Multi-Niche Human Bone Marrow On-A-Chip for Studying the Interactions of Adoptive CAR-T Cell Therapies with Multiple Myeloma

Multiple myeloma (MM), a cancer of bone marrow plasma cells, is the second-most common hematological malignancy. However, despite immunotherapies like chimeric antigen receptor (CAR)-T cells, relapse is nearly universal. The bone marrow (BM) microenvironment influences how MM cells survive, proliferate, and resist treatment. Yet, it is unclear which BM niches give rise to MM pathophysiology. Here, we present a 3D microvascularized culture system, which models the endosteal and perivascular bone marrow niches, allowing us to study MM-stroma interactions in the BM niche and model responses to therapeutic CAR-T cells. We demonstrated the prolonged survival of cell line-based and patient-derived multiple myeloma cells within our in vitro system and successfully flowed in donor-matched CAR-T cells. We then measured T cell survival, differentiation, and cytotoxicity against MM cells using a variety of analysis techniques. Our MM-on-a-chip system could elucidate the role of the BM microenvironment in MM survival and therapeutic evasion and inform the rational design of next-generation therapeutics.

TEASER

A multiple myeloma model can study why the disease is still challenging to treat despite options that work well in other cancers.

Spatial Morphoproteomic Features Predict Uniqueness of Immune Microarchitectures and Responses in Lymphoid Follicles

Multiplex imaging technologies allow the characterization of single cells in their cellular environments. Understanding the organization of single cells within their microenvironment and quantifying disease-status related biomarkers is essential for multiplex datasets. Here we proposed SNOWFLAKE, a graph neural network framework pipeline for the prediction of disease-status from combined multiplex cell expression and morphology in human B-cell follicles. We applied SNOWFLAKE to a multiplex dataset related to COVID-19 infection in humans and showed better predictive power of the SNOWFLAKE pipeline compared to other machine learning and deep learning methods. Moreover, we combined morphological features inside graph edge features to utilize attribution methods for extracting disease-relevant motifs from single-cell spatial graphs. The underlying subgraphs were further analyzed and associated with disease status across the dataset. We showed that SNOWFLAKE successfully extracted significant low dimensional embedding from subgraphs with a clear separation between disease status and helped characterize unique cellular interactions in the subgraphs. SNOWFLAKE is a generalizable pipeline for the analysis of multiplex imaging data modality by extracting disease-relevant subgraphs guided by graph-level prediction.

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet's ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

Subcellular spatially resolved gene neighborhood networks in single cells

Image-based spatial omics methods such as fluorescence in situ hybridization (FISH) generate molecular profiles of single cells at single-molecule resolution. Current spatial transcriptomics methods focus on the distribution of single genes. However, the spatial proximity of RNA transcripts can play an important role in cellular function. We demonstrate a spatially resolved gene neighborhood network (spaGNN) pipeline for the analysis of subcellular gene proximity relationships. In spaGNN, machine-learning-based clustering of subcellular spatial transcriptomics data yields subcellular density classes of multiplexed transcript features. The nearest-neighbor analysis produces heterogeneous gene proximity maps in distinct subcellular regions. We illustrate the cell-type-distinguishing capability of spaGNN using multiplexed error-robust FISH data of fibroblast and U2-OS cells and sequential FISH data of mesenchymal stem cells (MSCs), revealing tissue-source-specific MSC transcriptomics and spatial distribution characteristics. Overall, the spaGNN approach expands the spatial features that can be used for cell-type classification tasks.

Combinatorial treatment rescues tumour-microenvironment-mediated attenuation of MALT1 inhibitors in B-cell lymphomas

Activated B-cell-like diffuse large B-cell lymphomas (ABC-DLBCLs) are characterized by constitutive activation of nuclear factor κB driven by the B-cell receptor (BCR) and Toll-like receptor (TLR) pathways. However, BCR-pathway-targeted therapies have limited impact on DLBCLs. Here we used >1,100 DLBCL patient samples to determine immune and extracellular matrix cues in the lymphoid tumour microenvironment (Ly-TME) and built representative synthetic-hydrogel-based B-cell-lymphoma organoids accordingly. We demonstrate that Ly-TME cellular and biophysical factors amplify the BCR-MYD88-TLR9 multiprotein supercomplex and induce cooperative signalling pathways in ABC-DLBCL cells, which reduce the efficacy of compounds targeting the BCR pathway members Bruton tyrosine kinase and mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1). Combinatorial inhibition of multiple aberrant signalling pathways induced higher antitumour efficacy in lymphoid organoids and implanted ABC-DLBCL patient tumours in vivo. Our studies define the complex crosstalk between malignant ABC-DLBCL cells and Ly-TME, and provide rational combinatorial therapies that rescue Ly-TME-mediated attenuation of treatment response to MALT1 inhibitors.

Spatial subcellular organelle networks in single cells

Organelles play important roles in human health and disease, such as maintaining homeostasis, regulating growth and aging, and generating energy. Organelle diversity in cells not only exists between cell types but also between individual cells. Therefore, studying the distribution of organelles at the single-cell level is important to understand cellular function. Mesenchymal stem cells are multipotent cells that have been explored as a therapeutic method for treating a variety of diseases. Studying how organelles are structured in these cells can answer questions about their characteristics and potential. Herein, rapid multiplexed immunofluorescence (RapMIF) was performed to understand the spatial organization of 10 organelle proteins and the interactions between them in the bone marrow (BM) and umbilical cord (UC) mesenchymal stem cells (MSCs). Spatial correlations, colocalization, clustering, statistical tests, texture, and morphological analyses were conducted at the single cell level, shedding light onto the interrelations between the organelles and comparisons of the two MSC subtypes. Such analytics toolsets indicated that UC MSCs exhibited higher organelle expression and spatially spread distribution of mitochondria accompanied by several other organelles compared to BM MSCs. This data-driven single-cell approach provided by rapid subcellular proteomic imaging enables personalized stem cell therapeutics.

