Name: sivq-lcm protocol for the arcturusxt instrument
Uploaded: 2014-07-23T14:00:00.000+00:00
Duration: 7 min 37 s
Description: Watch this Scientific Journal Video about SIVQ-LCM Protocol for the ArcturusXT Instrument at JoVE.com

The study was supported in part by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Center for Cancer Research.

The described protocol was employed in accordance with NIH rules on the use of human tissue samples.
1. Tissue Preparation
<ol>
	<li>Prior to beginning, obtain human tissue specimens according to Institutional Review Board (IRB) protocols.</li>
	<li>Choose the type of tissue/cell block and corresponding processing method [formalin-fixed paraffin-embedded (FFPE), frozen, or ethanol-fixed paraffin-embedded (EFPE)]. Formalin fixation provides optimal histology, followed by ethanol fixation and flash frozen. However, fixation and tissue processing methods can affect DNA, RNA, and protein quantity and quality for downstream molecular analysis and should be considered.</li>
	<li>Cut the tissue/cell block sections onto the slide type (glass, membrane glass, or metal frame membrane) of choice.&#160;SIVQ analysis works equally well on all three slide types. Please note that the pseudo-coverslip method (described below) with xylenes and ethanol cannot be performed on the metal frame membrane slides since the slide must be inverted on the stage.</li>
	<li>Select a chemical- or IHC-based tissue stain to identify cells of interest from the background. Note that staining methods can also affect DNA, RNA, and protein quality and quantity of the tissue. Test the tissue after staining to assess baseline quality of biomolecules before proceeding with the protocol. SIVQ-LCM has been performed on tissue/cytology slides stained with: immunohistochemistry (IHC) with DAB15, immunofluorescence, fast red, de novo red, toluidine blue, and hematoxylin and eosin (H&#38;E) (unpublished data).</li>
</ol>
2. Specimen Imaging
<ol>
	<li>Load slides onto the motorized stage of the microdissection instrument and launch the related software. Select the check boxes to designate the positions of the loaded slides and ensure the captured image files are to be saved in jpeg format.</li>
	<li>Optimize the image quality by adjusting the brightness and focus of the image on the screen, using either the manual focus wheel or through the dissection instrument&#8217;s software.
	<ol>
		<li>Using the Image Toolbox within the dissection instrument&#8217;s software, set the lamp brightness and camera gain appropriately. Example values are brightness = 60 and gain = 220, with the diffuser.</li>
		<li>Focus either manually or with the autofocus feature in the software.</li>
	</ol>
	</li>
	<li>Capture a thumbnail overview image of the slide to provide a roadmap for the dissection process.
	<ol>
		<li>For optimal image quality of an uncoverslipped slide, utilize the diffuser below the condenser on the instrument, or, add a small amount (~30 &#956;l) of either ethanol or xylenes to improve the refractory index (pseudo-coverslip). When using xylenes, be aware they are toxic and proper safety measures must be used, including the use of a fume hood and protective lab coat, eye goggles, and gloves.</li>
		<li>Do NOT place the LCM cap on the slide until the ethanol or xylenes solution has completely cleared or the polymer on the cap will be distorted.</li>
	</ol>
	</li>
	<li>Navigate the slide and capture images of the areas to be dissected at 10X, 20X, or 40X magnification. If necessary, enhance the image with software such as AutoCorrect (in Microsoft Office Picture Manager) as previously described22.&#160;Images must be captured in jpeg format to allow them to be re-imported into the automated selection software.</li>
</ol>
3. Algorithm Analysis of the Image
<ol>
	<li>Transfer captured images from the microdissection instrument to the SIVQ folder.&#160;Install and open the ArcturusXT, AutoScan and SIVQ software packages on the computer attached to the dissection instrument. For access to the SIVQ software, please contact Dr. Ulysses Balis (ulysses@med.umich.edu).</li>
	<li>Open SIVQ and load the captured image (jpeg) of interest.</li>
	<li>Navigate to the area of interest and/or adjust the size of the display windows (Viewport 5 &#38; 6).&#160;In the SIVQ software, Viewport 5 shows the pre-processing image and Viewport 6 shows the post-processing image16.</li>
