Aydogan Ozcan - US grants

CBET-0754880, Ozcan

The proposed research plan covers the development of a new form of high resolution microscope by using an array of resonant nanostructures. This novel microscopy modality, which is termed as NanoArray based Microscopy (NAM) can improve the spatial resolution of a low numerical aperture (NA) microscope by e.g., 5 fold without degrading its large field-of-view (FOV). As a result, NAM can achieve a spatial resolution of ~500 nm over ~5 mm2 FOV, and a fast image acquisition speed of >200 mm2/min. Furthermore, the proposed NAM concept can also be extended to the mid-infrared part of the spectrum, providing a resolution of ~2 microns in the spectral wavelength region of 5-16 microns, which contains unique chemical signatures of many biomolecules. The broad goal of this proposal is to merge the concepts of microscopy
with nanophotonics and plasmonics to enable new imaging concepts.

[unreadable] DESCRIPTION (provided by applicant): To achieve high spatial resolution, most optical microscopes rely on expensive components such as high numerical aperture objectives or other lenses. Due to such free-space components, most high resolution microscopes still remain bulky, making them harder to integrate with cost-effective and miniaturized systems. However, in medicine/biology there exists a set of applications that would highly benefit from miniaturized high resolution microscopes that are ideally on chip. For this purpose, the proposed research plan aims to develop a new form of lens-free, compact digital microscope using a densely packed array of on chip nano-apertures. By properly designing an array of metallic nano-apertures, a high spatial resolution will be achieved even without using any lens or mechanical scanning. For this end, the designed nano-array will be fabricated onto a standard opto-electronic sensor array, and the object of interest will be in direct contact with the aperture array. As a result, the proposed on chip microscope can image two dimensional objects (>5 mm2 wide) at a high spatial resolution of d500 nm, and with a fast imaging speed of ~150 mm2/min. Overall, this application aims to advance the current state of on chip microscopy by using the key concepts of nano-photonics and plasmonics. Because the proposed approach is lensfree, it can be integrated with microfluidic systems in a compact space, and thus can significantly improve the way that high-throughput screening microscopy or point-of-care diagnostics are currently done. High resolution and rapid imaging technologies that can be integrated with disposable microfluidic devices are urgently needed today, especially for the developing world, where the resources are scarce. Another significant impact of the proposed imaging modality in health care may be in the field of histopathology. The proposed near-field imaging scheme can potentially enable quite rapid capturing of high resolution images of histopathology samples, which can then be transmitted over the internet to any physician in the world. This opportunity, which is termed "telepathology", will imply the global sharing of medical resources. For this end, this application may enable practical implementations of telepathology by significantly improving the imaging speed (>150 mm2/min). This rapid image acquisition speed may also have a significant impact on micro-array based genomics or proteomics, where massive amounts of high resolution data need to be collected in a short amount of time. [unreadable] [unreadable] PUBLIC HEALTH RELEVANCE: Lensfree On-Chip Near-field Microscopy based on Resonant Nano-Apertures Project Narrative We propose to develop a novel high resolution and lens-free digital microscope that is based on optical resonance properties of a specially designed array of nano-apertures fabricated on an opto-electronic sensor chip. This new microscopy approach does not require any mechanical scanning or objective-lenses, and therefore offers a simpler and more compact approach for high resolution near-field imaging. Furthermore, the image acquisition and computation time is fairly short, making it a quite fast imaging modality that can significantly improve the way that high-throughput screening microscopy or point-of-care diagnostics are currently done. [unreadable] [unreadable] [unreadable]

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."