Single-Cell and Spatial Analysis of Emergent Organoid Platforms

Organoids have emerged as a promising advancement of the two-dimensional (2D) culture systems to improve studies in organogenesis, drug discovery, precision medicine, and regenerative medicine applications. Organoids can self-organize as three-dimensional (3D) tissues derived from stem cells and patient tissues to resemble organs. This chapter presents growth strategies, molecular screening methods, and emerging issues of the organoid platforms. Single-cell and spatial analysis resolve organoid heterogeneity to obtain information about the structural and molecular cellular states. Culture media diversity and varying lab-to-lab practices have resulted in organoid-to-organoid variability in morphology and cell compositions. An essential resource is an organoid atlas that can catalog protocols and standardize data analysis for different organoid types. Molecular profiling of individual cells in organoids and data organization of the organoid landscape will impact biomedical applications from basic science to translational use.

Spatially variant immune infiltration scoring in human cancer tissues

The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.

Extracellular Matrix in Synthetic Hydrogel-Based Prostate Cancer Organoids Regulate Therapeutic Response to EZH2 and DRD2 Inhibitors

Following treatment with androgen receptor (AR) pathway inhibitors, ≈20% of prostate cancer patients progress by shedding their AR-dependence. These tumors undergo epigenetic reprogramming turning castration-resistant prostate cancer adenocarcinoma (CRPC-Adeno) into neuroendocrine prostate cancer (CRPC-NEPC). No targeted therapies are available for CRPC-NEPCs, and there are minimal organoid models to discover new therapeutic targets against these aggressive tumors. Here, using a combination of patient tumor proteomics, RNA sequencing, spatial-omics, and a synthetic hydrogel-based organoid, putative extracellular matrix (ECM) cues that regulate the phenotypic, transcriptomic, and epigenetic underpinnings of CRPC-NEPCs are defined. Short-term culture in tumor-expressed ECM differentially regulated DNA methylation and mobilized genes in CRPC-NEPCs. The ECM type distinctly regulates the response to small-molecule inhibitors of epigenetic targets and Dopamine Receptor D2 (DRD2), the latter being an understudied target in neuroendocrine tumors. In vivo patient-derived xenograft in immunocompromised mice showed strong anti-tumor response when treated with a DRD2 inhibitor. Finally, we demonstrate that therapeutic response in CRPC-NEPCs under drug-resistant ECM conditions can be overcome by first cellular reprogramming with epigenetic inhibitors, followed by DRD2 treatment. The synthetic organoids suggest the regulatory role of ECM in therapeutic response to targeted therapies in CRPC-NEPCs and enable the discovery of therapies to overcome resistance.

Subcellular localization of biomolecules and drug distribution by high-definition ion beam imaging

Simultaneous visualization of the relationship between multiple biomolecules and their ligands or small molecules at the nanometer scale in cells will enable greater understanding of how biological processes operate. We present here high-definition multiplex ion beam imaging (HD-MIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added structurally-unmodified small molecules. With this technology, the atomic constituents of the biomolecules themselves can be used in our system as the “tag” and we demonstrate measurements down to ~30 nm lateral resolution. We correlated the subcellular localization of the chemotherapy drug cisplatin simultaneously with five subnuclear structures. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. Unexpectedly, cells surviving multi-drug treatment with cisplatin and the BET inhibitor JQ1 demonstrated near total cisplatin exclusion from the nucleus, suggesting that selective subcellular drug relocalization may modulate resistance to this important chemotherapeutic treatment. Multiplexed high-resolution imaging techniques, such as HD-MIBI, will enable studies of biomolecules and drug distributions in biologically relevant subcellular microenvironments by visualizing the processes themselves in concert, rather than inferring mechanism through surrogate analyses.

Multiplexed ion beam imaging can provide subcellular localisation information but with limited resolution. Here the authors report an ion beam imaging method with nanoscale resolution which they use to assess the subcellular distribution of cisplatin.

Virtual and augmented reality for biomedical applications

3D visualization technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) have gained popularity in the recent decade. Digital extended reality (XR) technologies have been adopted in various domains ranging from entertainment to education because of their accessibility and affordability. XR modalities create an immersive experience, enabling 3D visualization of the content without a conventional 2D display constraint. Here, we provide a perspective on XR in current biomedical applications and demonstrate case studies using cell biology concepts, multiplexed proteomics images, surgical data for heart operations, and cardiac 3D models. Emerging challenges associated with XR technologies in the context of adverse health effects and a cost comparison of distinct platforms are discussed. The presented XR platforms will be useful for biomedical education, medical training, surgical guidance, and molecular data visualization to enhance trainees' and students' learning, medical operation accuracy, and the comprehensibility of complex biological systems.

EPCT-25. SMO PROTEIN DEPLETION IN SHH MEDULLOBLASTOMAS USING MICROBUBBLE-ENHANCED ULTRASOUND AND SIRNA LOADED CATIONIC NANOPARTICLES

RNA-based therapies offer unique advantages for treating pediatric brain tumors. However, the systemic delivery remains a major problem due to degradation of unmodified RNA in biological fluids, poor brain accumulation, and poor cancer cell uptake or escape from the endosomal lipid bilayer barrier. While nanoparticle encapsulation can prolong circulation time and facilitate cellular uptake, their accumulation in brain tumor remains particularly poor due to their low permeability across the blood-brain barrier and limited intratumoral penetration. Focused ultrasound, when combined with circulating microbubbles (MB-FUS) provides a physical method to transiently modulate the brain tumor microenvironment (TME) and improve nanoparticle delivery. Here, we have examined the delivery of siRNA targeting the Smoothened (SMO) pathway, packaged in 50 nm cationic lipid-polymer hybrid nanoparticles (cLPH:siRNA-SMO), combined with MB-FUS in murine SmoA2 sonic hedgehog (SHH) medulloblastoma. At 30 hours after treatment, we observed the depletion of the SMO protein target, responsible for driving SHH medulloblastoma formation and growth, in mice that had received treatment with MB-FUS and cLPH:siRNA-SMO, but not with cLPH:siRNA-SMO alone. We also confirmed that SMO protein depletion was spatially achieved in the tumor regions with detected cLPH:siRNA-SMO using FISH assay, and that there was 15 fold induction of tumor cell apoptosis compared to tumors in mice that had received cLPH:siRNA-SMO alone. The limited induction of apoptosis was observed with either cLPH:siRNA (non-targeting) or MB-FUS and cLPH:siRNA (non-targeting), suggest that the observed apoptosis induction in the SmoA2 model was the direct result of SMO depletion rather than nonspecific effects of MB-FUS or cLPH:siRNA. Our findings provide a paradigm shift in drug delivery in brain tumors, where physical methods and nanotechnology are tuned together to develop rational strategies for the effective delivery of nucleic acids in brain tumors.

