The Movement of Dance

These series of paintings displays a way skeletons can be shown and not just associated with death but in a fun and whimsical way shown through dance. I am making are about full body portraits of skeletons that are in costumes while in dancing poses. This is similar to the pictures in dance institution of the dancer. The influence comes from my own childhood with dancing is shared by using the colors of the costumes as very bright colors. The usage of the skeletons is the purest form of the body which can represent anyone and can feel more related towards the work. I like to play with the anatomy of the still figure and use movement in the figure much like Cezanne’s paintings were with color movement. Degas is another influence for my series because he works with dancers and their environment they’re in. The brush strokes of Cezanne and colors he used will he bought in through my background and figure with neutrals will balance out the costumes.The colors of the background is supposed to show movement more than the skeletons itself but isn’t the most important movement of the painting. The costumes that are vibrant also shows movement happening as well. The different dances I will be showing in the series is ballet, tap and jazz. The dances poses that are picked resonances with me because those were the very first dance styles I’ve learned. Conclusion: The body of work focuses on movement of the form and background. With the background the form compliment each other to show a tonality through action

The lowest crossing in 2D critical percolation

We study the following problem for critical site percolation on the triangular lattice. Let A and B be sites on a horizontal line e separated by distance n. Consider, in the half-plane above e, the lowest occupied crossing R from the half-line left of A to the half-line right of B. We show that the probability that R has a site at distance smaller than m from AB is of order (log (n/m))^{-1}, uniformly in 1 <= m < n/2. Much of our analysis can be carried out for other two-dimensional lattices as well.Comment: 16 pages, Latex, 2 eps figures, special macros: percmac.tex. Submitted to Annals of Probabilit

Germline genetic variation in prostate susceptibility does not predict outcomes in the chemoprevention trials PCPT and SELECT

Background The development of prostate cancer can be influenced by genetic and environmental factors. Numerous germline SNPs influence prostate cancer susceptibility. The functional pathways in which these SNPs increase prostate cancer susceptibility are unknown. Finasteride is currently not being used routinely as a chemoprevention agent but the long term outcomes of the PCPT trial are awaited. The outcomes of the SELECT trial have not recommended the use of chemoprevention in preventing prostate cancer. This study investigated whether germline risk SNPs could be used to predict outcomes in the PCPT and SELECT trial. Methods Genotyping was performed in European men entered into the PCPT trial (n = 2434) and SELECT (n = 4885). Next generation genotyping was performed using Affymetrix® Eureka™ Genotyping protocols. Logistic regression models were used to test the association of risk scores and the outcomes in the PCPT and SELECT trials. Results Of the 100 SNPs, 98 designed successfully and genotyping was validated for samples genotyped on other platforms. A number of SNPs predicted for aggressive disease in both trials. Men with a higher polygenic score are more likely to develop prostate cancer in both trials, but the score did not predict for other outcomes in the trial. Conclusion Men with a higher polygenic risk score are more likely to develop prostate cancer. There were no interactions of these germline risk SNPs and the chemoprevention agents in the SELECT and PCPT trials

Engineered nanotherapeutics for pulmonary aerosol delivery

Despite centuries of use and widespread application, aerosol delivery of therapeutics remains limited to a small subset of diseases and active pharmaceutical ingredients, mainly restricted to small molecule delivery for asthma management. Respiratory diseases which would benefit from direct and localized treatment span a much larger landscape; chronic obstructive pulmonary disease (COPD), lower respiratory infections, and lung cancers alone globally contribute 7.8 million annual deaths, with a reported 117 million pulmonary cases (~37% of population, 2012) and over $88 billion in health care costs in the US[1, 2]. To expand the application of aerosol delivery, novel approaches are needed. To address this need, we have explored various applications of nanoparticle immune engineering for respiratory therapeutics[3]. Incorrect immune responses lie at the heart of most respiratory diseases and advances in these therapeutic areas requires consideration of the unique environment. Notably, the lung has an abundance of antigen presenting cells (APCs), such as macrophages and dendritic cells (DC), which phagocytose foreign materials at the air-lung interface. There are a number of lung-specific APC populations[4, 5]. Some subsets are well understood, however, other specialized subsets have only recently been identified due to historic challenges in differentiating these populations[6, 7]. Thus, there are many remaining questions as to the division of labor between these cells, their significance in different disease conditions, and their interactions with other adjacent cell populations at the mucosal interface[8]. Advancing this understanding is critical to develop new therapeutics; APCs are poised as the gatekeepers to lung regulation and lung DC-subset specifically are likely cellular targets for therapeutic intervention[9]. In order to better understand how these lung innate immune cells respond to inhaled particle therapeutics, we have developed sets of engineered particles with defined physical properties that originate at the molecular level. We have developed a series of metal organic framework (MOF) nanoparticle carriers with independently tunable particle size and internal porosity, enabling systematic investigation of the effect of particle pore structure on cellular interactions. These UIO-66 MOF derivatives have not only been optimized as pulmonary aerosol carriers but provide critical insight on the role of internal particle porosity following cellular internalization. To further modulate the lung immune environment and evaluate the role of ligand surface density on immune-modulation, we simultaneously developed a series of degradable polymeric nanoparticle carriers with controlled surface densities of two Toll-like receptor (TLR) ligands, lipopolysaccharide (LPS), corresponding to TLR-4, and CpG oligodeoxynucleotide, corresponding to TLR-9[10]. Our in vitro results with murine bone marrow derived macrophages and in vivo studies following a direct instillation to murine airways both support a trade-off between particle dosage and optimal surface density; proinflammatory cytokine production was driven by the distribution of the adjuvant dose to a maximal number of innate cells, whereas the upregulation of costimulatory molecules on individual cells required an optimal density of TLR ligand on the particle surface. Taken together, results from these two sets of particle types demonstrate that both particle porosity and ligand surface density are critical parameters for tight control of immune stimulation and association with lung APCs and provide a foundation to build pathogen mimicking particle (PMP) vaccines and immunostimulatory therapeutics. References: 1. WHO: World Health Organization 2012. 2. NIH: National Heart, Lung, and Blood Institute 2012. 3. Moon, J. J.; Huang, B.; Irvine, D. J., Advanced materials (Deerfield Beach, Fla.) 2012, 24 (28), 3724-46. 4. Guilliams, M.; Lambrecht, B. N.; Hammad, H., Mucosal Immunol 2013, 6 (3), 464-73. 5. Kopf, M.; Schneider, C.; Nobs, S. P., Nat Immunol 2015, 16 (1), 36-44. 6. Blank, F.; Stumbles, P. A.; Seydoux, E.; Holt, P. G.; Fink, A.; Rothen-Rutishauser, B.; Strickland, D. H.; von Garnier, C., Am J Respir Cell Mol Biol 2013, 49 (1), 67-77. 7. Fytianos, K.; Drasler, B.; Blank, F.; von Garnier, C.; Seydoux, E.; Rodriguez-Lorenzo, L.; Petri-Fink, A.; Rothen-Rutishauser, B., Nanomedicine (Lond) 2016, 11 (18), 2457-2469. 8. Hasenberg, M.; Stegemann-Koniszewski, S.; Gunzer, M., Immunol Rev 2013, 25 (1), 189-214. 9. Zhao, L.; Seth, A.; Wibowo, N.; Zhao, C. X.; Mitter, N.; Yu, C.; Middelberg, A. P., Vaccine 2014, 32 (3), 327-37. 10. Noble, J.; Zimmerman, A.; Fromen, C. A., ACS Biomater Sci Eng 2017, 3 (4), 560-571