Pathology & Laboratory Medicine

Publications

Filter By Faculty

Filter by Principal Investigator

2021

Iyengar NM, Zhou XK, Mendieta H, Giri DD, El-Hely O, Winston L, et al. Effects of Adiposity and Exercise on Breast Tissue and Systemic Metabo-Inflammatory Factors in Women at High Risk or Diagnosed with Breast Cancer. Cancer Prev Res (Phila). 2021;14(5):541-550.

Martini R, Chen Y, Jenkins BD, Elhussin IA, Cheng E, Hoda SA, et al. Investigation of triple-negative breast cancer risk alleles in an International African-enriched cohort. Sci Rep. 2021;11(1):9247.

Mahdi Z, Ettel MG, Gonzalez RS, Hart J, Alpert L, Fang J, et al. Metastases can occur in cirrhotic livers with patent portal veins. Diagn Pathol. 2021;16(1):18.

O'Leary MK, Chen SS, Westblade LF, Alabi CA. Design of a PEGylated Antimicrobial Prodrug with Species-Specific Activation. Biomacromolecules. 2021;22(2):984-992.

Stonesifer CJ, Trager MH, Magro CM, Geskin LJ. CD8+ Lymphogranulomatous Dermatitis as a Manifestation of Malignancy-Associated Immunodeficiency: Rethinking Paraneoplastic Granulomas. Am J Dermatopathol. 2021;43(12):e222-e226.

Epstein JI, Amin MB, Fine SW, Algaba F, Aron M, Baydar DE, et al. The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer. Arch Pathol Lab Med. 2021;145(4):461-493.

Moskowitz AJ, Ghione P, Jacobsen E, Ruan J, Schatz JH, Noor S, et al. A phase 2 biomarker-driven study of ruxolitinib demonstrates effectiveness of JAK/STAT targeting in T-cell lymphomas. Blood. 2021;138(26):2828-2837.

Jesser EA, Brady NJ, Huggins DN, Witschen PM, O'Connor CH, Schwertfeger KL. STAT5 is activated in macrophages by breast cancer cell-derived factors and regulates macrophage function in the tumor microenvironment. Breast Cancer Res. 2021;23(1):104.

Huang J, Linares JF, Duran A, Xia W, Saltiel AR, Müller TD, et al. NBR1 is a critical step in the repression of thermogenesis of p62-deficient adipocytes through PPARγ. Nat Commun. 2021;12(1):2876.

Ikemura K, Bellin E, Yagi Y, Billett H, Saada M, Simone K, et al. Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study. J Med Internet Res. 2021;23(2):e23458.