	<li>Choose the size of the ring vector and number of rings to be used.</li>
	<li>Select the predicate image feature to be captured by right clicking on it in Viewport 6.</li>
	<li>Click &#8220;scan&#8221; to analyze the image.</li>
	<li>Adjust the statistical probability of image matching using the two sliding bars.&#160;The upper bar adjusts the overall vector specificity, and is used to exclude area from the initial scan (with sensitivity as defined by the selected &#8220;Stat&#8221; variable) that may represent excessive included area.&#160;Conversely, the lower slider is utilized to increase sensitivity, after a scan is performed, with the intent of increasing area that is classified as being a match.&#160;Both of these slider controls utilize the &#8220;Stat&#8221; variable as the initial baseline sensitivity threshold.</li>
	<li>To save the image, click &#8220;save as jpeg&#8221; (image is now saved in c:/vq_test folder/pics).</li>
	<li>Analyze the image with the algorithm. The output of the algorithm analysis needs to result in an annotated image for it to be used in SIVQ-LCM. At present, the current version of the SIVQ core engine is in beta version testing with the expectation that the full production version (available Q1 2014) will incorporate a full software development kit (SDK) and application programming interface (API) for simplified integration of user-generated spatial filters and downstream workflow data processing steps with the core ring matching engine.&#160;This SDK will be distributed with a complete set of documentation.
	<ol>
		<li>Ensure that the SIVQ heatmap is changed to a uniform red color.</li>
	</ol>
	</li>
	<li>Export the image. It is essential to re-embed the positional coordinates in the post-analysis jpeg image by using a HEX editor to paste in the file header from the original dissection instrument image.&#160;The appropriate data may be found between &#8220;Start of Image&#8221; marker (0xFF, 0xD8) and the first&#160;&#8220;Define Quantization Table&#8221; marker (0xFF, 0xDB).</li>
</ol>
4. Microdissection
<ol>
	<li>Place the LCM cap at the center of the region of interest, where the images were captured for the SIVQ analysis.</li>
	<li>Calibrate and Quality Control (QC) the UV/IR lasers and optimize the parameters, including power, duration, laser locations, and UV cutting speed (as recommended by the manufacturer). Perform these calibrations before re-importing the analyzed image.&#160;</li>
	<li>Open AutoScanXT (automated selection software) and import the analyzed image from c:/vq_test folder/pics.</li>
	<li>Train the automated selection software to recognize the SIVQ annotation and create the dissection map.
	<ol>
		<li>To create a training file, select four regions of interest (marked by &#8220;blue circles&#8221;) on the &#8220;red paint&#8221; of the SIVQ analyzed image.</li>
		<li>Select the background areas (marked by &#8220;red squares&#8221;) that are not to be dissected.</li>
		<li>Click on the &#8220;Analyze&#8221; button to generate the training file, which can be saved for subsequent uses.&#160;</li>
	</ol>
	</li>
	<li>Perform microdissection using the appropriate infrared (IR) and/or ultraviolet (UV) lasers.
	<ol>
		<li>Copy the selected areas onto the &#8220;live&#8221; image.</li>
		<li>In the &#8220;microdissect&#8221; toolbox, select the appropriate IR capture or UV cutting buttons.</li>
	</ol>
	</li>
	<li>After the dissection is complete, move the LCM cap to the QC station and capture an image of the dissected tissue/cells. Another approach is to place the cap on a blank area of the slide prior to moving it to the QC station, this allows the user to take pictures at various magnifications.</li>
	<li>Capture an image of the tissue area of interest after microdissection to further assess lifting efficiency.</li>
	<li>If the desired cells have been dissected successfully, click on the &#34;present stage&#34; button in the ArcturusXT software and remove the LCM cap to initiate the molecular extraction procedure for downstream analysis.</li>
</ol>

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Michael R. Emmert-Buck is an inventor on NIH-held patents covering laser capture microdissection and receives royalty-based payments through the NIH Technology Transfer Program.