0930501
Ozcan

Flow cytometry is a workhorse of modern cell biology and clinical diagnostics, but suffers from three significant downsides: (i) limited throughput; (ii) high cost; and (iii) challenges towards miniaturization while still keeping its throughput. Addressing these limitations is likely to increase the availability and application areas of cytometers, significantly transforming biomedical research and clinical analysis. In this proposal, to address the existing limitations of cell analysis platforms, the aim is to (1) Integrate inertial microfluidic focusing with an on-chip holographic imaging platform; and (2) Test the performance of this integrated system for conducting complete blood counts with white blood cell differentials. Given its compact and cost-effective design without sheath fluids or lenses, together with its ultra-large throughput, and unique holographic information content, the proposed on-chip cytometry platform is poised to have a transformative impact for stem cell, immunology & cancer related research, as well as clinical diagnostics especially in resource limited or point-of-care settings.
This proposal will also establish a complementary educational outreach program which will involve high school students from a predominantly underprivileged and socio-economically impacted neighborhood of San Fernando Valley, CA. Summer research projects, seminars and open house visits will serve the high school students to interact with a cutting edge research environment, helping to increase their scientific curiosity and shaping their career goals in science and engineering. Furthermore, during the timeline of this proposal, to better contribute to the development, recruitment, retention, and graduation of underrepresented engineering students on UCLA campus, several undergraduate research opportunities will be created to supplement the existing activities of the PI's in this regard. Finally, a new graduate level course titled "Lab-on-a-Chip Photonics"; will be developed, which aims to integrate "knowledge"; and "design"; aspects of engineering education into a single course.

DESCRIPTION (Provided by the applicant) Abstract: Micro-arrays provide a high-throughput platform for various key studies in functional-genomics, proteomics, epigenetics, medical-diagnostics and even tissue-engineering. Together with advanced biochemical detection, imaging and bioinformatics technologies, it is now possible to cost-effectively monitor the expression behavior of genes, proteins or other biomarkers, as well as screening the genome and proteome content of various cell lines, on-chip drug profiling or even detection of single-nucleotide-polymorphism. Therefore, micro-array technologies provide a vital platform for performing high-throughput screening experiments that shed light on our understanding of cellular, genomic, and proteomic processes occurring at the nano-scale. In this proposal, we aim to create the next-generation of micro-array technologies to achieve an unprecedented mega-throughput, i.e., label-free imaging of millions of DNA/protein microspots would be feasible per second. We term the broad-umbrella of these revolutionary technologies as Nano-plasmonic LUCAS. Specifically, we aim achieve a throughput of >120 cm2/second or >4.5 million spots/second for highlysensitive and label-free imaging of DNA/protein micro-arrays, which constitutes a speed improvement of >3 orders-of-magnitude when compared to the state-of-the-art. Label-free imaging is especially important not to perturb the natural bio-chemical, physical and structural properties of the original molecule-of-interest. It also makes the measurements much more quantitative, significantly improving the data quality;eliminates inconvenient labeling steps which further reduces the cost;and avoids cross-reactivity issues among secondary-probes which can significantly improve the detection of weak or transitional molecular interactions. This mega-throughput capability will revolutionize the speed of progress that is taken in proteomics/genetics research by orders-of-magnitude that could eventually lead to the development of improved strategies/therapies for combating previously intractable bio-medical problems and various diseases including cancer. Furthermore, the Nano-plasmonic LUCAS platform does not require any lenses, microscope-objectives or other bulk optical components, and therefore offers an extremely compact on-chip platform that can easily be merged with micro-fluidic systems to permit point-of-care operation. Public Health Relevance: In this high-risk high pay-off proposal, we aim to create the next generation of micro-array technologies to revolutionize the speed of progress that is taken in proteomics and genetics research by orders of magnitude that could eventually lead to the development of improved strategies and therapies for combating previously intractable bio-medical problems and various diseases including cancer.

0954482
Ozcan

The recent revolutionary progress in digital technologies together with novel image reconstruction algorithms and theories can fundamentally transform the way that we conduct cell microscopy, cytometry and medical diagnostics. With this vision, this proposal makes a systematic effort to highlight this timely opportunity to revolutionize cell microscopy by making it free of any lenses, lasers or other bulky optical components with a much simpler, compact and cost-effective imaging architecture especially suitable for telemedicine needs and requirements. Through incoherent lensfree cell holography & on-chip microscopy platform of this proposal (i.e., LUCAS), the PI proposes to compensate in the digital domain for the lack of complexity of optical components by recording individual phase & amplitude holograms of various cell types. These cell holograms also yield accurate reconstruction of microscopic images featuring sub-cellular resolution over a very large field of view (FOV) even at cell densities reaching up to ~0.4 Million cells/ìL. Merging cost-effective and compact LUCAS imagers with the state-of-the-art cell-phone technology will create numerous opportunities for telemedicine to improve health care especially in the developing world where medical facilities and infrastructure are extremely limited.