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Deep molecular profiling of biological tissues is an indicator of health and disease. We used imaging mass cytometry (IMC) to acquire spatially resolved 20-plex protein data in tissue sections from normal and chronic tonsillitis cases. We present SpatialViz, a suite of algorithms to explore spatial relationships in multiplexed tissue images by visualizing and quantifying single-cell granularity and anatomical complexity in diverse multiplexed tissue imaging data. Single-cell and spatial maps confirmed that CD68+ cells were correlated with the enhanced Granzyme B expression and CD3+ cells exhibited enrichment of CD4+ phenotype in chronic tonsillitis. SpatialViz revealed morphological distributions of cellular organizations in distinct anatomical areas, spatially resolved single-cell associations across anatomical categories, and distance maps between the markers. Spatial topographic maps showed the unique organization of different tissue layers. The spatial reference framework generated network-based comparisons of multiplex data from healthy and diseased tonsils. SpatialViz is broadly applicable to multiplexed tissue biology.

Single-cell analysis reveals effective siRNA delivery in brain tumors with microbubble-enhanced ultrasound and cationic nanoparticles

RNA-based therapies offer unique advantages for treating brain tumors. However, tumor penetrance and uptake are hampered by RNA therapeutic size, charge, and need to be "packaged" in large carriers to improve bioavailability. Here, we have examined delivery of siRNA, packaged in 50-nm cationic lipid-polymer hybrid nanoparticles (LPHs:siRNA), combined with microbubble-enhanced focused ultrasound (MB-FUS) in pediatric and adult preclinical brain tumor models. Using single-cell image analysis, we show that MB-FUS in combination with LPHs:siRNA leads to more than 10-fold improvement in siRNA delivery into brain tumor microenvironments of the two models. MB-FUS delivery of Smoothened (SMO) targeting siRNAs reduces SMO protein production and markedly increases tumor cell death in the SMO-activated medulloblastoma model. Moreover, our analysis reveals that MB-FUS and nanoparticle properties can be optimized to maximize delivery in the brain tumor microenvironment, thereby serving as a platform for developing next-generation tunable delivery systems for RNA-based therapy in brain tumors.

Nanoscopic subcellular imaging enabled by ion beam tomography

Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional (3D) subcellular MIBI is presented. Ion-beam tomography (IBT) compiles ion beam images that are acquired iteratively across successive, multiple scans, and later assembled into a 3D format without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, is then applied to the transformed ion image series, yielding 4-fold enhanced ion beam data cubes. To further generate 3D sub-ion-beam-width precision visuals, isolated ion molecules are localized in the raw ion beam images, creating an approach coined as SILM, secondary ion beam localization microscopy, providing sub-25 nm accuracy in original ion images. Using deep learning, a parameter-free reconstruction method for ion beam tomograms with high accuracy is developed for low-density targets. In cultured cancer cells and tissues, IBT enables accessible visualization of 3D volumetric distributions of genomic regions, RNA transcripts, and protein factors with 5 nm axial resolution using isotope-enrichments and label-free elemental analyses. Multiparameter imaging of subcellular features at near macromolecular resolution is implemented by the IBT tools as a general biocomputation pipeline for imaging mass spectrometry.

Spatially resolved 3D metabolomic profiling in tissues

Spatially resolved RNA and protein molecular analyses have revealed unexpected heterogeneity of cells. Metabolic analysis of individual cells complements these single-cell studies. Here, we present a three-dimensional spatially resolved metabolomic profiling framework (3D-SMF) to map out the spatial organization of metabolic fragments and protein signatures in immune cells of human tonsils. In this method, 3D metabolic profiles were acquired by time-of-flight secondary ion mass spectrometry to profile up to 189 compounds. Ion beams were used to measure sub-5-nanometer layers of tissue across 150 sections of a tonsil. To incorporate cell specificity, tonsil tissues were labeled by an isotope-tagged antibody library. To explore relations of metabolic and cellular features, we carried out data reduction, 3D spatial correlations and classifications, unsupervised K-means clustering, and network analyses. Immune cells exhibited spatially distinct lipidomic fragment distributions in lymphatic tissue. The 3D-SMF pipeline affects studying the immune cells in health and disease.

Cellular sociology regulates the hierarchical spatial patterning and organization of cells in organisms

Advances in single-cell biotechnology have increasingly revealed interactions of cells with their surroundings, suggesting a cellular society at the microscale. Similarities between cells and humans across multiple hierarchical levels have quantitative inference potential for reaching insights about phenotypic interactions that lead to morphological forms across multiple scales of cellular organization, namely cells, tissues and organs. Here, the functional and structural comparisons between how cells and individuals fundamentally socialize to give rise to the spatial organization are investigated. Integrative experimental cell interaction assays and computational predictive methods shape the understanding of societal perspective in the determination of the cellular interactions that create spatially coordinated forms in biological systems. Emerging quantifiable models from a simpler biological microworld such as bacterial interactions and single-cell organisms are explored, providing a route to model spatio-temporal patterning of morphological structures in humans. This analogical reasoning framework sheds light on structural patterning principles as a result of biological interactions across the cellular scale and up.