We present a protocol for the application of SIVQ-LCM to microdissect immunostained epithelial cells from FFPE human breast tissue. The use of an image analysis algorithm, such as SIVQ, reduces the amount of hands-on time required for the microdissection process. This is a potentially important advance for the field since operator time and effort is typically the rate-limiting step for the precise dissection of cells of interest. In the present protocol, we specifically adapted our procedure to the ArcturusXT instrument, although it likely will be possible to adapt SIVQ and other algorithms to other commercially available microdissection instruments as well. In addition to improving efficiency, this new approach may allow users who are non-histopathology experts to perform microdissection. Finally, the use of an algorithm to drive the microdissection process may enable greater reproducibility from site-to-site by removing user subjectivity in identifying cells of interest.
While SIVQ exhibits broad adaptability to multiple classes of image subject matter, including histology, it is important to recognize that it is not intended to serve as a universal image processing/segmentation tool, but rather, as a high-efficiency first-pass foreground selection tool. Used in this capacity, it has high utility for predicting whether or not a particular class of imagery subject matter is suitable for numerical segmentation approaches. When SIVQ is successful, there is high predictive power that either: a) a more refined and targeted image analysis/segmentation approach will be highly successful and/or b) an optimized, machine-selected SIVQ vector will be effective in rendering a clinical-workflow-ready solution. In either circumstance, the use of SIVQ serves as an effective triaging tool to identify imagery subject matter that poses computationally tractable solutions in terms of foreground segmentability.
While we previously described the use of the SIVQ-LCM protocol only for mRNA expression microarray experiments15, we believe the protocol is applicable to most downstream molecular assays, and may be particularly useful for molecular assays that require large numbers of cells, such as proteomics. For these studies, large amounts of cells need to be procured due to the inability to amplify proteins. In addition, the advent of newer technologies, such as Next-Gen Sequencing (NGS), emphasizes the need to begin with as pure of a sample as possible. The ability for SIVQ-LCM to isolate cells via both morphological features and/or staining qualities could enable the ability to more easily isolate pure cell populations.
It is critical to have properly prepared tissue for reproducible results for both the SIVQ analysis and microdissection. For optimal conditions for LCM it is best to perform dissects in a low humidity room and maintain properly dehydrated tissue. In addition, ensure that the staining of the tissue is reproducible. Finally, familiarity with the dissection instrument is essential to successful SIVQ-LCM.
The SIVQ-LCM protocol presented here is the first steps towards semi-automated microdissection, which may have applications in future clinical testing since current dissection methods are not easily capable of handling large workloads. In summary, we believe that SIVQ-LCM is a new foray into the field of automated microdissection and provides a starting point from which investigators and algorithm developers can further improve the technology.

Originally developed in the mid-1990s, laser capture microdissection (LCM) enables the user to precisely capture specific cells or cellular regions from a histological tissue section via microscopic visualization1,2. Many studies comparing molecular analysis of LCM versus tissue scrapes illustrate the value of the method3-12. In addition, there are three video protocol publications on the technology that are available for viewing13,14. However, despite its proven value, LCM can be tedious and laborious when the target of interest is a dispersed cell population in a heterogeneous tissue section, or when large numbers of cells are required for specific downstream applications such as proteomics. The burden placed on the human operator led us to develop a semi-automated dissection approach for LCM by combining a powerful image analysis algorithm to guide the LCM process15.
In collaboration with the University of Michigan, our laboratory at the NIH extended the previously developed and reported Spatially invariant vector quantization (SIVQ) algorithm in a manner to allow it to semi-automate the tissue selection process intrinsic to guided microdissection, thus making available a tool with the pathologist or life scientist in mind. Spatially invariant vector quantization (SIVQ) is an algorithm that allows the user to simply &#8220;click&#8221; on a histological feature of interest to create a ring vector (predicate image feature) that can be used to search the entire histological image, adjusting the statistical threshold as needed16-21. The resultant heat map displays the quality of matches to the initial predicate image feature and is subsequently converted into a single color (red) annotation map that can be imported into the LCM instrument. The automated selection software, AutoScanXT, is then used to draw a map based on SIVQ&#39;s annotation guiding the capture of the target cells from the tissue sample. The detailed protocol below describes the implementation of SIVQ into the microdissection workflow.