There is an urgent need for portable, rapid, sensitive and specific influenza surveillance systems worldwide. The PI proposes to fundamentally improve the diagnostic landscape of influenza within a flexible, cost-effective, and field portable telemedicine platform. They will develop a digital immunoassay system that makes use of novel electro-adaptive and programmable microfluidics technologies as well as cellphone based multispectral fluorescent cytometry and computational microscopy tools. The proposed system will create arrays of hundreds of thousands of encoded particles containing fluid droplets. These particles will be first segmented equally using inertial-microfluidic sorting so that there is a single particle per drop, where the presence of influenza subtype antigens and the associated enzyme-linked antibody sandwich will lead to an ?on or off? fluorescence signal in each drop. The number of drops lighting up (corresponding to specific color- and shape-coded particles with different subtype-specific antibodies) will then be imaged all in parallel using a cellphone-based multispectral imaging cytometry system. Through a custom-developed smart application running on the same cellphone, these immunoassay images will immediately be analyzed for sensitive and rapid detection of various influenza subtypes, where the test results will also be transmitted wirelessly to secure servers, enabling real-time spatio-temporal mapping and analysis of the disease.

PI: Ozcan, Aydogan
Institution: University of California-Los Angeles
Proposal number: 1444240
Title: EAGER: Mobile-phone based single molecule imaging of DNA and length quantification to analyze copy-number variations in genome

The aim of this proposal is to create a transformative fluorescent microscopy system that is integrated with next generation mobile-phones for imaging single DNA molecules. This field-portable imaging interface running on a smartphone will have the sensitivity and contrast to image single molecule DNA fragments over a large field of view. Demonstrating DNA imaging on a state-of-the-art mobile-phone would serve as a stepping stone to next-generation mobile micro-analysis, sensing and diagnostic tools and could lead to single molecule DNA sequencing on a smartphone.

The proposed design will have the capability to be broadly used in various clinical applications including early detection of cancers (e.g. stomach and brain), nervous system disorders and drug resistance in infectious diseases. This cellphone based single molecule imaging, DNA platform could also assist health-care professionals, epidemiologists and policy makers to track emerging trends and shed more light on cause-effect relationships.

Intellectual Description:
Single molecule imaging and DNA length quantification, both of which are currently not feasible using mobile-phone based imaging systems; require extreme detection sensitivity, signal-to-noise ratio (SNR), spatial resolution and automated sample handling and processing interfaces. To provide a transformative solution to these important tasks, the PI will design a multifunctional portable imaging device installed on a smartphone which will allow sample preparation and single molecule imaging within the same opto-mechanical attachment. This fluorescence microscope on a smartphone will be designed by integrating a laser diode, a disposable nano-channel chip, an external lens and a thin-film based emission filter in a robust attachment created by 3D printing techniques. High SNR fluorescence signal detection will be achieved by implementing high-angle/oblique illumination so that the direct excitation beam will not enter the low NA collection lens. They will also develop a compressive sampling based DNA length-estimation method which will utilize (i) the measured point spread function of the fluorescent microscope on the mobile-phone; (ii) the spatial sparsity of the objects (fluorescently labeled DNA molecules); and (iii) the linearity of the stretched DNA molecules within the field of view as a-priori constraints to estimate the length of the DNA fragment of interest with an accuracy that is significantly better than the resolution of their initial imaging system.

PI: Erickson, David
Proposal: 1343058
Title: INSPIRE Track 2: Public Health, Nanotechnology, and Mobility (PHeNoM)

This INSPIRE award brings together research areas traditionally supported by: the Biophotonics and Nanobiosensing Programs in the Chemical, Bioengineering, Environmental, and Transport Systems Division (CBET) of the Engineering Directorate (ENG); the Communications, Circuits and Sensing Systems Program in the Electrical, Communications and Cyber Systems Division (ECCS) of the ENG Directorate; the Science, Technology and Society Program in the Social and Economical Sciences Division of the Social, Behavioral and Economic Sciences Directorate (SBE); and the Smart Health and Wellbeing Program in the Information and Intelligent Systems Division (IIS) of the Computer & Information Science Engineering Directorate (CISE).