Isotopically Encoded Nanotags for Multiplexed Ion Beam Imaging

High-dimensional profiling of markers and analytes using approaches, such as barcoded fluorescent imaging with repeated labeling and mass cytometry has allowed visualization of biological processes at the single-cell level. To address limitations of sensitivity and mass-channel capacity, a nanobarcoding platform is developed for multiplexed ion beam imaging (MIBI) using secondary ion beam spectrometry that utilizes fabricated isotopically encoded nanotags. Use of combinatorial isotope distributions in 100 nm sized nanotags expands the labeling palette to overcome the spectral bounds of mass channels. As a proof-of-principle, a four-digit (i.e., 0001-1111) barcoding scheme is demonstrated to detect 16 variants of ²H, ¹⁹F, ^79/81Br, and ¹²⁷I elemental barcode sets that are encoded in silica nanoparticle matrices. A computational debarcoding method and an automated machine learning analysis approach are developed to extract barcodes for accurate quantification of spatial nanotag distributions in large ion beam imaging areas up to 0.6 mm². Isotopically encoded nanotags should boost the performance of mass imaging platforms, such as MIBI and other elemental-based bioimaging approaches.

COVID-19 Diagnostics, Tools, and Prevention

The Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), outbreak from Wuhan City, Hubei province, China in 2019 has become an ongoing global health emergency. The emerging virus, SARS-CoV-2, causes coughing, fever, muscle ache, and shortness of breath or dyspnea in symptomatic patients. The pathogenic particles that are generated by coughing and sneezing remain suspended in the air or attach to a surface to facilitate transmission in an aerosol form. This review focuses on the recent trends in pandemic biology, diagnostics methods, prevention tools, and policies for COVID-19 management. To meet the growing demand for medical supplies during the COVID-19 era, a variety of personal protective equipment (PPE) and ventilators have been developed using do-it-yourself (DIY) manufacturing. COVID-19 diagnosis and the prediction of virus transmission are analyzed by machine learning algorithms, simulations, and digital monitoring. Until the discovery of a clinically approved vaccine for COVID-19, pandemics remain a public concern. Therefore, technological developments, biomedical research, and policy development are needed to decipher the coronavirus mechanism and epidemiological characteristics, prevent transmission, and develop therapeutic drugs.

Multiplex Spatial Bioimaging for Combination Therapy Design

Multiplex spatial analyses dissect the heterogeneous cellular abundances and interactions in tumors. Single-cell bioimaging profiles many disease-associated protein biomarkers in patient biopsies to inform the design of cancer therapies. Guided by the mechanistic insights from spatial cellular maps, combination therapy can efficiently eliminate cancers with reduced off-targets, resistance, and relapse.

Digital posters for interactive cellular media and bioengineering education

Conventional posters are effective in disseminating progress reports in scientific meetings, but they fail to deliver the need for visualization of dynamic biological data and become costly with the increasing number of conferences and the reprinting needs for emerging research. Here we present digital posters that repurpose digital frames from the art community and experiment with multiplexed imaging movies of cells as a demonstration of the digital poster concept, providing an interactive and low-cost tool for next-generation sharing platforms.

3D-printed smartphone-based point of care tool for fluorescence- and magnetophoresis-based cytometry

In developing countries, there are often limited resources available to provide important medical diagnostics, which severely limits our ability to diagnose conditions and administer proper treatment, leading to high mortality rates for treatable conditions. Here, we propose a multiplex tool capable of density-based cell sorting via magnetic focusing in parallel with fluorescence imaging to provide highly specific clinical assays. While many cell sorting techniques and fluorescence microscopes generally are costly and require extensive user training, limiting accessibility and usability in developing countries, this device is compact, low-cost, and portable. The device can separate cells on the basis of density, which can be used to identify cell type and cell activity, and image the cells in either brightfield, darkfield, or fluorescent imaging modes using the built-in smartphone camera. The combination of these two powerful and versatile techniques - magnetic focusing and fluorescence imaging - will make this platform broadly applicable to a range of biomedical assays. Clinical applications include cell cytometry and immunocytochemistry-based assays in limited-resource settings, which can ultimately help to improve worldwide accessibility to medical diagnostics.

Bioart

Bioart is a creative practice that adapts scientific methods and draws inspiration from the philosophical, societal, and environmental implications of recombinant genetics, molecular biology, and biotechnology. Some bioartists foster inter- disciplinary relationships that blur distinctions between art and science. Others emphasize critical responses to emerging trends in the life sciences. Since bioart can be combined with realistic views of scientific developments, it may help inform the public about science. Artistic responses to biotechnology also integrate cultural commentary resembling political activism. Art is not only about ‘responses’, however. Bioart can also initiate new science and engineer- ing concepts, foster openness to collaboration and increasing scientific literacy, and help to form the basis of artists’ future relationships with the communities of biology and the life sciences.

Cellular identity at the single-cell level

A single cell creates surprising heterogeneity in a multicellular organism. While every organismal cell shares almost an identical genome, molecular interactions in cells alter the use of DNA sequences to modulate the gene of interest for specialization of cellular functions. Each cell gains a unique identity through molecular coding across the DNA, RNA, and protein conversions. On the other hand, loss of cellular identity leads to critical diseases such as cancer. Most cell identity dissection studies are based on bulk molecular assays that mask differences in individual cells. To probe cell-to-cell variability in a population, we discuss single cell approaches to decode the genetic, epigenetic, transcriptional, and translational mechanisms for cell identity formation. In combination with molecular instructions, the physical principles behind cell identity determination are examined. Deciphering and reprogramming cellular types impact biology and medicine.

Art on the Nanoscale and Beyond

Methods of forming and patterning materials at the nano- and microscales are finding increased use as a medium of artistic expression, and as a vehicle for communicating scientific advances to a broader audience. While sharing many attributes of other art forms, miniaturized art enables the direct engagement of sensory aspects such as sight and touch for materials and structures that are otherwise invisible to the eye. The historical uses of nano-/microscale materials and imaging techniques in arts and sciences are presented. The motivations to create artwork at small scales are discussed, and representations in scientific literature and exhibitions are explored. Examples are presented using semiconductors, microfluidics, and nanomaterials as the artistic media; these utilized techniques including micromachining, focused ion beam milling, two-photon polymerization, and bottom-up nanostructure growth. Finally, the technological factors that limit the implementation of artwork at miniature scales are identified, and potential future directions are discussed. As research marches toward even smaller length scales, innovative and engaging visualizations and artistic endeavors will have growing implications on education, communication, policy making, media activism, and public perception of science and technology.