<table><tbody><tr><td>Positive Charged Glass Slides</td><td>Thermo Scientific</td><td>4951Plus-001</td><td></td></tr><tr><td>Xylenes, ACS reagent, &amp;ge;98.5% xylenes + ethylbenzene basis&amp;nbsp;</td><td>Sigma Aldrich</td><td>247642</td><td>CAUTION: PLEASE USE PROPER SAFETY PROCEDURES.</td></tr><tr><td>Ethyl Alcohol, U.S.P. 200 Proof, Anhydrous</td><td>The Warner-Graham Company</td><td>6.505E+12</td><td>CAUTION: PLEASE USE PROPER SAFETY PROCEDURES.</td></tr><tr><td>Arcturus CapSure Macro LCM Caps</td><td>Life Technologies</td><td>LCM0211</td><td></td></tr><tr><td>ArcturusXT Laser Microdissection Instrument</td><td>Life Technologies</td><td>ARCTURUSXT</td><td></td></tr><tr><td>AutoScanXT Software</td><td>Life Technologies</td><td></td><td>An optional image analysis program for the ArcturusXT Laser Microdissection Device. This is software is required for SIVQ-LCM.</td></tr><tr><td>Spatially Invariant Vector Quantization (SIVQ)</td><td>University of Michigan</td><td></td><td>This tool suite is publicly available for academic collaborations. For access to the SIVQ algorithm, please contact Dr. Ulysses Balis [Ulysses@med.umich.edu]</td></tr></tbody></table>

sivq-lcm protocol for the arcturusxt instrument

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process.&#160;It aims to create an advanced, rapidly customizable laser dissection platform technology. In this report, we describe the integration of the image analysis software Spatially Invariant Vector Quantization (SIVQ) onto the ArcturusXT instrument. The ArcturusXT system contains both an infrared (IR) and ultraviolet (UV) laser, allowing for specific cell or large area dissections. The principal goal is to improve the speed, accuracy, and reproducibility of the laser dissection to increase sample throughput. This novel approach facilitates microdissection of both animal and human tissues in research and clinical workflows.

A FFPE human breast tissue section was immunostained for cytokeratin AE1/AE3 using a standard IHC protocol23. After staining, the tissue slide was placed on the ArcturusXT stage and the SIVQ-LCM protocol was initiated as described above. Since the tissue cannot be coverslipped for microdissection, the IHC+ stained cells can be difficult to discern visually (Figure 1A). Thus, to provide better index matching and an improved image, xylenes were added to the tissue section to create a pseudo-coverslip15 (Figure 1B). A jpeg image was then captured of the pseudo-coverslipped area and imported into SIVQ for the algorithm analysis. A predicate image feature (dark brown DAB stain) selected by the user initiated the SIVQ algorithm to analyze the image (Figure 1C). The SIVQ heatmap was then converted to a &#8220;red paint&#8221; that is recognized by the automated selection software (Figure 1D). The xylenes were allowed to evaporate and the SIVQ heatmap was imported into the automated selection software (Figure 1E) and the highlighted cells were dissected with the IR laser. The LCM cap was then moved to the QC station of the ArcturusXT instrument and visually inspected to assess dissection efficiency (Figure 1F). The remaining tissue was also inspected (Figure 1G) and the SIVQ heatmap was re-imported to further assess the microdissection efficiency (Figure 1H).
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51662/51662fig1highres.jpg" src="/files/ftp_upload/51662/51662fig1.jpg" /> 
Figure 1. SIVQ-LCM of IHC stained FFPE breast tissue. A) Uncoverslipped image of cytokeratin AE1/AE3 stained FFPE breast tissue. B) Xylenes coated (pseudo-coverslipped) image of panel A. C) SIVQ generated heatmap using a ring vector (predicate image) captured from the brown chromagen. D) The heatmap was converted to a single color (red). In the ArcturusXT, the AutoScanXT software was trained to recognize the red annotation. E) The microdissection map generated from the AutoScanXT algorithm. F) Image of the microdissected breast epithelial cells on the LCM cap. G) Image of the tissue on the slide after microdissection. H) Overlap of the microdissection map (panel E) on the tissue area that was dissected. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51662/51662fig1highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about SIVQ-LCM Protocol for the ArcturusXT Instrument at JoVE.com