Significance
The science and technology enabled by the Public Health, Nanotechnology and Mobility (PHeNoM) project may ultimately lead to widespread access to health information obtainable from lab-on-chip technology. This research project could alter the domestic healthcare landscape by enabling earlier-stage detection of disease, reducing the cost of public healthcare delivery, and allowing individuals to take better control of their own well-being. Such advances require the integration of the social and technical contexts of health care device deployment. This integration is accomplished by gathering feedback on early versions of the technology and modifying future designs based on that initial feedback. Iterations between feedback and design are facilitated by research efforts that interpret the feedback and guide the development process. The ultimate transfer of the technology to the marketplace is enabled by a new education effort that involves a unique combination of coursework, business plan development, pre-seed grant workshops, and collaborations with existing start-ups in the mobile health space.

Technical Description
Advancements in nanotechnology and microfluidics have enabled the development of lab-on-chip devices that can detect and quantify protein, genetic, and other biochemical markers of diseases with precision. Currently-available personalized diagnostic devices are limited to conditions that require either frequent monitoring (e.g. glucose for diabetics) or "binary" results (e.g. pregnancy). The goals of the PHeNoM program are to demonstrate that deployment of lab-on-chip technology can be fundamentally altered by taking advantage of ubiquitous smartphone technology and show that the fusion of physical sensing and molecular assays on mobile platforms enable healthcare diagnostics that are more informative than either technology alone.

To meet these aims, the investigators are focusing their efforts on developing and deploying three systems that may have an immediate impact on advancing personalized healthcare in the United States: a Stress-Phone for long term stress management, a Nutri-Phone for bloodwork-enabled nutritional awareness, and a Hema-Phone for monitoring viral loading in HIV+ patients. Beyond the immediate merits of these technologies, the broader merit of this project is the demonstration of new "bioinfo-mobile" diagnostics that intertwine the advantages of mobility, computation, physical sensing, and biomolecular assays.

This Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) project focuses on the creation of a human-centered smart toolset and service system for on-site and ubiquitous quantification and automated charaterization/classification of nanosize objects. Nanoparticles are being used in more and more commercial and industrial products while their health and environmental implications are still under debate. The toxicity of nanomaterials not only varies among different materials, but is also highly dependent on the dose of exposure. Developing a sensitive method to detect the release and spatio-temporal distribution of nanoparticles in the environment as well as in daily lives is a high priority before their toxicity effects are fully understood via long-term toxicological studies. Despite this urgent need for widespread detection and quantification of nanoparticle distributions, current technologies are lacking appropriate features for ubiquitous and cost-effective mapping and quantification of nanoparticle contamination. This project aims to create a transformative and human-centered toolset for on-site and ubiquitous quantification and automated characterization of nanomaterials found in houses, workplaces and the environment based on the cost-effective integration of computational imaging and mobile sensing techniques with big data based dynamic machine learning algorithms.

The central challenge in this project is to translate the bulky and expensive laboratory equipment currently used for nanoparticle quantification and characterization to field-portable, easy-to-use, cost-effective, and rapid analysis devices and smart service systems aiming to be massively used by consumers in their daily routines. To solve this challenge, highly sensitive optical imaging systems will be developed based on mass-produced Complementary Metal-Oxide Semiconductor (CMOS) sensor chips embedded in mobile phones with extraordinary signal to noise ratios (SNR) and large fields-of-view for high-throughput machine learning based automated nanoparticle analysis and classification. One approach this will take is to combine computational microscopy with self-assembled nanolenses around nanoparticles that significantly enhance imaging SNR and contrast. The aim of this approach is to enable automated detection and sizing of individual nanoparticles, mono-dispersed samples, and complex poly-dispersed mixtures, where the sample concentrations can span ~5 orders-of-magnitude and particle sizes can range from 40 nm to millimeter-scale, which provide unmatched performance metrics compared to existing nanoparticle sizing approaches. Another approach that will be implemented is the development of highly sensitive multi-modal (e.g. fluorescence plus dark-field) mobile phone based microscopy platforms for distributed nanoparticle imaging and sensing. Furthermore, in terms of big data analysis and machine learning tools, the techniques in this project can adaptively learn "semantic" similarities that can be used for more accurate data classification. These techniques are unlike existing techniques developed so far in the literature. The extant technologies are based only on signal similarities, which do not work well on multi-modality data. The smart and adaptive methods of this project are the first in the literature that come with confidence bounds, that is, they not only have the capability to accurately classify the information, but they also provide guarantees about the accuracy of this classification, which is quite important for self-learning smart service systems. Through these field-portable devices that are integrated with adaptive big data based decision analytics and quantification algorithms, spatio-temporal maps of nanoparticle concentrations and size distributions in various consumer samples will be created for public or personal monitoring (e.g., measurements of waterborne/airborne particles at home, workplace, or airborne particles along a freeway, etc.).

