Structured illumination microscopy

Illumination plays an important role in optical microscopy. Kohler illumination, introduced more than a century ago, has been the backbone of optical microscopes. The last few decades have seen the evolution of new illumination techniques meant to improve certain imaging capabilities of the microscope. Most of them are, however, not amenable for wide-field observation and hence have restricted use in microscopy applications such as cell biology and microscale profile measurements. The method of structured illumination microscopy has been developed as a wide-field technique for achieving higher performance. Additionally, it is also compatible with existing microscopes. This method consists of modifying the illumination by superposing a well-defined pattern on either the sample itself or its image. Computational techniques are applied on the resultant images to remove the effect of the structure and to obtain the desired performance enhancement. This method has evolved over the last two decades and has emerged as a key illumination technique for optical sectioning, super-resolution imaging, surface profiling, and quantitative phase imaging of microscale objects in cell biology and engineering. In this review, we describe various structured illumination methods in optical microscopy and explain the principles and technologies involved therein. (C) 2015 Optical Society of America

Structured Illumination Microscopy and a Quantitative Image Analysis for the Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse Model of Sarcoma.

Intraoperative assessment of surgical margins is critical to ensuring residual tumor does not remain in a patient. Previously, we developed a fluorescence structured illumination microscope (SIM) system with a single-shot field of view (FOV) of 2.1 × 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 μm). The goal of this study was to test the utility of this technology for the detection of residual disease in a genetically engineered mouse model of sarcoma. Primary soft tissue sarcomas were generated in the hindlimb and after the tumor was surgically removed, the relevant margin was stained with acridine orange (AO), a vital stain that brightly stains cell nuclei and fibrous tissues. The tissues were imaged with the SIM system with the primary goal of visualizing fluorescent features from tumor nuclei. Given the heterogeneity of the background tissue (presence of adipose tissue and muscle), an algorithm known as maximally stable extremal regions (MSER) was optimized and applied to the images to specifically segment nuclear features. A logistic regression model was used to classify a tissue site as positive or negative by calculating area fraction and shape of the segmented features that were present and the resulting receiver operator curve (ROC) was generated by varying the probability threshold. Based on the ROC curves, the model was able to classify tumor and normal tissue with 77% sensitivity and 81% specificity (Youden's index). For an unbiased measure of the model performance, it was applied to a separate validation dataset that resulted in 73% sensitivity and 80% specificity. When this approach was applied to representative whole margins, for a tumor probability threshold of 50%, only 1.2% of all regions from the negative margin exceeded this threshold, while over 14.8% of all regions from the positive margin exceeded this threshold.

超分辨远场生物荧光成像——突破光学衍射极限

长期以来,远场光学荧光显微镜凭借其非接触、无损伤、可探测样品内部等优点,一直是生命科学中最常用的观测工具。但由于衍射极限的存在,使传统的宽场光学显微镜横向和纵向的分辨率分别仅约为230 nm和1000 nm。为了揭示细胞内分子尺度的动态和结构特征,提高光学显微镜分辨率成为生命科学发展的迫切要求,在远场荧光显微镜的基础上,科学家们已经发展出许多实用的提高分辨率甚至超越分辨率极限的成像技术。例如,采用横向结构光照明提高横向分辨率到约100 nm,利用纵向驻波干涉效应将纵向分辨率提高5~10倍。然而,直到在光学荧光显微镜中引入非线性效应后,衍射极限才被真正突破,如受激荧光损耗显微镜利用非线性效应实现了30~50 nm的三维分辨率。另外应用荧光分子之间能量转移共振原理以及单荧光分子定位技术也可以突破衍射极限,甚至可以将分子定位精度提高到几个纳米的量级。

傅立叶分解法荧光层析成像

本文提出一种基于结构光照明和傅立叶分解方法的荧光层析成像技术，该技术首先将激发光的强度沿着光轴方向调制成余弦函数，然后用此激发光对样品作传统的二维扫描，在每一个扫描位置余弦函数的频率在一定的范围内扫描，同时一一对应地记录下所发出的荧光强度。只要对所纪录的荧光序列做一个简单的傅立叶变换，即可以得到此位置样品沿着光轴方向的荧光团分布。这样通过一个传统的二维扫描，就可以得到一个三维的阳样品分布。

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Helium ion microscopy visualizes lipid nanodomains in mammalian cells