SIVQ-LCM Protocol for the ArcturusXT Instrument

SIVQ-LCM is an innovative approach that harnesses a computer algorithm, Spatially Invariant Vector Quantization (SIVQ), to drive the laser capture microdissection (LCM) process. The SIVQ-LCM workflow greatly improves the speed and accuracy of microdissection, with applications in both the research and clinical settings.

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process.&#160;It aims to create an ...

sivq-lcm-protocol-for-the-arcturusxt-instrument

Universidad San Sebastian

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JoVE Journal

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8.6K Views.  National Institutes of Health. SIVQ-LCM is an innovative approach that harnesses a computer algorithm, Spatially Invariant Vector Quantization (SIVQ), to drive the laser capture microdissection (LCM) process. The SIVQ-LCM workflow greatly improves the speed and accuracy of microdissection, with applications in both the research and clinical settings.

Video: SIVQ-LCM Protocol for the ArcturusXT Instrument

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline

Biological small angle X-ray scattering (BioSAXS) is a powerful technique in molecular and structural biology used to determine solution structure, particle size and shape, and surface-to-volume ratio of macromolecules. The technique is applicable to a very wide variety of solution conditions spanning a broad range of concentrations, pH values, ionic strengths, temperatures, additives, etc., but the sample is required to be monodisperse. This caveat led to the implementation of liquid chromatography systems on SAXS beamlines. Here, we describe the upstream integration of size-exclusion (SEC) and ion-exchange chromatography (IEC) on a beamline, different methods for optimal background subtraction, and data reduction. As an example, we describe how we use SEC- and IEC-SAXS on a fragment of the essential vaccinia virus protein D5, consisting of a D5N helicase domain. We determine its overall shape and molecular weight, showing the hexameric structure of the protein.

The determination of the solution structure of a protein by small angle X-ray scattering (SAXS) requires monodisperse samples. Here, we present two possibilities to ensure minimal delays between sample preparation and data acquisition: online size-exclusion chromatography (SEC) and online ion-exchange chromatography (IEC).

Biological small angle X-ray scattering (BioSAXS) is a powerful technique in molecular and structural biology used to determine solution structure, ...

Biochemistry

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species

We present a method of analyzing sphingomyelin (SM) qualitatively and quantitatively by liquid chromatography-electrospray Ionization-tandem mass spectrometry (LC-ESI-MS/MS). SM is a common sphingolipid composed of a phosphorylcholine and a ceramide as the hydrophilic and hydrophobic component, respectively. A number of SM species are present in mammalian cells due to a variety in the sphingoid long chain base (LCB) and an N-acyl moiety in the ceramide. In this report, we show a method of estimating the number of carbon and double bonds in a LCB and an N-acyl moiety based on their corresponding product ions in MS/MS/MS (MS3) experiments. In addition, we present a quantitative analysis method for SM using two stable isotopically labeled SM species, which facilitates determining the range used in SM quantitation. The present method will be useful in characterizing a variety of SM species in biological samples and industrial products such as cosmetics.

Here, we present a protocol to quantify and qualify each sphingomyelin species using multiple reaction monitoring and MS/MS/MS mode, respectively.

We present a method of analyzing sphingomyelin (SM) qualitatively and quantitatively by liquid chromatography-electrospray Ionization-tandem mass ...