Entrepreneurship

High-tech businesses are the driving force behind global knowledge-based economies. Academic institutions have positioned themselves to serve the high-tech industry through consulting, licensing, and university spinoffs. The awareness of commercialization strategies and building an entrepreneurial culture can help academics to efficiently transfer their inventions to the market to achieve the maximum value. Here, the concept of high-tech entrepreneurship is discussed from lab to market in technology-intensive sectors such as nanotechnology, photonics, and biotechnology, specifically in the context of lab-on-a-chip devices. This article provides strategies for choosing a commercialization approach, financing a startup, marketing a product, and planning an exit. Common reasons for startup company failures are discussed and guidelines to overcome these challenges are suggested. The discussion is supplemented with case studies of successful and failed companies. Identifying a market need, assembling a motivated management team, managing resources, and obtaining experienced mentors lead to a successful exit.

Lensfree optofluidic plasmonic sensor for real-time and label-free monitoring of molecular binding events over a wide field-of-view

We demonstrate a high-throughput biosensing device that utilizes microfluidics based plasmonic microarrays incorporated with dual-color on-chip imaging toward real-time and label-free monitoring of biomolecular interactions over a wide field-of-view of >20 mm(2). Weighing 40 grams with 8.8 cm in height, this biosensor utilizes an opto-electronic imager chip to record the diffraction patterns of plasmonic nanoapertures embedded within microfluidic channels, enabling real-time analyte exchange. This plasmonic chip is simultaneously illuminated by two different light-emitting-diodes that are spectrally located at the right and left sides of the plasmonic resonance mode, yielding two different diffraction patterns for each nanoaperture array. Refractive index changes of the medium surrounding the near-field of the nanostructures, e.g., due to molecular binding events, induce a frequency shift in the plasmonic modes of the nanoaperture array, causing a signal enhancement in one of the diffraction patterns while suppressing the other. Based on ratiometric analysis of these diffraction images acquired at the detector-array, we demonstrate the proof-of-concept of this biosensor by monitoring in real-time biomolecular interactions of protein A/G with immunoglobulin G (IgG) antibody. For high-throughput on-chip fabrication of these biosensors, we also introduce a deep ultra-violet lithography technique to simultaneously pattern thousands of plasmonic arrays in a cost-effective manner.

Spectral demultiplexing in holographic and fluorescent on-chip microscopy

Lensfree on-chip imaging and sensing platforms provide compact and cost-effective designs for various telemedicine and lab-on-a-chip applications. In this work, we demonstrate computational solutions for some of the challenges associated with (i) the use of broadband, partially-coherent illumination sources for on-chip holographic imaging, and (ii) multicolor detection for lensfree fluorescent on-chip microscopy. Specifically, we introduce spectral demultiplexing approaches that aim to digitally narrow the spectral content of broadband illumination sources (such as wide-band light emitting diodes or even sunlight) to improve spatial resolution in holographic on-chip microscopy. We also demonstrate the application of such spectral demultiplexing approaches for wide-field imaging of multicolor fluorescent objects on a chip. These computational approaches can be used to replace e.g., thin-film interference filters, gratings or other optical components used for spectral multiplexing/demultiplexing, which can form a desirable solution for cost-effective and compact wide-field microscopy and sensing needs on a chip.

Albumin testing in urine using a smart-phone

We demonstrate a digital sensing platform, termed Albumin Tester, running on a smart-phone that images and automatically analyses fluorescent assays confined within disposable test tubes for sensitive and specific detection of albumin in urine. This light-weight and compact Albumin Tester attachment, weighing approximately 148 grams, is mechanically installed on the existing camera unit of a smart-phone, where test and control tubes are inserted from the side and are excited by a battery powered laser diode. This excitation beam, after probing the sample of interest located within the test tube, interacts with the control tube, and the resulting fluorescent emission is collected perpendicular to the direction of the excitation, where the cellphone camera captures the images of the fluorescent tubes through the use of an external plastic lens that is inserted between the sample and the camera lens. The acquired fluorescent images of the sample and control tubes are digitally processed within one second through an Android application running on the same cellphone for quantification of albumin concentration in the urine specimen of interest. Using a simple sample preparation approach which takes ~5 min per test (including the incubation time), we experimentally confirmed the detection limit of our sensing platform as 5-10 μg mL(-1) (which is more than 3 times lower than the clinically accepted normal range) in buffer as well as urine samples. This automated albumin testing tool running on a smart-phone could be useful for early diagnosis of kidney disease or for monitoring of chronic patients, especially those suffering from diabetes, hypertension, and/or cardiovascular diseases.

Smart-phone based computational microscopy using multi-frame contact imaging on a fiber-optic array

We demonstrate a cellphone based contact microscopy platform, termed Contact Scope, which can image highly dense or connected samples in transmission mode. Weighing approximately 76 grams, this portable and compact microscope is installed on the existing camera unit of a cellphone using an opto-mechanical add-on, where planar samples of interest are placed in contact with the top facet of a tapered fiber-optic array. This glass-based tapered fiber array has ~9 fold higher density of fiber optic cables on its top facet compared to the bottom one and is illuminated by an incoherent light source, e.g., a simple light-emitting-diode (LED). The transmitted light pattern through the object is then sampled by this array of fiber optic cables, delivering a transmission image of the sample onto the other side of the taper, with ~3× magnification in each direction. This magnified image of the object, located at the bottom facet of the fiber array, is then projected onto the CMOS image sensor of the cellphone using two lenses. While keeping the sample and the cellphone camera at a fixed position, the fiber-optic array is then manually rotated with discrete angular increments of e.g., 1-2 degrees. At each angular position of the fiber-optic array, contact images are captured using the cellphone camera, creating a sequence of transmission images for the same sample. These multi-frame images are digitally fused together based on a shift-and-add algorithm through a custom-developed Android application running on the smart-phone, providing the final microscopic image of the sample, visualized through the screen of the phone. This final computation step improves the resolution and also removes spatial artefacts that arise due to non-uniform sampling of the transmission intensity at the fiber optic array surface. We validated the performance of this cellphone based Contact Scope by imaging resolution test charts and blood smears.

