Low-noise electronic readout for high-throughput, portable biomolecular detection in microchannel arrays

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (leaves 57-58).There's not much that can be done to make research easier - but excitement and passion are two key elements of success, and two of the many things I have learned from my advisor, Scott Manalis. It has been (and will continue to be) an awesome opportunity that I am especially thankful for, to work in nanoscale sensing with him. Perhaps the next best thing to a great advisor is having friends to work with who are equally as excited as me, more experienced, and many times smarter. I am forever indebted to all the members of the lab who have contributed to my biggest asset - knowledge. Special respect to those who bestow humour with the facts: Nebojsa, Johnson, Mike, Phil, and of course Thomas without whom I would have been in the lab a lot longer and in Europe a lot less. Thanks for coming to lab with a smile and for helping me leave with one. Places like MIT are excellent institutions, mostly because of their students. I am thankful to all of the graduate students in other labs which are always glad to give some words of advice or spend a few hours explaining something not so trivial to me. Especially to those in Professor Rahul Sarpeshkar's laboratory, especially Soumya and Scott. I am also very lucky to have great friends outside of the lab, for constant support, empathy and for bettering my overall well-being. Also to those who have come into my life and left at some point, I have gained so many more things from you than you may realize. Finally, to those who have probably contributed the most to my research success - without a single formula or circuit diagram, my family: Habibullah, Rosemin and Alizahra. You made me realize that as with life, struggle is the meaning of research. Defeat or victory is in the hands of God, but struggle itself is man's duty and should be his joy.by Rumi Chunara.S.M

From the User to the Medium: Neural Profiling Across Web Communities

Online communities provide a unique way for individuals to access information from those in similar circumstances, which can be critical for health conditions that require daily and personalized management. As these groups and topics often arise organically, identifying the types of topics discussed is necessary to understand their needs. As well, these communities and people in them can be quite diverse, and existing community detection methods have not been extended towards evaluating these heterogeneities. This has been limited as community detection methodologies have not focused on community detection based on semantic relations between textual features of the user-generated content. Thus here we develop an approach, NeuroCom, that optimally finds dense groups of users as communities in a latent space inferred by neural representation of published contents of users. By embedding of words and messages, we show that NeuroCom demonstrates improved clustering and identifies more nuanced discussion topics in contrast to other common unsupervised learning approaches

Electronic readout of microchannel resonators for precision mass sensing in solution by Rumi Chunara.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 115-120).Microfabricated transducers have enabled new approaches for detection of biomolecules and cells. Integration of electronics with these tools simplify systems and provide platforms for robust use outside of the laboratory setting. Suspended microchannel resonators (SMRs) are sensitive microfluidic platforms used to precisely measure the buoyant mass of single cells and monolayers of protein in fluid environments. Conventionally, micro cantilever deflection is measured by the optical-lever technique, wherein a laser beam is reflected off the cantilever onto a position sensitive photodiode. This thesis introduces microchannel resonators with electronic readout, eliminating the use of external optical components for resolving the sensor's resonant frequency. Piezo resistors have been fabricated on SMRs through ion implantation integrated with the existing SMR fabrication process. We fabricated two designs: one with a cantilever length of 210 pm and resonant frequency of -347 kHz, and the other with a cantilever length of 406 pm and resonant frequency of ~92 kHz. The work here builds upon knowledge of signal transduction from static and dynamic cantilever based sensors because the piezo resistors are implemented on vacuum encapsulated devices containing fluid. Electronic readout is shown to resolve the microchannel resonance frequency with an Allan variance of 5 x 10-18 (210 pm) and 2 x 1017 (406 pm) using a 100ms gate time, corresponding to a mass resolution of 0.1 and 0.4 fg respectively. This mass resolution calculated from piezoresistive readout frequency stability, is approximately 3X better than optical readout for the 210 pm device and 1.3X for the 406 pm device using the same gate time. Resolution is expected to improve with further optimization of the system. To demonstrate the readout, histograms of the buoyant masses of a mixture of size standard polystyrene beads (with nominal diameters 1.6, 1.8, and 2.0 pm) and budding yeast cells were made.Ph.D

Using search queries for malaria surveillance, Thailand

Background: Internet search query trends have been shown to correlate with incidence trends for select infectious diseases and countries. Herein, the first use of Google search queries for malaria surveillance is investigated. The research focuses on Thailand where real-time malaria surveillance is crucial as malaria is re-emerging and developing resistance to pharmaceuticals in the region. Methods: Official Thai malaria case data was acquired from the World Health Organization (WHO) from 2005 to 2009. Using Google correlate, an openly available online tool, and by surveying Thai physicians, search queries potentially related to malaria prevalence were identified. Four linear regression models were built from different sub-sets of malaria-related queries to be used in future predictions. The models’ accuracies were evaluated by their ability to predict the malaria outbreak in 2009, their correlation with the entire available malaria case data, and by Akaike information criterion (AIC). Results: Each model captured the bulk of the variability in officially reported malaria incidence. Correlation in the validation set ranged from 0.75 to 0.92 and AIC values ranged from 808 to 586 for the models. While models using malaria-related and general health terms were successful, one model using only microscopy-related terms obtained equally high correlations to malaria case data trends. The model built strictly of queries provided by Thai physicians was the only one that consistently captured the well-documented second seasonal malaria peak in Thailand. Conclusions: Models built from Google search queries were able to adequately estimate malaria activity trends in Thailand, from 2005–2010, according to official malaria case counts reported by WHO. While presenting their own limitations, these search queries may be valid real-time indicators of malaria incidence in the population, as correlations were on par with those of related studies for other infectious diseases. Additionally, this methodology provides a cost-effective description of malaria prevalence that can act as a complement to traditional public health surveillance. This and future studies will continue to identify ways to leverage web-based data to improve public health

Race, Ethnicity and National Origin-based Discrimination in Social Media and Hate Crimes Across 100 U.S. Cities

We study malicious online content via a specific type of hate speech: race, ethnicity and national-origin based discrimination in social media, alongside hate crimes motivated by those characteristics, in 100 cities across the United States. We develop a spatially-diverse training dataset and classification pipeline to delineate targeted and self-narration of discrimination on social media, accounting for language across geographies. Controlling for census parameters, we find that the proportion of discrimination that is targeted is associated with the number of hate crimes. Finally, we explore the linguistic features of discrimination Tweets in relation to hate crimes by city, features used by users who Tweet different amounts of discrimination, and features of discrimination compared to non-discrimination Tweets. Findings from this spatial study can inform future studies of how discrimination in physical and virtual worlds vary by place, or how physical and virtual world discrimination may synergize