Applying X-ray Imaging Crystal Spectroscopy for Use as a High Temperature Plasma Diagnostic

X-ray spectra provide a wealth of information on high temperature plasmas; for example electron temperature and density can be inferred from line intensity ratios. By using a Johann spectrometer viewing the plasma, it is possible to construct profiles of plasma parameters such as density, temperature, and velocity with good spatial and time resolution. However, benchmarking atomic code modeling of X-ray spectra obtained from well-diagnosed laboratory plasmas is important to justify use of such spectra to determine plasma parameters when other independent diagnostics are not available. This manuscript presents the operation of the High Resolution X-ray Crystal Imaging Spectrometer with Spatial Resolution (HIREXSR), a high wavelength resolution spatially imaging X-ray spectrometer used to view hydrogen- and helium-like ions of medium atomic number elements in a tokamak plasma. In addition, this manuscript covers a laser blow-off system that can introduce such ions to the plasma with precise timing to allow for perturbative studies of transport in the plasma.

X-ray spectra provide a wealth of information on high temperature plasmas. This manuscript presents the operation of a high wavelength resolution spatially imaging X-ray spectrometer used to view hydrogen- and helium-like ions of medium atomic number elements in a tokamak plasma.

X-ray spectra provide a wealth of information on high temperature plasmas; for example electron temperature and density can be inferred from line ...

Engineering

Measurements of Long-range Electronic Correlations During Femtosecond Diffraction Experiments Performed on Nanocrystals of Buckminsterfullerene

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the results of femtosecond X-ray free electron laser (XFEL) experiments. An increasing number of experimental observations have shown that although nuclear motion can be negligible, given a short enough incident pulse duration, electronic motion cannot be ignored. The current and widely accepted models assume that although electrons undergo dynamics driven by interaction with the pulse, their motion could largely be considered &#39;random&#39;. This would then allow the supposedly incoherent contribution from the electronic motion to be treated as a continuous background signal and thus ignored. The original aim of our experiment was to precisely measure the change in intensity of individual Bragg peaks, due to X-ray induced electronic damage in a model system, crystalline C60. Contrary to this expectation, we observed that at the highest X-ray intensities, the electron dynamics in C60 were in fact highly correlated, and over sufficiently long distances that the positions of the Bragg reflections are significantly altered. This paper describes in detail the methods and protocols used for these experiments, which were conducted both at the Linac Coherent Light Source (LCLS) and the Australian Synchrotron (AS) as well as the crystallographic approaches used to analyse the data.

We describe an experiment designed to probe the electronic damage induced in nanocrystals of Buckminsterfullerene (C60) by intense, femtosecond pulses of X-rays. The experiment found that, surprisingly, rather than being stochastic, the X-ray induced electron dynamics in C60 are highly correlated, extending over hundreds of unit cells within the crystals1.

The precise details of the interaction of intense X-ray pulses with matter are a topic of intense interest to researchers attempting to interpret the ...

Chemistry

High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis

The goal of this protocol is to build a parallel high-extinction and high-resolution optical Brillouin spectrometer. Brillouin spectroscopy is a non-contact measurement method that can be used to obtain direct readouts of viscoelastic material properties. It has been a useful tool in material characterization, structural monitoring and environmental sensing. In the past, Brillouin spectroscopy has usually employed scanning Fabry-Perot etalons to perform spectral analysis. This process requires high illumination power and long acquisition times, making the technique unsuitable for biomedical applications. A recently introduced novel spectrometer overcomes this challenge by employing two VIPAs in a cross-axis configuration. This innovation enables sub-Gigahertz (GHz) resolution spectral analysis with sub-second acquisition time and illumination power within the safety limits of biological tissue. The multiple new applications facilitated by this improvement are currently being explored in biological research and clinical application.

Here we present a protocol to build a rapid Brillouin spectrometer. Cascading virtually imaged phase array (VIPA) etalons achieve a measurement speed more than 1,000 times faster than traditional scanning Fabry-Perot spectrometers. This improvement provides the means for Brillouin analysis of tissue and biomaterials at low power levels in vivo.

The goal of this protocol is to build a parallel high-extinction and high-resolution optical Brillouin spectrometer. Brillouin spectroscopy is a ...