The broader impacts of this transformative research include (1) The development of these nanoparticle sensing and quantification platforms and smart service systems will extend the boundaries of current optical metrology science, resulting in new advances in the fields of nanophotonics and optical microscopy (2) These devices will also be easy to translate into various biomedical, chemical and material science applications, significantly impacting the use and regulations of nanotechnologies in consumer market and related products. (3) This project would deliver a paradigm-shift by ubiquitous quantification and spatiotemporal mapping/monitoring of nanoparticle contamination and exposure even in non-laboratory settings, assisting in the revelation and better understanding of various cause-effect relationships at the consumer level that have remained unidentified so far due to the limitations of existing nano-imaging, detection and quantification technologies, also providing maps of potential health risks. (4) This project will also establish a complementary educational outreach program based in California.

The lead institution and primary partners included in this cross-organizational interdisciplinary project are: Lead Academic Institution: University of California, Los Angeles, CA, School of Engineering, Electrical and Bioengineering Departments; Primary Industrial Partner: Holomic LLC (Small Business located in Los Angeles, CA); Other Industrial Partner: Google Inc. (Large Business located in Mountain View, CA).

? DESCRIPTION (provided by applicant: Assessment and monitoring of the viral load of HIV+ patients and their adherence to antiretroviral (ART) therapy are critically important for controllig the course of the disease, assessing transmission risks, and monitoring of HIV infection within communities. Viral load measurements are currently conducted in laboratory settings using costly and bulky apparatus including benchtop optical microscopes and sample preparation steps that require advanced lab instruments, which are hard to find and operate in resource limited environments or at the patient's home. In addition to the complexity, cost and bulkiness of existing tools, HIV viral load measurement methods currently rely on blood drawing, which can in general create significant sanitary and safety concerns in resource limited settings or at home. The proposed research plan covers the development and testing of a field-portable and label-free flexible sensing platform that is based on surface plasmon resonant (SPR) properties of specially designed quasi three-dimensional metal nanostructures (MNS) which will be integrated with commercially available soft contact lenses to create a cost effective and non-invasive diagnostic tool that can work even at home for measuring the viral load of HIV+ patients using tear. This new sensing platform will be designed to achieve flexibility by constructing its sensing unit on flexible substrates to enable intimate, direct contact with curved or irregular surfaces such as the human eye without any additional sample retrieval or processing steps and without obscuring natural vision or causing user discomfort. In addition to the flexible plasmonic sensor integrated onto the contact lens surface, we will also create a field portable and cost- effective smart phone based spectral reader platform to specifically analyze and quantify the viral load through multi-spectral imaging and automated analysis of the built-in nano-sensor on the surface of each contact lens. Previous studies have shown that HIV particles exist in tear and ocular fluids of HIV+ patients, and therefore tracking HIV status through tear can present a much safer and simpler approach for monitoring of HIV+ patients and their adherence to ART. In addition to improving care adherence and non- invasively quantifying the viral load of HIV+ patients through tear films, this proposed platform will ultimately provide a simple, cost-effective and light-weight toolset for multiplexed biological and chemical sensing needs, enabling various other future biomedical applications of wearable sensors.

Chronic diseases such as diabetes and cardiovascular disease (CVD) are a leading cause of morbidity and mortality. Every 30 seconds one American will be diagnosed with diabetes and another will suffer a coronary event. These diseases are a burden in underserved communities across the US due to higher prevalence and reduced access to care. Overcoming this human and economic burden is a grand challenge. The vision for the NSF-ERC on Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) is to change the paradigm for the health of underserved populations by developing revolutionary, cost-effective technologies and systems at the point-of-care. Led by Gerard Coté at Texas A&M University in partnership with the University of California at Los Angeles, Rice University, and Florida International University, PATHS-UP brings outstanding expertise to overcome four barriers endemic to POC devices, the need to: be field deployable, have high accuracy, have low complexity, and be affordable. The mission of PATHS-UP is defined by two overarching goals: (1) to engineer transformative, robust, and affordable technologies to improve healthcare access, enhance the quality of service and life, and reduce healthcare costs and (2) to recruit and educate a diverse group of scientists and engineers who will lead the future in developing enabling technologies to improve health in underserved communities.

