John Higgins' Lab
I study the dynamics of human pathophysiologic processes by developing mathematical descriptions of complex human disease phenotypes and how they change over time. The research combines medical insight, dynamic systems theory, and experiments utilizing microfluidics, video processing, flow cytometry, simulation, and large-scale analysis of medical databases in pursuit of two goals: (1) advancing fundamental understanding of the dynamics of human pathophysiology, and (2) improving patient diagnosis, monitoring, and treatment.
Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring
Sci Transl Med. 2016;8:359ra130 - PMID: 27708063
Cellular normoxic biophysical markers of hydroxyurea treatment in sickle cell disease.
Determinants of red blood cell alloantibody detection duration: analysis of multiply alloimmunized patients supports peritransfusion factors.
Transfusion. 2017;:ePub - PMID: 28639314
Michael Dworkin (Higgins Lab
) won a best poster award for his poster “Improved estimation of average glucose from HbA1c by adjusting HbA1c for RBC age” at the 2017 Harvard Medical School Pathology Annual Retreat.
Our latest paper - Malka, Nathan, and Higgins. “Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring”. 5 October 2016, Science Translational Medicine. 8, 359ra130 (2016)- is now accessible for free:
Roy Malka from the Higgins Lab
, has won the prize for best MGH Pathology poster from a resident or fellow this year for his abstract entitled “Patient-Specific Inference of Average Glucose from Glycated Hemoglobin: Toward Personalized Diabetic Monitoring with Precision Laboratory Medicine”. Congratulations, Roy!