Cell membranes are composed of two-dimensional bilayers of amphipathic lipids, which allow a lateral movement of the respective membrane components. These components are arranged in an inhomogeneous manner as transient micro- and nanodomains, which are believed to be crucially involved in the regulation of signal transduction pathways in mammalian cells. Because of their small size (diameter 10-200 nm), membrane nanodomains cannot be directly imaged using conventional light microscopy. Here, we present direct visualization of cell membrane nanodomains by helium ion microscopy (HIM). We show that HIM is capable to image biological specimens without any conductive coating, and that HIM images clearly allow the identification of nanodomains in the ultrastructure of membranes with 1.5 nm resolution. The shape of these nanodomains is preserved by fixation of the surrounding unsaturated fatty acids while saturated fatty acids inside the nanodomains are selectively removed. Atomic force microscopy, fluorescence microscopy, 3D structured illumination microscopy and direct stochastic optical reconstruction microscopy provide additional evidence that the structures in the HIM images of cell membranes originate from membrane nanodomains. The nanodomains observed by HIM have an average diameter of 20 nm and are densely arranged with a minimal nearest neighbor distance of ~15 nm.

Coding Strategies for X-ray Tomography

This work focuses on the construction and application of coded apertures to compressive X-ray tomography. Coded apertures can be made in a number of ways, each method having an impact on system background and signal contrast. Methods of constructing coded apertures for structuring X-ray illumination and scatter are compared and analyzed. Apertures can create structured X-ray bundles that investigate specific sets of object voxels. The tailored bundles of rays form a code (or pattern) and are later estimated through computational inversion. Structured illumination can be used to subsample object voxels and make inversion feasible for low dose computed tomography (CT) systems, or it can be used to reduce background in limited angle CT systems.

On the detection side, coded apertures modulate X-ray scatter signals to determine the position and radiance of scatter points. By forming object dependent projections in measurement space, coded apertures multiplex modulated scatter signals onto a detector. The multiplexed signals can be inverted with knowledge of the code pattern and system geometry. This work shows two systems capable of determining object position and type in a 2D plane, by illuminating objects with an X-ray `fan beam,' using coded apertures and compressive measurements. Scatter tomography can help identify materials in security and medicine that may be ambiguous with transmission tomography alone.

Shadows : Re-visualising the shark. Developing a framework for hybrid photography in the illumination of nonhuman animal and ecological perspectives at Heron Island and Gladstone, Great Barrier Reef

This study investigated how and to what degree “hybrid photography”—the simultaneous use of indexical and fictional properties and strategies— innovates the representation of animals within animalcentric, ecocentric frameworks. Design theory structured this project’s Practice-led, Visual research methodology framework. Grounded theory processes articulated emerging categories of hybrid photography through systematically and comparatively treating animal photography works for reflexive analysis. Design theory then applied and clarified categories, developing practice that re-visualised shark perspectives as new ecological discourse. Shadows, a creative practice installation, realised a full-scale photographic investigation into shark and marine animal realities of a specific environment—Heron Island and Gladstone, Great Barrier Reef—facing ecological crisis from dredging and development at Gladstone Harbour. Works rendered and explored hybrid photography’s capacity for illuminating nonhuman animals, in particular, sharks, and comprise 65% of this project’s weighting. This exegetical paper offers a definition, strategies and evaluation of hybrid photography in unsettling animal perspectives as effective ecological discourse, and comprises 35%.

Synthesis of self-light-scattering wrinkle structured ZnO photoanode by sol-gel method for dye-sensitized solar cells

A special morphological zinc oxide (ZnO) photoanode for dye-sensitized solar cell was fabricated by simple sol-gel drop casting technique. This film shows a wrinkled structure resembling the roots of banyan tree, which acts as an effective self scattering layer for harvesting more visible light and offers an easy transport path for photo-injected electrons. These ZnO electrode of low thickness (similar to 5 mu m) gained an enhanced short-circuit current density of 6.15 mA/cm(2), open-circuit voltage of 0.67 V, fill factor of 0.47 and overall conversion efficiency of 1.97 % under 1 sun illumination. This shows a high conversion efficiency and a superior performance than that of ZnO nanoparticle-based photoanode (eta similar to 1.13 %) of high thickness (similar to 8 mu m).

A structured return to the 'Fourth Estate': interviews and inquiry that challenge entrenched authorities' 'knowledge'

Contemporary debates on the role of journalism in society are continuing the tradition of downplaying the role of proactive journalism - generally situated under the catchphrase of the Fourth Estate - in public policy making. This paper puts the case for the retention of a notion of a proactive form of journalism which can be broadly described as "investigative ", because it is important to the public policy process in modern democracies. It argues that critiques that downplay the potential of this form of journalism are flawed and overly deterministic. Finally. it seeks to illustrate how journalists can proactively inquire in ways that are relevant to the lives ofpeople in a range of settings, and that question elite sources in the interests ofthose people.