Computational imaging, sensing and diagnostics for global health applications

In this review, we summarize some of the recent work in emerging computational imaging, sensing and diagnostics techniques, along with some of the complementary non-computational modalities that can potentially transform the delivery of health care globally. As computational resources are becoming more and more powerful, while also getting cheaper and more widely available, traditional imaging, sensing and diagnostic tools will continue to experience a revolution through simplification of their designs, making them compact, light-weight, cost-effective, and yet quite powerful in terms of their performance when compared to their bench-top counterparts.

Increased space-bandwidth product in pixel super-resolved lensfree on-chip microscopy

Pixel-size limitation of lensfree on-chip microscopy can be circumvented by utilizing pixel-super-resolution techniques to synthesize a smaller effective pixel, improving the resolution. Here we report that by using the two-dimensional pixel-function of an image sensor-array as an input to lensfree image reconstruction, pixel-super-resolution can improve the numerical aperture of the reconstructed image by ~3 fold compared to a raw lensfree image. This improvement was confirmed using two different sensor-arrays that significantly vary in their pixel-sizes, circuit architectures and digital/optical readout mechanisms, empirically pointing to roughly the same space-bandwidth improvement factor regardless of the sensor-array employed in our set-up. Furthermore, such a pixel-count increase also renders our on-chip microscope into a Giga-pixel imager, where an effective pixel count of ~1.6–2.5 billion can be obtained with different sensors. Finally, using an ultra-violet light-emitting-diode, this platform resolves 225 nm grating lines and can be useful for wide-field on-chip imaging of nano-scale objects, e.g., multi-walled-carbon-nanotubes.

Wide-field optical detection of nanoparticles using on-chip microscopy and self-assembled nanolenses

The direct observation of nanoscale objects is a challenging task for optical microscopy because the scattering from an individual nanoparticle is typically weak at optical wavelengths. Electron microscopy therefore remains one of the gold standard visualization methods for nanoparticles, despite its high cost, limited throughput and restricted field-of-view. Here, we describe a high-throughput, on-chip detection scheme that uses biocompatible wetting films to self-assemble aspheric liquid nanolenses around individual nanoparticles to enhance the contrast between the scattered and background light. We model the effect of the nanolens as a spatial phase mask centred on the particle and show that the holographic diffraction pattern of this effective phase mask allows detection of sub-100 nm particles across a large field-of-view of >20 mm². As a proof-of-concept demonstration, we report on-chip detection of individual polystyrene nanoparticles, adenoviruses and influenza A (H1N1) viral particles.

A personalized food allergen testing platform on a cellphone

We demonstrate a personalized food allergen testing platform, termed iTube, running on a cellphone that images and automatically analyses colorimetric assays performed in test tubes toward sensitive and specific detection of allergens in food samples. This cost-effective and compact iTube attachment, weighing approximately 40 grams, is mechanically installed on the existing camera unit of a cellphone, where the test and control tubes are inserted from the side and are vertically illuminated by two separate light-emitting-diodes. The illumination light is absorbed by the allergen assay, which is activated within the tubes, causing an intensity change in the acquired images by the cellphone camera. These transmission images of the sample and control tubes are digitally processed within 1 s using a smart application running on the same cellphone for detection and quantification of allergen contamination in food products. We evaluated the performance of this cellphone-based iTube platform using different types of commercially available cookies, where the existence of peanuts was accurately quantified after a sample preparation and incubation time of ~20 min per test. This automated and cost-effective personalized food allergen testing tool running on cellphones can also permit uploading of test results to secure servers to create personal and/or public spatio-temporal allergen maps, which can be useful for public health in various settings.

High-throughput screening of large volumes of whole blood using structured illumination and fluorescent on-chip imaging

Undiluted blood samples are difficult to image in large volumes since blood constitutes a highly absorbing and scattering medium. As a result of this limitation, optical imaging of rare cells (e.g., circulating tumour cells) within unprocessed whole blood remains a challenge, demanding the use of special microfluidic technologies. Here we demonstrate a new fluorescent on-chip imaging modality that can rapidly screen large volumes of absorbing and scattering media, such as undiluted whole blood samples, for detection of fluorescent micro-objects at low concentrations (for example ≤50-100 particles/mL). In this high-throughput imaging modality, a large area microfluidic device (e.g., 7-18 cm(2)), which contains for example ~0.3-0.7 mL of undiluted whole blood sample, is directly positioned onto a wide-field opto-electronic sensor-array such that the fluorescent emission within the microchannel can be detected without the use of any imaging lenses. This microfluidic device is then illuminated and laterally scanned with an array of Gaussian excitation spots, which is generated through a spatial light modulator. For each scanning position of this excitation array, a lensfree fluorescent image of the blood sample is captured using the opto-electronic sensor-array, resulting in a sequence of images (e.g., 144 lensfree frames captured in ~36 s) for the same sample chip. Digitally merging these lensfree fluorescent images based on a maximum intensity projection (MIP) algorithm enabled us to significantly boost the signal-to-noise ratio (SNR) and contrast of the fluorescent micro-objects within whole blood, which normally remain undetected (i.e., hidden) using conventional uniform excitation schemes, involving plane wave illumination. This high-throughput on-chip imaging platform based on structured excitation could be useful for rare cell research by enabling rapid screening of large volume microfluidic devices that process whole blood and other optically dense media.

