., Roland B. Walter, Scott C. Jeffrey, et al.. (2013). SGN-CD33A: a novel CD33-targeting antibody–drug conjugate using a pyrrolobenzodiazepine dimer is active in models of drug-resistant AML. Blood. 122(8). 1455–1463. 291 indexed citations

Sutherland, May S.K., Roland B. Walter, Scott C. Jeffrey, et al.. (2012). SGN-CD33A: A Novel CD33-Directed Antibody-Drug Conjugate, Utilizing Pyrrolobenzodiazepine Dimers, Demonstrates Preclinical Antitumor Activity Against Multi-Drug Resistant Human AML. Blood. 120(21). 3589–3589. 7 indexed citations

Lewis, Timothy S., Kim M. Kissler, Ivan J. Stone, et al.. (2007). The Humanized Anti-CD40 Monoclonal Antibody, SGN-40, Potentiates Chemotherapy Regimens in NHL Xenograft Models Via Pro-Apoptotic Signaling.. Blood. 110(11). 2342–2342. 6 indexed citations

Sutherland, May S.K., Russell J. Sanderson, Kristine A. Gordon, et al.. (2006). Lysosomal Trafficking and Cysteine Protease Metabolism Confer Target-specific Cytotoxicity by Peptide-linked Anti-CD30-Auristatin Conjugates. Journal of Biological Chemistry. 281(15). 10540–10547. 222 indexed citations

Lewis, Timothy S., May S.K. Sutherland, Mechthild Jonas, et al.. (2006). The Humanized Anti-CD40 Antibody, SGN-40, Promotes Apoptosis Signaling and Is Effective in Combination with Standard Therapies in Lymphoma Xenograft Models.. Blood. 108(11). 2499–2499. 5 indexed citations

Sutherland, May S.K., Timothy S. Lewis, Changpu Yu, et al.. (2006). SGN-33 Modulates Cytokine and Chemokine Production by Activated Monocytes and Macrophages.. Blood. 108(11). 1995–1995. 2 indexed citations

10.

Winkler, David G., May S.K. Sutherland, Ethan W. Ojala, et al.. (2004). Sclerostin Inhibition of Wnt-3a-induced C3H10T1/2 Cell Differentiation Is Indirect and Mediated by Bone Morphogenetic Proteins. Journal of Biological Chemistry. 280(4). 2498–2502. 139 indexed citations

11.

Stein, Bernd & May S.K. Sutherland. (1998). IL-6 as a drug discovery target. Drug Discovery Today. 3(5). 202–213. 40 indexed citations

12.

Rao, L.G., et al.. (1996). Positive interaction between 17β-estradiol and parathyroid hormone in normal human osteoblasts cultured long term in the presence of dexamethasone. Osteoporosis International. 6(2). 111–119. 10 indexed citations

13.

Rao, L.G., John N. Wylie, May S.K. Sutherland, & TM Murray. (1996). 17β-Oestradiol enhances the stimulatory effect of 1,25-dihydroxyvitamin D3 on alkaline phosphatase activity in human osteosarcoma SaOS-2 cells in a differentiation-dependent manner. Journal of Endocrinology. 148(1). 181–187. 25 indexed citations

14.

Sutherland, May S.K., L.G. Rao, John N. Wylie, et al.. (1995). Age-dependent expression of osteoblastic phenotypic markers in normal human osteoblasts cultured long term in the presence of dexamethasone. Osteoporosis International. 5(5). 335–343. 31 indexed citations

15.

Rao, L.G., John N. Wylie, May S.K. Sutherland, & Timothy M. Murray. (1994). 17 beta-estradiol and parathyroid hormone potentiate each other's stimulatory effects on alkaline phosphatase activity in SaOS-2 cells in a differentiation-dependent manner.. Endocrinology. 134(2). 614–620. 28 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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