Bioengineering

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray beam induced current (XBIC) measurements allow mapping of&#160;the nanoscale performance of electronic devices such as solar cells. Ideally, XBIC is employed simultaneously with other techniques within a multi-modal X-ray microscopy approach. An example is given herein combining XBIC with X-ray fluorescence to enable point-by-point correlations of the electrical performance with chemical composition. For the highest signal-to-noise ratio in XBIC measurements, lock-in amplification plays a crucial role. By this approach, the X-ray beam is modulated by an optical chopper upstream of the sample. The modulated X-ray beam induced electrical signal is amplified and demodulated to the chopper frequency using a lock-in amplifier. By optimizing low-pass filter settings, modulation frequency, and amplification amplitudes, noise can efficiently be suppressed for the extraction of a clear XBIC signal. A similar setup can be used to measure the X-ray beam induced voltage (XBIV). Beyond standard XBIC/XBIV measurements, XBIC can be measured with bias light or bias voltage applied such that outdoor working conditions of solar cells can be reproduced during in-situ and operando measurements. Ultimately, the multi-modal and multi-dimensional evaluation of electronic devices at the nanoscale enables new insights into the complex dependencies between composition, structure, and performance, which is an important step towards solving the materials&#39; paradigm.

A setup for X-ray beam induced current measurements at synchrotron beamlines is described. It unveils the nanoscale performance of solar cells and extends the suite of techniques for multi-modal X-ray microscopy. From wiring to signal-to-noise optimization, it is shown how to perform state-of-the-art XBIC measurements at a hard X-ray microprobe.

X-ray beam induced current (XBIC) measurements allow mapping of&#160;the nanoscale performance of electronic devices such as solar cells. Ideally, XBIC is ...

Sample Preparation and Transfer Protocol for In-Vacuum Long-Wavelength Crystallography on Beamline I23 at Diamond Light Source

Long-wavelength macromolecular crystallography (MX) exploits the anomalous scattering properties of elements, such as sulfur, phosphorus, potassium, chlorine, or calcium, that are often natively present in macromolecules. This enables the direct structure solution of proteins and nucleic acids via experimental phasing without the need of additional labelling. To eliminate the significant air absorption of X-rays in this wavelength regime, these experiments are performed in a vacuum environment. Beamline I23 at Diamond Light Source, UK, is the first synchrotron instrument of its kind, designed and optimized for MX experiments in the long wavelength range towards 5 &#197;. 
To make this possible, a large vacuum vessel encloses all endstation components of the sample environment. The necessity to maintain samples at cryogenic temperatures during storage and data collection in vacuum requires the use of thermally conductive sample holders. This facilitates efficient heat removal to ensure sample cooling to approximately 50 K. The current protocol describes the procedures used for sample preparation and transfer of samples into vacuum on beamline I23. Ensuring uniformity in practices and methods already established within the macromolecular crystallography community, sample cooling to liquid nitrogen temperature can be performed in any laboratory setting equipped with standard MX tools. 
Cryogenic storage and transport of samples only require standard commercially available equipment. Specialized equipment is required for the transfer of cryogenically cooled crystals from liquid nitrogen into the vacuum endstation. Bespoke sample handling tools and a dedicated Cryogenic Transfer System (CTS) have been developed in house. Diffraction data collected on samples prepared using this protocol show excellent merging statistics, indicating that the quality of samples is unaltered during the procedure. This opens unique opportunities for in-vacuum MX in a wavelength range beyond standard synchrotron beamlines.

Here, we present a protocol for cryogenic sample preparation and transfer of crystals into the vacuum endstation on beamline I23 at Diamond Light Source, for long-wavelength macromolecular X-ray crystallography experiments.

Long-wavelength macromolecular crystallography (MX) exploits the anomalous scattering properties of elements, such as sulfur, phosphorus, potassium, ...