Giga-pixel lensfree holographic microscopy and tomography using color image sensors

We report Giga-pixel lensfree holographic microscopy and tomography using color sensor-arrays such as CMOS imagers that exhibit Bayer color filter patterns. Without physically removing these color filters coated on the sensor chip, we synthesize pixel super-resolved lensfree holograms, which are then reconstructed to achieve ∼350 nm lateral resolution, corresponding to a numerical aperture of ∼0.8, across a field-of-view of ∼20.5 mm². This constitutes a digital image with ∼0.7 Billion effective pixels in both amplitude and phase channels (i.e., ∼1.4 Giga-pixels total). Furthermore, by changing the illumination angle (e.g., ±50°) and scanning a partially-coherent light source across two orthogonal axes, super-resolved images of the same specimen from different viewing angles are created, which are then digitally combined to synthesize tomographic images of the object. Using this dual-axis lensfree tomographic imager running on a color sensor-chip, we achieve a 3D spatial resolution of ∼0.35 µm×0.35 µm×∼2 µm, in x, y and z, respectively, creating an effective voxel size of ∼0.03 µm³ across a sample volume of ∼5 mm³, which is equivalent to >150 Billion voxels. We demonstrate the proof-of-concept of this lensfree optical tomographic microscopy platform on a color CMOS image sensor by creating tomograms of micro-particles as well as a wild-type C. elegans nematode.

Lensless fluorescent on-chip microscopy using a fiber-optic taper

We demonstrate a lensfree on-chip fluorescent microscopy platform that can image fluorescently labeled cells over ~60 mm(2) field-of-view with <4 urn spatial resolution. In this lensfree imaging system, micro-objects of interest are directly located on a tapered fiber-optic faceplate which has > 5-fold higher density of fiber-optic waveguides in its top facet compared to the bottom facet. For excitation, an incoherent light source (e.g., a simple light emitting diode--LED) is used to pump fluorescent objects through a glass hemi-sphere interface. Upon interacting with the entire sample volume, the excitation light is rejected by total internal reflection process occurring at the bottom of the sample substrate. Fluorescent emission from the objects is then collected by the smaller facet of the tapered faceplate and is delivered to a detector-array with an image magnification of ~2.4X. A compressive sampling based decoding algorithm is used for sparse signal recovery, which further increases the space-bandwidth-product of our lensfree on-chip fluorescent imager. We validated the performance of this lensfree imaging platform using fluorescent micro-particles as well as labeled water-borne parasites (e.g., Giardia Muris cysts). Such a compact and wide-field fluorescent microscopy platform could be valuable for cytometry and rare cell imaging applications as well as for micro array research.

Lensless fluorescent microscopy on a chip

On-chip lensless imaging in general aims to replace bulky lens-based optical microscopes with simpler and more compact designs, especially for high-throughput screening applications. This emerging technology platform has the potential to eliminate the need for bulky and/or costly optical components through the help of novel theories and digital reconstruction algorithms. Along the same lines, here we demonstrate an on-chip fluorescent microscopy modality that can achieve e.g., <4 μm spatial resolution over an ultra-wide field-of-view (FOV) of >0.6-8 cm(2) without the use of any lenses, mechanical-scanning or thin-film based interference filters. In this technique, fluorescent excitation is achieved through a prism or hemispherical-glass interface illuminated by an incoherent source. After interacting with the entire object volume, this excitation light is rejected by total-internal-reflection (TIR) process that is occurring at the bottom of the sample micro-fluidic chip. The fluorescent emission from the excited objects is then collected by a fiber-optic faceplate or a taper and is delivered to an optoelectronic sensor array such as a charge-coupled-device (CCD). By using a compressive-sampling based decoding algorithm, the acquired lensfree raw fluorescent images of the sample can be rapidly processed to yield e.g., <4 μm resolution over an FOV of >0.6-8 cm(2). Moreover, vertically stacked micro-channels that are separated by e.g., 50-100 μm can also be successfully imaged using the same lensfree on-chip microscopy platform, which further increases the overall throughput of this modality. This compact on-chip fluorescent imaging platform, with a rapid compressive decoder behind it, could be rather valuable for high-throughput cytometry, rare-cell research and microarray-analysis.

Optofluidic fluorescent imaging cytometry on a cell phone

Fluorescent microscopy and flow cytometry are widely used tools in biomedical sciences. Cost-effective translation of these technologies to remote and resource-limited environments could create new opportunities especially for telemedicine applications. Toward this direction, here we demonstrate the integration of imaging cytometry and fluorescent microscopy on a cell phone using a compact, lightweight, and cost-effective optofluidic attachment. In this cell-phone-based optofluidic imaging cytometry platform, fluorescently labeled particles or cells of interest are continuously delivered to our imaging volume through a disposable microfluidic channel that is positioned above the existing camera unit of the cell phone. The same microfluidic device also acts as a multilayered optofluidic waveguide and efficiently guides our excitation light, which is butt-coupled from the side facets of our microfluidic channel using inexpensive light-emitting diodes. Since the excitation of the sample volume occurs through guided waves that propagate perpendicular to the detection path, our cell-phone camera can record fluorescent movies of the specimens as they are flowing through the microchannel. The digital frames of these fluorescent movies are then rapidly processed to quantify the count and the density of the labeled particles/cells within the target solution of interest. We tested the performance of our cell-phone-based imaging cytometer by measuring the density of white blood cells in human blood samples, which provided a decent match to a commercially available hematology analyzer. We further characterized the imaging quality of the same platform to demonstrate a spatial resolution of ~2 μm. This cell-phone-enabled optofluidic imaging flow cytometer could especially be useful for rapid and sensitive imaging of bodily fluids for conducting various cell counts (e.g., toward monitoring of HIV+ patients) or rare cell analysis as well as for screening of water quality in remote and resource-poor settings.