PATHS-UP will develop two transformative engineered systems to monitor key biomarkers (biochemical, biophysical, and behavioral) of chronic disease: a Lab-in-your-Palm (LiyP) and a Lab-on-a-Wrist (LoaW). The LiyP will be enabled by novel amplification biochips based on nano-engineered single-molecule chain reactions combined with innovative handheld computational imaging and modular spectroscopic instruments. The LoaW will be enabled by unique, "bar-code like" biochemical marker implants (grain of rice in size) coupled with a novel wrist-worn spectral imager to visualize the implant through tissue and innovative sensors to monitor biophysical markers (cuffless blood pressure, heart rate). PATHS-UP will also develop innovative algorithms that monitor behavior (diet, medication intake) and predict long-term complications. These enabling technologies are founded on rigorous research in biomaterials, nanoscale systems, sample enrichment, computational imaging, multimodal data integration, and machine learning. Testbeds include one-of-a-kind in vitro phantoms, human subject studies in controlled lab environments, and patients in underserved communities. Developing and integrating these transformational systems into communities requires a multidisciplinary team of engineers, medical doctors, public health experts, industry professionals, and community health leaders. Such broad technical scope and societal outreach go beyond traditional funding sources and require the formation of the PATHS-UP ERC. The team will use participatory design and community engagement to prevent PATHS-UP from merely throwing technologies at these communities, and instead develop technologies that seamlessly integrate into their lives.

Underserved communities in every US state have higher prevalence and less access to equitable healthcare services. Thus, many people in these communities go undiagnosed or are diagnosed late, which can lead to serious consequences. To address this challenge, PATHS-UP will develop advanced technologies to prevent, delay the onset, and manage diabetes and cardiovascular disease. This requires both the development of transformational health technologies and systems and a paradigm shift in how these technologies are integrated into communities. Beyond the obvious societal health impact of the Center?s systems, the students, post-docs, and faculty nurtured by the Center?s intellectual community will also be a significant outcome of PATHS-UP. The team has a passion to promote meaningful, lasting, engagement with K-College students, especially under-represented minorities and K-12 teachers in our partner underserved communities. PATHS-UP will provide experiential learning and new engineering/public health curriculum for college students, research experiences for K-12 students and their teachers, and opportunities for participatory design with key stakeholders and community engagement, to promote a rich intellectual environment. The team also has a history of entrepreneurship, having spun off biomedical companies with students, and see building the innovation ecosystem as a vital part of PATHS-UP.

? DESCRIPTION (provided by applicant: Assessment and monitoring of the viral load of HIV+ patients and their adherence to antiretroviral (ART) therapy are critically important for controllig the course of the disease, assessing transmission risks, and monitoring of HIV infection within communities. Viral load measurements are currently conducted in laboratory settings using costly and bulky apparatus including benchtop optical microscopes and sample preparation steps that require advanced lab instruments, which are hard to find and operate in resource limited environments or at the patient's home. In addition to the complexity, cost and bulkiness of existing tools, HIV viral load measurement methods currently rely on blood drawing, which can in general create significant sanitary and safety concerns in resource limited settings or at home. The proposed research plan covers the development and testing of a field-portable and label-free flexible sensing platform that is based on surface plasmon resonant (SPR) properties of specially designed quasi three-dimensional metal nanostructures (MNS) which will be integrated with commercially available soft contact lenses to create a cost effective and non-invasive diagnostic tool that can work even at home for measuring the viral load of HIV+ patients using tear. This new sensing platform will be designed to achieve flexibility by constructing its sensing unit on flexible substrates to enable intimate, direct contact with curved or irregular surfaces such as the human eye without any additional sample retrieval or processing steps and without obscuring natural vision or causing user discomfort. In addition to the flexible plasmonic sensor integrated onto the contact lens surface, we will also create a field portable and cost- effective smart phone based spectral reader platform to specifically analyze and quantify the viral load through multi-spectral imaging and automated analysis of the built-in nano-sensor on the surface of each contact lens. Previous studies have shown that HIV particles exist in tear and ocular fluids of HIV+ patients, and therefore tracking HIV status through tear can present a much safer and simpler approach for monitoring of HIV+ patients and their adherence to ART. In addition to improving care adherence and non- invasively quantifying the viral load of HIV+ patients through tear films, this proposed platform will ultimately provide a simple, cost-effective and light-weight toolset for multiplexed biological and chemical sensing needs, enabling various other future biomedical applications of wearable sensors.

