Academic affiliated training centers in humanitarian health, Part I: program characteristics and professionalization preferences of centers in North America.

The collaborative London based non-governmental organization network ELRHA (Enhancing Learning and Research for Humanitarian Assistance) supports partnerships between higher education institutions and humanitarian organizations worldwide with the objective to enhance the professionalization of the humanitarian sector. While coordination and control of the humanitarian sector has plagued the response to every major crisis, concerns highlighted by the 2010 Haitian earthquake response further catalyzed and accelerated the need to ensure competency-based professionalization of the humanitarian health care work force. The Harvard Humanitarian Initiative sponsored an independent survey of established academically affiliated training centers in North America that train humanitarian health care workers to determine their individual training center characteristics and preferences in the potential professionalization process. The survey revealed that a common thread of profession-specific skills and core humanitarian competencies were being offered in both residential and online programs with additional programs offering opportunities for field simulation experiences and more advanced degree programs. This study supports the potential for the development of like-minded academic affiliated and competency-based humanitarian health programs to organize themselves under ELRHA's regional "consultation hubs" worldwide that can assist and advocate for improved education and training opportunities in less served developing countries.

Quantifying signal changes in nano-wire based biosensors.

In this work, we present a computational methodology for predicting the change in signal (conductance sensitivity) of a nano-BioFET sensor (a sensor based on a biomolecule binding another biomolecule attached to a nano-wire field effect transistor) upon binding its target molecule. The methodology is a combination of the screening model of surface charge sensors in liquids developed by Brandbyge and co-workers [Sørensen et al., Appl. Phys. Lett., 2007, 91, 102105], with the PROPKA method for predicting the pH-dependent charge of proteins and protein-ligand complexes, developed by Jensen and co-workers [Li et al., Proteins: Struct., Funct., Bioinf., 2005, 61, 704-721, Bas et al., Proteins: Struct., Funct., Bioinf., 2008, 73, 765-783]. The predicted change in conductance sensitivity based on this methodology is compared to previously published data on nano-BioFET sensors obtained by other groups. In addition, the conductance sensitivity dependence from various parameters is explored for a standard wire, representative of a typical experimental setup. In general, the experimental data can be reproduced with sufficient accuracy to help interpret them. The method has the potential for even more quantitative predictions when key experimental parameters (such as the charge carrier density of the nano-wire or receptor density on the device surface) can be determined (and reported) more accurately.

Specific and reversible immobilization of histidine-tagged proteins on functionalized silicon nanowires.

Silicon nanowire (Si NW)-based field effect transistors (FETs) have shown great potential as biosensors (bioFETs) for ultra-sensitive and label-free detection of biomolecular interactions. Their sensitivity depends not only on the device properties, but also on the function of the biological recognition motif attached to the Si NWs. In this study, we show that SiNWs can be chemically functionalized with Ni:NTA motifs, suitable for the specific immobilization of proteins via a short polyhistidine tag (His-tag) at close proximity to the SiNW surface. We demonstrate that the proteins preserve their function upon immobilization onto SiNWs. Importantly, the protein immobilization on the Si NWs is shown to be reversible after addition of EDTA or imidazole, thus allowing the regeneration of the bioFET when needed, such as in the case of proteins having a limited lifetime. We anticipate that our methodology may find a generic use for the development of bioFETs exploiting functional protein assays because of its high compatibility to various types of NWs and proteins.