Gil Mor

Prof. Gil Mor

Wayne State University, Detroit, Michigan, USA
orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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10 May 2010 in American Journal of Reproductive Immunology
Verified
Journal Article
Open access
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Gil MorGil Mor
Gil Mor
ICIngrid Cardenas
Ingrid Cardenas
Citation Mor G, Cardenas I. The immune system in pregnancy: a unique complexity. Am J Reprod Immunol 2010 Placental immune response and its tropism for specific viruses and pathogens affect the outcome of the pregnant woman’s susceptibility to and severity of certain infectious diseases. The generalization of pregnancy as a condition of immune suppression or increased risk is misleading and prevents the determination of adequate guidelines for treating pregnant women during pandemics. There is a need to evaluate the interaction of each specific pathogen with the fetal/placental unit and its responses to design the adequate prophylaxis or therapy. The complexity of the immunology of pregnancy and the focus, for many years, on the concept of immunology of pregnancy as an organ transplantation have complicated the field and delayed the development of new guidelines with clinical implications that could help to answer these and other relevant questions. Our challenge as scientists and clinicians interested in the field of reproductive immunology is to evaluate many of the ‘classical concepts’ to define new approaches for a better understanding of the immunology of pregnancy that will benefit mothers and fetuses in different clinical scenarios.

14 March 2011 in Annals of the New York Academy of Sciences
Verified
Journal Article
Closed access
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Gil MorGil Mor
Gil Mor
ICIngrid Cardenas
Ingrid Cardenas
VAVikki Abrahams
Vikki Abrahams
SGSeth Guller
Seth Guller

13 January 2015 in American Journal of Reproductive Immunology
Verified
Journal Article
Closed access
PDF file
MSMichelle Silasi
Michelle Silasi
ICIngrid Cardenas
Ingrid Cardenas
JKJa-Young Kwon
Ja-Young Kwon
KRKaren Racicot
Karen Racicot
PAPaula Aldo
Paula Aldo
Gil MorGil Mor
Gil Mor

1 January 2009 in Cell Cycle
Verified
Journal Article
Closed access
AAAyesha B. Alvero
Ayesha B. Alvero
RCRui Chen
Rui Chen
HFHan-Hsuan Fu
Han-Hsuan Fu
MMMichele Montagna
Michele Montagna
PSPeter E. Schwartz
Peter E. Schwartz
Gil MorGil Mor
Gil Mor
A major burden in the treatment of ovarian cancer is the high percentage of recurrence and chemoresistance. Cancer stem cells (CSCs) provide a reservoir of cells that can self-renew, can maintain t...

12 May 2005 in Proceedings of the National Academy of Sciences
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Journal Article
Closed access
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Gil MorGil Mor
Gil Mor
IVIrene Visintin
Irene Visintin
YLYinglei Lai
Yinglei Lai
HZHongyu Zhao
Hongyu Zhao
PSPeter Schwartz
Peter Schwartz
DWDavid C. Ward
David C. Ward
Early diagnosis of epithelial ovarian cancer (EOC) would significantly decrease the morbidity and mortality from this disease but is difficult in the absence of physical symptoms. Here, we report a blood test, based on the simultaneous quantization of four analytes (leptin, prolactin, osteopontin, and insulin-like growth factor-II), that can discriminate between disease-free and EOC patients, including patients diagnosed with stage I and II disease, with high efficiency (95%). Microarray analysis was used initially to determine the levels of 169 proteins in serum from 28 healthy women, 18 women newly diagnosed with EOC, and 40 women with recurrent disease. Evaluation of proteins that showed significant differences in expression between controls and cancer patients by ELISA assays yielded the four analytes. These four proteins then were evaluated in a blind cross-validation study by using an additional 106 healthy females and 100 patients with EOC (24 stage I/II and 76 stage III/IV). Upon sample decoding, the results were analyzed by using three different classification algorithms and a binary code methodology. The four-analyte test was further validated in a blind binary code study by using 40 additional serum samples from normal and EOC cancer patients. No single protein could completely distinguish the cancer group from the healthy controls. However, the combination of the four analytes exhibited the following: sensitivity 95%, positive predictive value (PPV) 95%, specificity 95%, and negative predictive value (NPV) 94%, a considerable improvement on current methodology.

4 July 2014 in American Journal of Reproductive Immunology
Verified
Journal Article
Closed access
PDF file
KRKaren Racicot
Karen Racicot
JKJa-Young Kwon
Ja-Young Kwon
PAPaulomi Aldo
Paulomi Aldo
MSMichelle Silasi
Michelle Silasi
Gil MorGil Mor
Gil Mor