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular level in the chemical and biomedical sciences. Although commercial SIM systems are available, systems that are custom designed in the laboratory can outperform commercial systems, the latter typically designed for ease of use and general purpose applications, both in terms of imaging fidelity and speed. This article presents an in-depth guide to building a SIM system that uses total internal reflection (TIR) illumination and is capable of imaging at up to 10 Hz in three colors at a resolution reaching 100 nm. Due to the combination of SIM and TIRF, the system provides better image contrast than rival technologies. To achieve these specifications, several optical elements are used to enable automated control over the polarization state and spatial structure of the illumination light for all available excitation wavelengths. Full details on hardware implementation and control are given to achieve synchronization between excitation light pattern generation, wavelength, polarization state, and camera control with an emphasis on achieving maximum acquisition frame rate. A step-by-step protocol for system alignment and calibration is presented and the achievable resolution improvement is validated on ideal test samples. The capability for video-rate super-resolution imaging is demonstrated with living cells.

This article provides an in depth guide for the assembly and operation of a structured illumination microscope operating with total internal reflection fluorescence illumination (TIRF-SIM) to image dynamic biological processes with optical super-resolution in multiple colors.

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular ...

Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

A novel elemental and chemical analysis scheme based on electron-channeling phenomena in crystalline materials is introduced, where the incident high-energy electron beam is rocked with the submicrometric pivot point fixed on a specimen. This method enables us to quantitatively derive the site occupancies and site-dependent chemical information of impurities or intentionally doped functional elements in a specimen, using energy-dispersive X-ray spectroscopy and electron energy-loss spectroscopy attached to a scanning transmission electron microscope, which is of significant interest to current materials science, particularly related to nanotechnologies. This scheme is applicable to any combination of elements even when the conventional Rietveld analysis by X-ray or neutron diffraction occasionally fails to provide the desired results because of limited sample sizes and close scattering factors of neighboring elements in the periodic table. In this methodological article, we demonstrate the basic experimental procedure and analysis method of the present beam-rocking microanalysis.

We provide a general outline of quantitative microanalysis methods for estimating the site occupancies of impurities and their chemical states by taking advantage of electron-channeling phenomena under incident electron beam-rocking conditions, which reliably extract information from minority species, light elements, oxygen vacancies, and other point/line/planar defects.

A novel elemental and chemical analysis scheme based on electron-channeling phenomena in crystalline materials is introduced, where the incident ...

Using a Cyclic Ion Mobility Spectrometer for Tandem Ion Mobility Experiments

Accurate characterization of chemical structures is important to understand their underlying biological mechanisms and functional properties. Mass spectrometry (MS) is a popular tool but is not always sufficient to completely unveil all structural features. For example, although carbohydrates are biologically relevant, their characterization is complicated by numerous levels of isomerism. Ion mobility spectrometry (IMS) is an interesting complement because it is sensitive to ion conformations and, thus, to isomerism. 
Furthermore, recent advances have significantly improved the technique: the last generation of Cyclic IMS instruments offers additional capabilities compared to linear IMS instruments, such as an increased resolving power or the possibility to perform tandem ion mobility (IMS/IMS) experiments. During IMS/IMS, an ion is selected based on its ion mobility, fragmented, and reanalyzed to obtain ion mobility information about its fragments. Recent work showed that the mobility profiles of the fragments contained in such IMS/IMS data can act as a fingerprint of a particular glycan and can be used in a molecular networking strategy to organize glycomics datasets in a structurally relevant way. 
The goal of this protocol is thus to describe how to generate IMS/IMS data, from sample preparation to the final Collision Cross Section (CCS) calibration of the ion mobility dimension that yields reproducible spectra. Taking the example of one representative glycan, this protocol will show how to build an IMS/IMS control sequence on a Cyclic IMS instrument, how to account for this control sequence to translate IMS arrival time into drift time (i.e., the effective separation time applied to the ions), and how to extract the relevant mobility information from the raw data. This protocol is designed to clearly explain the critical points of an IMS/IMS experiment and thus help new Cyclic IMS users perform straightforward and reproducible acquisitions.

Ion mobility spectrometry (IMS) is an interesting complement to mass spectrometry for the characterization of biomolecules, notably because it is sensitive to isomerism. This protocol describes a tandem IMS (IMS/IMS) experiment, which allows the isolation of a molecule and the generation of the mobility profiles of its fragments.