ABSTRACT Crystal arthropathy is the most common type of inflammatory arthritis, caused by the deposition of either monosodium urate (MSU) or calcium pyrophosphate dihydrate (CPP) crystals in or around joints, clinically recognized as either gout or pseudogout. Diagnosis of crystal arthropathy can be established by identifying MSU or CPPD crystals in the synovial fluid with a compensated polarized light microscope (CPLM). CPLM has been the gold- standard diagnostic instrument for crystal arthropathy since 1961. However, given the limited field of view (FOV) of CPLM, examination for crystals can be laborious. Furthermore, the sensitivity of CPLM can be affected by crystal concentration, size, and birefringent properties (particularly for CPP crystals), as well as technician experience. There exists the need to develop an inexpensive high-resolution, wide-FOV polarized microscopic device for synovial fluid screening, with improved sensitivity. Lens-free on-chip microscopy has developed in the past decade. The advantages of the lens-free microscope include high-resolution, wide FOV, low cost and compact instrumentation. However, lens-free technology has not been adapted to perform polarized imaging due to a fundamental difference in its imaging principle. We have developed a way to overcome this challenge and have preliminary data showing the ability of our system to accurately detect both MSU and CPP crystals. The proposed lens-free polarized on-chip microscope will enable the rapid screening and sensitive detection of birefringent crystals in synovial fluid samples of patients, greatly improving the sensitivity and efficiency of gout and pseudogout diagnosis.

Microscopic imaging of tissue samples is a fundamental tool used for the diagnosis of various diseases and forms the workhorse of pathology and biological sciences. The clinically-established gold standard image of a tissue section is the result of a laborious process. This work will demonstrate the ability to virtually stain label-free tissue sections and will revolutionize the current paradigm for histological analysis.


To demonstrate deep learning-based virtual histology staining of label-free human tissue samples this proposal will use salivary gland, thyroid, kidney, liver and lung samples, and will use three commonly used stains: H&E (salivary gland and thyroid), Jones stain (kidney) and Masson's Trichrome (liver and lung). This proposal will determine the staining efficacy of the proposed approach for whole slide images and will blindly evaluate the virtually stained outputs with gold standard stained samples. The output of this proposed system will be validated by a group of pathologists who will compare histopathological features with the virtual staining technique against conventional histology techniques.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Plaque assays are widely used for measuring the infectious concentration of viral samples and form a very important tool for vaccine development, especially for the evaluation of the performance of new vaccines at the exploratory and preclinical stages. This standard method is laborious and takes days to get the results, and is subject to human errors since it depends on manual plaque counting. Molecular techniques such as polymerase chain reaction (PCR or reverse transcription PCR) and western blots can be used to quantify the viral genome. However, none of these methods provide information about the infectivity of the virus and cannot measure plaque forming units. This proposal aims to create a computational sensor platform for accelerated testing of SARSCoV-2 viability and infectivity using deep learning-based plaque assays and achieve accurate and automated plaque forming unit (PFU) measurements within hours as opposed to days with standard plaque assays.

The proposed computational imaging system will periodically capture coherent microscopic images of the cytopathogenic effects of viruses on cell cultures and analyze these time lapsed holographic images using deep neural networks (DNNs) for rapid detection of viral destruction of the cell monolayer. In addition to early and automated detection of plaque forming units, this unique platform will further make use of deep learning for high-throughput holographic image reconstruction of the assay volume to perform tile-scan imaging of the entire well plate within 5 min, corresponding to an imaging throughput of ~50 cm2/min. Powered by deep learning, this automated and cost-effective viral plaque monitoring platform can be transformative for a wide range of applications in microbiology and virology by significantly reducing the detection time without labeling or the need for an expert, or manual inspection. The project will also establish a complementary educational outreach program that will involve (1) public interviews and popular science articles in news media and internet; (2) undergraduate research opportunities in the PI?s laboratory involving minority students; and (3) graduate student training through organization of workshops, seminars and conferences. Furthermore, research projects, seminars and open house visits will serve undergrads and high school students (especially from minority groups) to interact with a cutting edge research environment, helping to increase their scientific curiosity and shaping their career goals in science and engineering.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.