BE Seminars & Events

34% of all 18 to 24 year olds in the U.S. are federally defined underrepresented minorities (URM). This group constitutes 12% of all BS degree recipients in engineering in the U.S. but only 8% of the B.S. degrees in BME and only 4% of the PhD's in BME. In 2002 when the BME Department was started at The City College of New York it was decided to create a department where the tenure track faculty would reflect the diversity of the undergraduate student body which was 50% URM and 50% female at the time. The fledgling department was also awarded one of two grants from NIH whose goal was to encourage URM undergraduates to purse graduate education in a life science and potentially a PhD. This grant which was renewed in 2007 and ended in the summer of 2013 has played a pivotal role in shaping the future of the department. Of particular importance in the retention of students was a novel mentorship program in which every undergraduate NIH Minority Scholar was matched with a PhD student who met with them on a weekly basis for their entire stay at the college from freshman to graduation. Virtually every PhD student and faculty member in the department was involved in some way with an NIH Minority Scholar. This interaction had a remarkable effect on faculty recruitment whose diversity today is singular among all major STEM departments in the U.S. Currently 57% of the tenure track faculty in BME are female (43%) and or URM (36%), and 70% of the PhD students are female and/or URM. For the past nine years the department has also had highest teaching evaluation in the Grove School of Engineering. This talk will tell the story of how this happened.

Nanoparticles with unique physical and chemical properties can be rendered water-soluble and biocompatible for use in cancer diagnosis, imaging and therapy. This talk will highlight some of the recent advances in the following four areas: 1) application of materials in improving the sensitivity of biomarker detection; 2) use of different nanomaterials (both rigid inorganic materials and biodegradable polymeric materials) for multimodality imaging (PET, optical, MRI, photoacoustic, etc); 3) drug and gene loaded nanomaterials for cancer therapy; and 4) theranostic nanoplatforms with both imaging and therapeutic components combined. The challenges and future perspectives of nanomedicine in cancer research will also be discussed.

Deep brain stimulation (DBS) has been used for treating Parkinson's Disease with great success and somewhat lesser success for epilepsy.The mechanism by which DBS works is not well understood and thus limits our ability to really tune stimulation to maximize benefits.In this talk I will discuss theoretical approaches to understand how pathological neural activity is generated in these diseases and approaches to optimize DBS therapy.

Biomaterials have evolved over recent decades; transitioning from stealth implants that hide from the body to tools with biological functions that interact with and manipulate their surrounding environment. Biomaterials are the building blocks for scaffolds that direct cell and tissue function for applications in regenerative medicine. Regenerative medicine aims to rebuild and repair tissues in the body lost due to trauma, disease or congenital abnormalities. Our scaffold design centers on synthetic and biologically-derived polymers that are combined to produce biomaterials with controlled physical and physiological properties. The lecture will discuss the continuum of the biomaterials development and translation process from biomaterial structure-cell function correlations to clinical translation in cartilage and soft tissue repair.

Abstract:  The configuration of connections in the human connectome, the "wiring map" of an organism’s neural system, is thought to arise from a drive to reduce the total cost of wiring while simultaneously promoting efficient information processing. We attempted to disentangle the contributions made by these components by incorporating geometric (spatial) and topological information into the wiring rules of network generative models for the human connectome.

Across three independently acquired human MRI datasets (N=380 participants in total), we found that generative models where connection formation was based solely on spatial proximity were unable to produce realistic synthetic networks. Specifically, such models underestimate the number of long-range connections and fail to reproduce the distance-dependent degree assortativity that characterize empirical human connectomes.

On the other hand, models whose wiring rule included both spatial and topological information were able to match these properties and others. Of this class of models, we found that the best-fitting model combined a topological parameter for homophily, calculated as the similarity of connectivity profiles, and a geometric parameter that penalized the formation of long-distant connections. Fitting these models to the connectomes of a cohort whose ages ranged from 7-85 years, we find that the homophily parameter remains constant with age, whereas there was a monotonic reduction of the geometric parameter, suggesting that “older” networks penalize long-distance connections proportionally less.