Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Phosphatidylserine is a global immunosuppressive signal in efferocytosis, infectious disease, and cancer
2016532 citationsRaymond B. Birge, Sebastian Boeltz et al.Cell Death and Differentiationprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
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This map shows the geographic impact of A. J. Schroit'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 A. J. Schroit with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. J. Schroit more than expected).
This network shows the impact of papers produced by A. J. Schroit. 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 A. J. Schroit. The network helps show where A. J. Schroit may publish in the future.
Co-authorship network of co-authors of A. J. Schroit
This figure shows the co-authorship network connecting the top 25 collaborators of A. J. Schroit.
A scholar is included among the top collaborators of A. J. Schroit 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 A. J. Schroit. A. J. Schroit 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.
Birge, Raymond B., Sebastian Boeltz, Sushil Kumar, et al.. (2016). Phosphatidylserine is a global immunosuppressive signal in efferocytosis, infectious disease, and cancer. Cell Death and Differentiation. 23(6). 962–978.532 indexed citations breakdown →
Fidler, I. J. & A. J. Schroit. (1986). Macrophage recognition of self from nonself: implications for the interaction of macrophages with neoplastic cells.. PubMed. 38. 183–207.4 indexed citations
Bucana, C D, et al.. (1983). Ultrastructural studies of the interaction between liposome-activated human blood monocytes and allogeneic tumor cells in vitro.. PubMed. 112(1). 101–11.44 indexed citations
14.
Schroit, A. J. & Marc E. Key. (1983). Induction of syngeneic tumour-specific immunity by liposomes reconstituted with L2C tumour-cell antigens.. PubMed. 49(3). 431–8.7 indexed citations
15.
Schroit, A. J., IR Hart, Jeppe Madsen, & I. J. Fidler. (1983). Selective delivery of drugs encapsulated in liposomes: natural targeting to macrophages involved in various disease states.. PubMed. 2(2). 97–100.31 indexed citations
16.
Schroit, A. J., Enzo Galligioni, & I. J. Fidler. (1983). Factors influencing the in situ activation of macrophages by liposomes containing muramyl dipeptide. 47(1). 87–94.25 indexed citations
17.
Schroit, A. J. & I. J. Fidler. (1982). Delivery of macrophage-augmenting factors encapsulated in liposomes for destruction of tumor metastases.. PubMed. 102 pt A. 347–55.1 indexed citations
18.
Fidler, I. J., S Sone, William E. Fogler, et al.. (1982). Efficacy of liposomes containing a lipophilic muramyl dipeptide derivative for activating the tumoricidal properties of alveolar macrophages in vivo. 1(1). 43–55.55 indexed citations
Schroit, A. J. & Ruth Gallily. (1974). Studies on the binding and phagocytic inhibition properties of antimacrophage globulin (AMG).. PubMed. 26(5). 971–81.8 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.