Wide-field lensless fluorescent microscopy using a tapered fiber-optic faceplate on a chip

We demonstrate lensless fluorescent microscopy over a large field-of-view of ~60 mm(2) with a spatial resolution of <4 µm. In this on-chip fluorescent imaging modality, the samples are placed on a fiber-optic faceplate that is tapered such that the density of the fiber-optic waveguides on the top facet is >5 fold larger than the bottom one. Placed on this tapered faceplate, the fluorescent samples are pumped from the side through a glass hemisphere interface. After excitation of the samples, the pump light is rejected through total internal reflection that occurs at the bottom facet of the sample substrate. The fluorescent emission from the sample is then collected by the smaller end of the tapered faceplate and is delivered to an opto-electronic sensor-array to be digitally sampled. Using a compressive sampling algorithm, we decode these raw lensfree images to validate the resolution (<4 µm) of this on-chip fluorescent imaging platform using microparticles as well as labeled Giardia muris cysts. This wide-field lensfree fluorescent microscopy platform, being compact and high-throughput, might provide a valuable tool especially for cytometry, rare cell analysis (involving large area microfluidic systems) as well as for microarray imaging applications.

Lensfree fluorescent on-chip imaging of transgenic Caenorhabditis elegans over an ultra-wide field-of-view

We demonstrate lensfree on-chip fluorescent imaging of transgenic Caenorhabditis elegans (C. elegans) over an ultra-wide field-of-view (FOV) of e.g., >2–8 cm² with a spatial resolution of ∼10µm. This is the first time that a lensfree on-chip platform has successfully imaged fluorescent C. elegans samples. In our wide-field lensfree imaging platform, the transgenic samples are excited using a prism interface from the side, where the pump light is rejected through total internal reflection occurring at the bottom facet of the substrate. The emitted fluorescent signal from C. elegans samples is then recorded on a large area opto-electronic sensor-array over an FOV of e.g., >2–8 cm², without the use of any lenses, thin-film interference filters or mechanical scanners. Because fluorescent emission rapidly diverges, such lensfree fluorescent images recorded on a chip look blurred due to broad point-spread-function of our platform. To combat this resolution challenge, we use a compressive sampling algorithm to uniquely decode the recorded lensfree fluorescent patterns into higher resolution images, demonstrating ∼10 µm resolution. We tested the efficacy of this compressive decoding approach with different types of opto-electronic sensors to achieve a similar resolution level, independent of the imaging chip. We further demonstrate that this wide FOV lensfree fluorescent imaging platform can also perform sequential bright-field imaging of the same samples using partially-coherent lensfree digital in-line holography that is coupled from the top facet of the same prism used in fluorescent excitation. This unique combination permits ultra-wide field dual-mode imaging of C. elegans on a chip which could especially provide a useful tool for high-throughput screening applications in biomedical research.

Lensfree sensing on a microfluidic chip using plasmonic nanoapertures

We demonstrate lensfree on-chip sensing within a microfluidic channel using plasmonic nanoapertures that are illuminated by a partially coherent quasimonochromatic source. In this approach, lensfree diffraction patterns of metallic nanoapertures located at the bottom of a microfluidic channel are recorded using an optoelectronic sensor-array. These lensfree diffraction patterns can then be rapidly processed, using phase recovery techniques, to back propagate the optical fields to an arbitrary depth, creating digitally focused complex transmission patterns. Cross correlation of these patterns enables lensfree on-chip sensing of the local refractive index surrounding the near-field of the plasmonic nanoapertures. Based on this principle, we experimentally demonstrate lensfree sensing of refractive index changes as small as ∼2×10(-3). This on-chip sensing approach could be quite useful for development of label-free microarray technologies by multiplexing thousands of plasmonic structures on the same microfluidic chip, which can significantly increase the throughput of sensing.

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

We demonstrate lensfree holographic microscopy on a chip to achieve approximately 0.6 microm spatial resolution corresponding to a numerical aperture of approximately 0.5 over a large field-of-view of approximately 24 mm2. By using partially coherent illumination from a large aperture (approximately 50 microm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans.

Lensless wide-field fluorescent imaging on a chip using compressive decoding of sparse objects

We demonstrate the use of a compressive sampling algorithm for on-chip fluorescent imaging of sparse objects over an ultra-large field-of-view (>8 cm(2)) without the need for any lenses or mechanical scanning. In this lensfree imaging technique, fluorescent samples placed on a chip are excited through a prism interface, where the pump light is filtered out by total internal reflection after exciting the entire sample volume. The emitted fluorescent light from the specimen is collected through an on-chip fiber-optic faceplate and is delivered to a wide field-of-view opto-electronic sensor array for lensless recording of fluorescent spots corresponding to the samples. A compressive sampling based optimization algorithm is then used to rapidly reconstruct the sparse distribution of fluorescent sources to achieve approximately 10 microm spatial resolution over the entire active region of the sensor-array, i.e., over an imaging field-of-view of >8 cm(2). Such a wide-field lensless fluorescent imaging platform could especially be significant for high-throughput imaging cytometry, rare cell analysis, as well as for micro-array research.

Lensfree on-chip imaging using nanostructured surfaces

We introduce the use of nanostructured surfaces for lensfree on-chip microscopy. In this incoherent on-chip imaging modality, the object of interest is directly positioned onto a nanostructured thin metallic film, where the emitted light from the object plane, after being modulated by the nanostructures, diffracts over a short distance to be sampled by a detector-array without the use of any lenses. The detected far-field diffraction pattern then permits rapid reconstruction of the object distribution on the chip at the subpixel level using a compressive sampling algorithm. This imaging modality based on nanostructured substrates could especially be useful to create lensfree fluorescent microscopes on a compact chip.

Wide field-of-view lens-free fluorescent imaging on a chip

We demonstrate an on-chip fluorescent detection platform that can simultaneously image fluorescent micro-objects or labeled cells over an ultra-large field-of-view of 2.5 cm x 3.5 cm without the use of any lenses, thin-film filters and mechanical scanners. Such a wide field-of-view lensless fluorescent imaging modality, despite its limited resolution, might be very important for high-throughput screening applications as well as for detection and counting of rare cells within large-area microfluidic devices.